Turkiye Greenhouse Gas Inventory (1990 - 2021)
MBA, M.Sc Nurcan TALAYvisibility
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ES.1 Background Information on Greenhouse Gas Inventories The United Nations Framework Convention on Climate Change (UNFCCC) is an international treaty established in 1992 to cooperatively address climate change issues. The ultimate objective of the UNFCCC is to stabilize atmospheric greenhouse gas (GHG) concentrations at a level that would prevent dangerous interference with the climate system. Türkiye ratified the UNFCCC in May 2004. To achieve its objective and implement its provisions, the UNFCCC lays out several guiding principles and commitments. Specifically, Articles 4 and 12 commit all Parties to develop, periodically update, publish and make available to the COP their national inventories of anthropogenic emissions by sources and removals by sinks of all GHGs not controlled by the Montreal Protocol. National inventory of Türkiye is prepared and submitted annually to the UNFCCC by April 15 of each year, in accordance with revised Guidelines for the preparation of national communications by Parties included in Annex I to the Convention, Part I: UNFCCC reporting guidelines on annual inventories (UNFCCC Reporting Guidelines). The annual inventory submission consists of the National Inventory Report (NIR) and the Common Reporting Format (CRF) tables. Türkiye, as an Annex I party to the United Nations Framework Convention on Climate Change (UNFCCC), reports annually on greenhouse gas (GHG) inventories. This National Inventory Report (NIR) contains national GHG emission/removal estimates for the period of 1990-2021. Pursuant to Decision 24/CP.5, all Parties listed in Annex I of the UNFCCC are required to prepare and submit annual NIR containing detail and complete information on the entire process of preparation of such GHG inventories. The purpose of such reports is to ensure the transparency, accuracy, consistency, comparability and completeness of inventories and support the independent review process. This inventory submission follows the revised UNFCCC Reporting Guidelines, adopted through Decision 24/CP.19 at COP 19. Together with the common reporting format (CRF) tables, Türkiye submits a National Inventory Report (NIR), which refers to the period covered by the inventory tables and describes the methods and data sources on which the pertinent calculations are based. The report, and the CRF tables, have been prepared pursuant to the UNFCCC guidelines on annual inventories (24/CP.19
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TURKISH
GREENHOUSE GAS
INVENTORY
1990 - 2021
National Inventory Report for submission under
the United Nations Framework Convention on Climate Change
April 2023
TURKISH
GREENHOUSE GAS
NATIONAL
INVENTORY
1990 - 2021
GREENHOUSE GAS
INVENTORY
National InventoryREPORT
Report for submission under
the United Nations Framework Convention on Climate Change
1990-2021
Annual Report for submission under
the "United Nations Framework
Convention on Climate Change"
TURKISH STATISTICAL INSTITUTE
April 2023
CONTACT INFORMATION
Turkish Statistical Institute
Fatma Betül DEMİROK (National Inventory Focal Point)
Turkish Statistical Institute
Tel: +90-312-4547791
e-mail: [email protected]
Erhan ÜNAL
Turkish Statistical Institute
Tel: +90-312-4547803
e-mail: [email protected]
Kadir AKSAKAL
Turkish Statistical Institute
Tel: +90-312-4547802
e-mail: [email protected]
Elif YILMAZ
Turkish Statistical Institute
Tel: +90-312-4547817
e-mail: [email protected]
İlhan TARLACI
Turkish Statistical Institute
Tel: +90-312-4547209
e-mail: [email protected]
Turkish Statistical Institute is responsible for all cross-cutting issues, energy (except for 1.A.1.a Public
Electricity and Heat Production and 1.A.3 Transport), industrial processes and product use, agriculture and
waste sectors.
Turkish GHG Inventory Report 1990-2021
III
Ministry of Energy and Natural Resources
Ümit ÇALIKOĞLU
Ministry of Energy and Natural Resources
Tel: +90-312-5465624
e-mail: [email protected]
Büşra Sıla AKSAKAL
Ministry of Energy and Natural Resources
Tel: +90-312-5465625
e-mail: [email protected]
Nesibe Feyza TAMER
Ministry of Energy and Natural Resources
Tel: +90-312-5465626
e-mail: [email protected]
Ministry of Energy and Natural Resources is responsible for energy balance tables and for the section 1.A.1.a
Public Electricity and Heat Production.
Ministry of Transport and Infrastructure
Burak ÇİFTÇİ
Ministry of Transport and Infrastructure
Tel: +90-312-2031903
e-mail: [email protected]
Hasan Umur ALSANCAK
Ministry of Transport and Infrastructure
Tel: +90-312-2031000/3072
e-mail:[email protected]
Ministry of Transport and Infrastructure is responsible for transport sector.
Ministry of Environment, Urbanization and Climate Change
Veysel SELİMOĞLU
Ministry of Environment, Urbanization and Climate Change
Tel: +90-312-4242323/7070
e-mail: [email protected]
Ministry of Environment, Urbanization and Climate Change is responsible for F-gases.
IV
Turkish GHG Inventory Report 1990-2021
Ministry of Agriculture and Forestry
Prof. Yusuf SERENGİL
İstanbul University-Cerrahpaşa, Faculty of Forestry
Tel: +90-212-3382400
e-mail: [email protected]
Ümit TURHAN
Ministry of Agriculture and Forestry - General Directorate of Forestry
Tel:+90-312-2481713
e-mail: [email protected]
Eray ÖZDEMİR
Ministry of Agriculture and Forestry - General Directorate of Forestry
Tel:+90-312-2481720
e-mail: [email protected]
Uğur KARAKOÇ
Ministry of Agriculture and Forestry - General Directorate of Forestry
Tel:+90-312-2481726
e-mail: [email protected]
General Directorate of Forestry is responsible for LULUCF - forestry sector.
Abdüssamet AYDIN
Ministry of Agriculture and Forestry - General Directorate of Agricultural Reform
Tel: +90-312-2588123
e-mail: [email protected]
Nurdan BUĞDAY
Ministry of Agriculture and Forestry - General Directorate of Agricultural Reform
Tel: +90-312-2588132
e-mail: [email protected]
General Directorate of Agricultural Reform is responsible for LULUCF - other land use sector.
Turkish GHG Inventory Report 1990-2021
V
Executive Summary
EXECUTIVE SUMMARY
ES.1 Background Information on Greenhouse Gas Inventories
The United Nations Framework Convention on Climate Change (UNFCCC) is an international treaty
established in 1992 to cooperatively address climate change issues. The ultimate objective of the
UNFCCC is to stabilize atmospheric greenhouse gas (GHG) concentrations at a level that would prevent
dangerous interference with the climate system. Türkiye ratified the UNFCCC in May 2004.
To achieve its objective and implement its provisions, the UNFCCC lays out several guiding principles
and commitments. Specifically, Articles 4 and 12 commit all Parties to develop, periodically update,
publish and make available to the COP their national inventories of anthropogenic emissions by sources
and removals by sinks of all GHGs not controlled by the Montreal Protocol.
National inventory of Türkiye is prepared and submitted annually to the UNFCCC by April 15 of each
year, in accordance with revised Guidelines for the preparation of national communications by Parties
included in Annex I to the Convention, Part I: UNFCCC reporting guidelines on annual inventories
(UNFCCC Reporting Guidelines). The annual inventory submission consists of the National Inventory
Report (NIR) and the Common Reporting Format (CRF) tables.
Türkiye, as an Annex I party to the United Nations Framework Convention on Climate Change (UNFCCC),
reports annually on greenhouse gas (GHG) inventories. This National Inventory Report (NIR) contains
national GHG emission/removal estimates for the period of 1990-2021.
Pursuant to Decision 24/CP.5, all Parties listed in Annex I of the UNFCCC are required to prepare and
submit annual NIR containing detail and complete information on the entire process of preparation of
such GHG inventories. The purpose of such reports is to ensure the transparency, accuracy, consistency,
comparability and completeness of inventories and support the independent review process.
This inventory submission follows the revised UNFCCC Reporting Guidelines, adopted through Decision
24/CP.19 at COP 19.
Together with the common reporting format (CRF) tables, Türkiye submits a National Inventory Report
(NIR), which refers to the period covered by the inventory tables and describes the methods and data
sources on which the pertinent calculations are based. The report, and the CRF tables, have been
prepared pursuant to the UNFCCC guidelines on annual inventories (24/CP.19) and in conformance with
Turkish GHG Inventory Report 1990-2021
i i
Executive Summary
the 2006 Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas
(GHG) Inventories (2006 IPCC Guidelines).
The annual GHG inventory provides information on the trends in national GHG emissions and removals
since 1990. This information is essential for the planning and monitoring of climate policies.
Turkish Statistical Institute (TurkStat) is the responsible agency for compiling the National GHG
Inventory. GHG inventory of Türkiye is prepared by "GHG Emissions Inventory Working Group" which
is set up by the decision of the Coordination Board on Climate Change (CBCC). TurkStat is the
responsible organization for the coordination of working group (WG). Moreover, TurkStat has been
designated as the National inventory focal point of Türkiye by the decision taken by CBCC in 2009.
The Official Statistics Programme (OSP), based on the Statistics Law of Türkiye No. 5429 and
Presidential Order No. 4, has been prepared for a 5-year-period in order to determine the basic principles
and standards dealing with the production and dissemination of official statistics and to produce reliable,
timely, transparent and impartial data required at national and international level. The responsibility for
compiling the National GHG Inventory has also been given to TurkStat by the OSP. The inventory
preparation is a joint work of GHG emission inventory WG.
The main institutions involved in GHG inventory are;
Turkish Statistical Institute (TurkStat),
Ministry of Energy and Natural Resources (MENR),
Ministry of Transport and Infrastructure (MoTI),
Ministry of Environment, Urbanization and Climate Change (MoEUCC),
Ministry of Agriculture and Forestry (MoAF).
The National GHG emissions/removals are calculated by using 2006 IPCC Guidelines. The GHG Inventory
includes direct GHGs as carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), fluorinated gases
(F-gases); hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6), nitrogen
trifluoride (NF3) and indirect GHGs as nitrogen oxides (NOx), carbon monoxide (CO), non-methane
volatile organic compounds (NMVOC), sulphur dioxide (SO2) and ammonia (NH3) emissions originated
from energy, industrial processes and product use (IPPU), agriculture and waste. The emissions and
removals from land use, land use change and forestry (LULUCF) are also included in the inventory.
ii
Turkish GHG Inventory Report 1990-2021
ii
Executive Summary
ES.2 Summary of National Emission and Removal Related Trends
Total GHG emissions, excluding the LULUCF sector, were estimated to be 564.4 Mt of CO2 equivalent
(CO2 eq.) in 2021. This represents an increase of 40.4 Mt, or 7.7%, in emissions compared to 2020, and
a 157.1% increase compared to 1990 (Table ES 1).
Table ES 1 Greenhouse gas emissions, 1990-2021
Total emissions
(Mt CO2 eq.
excluding LULUCF)
Change compared to
1990 (%)
Net emissions
(Mt CO2 eq.
including LULUCF)
Change compared to
1990 (%)
1990
2000
2010
2015
2016
2017
2018
2019
2020
2021
219.5
298.9
398.8
475.0
501.1
528.6
523.1
508.7
524.0
564.4
-
36.2
81.7
116.4
128.3
140.8
138.3
131.7
138.7
157.1
153.0
230.9
326.9
402.2
428.0
453.6
453.4
446.0
467.0
517.2
-
50.9
113.6
162.8
179.7
196.4
196.3
191.5
205.2
238.0
Total GHG emissions, including the LULUCF sector, were 517.2 Mt CO2 eq. in 2021. Thus, LULUCF
included total emissions decreased by 10.7% compared to 2020 emissions. There is a 238% increase
from 1990 to 2021 (Table ES 1).
Table ES 2 Overview of GHG emissions and removals, 1990-2021
(Mt CO2 eq.)
GHG emissions
1990
2000
2010
2015
2016
2017
2018
2019
2020
2021
CO2 (excluding LULUCF)
151.6
229.9
316.2
384.9
406.0
430.9
422.1
402.7
412.9
452.7
CO2 (including LULUCF)
85.0
161.6
244.2
312.0
332.6
355.7
352.2
339.8
355.7
404.3
CH4 (excluding LULUCF)
42.5
43.7
51.6
52.8
55.6
56.8
60.4
63.2
63.9
64.0
CH4 (including LULUCF)
42.6
43.8
51.7
52.8
55.6
56.9
60.4
63.3
64.0
64.7
N2O (excluding LULUCF)
25.0
24.8
27.4
32.3
34.3
35.4
35.5
37.0
40.5
40.3
N2O (including LULUCF)
25.0
24.9
27.5
32.4
34.5
35.6
35.6
37.1
40.7
40.9
HFCs
NO
0.1
3.1
4.8
5.1
5.3
5.0
5.7
6.5
7.2
PFCs
0.5
0.4
0.4
0.1
0.0
0.0
0.0
0.0
0.0
0.0
SF6
NO
0.0
0.1
0.1
0.1
0.1
0.1
0.2
0.2
0.1
Total (excluding LULUCF)
219.5
298.9
398.8
475.0
501.1
528.6
523.1
508.7
524.0
564.4
Total (including LULUCF)
153.0
230.9
326.9
402.2
428.0
453.6
453.4
446.0
467.0
517.2
Note that 0.0 kt figures refer to values smaller than 0.05 but greater than zero.
Total GHG emissions as CO2 eq. for the year 2021 were 564.4 Mt (excluding LULUCF). Overall in 2021,
the energy sector had the largest portion with a 71.3% share of total emissions. The energy sector was
followed by the sectors of IPPU with 13.3%, agriculture with 12.8% and waste with 2.6%. GHG
emissions by sectors are presented in Table ES 3 for 1990-2021.
Turkish GHG Inventory Report 1990-2021
iii iii
Executive Summary
Table ES 3 Greenhouse gas emissions by sectors, 1990-2021
(Mt CO2 eq.)
Year
Energy
IPPU
Agriculture
LULUCF
Waste
Total
(Excluding
LULUCF)
Total
(Including
LULUCF)
1990
139.5
22.9
46.1
-66.5
11.1
219.5
153.0
144.0
24.6
46.9
-67.4
11.3
226.8
159.4
150.3
24.3
47.0
-67.5
11.5
233.1
165.7
156.8
24.8
47.4
-66.6
11.8
240.8
174.2
153.3
24.1
44.9
-68.0
12.0
234.4
166.4
166.3
25.5
44.1
-67.8
12.3
248.2
180.5
184.0
26.2
44.8
-67.1
12.7
267.6
200.5
196.1
27.0
42.5
-70.4
13.2
278.8
208.4
195.8
27.3
43.7
-70.6
13.5
280.3
209.7
193.8
25.8
44.3
-71.2
13.9
277.8
206.6
216.0
26.2
42.3
-68.1
14.3
298.9
230.9
199.2
25.8
39.9
-70.8
14.8
279.7
209.0
206.0
26.8
37.6
-69.3
15.2
285.6
216.3
220.5
28.2
40.6
-71.2
15.6
304.8
233.6
226.3
30.8
41.3
-69.7
16.1
314.4
244.7
244.5
34.3
42.4
-71.8
16.4
337.6
265.8
260.5
36.8
43.9
-71.5
16.8
358.0
286.5
291.5
39.7
43.4
-71.8
17.1
391.7
319.9
288.3
41.7
41.3
-67.9
17.2
388.5
320.6
292.9
43.1
42.0
-70.8
17.2
395.2
324.3
287.9
49.1
44.4
-71.9
17.4
398.8
326.9
310.0
54.0
46.9
-75.6
17.8
428.6
353.0
321.6
56.3
52.7
-73.4
17.6
448.2
374.8
308.3
59.3
55.9
-76.5
16.7
440.2
363.7
326.7
60.1
56.2
-76.9
16.5
459.5
382.6
342.0
59.7
56.1
-72.8
17.1
475.0
402.2
361.7
63.8
58.9
-73.1
16.7
501.1
428.0
382.4
66.6
63.3
-75.0
16.3
528.6
453.6
373.4
67.7
65.3
-69.8
16.6
523.1
453.4
365.6
59.0
68.0
-62.7
16.1
508.7
446.0
366.6
68.0
73.2
-56.9
16.3
524.0
467.0
402.5
75.1
72.1
-47.1
14.7
564.4
517.2
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
IPPU: Industrial Processes and Product Use
LULUCF: Land Use, Land Use Change and Forestry
As shown in Table ES 3, emissions from energy increased by 9.8% to 402.5 Mt CO2 eq. in 2021 compared
to 2020. However, there is a 188.4% increase compared to 1990. Emissions in the IPPU sector increased
to 75.1 Mt CO2 eq. in 2021 which is 10.6% higher than the emissions in 2020. Emissions in the
agriculture and waste sectors were 72.1 Mt CO2 eq. and 14.7 Mt CO2 eq. respectively in 2021.
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Turkish GHG Inventory Report 1990-2021
iv
Executive Summary
ES.3 Overview of Emission Estimates and Trends
In 2021, the highest portion of total CO2 emissions originated from the energy sector with 85.2%. The
remaining 14.5% originated from IPPU, 0.3% from agriculture and a percentage close to zero from
waste. CO2 emissions from energy increased by 9.6% compared to 2020 while increased by 197.1% as
compared to 1990. CO2 emissions from IPPU increased by 10.9% compared to 2020 and increased by
208.4% compared to 1990.
The largest portion of CH4 emissions originated from agriculture with 61.4% while a share of 19.3% is
from energy, and 19.3% from waste and industrial processes and product use. CH4 emissions from
agriculture increased by 0.8% compared to 2020 and it increased by 56.6% compared to 1990. Though
CH4 emissions from waste decreased by 12% compared to 2020, it increased by 28.5% compared to
1990.
While 78% of N2O emissions was from agriculture, 11.1% was from energy, 5.9% was from waste, and
5% was from IPPU. There is a 0.5% decrease and 61.5% increase in total N2O emissions compared to
2020 and 1990, respectively. GHG emissions by sectors are shown in Table ES 4.
Table ES 4 GHG emissions, 1990-2021
Emission
sources
1990
2000
2010
2015
2016
2017
2018
Total
Energy
IPPU
Agriculture
Waste
151 615
129 817
21 312
460
26.6
229 937
204 494
24 804
617
21.0
316 193
271 648
43 889
645
11.2
384 930
330 859
53 259
811
1.1
Total
Energy
IPPU
Agriculture
Waste
1 700
311
0.3
1 005
384
1 747
361
0.4
878
507
2 066
491
0.4
951
623
2 111
296
0.6
1 214
601
2 223
420
0.7
1 219
584
2 273
356
0.7
1 353
564
2 416
383
0.7
1 456
577
Total
Energy
IPPU
Agriculture
Waste
84
6.5
3.6
69
4.9
83
8.5
2.8
66
5.5
92
13.3
5.5
67
6.3
108
12.5
4.9
84
7.1
115
13.1
4.1
91
7.1
119
13.8
3.9
94
7.3
119
12.6
6.1
93
7.4
(kt)
2019
2020
2021
CO2
CH4
N2O
405
347
57
1
950
363
290
295
1.8
IPPU: Industrial Processes and Product Use. The LULUCF sector is not included.
Figures in the table may not add up to the totals due to rounding.
430
369
60
1
901
398
052
450
1.5
422
360
60
1
Turkish GHG Inventory Report 1990-2021
059
087
713
257
1.2
402
350
51
1
692
282
120
288
2.4
412
352
59
1
927
005
261
657
3.6
452 703
385 662
65 735
1 302
3.6
2 529
470
0.6
1 503
555
2 556
435
0.6
1 560
560
2 561
494
0.7
1 573
493
124
11.9
6.8
98
7.5
136
12.4
6.7
109
7.7
135
15.0
6.8
106
7.9
v v
Executive Summary
ES.4 Indirect GHG Emissions
Emissions of NOx, CO, NMVOC, SO2 and NH3 were also included in the report because they influence
climate change indirectly. Table ES 5 shows indirect GHG emissions. 99% of total NOx emissions which
was 0.97 Mt, comes from energy sector. Similarly, 91.7% of total CO emissions as high as 1.78 Mt in
2021 was due to the energy sector. NMVOC emissions was 1.2 Mt in 2021. The largest portion of NMVOC
emissions came from agriculture with 44.5% which is followed by IPPU with 32.3% and almost all SO2
emissions close to 2.7 Mt was from the energy sector in 2021.
Table ES 5 Indirect GHG emissions, 1990-2021
Emission sources
NOx
2000
2010
2015
2016
2017
2018
2019
2020
2021
Total
Energy
IPPU
LULUCF
Waste
253
250
0.95
0.51
0.93
1 475
1465
7.62
1.05
1.14
979
976
2.77
0.14
0.43
959
955
3.7
0.13
0.02
991
988
3.52
0.41
0.03
973
968
3.8
0.6
0.03
959
954
4.06
0.33
0.03
970
965
4.2
0.68
0.03
956
950
4.33
0.91
0.06
981
972
5.06
4.34
0.06
Total
Energy
IPPU
LULUCF
Waste
2 040
1 997
8.60
18.40
16.41
7 812
7 746
8.50
37.60
19.99
3 404
3 384
7.30
5.10
7.48
2 368
2 354
8.40
4.60
0.39
2 354
2 328
10.80
14.60
0.56
2 188
2 155
10.60
21.50
0.56
1 659
1 642
10.60
6.40
0.56
1 776
1 747
10.60
18.40
0.70
1 940
1 905
10.80
23.10
1.06
1 942
1 780
11.10
149.50
1.06
896
283
252
356
4.90
1 454
752
317
354
30.20
1 098
404
328
332
35.60
1 091
287
346
414
44.00
1 095
284
351
419
39.90
1 121
263
358
461
39.90
1 098
208
363
487
40.50
1 125
220
366
499
40.50
1 167
240
369
517
40.90
1 166
229
377
519
41.00
Total
Energy
IPPU
Waste
1 683
1 683
0.73
0.03
2 070
2 070
0.70
0.04
2 471
2 470
0.54
0.01
1 949
1 949
0.69
0.00
2 266
2 265
0.82
0.00
2 375
2 374
0.85
0.00
2 524
2 523
0.85
0.00
2 529
2 528
0.85
0.00
2 305
2 304
0.91
0.00
2 693
2 692
0.95
0.00
Total
Energy
IPPU
Waste
85
1.00
5.80
78.30
97
1.50
3.50
91.90
62
2.70
4.00
55.20
59
9.20
4.10
45.30
45
5.70
3.20
36.40
46
4.50
3.70
38.10
41
3.30
5.10
32.50
43
3.70
6.40
32.50
46
4.10
6.50
35.70
49
4.20
7.70
36.80
CO
NMVOC
Total
Energy
IPPU
Agriculture
Waste
SO2
NH3
Note that 0.00 kt figures refer to values smaller than 0.005 kt but greater than zero.
Figures in the table may not add up to the totals due to rounding.
IPPU: Industrial Processes and Product Use
vi
(kt)
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Contents
1
CONTENTS
Page
EXECUTIVE SUMMARY .................................................................................................................... i
ES.1 Background Information on Greenhouse Gas Inventories ....................................................... i
ES.2 Summary of National Emission and Removal Related Trends ................................................. iii
ES.3 Overview of Emission Estimates and Trends ......................................................................... v
ES.4 Indirect GHG Emissions ....................................................................................................... vi
CONTENTS .................................................................................................................................. vii
TABLES......................................................................................................................................... xi
FIGURES ....................................................................................................................................xviii
ABBREVIATIONS AND ACRONYMS ............................................................................................... xxii
1. INTRODUCTION ....................................................................................................................... 1
1.1.
Background Information on GHG Inventories ...................................................................... 1
1.2.
Institutional Arrangements ................................................................................................. 2
1.2.1. Institutional, Legal and Procedural Arrangements ........................................................... 2
1.2.2. Overview of Inventory Planning, Preparation and Management ....................................... 5
1.2.3. Quality Assurance, Quality Control and Verification ......................................................... 6
1.3.
Brief Description of the Process of Inventory Preparation ....................................................15
1.4.
Brief General Description of Methodologies and Data Sources .............................................17
1.5.
Brief Description of Key Source Categories .........................................................................20
1.6.
General Uncertainty Evaluation ..........................................................................................22
1.7.
General Assessment of Completeness ................................................................................23
2. TRENDS IN GREENHOUSE GAS EMISSIONS ..............................................................................24
2.1.
Emission Trends for Aggregated Greenhouse Gas Emissions................................................24
2.2.
Emission Trends by Gas ....................................................................................................27
2.3.
Emission Trends by Sector ................................................................................................33
2.4.
Emission Trends for Indirect Greenhouse Gases .................................................................42
3. ENERGY (CRF Sector 1) ...........................................................................................................43
3.1.
Sector Overview ...............................................................................................................43
3.2.
Fuel Combustion (Sector 1.A) ............................................................................................49
3.2.1. Comparison of the sectoral approach with reference approach ........................................55
3.2.2. International bunker fuels ............................................................................................60
3.2.2.1. International aviation ..............................................................................................60
3.2.2.2. International navigation ..........................................................................................62
3.2.3. Feedstocks, Reductants and other non-energy use of fuels.............................................64
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Contents
3.2.4. Energy industries (Category 1.A.1)................................................................................65
3.2.4.1. Public electricity and heat production (Category 1.A.1.a) ...........................................68
3.2.4.2. Petroleum refining (Category 1.A.1.b) ......................................................................80
3.2.4.3. Manufacture of solid fuels and other energy industries (Category 1.A.1.c) ..................82
3.2.5. Manufacturing industries and construction (Category 1.A.2) ...........................................83
3.2.5.1. Iron and steel industries (Category 1.A.2.a) .............................................................89
3.2.5.2. Non-ferrous metal (Category 1.A.2.b) ......................................................................92
3.2.5.3. Chemicals (Category 1.A.2.c) ..................................................................................93
3.2.5.4. Pulp, paper and print (Category 1.A.2.d) ..................................................................95
3.2.5.5. Food processing, beverages and tobacco (Category 1.A.2.e) .....................................97
3.2.5.6. Non-metallic minerals (Category 1.A.2.f) ..................................................................98
3.2.5.7. Other industries (Category 1.A.2.g) ....................................................................... 102
3.2.6. Transport (Category 1.A.3) ......................................................................................... 104
3.2.6.1. Civil aviation (Category 1.A.3.a) ............................................................................ 112
3.2.6.2. Road transportation (Category 1.A.3.b) .................................................................. 119
3.2.6.3. Railways (Category 1.A.3.c) .................................................................................. 123
3.2.6.4. Water-borne navigation (Category 1.A.3.d) ............................................................ 126
3.2.6.5. Pipeline transport (Category 1.A.3.e.i) ................................................................... 128
3.2.6.6. Off road transportation (Category 1.A.3.e.ii)........................................................... 130
3.2.7. Other sectors (Category 1.A.4) ................................................................................... 131
3.2.7.1. Commercial/Institutional (Category 1.A.4.a) ........................................................... 133
3.2.7.2. Residential (Category 1.A.4.b) ............................................................................... 135
3.2.7.3. Agriculture/Forestry/Fisheries (Category 1.A.4.c) .................................................... 136
3.2.8. Other (Category 1.A.5) ............................................................................................... 138
3.3.
Fugitive Emission from Fuels (Category 1.B) ..................................................................... 139
3.3.1. Solid fuels (Category 1.B.1) ........................................................................................ 140
3.3.2. Oil and natural gas (Category 1.B.2) ........................................................................... 145
3.4.
CO2 Transport and Storage (Category 1.C) ....................................................................... 149
4. INDUSTRIAL PROCESSES AND PRODUCT USE (CRF Sector 2) .................................................. 150
4.1.
Sector Overview ............................................................................................................. 150
4.2.
Mineral Industry (Category 2.A) ...................................................................................... 153
4.2.1. Cement production (Category 2.A.1) ........................................................................... 154
4.2.2. Lime production (Category 2.A.2) ............................................................................... 158
4.2.3. Glass production (Category 2.A.3)............................................................................... 163
4.2.4. Other process uses of carbonates (Category 2.A.4) ...................................................... 167
4.2.4.1. Ceramics (Category 2.A.4.a) .................................................................................. 167
4.2.4.2. Other uses of soda ash (Category 2.A.4.b) ............................................................. 172
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1
4.2.4.3. Non metallurgical magnesia production (Category 2.A.4.c) ...................................... 174
4.3.
Chemical Industry (Category 2.B) .................................................................................... 177
4.3.1. Ammonia production (Category 2.B.1) ........................................................................ 178
4.3.2. Nitric acid production (Category 2.B.2) ........................................................................ 182
4.3.3. Adipic acid production (Category 2.B.3) ....................................................................... 185
4.3.4. Caprolactam, glyoxal and glyoxylic acid production (Category 2.B.4) ............................. 185
4.3.5. Carbide production (Category 2.B.5) ........................................................................... 185
4.3.6. Titanium dioxide production (Category 2.B.6) .............................................................. 188
4.3.7. Soda ash production (Category 2.B.7) ......................................................................... 188
4.3.8. Petrochemical and carbon black production (Category 2.B.8) ........................................ 191
4.3.9. Fluorochemical production (Category 2.B.9) ................................................................ 194
4.4.
Metal Industry (Category 2.C) ......................................................................................... 194
4.4.1. Iron and steel production (Category 2.C.1) .................................................................. 195
4.4.2. Ferroalloys production (Category 2.C.2) ...................................................................... 204
4.4.3. Aluminium production (Category 2.C.3) ....................................................................... 208
4.4.4. Magnesium production (Category 2.C.4)...................................................................... 215
4.4.5. Lead production (Category 2.C.5) ............................................................................... 217
4.4.6. Zinc production (Category 2.C.6) ................................................................................ 220
4.5.
Non-Energy Products from Fuels and Solvent Use (Category 2.D) ...................................... 224
4.5.1. Lubricant use (Category 2.D.1) ................................................................................... 224
4.5.2. Paraffin wax use (Category 2.D.2) .............................................................................. 226
4.6.
Electronics Industry (Category 2.E) .................................................................................. 228
4.7.
Product Use as Substitutes for ODS (Category 2.F) ........................................................... 229
4.8.
Other Product Manufacture and Use (Category 2.G) ......................................................... 233
5. AGRICULTURE (CRF Sector 3) ................................................................................................ 236
5.1.
Sector Overview ............................................................................................................. 236
5.2.
Enteric Fermentation (Category 3.A) ................................................................................ 250
5.3.
Manure Management (Category 3.B) ............................................................................... 256
5.4.
Rice Cultivation (Category 3.C) ........................................................................................ 267
5.5.
Agricultural Soils (Category 3.D) ...................................................................................... 271
5.6.
Prescribed Burning of Savannas (Category 3.E) ................................................................ 280
5.7.
Field Burning of Agricultural Residues (Category 3.F) ........................................................ 280
5.8.
Liming (Category 3.G)..................................................................................................... 283
5.9.
Urea Application (Category 3.H) ...................................................................................... 283
5.10. Other Carbon-Containing Fertilizers (Category 3.I)............................................................ 286
5.11. Other (Category 3.J) ....................................................................................................... 286
6. LULUCF (CRF Sector 4) ........................................................................................................... 287
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Contents
6.1. Sector Overview ............................................................................................................... 287
6.2. Forest Land (4.A) .............................................................................................................. 299
6.3. Croplands (4.B) ................................................................................................................ 318
6.4. Grassland (4.C)................................................................................................................. 336
6.5. Wetlands (4.D) ................................................................................................................. 342
6.6. Settlements (4.E) .............................................................................................................. 350
6.7. Other land (4.F) ................................................................................................................ 358
6.8. Direct N2O emissions from N inputs to managed soils (4(I)) ................................................ 359
6.9. Emissions and removals from drainage and rewetting and other management of organic and
mineral soils (4(II)) ................................................................................................................. 361
6.10. N2O emissions from N mineralization/immobilization associated with loss/gain of soil organic
matter resulting from change of land use or management of mineral soils (4(III)) ...................... 362
6.11. Indirect N2O emissions from managed soils (4(IV)) ........................................................... 364
6.12. Biomass Burning (4(V)) ................................................................................................... 366
6.13. Harvested Wood Products (4.G) ....................................................................................... 369
7. WASTE (CRF Sector 5) ............................................................................................................ 371
7.1. Sector Overview ............................................................................................................... 371
7.2. Solid Waste Disposal (Category 5.A) .................................................................................. 373
7.3. Biological Treatment of Solid Waste (Category 5.B)............................................................. 394
7.4. Incineration and Open Burning of Waste (Category 5.C) ..................................................... 400
7.5. Wastewater Treatment and Discharge (Category 5.D) ......................................................... 409
7.6. Other (Category 5.E)......................................................................................................... 429
8. OTHER................................................................................................................................... 430
9. INDIRECT CARBON DIOXIDE AND NITROUS OXIDE EMISSIONS ............................................... 430
10. RECALCULATIONS AND IMPROVEMENTS ............................................................................... 431
Annex 1: Key Categories ............................................................................................................. 439
Annex 2: Uncertainty .................................................................................................................. 457
Annex 3: Country Specific Carbon Content Determination and Emission Factors ............................. 486
Annex 4: National Energy Balance Sheets, 2021 ........................................................................... 499
Annex 5: Completeness .............................................................................................................. 502
References ................................................................................................................................. 509
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Tables
TABLES
Page
Table ES 1 Greenhouse gas emissions, 1990-2021 .......................................................................... iii
Table ES 2 Overview of GHG emissions and removals, 1990-2021 .................................................... iii
Table ES 3 Greenhouse gas emissions by sectors, 1990-2021 .......................................................... iv
Table ES 4 GHG emissions, 1990-2021 ........................................................................................... v
Table ES 5 Indirect GHG emissions, 1990-2021 ............................................................................... vi
Table 1.1 Institutions by responsiblities for national GHG inventory .................................................. 4
Table 1.2 Criteria for assessing achievement of quality objectives .................................................... 8
Table 1.3 Time schedule for preparation of the “t-2” annual inventory submission............................16
Table 1.4 Summary for methods and emission factors used, 2021 ...................................................18
Table 1.5 Activity data sources for GHG inventory ..........................................................................19
Table 1.6 Key categories for GHG inventory, 2021 ..........................................................................21
Table 2.1 Aggregated GHG emissions by sectors ............................................................................26
Table 2.2 Aggregated GHG emissions excluding LULUCF .................................................................28
Table 2.3 Fluorinated gases emissions by sector, 1990-2021 ...........................................................32
Table 2.4 Contribution of sectors to the net GHG emissions ............................................................35
Table 2.5 Contribution of sectors to the GHG emissions without LULUCF .........................................35
Table 2.6 Total emissions from the energy sector by source ...........................................................36
Table 2.7 Total emissions from the industrial process and product use sector by source ...................37
Table 2.8 Total emissions from the agriculture sector by source ......................................................38
Table 2.9 Total emissions and removals from the LULUCF sector by source .....................................39
Table 2.10 Total emissions from the waste sector by source ...........................................................41
Table 2.11 Total emissions for indirect greenhouse gases, 1990-2021 .............................................42
Table 3.1 Energy sector emissions by gas, 1990-2021 ....................................................................44
Table 3.2 Energy sector GHG emissions, 1990-2021 .......................................................................45
Table 3.3 Summary of methods and emission factors used in energy sector.....................................48
Table 3.4 Summary table for the data source in fuel combustion (1A) sector ...................................50
Table 3.5 Country specific carbon contents of fuels ........................................................................50
Table 3.6 Country specific oxidation factor of fuels .........................................................................51
Table 3.7 CO2 emission factors of fuels ..........................................................................................51
Table 3.8 Emissions from fuel combustion (1A), 1990-2021 ............................................................52
Table 3.9 Fuel allocation in reference approach ..............................................................................56
Table 3.10 CO2 emissions from fuel combustion, 1990-2021 ...........................................................57
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Tables
Table 3.11 Comparison of CO2 from fuel combustion between reference and sectoral approach, 19902021............................................................................................................................................59
Table 3.12 Emissions and fuel for international aviation, 1990-2021 ................................................61
Table 3.13 Emissions and fuel for international navigation, 1990-2021 ............................................63
Table 3.14 Summary table for use of feedstock, reductants and other non energy use of .................64
Table 3.15 GHG emissions from energy industries, 1990-2021 ........................................................66
Table 3.16 Emissions from category 1A1a, 1990-2021 ....................................................................71
Table 3.17 Average NCVs of fuels used in category 1.A.1.a .............................................................72
Table 3.18 CO2 emission factors used for source category 1.A.1.a, 1990-2021 .................................73
Table 3.19 CH4 and N2O emission factors used for source category 1.A.1.a ......................................74
Table 3.20 IEFs of fuels used for category 1.A.1.a, 1990-2021 ........................................................76
Table 3.21 Comparison of GHG emissions from 1.A.1.a category ,1990-2021 ...................................77
Table 3.22 Comparison of solid fuel consumption, 1990-2021 .........................................................78
Table 3.23 Emissions from petroleum refining, 1990-2021 ..............................................................80
Table 3.24 Emissions from category 1.A.1.c, 1990-2021 .................................................................82
Table 3.25 Fuel combustion emissions from manufacturing industry and construction, 1990-2021 .....84
Table 3.26 GHG emissions from manufacturing industry and construction, 1990-2021 ......................85
Table 3.27 Contribution of subsectors of manufacturing industries and construction, 2020-2021 .......86
Table 3.28 Defualt CH4 and N2O EFs for 1A2 sector ........................................................................87
Table 3.29 CO2 implied emission factors for 1A2 category ...............................................................88
Table 3.30 Fuel combustion emissions from iron and steel industry, 1990-2021 ...............................90
Table 3.31 Fuel combustion emissions from non-ferrous metals, 1990-2021 ....................................92
Table 3.32 Fuel combustion emissions from chemicals, 1990-2021 ..................................................94
Table 3.33 Fuel combustion emissions from pulp, paper and print, 1990-2021 .................................96
Table 3.34 Fuel combustion emissions from 1A2e category, 1990-2021 ..........................................97
Table 3.35 Fuel combustion emissions from non-metallic minerals, 1990-2021 .................................99
Table 3.36 Fuel combustion emissions from other industries, 1990-2021 ....................................... 102
Table 3.37 GHG emissions from transport sector, 1990-2021 ........................................................ 105
Table 3.38 GHG emissions by transport mode, 1990-2021 ............................................................ 105
Table 3.39 Method used in the calculation of GHG emissions by transport modes ........................... 111
Table 3.40 GHG emissions from domestic aviation, 1990-2021 ...................................................... 117
Table 3.41 GHG emissions for LTO and cruise in domestic aviation, 2021 ...................................... 117
Table 3.42 IEFs of domestic aviation 1990-2021........................................................................... 118
Table 3.43 GHG emissions from road transportation, 1990-2021 ................................................... 119
Table 3.44 Comparison of COPERT and current methodology for GHG emissions from road
transportation, 2016-2018 .......................................................................................................... 122
Table 3.45 GHG emissions from railway, 1990-2021 ..................................................................... 123
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Table 3.46 GHG emissions from domestic navigation, 1990-2021 .................................................. 126
Table 3.47 The trend in GHG emissions from pipeline transport, 1990-2021 ................................... 129
Table 3.48 Fuel combustion emissions from other sectors (1A4), 1990-2021 .................................. 132
Table 3.49 N2O and CH4 emission factors of fuels used in others sector (1A4). ............................... 133
Table 3.50 Fuel combustion emissions from 1.A.4.a category, 1990-2021 ...................................... 133
Table 3.51 Fuel combustion emissions from residential sector, 1990-2021 ..................................... 135
Table 3.52 Fuel combustion emissions from agriculture sector, 1990-2021 ..................................... 137
Table 3.53 Fugitive emissions from fuels, 1990-2021 .................................................................... 139
Table 3.54 Fugitive emissions from fuels by subcategory, 1990-2021 ............................................ 140
Table 3.55 Fugitive emissions from solid fuels, 1990-2021 ............................................................ 141
Table 3.56 Fugitive emissions from abandoned coal mines,1990-2021 ........................................... 143
Table 3.57 Coefficients used in the calculation of abandoned coal mines methane emission ............ 144
Table 3.58 Fugitive emissions from oil and natural gas systems,1990-2021 .................................... 145
Table 4.1 Industrial processes and product use sector emissions, 2021 ......................................... 150
Table 4.2 Industrial processes and product use emissions by gas, 1990- 2021 ............................... 151
Table 4.3 Overview of industrial processes and product use sector emissions, 1990-2021 ............... 151
Table 4.4 CO2 emissions from cement production, 1990-2021 ....................................................... 157
Table 4.5 Lime production and CO2 emissions, 1990-2021 ............................................................ 161
Table 4.6 Molten glass production and CO2 emissions by type of glass, 1990-2021 ......................... 165
Table 4.7 EFs for carbonates, 1990-2021 ..................................................................................... 165
Table 4.8 Raw material consumption and production, 1990-2021 .................................................. 169
Table 4.9 Carbonate EFs for all years in the time series ................................................................ 169
Table 4.10 CO2 emissions from raw material consumption, 1990-2021........................................... 170
Table 4.11 Activity data for the other use of soda ash and CO2 emissions, 1990-2021 .................... 173
Table 4.12 Magnesia production and CO2 emissions, 1990-2021 .................................................... 176
Table 4.13 Ammonia production and CO2 emissions, 1990-2021 .................................................... 180
Table 4.14 Nitric acid production and N2O emissions, 1990-2021 ................................................... 183
Table 4.15 Calcium carbide production and CO2 emissions, 1990-2021 .......................................... 187
Table 4.16 Soda ash production and CO2 emissions, 1990-2021 .................................................... 190
Table 4.17 CO2 emissions from flaring in petrochemical sector, 1990-2021 .................................... 192
Table 4.18 CO2 emissions allocations in 2.C.1 category, 1990-2021 ............................................... 197
Table 4.19 Sinter, pellet and iron & steel production by plant type, 1990-2021 .............................. 201
Table 4.20 Emission factors iron and steel production ................................................................... 202
Table 4.21 Ferroalloys production and emissions, 1990-2021 ........................................................ 206
Table 4.22 PFCs, CF4 and C2F6 emissions 1990-2021..................................................................... 211
Table 4.23 Aluminium production emissions, 1990-2021 ............................................................... 212
Table 4.24 Emission factors for aluminium production with Søderberg cells, 2005-2015 .................. 213
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Table 4.25 Emission factors for aluminium production with Prebaked cells, 2015-2021 ................... 213
Table 4.26 CO2 emissions from magnesium production, 2016-2021 ............................................... 216
Table 4.27 SF6 emissions from magnesium casting, 2016-2021 ..................................................... 216
Table 4.28 Lead production and CO2 emissions from lead production, 1990-2021 ........................... 219
Table 4.29 Zinc productions and CO2 emission (kt), 1990-2021 ..................................................... 222
Table 4.30 The Amount of lubricant used and CO2 emissions, 1990-2021 ...................................... 225
Table 4.31 The Amount of paraffin wax used and CO2 emissions, 1990-2021 ................................. 227
Table 4.32 Consumption of each gases, 2010-2021 ...................................................................... 229
Table 4.33 Total HFCs emissions, 1999-2021 ............................................................................... 231
Table 4.34 HFCs Emissions ......................................................................................................... 232
Table 4.35 SF6 Consumption and Electricity Consumption ............................................................. 234
Table 5.1 Categories of the agriculture sector and emitted gases .................................................. 236
Table 5.2 Agriculture sector emissions and overall percentages by categories, 2021 ....................... 237
Table 5.3 Overview of the agriculture sector emissions, 1990‒2021 .............................................. 238
Table 5.4 Agriculture sector emissions ‒ comparison between 2020 and 2021................................ 241
Table 5.5 Overview of GHGs in the agriculture sector, 1990‒2021 ................................................. 243
Table 5.6 Livestock population numbers in Türkiye, 1990‒2021 .................................................... 245
Table 5.7 Subcategories of cattle population, 1990‒2021 .............................................................. 247
Table 5.8 Subcategories of dairy cattle population, 1990‒2021 ..................................................... 247
Table 5.9 Overview of CH4 emissions in the agriculture sector, 1990‒2021 .................................... 248
Table 5.10 Overview of N2O emissions in the agriculture sector, 1990‒2021 .................................. 249
Table 5.11 Enteric fermentation CH4 emissions, 1990‒2021 .......................................................... 252
Table 5.12 Key T2 parameters and estimated emissions for dairy cattle, 1990‒2021 ...................... 255
Table 5.13 Key T2 parameters and estimated emissions for non-dairy cattle, 1990‒2021 ................ 255
Table 5.14 Overview of emissions from manure management, 1990‒2021..................................... 258
Table 5.15 Typical animal mass, Nrate and Nex values for cattle and poultry, 1990‒2021 ............... 261
Table 5.16 Typical animal mass, Nrate and Nex values for some livestock species .......................... 261
Table 5.17 Manure management CH4 emission factors for cattle and swine .................................... 264
Table 5.18 Manure management CH4 emission factors for sheep and other livestock ...................... 264
Table 5.19 Manure Management System Distribution, 1990‒2021 ................................................. 265
Table 5.20 Irrigated area and estimated emissions for rice cultivation, 1990‒2021 ......................... 268
Table 5.21 Overview of N2O emissions from managed soils, 1990‒2021 ........................................ 273
Table 5.22 Categories of Direct N2O emissions of agricultural soils, 1990‒2021 .............................. 273
Table 5.23 Subcategories of Organic N fertilizers emissions, 1990‒2021 ........................................ 274
Table 5.24 Categories of Indirect N2O emissions of agricultural soils, 1990‒2021 ........................... 274
Table 5.25 Crop data used for crop residue calculations ................................................................ 277
Table 5.26 Emissions from field burning of agricultural residues, 1990 and 2021 ............................ 281
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Table 6.1 Key categories identification in the LULUCF sector (Tier 1) ............................................. 289
Table 6.2 Ecozones in Türkiye and their relationships with climate classifications (Serengil, 2018) .. 291
Table 6.3 Classification approach for all categories and subcategories under SBLMS ....................... 294
Table 6.4 A sample land use matrix (2015) .................................................................................. 297
Table 6.5 Confusion Matrix ......................................................................................................... 298
Table 6.6 Completeness Table..................................................................................................... 298
Table 6.7 Annual increment rates of forest types in Türkiye .......................................................... 300
Table 6.8 Forest area (kha) changes in Türkiye, 1990-2021 .......................................................... 301
Table 6.9 Forest inventory, 1972 (Source: GDF) ........................................................................... 303
Table 6.10 Growing stock, 1990-2021 (Source: GDF).................................................................... 304
Table 6.11 Annual volume increment, 1990-2021 (Source: GDF) ................................................... 304
Table 6.12 Area of Land converted to forest land ......................................................................... 308
Table 6.13 The Average basic wood density and national BCEF’s factors (Tolunay, 2013) ............... 310
Table 6.14 Coefficients used to calculate CS and CSC in L-FL ........................................................ 310
Table 6.15 Carbon stocks in DOM used for all forest areas in Türkiye ............................................ 311
Table 6.16 SOC stocks of forests disaggregated for ecozones........................................................ 311
Table 6.17 Uncertainty calculation results for the whole LULUCF sector ......................................... 313
Table 6.18 Uncertainty summary table for Forest land subcategories ............................................. 314
Table 6.19 Changes by the recalculation of Forest Land Remaining Forest Land subcategory .......... 316
Table 6.20 Coefficients and CS values used in annual/perennial conversions in cropland category ... 322
Table 6.20a Coefficients and soil CS values used in annual/perennial conversions in cropland category
................................................................................................................................................. 323
Table 6.21 Coefficients and CS values used in L-CL category ......................................................... 325
Table 6.22 Coefficients and CS values used in L-CL category ......................................................... 328
Table 6.23 Coefficients and soil CS values used in L-CL category ................................................... 329
Table 6.24 Uncertainty summary table for Cropland subcategories ................................................ 334
Table 6.25 Coefficients and living biomass CS values for L-GL subcategories .................................. 338
Table 6.26 Coefficients and DOM CS values for L-GL subcategories ............................................... 339
Table 6.27 Coefficients and soil CS values for L-GL subcategories.................................................. 339
Table 6.28 Uncertainty summary table for Grassland subcategories ............................................... 340
Table 6.29 Coefficients and living biomass CS values for L-WL subcategories ................................. 345
Table 6.30 Coefficients and DOM CS values for L-WL subcategories .............................................. 346
Table 6.31 Coefficients and soil CS values for L-WL subcategories ................................................. 347
Table 6.32 Uncertainty summary table for Wetland subcategories ................................................. 348
Table 6.33 Total carbon stocks calculated for various settlements intensity classes (Serengil et al.,
2015) ........................................................................................................................................ 352
Table 6.34 Coefficients and living biomass CS values for L-SL subcategories .................................. 354
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Table 6.35 Coefficients and DOM CS values for L-SL subcategories................................................ 355
Table 6.36 Coefficients and soil CS values for L-SL subcategories .................................................. 356
Table 6.37 Uncertainty summary table for Settlement subcategories ............................................. 357
Table 6.38 The coefficients and EF used in Other land category .................................................... 358
Table 6.39 Uncertainty summary table for Otherland subcategories ............................................... 359
Table 6.40 Uncertainty summary table for 4 (I) category .............................................................. 360
Table 6.41 Uncertainty summary table for 4 (II) category ............................................................. 361
Table 6.42 EFs used for N2O emissions ........................................................................................ 362
Table 6.43 Uncertainty summary table for 4 (III) category............................................................ 363
Table 6.44 EFs used for N2O emissions ........................................................................................ 365
Table 6.45 Uncertainty summary table for 4 (IV) category ............................................................ 365
Table 6.46 EFs used for Biomass burning emissions ..................................................................... 367
Table 6.47 Uncertainty summary table for 4 (V) category ............................................................. 368
Table 7.1 CO2 equivalent emissions for the waste sector, 2021 ...................................................... 371
Table 7.2 Summary of methods and emission factors used ........................................................... 372
Table 7.3 CH4 generated, recovered and emitted from SWDS, 1990-2021 ...................................... 375
Table 7.4 Number of managed SWDS, 1992-2020 ........................................................................ 377
Table 7.5 Amount of municipal waste by disposal methods, 1994-2020 ......................................... 377
Table 7.6 Annual MSW and distribution of waste by management type, 1990-2021 ........................ 378
Table 7.7 Mid-year population, 1990-2021 ................................................................................... 378
Table 7.8 Waste per capita, 1990-2021........................................................................................ 379
Table 7.9 Percentage of MSW disposed in the SWDS, 1990-2021 .................................................. 380
Table 7.10 Waste composition data, 1990-2021 ........................................................................... 382
Table 7.11 Annual IW and distribution of waste by management type, 1990-2021 ......................... 383
Table 7.12 GDP by production approach, 1990-2021 .................................................................... 384
Table 7.13 Industrial waste activity data, 1990-2021 .................................................................... 385
Table 7.14 Weighted averages of MCF, 1990-2021 ....................................................................... 386
Table 7.15 DOC values by individual waste type ........................................................................... 386
Table 7.16 DOC by weight, 1990-2021 ........................................................................................ 387
Table 7.17 Dry temperate k values by waste type ........................................................................ 387
Table 7.18 Methane recovery, 1990-2021 .................................................................................... 389
Table 7.19 CH4 generated from SS at SWDS, 1990-2021 ............................................................... 390
Table 7.20 Annual SS and distribution of waste by management type, 1990-2021 .......................... 390
Table 7.21 CH4 generated from CW at SWDS, 1990-2021.............................................................. 391
Table 7.22 Annual CW and distribution of waste by management type, 1990-2021......................... 392
Table 7.23 Number and total capacity of composting plants, 1994-2021 ........................................ 396
Table 7.24 Activity data, CH4 and N2O emissions from composting, 1990-2021 ............................... 397
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Table 7.25 CO2 emissions from open burning of waste, 1990-2021 ................................................ 402
Table 7.26 CH4 emissions from open burning of waste, 1990-2021 ................................................ 403
Table 7.27 N2O emissions from open burning of waste, 1990-2021 ............................................... 405
Table 7.28 The fraction and amount of MSW open-burned, 1990-2021 .......................................... 406
Table 7.29 Default dry matter content, total carbon content and fossil carbon fraction ................... 407
Table 7.30 CH4 generated, recovered and emitted from domestic wastewater, 1990-2021 .............. 410
Table 7.31 Fraction of population and total, rural, urban population, 1990-2021 ............................ 412
Table 7.32 Total organics in wastewater (TOW) and organic component removed as sludge (S) for
domestic wastewater, 1990-2021 ................................................................................................ 413
Table 7.33 Degrees of treatment utilization (T) by population class ............................................... 414
Table 7.34 MCF, EFs, utilization degrees and weighted EFs by population class .............................. 414
Table 7.35 Methane recovery, 1990-2021 .................................................................................... 415
Table 7.36 Amount of sewage sludge by disposal and recovery methods, 1994-2020 ..................... 417
Table 7.37 CH4 emissions from industrial wastewater by sector, 1990-2021 ................................... 419
Table 7.38 Amount of industrial wastewater discharged by sector, 1990-2021 ............................... 421
Table 7.39 COD values by industry type....................................................................................... 421
Table 7.40 TOWi in wastewater by industry sector, 1990-2021 ...................................................... 422
Table 7.41 MCF, EFs, fractional usages and weighted EF for industrial wastewater ......................... 423
Table 7.42 N2O emissions from wastewater, 1990-2021 ................................................................ 425
Table 7.43 Population and per capita protein consumption, 1990-2021 .......................................... 426
Table 7.44 Parameters for estimation of nitrogen in effluent, 2021 ................................................ 427
Table 10.1 Recalculations made in the current submission and their implications to the emission level,
1990 and 2020 ........................................................................................................................... 434
Table A1 Key category analysis summary, 2021 ........................................................................... 440
Table A2 Key category analysis level assessment with LULUCF, 2021 ............................................ 441
Table A3 Key category analysis level assessment without LULUCF, 2021 ........................................ 445
Table A4 Key category analysis trend assessment with LULUCF, 2021 ........................................... 449
Table A5 Key category analysis trend assessment without LULUCF, 2021....................................... 453
Table A6 Approach 1 Uncertainty assessment .............................................................................. 459
Table A7.1 Approach 2 Uncertainty assessment (Monte Carlo Simulation Method) for 2017 ............ 467
Table A7.2 Approach 2 Uncertainty assessment (Monte Carlo Simulation Method) for 2018 ............ 468
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Figures
FIGURES
Page
Figure 2.1 Emission trend for aggregated GHG emissions, 1990-2021 ..............................................24
Figure 2.2 Trends in emissions per capita and dollar of GDP relative to 1990 ...................................25
Figure 2.3 GHG Emissions and sinks by sector, 1990-2021 ..............................................................26
Figure 2.4 Emission trend of main GHGs, 1990-2021 ......................................................................27
Figure 2.5 Trends in emissions by gas relative to 1990 ...................................................................28
Figure 2.6 CO2 emissions by sector, 1990-2021 ..............................................................................29
Figure 2.7 CH4 emissions by sector, 1990-2021 ..............................................................................30
Figure 2.8 N2O emissions by sector, 1990-2021 ..............................................................................31
Figure 2.9 GHG emission trend by sectors, 1990-2021 ....................................................................33
Figure 2.10 Electricity generation and shares by energy resources, 2019-2021 .................................34
Figure 2.11 Trend of total emissions from the energy sector, 1990-2021 .........................................36
Figure 2.12 Trend of total emissions from IPPU sector, 1990-2021 ..................................................37
Figure 2.13 Trend of total emissions from agriculture sector, 1990-2021 .........................................38
Figure 2.14 Trend of total emissions from the LULUCF sector, 1990-2021 ........................................40
Figure 2.15 Trend of total emissions from the waste sector, 1990-2021 ...........................................41
Figure 3.1 GHG emissions from fuel combustion, 1990-2021 ...........................................................46
Figure 3.2 Fugitive emissions, 1990-2021 ......................................................................................47
Figure 3.3 CO2 emissions from fuel combustion, 1990-2021 ............................................................53
Figure 3.4 CO2 emissions from fuel combustion by sectors, 1990 and 2021 ......................................53
Figure 3.5 CH4 emissions from fuel combustion, 1990-2021 ............................................................54
Figure 3.6 N2O emissions from fuel combustion, 1990-2021 ............................................................54
Figure 3.7 CO2 emissions from fuel combustion, 1990-2021 ............................................................58
Figure 3.8 GHG emissions from international aviation, 1990-2021 ...................................................61
Figure 3.9 GHG emissions from international navigation, 1990-2021 ................................................63
Figure 3.10 Energy mix of category 1.A.1.a, 1990-2021 ..................................................................69
Figure 3.11 Electricity generation and shares by energy resources, 2020 - 2021...............................70
Figure 3.12 Electricity generation and shares by energy resources, 1990 - 2021...............................70
Figure 3.13 GHG emissions for transportation sector, 1990-2021 ................................................... 104
Figure 3.14 GHG emission trend by transport mode, 1990-2021 .................................................... 106
Figure 3.15 Comparison of number of flights, fuel consumption and GHG emissions of civil aviation,
1990-2021 ................................................................................................................................. 107
Figure 3.16 Emission distributions by fuel types in road transportation, 1990-2021 ......................... 108
Figure 3.17 Passenger-km by road, 1998-2021............................................................................. 109
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Figure 3.18 Passenger-km by railway, 1998-2021 ......................................................................... 109
Figure 3.19 GHG emissions for domestic aviation, 1990-2021........................................................ 112
Figure 3.20 CH4 and N2O emissions for domestic aviation, 1990-2021 ............................................ 113
Figure 3.21 Passenger traffic, 2006-2021 ..................................................................................... 114
Figure 3.22 Freight traffic, 2006-2021.......................................................................................... 115
Figure 3.23 Number of domestic LTO, 1990-2021 ......................................................................... 116
Figure 3.24 GHG emissions for road transportation, 1990-2021 ..................................................... 120
Figure 3.25 CH4 and N2O emissions for road transportation, 1990-2021 ......................................... 120
Figure 3.26 CO2 emission distributions by fuel types (%), 2021 ..................................................... 121
Figure 3.27 GHG emissions for railways, 1990-2021 ..................................................................... 124
Figure 3.28 CH4 and N2O emissions from railways, 1990-2021....................................................... 124
Figure 3.29 GHG emissions from domestic water-borne navigation, 1990-2021 .............................. 127
Figure 3.30 CH4 and N2O emissions from domestic water-borne navigation, 1990-2021 .................. 127
Figure 3.31 GHG emissions from pipeline transport, 1990-2021 ..................................................... 129
Figure 3.32 Domestic coal production 1990-2021 ......................................................................... 142
Figure 3.33 CH4 emissions from coal mining, 1990-2021 ............................................................... 142
Figure 3.34 Oil production, 1990–2021 ........................................................................................ 146
Figure 3.35 Natural gas production, 1990-2021 ............................................................................ 146
Figure 3.36 Natural gas transmission by pipeline, 1990-2021 ........................................................ 147
Figure 3.37 Fugitive emissions from oil and gas system, 1990-2021 .............................................. 147
Figure 4.1 Emissions from industrial processes and product use by subsector, 2021 ....................... 152
Figure 4.2 Emissions from industrial processes and product use by subsector, 1990–2021 .............. 153
Figure 4.3 Share of CO2 emissions from mineral production, 2021 ................................................. 154
Figure 4.4 Trend at clinker, cement production and related CO2 emissions, 1990-2021 ................... 155
Figure 4.5 CO2 emissions from lime production, 1990-2021 .......................................................... 160
Figure 4.6 CO2 emissions from glass production, 1990-2021 ......................................................... 164
Figure 4.7 CO2 emissions from other uses of carbonates, 1990-2021 ............................................. 167
Figure 4.8 CO2 emissions, by raw materials type, from ceramics, 1990-2021 .................................. 168
Figure 4.9 CO2 emissions from other use of soda ash, 1990-2021.................................................. 172
Figure 4.10 CO2 emissions from magnesia production, 1990-2021 ................................................. 175
Figure 4.11 CO2 emissions from chemical industry, 2021............................................................... 177
Figure 4.12 CO2 emissions and removals from ammonia production, 1990-2021 ............................. 179
Figure 4.13 N2O emissions from nitric acid productions, 1990-2021 ............................................... 182
Figure 4.14 CO2 emissions due to carbide production, 1990-2021 .................................................. 186
Figure 4.15 CO2 Emissions resulting from soda ash production 2009-2021 ..................................... 189
Figure 4.16 Emissions from metal industry, 2021.......................................................................... 195
Figure 4.17 CO2 emissions allocations within the 2.C.1 CRF category, 1990-2021 ........................... 197
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Figures
Figure 4.18 Allocations of the emissions from integrated iron and steel plants ................................ 200
Figure 4.19 Comparing emissions (kt CO2 eq.) and steel production (kt) from BOFs anf EAFs .......... 201
Figure 4.20 CO2 emissions from ferroalloys production, 1990-2021 ................................................ 205
Figure 4.21 CO2 emissions from aluminium production, 1990-2021 ................................................ 209
Figure 4.22 CO2 emissions from primary and secondary zinc production, 1990-2021....................... 222
Figure 4.23 Total HFCs emissions, 1999-2021 .............................................................................. 231
Figure 4.24 HFC-227ea Emissions (tonnes), 2000-2021 ................................................................ 233
Figure 4.25 SF6 emissions, 1996-2021 ......................................................................................... 235
Figure 5.1 Cumulative emissions of agricultural categories, 1990‒2021.......................................... 239
Figure 5.2 Category shares and methods used in the agriculture sector, 2021 ................................ 240
Figure 5.3 Trends in major agriculture categories ......................................................................... 242
Figure 5.4 Trends in minor agriculture categories ......................................................................... 242
Figure 5.5 Population numbers for cattle categories, 1990‒2021 ................................................... 246
Figure 5.6 Enteric Fermentation Emission Sources, 2021 ............................................................... 251
Figure 5.7 Manure Management Emission Sources, 2021 .............................................................. 257
Figure 5.8 Comparing CH4 and N2O emission trends, 1990‒2021 ................................................... 260
Figure 5.9 Harvested area and emitted CH4 for rice cultivation, 1990‒2021 .................................... 267
Figure 5.10 Sub-categories of Agricultural Soils Emission Sources, 2021 ........................................ 272
Figure 5.11 Climate Map of Türkiye ............................................................................................. 278
Figure 5.12 Urea application and emitted CO2, 1990‒2021 ............................................................ 284
Figure 6.1 The trend of LULUCF sector net removals including HWP 1990-2021 ............................. 287
Figure 6.2 The ecoregions in Türkiye (Serengil, 2018) .................................................................. 290
Figure 6.3 The temporal structure of the SBLMS with the satellites used ........................................ 294
Figure 6.4 Change detection approach between reference years ................................................... 296
Figure 6.5 Gains and losses in Forest land Remaining Forest land subcategory (FL-FL) ................... 306
Figure 6.6 Gains and losses in Land Converted to Forest land subcategory (L-FL) ........................... 307
Figure 6.7 Area data for Land Converted to Forest land subcategory ............................................. 307
Figure 6.8 The changes in net emissions and removals in CL-CL and L-CL subcategories ................ 318
Figure 6.9 The change in area of CL-CL ....................................................................................... 319
Figure 6.10 The change in area of L-CL ....................................................................................... 319
Figure 6.11 The change in net emissions in Grassland category..................................................... 336
Figure 6.12 The change in area of GL-GL ..................................................................................... 337
Figure 6.13 The change in area of L-GL ....................................................................................... 337
Figure 6.14 The emissions/removals from wetlands category ........................................................ 343
Figure 6.15 a The change in area of managed wetlands ............................................................... 344
Figure 6.15 b The change in area of unmanaged wetlands............................................................ 344
Figure 6.16 The change in net emissions in settlements................................................................ 350
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Figures
Figure 6.17 The change in area of settlements ............................................................................. 351
Figure 6.18 Impervious areas in the study area (Alibeyköy, Sazlıdere and Kağıthane watersheds in
Istanbul) .................................................................................................................................... 353
Figure 6.19 Carbon intensity in the study area (Alibeyköy, Sazlıdere and Kağıthane watersheds in
Istanbul) .................................................................................................................................... 353
Figure 6.20 Emissions and removals in HWP pool ......................................................................... 369
Figure 7.1 Total GHG emissions of waste sector, 1990-2021 ......................................................... 372
Figure 7.2 CH4 emissions from solid waste disposal, 1990-2021 .................................................... 375
Figure 7.3 Amount of waste treated by composting plants, 1990-2021 .......................................... 398
Figure 7.4 CH4 emissions from composting, 1990-2021 ................................................................. 398
Figure 7.5 N2O emissions from composting, 1990-2021 ................................................................ 398
Figure 7.6 CO2 emissions from open burning of waste, 1990-2021 ................................................ 402
Figure 7.7 CH4 emissions from open burning of waste, 1990-2021 ................................................ 404
Figure 7.8 N2O emissions from open burning of waste, 1990-2021 ................................................ 405
Figure 7.9 Total amount of MSW open-burned, 1990-2021 ........................................................... 406
Figure 7.10 CH4 emissions from domestic wastewater, 1990-2021 ................................................. 411
Figure 7.11 CH4 emissions from industrial wastewater, 1990-2021 ................................................ 419
Figure 7.12 N2O emissions from wastewater, 1990-2021............................................................... 425
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Abbreviations and Acronyms
ABBREVIATIONS AND ACRONYMS
xxii
2006 IPCC Guidelines
2006 IPCC Guidelines for National Greenhouse Gas Inventories
ABPRS
Address Based Population Registration System
AD
Activity data
AFOLU
Agriculture, Forestry and Other Land Use
AWMS
Animal waste management systems
BCEF
Biomass conversion and expansion factor
BEF
Biomass expansion factor
BOD
Biochemical oxygen demand
BOF
Basic oxygen furnace
BOTAŞ
Petroleum Pipeline Corporation
BWD
Basic wood density
C
Carbon
°C
Degree centigrade
C2F6
Hexafluoroethane
CaCO3
Calcium carbonate
CAGR
Compound annual growth rate
CaMg(CO3)2
Dolomite
CaO
Calcium oxide
CBCC
Coordination Board on Climate Change
CBCCA
Coordination Board on Climate Change and Adaptation
CBCCAM
Coordination Board on Climate Change and Air Management
CF
Carbon fraction of dry matter
CF
Carbon fraction
CF4
Carbon tetrafluoride
CFCs
Chlorofluorocarbons
CH4
Methane
CITEPA
Technical Reference Center for Air Pollution and Climate Change
CKD
Cement kiln dust
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Abbreviations and Acronyms
CL-SL
Cropland converted to settlements
cm
Centimeter
CO
Carbon monoxide
CO2
Carbon dioxide
CO2 eq.
Carbon dioxide equivalent
COD
Chemical oxygen demand
CORINAIR
Core Inventory of Air Emissions in Europe
CORINE
Coordinate Information on the Environment
CRF
Common Reporting Format
CS
Country specific
CSC
Carbon stock change
D
Default
DG
Directorate of General
dm
Dry matter content
DOC
Degradable organic carbon
DoCC
Directorate of Climate Change
DOM
Dead Organic Matter
DOCF
Fraction of degradable organic carbon
EAF
Electric arc furnace
EF
Emission factor
EFc
Baseline emission factor for continuously flooded fields without organic
amendments
EHCIP
Environmental Heavy Cost Investment Planning
EMEP
European Monitoring and Evaluation Programme
ENVANIS
Inventory Statistical System for Forests
ERT
Expert Review Team
EU
European Union
F
Fraction of methane
FAO
Food and Agriculture Organization of the United Nations
FAOSTAT
Statistical database of the FAO
FCF
Fossil carbon content
F-gas
Fluorinated gas
FOD
First Order Decay
FracGASF
Fraction of synthetic fertiliser N that volatilises as NH3 and NOx
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Abbreviations and Acronyms
xxiv
FracGASMS
Percent of managed manure nitrogen that volatilises as NH3 and NOx in the
manure management system S
FracGASM
Fraction of applied organic N fertiliser materials and of urine and dung N
deposited by grazing animals that volatilises as NH3 and NOx
FracLEACH-(H)
Fraction of all N added to/mineralised in managed soils in regions where
leaching/runoff occurs that is lost through leaching and runoff
FracLEACHMS
Percent of managed manure nitrogen losses due to runoff and leaching
during solid and liquid storage of manure
Fcomp
Annual amount of total compost N applied to soils
Fsew
Annual amount of total sewage N that is applied to soils
g
gram
GDF
General Directorate of Forestry
GDP
Gross Domestic Product
GE
Gross energy intake
Gg
Gigagram
GHG
Greenhouse gas
GIS
Geographical Information System
GJ
Gigajoule
GL-SL
Grasslands converted to settlement
GW
Gigawatt
GWh
Gigawatt hour
ha
Hectare
HAC
High activity clay
HFC
Hydrofluorocarbon
HWP
Harvested wood product
ICP
International Cooperative Programme
IE
Included elsewhere
IEA
International Energy Agency
IEF
Implied emission factor
IFA
International Fertilizer Association
IPCC
Intergovernmental Panel on Climate Change
IPPU
Industrial processes and product use
IW
Industrial Waste
k
Methane generation rate constant
kha
Kilo hectare
Turkish GHG Inventory Report 1990-2021
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Abbreviations and Acronyms
KISAD
Lime Producers Association
km
kilometer
kt
Kilo tonnes
ktoe
Kilo tonnes of oil equivalent
kW
Kilowatt
kWh
Kilowatt hour
L
Litter
LPG
Liquefied petroleum gas
LRS
LULUCF reporting system
LTO
Landing and take-off
LULUCF
Land Use, Land Use Change and Forestry
MAPEG
General Directorate of Mining and Petroleum Affairs
MC
Monte Carlo
MCF
Methane correction factor
ME
Main engine
MENR
Ministry of Energy and Natural Resources
MgCO3
Magnesium carbonate
MgO
Magnesium oxide
MJ
Megajoule
MMS
Manure Management System(s)
MoAF
Ministry of Agriculture and Forestry
MoEF
Ministry of Environment and Forestry
MoEU
Ministry of Environment and Urbanization
MoEUCC
Ministry of Environment, Urbanization and Climate Change
MoT
Ministry of Trade
MoTI
Ministry of Transport and Infrastructure
MRV
Monitoring, Reporting, Verification
MS
Manure Management System Usage
MSm3
Million standard cubic meter
MSW
Municipal solid waste
Mt
Million tonnes
MW
Megawatt
N
Nitrogen
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Abbreviations and Acronyms
xxvi
N2O
Nitrous oxide
NA
Not applicable
Na2CO3
Sodium carbonate
NaCl
Sodium cloride
NCV
Net calorific value
NE
Not estimated
NES
EU Integrated Environmental Adaptation Strategy
Nex
Annual nitrogen excretion
NF3
Nitrogen trifluoride
NH3
Ammonia
NIR
National Inventory Report
NMVOC
Non-methane volatile organic compounds
NO
Not occurring
NOx
Nitrogen oxides
ODS
Ozone-depleting substances
ODU
Oxidised During Use
OHF
Open hearth furnace
OSP
Official Statistics Programme
OX
Oxidation factor
PFC
Perfluorocarbon
PRODCOM
Industrial Production Statistics Survey
PS
Plant specific
QA/QC
Quality assurance and quality control
R
Root-to-shoot ratio
S
Soil
SEM
Ship Emission Model
SF6
Sulphur hexafluoride
SFOC
Specific Fuel Oil Consumption
SFo
Scaling factor regarding organic amendment type and amount applied
SFp
Scaling factor regarding water regime before the cultivation period
SFs,r
Scaling factor for soil type, rice cultivar, etc., if available
SFw
Scaling factor regarding water regime during the cultivation period
SO2
Sulphur dioxide
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Abbreviations and Acronyms
SOx
Sulphur oxide
SOM
Soil Organic Matter
SWDS
Solid waste disposal sites
t
Tonnes
T
Degrees of treatment utilization
TPLANT
Degree of utilization of modern, centralized wastewater treatment plants
T1
Tier 1
T2
Tier 2
T3
Tier 3
TACCC
Transparency, accuracy, comparability, consistency, and completeness
TADPK
Tobacco and Alcohol Market Regulatory Authority
TurkCimento
Turkish Cement Manufacturer’s Association
TEİAŞ
Turkish Electricity Transmission Company
TJ
Terajoule
TOBB
The Union of Chambers and Commodity Exchanges of Türkiye
TOR
Terms of Reference
TOW
Total organics in wastewater
TPES
Total Primary Energy Supply
TRGM
General Directorate of Agricultural Reform
TTGV
Technology Development Foundation of Türkiye
TUBITAK
Scientific and Technical Research Council of Türkiye
TurkStat
Turkish Statistical Institute
TÜPRAŞ
Turkish Petroleum Refineries Co.
TWh
Terawatt hour
UNECE
United Nations Economic Commission for Europe
UNFCCC
United Nations Framework Convention on Climate Change
USD
United States dollar
Vol
Volume
WF
Waste fractions
WG
Working group
Ym
Methane conversion factor
yr
year
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xxviii
xxviii
Introduction
1. INTRODUCTION
1.1. Background Information on GHG Inventories
The UNFCCC, the Kyoto Protocol and the Paris Agreement were ratified by Türkiye in 2004, 2009 and
2021, respectively. As an Annex I party to Convention, Türkiye is required to develop annual inventories
on emissions and removals of GHG not controlled by the Montreal Protocol using the IPCC Guidelines.
National Greenhouse Gas Inventory of Türkiye was set up in 2006. Inventory covers all sources of
emissions and removals described in 2006 IPCC Guidelines for National Greenhouse Gas Inventories
(2006 IPCC Guidelines). Emissions and removals have been estimated and reported in line with the
2006 IPCC Guidelines. The National GHG Inventory consists of the national inventory report (NIR) and
the common reporting format (CRF) tables in accordance with the UNFCCC reporting guidelines
(24/CP.19). Time series of emissions and removals from 1990 to latest inventory year are covered in
the Common Reporting Format (CRF).
2006 IPCC Guidelines were provided for the following sectors:
Energy
Industrial Processes and Product Use (IPPU)
Agriculture
Land Use, Land Use Change and Forestry (LULUCF)
Waste
The emission inventory includes direct GHGs as CO2, CH4, N2O, HFCs, PFCs, SF6, NF3 and indirect gases
as NOx, CO, NMVOC, SO2 and NH3 emissions originated from energy, IPPU, agriculture, and waste. The
emissions and removals from LULUCF are also included in the inventory. Indirect CO2 emissions that are
among the consequences of the activities of the reporting entity, but available at sources owned or
controlled by another entity do not occur.
In this report, the national GHG emissions and removals from 1990 to 2021, emission and removal
sources, emission factors (EFs), difference between reference and sectoral approach, emission trends,
fluctuations, changes, uncertainty estimations and key source categories were evaluated in detail.
Turkish GHG Inventory Report 1990-2021
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Introduction
1.2. Institutional Arrangements
1.2.1.
Institutional, Legal and Procedural Arrangements
The Turkish national inventory system is featured by centralized governance. Ministry of Environment,
Urbanization and Climate Change (MoEUCC) is the National Focal Point of the UNFCCC, and is
responsible for climate change and air pollution policies and measures. Türkiye established the
Coordination Board on Climate Change (CBCC) in 2001 with the Prime Ministerial Circular No. 2001/2 in
order to determine the policies, measures and activities to be pursued by Türkiye on climate change.
Under the chairmanship of MoEUCC, this board is composed of high level representatives
(Undersecretary and President) from Ministries related to foreign relations, finance, economy, energy,
transport, industry, agriculture, forestry, health, education, TurkStat, and Non-Governmental
Organisations (NGOs) from business sector. The CBCC was restructured in 2013, and renamed as
Coordination Board on Climate Change and Air Management (CBCCAM). The CBCCAM, a public body
created by Prime Minister Circular 2013/11, is competent for taking decisions and measures related to
climate change and air management. The CBCCAM decisions are the first legal means for the national
inventory system.
Türkiye has also taken steps to strengthen its institutional arrangements. In 2021, Türkiye established
a new Directorate of Climate Change (DoCC) under the MoEUCC with Presidential Decree No. 85 on
Amending Certain Presidential Decrees. With the same decree, CBCCAM was replaced by the
Coordination Board on Climate Change and Adaptation (CBCCA), and it was stated that climate change
negotiations would be conducted by a Chief Negotiator (Relevant Deputy Minister). In addition, it was
stated that the Secretariat services of the Coordination Board would be carried out by the CCO. The
Coordination Board is responsible for determining, monitoring, and evaluating plans, policies, strategies,
and actions related to climate change. The Coordination Board, which is an an inter-ministerial
coordination mechanism and chaired by the Minister, consists of twenty-two members, including
TurkStat.
The draft directive on the working procedures and principles of the Coordination Board will be prepared
by the DoCC, and within this scope, sub-working groups will be formed, the details of which will be
determined in the directive. Since studies on this directive are still ongoing, current studies are carried
out with seven working groups (WGs) within the scope of the CBCCAM:
2
GHG Mitigation WG
Climate Change Adverse Effects and Adaptation WG
GHG Emission Inventory WG
Finance WG
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Introduction
Technology Development and Transfer WG
Education, Capacity Building WG
Air Management WG
The national GHG inventory is prepared under the auspices of the "GHG Emission Inventory Working
Group" which was established in 2001 by the former CBCC. TurkStat was formally appointed as single
national responsible authority to coordinate and implement national inventory activities from planning
to management by Decision 2009/1 of the CBCC in 2009. TurkStat is also in charge of annual inventory
submission to the UNFCCC Secretariat and of responding to the ERT recommendations.
Also, the legal basis of the national inventory system is currently provided by the Statistics Law of
Türkiye through the Official Statistics Programme (OSP). The OSP is based on the Statistics Law of
Türkiye No. 5429 and Presidential Order No. 4, and was first prepared in 2007 for a 5-year-period and
updated every 5 years. OSP identifies the basic principles and standards dealing with the production
and dissemination of official statistics and produces reliable, timely, transparent and impartial data
required at national and international level. For all kinds of official statistics, the responsible and related
institutions are defined, data compilation methodology and the publication periodicity/schedule of official
statistics are specified. TurkStat is the responsible institution for the compilation of the national GHG
inventory through the OSP and coordinates the activities of the GHG emission inventory working group
established in the scope of OSP with the same composition as the GHG emission inventory working
group under the CBCCAM.
The GHG national inventory is compiled by GHG Emission Inventory working group under the
coordination of TurkStat.
The institutions included in the working group are:
Turkish Statistical Institute (TurkStat),
Ministry of Energy and Natural Resources (MENR),
Ministry of Transport and Infrastructure (MoTI),
Ministry of Environment, Urbanization and Climate Change (MoEUCC),
Ministry of Agriculture and Forestry (MoAF).
The national inventory arrangements are designed and operated to ensure the TACCC quality objectives
and timeliness of the national GHG inventories. The quality requirements are fulfilled by implementing
consistently inventory quality management procedures.
Responsibilities of the institutions involved in the national GHG inventory are shown in Table 1.1.
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Introduction
Table 1.1 Institutions by responsiblities for national GHG inventory
Sector
Energy
Collection
of AD
CRF category
1 –Energy
(Excluding 1.A.1.a
– Public electricity
and heat
production, and
1.A.3 – Transport)
Selection
of
methods
and EFs
Filling in
CRF
tables
and
GHG
emission preparing
NIR
calculations
Quality
control
MENR,
TurkStat
TurkStat
TurkStat
TurkStat
TurkStat
MENR
MENR
MENR
MENR
MENR
1.A.3 – Transport
MoTI,
TurkStat
MoTI
MoTI
MoTI
MoTI
1.A.1.a – Public
electricity and heat
production
Industrial processes
and
product use
2 – IPPU (except Fgases)
TurkStat
TurkStat
TurkStat
TurkStat
TurkStat
F-gases
MoEUCC
MoEUCC
MoEUCC
MoEUCC
MoEUCC
Agriculture
3 – Agriculture
TurkStat
TurkStat
TurkStat
TurkStat
TurkStat
Land use, land-use
change and forestry
4 – LULUCF
MoAF
MoAF
MoAF
MoAF
MoAF
Waste
5 – Waste
TurkStat
TurkStat
TurkStat
TurkStat
TurkStat
Cross cutting issues
Key category analysis
TurkStat
Uncertainty analysis
National Inventory Official Consideration and Approval
The national GHG inventory is subject to an official consideration and approval procedure before its
submission to the UNFCCC. The national inventory is subject to a two-step official consideration and
approval process. The final version of the NIR and CRF tables is first approved by the TurkStat
Presidency and published in the official TurkStat press release. The latest press release of Greenhouse
Gas Emissions Statistics can be found on https://data.tuik.gov.tr/Bulten/Index?p=Greenhouse-GasEmissions-Statistics-1990-2021-49672
as
scheduled
on
National
Data
Publishing
Calendar.
Subsequently, The MoEUCC as National Focal Point to the UNFCCC provides final checks and approval
of the CRF tables via CRF web application tool as a final step prior to its submission to the UNFCCC.
TurkStat, as the Single National Entity, is responsible for official inventory submission to UNFCCC, and
also responsible for responding to the UNFCCC expert review team (ERT) recommendations on national
4
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Introduction
inventory improvement and ensuring they are incorporated in the current and following NIR(s) in the
broader context of its continuous improvement.
1.2.2.
Overview of Inventory Planning, Preparation and Management
The inventory planning system of Türkiye is conducted in line with quality assurance and quality control
(QA/QC) plan. Planning stage is under the responsibility of GHG Inventory WG. Planning activities
include data collection and processing, selection of EF estimation methodology, compilation of CRF and
NIR, UNFCCC expert review team (ERT) recommendations, documentation and archiving, verification
through time series consistency and cross checks, reporting and publication process.
Every year in the autumn, about October, WG meeting is organized to agree on a work plan and calendar
for the following submission.
Information required for the inventory are mostly covered by OSP. Distribution of work for data
gathering, processing and estimation of emissions are shown in Table 1.1. Emissions originating from
energy, industrial processes and product use, agriculture and waste, and emissions and removals from
LULUCF are calculated at national level annually by using recommended approaches in 2006 IPCC
Guidelines. Fuel combustion emissions other than electricity generation and transport are calculated by
TurkStat via using the energy balance tables of the Ministry of Energy and Natural Resources. Emissions
from industrial processes (excluding F-gases), agriculture, waste and fugitive emissions from coal
mining, oil and gas systems are also calculated by TurkStat. The emissions originating from public
electricity and heat production are calculated on the basis of plant level data by the Ministry of Energy
and Natural Resources; the emissions originating from transportation are calculated by the Ministry of
Transport and Infrastructure. The fluorinated gases are calculated by the Ministry of Environment,
Urbanization and Climate Change. Emissions and removals from land use, land-use change and forestry
are estimated by the Ministry of Agriculture and Forestry.
Every sector expert that performs the emission estimation is responsible for the data entry to CRF
reporter, and preparation of the related section or sub-section of NIR. TurkStat compiles and makes
key source and uncertainty analysis and does final quality checks, and submits the national GHG
inventory to the UNFCCC Secretariat.
TurkStat is also responsible for archiving the GHG inventory. Central archiving is carried out by TurkStat.
EFs, AD, calculation sheets, CRF and NIR outputs, etc. regarding the emission inventory are archived
on TurkStat main server. All inventory related documents are also archived by the relevant Ministries
for the CRF categories under their responsibilities.
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Introduction
1.2.3.
Quality Assurance, Quality Control and Verification
QA/QC and verification procedures are an integral and indispensable part of the national GHG inventory
of Türkiye. The quality of the national inventory system is ensured by the QA/QC system, through the
QA/QC plan adopted by the CBCCAM decision in 2014 and revised and updated in 2017. The QA/QC
plan introduces the structure and purpose of the QA/QC system, endorse the quality objectives. The
main objective of the QA/QC plan is to ensure that the national GHG inventory is prepared in accordance
with the quality objectives: transparency, accuracy, comparability, consistency, completeness (TACCC)
as defined in UNFCCC reporting guidelines (24/CP.19). Türkiye also considers three additional quality
objectives as improvement, sustainability and timeliness.
Improvement: Processes ensure that the inventory represents the best possible estimates of GHG
emissions and removals for all categories, given the current state of scientific knowledge, data
availability and national resources, taking into account information gained and lessons learned from
reporting and review in the latest GHG inventory cycle.
Sustainability: Processes ensure the continuity of the GHG inventory system through institutional
memory by establishing a documentation/archiving system and methodological manuals, as well as a
training for newcomers and periodic refreshment trainings for existing inventory experts.
Timeliness: All of the QA/QC procedures are developed with a view to enabling the timely submission
of the NIR and the accompanying CRF tables to the UNFCCC by 15 April each year. In addition, inventory
inputs, references and materials should be transparently documented and accessible, to enable timely
responses to external requests for information, including formal and informal inventory review
processes.
Together with verification, the implementation of QA/QC procedures are considered integral part of
national inventory preparation and play a pivotal role not only to achieve the quality objectives but also
for continuous reassessing and improving the national inventory where needed.
TurkStat is the designated body for overall implementation of the QA/QC system and for ensuring
coordination of the QA/QC activities.
Quality Control (QC) is a system of routine technical activities to assess and maintain the quality of the
inventory as it is being compiled. It is performed by personnel compiling the inventory. QC activities
include general methods such as accuracy checks on data acquisition and calculations, and the use of
approved standardised procedures for emission and removal calculations, measurements, estimating
uncertainties, archiving information and reporting. QC activities also include technical reviews of
categories, activity data, emission factors, other estimation parameters, and methods.
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Introduction
The data used in the preparation of the national GHG inventory for the IPPU, agriculture, and waste
sectors are obtained from industrial production statistics, agricultural statistics, and waste statistics
databases of TurkStat. TurkStat is producing all its statistics according to the European Statistics Code
of Practice which covers a common quality framework with the European Statistical System. Therefore,
high quality data are used in the inventory.
In Türkiye, in addition to data available from national statistics, some plant-level data are used to
estimate input parameters for emissions calculations. No QC procedures are available for data providers
at the moment. If data are official statistics from TurkStat, then it is ensured that the statistics are
produced in line with the EU code of practice. However, if the data source is not from the official
statistics QC can be performed by the inventory team.
In detail, with regard to QC the following rules and steps apply:
Each institution involved in national inventory development is responsible for its own
general and category specific QC activities,
Both general and category specific QC activities are carried out by sectorial QC experts
within the Institutions, using the ad hoc check lists attached in Annex II (general QC)
and Annex III (category specific) of the QA/QC plan,
Check lists are filled in by sectorial QC experts for the CRF categories under their
responsibility and sent to TurkStat with an official letter,
TurkStat files the letters,
QC sectorial experts make the corrections needs emerging from the QC activities,
TurkStat prepares a summary of the QC results,
An improvement plan is prepared by the national inventory team under TurkStat
coordination.
The QA/QC plan (approved in 2017) including above mentioned annexes can be found at
https://biruni.tuik.gov.tr/yayin/views/visitorPages/english/index.zul.
Criteria for assessing achievement of quality objectives is given below in Table 1.2.
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Introduction
Table 1.2 Criteria for assessing achievement of quality objectives
Data quality
Criteria for assessing achievement of quality objective
objective
Accuracy
Emissions are neither overestimated or underestimated as far as can
be judged,
Uncertainty estimates are provided for AD, EF, and emissions in each
category for the base year, the most recent year, and the trend.
Comparability
Türkiye applies methods from the 2006 IPCC Guidelines, in
accordance with the significance of the category in the country (e.g.,
whether or not it is a key category) and national circumstances.
Completeness
All categories for which methods are provided in the 2006 IPCC
Guidelines are included in the national GHG inventory,
Emissions estimates cover the entire geographic area of Türkiye,
Emissions values or notation keys are provided for each cell in the
CRF tables,
If despite the best efforts, emissions for a category for which
methods are provided in the 2006 IPCC Guidelines cannot be
provided, the situation regarding the lack of reporting is
transparently described in the NIR.
Consistency
Türkiye has applied the same method across the time series for a
given category and can explain the trends observed in the time
series,
If the same method is not used for the entire time series in a
category, Türkiye can explain (and documents in the NIR) why the
selected method(s) ensure time series consistency.
Improvement
The national inventory improvement plan is updated with the
recommendations and encouragements from the relevant review
processes (e.g. UNFCCC) and QA/QC summary reports,
Sustainability
Türkiye implements findings from review processes where feasible.
All inventory related documents (NIR, data sheets, EFs, CRF tables)
are archived annually,
All information on choice of methodology, EFs and parameters,
assumptions used, are documented and updated as needed,
8
All methodological manuals are prepared and updated as needed.
Turkish GHG Inventory Report 1990-2021
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Introduction
Table 1.2 Criteria for assessing achievement of quality objectives (cont’d)
Data quality
Criteria for assessing achievement of quality objective
objective
Timeliness
Inventory is submitted to the UNFCCC by 15 April annually,
Transparency
Türkiye is able to timely respond to questions from the UNFCCC ERT.
Information necessary to reproduce the emissions estimates is either
provided in the annual submission or referenced therein,
The elements required to be included in the NIR per paragraph 50 of
the annex to decision 24/CP.19 are included, in particular clear
descriptions of:
o
All methods selected and models used
o
Values and sources of AD, EFs and other parameters
o
Relevant information on key categories and uncertainties
o
Recalculations are clearly explained
o
Completeness of the inventory
o
Changes in response to the review process
o
Description of the national inventory arrangements.
General QC Procedures
General QC procedures include generic quality checks related to calculations; data processing,
completeness, and documentation that are applicable to all inventory source and sink categories.
General QC procedures are applied routinely to all categories by sector experts using the check lists
attached in Annex II of the QA/QC plan during the acquisition of data and the emissions calculation
procedures and during the compilation of NIR and the CRF tables.
Each sector expert should fill and sign the check list that the necessary QC checks were undertaken.
Each sector expert should carry out immediate corrections of the input data/emissions calculations
where errors are found. If an issue cannot be resolved during the current inventory submission, the
sector experts should include an explanation for aspects still posing problems along with a
recommendation(s) for future work on these issues. Such issues may then be incorporated into the
inventory improvement plan. A copy of the completed checklist is sent to TurkStat and is archived in
TurkStat.
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Introduction
The types of activities and procedures undertaken by sectoral experts include, but are not limited to:
Cross-check descriptions of AD, EFs and other estimation parameters with information
on categories and ensure that these are properly recorded and archived. This step
includes ensuring that definitions and assumptions for the underlying AD match the
definitions of categories used in the GHG inventory. In some cases, data collected from
national statistics may have different coverage than that required for inventory
preparation,
Ensure that the time series of input EF, AD and other parameters are justifiable, and that
any outliers can be explained by national circumstances,
Ensure that proper bibliographic information is available and documented in the archives
for all input parameters,
Cross-check a sample of input data to ensure that there are no transcription errors,
Where AD or EF data are obtained from plant operators, Türkiye plant level data are
compared with previous data and related indicators (kwh/TJ, kwh/m3 CH4) and published
national data,
Check that units are properly labeled for all input data and, for a subset of parameters,
correctly transcribed and applied in the emissions calculation spreadsheets,
Where a parameter is based on expert judgement, identifying information for the expert
(including their affiliation and any relevant expertise) is documented and archived,
Has the sector expert identified where recalculations of previous input data have been
undertaken? Qualitative reasons for, and the quantitative impacts of, these recalculations
should be documented in the NIR.
Category-Specific QC Procedures
Category-specific QC procedures complement general inventory QC procedures and are directed at
specific types of data used in calculating GHG emissions for individual source or sink categories. These
procedures require knowledge of the specific category, the types of data available and the parameters
associated with emissions or removals, and are performed in addition to the general QC checks.
Category specific QC procedures are also applied by sector experts using the check lists attached in
Annex III of the QA/QC plan.
Each sector expert should fill and sign the check list that the necessary QC checks were undertaken,
and summarizes the unsolved issues. A copy of the completed checklist is sent to TurkStat and is
archived in TurkStat.
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Introduction
The types of activities and procedures undertaken by sectoral experts include, but are not limited to:
Assumptions for AD, EFs and other parameters are compared with IPCC values and
significant differences are noted,
National and regional comparability and trends of AD, EF or other assumptions are
checked against alternative data sources,
Conduct of an in-depth review of the background data used to develop a country-specific
EF, including the adequacy of any plant-level measurement programmes upon which the
country-specific EF was developed. Such an in-depth review may also involve an
assessment of any national literature used in support of the development of the countryspecific factor,
Evaluate any peer reviewed literature evaluating national or plant level statistics and
suitability for the use in the GHG inventory,
Hand-checking the accuracy of random calculations,
To the extent possible, are the only hardwired data in the spreadsheets the basic input
data (e.g., AD, EFs and assumptions) with all other spreadsheets using spreadsheet tools
to link and calculate emissions,
Reviewing the time series consistency of emissions calculations for any outliers and
compare whether the values are within the minimum – maximum interval of other
Parties,
Checking a random sampling of conversion factors to ensure proper calculation from
input data to emissions calculations,
Is the IEF calculated reasonable compared with the previous annual submission and with
the 2006 IPCC Guidelines,
Is the time series of the IEF reasonable- are any large changes explainable,
Checking that confidentiality is assured by Statistics Law of Türkiye,
Are emissions estimates (or notation keys) available for all years of the time series for
mandatory categories, from 1990 to the year “t-2” and do the emissions estimates cover
all sources in the category (as determined by cross checks using other publicly available
information),
Identify parameters (e.g., AD, constants) that are common to multiple categories and
confirm that there is consistency in the values used for these parameters in the
emission/removal calculations. This is particularly important when reviewing calculations
for the agriculture and LULUCF sector, as well as when reviewing input data between the
reference and the sectoral approach.
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Introduction
QC Procedures Applied to Compiled NIR and CRF Tables
TurkStat undertakes further quality checks on compiled CRF and NIR. The types of activities and
procedures undertaken include:
CRF tables
Completeness of all cells in the CRF tables with either a value or a notation key,
Appropriateness of notation keys used ,
Where the notation key “NE” or “IE” is used, whether an appropriate description is
included in CRF table 9 to indicate why data are not reported (in the case of “NE”) or
where data are reported (in case of “IE”),
Where emissions data are reported as confidential, it is ensured that emissions are
included elsewhere (properly aggregated to assure confidentiality of information) and,
therefore, included in national totals,
Check whether appropriate tiers are used for key categories, in accordance with the
decision trees in the 2006 IPCC Guidelines. Where appropriate tiers are not used, is an
appropriate discussion included in the NIR to document the national circumstances
surrounding the methodological choice?
Review of documentation boxes of the CRF tables for appropriate content and language.
All tables, figures and text have been updated to reflect the latest annual data,
Does the description of trends match the trends seen taking into account the latest year,
NIR
and any recalculations of earlier years’ data,
Check the introductory chapters and annex to make sure that the data contained therein
match the latest inventory data,
Have all recalculations identified been documented in the NIR and the impacts of the
recalculation described?
Assessment of completeness of the category described in the NIR,
Consistent use of units in the NIR and the CRF tables,
A general check of the NIR should be done for consistency,
All references should be included in the NIR and the same reference should be referred
to consistently across chapters,
Ensure that all web links are active and direct the readers to the appropriate content.
After inventory submission to UNFCCC, ensures that all inventory related materials were
archived by inventory sectoral experts.
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Introduction
In 2019 submission, emissions from energy, IPPU and agriculture sectors were calculated on SAS
(Statistical Analysis System) and it was double checked by the calculations on the Excel sheets by two
different experts and any finding errors were corrected.
Quality Assurance
Quality Assurance (QA) is a planned system of review procedures conducted by personnel not directly
involved in the inventory compilation/development process. Reviews, preferably by independent third
parties, are performed upon a completed inventory following the implementation of QC procedures.
Reviews verify that measurable objectives (data quality objectives) were met, ensure that the inventory
represents the best possible estimates of emissions and removals given the current state of scientific
knowledge and data availability, and support the effectiveness of the QC programme.
Due to the comprehensive and costly nature of QA activities, these procedures are only applied for
selected categories and selected years, and generally only for key categories.
Our approach to QA is to prioritize:
The categories that have high uncertainty,
The categories that are recalculated,
The categories that were included in the improvement plan.
In Türkiye, QA activities are conducted by experts in the scope of European Union (EU) funded Projects.
For this purpose, first, in the scope of EU funded Upgrading the Statistical System of Türkiye project,
external experts from EU countries were invited to review Turkish GHG Inventory for all categories
before in-country review in 2014. Some improvements has been achieved based on review outputs of
the EU inventory experts.
Also the EU funded Project named as Technical Assistance for Support to Mechanisms for Monitoring
Türkiye’s GHG Emissions, project period was January 2015 - April 2017, aimed to strengthen existing
capacities in Türkiye and assist the country to:
Fully implement a monitoring mechanism of GHG emissions in Türkiye, in line with the
EU Monitoring Mechanism Regulation 525/2013 repealing Decision 280/2004/EC, and
Better fulfill its reporting requirements to the UNFCCC, including national GHG
inventories, National Communications and Biennial Reports.
Under the technical assistances of experts from project team national GHG inventory was reviewed and
improved through workshops, mentor style trainings, and meetings organized.
Turkish GHG Inventory Report 1990-2021
13 13
Introduction
For the period 2017-2019, TurkStat was responsible for implementing an investment project with the
objective of improving the GHG Inventory. Under this project, a QA work was conducted for the
agriculture sector in 2017. Likewise, another QA work was conducted for the energy sector in 2018.
“Technical Assistance for New Era for Statistics Programme” which is co-funded by the European Union
and the Republic of Türkiye, has been started since March 2019. Within the scope of this project, under
sub-activity “National Greenhouse Gas Inventory”, the experts from CITEPA – Technical Reference
Center for Air Pollution and Climate Change – provided QA works for the energy, IPPU, agriculture and
waste sectors of the Turkish GHG Inventory between December 2019 and February 2020.
In addition, GHG inventory submission of Türkiye is subject to review by an international team of experts
on an annual basis in accordance with decision 13/CP.20. During the review week, Türkiye ensures that
all institutions, organizations and responsible sector experts are available to provide necessary
information and supporting documentation to the review team in a timely manner. The Expert Review
Team (ERT) then develops an annual review report based on the findings of the review. These annual
review reports are considered as supplementary to the QA procedures undertaken by experts in Türkiye.
Findings in the annual review reports are considered feedback for improvement of the GHG inventory,
and as such are included in inventory improvement plan of Türkiye.
Verification
Verification activities typically include comparing inventory estimates with independent estimates to
either confirm the reasonableness of the inventory estimates or identify major discrepancies. Verification
activities may be directed at specific categories or the inventory as a whole, and their application will
depend on the availability of independent estimation methodologies that can be used for comparison.
Each institution involved in national inventory development is responsible for its own verification
activities. Sectorial experts within the Institution carry out the activities.
In Türkiye, some level of verification happens on an annual basis, as Türkiye estimates and reports CO2
emissions from fossil fuel combustion based on both the reference approach and the sectoral approach.
Differences in the emissions estimated using these two approaches are described in the NIR.
The national GHG emissions in the energy sector are estimated by using fuel consumption data taken
from energy balance tables produced by the MENR. These data are compared with International Energy
Agency (IEA) data. Inconsistencies between two data sets are identified and the reasons for these
inconsistencies are investigated.
14
Turkish GHG Inventory Report 1990-2021
14
Introduction
Also lower tier IPCC methods are applied for comparison in especially energy sector. Emissions
calculated and reported on the basis of higher tiers (Tier 2 or Tier 3) are compared with emissions
calculated by Tier 1 method.
In current situation, in Türkiye, there is no other emission calculation to compare whole inventory or
sub-sectors. However, Regulation on the Monitoring of Greenhouse Gases has been came into force
since 2012. In the scope of that Regulation, companies report their verified GHG emissions to the
MoEUCC from 2017 onwards. GHG emissions from most of the IPCC categories are compared with those
emissions reported under the MRV Regulation.
Documentation and Archiving
Regarding documentation and archiving, all sectoral experts archive all inputs used in the inventory
process, outputs, selected EFs, work files, e-mails and official letters on their computer, on a network
server with restricted access or on an external drive as softcopy or as hardcopy. Archiving is done
according to Regulation on State Archive Services. Sectoral experts are responsible for archiving in their
own institutions.
Central archiving is carried out by TurkStat. EFs, AD, calculation tables, CRF and NIR outputs, etc.
regarding the emission inventory are stored on TurkStat main server. Sectoral experts transfer EFs, AD
and calculation tables used in emission calculations to TurkStat within 6 weeks following the date of
submission of the Annual Inventory to UNFCCC Secretariat.
1.3. Brief Description of the Process of Inventory Preparation
Inventory preparation of Türkiye starts with inventory planning which covers recalculations,
methodological improvements and refinements according to quality management and improvement
plans based on learning from previous inventory cycle, UNFCCC review reports and collaborations with
government institutions. Reviewing the calculation methods are finalized by the end of October and the
data collection process is completed by the end of November. After that, emission estimates and QC
checks are done by the end of January. Data entry into the CRF Reporter is done by mid-February. NIR
text and tables are then prepared according to UNFCCC guidelines. The inventory process also involves
key category assessment, recalculations, uncertainty assessment, documentation and archiving. Main
steps in the annual inventory preparation process are summarized below in Table 1.3 with starting and
ending dates.
Turkish GHG Inventory Report 1990-2021
15 15
Introduction
Table 1.3 Time schedule for preparation of the “t-2” annual inventory submission
Activity
16
Start date
Deadline
1.
Inventory planning by GHG Inventory WG
(Creating Inventory Improvement Plan, recalculation, etc.)
01.05.XX-1
30.09.XX-1
2
Reviewing emission calculation methods, EFs, AD sources,
etc. by GHG Inventory WG
15.09.XX-1
31.10.XX-1
3.
Collection of AD and QC of the data by the institutions
involved
01.10.XX-1
30.11.XX-1
4.
Calculation of all emissions from electricity production,
transportation, F-gas, emissions and removals from LULUCF
by the related institutions, and transfer to TurkStat
30.11.XX-1
31.01.XX
5.
Calculation of emissions under the responsibility of TurkStat
30.11.XX-1
31.01.XX
6.
QC of the calculated emissions
30.11.XX-1
31.01.XX
7.
AD and emission entry into the CRF Reporter by sectoral
experts
31.01.XX
15.02.XX
8.
Performing key source, trend and uncertainty analysis by
TurkStat
15.02.XX
01.03.XX
9.
Preparation of National Inventory Report by the institutions
involved and compilation by TurkStat
15.02.XX
15.03.XX
10.
Release of the GHG Emissions Statistics as press release on
TurkStat webpage
15.03.XX
31.03.XX
11.
Sending National GHG Inventory for approval by Inventory
Focal Point (National Inventory Compiler)
01.04.XX
10.04.XX
12.
Approval of National GHG Inventory by National Focal Point
01.04.XX
10.04.XX
13.
Reporting of Inventory to UNFCCC Secretariat by TurkStat
10.04.XX
15.04.XX
14.
Documentation and archiving processes
15.04.XX
15.05.XX
Turkish GHG Inventory Report 1990-2021
16
Introduction
1.4. Brief General Description of Methodologies and Data Sources
The National GHGs are calculated by using 2006 IPCC Guidelines. CO2 emissions from energy are
calculated by using Tier 2 (T2) approach except for biomass and other fossil fuels. CH4 and N2O
emissions from all subcategories of energy excepting 1A1a category are calculated by using Tier 1 (T1).
Technology specific EFs are used for CH4 and N2O emissions from 1A1a category. For the emissions
from coke production, due to plant specific data are gathered, Tier 3 (T3) methodology are used.
For industrial process and product use, T2 methodology was used for the CO2 emissions from cement
production, ammonia (NH3) production. T3 methodology is used for CO2 emissions from iron and steel
production and GHG emissions from aluminum production. For the emissions from rest of the IPPU
categories, T1 methodology was used.
For agriculture sector; T2 is used for emissions from cattle enteric fermentation. For the other categories
T1 methodology was used.
For LULUCF; T2 methodology was used for the emissions/removals from forestland, cropland, grassland
and emissions from harvested wood product (HWP). For the other categories T1 methodology was used.
In waste sector; for the CO2 emissions from open burning of waste, which is only CO2 emission source
for waste sector is calculated by using T2 method. For CH4 emissions from solid waste disposal and
wastewater treatment and discharge, T2 methodology was used while T1 was used for the other nonkey categories. For N2O emissions, T1 methodology was used for all relevant categories.
All tier methodologies are summarized on sector basis in below Table 1.4.
Turkish GHG Inventory Report 1990-2021
17 17
Introduction
Table 1.4 Summary for methods and emission factors used, 2021
CO2
Method Emission
applied
factor
CH4
Method Emission
applied
factor
N2O
Method Emission
applied
factor
1. Energy
T1,T2,T3
CS,D,PS
T1,T2,T3
D,PS
T1,T2,T3
D,PS
A. Fuel combustion
T1,T2,T3
CS,D,PS
T1,T2,T3
D,PS
T1,T2,T3
D,PS
1. Energy industries
T2,T3
CS,D,PS
T2,T3
D,PS
T2,T3
D,PS
2. Manufacturing industries and construction
T1,T2
CS,D
T1
D
T1
D
3. Transport
T1,T2
CS,D
T1,T2
D
T1,T2
D
4. Other sectors
T1,T2
CS,D
T1
D
T1
D
Greenhouse Gas Source and Sink
Categories
B. Fugitive emissions from fuels
T1
D
T1
D
T1
D
1. Solid fuels
NE
NE
T1
D
NE
NE
2. Oil and natural gas
T1
D
T1
D
T1
D
T1
D
T1,T2,T3
CS,D,PS
T1
D
T1
D
T1,T2
CS,D
C. CO2 transport and storage
2. Industrial processes and product use
A. Mineral industry
B. Chemical industry
T1,T2
CS,D
NE
NE
T1
D
T1,T2,T3
CS,D,PS
T1
D
NE
NE
T1
D
NE
NE
NE
NE
G. Other product manufacture and use
NA
NA
NA
NA
NA
NA
H. Other
NA
NA
NA
NA
NA
NA
3. Agriculture
T1
D
T1,T2
CS,D
T1
D
T1,T2
CS,D
B. Manure management
T1
D
T1
D
C. Rice cultivation
T1
D
T1
D
NO
NO
NO
NO
T1
D
T1
D
C. Metal industry
D. Non-energy products from fuels
and solvent use
E. Electronic industry
F. Product uses as ODS substitutes
A. Enteric fermentation
D. Agricultural soils
E. Prescribed burning of savannas
F. Field burning of agricultural residues
G. Liming
NE
NE
H. Urea application
T1
D
I. Other carbon-containing fertilizers
NO
NO
J. Other
NO
NO
NO
NO
NO
NO
T1,T2,T3
CS,D
T1
D
T1
D
A. Forest land
T2,T3
CS,D
T1
D
T1
D
B. Cropland
T1,T2
CS,D
NE
NE
T1
D
C. Grassland
T1,T2
CS,D
NE
NE
T1
D
D. Wetlands
T1,T2
CS,D
NE
NE
T1
D
T1
D
NE
NE
NE
NE
T1
D
NO
NO
NO
NO
T2,T3
CS,D
4. Land use, land-use change and forestry
E. Settlements
F. Other land
G. Harvested wood products
H. Other
NO
NO
NO
NO
NO
NO
5. Waste
T2
CS,D
T1,T2
CS,D
T1
D
A. Solid waste disposal
NA
NA
T2
CS,D
T1
D
T1
D
T2
CS,D
T1
D
T1
D
T2
CS
T1
D
B. Biological treatment of solid waste
C. Incineration and open burning of waste
D. Waste water treatment and discharge
Table 1.5 provides an overview for inventory data sources by sectors;
18
18
Turkish GHG Inventory Report 1990-2021
Introduction
Table 1.5 Activity data sources for GHG inventory
Sector
Category
Activity data source
Energy – 1
(excluding 1.A.1 – Energy
industry and 1.A.3 –
Transportation)
Energy
Directorate of Energy Efficiency and Environment and
PETKIM - waste incineration data
Public electricity and heat
production – 1.A.1.a
MENR - Facility base electricity and heat production
statistics
Petroleum Refining– 1.A.1.b
TÜPRAŞ- STAR Rafineri emission data
Manufacture of solid fuels and
other energy industries– 1.A.1.c
Integrated iron and steel plants- fuel consumption for
coke production
Transportation – 1.A.3
TurkStat-road vehicle fleet and vehicle-km travelled,
MENR, MAPEG - fuel consumption by transport mode
MoTI/DG of State Airports Authority - air traffic data
2.A.1.Cement
Turkish Cement Manufacturer’s Association- production
data, Producers- production data and EF, TurkStatIndustrial production statistics
2.A.2. Lime
Turkish Lime Association- production data,
Producers- production data and EF,
Steel plants- production data, TurkStat- Industrial
production statistics
2.A.3 Glass
Producers- glass production data and parameters
2.A.4 Other process uses of
carbonates
2.B.1. Ammonia Prod.
Industrial
Process and
Product Use
MENR Energy balance sheet-sectoral fuel consumption
data (for sectoral approach) and fuel supply data (for
reference approach)
Turkish Ceramics Federation- production data,
Producers- production and raw material consumption
data, TurkStat- Industrial production and foreign trade
statistics
Producers- production and fuel consumption data
BOTAS (Petroleum Pipeline Corporation)- Carbon content
of natural gas, TurkStat- Industrial production statistics
2.B.2 Nitric Acid Prod.
Producers- production data and technology
TurkStat- Industrial production statistics
2.B.5. Carbide Prod.
TurkStat-Foreign trade statistics and industrial production
statistics
2.B.7. Soda ash prod.
Producers- production and raw material data
2.B.8. Petrochemical and
carbon black prod.
Producers- production data
2.C.2. Iron and Steel Prod.
Producers- production data and other parameters
Turkish Steel Producers Association- production data
2.C.2. Ferroalloy prod.
Producers- production data
TurkStat- Industrial production statistics
2.C.3 Aluminium Prod.
Producer- production data and other parameters
2.C.4 Magnesium Prod.
Producer- production data and other parameters
2.C.5. Lead Prod.
TurkStat- MoEUCC recycled waste batteries data
2.C.6. Zinc Prod.
Producers- production data, TurkStat- Industrial
production statistics
2.D.1. Lubricant Use
MENR- consumption data
2.D.2. Paraffin wax use
MENR- consumption data
Turkish GHG Inventory Report 1990-2021
19 19
Introduction
Table 1.5 Activity data sources for GHG inventory (cont’d.)
Sector
Category
2.E. Electronic industry
2.F. Product uses as
substitutes for ODS
2.G.1. Electrical equipment
Agriculture
Agriculture – 3
Activity data source
TurkStat - trade statistics
Ministry of Trade (MoT) - trade statistics
MoT - trade statistics - Turkish Electricity Transmission
Corporation (TEİAŞ)
TurkStat Livestock population
Crop production data
Waste disposal and treatment statistics
General Directorate of Meteorology - Temperature data
MoAF- Inorganic N Fertilizers application data, urea
application data
Land Use,
Land Use
Change and
Forestry
MoAF (General Directorate of Forestry) Landsat Satellite Images
Copernicus HRL for Forest (Sentinel)
Forestry Statistics
The annual commercial cutting and fuel wood data
The annual forest fire information
The annual illegal cutting and wood gathering information
LULUCF – 4
MoAF (General Directorate of Agricultural Reform) Landsat Satellite Images
CORINE land use maps
LPIS
General Directorate of State Hydraulic Works - the data of
dam constructions
MoAF (General Directorate of Agricultural Research and
Policies) - Soil Information System
Waste
Waste – 5
TurkStat Waste disposal and treatment statistics
Wastewater discharge and treatment statistics
GDP
Population estimations and projections
MoEUCC, TurkStat - waste composition data
Composting plants - amount of composted waste
Methane recovery facilities - amount of methane recovered
from landfills and wastewater treatment plants
1.5. Brief Description of Key Source Categories
The 2006 IPCC Guidelines for National GHG Inventories (2006 IPCC Guidelines) recommend as good
practice the identification of key categories of emissions and removals. The intent is to help inventory
agencies prioritize their efforts to improve overall estimates. A key category is defined as “one that is
prioritized within the national inventory system because its estimate has a significant influence on a
country’s total inventory of GHG in terms of the absolute level of emissions and removals, the trend in
emissions and removals, or uncertainty in emissions and removals” (2006 IPCC Guidelines); this term is
used in reference to both source and sink categories.
20
Turkish GHG Inventory Report 1990-2021
20
Introduction
For the 1990-2021 GHG inventory, level and trend key category assessments were performed according
to the recommended IPCC approach found in Volume 1, Section 4.3.1, of the 2006 IPCC Guidelines.
The details of key category analysis are given in Annex 1.
Based on the key category with and without LULUCF, the followings are determined as key source in
2021.
Table 1.6 Key categories for GHG inventory, 2021
Criteria used
for key source
identification
Gas
CO2
L
T
1.A.1 Fuel combustion - Energy Industries - Liquid Fuels
X
X
Key
category
exc.
LULUCF
X
1.A.1 Fuel combustion - Energy Industries - Solid Fuels
CO2
X
X
X
X
1.A.1 Fuel combustion - Energy Industries - Gaseous Fuels
1.A.2 Fuel combustion - Manufacturing Industries and Construction
- Liquid Fuels
1.A.2 Fuel combustion - Manufacturing Industries and Construction
- Solid Fuels
1.A.2 Fuel combustion - Manufacturing Industries and Construction
- Gaseous Fuels
1.A.2 Fuel combustion - Manufacturing Industries and Construction
- Other Fossil Fuels
1.A.3.a Domestic Aviation
CO2
X
X
X
X
CO2
X
X
X
X
CO2
X
X
X
X
CO2
X
X
X
X
X
X
CO2
X
X
X
1.A.3.b Road Transportation
CO2
X
X
X
X
1.A.4 Other Sectors - Liquid Fuels
CO2
X
X
X
X
1.A.4 Other Sectors - Solid Fuels
CO2
X
X
X
X
1.A.4 Other Sectors - Gaseous Fuels
CO2
X
X
X
X
1.A.4 Other Sectors - Biomass
CO2
X
X
X
1.B.1 Fugitive emissions from Solid Fuels
1.B.2.b Fugitive emissions from Fuels - Oil and Natural Gas Natural Gas
2.A.1 Cement Production
CH4
X
X
X
X
X
CO2
X
X
X
X
2.A.2 Lime Production
CO2
X
X
X
X
2.A.4 Other Process Uses of Carbonates
CO2
X
X
X
2.C.1 Iron and Steel Production
CO2
X
X
X
X
2.F.6 Other Applications
F-gases
X
X
X
X
3.A Enteric Fermentation
CH4
X
X
X
X
3.B Manure Management
CH4
X
X
X
X
3.B Manure Management
N 2O
X
X
X
X
3.D.1 Direct N2O Emissions From Managed Soils
N 2O
X
X
X
X
3.D.2 Indirect N2O Emissions From Managed Soils
N 2O
X
X
X
X
4.A.1 Forest Land Remaining Forest Land
CO2
X
X
X
4.G Harvested Wood Products
CO2
X
X
X
4(V) Biomass Burning
CO2
X
X
X
5.A Solid Waste Disposal
CH4
X
X
X
X
5.D Wastewater Treatment and Discharge
CH4
X
X
X
X
5.D Wastewater Treatment and Discharge
N 2O
Key Categories of Emissions and Removals
CO2
X
CH4
X
Key
category
inc.
LULUCF
X
X
Note: L: Level assessment; T: Trend assessment
Turkish GHG Inventory Report 1990-2021
21 21
Introduction
Based on the results of the key category analysis, it is tried to increase the Tiers in emissions/removals
estimation. However due to resource restrictions, Tier 1 approaches have to be used for some key
categories, such as CH4 emissions from other sectors, solid fuels and oil and gas systems in energy
sectors, CH4 emissions from manure management, N2O emissions from agricultural soils and wastewater
treatment and discharge. Efforts to increase the tiers for all key categories is continuing.
1.6. General Uncertainty Evaluation
For calculation of uncertainty, error propagation method (Approach 1) for combining uncertainties, as
outlined in Volume 1 (Chapter 3) of the 2006 IPCC Guidelines for National GHG Inventories (2006 IPCC
Guidelines) is used. Also for some key categories and non-key categories Monte Carlo Simulation
(Approach 2) is implemented. Please refer to Annex 2 for more detailed explanations and distributions
of applied techniques. However, general combined uncertainty is estimated with Approach 1 due to the
lack of calculated categories.
The general procedures for uncertainty analysis based on the expert judgment are as follows;
Uncertainties of each activity are allocated by using EFs and AD uncertainties,
Emissions are estimated for each (CO2, CH4, N2O, HFC, PFC and SF6) gases,
The uncertainties for industrial processes data are estimated by TurkStat,
The uncertainties of F-gases data are estimated by MoEUCC,
The uncertainties of agricultural activities data are estimated by TurkStat,
The uncertainties of waste data are estimated by TurkStat,
The uncertainties for sectoral energy usage data are estimated by MENR,
The uncertainties of transport data are estimated by MoTI,
The uncertainties of forestry and other land use data are estimated by MoAF.
Quantitative estimates of the uncertainties in the emissions are calculated using direct sectoral expert
judgement based on the data collection matters considering completeness, accuracy and other
parameters. The overall combined uncertainty with LULUCF is 8.0%, and 5.5% without LULUCF by
means of Approach 1.
22
Turkish GHG Inventory Report 1990-2021
22
Introduction
1.7. General Assessment of Completeness
Completeness by source and sink categories: The inventory is considered to be largely complete with
only a few minor sources not estimated, due to either a lack of available information. These sources are
considered to be insignificant, when compared with the inventory as a whole. The categories given in
Annex 5 were not estimated due to insufficient data or methodology.
Completeness by geographical coverage: Geographical coverage of the inventory is complete. It includes
all territories of Türkiye.
A complete set of CRF tables are provided for all years and estimates are calculated in a consistent
manner.
Complete list of source/sink categories reported as “NE” and “IE” is given in Annex 5.
Turkish GHG Inventory Report 1990-2021
23 23
1
Trends in Greenhouse Gas Emissions
2. TRENDS IN GREENHOUSE GAS EMISSIONS
2.1. Emission Trends for Aggregated Greenhouse Gas Emissions
Total GHG emissions, excluding the LULUCF sector, were 564.4 Mt CO2 eq. in 2021. This represents an
increase of 344.9 Mt CO2 eq. (157.1%) on total emissions in 1990 and an increase of 40.4 Mt CO2 eq.
(7.7%) in 2020.
Net GHG emissions, including the LULUCF sector, were 517.2 Mt CO2 eq. in 2021. This represents an
increase of 364.2 Mt CO2 eq. (238%) on net emissions in 1990 and an increase of 50.2 Mt CO2 eq.
(10.7%) in 2020.
Figure 2.1 presents total and net GHG emissions from 1990 to 2021.
Figure 2.1 Emission trend for aggregated GHG emissions, 1990-2021
600
(Mt CO2 eq.)
500
400
300
200
Total emissions (excluding LULUCF)
24
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
100
Net emissions (including LULUCF)
Turkish GHG Inventory Report 1990-2021
24
Trends in Greenhouse Gas Emissions
There is a positive trend in the total emissions over the period 1990-2021. However, economic
recessions had directly caused reductions in the total GHG emissions in 1994, 1999, 2001, 2008, 2018
and 2019. In these years, total emissions are decreased by 2.7%, 0.9%, 6.4%, 0.8%, 1% and 2.7% as
compared to the previous year’s emissions respectively. Although there is no economic recession, total
emissions are slightly decreased by 1.8% in 2013.
The fluctuations in the emission trends are mainly due to the trends in economic activities. Therefore,
GDP can be thought as the main driver of the GHG emissions in Türkiye. It has nearly the same pattern
as total GHG emissions for the period 1990-2021. It reached 807 billion USD in 2021 from 149 billion
USD in 1990. While the Real GDP figures of the World Bank until 2019 were used for comparison, the
official GDP ($) figures of TurkStat started to be used in 2020.
Population is another driver of the emission trends in national inventories. The mid-year population of
Türkiye increased about 52.7% for the period 1990-2021. While it was 55.1 million in 1990, it reached
84.1 million in 2021. Accordingly, CO2 eq. emissions per capita are 6.7 kt in 2021, while it was 4.0 kt in
1990.
Figure 2.2 shows trends on various statistics related to greenhouse gas emissions normalized to 1990
as a baseline year. These values represent the relative change (in comparison with base year for every
year) in each statistic since 1990. The direction of the emissions per $ of GDP trend started to change
after 2002, when GDP (in current price) began to peak, while population and emissions per capita
continued to increase slightly.
Figure 2.2 Trends in emissions per capita and dollar of GDP relative to 1990
800
Index vs. 1990
700
600
500
400
300
200
GDP in current price
Population
Emissions per capita
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
100
Emissions per $GDP
Source: https://data.tuik.gov.tr/Bulten/Index?p=Yillik-Gayrisafi-Yurt-Ici-Hasila-2021-45834
Turkish GHG Inventory Report 1990-2021
25 25
1
Trends in Greenhouse Gas Emissions
Table 2.1 gives summary data for GHG emissions for some selected years between 1990 and 2021.
Table 2.1 Aggregated GHG emissions by sectors
(Mt CO2 eq.)
Sector
1990
2000
2010
2015
2016
2017
2018
2019
2020
2021
Total
(exc. LULUCF)
219.53
298.92
398.79
474.97
501.11
528.57
523.11
508.73
523.99
564.39
Energy
139.54
216.04
287.88
341.99
361.75
382.41
373.40
365.58
366.57
402.48
IPPU
22.86
26.20
49.06
59.72
63.75
66.63
67.74
59.00
67.96
75.14
Agriculture
46.05
42.33
44.41
56.13
58.89
63.26
65.34
68.02
73.15
72.08
Waste
11.08
14.34
17.45
17.12
16.71
16.26
16.63
16.12
16.31
14.70
-66.51
-68.05
-71.88
-72.81
-73.11
-74.96
-69.75
-62.72
-56.95
-47.15
-
36.16
81.66
116.36
128.27
140.78
138.29
131.74
138.69
157.09
LULUCF
Comp. to 1990 (%)
In overall 2021 emissions excluding LULUCF, the energy sector had the largest portion with 71.3%. The
energy sector was followed by the sectors of IPPU with 13.3%, agriculture with 12.8%, and waste with
2.6%. In Figure 2.3 fluctuations of whole sectors can be seen for the entire period starting with 1990.
Figure 2.3 GHG Emissions and sinks by sector, 1990-2021
26
Turkish GHG Inventory Report 1990-2021
26
Trends in Greenhouse Gas Emissions
2.2. Emission Trends by Gas
Total CO2 emissions (excluding LULUCF) increased by 198.6% from 1990 to 2021. CH4 emissions
(excluding LULUCF) increased by 50.7% and N2O emissions (excluding LULUCF) increased by 61.5%.
Total CO2 emissions (including LULUCF) increased by 375.8% from 1990 to 2021. There are no
significant changes in other GHGs by taking into account the LULUCF sector. CH4 emissions (including
LULUCF) increased by 52% and N2O emissions (including LULUCF) increased by 63.5%.
As shown in Figure 2.4, the CO2 emissions show a general increasing trend, while N2O
and CH4 emissions are not changing considerably.
Figure 2.4 Emission trend of main GHGs, 1990-2021
500
450
(Mt CO2 eq.)
400
350
300
250
200
150
100
CO₂
CH₄
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
50
N₂O
Turkish GHG Inventory Report 1990-2021
27 27
1
Trends in Greenhouse Gas Emissions
Table 2.2 gives summary data for GHG emissions by gas for some selected years between 1990 and
2021.
Table 2.2 Aggregated GHG emissions excluding LULUCF
(Mt CO2 eq.)
Gas
1990
2000
2010
2015
2016
2017
2018
2019
2020
2021
Total
219.53
298.92
398.79
474.97
501.11
528.57
523.11
508.73
523.99
564.39
CO2
151.61
229.94
316.19
384.93
405.95
430.90
422.06
402.69
412.93
452.70
CH4
42.49
43.67
51.65
52.78
55.58
56.82
60.41
63.22
63.89
64.02
N2O
24.95
24.77
27.45
32.26
34.35
35.44
35.46
36.97
40.49
40.31
HFCs
NO
0.12
3.05
4.82
5.11
5.26
5.04
5.68
6.50
7.21
PFCs
0.47
0.41
0.39
0.09
0.04
0.03
0.01
0.02
0.01
0.01
NO
0.01
0.07
0.08
0.08
0.12
0.13
0.16
0.17
0.14
SF6
Figure 2.5 shows trends in the index for each year compared to previous year by gas for the 1990-2021
period. 1990 is assumed as “100” for indexing. All gases are showing an increasing trend compared to
1990 and also to previous years in general. The sharpest trend belongs to F-gases since they increased
by 1457% in proportion to 1990.
Figure 2.5 Trends in emissions by gas relative to 1990
(1990=100)
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
1600
1500
1400
1300
1200
1100
1000
900
800
700
600
500
400
300
200
100
0
CO₂
28
CH₄
N₂O
F Gases
Turkish GHG Inventory Report 1990-2021
Total
28
Trends in Greenhouse Gas Emissions
Carbon Dioxide (CO2)
In 2021, CO2 emissions are 452.7 Mt (excluding LULUCF), 9.6% above the 2020 level and 198.6% above
the 1990 level. Figure 2.6 illustrates the trend in CO2 emissions. It is seen that CO2 emissions are
dominated by the energy sector which is the main driver for the rising trend in emissions. This situation
is caused by the growing industrial sector and population in Türkiye. In 2021 excluding the LULUCF, the
energy sector is responsible for 85.2% of the total CO2 emissions while IPPU is responsible for 14.5%.
The agriculture and waste sectors do not cause a significant amount of CO2 emission.
Figure 2.6 CO2 emissions by sector, 1990-2021
Energy
IPPU
Agriculture
LULUCF
Turkish GHG Inventory Report 1990-2021
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
- 50
- 100
- 150
(Mt)
1990
500
450
400
350
300
250
200
150
100
50
Waste
29 29
1
Trends in Greenhouse Gas Emissions
Methane (CH4)
The trend in emissions of CH4 is broken down by source in Figure 2.7, CH4 is the second most significant
GHG after CO2 in Türkiye since 1990. Emissions of CH4 have increased by 50.7% since the base year
1990 and have increased by 0.2% compared to 2020. In 2021, CH4 emissions were 2 561 kt excluding
the LULUCF.
The major sectors of CH4 are enteric fermentation from agriculture, solid waste disposal from the waste
sector and fugitive emissions in the energy sector. Emissions from IPPU and LULUCF are not significant
sources of CH4 in comparison with other sectors. Generally, all sectors have risen since 1990.
Figure 2.7 CH4 emissions by sector, 1990-2021
(Mt)
3 000
2 500
2 000
1 500
1 000
Energy
30
IPPU
Agriculture
LULUCF
Turkish GHG Inventory Report 1990-2021
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
500
Waste
30
Trends in Greenhouse Gas Emissions
Nitrous Oxide (N2O)
In 2021, N2O emissions are 135 kt without LULUCF and it slightly decreased from the level of 2020 (0.6
kt) but 61.5% above the 1990 level. As it is seen from Figure 2.8, the agriculture sector is the main
contributor of N2O emissions in all the years and the share is 78% in 2021. The energy sector is
responsible for 11.1% and waste sector is responsible for 5.9% of all N2O emissions. IPPU has a minor
share of the N2O emissions by 5%.
Figure 2.8 N2O emissions by sector, 1990-2021
160
(kt)
140
120
100
80
60
40
Energy
IPPU
Agriculture
LULUCF
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
20
Waste
Fluorinated Gases (HFCs, PFCs, SF6)
The F-gases are only caused by the IPPU sector. In 2021, 7 361 kt CO2 eq. of F-gases released to the
atmosphere. It is seen from Table 2.3 that total F-gas emissions increased by 1457% since 1990. The
main contributor to total F-gas emissions is HFCs emissions and it is mainly the results of efforts to
phase out CFCs and other ODS under the provisions of the Montreal Protocol. Additionally increasing
demand of refrigerant and air conditioning sector are also responsible for the rising trend of HFCs
emissions in Türkiye.
Emission values of PFCs, CF4 and C2F6 decreased after 2015, compared to previous years due to the
change of aluminium production system from Søderberg to Prebaked smelted in 2015. There has been
a decreasing trend in the number of anode effects after switching to prebaked smelter system.
Turkish GHG Inventory Report 1990-2021
31 31
1
Trends in Greenhouse Gas Emissions
Table 2.3 Fluorinated gases emissions by sector, 1990-2021
(kt CO2 eq.)
32
Year
HFCs
PFCs
SF6
1990
NO
472.80
NO
1991
NO
556.99
NO
1992
NO
519.75
NO
1993
NO
519.04
NO
1994
1995
NO
NO
463.88
409.33
NO
NO
1996
NO
413.23
10.05
1997
NO
412.70
11.10
1998
NO
411.26
11.90
1999
NO
410.60
12.36
2000
115.66
409.25
13.34
2001
232.00
410.77
13.16
2002
417.19
415.90
13.95
2003
628.80
420.15
15.16
2004
909.37
425.89
16.44
2005
1 146.88
399.26
17.67
2006
2007
1 424.19
1 713.19
332.75
422.14
19.40
21.04
2008
1 896.14
393.41
21.98
2009
2 111.28
192.84
21.30
2010
3 054.43
387.57
65.48
2011
3 432.77
362.65
67.37
2012
4 256.95
271.33
68.58
2013
4 471.16
199.98
69.02
2014
4 929.70
186.65
74.88
2015
4 817.55
91.37
81.83
2016
5 110.99
37.37
79.53
2017
5 256.44
25.17
122.79
2018
2019
5 040.33
5 676.60
10.09
17.10
134.31
156.02
2020
6 497.73
10.38
171.50
2021
7 209.80
6.79
144.05
Turkish GHG Inventory Report 1990-2021
32
Trends in Greenhouse Gas Emissions
2.3. Emission Trends by Sector
Figure 2.9 GHG emission trend by sectors, 1990-2021
500
(Mt CO2 eq.)
400
300
200
100
0
1. Energy
3. Agriculture
5. Waste
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
-200
1990
-100
2. Industrial processes and product use
4. Land use, land-use change and forestry
1990-2021: Out of decreasing trend of LULUCF sector (29.1%) all sectors have an increasing trend
from 1990 to 2021 including energy (188%), IPPU (229%), waste (33%) and agriculture (57%).
The main reasons for the increasing sectors are population growth, a growing economy and an increase
in energy demand.
The main reasons for the rise in removals of LULUCF are improvements in sustainable forest
management, afforestation, rehabilitation of degraded forests, reforestations on forest land and
conversion of coppices to productive forests in forest land remaining forest land, efficient forest fire
management and protection activities, conversions to perennial croplands from annual croplands and
grasslands, and conversions to grasslands from annual croplands. The main reasons for the increase in
emissions of LULUCF are related to drought and biomass burning as wildfire (e.g. in the year 2008; 29.7
kha forest area, in the year 2021; 134.8 kha forest area burned), intense harvest policies, deforestation,
conversions to wetlands (flooded land) and settlements.
2020-2021: There are increasing trends in the annual change for energy (9.8%) and IPPU (10.6%)
sectors from 2020 to 2021. The sectors having decreasing trends are agriculture (1.5%), waste (9.9%)
and LULUCF (17.2%).
Turkish GHG Inventory Report 1990-2021
33 33
1
Trends in Greenhouse Gas Emissions
In the energy sector; energy industries, transport, manufacturing industries and construction and other
sectors show 12.4%, 13.04%, 10.1% and 0.2% increase respectively in 2021. Figure 2.10 shows
electricity production from different energy sources for the period, 2019-2021.
Figure 2.10 Electricity generation and shares by energy resources, 2019-2021
40
37.1
(%)
33.2
35
34.5
30.9
30
25
20
29.2
25.5
23.1
18.9
16.7
15
14.7
16.8
19.1
10
5
0
0.1 0.1 0.1
Natural Gas
Coal
Hydro
2019
2020
Other Renewable
and Waste
Liquid Fuels
2021
The decrease in emissions from the waste sector is mainly due to the increase in methane recovery
processes, particularly in recent years. The detailed reasons behind the emission trends and main drivers
for all sectors are discussed by each sub-sector in the related chapters.
While Table 2.4 provides a contribution of sectors to the net GHG emissions by sectors for some selected
years between 1990 and 2021, Table 2.5 shows the same shares for the GHG emissions without LULUCF.
34
Turkish GHG Inventory Report 1990-2021
34
Trends in Greenhouse Gas Emissions
Table 2.4 Contribution of sectors to the net GHG emissions
(%)
Sectors
1990
2000
2010
2015
2016
2017
2018
2019
2020
2021
Energy
91.19
93.58
88.29
88.27
87.44
86.29
82.63
82.25
78.93
78.15
IPPU
14.94
11.35
15.05
15.41
15.41
15.04
14.99
13.27
14.63
14.59
Agriculture
30.10
18.34
13.62
14.49
14.24
14.28
14.46
15.30
15.75
13.99
7.24
6.21
5.35
4.42
4.04
3.67
3.68
3.63
3.51
2.85
-43.47
-29.48
-22.05
-18.79
-17.67
-16.91
-15.44
-14.11
-12.26
-9.15
Waste
LULUCF
Table 2.5 Contribution of sectors to the GHG emissions without LULUCF
(%)
Sectors
1990
2000
2010
2015
2016
2017
2018
2019
2020
2021
Energy
63.56
72.28
72.19
72.00
72.19
72.35
71.38
71.86
69.96
71.31
IPPU
10.41
8.76
12.30
12.57
12.72
12.61
12.95
11.60
12.97
13.31
Agriculture
20.98
14.16
11.14
11.82
11.75
11.97
12.49
13.37
13.96
12.77
5.05
4.80
4.37
3.60
3.34
3.08
3.18
3.17
3.11
2.60
Waste
Energy
As in most countries, the energy system in Türkiye is largely driven by fuel combustion, followed by
fugitive emissions from fuels and then CO2 transport and storage. In 2021, emissions from the energy
sector are 71.3% of total emissions, excluding LULUCF. Emissions in CO2 eq. from the energy sector
are reported in Table 2.6 and shown in Figure 2.11.
CO2 emissions, 95.8% of the total energy sector emissions, showed an increase of 197.1% from 1990
to 2021. CH4 emissions are just 3.1% of the total, increased by 58.9% in comparison with 1990. N2O
emissions, with a 1.1% contribution to total emissions of the energy sector, show an 129.7% increase
in proportion to the year 1990.
Turkish GHG Inventory Report 1990-2021
35 35
1
Trends in Greenhouse Gas Emissions
Table 2.6 Total emissions from the energy sector by source
(kt CO2 eq.)
1990
Total
1.A Fuel
combustion
1.A.1 Energy
industries
1.A.2
Manufacturing
industries and
construction
1.A.3 Transport
1.A.4 Other
sectors
1.B Fugitive
emissions from
fuels
2000
2010
2015
2016
2017
2018
2019
2020
2021
139 536 216 045 287 878 341 994 361 747 382 412 373 402
365 581
366 567
402 480
135 026 209 899 279 652 336 497 353 151 375 713 365 740
355 905
357 986
392 292
149 644
141 894
159 506
37 188
77 725 114 153 135 780 146 030 157 363 158 586
37 162
57 945
52 333
59 593
60 079
60 189
59 669
54 565
60 186
66 236
26 969
36 465
45 392
75 798
81 841
84 770
84 617
82 428
80 680
91 200
33 707
37 764
67 773
65 327
65 201
73 391
62 869
69 269
75 225
75 350
4 510
6 145
8 226
5 496
8 596
6 699
7 662
9 676
8 581
10 188
3 598
4 836
6 151
2 733
5 896
3 681
4 885
6 770
5 558
6 493
912
1 309
2 075
2 763
2 700
3 017
2 777
2 906
3 023
3 695
0.13
0.13
0.13
0.13
0.13
0.13
0.13
0.13
0.13
0.13
1.B.1 Solid fuels
1.B.2 Oil and
natural gas
1.C CO2 transport
and storage
Figure 2.11 Trend of total emissions from the energy sector, 1990-2021
450 000
(kt CO2 eq.)
400 000
350 000
300 000
250 000
200 000
150 000
100 000
1A1
1A2
1A3
1A4
1B1
1B2
2020
2021
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
50 000
1C
GHG emissions of the energy sector, in CO2 eq., show an increase of 188% from 1990 to 2021.
Generally, an upward trend is noted from 1990 to 2021.
36
36
Turkish GHG Inventory Report 1990-2021
Trends in Greenhouse Gas Emissions
IPPU
Emissions from the industrial process and product use sector have a share of 13.3% of Türkiye's total
emissions excluding LULUCF in 2021. CO2 emissions are 87.5% of total IPPU emissions in 2021. N2O
and CH4 have a minor impact on IPPU emissions and N2O increased by 90.2% compared to 1990.
Emissions by each subsector of IPPU are tabulated in Table 2.7 for the 1990-2021 period. Figure 2.12
shows the trend for the IPPU related emissions by cumulating its subsectors.
Table 2.7 Total emissions from the industrial process and product use sector by source
(kt CO2 eq.)
1990
2000
2010
2015
2016
2017
2018
2019
2020
2021
Total
22 856 26 199 49 060 59 719 63 754 66 628 67 738 59 003 67 962 75 136
2.A Mineral industry
13 424 18 418 34 087 40 304 43 821 46 473 46 212 38 547 47 078 50 616
2.B Chemical industry
1 629
1 061
1 903
2.C Metal industry
2.D Non-energy
products from fuels
and solvent use
7 620
6 313
9 519 11 457 12 439 12 731 12 805 11 381 11 047 12 909
183
277
432
266
146
152
206
138
134
170
NO
NO
42
42
42
45
57
58
59
65
NO
116
3 054
4 817
5 111
5 256
5 040
5 677
6 498
7 210
NO,NE
13
23
40
36
73
71
58
57
29
2.E Electronic industry
2.F Product uses as
ODS substitutes
2.G Other product
manufacture and use
2 792
2 159
1 897
3 346
3 144
3 091
4 137
Figure 2.12 Trend of total emissions from IPPU sector, 1990-2021
80 000
(kt CO2 eq.)
70 000
60 000
50 000
40 000
30 000
20 000
2A
2B
2C
2D
2E
2F
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
10 000
2G
IPPU related emissions increased by 228.7% from 1990 to 2021. Due to the growth of population and
production especially for the recent decade, emissions from the IPPU sector are increased.
Turkish GHG Inventory Report 1990-2021
37 37
1
Trends in Greenhouse Gas Emissions
Agriculture
Enteric fermentation is by far the largest source of GHG emissions of agriculture in Türkiye since 1990.
The agriculture sector includes emissions from enteric fermentation, manure management, rice
cultivation, agricultural soils, field burning of agricultural residues and urea application. In 2021, the
agriculture sector accounted for 12.8% of total emissions in Türkiye. Enteric fermentation and
agricultural soils dominate the trends in this sector between 1990 and 2021 as seen in Table 2.8 and
they have an increase of 56.1% and 51.6% compared to 1990 respectively.
The most important portion in each gas is CH4 with 54.6%, then comes N2O with 43.6% share in the
agriculture sector emissions. CO2 has the lowest contribution with 1.8%.
Table 2.8 Total emissions from the agriculture sector by source
(kt CO2 eq.)
1990
2000
2010
2015
2016
2017
2018
2019
2020
2021
Total
46 054 42 332 44 409 56 133 58 894 63 262 65 338 68 022 73 154 72 075
3.A Enteric fermentation
22 397 19 234 20 946 26 947 26 984 30 110 32 136 33 368 34 615 34 953
3.B Manure management
3.C Rice cultivation
3.D Agricultural soils
5 436
5 142
5 391
6 956
7 060
7 697
8 508
8 597
9 060
9 144
100
128
202
240
243
234
252
263
262
269
17 314 16 870 17 006 21 006 23 147 23 607 23 022 24 342 27 389 26 249
3.F Field burning of
agricultural residues
347
340
219
174
164
165
163
165
171
159
3.H Urea application
460
617
645
811
1 295
1 450
1 257
1 288
1 657
1 302
Figure 2.13 Trend of total emissions from agriculture sector, 1990-2021
80 000
(kt CO2 eq.)
70 000
60 000
50 000
40 000
30 000
20 000
3A
38
3B
3C
3D
3F
2021
2020
2018
2019
2017
2015
2016
2014
2012
2013
2011
2009
2010
2008
2006
2007
2005
2003
2004
2002
2000
2001
1999
1997
1998
1996
1994
1995
1993
1991
1992
1990
10 000
3H
Turkish GHG Inventory Report 1990-2021
38
Trends in Greenhouse Gas Emissions
LULUCF
GHG emissions of the LULUCF sector from sources and removals by sinks are estimated and reported
for categories of managed lands: forest land, cropland, grassland, wetlands, settlements, harvested
wood products, other land and others.
In 2021, total CO2 eq. emissions and removals of the LULUCF sector have decreased by 17.2% compared
to 2020. Table 2.9 reports emissions and removals from the LULUCF sector by source.
Table 2.9 Total emissions and removals from the LULUCF sector by source
(kt CO2 eq.)
1990
2000
2010
2015
2016
2017
2018
2019
2020
2021
Total
-66 511 -68 052 -71 880 -72 807 -73 110 -74 959
-69 752 -62 720 -56 948 -47 146
4.A Forest land
-63 605 -64 376 -65 874 -62 937 -62 371 -65 323
-60 188 -53 999 -48 220 -33 945
4.B Cropland
0,69
38
453
4.C Grassland
4.D Wetlands
0,03
97
0,01
176
NO,IE
4.F Other land
4.G Harvested
wood products
4.E Settlements
457
344
368
352
381
395
387
636
983
656
705
708
768
777
722
413
- 20
271
288
222
188
189
230
145
426
419
406
413
407
413
419
421
NO,NE,IE
187
601
764
617
653
650
671
696
686
-2 907
-4 337
-8 587 -12 541 -13 102 -12 133
-11 973 -11 215 -11 281 -15 725
39
Turkish GHG Inventory Report 1990-2021
39
1
Trends in Greenhouse Gas Emissions
Figure 2.14 Trend of total emissions from the LULUCF sector, 1990-2021
10 000
(kt CO2 eq.)
- 10 000
- 20 000
- 30 000
- 40 000
- 50 000
- 60 000
- 70 000
4A
4B
4C
4D
4E
4F
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
- 90 000
1990
- 80 000
4G
LULUCF emissions or removals, in CO2 equivalent, are variable over the reporting period 1990-2021 as
seen in Figure 2.14. Generally, decreases in removals were influenced by fires and drought in the
relevant areas. Moreover, rises are originated mainly from forest management, afforestation,
rehabilitation of degraded forests, reforestations on forest land, etc.
Waste
The waste sector includes GHG emissions from the treatment and disposal of wastes, open burning,
wastewater treatment and discharge. Waste incineration emissions are included in the inventory
however it is reported under the energy sector. The waste sector GHG emissions are tabulated in Table
2.10. Total waste emissions for the year 2021 are 2.6% of total GHG emissions (without LULUCF).
Considering emissions by gas, the most important GHG is CH4 which accounts for 83.9% of the total
and shows an increase of 28.5% from 1990 to 2021. N2O levels have increased by 62.3% whereas CO2
decreased by 86.3% from 1990 to 2021; these gases account for 16.1% and 0.02% share in the waste
sector.
40
Turkish GHG Inventory Report 1990-2021
40
Trends in Greenhouse Gas Emissions
Table 2.10 Total emissions from the waste sector by source
Total
1990
2000
2010
2015
11 081
14 341
17 446
17 122
16 713 16 263 16 630 16 120 16 308 14 698
6 730
9 582
12 564
12 557
12 095 11 524 11 605 11 035 11 111
16
17
30
23
24
23
20
22
21
25
105
87
37
2
4
3
2
5
7
7
4 230
4 656
4 815
4 539
4 590
4 713
5 001
5 058
5 169
5 328
5.A Solid waste disposal
5.B Biological treatment
of solid waste
5.C Incineration and
open burning of waste
5.D Wastewater
treatment and discharge
2016
2017
2018
(kt CO2 eq.)
2019
2020
2021
9 338
Figure 2.15 Trend of total emissions from the waste sector, 1990-2021
20 000
(kt CO2 eq.)
18 000
16 000
14 000
12 000
10 000
8 000
6 000
4 000
5A
5B
5C
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
2 000
5D
Figure 2.15 shows trends in the waste sector between 1990-2021. The trend is mainly driven by solid
waste disposal with 63.5% of the emissions were from, followed by wastewater treatment and discharge
36.3% from, 0.17% from biological treatment of solid waste and 0.05% from open burning of waste.
Total emissions, in CO2 equivalent, decreased by 9.9% from 2020 to 2021.
Turkish GHG Inventory Report 1990-2021
41 41
1
Trends in Greenhouse Gas Emissions
2.4. Emission Trends for Indirect Greenhouse Gases
Emission trends of NOX, CO, NMVOC, SO2 and NH3 from 1990 to 2021 are given in Table 2.11.
Table 2.11 Total emissions for indirect greenhouse gases, 1990-2021
(kt)
Gas
1990
2000
2010
2015
2016
2017
2018
2019
2020
2021
NOX
253
1 475
979
959
991
973
959
970
956
981
2 041
7 812
3 404
2 367
2 354
2 188
1 659
1 776
1 940
1 942
896
1 453
1 098
1 091
1 095
1 121
1 098
1 126
1 166
1 166
SO2
1 683
2 070
2 471
1 949
2 266
2 375
2 524
2 529
2 305
2 693
NH3
85
97
62
59
45
46
41
43
46
49
CO
NMVOC
1990-2021: While three indirect gases have an increasing trend from 1990 to 2021 including NOX
(288.4%), SO2 (60%) and NMVOC (30.1%), two gases have a decreasing trend including CO (4.8%)
and NH3 (42.8%).
2020-2021: There are both increasing and decreasing trends in the annual change for each gas from
2020 to 2021. The gases having increasing trends are NOX (2.7%), SO2 (16.8%) and NH3 (5.2%). The
gases that have decreasing trends are CO (0.1%), NMVOC (0.1%).
42
Turkish GHG Inventory Report 1990-2021
42
Energy
1
3. ENERGY (CRF Sector 1)
3.1. Sector Overview
The energy sector includes emissions from the combustion of fossil fuels (1.A.1 energy industries; 1.A.2
manufacturing industries and construction; 1.A.3 transport; and 1.A.4 other sectors; as well as fugitive
emissions from fossil fuels (1.B) and CO2 transportation and storage (1.C).
Energy sector is the major source of Turkish anthropogenic GHG emissions. In overall 2021 GHG
emissions (excluding LULUCF), the energy sector had the largest portion with 71%.
Energy sector CO2 emissions constituted 85.2% of total CO2 emissions in 2021. The non-CO2 emissions
from energy-related activities represented rather small portion of the total national emissions. CH4
emissions are 19.3% of total national CH4 emissions and N2O emissions are 11.1% of total N2O emissions
in 2021.
Total emissions from the energy sector for 2021 were estimated to be 402.5 Mt CO2 eq. (Table 3.1)
Energy industries were the main contributor, accounting for 39.6% of emissions from the energy sector.
It is followed by transport sector with 22.7%, other sector with 18.7% and manufacturing industries
with 16.5% (Table 3.2).
Energy sector GHG emissions increased by 188.4% between 1990 and 2021 whereas annual emissions
from 2020 to 2021 increased by 9.8% (35 914 Kt CO2 eq.).
Turkish GHG Inventory Report 1990-2021
43 43
1
Energy
Table 3.1 Energy sector emissions by gas, 1990-2021
(kt)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
44
CO2
129
156
204
232
271
293
305
293
310
330
347
369
360
350
352
385
817
801
494
920
648
139
574
729
197
859
363
398
087
282
005
662
CH4
N2O
311
286
361
338
491
504
525
467
534
296
420
356
383
470
435
494
6.5
7.9
8.5
10.5
13.3
14.2
9.8
9.9
10.6
12.5
13.1
13.8
12.6
11.9
12.4
15.0
Turkish GHG Inventory Report 1990-2021
CO2 eq.
139
166
216
244
287
309
321
308
326
341
361
382
373
365
366
402
536
298
045
483
878
969
639
346
712
994
747
412
402
581
567
480
44
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Energy
139 536
166 298
216 045
244 483
287 878
309 969
321 639
308 346
326 712
341 994
361 747
382 412
373 402
365 581
366 567
402 480
Fuel
combustion
total
135 026
162 275
209 899
238 731
279 652
300 904
312 258
299 822
316 495
336 497
353 151
375 713
365 740
355 905
357 986
392 292
Energy
industries
37 188
50 440
77 725
90 970
114 153
126 270
127 087
121 589
132 413
135 780
146 030
157 363
158 586
149 644
141 894
159 506
Manufacturing
industries and
construction
37 162
40 000
57 945
63 011
52 333
52 592
61 059
52 983
54 444
59 593
60 079
60 189
59 669
54 565
60 186
66 235
Fuel combustion
Transport
26 969
34 113
36 465
42 041
45 392
47 386
62 525
68 865
73 559
75 798
81 841
84 770
84 617
82 428
80 680
91 200
Other
sectors
33 707
37 722
37 764
42 709
67 773
74 656
61 586
56 384
56 079
65 327
65 201
73 391
62 869
69 269
75 225
75 350
Total
fugitive
emissions
4 510
4 023
6 145
5 752
8 226
9 065
9 381
8 524
10 216
5 496
8 596
6 699
7 662
9 676
8 581
10 188
Solid
fuels
3 598
2 985
4 836
3 941
6 151
6 662
6 851
6 324
7 318
2 733
5 896
3 681
4 885
6 770
5 558
6 493
Oil and
natural
gas
912
1 038
1 309
1 811
2 075
2 403
2 530
2 199
2 898
2 763
2 700
3 017
2 777
2 906
3 023
3 695
Fugitive emissions from fuels
Table 3.2 Energy sector GHG emissions, 1990-2021
CO2
transport
and storage
0.13
0.13
0.13
0.13
0.13
0.13
0.13
0.13
0.13
0.13
0.13
0.13
0.13
0.13
0.13
0.13
(kt CO2 eq.)
45
Energy
Turkish GHG Inventory Report 1990-2021
1
45
1
Energy
Energy sector GHG emissions mainly are coming from stationary combustion. Total emissions from
stationary combustion are 301 Mt CO2 eq. in 2021, equal to 53.3% of total national GHG emissions
(excluding LULUCF).
The energy industries subsector (1.A.1) contributed 160 Mt CO2 eq. in 2021 while the GHG emissions
from manufacturing industries and construction subsector (1.A.2) emissions were 66.2 Mt CO2 eq. and
GHG emissions from other sectors (1.A.4) were 75.3 Mt. The transport sector GHG emissions were 91.2
Mt in the same year.
GHG emissions from stationary combustion increased by 179% (193 Mt CO2 eq.) between 1990 and
2021, and increased by 8.6% (23.7 Mt CO2 eq.) between 2020 and 2021.
Figure 3.1 GHG emissions from fuel combustion, 1990-2021
450
400
(Mt CO2 eq).
350
300
250
200
150
100
50
0
Stationary Combustion
Fuel combustion total
Transport
In 2021, transport contributed 91.2 Mt CO2 eq., which is 16.2% of total GHG emissions (excluding
LULUCF). The major source of transport emissions in Türkiye is road transportation. It accounts for
94.8% of transport emissions. It is followed by domestic aviation while other sources are far smaller:
domestic aviation with 3.1% and domestic navigation with 1.2%. Pipeline transport contribution was
0.4% and railway contribution was 0.4%.
Fuel used in international aviation and marine bunkers is reported separately from the national total. In
2021, international bunker GHG emissions were 10.3 Mt CO2 eq.
46
Turkish GHG Inventory Report 1990-2021
46
Energy
1
Emissions from transport sector increased 238.2% (64.2 Mt CO2 eq.) in 2021 compared to 1990. In the
same period increase in road transportation emissions was 249.1%, in domestic aviation it was 209.5%
and in domestic navigation it was 121.7%. Emissions from railway transport decreased by 50.6%
between 1990 and 2021.
Total fugitive emissions for 2021 were 10.2 Mt CO2 eq., representing 0.002% of total GHG emissions
(excluding LULUCF). Oil and natural gas systems contributed 30%, solid fuels account for the remaining
70% of fugitive emissions.
Overall fugitive emissions increased 125.9% between 1990 and 2021. In 2014 a serious mine accident
happened and many underground mines were closed in the following year as a precaution, therefore in
2015 fugitive emissions were decreased remarkably. In 2021, the underground coal production activity
increased and therefore in 2021 fugitive emissions from solid fuels were increased. In overall, from 1990
to 2021, fugitive emissions from oil and natural gas systems increased by 305.3%. Emissions from solid
fuels increased by 88.2% in the same period.
Figure 3.2 Fugitive emissions, 1990-2021
12
(Mt CO2 eq).
10
8
6
4
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2
Total
Solid Fuels
Oil and natural gas
2006 IPCC Guidelines are used for energy sector emission estimation. The methodology for emissions
from stationary energy sectors is a mix of T1, T2 and T3 approaches. In transport sector, T1 and T2
approaches have been used. Fugitive emissions were estimated by T1 approach (Table 3.3).
Turkish GHG Inventory Report 1990-2021
47 47
1
Energy
Table 3.3 Summary of methods and emission factors used in energy sector
CO2
CH4
GHG sources and sink
categories
Method
applied
Emission
factor
1. Energy
T1,T2,T3
A. Fuel combustion
N2O
Method Emission
applied
factor
Method
applied
CS,D,PS
T1,T2,T3
D,PS
T1,T2,T3
D,PS
T1,T2,T3
CS,D,PS
T1,T2,T3
D,PS
T1,T2,T3
D,PS
1. Energy industries
2. Manufacturing industries
and construction
T2,T3
CS,D,PS
T2,T3
D,PS
T2,T3
D,PS
T1,T2
CS,D
T1
D
T1
D
3. Transport
T1,T2
CS,D
T1,T2
D
T1,T2
D
4. Other sectors
T1,T2
CS,D
T1
D
T1
D
B. Fugitive emissions from fuels
Emission
factor
T1
D
T1
D
T1
D
1. Solid fuels
NA
NA
T1
D
NA
NA
2. Oil and natural gas
T1
D
T1
D
T1
D
T1
D
-
-
-
-
C. CO2 transport and storage
Country specific and plant specific carbon contents of liquid, solid and gaseous fuels are used for CO2
emissions estimation. For CH4 and N2O emissions, 2006 IPCC default emissions factors are used.
Sector QA/QC and Verification
Quality control for energy category was performed on the basis of QA/QC plan of Türkiye. All emission
factors and implied emission factors are compared with 2006 IPCC Guideline defaults and any outlines
were examined. In this inventory, 1A2 and 1A4 sectorial approach emissions and 1AB reference
approach fuel combustion emissions were calculated on SAS and it was double checked by the
calculations on the Excel sheets by two different experts and any findings were corrected.
In 2017 August, energy sector expert, from Finland, have come to TurkStat to review the energy sector
in scope of a project coordinated by TurkStat. Moreover, Turkish inventory have been reviewed by ERT
in 2017 September. Based on those findings improvements were done in the energy sector. These
improvements are explained and the effect of the recalculations are shown with in the relevant sectorial
subtitle in NIR submitted in 2018. Another QA process was also conducted in 2020 by an expert from
CITEPA for this sector.
The main critic during the reviews is the consistency of the energy sector. This is because the national
energy balance tables, which are the main data source of energy sector, are not in time series.
Inconstancies come to exist when the national energy balance tables are used in the time series
inventory calculations. In order to overcome this problem national energy balance tables should be
reallocated and made consistent in the time series. This problem will be handled in the following years.
48
Turkish GHG Inventory Report 1990-2021
48
Energy
1
3.2. Fuel Combustion (Sector 1.A)
The major source of GHGs in Türkiye is the fossil fuel combustion. The emissions from fossil fuel
combustion are calculated by TurkStat with cooperation with the Ministry of Energy and National
Resources(MENR) and the Ministry of Transport and Infrastructure (MoTI). The emissions from public
electricity and heat production were calculated by MENR and the emissions from transport were
calculated by MoTI, and the other energy sub-sectors were calculated by TurkStat. 2006 IPCC Guidelines
were used in emissions estimation for all energy subcategories.
The emissions from public electricity and heat production (1.A.1.a) are calculated on the basis of plant
specific fuel consumption and net calorific values (NCVs) with country specific carbon contents of fuels.
Technology specific CH4 and N2O emission factors from 2006 IPCC Guidelines are used for 1.A.1.a
category for since 2003 and 2006 IPCC Guidelines default CH4 and N2O EFs are used for 1990-2002
period since combustion technology data is available from 2003 onward for this category.
For petroleum refining sector (1.A.1.b), fuel consumption data, NCVs and carbon content of fuels are
compiled directly from the refineries. In the same way for manufacture of solid fuels (1.A.1.c) categories,
plant specific AD and plant specific carbon content are used in the emission estimation. 2006 IPCC
Guidelines default EFs are used for CH4 and N2O emission estimation.
Emissions from manufacturing industry and construction and other sectors (1.A.2), (1.A.4) were
estimated by using energy balance tables. For CO2 emission estimation both country specific and default
carbon contents and oxidation factors are used depending on the data availability. 2006 IPCC Guidelines
default EFs are used for CH4 and N2O emission estimation.
Transportation sector (1.A.3) consists of road transportation, domestic aviation, railways, domestic
navigation and pipeline transportation. Data availability in road transportation, navigation sector and
railways allows mostly T1 methodology in the emission estimations. Country specific carbon content of
diesel oil and residual fuel oil are used for CO2 emission estimations but for gasoline and liquefied
petroleum gas (LPG) 2006 IPCC default emission factors are used. T2 methodology was used for the
calculation of emissions from domestic aviation. Also T2 methodology was used for the calculation of
CO2 emissions from pipeline transportation. 2006 IPCC Guidelines default EFs are used for CH4 and N2O
emission estimation. The following table summarizes the data source for the 1A sectors.
Turkish GHG Inventory Report 1990-2021
49 49
1
Energy
Table 3.4 Summary table for the data source in fuel combustion (1A) sector
Category
Data Source
1A1a Electricity and Heat Production
Plant specific
1A1b Petroleum Refining
Plant specific
1A1c Manufacturing of Solid Fuels and Other Energy Industries
Plant specific
1A2 Manufacturing Industries and Construction
National energy balance table
1A3 Transport
See chapter 3.2.6
1A4 Other Sectors
National energy balance table
1AB Fuel Combustion Reference Approach
National energy balance table
1AD Feedstocks Reductants and Other non-Energy use of fuels
See chapter 3.2.3
National energy balance tables, which are published by the MENR every year, are the most important
input for the energy sector emission calculations. The source of data for the electricity production sector
of national energy balance is Turkish Electricity Transmission Corporation (TEİAŞ). The data that TEİAŞ
sends includes electricity generation, fuel consumption in both original units and TJ, with respect to
energy resources and license type of electricity generators. After the data is compared with previous
years, it is directly used in the relevant sections of the energy balance table. For the supply part of
national energy balance table (indigenous production, import, export, bunkers, stock change), the
administrative sources of relevant stakeholders such as EPDK, BOTAŞ, TEİAŞ, TTK, TKİ, MTA, MAPEG
are utilized. For the demand part of national energy balance table, the industry sector data is collected
through questionnaires applied by MENR/EİGM to the relevant companies/firms. For the other sectors,
administrative sources of relevant stakeholders are used. In the process of compiling data, the sectoral
reports of stakeholders are examined, as well as time series analysis and quality control with respect to
both energy resources and sectors are applied. The following table shows the country specific carbon
content (as ton carbon / TJ fuel) of fuels used in calculating the CO2 emissions. NCVs can be found
Annex 3.
Table 3.5 Country specific carbon contents of fuels
Fuel types
Unit
1990
2000
2010
2015 2018 2019 2020 2021
Hard coal
t/TJ
25.79
26.38
27.28
26.16
26.08
26.87
25.56
26.09
Lignite
Coke
Petrocoke
Fuel oil
t/TJ
t/TJ
t/TJ
t/TJ
32.79
30.14
26.55
21.33
31.61
30.14
26.55
21.33
31.57
29.95
26.55
21.33
30.57
30.10
26.55
21.33
30.51
29.48
26.55
21.33
30.09
29.59
26.55
21.33
29.80
30.19
26.55
21.33
29.60
29.67
26.55
21.33
Diesel
Naphta
Natural gas
t/TJ
t/TJ
t/TJ
20.03
20.13
15.13
20.03
20.13
15.13
20.03
20.13
15.17
20.03
20.13
15.19
20.03
20.13
15.08
20.03
20.13
14.64
20.03
20.13
15.19
20.03
20.13
15.12
The following table shows the country specific oxidation factors of fuels used in calculating the CO2
emissions factors.
50
Turkish GHG Inventory Report 1990-2021
50
1
Energy
Table 3.6 Country specific oxidation factor of fuels
Fuel types
1990
2000
2010
2015
2017
2018
2019
2020
2021
Hard coal
Lignite
0.988
0.950
0.988
0.950
0.985
0.953
0.963
0.960
0.975
0.973
0.975
0.973
0.983
0.966
0.979
0.959
0.976
0.967
Fuel oil
Diesel
0.984
0.984
0.984
0.984
0.984
0.984
0.984
0.984
0.984
0.984
0.984
0.984
0.984
0.984
0.984
0.984
0.984
0.984
The following table shows the CO2 emissions factors of all the fuels. The decrease in carbon content
over time (32.79 and 29.60 t/TJ for 1990 and 2021,) led to a lower EF even when the oxidation factor
increases.
Either country specific carbon contents or IPCC default carbon contents are used in the calculations
depending on the data availability. CO2 EFs are calculated by the formula below.
CO2 EF = C content of fuel x Oxidation factor of fuel x (44/12)
Country specific carbon content and oxidation rates were calculated through fuel analysis and ash-slag
or stack gas analysis reports.
Table 3.7 CO2 emission factors of fuels
Fuel types
Unit
1990
2000
2019
2020
2021
Hard coal
t/TJ
93.4
95.5
2010 2017 2018
98.6
94.5
94.1
96.9
91.8
93.64
Lignite
Asphaltite
Coke
Coal tar
t/TJ
t/TJ
t/TJ
t/TJ
114.2
96.1
110.5
80.7
110.1
96.1
110.5
80.7
110.3
96.1
109.8
80.7
107.2
96.1
112.2
80.7
107.5
96.1
108.1
80.7
106.6
96.1
108.5
80.7
Crude oil
Petrocoke
Fuel oil
Diesel
t/TJ
t/TJ
t/TJ
t/TJ
73.3
97.4
77.0
72.3
73.3
97.4
77.0
72.3
73.3
97.4
77.0
72.3
73.3
97.4
77.0
72.3
73.3
97.4
77.0
72.3
73.7
97.4
77.0
72.3
73.7
97.4
77.0
72.3
73.7
97.4
77.0
72.3
Gasoline
LPG
Rafinery gas
Aviation fuel
t/TJ
t/TJ
t/TJ
t/TJ
69.3
63.1
57.6
71.5
69.3
63.1
57.6
71.5
69.3
63.1
57.6
71.5
69.3
63.1
57.6
71.5
69.3
63.1
57.6
71.5
69.3
63.1
57.6
71.5
69.3
63.1
57.6
71.5
69.3
63.1
57.6
71.5
Kerosene
Naphta
Intermediate products
Base oils
t/TJ
t/TJ
t/TJ
t/TJ
71.9
72.7
73.3
73.3
71.9
72.7
73.3
73.3
71.9
72.7
73.3
73.3
71.9
72.7
73.3
73.3
71.9
72.7
73.3
73.3
71.9
72.7
73.3
73.3
71.9
72.7
73.3
73.3
71.9
72.7
73.3
73.3
White spirit
Bitumen
Other petroleum products
Natural gas
t/TJ
t/TJ
t/TJ
t/TJ
73.3
80.7
73.3
55.5
73.3
80.7
73.3
55.5
73.3
80.7
73.3
55.6
73.3
80.7
73.3
55.6
73.3
80.7
73.3
55.6
73.3
80.7
73.3
53.7
73.3
80.7
73.3
53.7
73.3
80.7
73.3
55.4
Fuel wood
Animal&Vegetable waste
Biofuels
t/TJ
t/TJ
t/TJ
111.8
100.1
70.8
111.8
100.1
70.8
111.8
100.1
70.8
111.8
100.1
70.8
111.8
100.1
70.8
111.8
100.1
70.8
111.8
100.1
70.8
111.8
100.1
70.8
Turkish GHG Inventory Report 1990-2021
104.8 104.08
96.1
96.1
110.7 108.8
80.7
80.7
51 51
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Energy
CO2, CH4 and N2O Emissions from fuel combustion were calculated for the period 1990-2021
Table 3.8 Emissions from fuel combustion (1A), 1990-2021
(kt)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
52
CO2
135
162
209
238
279
300
312
299
316
336
353
375
365
355
357
392
026
275
899
731
652
904
258
822
495
497
151
713
740
905
986
292
129
156
204
232
271
292
305
293
310
330
347
369
359
350
351
385
CH4
N2O
CO2 eq.
596
592
326
779
492
989
430
584
051
705
205
241
912
099
809
452
139.3
133.7
121.7
113.2
168.4
147.9
155.9
131.5
130.9
82.5
82.3
94.1
83.4
89.9
99.3
94.7
6.5
7.9
8.5
10.5
13.3
14.2
9.8
9.9
10.6
12.5
13.0
13.8
12.6
11.9
12.4
15.0
Turkish GHG Inventory Report 1990-2021
52
1
Energy
Figure 3.3 CO2 emissions from fuel combustion, 1990-2021
450
(Mt CO2 eq).
400
350
300
250
200
150
100
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
50
Energy ind
Manufacturing Industries and Construction
Transport
Other sectors
Energy industry has the highest share in total CO2 emission from fuel combustion in 2020. It is followed
by transport, other sectors, and manufacturing industries and construction.
Figure 3.4 CO2 emissions from fuel combustion by sectors, 1990 and 2021
1990
2021
Energy industries
25%
28%
Manufacturing industries
and construction
Transport
20%
19%
41%
23%
Other sectors
27%
17%
Turkish GHG Inventory Report 1990-2021
53 53
0
54
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
200
180
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
1
Energy
Figure 3.5 CH4 emissions from fuel combustion, 1990-2021
(kt)
160
140
120
100
80
60
40
20
Figure 3.6 N2O emissions from fuel combustion, 1990-2021
16
14
12
10
8
6
4
2
Turkish GHG Inventory Report 1990-2021
54
Energy
1
3.2.1. Comparison of the sectoral approach with reference approach
The IPCC Reference Approach is a top down inventory based on production, imports, exports, stock
change and international bunker consumption of fuels.
2006 IPCC methodology is used for reference approach CO2 estimation. The estimation based on the
apparent consumption of fuels in the country. The apparent consumption of primary fuels has been
calculated by using the following formula:
Apparent consumption = Domestic production + imports - exports - change
(increase/decrease) in stocks - international bunkers
Apparent consumption of secondary fuels has been calculated by using the following formula:
Apparent consumption= imports - exports - change (increase/decrease) in stocksinternational bunkers
The apparent consumption is need to be adjusted for feedstocks, reductants and other non-energy use
of fuels. The fossil fuels used for non-energy purposes should be deducted from the apparent
consumption in order to avoid double counting in reference approach. (See section 3.2.3 Feedstocks,
Reductants and Other Non-Energy Use of Fuels )
Domestic production, import, export, stock change and international bunkers have been taken from
national energy balance tables for all primary fuels and petroleum products in ktoe unit.
Note that the reference approach emission calculation is dependent on the national energy balance
tables and the fuel classification in the national energy balance table is different than CRF fuel
classification. Therefore, the fuels in the national energy balance table is allocated into CRF fuel
classification according to the table below.
The allocation of fuels into the CRF 1AB category is shown in the table below.
Turkish GHG Inventory Report 1990-2021
55 55
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Energy
Table 3.9 Fuel allocation in reference approach
56
Fuel allocated under
national energy balance
table
Fuel allocated under
CRF 1AB sector
Hard coal
Lignite
Asphaltite
Coke
Coking coal
Lignite
Sub bitiminous coal
Coke oven coke
Coal tar
Crude oil
Petrocoke
Fuel oil
Coal tar
Crude oil
Petroleum coke
Residual fuel oil
Diesel
Gasoline
LPG
Rafinery gas
Diesel oil
Gasoline
LPG
Other oil
Aviation fuel
Kerosene
Naphta
Intermediate products
Jet kerosene
Other kerosene
Naphta
Other oil
Base oils
White spirit
Bitumen
Other petroleum products
Other
Other
Other
Other
Natural gas
Fuel wood
Animal&Vegetable waste
Biofuels
Natural gas
Solid biomass
Solid biomass
Liquid biomass
oil
oil
oil
oil
Turkish GHG Inventory Report 1990-2021
56
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Reference Approach
Liquid fuels
Solid fuels
(excluding
(excluding
international
international
Gaseous
bunkers)
bunkers)
fuels
66 028
63 511
5 538
83 270
68 610
12 363
91 665
94 125
28 572
94 669
89 275
50 823
86 236
126 348
72 623
85 800
130 463
85 643
93 059
135 973
84 926
95 477
118 580
86 085
98 536
128 608
92 030
108 488
131 236
90 528
115 166
139 291
87 954
115 623
152 470
101 863
111 097
157 027
93 420
108 087
167 917
82 157
108 873
158 904
91 445
115 959
159 075
111 890
Total
135 077
164 243
214 362
234 767
285 207
301 906
313 958
300 143
319 174
330 252
342 411
369 956
370 073
366 932
368 835
399 054
Liquid fuels
Solid fuels
(excluding
(excluding
international international
bunkers)
bunkers)
59 784
63 097
77 694
65 272
82 142
92 771
83 824
95 209
79 519
120 685
82 652
125 209
88 192
131 071
92 556
114 671
97 263
119 671
106 454
128 050
116 047
139 932
118 618
145 944
113 695
150 719
111 592
154 587
111 691
148 245
117 618
153 277
Table 3.10 CO2 emissions from fuel combustion, 1990-2021
Gaseous
fuels
6 716
13 626
29 371
53 671
70 847
84 582
85 364
85 191
91 878
94 388
89 719
102 843
93 286
81 577
89 908
112 654
Other
fossil
fuels
NO
1
42
75
441
545
803
1 166
1 238
1 812
1 508
1 836
2 211
2 343
1 966
1 904
Sectoral Approach
Total
129 596
156 592
204 326
232 779
271 492
292 989
305 430
293 584
310 051
330 705
347 205
369 241
359 912
350 099
351 809
385 452
57
(kt)
Energy
Turkish GHG Inventory Report 1990-2021
1
57
1
Energy
Figure 3.7 CO2 emissions from fuel combustion, 1990-2021
450
400
350
300
250
200
150
100
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
50
Referance Approach
58
Sectoral Approach
Turkish GHG Inventory Report 1990-2021
58
1
Energy
Table 3.11 Comparison of CO2 from fuel combustion between reference and sectoral
approach, 1990-2021
Reference approach
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Apparent
consumption
(PJ)
1 795
2 188
2 891
3 293
4 005
4 300
4 461
4 343
4 596
4 815
5 037
5 361
5 261
5 141
5 261
5 778
Emissions
(kton CO2)
135 077
164 243
214 362
234 767
285 207
301 906
313 958
300 143
319 174
330 252
342 411
369 956
370 073
366 932
368 835
399 054
Sectoral approach
Apparent
consumption
(PJ)
1 792
2 174
2 778
3 658
3 962
4 118
4 003
4 269
4 529
4 724
5 030
4 875
4 704
4 818
5 388
1 792
Emissions
(kton CO2)
135 026
162 275
209 899
279 652
300 904
312 258
299 822
316 495
336 497
353 151
375 713
365 740
355 905
357 986
392 292
135 026
Difference in
emissions
(%)
0.0
-1.2
-2.1
-1.9
-0.3
-0.5
-0.1
-0.8
1.9
3.1
1.6
-1.2
-3.0
-2.9
-1.7
0.0
Explanation of differences:
While converting to common energy units, the reference approach multiplies the apparent fuel
consumption by a single conversion factor. On the other hand, each fuel has different heat content.
Sectoral approach uses sector specific heat value provided in the energy balance tables.
In sectoral approach fuel consumption and NCVs of 1A1 category have been collected directly from the
end users (from electricity and heat producers, refineries and coke producers). It brings differences
between the sectoral and reference approaches since the plant level NCVs differ from average NCVs
used in energy balance tables. Especially for solid fuels and more specifically for the Turkish lignite,
such differences in NCVs are causing differences. Since the Turkish lignite is poor quality fuel, its NCV
is generally too low from that of literature lignite. In plant level, data regarding the NCV of lignite
changes in a wide range (from 1000 to 6000 kg/kcal). However, in national balance tables, an average
NCV value is about 2200 kcal/kg is used. Based on the quality of lignite used in a specific year,
consumption in TJ differs from the national energy balance data. This causes differences in emissions.
Recalculation:
There is no recalculation in this sector.
Turkish GHG Inventory Report 1990-2021
59 59
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Energy
3.2.2. International bunker fuels
In consistent with the UNFCCC reporting guidelines, CO2, CH4 and N2O emissions from international
bunker fuels are calculated and reported separately.
3.2.2.1. International aviation
The fuel type used in international aviation is jet kerosene. Table 3.12 shows the trend in emissions of
CO2, CH4, and N2O from international aviation between 1990 and 2021.
GHG emissions from international aviation have an increasing trend in consistent with the growth in
international aviation sector. CO2 eq. emissions were 8.39 Mt in 2021 (Figure 3.8) while it was 0.56 Mt
in 1990.
Emissions from international aviation are calculated using the T1 methodology given in the 2006 IPCC
Guidelines. The following equation is used.
According to the 2006 IPCC Guidelines, the Tier 1 method should only be used for aircraft using aviation
gasoline, not larger aircraft using jet kerosene however use of a higher tier method is not possible in
Türkiye because aircraft operational use data are not available.
Energy balance tables were used for AD. To estimate emissions, Türkiye applies the default emission
factors from the 2006 IPCC Guidelines as follows: CO2 (71500 kg/TJ), CH4 (0.5 kg/TJ) and N2O (2 kg/TJ).
60
Turkish GHG Inventory Report 1990-2021
60
1
Energy
Figure 3.8 GHG emissions from international aviation, 1990-2021
16 000
(kt. CO2 eq.)
14 000
12 000
10 000
8 000
6 000
4 000
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
2 000
Table 3.12 Emissions and fuel for international aviation, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
CO2
(kt)
552
807
1 599
3 330
5 858
6 769
7 684
8 661
9 922
11 085
10 630
11 015
12 006
13 917
5 842
8 321
CH4
(kt)
0.004
0.006
0.011
0.023
0.041
0.047
0.054
0.061
0.069
0.078
0.074
0.077
0.084
0.097
0.041
0.058
N2O
(kt)
0.02
0.02
0.04
0.09
0.16
0.19
0.21
0.24
0.28
0.31
0.30
0.31
0.34
0.39
0.16
0.23
CO2 eq
(kt)
556
814
1 612
3 358
5 908
6 827
7 750
8 734
10 007
11 180
10 720
11 109
12 108
14 036
5 892
8 392
Turkish GHG Inventory Report 1990-2021
Aviation
bunkers
(TJ)
7 718
11 290
22 359
46 570
81 937
94 671
107 473
121 129
138 775
155 037
148 668
154 053
167 911
194 649
81 712
116 377
61 61
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Energy
3.2.2.2. International navigation
The fuel type used in international navigation is diesel and residual fuel oil. Table 3.13 shows the trend
in emissions of CO2, CH4 and N2O from international navigation between 1990 and 2021.
GHG emissions from international navigation have an increasing trend corresponding to the growth in
the international navigation sector. CO2 eq. emissions were 1.89 Mt in 2021 (Figure 3.9) while it was
0.4 Mt in 1990.
Emissions from international navigation were calculated using the T1 and T2 methodology given in 2006
IPCC Guidelines. Country specific carbon content is used for CO2 emission estimation. 2006 IPCC default
EFs are used for CH4 and N2O emissions. The following equation is used. Activity data in international
navigation provided by the EMRA were compared with those of DG of Mining and Petroleum Affairs,
reported to IEA.
Where:
a = fuel type (residual fuel oil and gas diesel oil)
b = water-borne navigation type (the type of vessel b is ignored at Tier 1)
Country specific carbon content is used for CO2 emission estimation. To estimate CH4 and N2O emissions,
Türkiye applies the default emission factors from the 2006 IPCC Guidelines as follows: CH4 (7 kg/TJ)
and N2O (2 kg/TJ).
62
Turkish GHG Inventory Report 1990-2021
62
1
Energy
Figure 3.9 GHG emissions from international navigation, 1990-2021
4 000
(kt. CO2 eq.)
3 500
3 000
2 500
2 000
1 500
1 000
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
500
Table 3.13 Emissions and fuel for international navigation, 1990-2021
Year
CO2
(kt)
CH4
(kt)
N2O
(kt)
CO2 eq.
(kt)
Navigation
bunkers
(TJ)
1990
379
0.035
0.01
383
5 035
1995
587
0.055
0.02
593
7 819
2000
1 279
0.118
0.03
1 292
16 861
2005
3 376
0.312
0.09
3 411
44 586
2010
2 407
0.217
0.06
2 431
31 058
2011
1 951
0.176
0.05
1 971
25 160
2012
2 618
0.237
0.07
2 645
33 786
2013
2 892
0.261
0.07
2 921
37 316
2014
3 260
0.294
0.08
3 292
41 958
2015
2 742
0.248
0.07
2 769
35 358
2016
3 006
0.271
0.08
3 036
38 654
2017
2 871
0.262
0.08
2 900
37 487
2018
3 101
0.284
0.08
3 132
40 520
2019
2 833
0.260
0.07
2 862
37 186
2020
1 726
0.162
0.05
1 744
23 145
2021
1 872
0.176
0.05
1 891
25 120
Turkish GHG Inventory Report 1990-2021
63 63
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Energy
Recalculations:
There is no recalculation for this category.
3.2.3. Feedstocks, Reductants and other non-energy use of fuels
In accordance with the 2006 IPCC Guidelines, AD and emissions associated with the non-energy use of
fuels are not reported within the fuel combustion subsector. The table below summarizes reporting of
carbon stored and emissions related to use of feedstock, reductants and other non-energy use of fuels.
Table 3.14 Summary table for use of feedstock, reductants and other non energy use of
64
Use of fuel
Reported in inventory
Data Source
Reductant for ferroalloy
production
Emissions in 2.C.2; in RA
subtracted from coke
Plant specific
Reductant for carbide
production
Emissions is 2.B.5; in RA
subtracted from coke
Plant specific
Reductants for steel
production in Electric Arc
Furnaces
Emissions in 2.C.1; in RA
subtracted from coke oven coke
and natural gas
Estimated from EAF primary
steel production data
Reductants for steel
production in integrated iron
and steel plants
Emissions is 2.C.1; in RA
subtracted from coking coal
Plant specific
Feedstock for ammonia
production
Emissions in 2.B.2; in RA
subtracted from natural gas
Plant specific
Feedstock for petrochemical
industry
Carbon stored, in RA subtracted
from naphta
National energy balance table
Use of lubricants
Emissions in2.D.1; in RA
subtracted from other oil
National energy balance table
(Aggregated under other oil)
Use of parrafin and wax
Emissions in 2.D.1; in RA
subtracted from other oil
National energy balance table
(Aggregated under other oil)
Use of bitumen for road
paving, asphalt roofing etc.
Carbon stored, in RA subtracted
from other oil
National energy balance table
(Aggregated under other oil)
Refinery feedstocks
Carbon stored, in RA subtracted
from other oil
National energy balance table
(Aggregated under other oil)
Turkish GHG Inventory Report 1990-2021
64
Energy
1
Fossil fuels are used in integrated iron and steel plants for reducing iron ore into iron metal. The
reduction process causes CO2 emissions. These emissions are reported under IPPU category. The
amount of carbon (fossil fuel originated, not limestone etc.) reported in the IPPU is converted into the
amount of coking coal and it is subtracted from the reference approach.
In the national energy balance tables, feedstock and non-energy use of fuels are given separately and
those consumptions are not included in fuel consumptions. Naphtha is given as feedstock in the national
energy balance tables. Fuels used for non-energy purposes are lubricants, bitumen, solvents and
rafinery feedstocks. But they were not given separately in the national energy balance tables till 2015.
They were included in the aggregated item “other petroleum products".
Emissions from lubricants and paraffin-wax use are included under 2.D-non-energy products from fuels
and solvent use category. However, bitumen is used for road paving or asphalt roofing purposes and
carbon is stored in the products it is not released. Refinery feedstock is used in the refining industry
and is transformed into one or more components and/or finished products. Naphtha is used as feedstock
for petrochemical industry.
Recalculation:
There is no recalculation in this sector.
3.2.4. Energy industries (Category 1.A.1)
Source Category Description:
This source category includes the emission from the public electricity and heat production, petroleum
refining and manufacture of solid fuels in Türkiye. This category is one of the main emission sources in
Türkiye. The share of GHG emissions as CO2 eq. from energy industries in total fuel combustion was
39.9% in 2021 while it was 28% in 1990. The source category 1.A.1 is a key category in terms of
emission level and emission trend of CO2 from liquid, solid and gaseous fuels in 2021.
Turkish GHG Inventory Report 1990-2021
65 65
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Energy
Table 3.15 GHG emissions from energy industries, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
CO2
(kt)
37 065
50 272
77 486
89 635
112 053
123 633
124 665
119 431
130 106
133 596
142 857
153 679
157 538
148 793
140 993
158 004
CH4
(kt)
0.4
0.6
1.0
1.2
1.7
1.9
1.9
1.8
1.9
1.9
2.0
2.1
2.0
1.8
1.8
2.3
N2O
(kt)
0.4
0.5
0.7
2.6
4.0
4.2
3.8
4.1
4.4
3.9
4.1
4.6
3.3
2.7
2.9
4.8
Fuel
CO2 eq. consumption
(kt)
(TJ)
37 188
394 380
50 440
545 725
77 725
906 993
90 428
1 105 792
113 287
1 399 287
124 940
1 539 508
125 858
1 575 560
120 685
1 509 864
131 453
1 681 085
134 795
1 686 737
144 143
1 753 704
155 096
1 914 651
158 586
1 901 427
149 644
1 709 801
141 894
1 726 604
159 506
2 034 361
Methodological Issues:
2006 IPCC Guidelines T2 and T3 approaches were used for emission calculation in energy industries.
The emissions from public electricity and heat production (1.A.1.a) are calculated on the basis of plant
specific fuel consumption and NCVs with country specific carbon contents of fuels. For petroleum refining
sector, fuel data, NCV and carbon content of fuels were compiled directly from the refineries. For
manufacture of solid fuels (1.A.1.c) category, plant specific AD and carbon content were used in the
emission estimation.
Emissions from CRF category 1.A.1.a, have been estimated by the MENR by using 2006 IPCC T2, T3
approaches. Plant-specific NCVs were used to calculate heat values that led to emissions. Plant level
fuel consumption and NCVs of fuels are received from Turkish Electricity Transmission Company (TEİAŞauthority for Turkish electricity transmission). Carbon contents of fuels are calculated using fuel analysis
reports and oxidation rates are calculated using ash and slag analysis reports for solid fuels, and stack
gas analysis reports for liquid and gaseous fuels. CO2 emissions from liquid, solid and gaseous fuels
used in public electricity and heat production (1.A.1.a) are calculated using country specific carbon
content of fuels and oxidation rates. For biomass and other fossil fuels on the other hand, default carbon
contents and oxidation rates were used given in the 2006 IPCC Guidelines. Activity data of CH4 and N2O
emissions from CRF category 1A1a, have been estimated by using plant specific fuel consumption and
NCVs. For the years 2000-2020 technology information of power plants were obtained. According to
66
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66
Energy
1
type of technology, using 2006 IPCC Guidelines for National Greenhouse Gas Inventories, emission
factors were chosen in order for CH4 and N2O to be estimated with Tier 3.
Emissions from petroleum refining (CRF 1.A.1.b) were calculated according to 2006 IPCC T2 approach
by TurkStat. Fuel consumption, NCVs and carbon content of fuels were compiled directly from refineries.
CO2 emissions from 1.A.1.b were calculated by using average carbon contents of fuels used in the
refineries with IPCC default oxidation rates. CH4 and N2O emissions from CRF category 1.A.1.b, have
been estimated by using refineries total fuel consumption and average NCVs for refineries with IPCC
default EFs.
Emissions from manufacture of solid fuels (CRF 1.A.1.c) were calculated according to 2006 IPCC T2, T3
approaches by TurkStat. Coke production in integrated iron and steel production plants have been
considered in this category. Plant specific fuel consumption, NCVs and carbon content of fuels were
compiled from each plant. CO2 emissions from 1.A.1.c were calculated by using plant specific AD, carbon
contents of fuels and IPCC default oxidation rates. CH4 and N2O emissions from CRF category 1.A.1.c,
have been estimated by using plant specific fuel consumption and NCVs and IPCC default EFs.
Recalculation:
There is recalculation in emissions from 1.A.1.b. Petroleum Refining due to the use of MRV data for the
years 2018-2020 and emissions from 1.A.1.c for the years 1990-1991 and 2005-2020 due to the change
of emissions factor’s parameters.
Turkish GHG Inventory Report 1990-2021
67 67
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Energy
3.2.4.1. Public electricity and heat production (Category 1.A.1.a)
Source Category Description:
Public electricity and heat production category includes electricity and heat production of all electricity
generation installations in operation, including auto producers. Auto producers are the facilities that
produce electricity that they use for their purposes. Their AD (Activity Data) for electricity production
and sold heat are taken under 1.A.1.a. Unsold heat, namely the heat they use for industry purpose, on
the other hand, is taken under the related industry subcategory they belong to avoid double-counting
for the whole time series. For 1.A.1.a sector, plant-specific AD's are gathered from Turkish Electricity
Transmission Company (TEİAŞ).
Total installed capacity reached 99,820 MW in 2021 with a 4% increase from the previous year and
nearly 6.1 times higher than the 1990 values. The total gross electricity consumption increased by 8.7%
in 2021 compared to the previous year. In 2021, gross consumption was 332,871 GWh; meanwhile, in
2020, this figure was realized as 306,109 GWh. Above mentioned installed capacities, and consumption
amounts belong to electricity production companies and auto producers as well. In 2021, natural gas
had a high share of 33.2% in all electricity production, which was followed by hydro (16.7%), other
bituminous coal (16.4%), Turkish lignite (12.8%), other renewable and wastes (12.6%) and oil (0.08%).
From 2020 to 2021, electricity production from hydropower plants decreased by 28.4%. The amount of
electricity produced from other bituminous coal has decreased from 62.51 TWh to 54.95 TWh On the
other hand, electricity production from natural gas increased from 70.93 TWh to 111.18 TWh and
Turkish lignite from 37.94 TWh to 42.98 TWh.
In 2021 electricity production from fossil-fueled thermal power plants has accounted for 214.844 TWh
of 334.723 TWh production, while in 2020, electricity production from fossil-fueled thermal power plants
had accounted for 177.066 TWh of a total of 306.703 TWh production. Fossil fueled thermal share in
electricity production increased from 57.73% in 2020 to 64.19% in 2021.
68
Turkish GHG Inventory Report 1990-2021
68
Energy
1
Figure 3.10 Energy mix of category 1.A.1.a, 1990-20211
100%
90%
80%
70%
60%
50%
40%
30%
20%
0%
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
10%
Coal
Liquid Fuels
Natural Gas
Hydro
Renewable energy and Wastes
There was an increase in wind installed capacity from 8,832 MW in 2020 to 10,607 MW in 2021.
Renewable Law, which came into force in 2005 later revised in 2011, provided some supporting
mechanisms for purchasing electricity from solar, biomass, geothermal, wind, and hydraulic energy. In
the year 2021, solar power plants installed capacity raised to 7,816 MW. The voluntary carbon market's
role is important to mention, as many wind projects in the country generate and sell the voluntary
carbon credits.
Electricity generation from animal and yard waste has increased by 36% compared to the previous year,
reaching 2,035 MW of installed power, generating 7,779 GWh of power in 2021.
In 2021, Total Primary Energy Supply (TPES) of Türkiye was 6 675 102.01 TJ, 8 % increase compared
to 2020. Oil had a share of 1 841 489.70 TJ while hard coal and natural gas accounted for 981 541.40
TJ and 2 061 202.38 TJ, respectively.
1Electricity
Statistics, TEİAŞ (https://www.teias.gov.tr/tr-TR/turkiye-elektrik-uretim-iletim-istatistikleri )
Turkish GHG Inventory Report 1990-2021
69 69
1
Energy
Figure 3.11 Electricity generation and shares by energy resources, 2020 - 20212
40%
35%
34.5%
33.2%
30.9%
30%
23.1%
25%
25.5%
20%
16.8%
16.7%
19.1%
15%
10%
5%
0.1%
0%
0.1%
2020
Coal
Liquid Fuels
2021
Natural Gas
Hydro
Renewable energy and Wastes
Figure 3.12 Electricity generation and shares by energy resources, 1990 - 20213
45%
40.2%
40%
35.1%
35%
33.2%
30.9%
30%
25%
17.7%
20%
16.7%
19.1%
15%
10%
6.9%
5%
0.1%
0%
0.1%
1990
Coal
Liquid Fuels
2021
Natural Gas
Hydro
Renewable energy and Wastes
Primary energy (domestic) production was 1 956 084.42 TJ in 2021 and provided 29.9% of the overall
energy supply. The share of imports in TPES was about 70.1% in 2021.
The production of solid fossil fuels, excluding animal & yard waste, has increased from 658 188.76 TJ
in 2020 to 747 729.36 TJ in 2021. The main domestic energy source remains as Turkish lignite, with
2Electricity
3Electricity
70
Statistics, TEİAŞ (https://www.teias.gov.tr/tr-TR/turkiye-elektrik-uretim-iletim-istatistikleri )
Statistics, TEİAŞ (https://www.teias.gov.tr/tr-TR/turkiye-elektrik-uretim-iletim-istatistikleri )
Turkish GHG Inventory Report 1990-2021
70
Energy
1
production increased from 71.64 Mt in 2020 to 83.56 Mt in 2021, which represented an increase by
about %16.64
GHG emissions from public electricity and heat production in total fuel combustion were 37.9% in 2021,
and even it was 24.4% in 1990. According to Table 3.16, fuel consumption increased from 1 585 675
TJ in 2020 to 1 892 330 TJ in 2021 when the CO2 emissions increased from 130 770 kt in 2020 to 147
901 kt in 2021. In other words, fuel consumption increased by 19.3% compared to the previous year,
while CO2 emissions increased by 13.1%. The main reason why the increase in fuel consumption is
higher than the increase in emissions is that the share of coal in electricity generation decreased by
approximately 4% in 2021, while the share of natural gas (33.2%) increased compared to the previous
year (23.1%). Compared to last year, the share of hydroelectricity decreased by about 9%, whereas
the share of other renewables in production increased from about 17% to 19%.
Table 3.16 Emissions from category 1A1a, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
32
45
73
84
107
118
119
114
125
126
134
144
148
138
130
147
CO2
823
860
139
623
664
730
702
861
665
767
280
814
992
273
770
901
CH4
0.3
0.5
0.9
1.1
1.6
1.8
1.8
1.7
1.8
1.8
1.9
1.9
1.9
1.7
1.7
2.2
N2O
0.4
0.5
0.7
2.5
4.0
4.2
3.8
4.0
4.3
3.8
4.1
4.6
3.3
2.7
2.9
4.8
CO2 eq.
32 938
46 020
73 371
85 407
108 892
120 031
120 889
116 110
127 006
127 958
135 554
146 220
150 032
139 116
131 662
149 395
1
1
1
1
1
1
1
1
1
1
1
1
1
Fuel
346 707
490 230
854 300
036 864
344 379
478 115
512 807
451 358
624 731
591 475
644 763
804 038
791 670
580 085
585 675
892 330
Methodological Issues:
Activity Data
The plant-specific activity data for the whole time series is obtained from Turkish Electricity Transmission
Company (TEİAŞ) in a compiled form. After data obtaining, sector experts checked whether there were
data errors or omissions, and then data compared with fuel specific default values from IPCC guidelines
and literature. Cross checks, including fuel capacity factor controls, and examining outliers give some
opinion about data consistency. Suspicious data are corrected by getting in contact with Turkish
Electricity Transmission Company (TEİAŞ).
Turkish GHG Inventory Report 1990-2021
71 71
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Energy
As soon as the sector experts are assured about data reliability, data entry to the overall calculation
table begins. After entering data of every single plant that produced electricity in the related year, the
heat content of fuels is calculated with plant-specific data obtained from Turkish Electricity Transmission
Company (TEİAŞ). In order to obtain plant-specific activity data, the amount of feedstock fuel used is
multiplied by plant-specific NCVs to get heat values in terms of TJ. Average NCVs are given in Table
3.17.
Table 3.17 Average NCVs of fuels used in category 1.A.1.a
Fuel Type
Sub-Bituminous Coal
Natural gas
Residual Fuel Oil
Other bituminous coal
Turkish lignite
Gas\Diesel Oil
(TJ/kt)
Weighted
average Default
13.56
18.90
53.52
48.00
46.20
40.40
23.39
25.80
6.64
11.90
43.12
43.00
The multipliers of EF, namely, carbon content and oxidation rates, were calculated. For Turkish lignite,
sub-bituminous, and other bituminous coal, ultimate analysis results obtained from coal-fired power
plants were used to calculate the related coal types' carbon content. The same procedure was applied
for liquid fuels through residual fuel oil characteristics and mass percentage of carbon. For natural gas,
volumetric fractions of gas concentrations were obtained through gas chromatography analysis from
Petroleum Pipeline Company (BOTAŞ). Using the gases and some stoichiometry density, each gas
compound's carbon mass amount was calculated and summed up to reach an overall carbon amount.
The oxidation rate of solid fuels was calculated using the mass percentage of carbon in ash-slag analysis
reports obtained from coal-firing plants. For gaseous fuels, measured CO concentrations in the stack
gas were used in order to calculate the mass percentage of the unoxidized carbon and then the oxidation
rate of the related fuel. In order to calculate the oxidation rate of gaseous fuels (natural gas), CO
concentrations measured in the stack gas of the related plants were obtained from the Ministry of
Environment and Urbanization. Some of the analysis reports and calculation steps were shared in Annex
3. CO2 EFs used for source category 1.A.1.a were listed in Table 3.18 for the whole time series on a fuel
basis.
For CH4 and N2O emissions starting from the year 2000, plant-specific technology classification
information was obtained from Turkish Electricity Transmission Company (TEİAŞ). Using Table 2.6:
Utility Source Emission Factors from Stationary Combustion Chapter of Guideline, Tier 3 EFs for CH4 and
N2O were chosen.
EFs for CH4 and N2O were listed in Table 3.19 for the whole time series on a fuel basis.
72
Turkish GHG Inventory Report 1990-2021
72
Turkish
Lignite
114.16
113.39
110.05
113.50
110.26
109.48
109.29
109.09
107.63
107.63
107.41
107.24
107.55
106.62
104.44
104.82
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
93.35
91.76
96.89
94.12
94.50
85.32
92.38
93.15
96.18
96.65
95.10
98.56
94.23
95.52
102.17
93.37
SubBituminous
Coal
93.04
94.50
94.58
92.75
91.55
91.37
92.64
87.70
93.57
88.89
89.11
90.01
85.24
88.62
NO
NO
Other
Bituminous
Coal
55.46
53.77
55.50
55.74
56.02
56.04
58.66
58.23
58.23
58.23
58.23
58.23
58.23
58.23
58.23
58.23
Natural
Gas
76.97
76.97
76.97
76.97
76.97
76.97
76.97
76.97
76.97
76.97
76.97
76.97
76.97
76.97
76.97
76.97
Residual
Fuel Oil
72.28
72.28
72.28
72.28
72.28
72.28
72.28
72.28
72.28
72.28
72.28
72.28
72.28
72.28
72.28
72.28
Diesel
Oil
63.07
63.07
63.07
63.07
63.07
63.07
63.07
63.07
63.07
63.07
63.07
63.07
63.07
63.07
63.07
63.07
LPG
54.63
54.63
54.63
54.63
54.63
54.63
54.63
54.63
54.63
54.63
54.63
54.63
54.63
54.63
NO
NO
Biogas
143.00
143.00
143.00
143.00
143.00
143.00
143.00
143.00
143.00
143.00
143.00
143.00
143.00
143.00
NO
NO
Industrial
Waste
111.83
111.83
111.83
111.83
111.83
111.83
111.83
111.83
111.83
111.83
111.83
111.83
111.83
111.83
NO
NO
Woodwood
waste
42.30
39.74
38.87
37.35
37.46
37.46
37.46
37.46
37.46
37.46
37.46
37.46
37.46
37.46
37.46
37.46
Coke
Oven
Gas
95.33
95.33
95.33
95.33
95.33
95.33
95.33
95.33
95.33
95.33
95.33
95.33
95.33
95.33
95.33
95.33
Black
Liquor
255.95
259.60
259.60
259.60
259.60
259.60
259.60
259.60
259.60
259.60
259.60
259.60
259.60
259.60
259.60
259.60
Blast
Furnace
Gas
Table 3.18 CO2 emission factors used for source category 1.A.1.a, 1990-2021
97.53
97.53
97.53
97.53
97.53
97.53
97.53
97.53
97.53
97.53
97.53
97.53
97.53
97.53
97.53
97.53
Petroleum
Coke
181.87
181.87
181.87
181.87
181.87
181.87
181.87
181.87
181.87
181.87
181.87
181.87
181.87
181.87
181.87
181.87
Oxygen
Steel
Furnace Gas
Turkish GHG Inventory Report 1990-2021
73
80.67
80.67
80.67
80.67
80.67
80.67
80.67
80.67
80.67
80.67
80.67
80.67
80.67
80.67
80.67
80.67
Coal
Tar
57.57
57.57
57.57
57.57
57.57
57.57
57.57
57.57
57.57
57.57
57.57
57.57
57.57
57.57
57.57
57.57
Refinery
Gas
(t/TJ)
Energy
1
73
1
Energy
Table 3.19 CH4 and N2O emission factors used for source category 1.A.1.a
(kg/TJ)
Fuel Types
CH4
N2O
Fuel Oil
Steam
0.8
0.3
Internal Combustion
Combined Heat
0.8
0.8
0.3
0.3
0.9
0.9
0.4
0.4
Liquid Fuels
Liquid Fuels
Diesel Oil, Naphtha
Steam
Internal Combustion
Combined Heat
0.9
0.4
Solid Fuels
Turkish Lignite and Sub-Bituminous and
Other Bituminous Coal
Dry bottom, wall fired
0.7
0.5
Fluidised Bed
Lignite (other types of
technology)
Sub-Bituminous and
Coking Coal
61
0.7
1.4
0.7
1.4
Natural Gas
Boiler
4
1
Gas Engine
Gas Turbine
4
4
1
1
Internal Combustion
Combined Heat
4
1
1
3
Other Fuels
Coke Oven Gas
1
0.1
Blast Furnace Gas
Oxygen Steel Furnace Gas
1
1
0.1
0.1
Coal Tar
LPG
1
1
1.5
0.1
Refinery Gas
Petroleum Coke
Other Petroleum Products
1
3
3
0.1
0.6
0.6
Black Liquor
74
1
3
2
Industrial Waste
Biomass
30
4
Biogas
Wood waste
1
11
1
7
Turkish GHG Inventory Report 1990-2021
74
Energy
1
Comparability and Accuracy through Nomenclature Change:
NCV of Turkish lignite differs significantly from that of the Energy Statistics Handbook and general fuel
literature. It is even lower than the lowest value of lignite in all reports of the Parties. Analysis reports
support this NCV data of Turkish lignite. Its average carbon content in 2021 is 29.6 kg/GJ, approaches
the upper limit of 2006 IPCC Guidelines (31.3 kg/GJ). To recategorize our local lignite, we renamed it
as "Turkish Lignite" to separate it from literature lignite and avoid misleading comparisons.
Carbon Capture and Storage in 1.A.1.a, if applicable
CO2 capture from flue gases and CO2 storage is not occurring in Türkiye, except pilot scaled research
fields.
Implied Emission Factor (IEF) Trends and Comments
IEFs were examined in the following table to see time-series consistency for solid, liquid, gaseous fuels,
and biomass.
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75 75
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Energy
Table 3.20 IEFs of fuels used for category 1.A.1.a, 1990-2021
CO2
Solid Fuels
Years
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Liquid Fuels
Gaseous Fuels
CH4
N2O
Biomass
Biomass
CHP
Electricity
Generation
CHP
Electricity
Generation
CHP
Electricity
Generation
CHP
Electricity
Generation
CHP
Electricity
Generation
120.03
125.53
130.35
134.30
132.06
132.06
111.14
105.74
120.84
107.77
119.49
117.31
112.17
111.78
113.41
112.78
110.51
109.76
107.83
105.10
102.89
105.23
100.49
101.35
101.98
102.26
101.49
102.14
100.79
101.13
74.03
76.05
70.62
69.63
60.18
61.41
64.07
69.34
76.97
76.97
76.97
76.97
76.97
76.97
76.88
76.74
75.55
76.09
76.10
75.41
73.23
73.84
75.79
73.52
74.00
73.24
76.24
75.73
76.36
72.95
58.23
58.23
58.23
58.23
58.23
58.23
58.23
58.23
58.23
58.66
56.04
56.02
55.75
55.50
53.77
55.46
58.23
58.23
58.23
58.23
58.23
58.23
58.23
58.23
58.23
58.66
56.04
56.02
55.75
55.50
53.77
55.46
4.80
2.37
4.57
2.41
1.11
1.54
2.29
1.40
1.38
1.25
1.76
1.93
1.63
2.02
2.92
1.11
1.44
1.08
1.10
1.10
1.09
1.07
1.04
1.02
1.31
1.81
2.98
4.62
2.13
1.68
3.06
1.82
1.03
1.31
1.74
1.23
1.22
1.14
1.45
1.56
1.38
1.61
1.65
1.06
1.25
1.05
1.05
1.05
1.05
1.04
1.02
1.01
1.19
1.49
2.18
3.17
IEFs of CO2 for solid fuels range from 101 to 140 t/TJ. It is mainly because of local Turkish lignite and
its share in solid fuels. Unlike literature lignite of statistics manual, Turkish lignite has a very low NCV,
about one-fifth of literature. Its share in the solid fuels affects the overall IEF causing a dramatic rise
and fall like its trend through the years 2001-2014 for 1.A.1.a.i.
IEFs of gaseous fuels do not change considerably over time; for example, IEFs of CO2 range from 53.77
to 58 t CO2/TJ. The reason for this change is the use of more gas chromatography results for analysis.
After 2000 the values of CHP Generation are the same as Electricity Generation.
Fluctuations in IEFs, especially declines, are mainly owing to the increasing share of biogas. Rising in
the trend, however, due to the share of black liquor. "Other Fossil Fuels" node is used for industrial
wastes data reporting consisting of the clinic and hazardous wastes.
Emission estimation with T2, T3 approach using plant-specific data is compared with the T1 emission
estimation using fuel data from national energy balance tables. Comparison with the T1 emission
estimation results is given in Table 3.21.
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Energy
Table 3.21 Comparison of GHG emissions from 1.A.1.a category ,1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
GHG emissions
with plant-specific data
GHG
Emission
Fuel
(kt CO2 consumption
eq.)
(TJ)
32 938
346 707
46 020
490 230
73 371
854 300
85 407
1 036 864
108 892
1 344 379
120 031
1 478 115
120 889
1 512 807
116 110
1 451 358
127 006
1 624 731
127 958
1 591 475
135 554
1 644 763
146 220
1 804 038
150 032
1 791 671
139 116
1 580 085
131 662
1 585 675
149 395
1 892 330
GHG emissions with
national energy balance
data
GHG
Emission
Fuel
(kt CO2 consumption
eq.)
(TJ)
35 135
360 733
48 744
509 424
80 991
906 121
84 970
1 032 611
113 798
1 424 949
125 560
1 552 324
126 359
1 581 349
119 945
1 519 613
136 476
1 726 151
127 582
1 493 912
135 622
1 584 311
150 275
1 749 863
156 740
1 751 999
147 507
1 548 046
139 561
1 541 974
158 502
1 915 698
GHG
emission
(kt CO2
eq.)
2 197
2 724
7 620
- 437
4 906
5 529
5 470
3 835
9 470
- 376
68
4 055
6 708
8 391
7 899
9 107
Difference
Fuel
consumption
(TJ)
14 026
19 194
51 821
-4 253
80 570
74 209
68 542
68 255
101 420
-97 563
-60 452
-54 175
-39 672
-32 039
-43 701
-23 368
The differences between T1 (national energy balance data) and T2, T3 (plant-specific data) results are
mainly related to the solid fuels, especially NCVs of Turkish lignite. Because of the Turkish lignite's
character, its NCV is lower than the lignite in literature. In plant-specific data, especially NCV of lignite
changes in a wide range as 1000-5400 kg/kcal. However, in national balance tables, an average NCV
value is around 2000 kcal/kg. Based on the quality of lignite used in a specific year, consumption in TJ
differs from the national energy balance data. This causes differences in emissions. For example, in
2005, 42% of lignite consumed in 1A1a category has NCVs less than 1500 kcal/kg, 58% has NCVs in
1700-6000, while NCV in the national balance table is used as 1400 kcal/kg for 2005. Therefore, lignite
consumption in CRF (plant-specific data) is 16,2% higher than national balance figures. On the other
hand, in 2014, 70% of lignite consumption in plant-specific data has NCV less than 2000, while in
national balance average NCV for lignite is used as 2100 kcal/kg. That results in a 12.1% decrease in
lignite consumption in TJ (Table 3.22). With the improvements in the energy balance table in recent
years, the difference between the plant-specific NCV and national balance average NCV has decreased
gradually, but there was an increase 1.1% in 2021.
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Table 3.22 Comparison of solid fuel consumption, 1990-2021
National energy balance data
Plant specific data
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Hard coal
consumption
Lignite
consumption
(kt)
474
1 246
1 942
5 174
6 935
10 116
11 760
11 707
13 826
16 126
17 966
19 485
23 437
23 321
24 235
21 470
29
39
52
47
55
60
54
45
51
48
58
62
71
74
61
71
(TJ)
7 761
15 866
30 130
108 533
154 215
230 759
287 433
279 108
332 019
389 644
436 847
466 990
555 837
548 539
553 834
492 101
(kt)
884
815
539
414
437
271
584
919
967
820
974
837
990
397
471
448
(TJ)
205 169
275 859
371 196
324 826
389 958
423 208
378 208
327 977
363 512
350 379
420 041
432 048
482 560
505 425
407 980
474 748
Hard coal
consumption
Lignite
consumption
(kt)
474
1 245
1 942
5 171
6 934
10 117
11 761
11 707
14 039
16 071
17 966
19 485
23 437
23 320
23 653
21 470
(kt)
29 884
39 815
52540
47 413
55 436
60 271
54 586
45 919
57 411
48 755
58 974
62 837
71 990
74 396
59 835
71 448
(TJ)
7 764
16 232
30100
108 531
154 272
247 412
287 616
279 238
337 447
388 577
436 657
466 466
555 596
547 944
555 774
491 515
(TJ)
202 692
277 051
373 143
272 791
391 552
423 429
378 692
328 369
407 424
349 232
424 445
438 039
487 535
512 511
412 198
480 125
Uncertainties and Time-Series Consistency
AD's have been compiled from all public electricity and heat production facilities by Turkish Electricity
Transmission Company (TEİAŞ) via survey. As a result of the change made in the activity data source,
no bias in total electricity production was published in the Activity Report of TEİAŞ. On the other hand,
compared to General Energy Balance Sheets AD of 1.A.1.a category had some bias in the amount of
fuel used. Experts of MENR determined uncertainties. For hard coal and Turkish lignite, there is no bias
for AD. There is no bias in 2021.
CO2 emission factors uncertainties
Solid fuels: Turkish lignite, other bituminous coal, sub-bituminous coal tar, coke oven gas, blast
furnace gas, and oxygen steel furnace gas have been used as solid fuels in 1.A.1.a category, and
combined uncertainty for solid fuels was calculated as 3.5% with Approach 1 method. In 2019
submission combined uncertainty estimates of solid fuels are quantified using the Monte Carlo
simulation. Uncertainty in solid fuels CO2 emissions in 2017 are estimated at -2.97% to +2.91% with
Approach 2 method. For more details, please refer to the Uncertainty chapter at the end of the Inventory
report in Annex 2.
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1
Liquid fuels: Residual fuel oil, diesel oil, naphtha, LPG, petroleum coke, refinery gas, and other oil
products have been used as liquid fuels in 1.A.1.a category. The combined uncertainty for these liquid
fuels was calculated as 4.24% with the Approach 1 method. In 2019 submission combined uncertainty
estimates of liquid fuels are quantified using the Monte Carlo simulation. Uncertainty in liquid fuels CO2
emissions in 2017 are estimated at ±2.65% with Approach 2 method. For more details, please refer to
the Uncertainty chapter at the end of the Inventory report in Annex 2.
Gaseous Fuels: Natural gas has been used as gaseous fuels in 1.A.1.a category, and uncertainty for
gaseous fuels was calculated as 1.5% with the Approach 1 method. In 2019 submission combined
uncertainty estimates of Gaseous fuels are quantified using the Monte Carlo simulation. Uncertainty in
Gaseous fuels CO2 emissions in 2017 are estimated at -1.46% to +1.47% with the Approach 2 method.
For more details, please refer to the Uncertainty chapter at the end of the Inventory report in Annex 2.
Biomass: Default EF in 2006 IPCC Guidelines on page 1.26 in the landfill gas distribution figure the
most frequent EF is 47 000 kg/TJ. The default value that we used for biomass is 54 600 kg/TJ. Bias in
between is 13.91% that was taken as uncertainty for biogas. Default EF in 2006 IPCC Guidelines on
page 1.27 in the wood/wood waste distribution figure the most frequent EF is 103 000 kg/TJ. The
default value that we used for wood/wood waste is 112 000 kg/TJ. Bias in between is 8% that was
taken as uncertainty for wood/wood waste. These two biomass fuels' uncertainties were combined using
a weighted average according to the generated heat amount. So the combined uncertainty for biomass
is 9.57%.
Other Fossil Fuels: Default EFs were taken from 2006 IPCC Guidelines for industrial wastes (mainly
composed of hazardous and clinic waste) and waste oils. On the other hand, there was no default
uncertainty value for industrial waste EF throughout the guideline.
EFs uncertainty for CH4 and N2O were taken from 2006 IPCC Guidelines Vol.2 page 2.38 Table 2.12 and
considered 100% (mid-value in the range).
Recalculation
There is no recalculation for this category.
Planned Improvement
There is no planned improvement in this category.
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3.2.4.2. Petroleum refining (Category 1.A.1.b)
Source Category Description:
All fossil fuels consumed for petroleum refineries process operations were covered in CRF category
1.A.1.b. However autoproducers within the refineries were included in the 1.A.1.a category. The share
of GHG emissions as CO2 eq. from petroleum refining in energy industries sector (1A1) was 4.9% in
2021 and it was also 6.2% in 1990.
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Table 3.23 Emissions from petroleum refining, 1990-2021
Share in
Fuel
1A1
CO2
CH4
N2O CO2 eq. consumption
category
(kt)
(kt)
(kt)
(kt)
(TJ)
(%)
2 289
0.07
0.014
2 295
32 091
6.2
2 984
0.09
0.016
2 991
43 872
5.9
2 914
0.09
0.017
2 922
41 749
3.8
4 265
0.12
0.019
4 273
66 632
4.7
3 531
0.08
0.012
3 537
58 930
3.1
4 326
0.09
0.012
4 331
73 409
3.5
4 210
0.09
0.012
4 216
72 549
3.3
3 549
0.08
0.010
3 554
60 957
3.0
3 424
0.07
0.009
3 429
59 412
2.6
5 503
0.12
0.015
5 510
96 958
4.1
8 347
0.16
0.022
8 358
129 038
5.8
8 717
0.16
0.019
8 727
136 691
5.6
6 224
0.11
0.013
6 231
96 319
4.5
8 136
0.13
0.014
8 143
115 930
5.4
7 991
0.14
0.016
7 999
126 775
6.4
7 756
0.13
0.014
7 764
128 082
4.9
Total emissions from petroleum refining were decreased by 236 kt CO2 eq. from 2020 to 2021 (3% of
decrease).
Methodological Issues:
Emissions from petroleum refining (CRF 1.A.1.b) were calculated according to 2006 IPCC T2 approach
by TurkStat for the years 1990-2017. Fuel consumption, NCVs and carbon content and CO2 emissions
are taken from plants which is also reported to the Directorate of Climate Change. CH4 and N2O
emissions from CRF category 1.A.1.b, have been estimated by using refineries total fuel consumption
and average NCVs for refineries and 2006 IPCC default EFs. For the year 2018-2021; MRV data reported
by plant were taken into consideration.
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Uncertainties and Time-Series Consistency:
All refineries are covered in the inventory. AD uncertainty of both liquid and gaseous fuels for refineries
is considered 2% as indicated in table 2.15 of 2006 IPCC Guidelines Vol.2. Since AD for refineries have
been taken directly from the refineries, uncertainty level for survey data were considered and to be
conservative the maximum uncertainty value was used.
EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 page 2.38. Uncertainty values were
considered as 7% for CO2 and 100% (mid value in the range) for CH4 and N2O.
Source-Specific QA/QC and Verification:
Quality control for 1.A.1.b category was performed on the basis of QA/QC plan. It was first confirmed
with refinery authorities that AD do not include the autoproducers consumption in the refinery. Calorific
values provided by the refinery are checked with national average NCVs of fuels to ensure the use of
NCVs in emission estimation. Also carbon content of fuels provided by the refinery checked with IPCC
default values to ensure they are in the range. Emissions from refineries were also calculated by using
national energy balances to compare results. There is 23% difference between the results for the year
2021. This difference may come from process gases which are used as fuel in plants and they can not
be seen in national balances table which are Plt 47 Hydrocracker Fuel Gas, Vacuum Off Gas, PSA off
gas, CCR coke, FCC coke, VDU off gas, Klaus tail gas, Vent Gas.
Recalculation:
In this submission, CO2 emissions from plants were taken from plants. Regulation on “Greenhouse Gases
Emission Monitoring“ went into force on April 25, 2012 with the publication of 28274 numbered official
gazette. And plants started to report their 2018 emissions in 2020. 2018-2021 CO2 emissions were taken
directly from plants and 2018-2020 emissions were recalculated.
Planned Improvement:
It is planned to revise emissions for the years 1990-2017 by taking into account plant specific emissions
data and the amount of petroleum refined for the years 2018-2021.
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3.2.4.3. Manufacture of solid fuels and other energy industries (Category 1.A.1.c)
Source Category Description:
All coke production facilities were covered in CRF category 1.A.1.c. The share of GHG emissions as CO2
eq. from manufacture of solid fuels category in 1A1 category was 1.5% in 2021 while it was 5.3% in
1990.
Table 3.24 Emissions from category 1.A.1.c, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
CO2
(kt)
1 953
1 429
1 432
1 289
1 724
1 908
1 982
1 925
1 976
2 311
2 117
2 415
2 322
2 384
2 231
2 347
CH4
(kt)
0.016
0.012
0.011
0.013
0.012
0.011
0.012
0.014
0.014
0.016
0.014
0.014
0.013
0.014
0.014
0.014
N2O
(kt)
0.005
0.001
0.001
0.003
0.001
0.001
0.001
0.001
0.001
0.002
0.001
0.001
0.001
0.002
0.001
0.001
CO2 eq.
(kt)
1 955
1 429
1 433
1 291
1 725
1 908
1 983
1 926
1 977
2 312
2 118
2 416
2 323
2 384
2 232
2 347
Fuel
consumption
(TJ)
15 581
11 623
10 944
12 074
11 560
11 473
12 348
13 829
14 220
15 987
13 792
14 052
13 438
13 786
14 154
13 949
Share in
1A1
Category
(%)
5.3
2.8
1.8
1.4
1.5
1.5
1.6
1.6
1.5
1.7
1.5
1.6
1.5
1.6
1.6
1.5
Total emissions from manufacture of solid fuels and other energy industries were increased by 115 kt
CO2 eq. from 2020 to 2021 (5.2% of increase) due to increase of fuel consumption.
Methodological Issues:
Emissions from manufacture of solid fuels (CRF 1.A.1.c) were calculated according to 2006 IPCC T3
approach by TurkStat. Coke production in integrated iron and steel production plants have been
considered in this category. Coke oven gas, blast furnace gas, and rarely natural gas have been used
for heating of coke ovens. Plant specific fuel consumption, NCVs and carbon content of fuels were
compiled from each plant. CO2 emissions from 1.A.1.c were calculated by using plant specific AD, carbon
contents of fuels and 2006 IPCC default oxidation rates. CH4 and N2O emissions from CRF category
1.A.1.c, have been estimated by using plant specific fuel consumption and NCVs and 2006 IPCC default
EFs.
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Uncertainties and Time-Series Consistency:
All coke production facilities were covered in the inventory. AD uncertainty for solid fuels for coke plants
were considered 2% as indicated in Table 2.15 of 2006 IPCC Guidelines Vol.2. Since AD have been
taken directly from the coke plants, uncertainty level for survey data were considered and to be
conservative the maximum uncertainty value was used.
EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 page 2.38. Uncertainty values were
considered as 7% for CO2 and 100% (mid value in the range) for CH4 and N2O.
Source-Specific QA/QC and Verification:
Quality control for 1.A.1.c category was performed on the basis of QA/QC plan. Calorific values provided
by the coke plants checked with national average NCVs of fuels to ensure the use of NCVs in emission
estimation. Also carbon content of fuels provided by the coke plants compared with 2006 IPCC default
values. Carbon mass balances on integrated iron and steel plants is done in the IPPU sector as a part
of QC/QA of activity data. This control also assures the fuel consumption in the coke ovens.
Recalculation:
Emissions for the years 1990,1991 and 2005-2020 were recalculated due to the calculation error. The
effect of error varie between -4.2% and 3.8%.
Planned Improvement:
Recently carbon mass balance on integrated iron and steel plants in cooperation with sector experts
have been done and good results are taken. There is no planned improvement at the moment.
3.2.5. Manufacturing industries and construction (Category 1.A.2)
Source Category Description:
This source category consists of manufacturing industries sectors. IPCC categorizes manufacturing
industry as iron and steel, nonferrous metal, chemicals, pulp, paper and print, food processing,
beverages and tobacco, non-metallic minerals and other industry. Until 2015 sectoral breakdown of
national energy balance tables are not fully in line with CRF categories. In the national energy balance
tables, pulp, paper and print sector were presented separately from 2011 onward. It was presented
under “other industries (1.A.2.g)” category before 2011. Food processing category included only sugar
industry for 1990-2010 periods. From 2011 onward all food processing industries were covered but
beverages and tobacco industry were still included under “other industries (1.A.2.g)” category. However,
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starting from 2015, national energy balance tables are detailed and provided energy consumption for
all economical activities so GHG emissions are allocated in line with CRF category.
Table 3.25 Fuel combustion emissions from manufacturing industry and construction,
1990-2021
Share in fuel
combustion
Fuel
(1A)
CO2
CH4
N2O
CO2 eq. consumption
category
Year
(kt)
(kt)
(kt)
(kt)
(TJ)
(%)
1990
37 004
2.17
0.35
37 162
386 908
27.5
1995
39 843
2.06
0.35
40 000
452 068
24.6
2000
57 657
3.91
0.64
57 945
629 742
27.6
2005
62 731
3.85
0.62
63 011
743 394
26.5
2010
52 120
3.00
0.47
52 333
639 363
18.8
2011
52 380
2.91
0.47
52 592
662 028
17.6
2012
60 821
3.28
0.52
61 059
760 755
19.6
2013
52 772
2.92
0.47
52 983
648 612
17.7
2014
54 233
2.93
0.46
54 444
680 149
17.3
2015
59 359
3.23
0.52
59 593
765 682
18.5
2016
59 840
3.29
0.53
60 079
785 911
17.7
2017
59 958
3.17
0.51
60 189
780 500
16.5
2018
59 369
4.26
0.65
59 669
814 062
16.4
2019
54 277
4.09
0.62
54 565
754 558
15.4
2020
59 869
4.49
0.69
60 186
814 780
16.9
2021
65 873
5.16
0.78
66 235
910 709
17.0
There is a sharp decrease in the emissions in 2008. This is due to the global economic downturn in
2008. GHG emissions from 1.A.2 category is 66.2 Mt CO2 eq. in 2021 which is 17% of total fuel
combustion and 11.8% of total national emissions (excluding LULUCF), whereas GHG emissions from
1.A.2 category was 37.2 Mt CO2 eq. which is 27.5% of total fuel combustion and 15.4% of total national
emissions (excluding LULUCF) in 1990. GHG emissions from 1.A.2 category have been increase by 6 Mt
CO2 eq. (10.1%) from 2020 to 2021.
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Table 3.26 GHG emissions from manufacturing industry and construction, 1990-2021
(kt CO2 eq.)
Food
Pulp, processing
Iron
Nonpaper beverages
Nonand ferrous Chemical
and
and metallic
Other
Year
Total
steel metals
s
print
tobacco minerals industries
1990 37 162
6 686
1 088
4 893
IE
2 909
8 262
13 324
1995 40 000
5 591
1 756
4 962
IE
1 690
8 794
17 207
2000 57 945
6 566
1 952
3 762
IE
2 152
9 249
34 263
2005 63 011
5 482
2 225
5 346
IE
2 125
14 882
32 949
2010 52 333
3 657
1 153
2 900
IE
882
21 359
22 383
2011 52 592
3 990
755
3 139
776
3 386
25 345
15 200
2012 61 059
4 380
1 173
4 646
743
3 536
27 939
18 643
2013 52 983
4 638
760
3 942
766
3 609
26 374
12 894
2014 54 444
4 992
989
3 705
888
3 328
28 257
12 285
2015 59 593
5 287
1 199
6 689
963
4 368
29 955
11 133
2016 60 079
4 190
1 407
6 071
1 076
4 971
31 633
10 733
2017 60 189
4 327
1 136
5 317
942
4 930
32 578
10 959
2018 59 669
4 273
809
7 032
982
5 089
30 220
11 266
2019 54 565
4 620
773
6 404
1 024
5 190
25 451
11 103
2020 60 186
5 633
694
6 840
1 270
5 877
29 618
10 255
2021 66 235
5 823
868
8 296
1 281
6 338
32 718
10 910
Non-metallic minerals and chemicals and other industries are the main contributors for GHG emissions
in 1.A.2 category. The share of non-metallic minerals is 49.4%.
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Table 3.27 Contribution of subsectors of manufacturing industries and construction,
2020-2021
Share in
manufacturi
Changes from
Emissions
ng industry
(kt CO2 eq.)
2020 to 2021
(%)
(kt CO2
2020
2021
2020 2021
eq.) (%)
60 186
66 235
1.A.2 Total
6 049
10.1
100.0 100.0
5 633
5 823
Iron and steel
191
3.4
9.4
8.8
694
868
Non-ferrous metals
173
25.0
1.2
1.3
6 840
8 296
Chemicals
1 456
21.3
11.4
12.5
Pulp, paper and
1 270
1 281
print
11
0.9
2.1
1.9
Food processing,
beverages and
5 877
6 388
461
7.8
tobacco
9.8
9.6
Non-metallic
29 618
32 178
minerals
3 100
10.5
49.2
49.4
10 255
10 910
Other industries
656
6.4
17
16.5
GHG emissions from 1.A.2 category have been increased by 10% between 2020 and 2021.
Manufacturing industry and construction category is a key category in terms of emission level and
emission trend of CO2 emissions from liquid, solid and gaseous fuels in 2020. It is also a key category
in terms of emission level of CO2 from other fossil fuels
Methodological Issues:
GHG emissions from 1.A.2 sector are calculated by using 2006 IPCC T1 and T2 approaches by TurkStat.
Fuel consumption data are taken from the national energy balance tables in both kt and ktoe units.
Country specific CO2 EFs are used when available, otherwise default CO2 EFs are used. All CO2 EFs are
given in table 3.18 under 3.2 Fuel Combustion Sector. All CH4 and N2O EFs are default. The default CH4
and N2O EFs for 1A2 sector are tabulated below. Due to the different types of fuels among many
industrial areas and varying composition of natural gas purchased by the countries, EFs show significant
interannual changes.
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Table 3.28 Defualt CH4 and N2O EFs for 1A2 sector
Emission Factors
Source
Sub Sectors
CH4 (kg/TJ)
N2O(kg/TJ)
1A2 sector
Coal products
10
1.5
Table 2.3
LPG
1
0.1
Table 2.3
Other Petroluem
3
0.6
Table 2.3
products
Derived gases
1
0.1
Table 2.3
Wood
30
4
Table 2.3
Natural gas
1
0.1
Table 2.3
Data on waste incineration for energy recovery have been compiled by TurkStat via survey until 2015
inventory year, after 2015 the waste incineration data were supplied by Directorate of Energy Efficiency
and Environment. The list of all waste incineration facilities having waste incineration licenses was
determined from the MoEU. Then the amount of waste incinerated and NCVs as MJ/kg by waste types
were compiled from all facilities listed by the MoEU. Plant specific waste incineration data and NCVs
were used in the GHG estimation. But, 2006 IPCC default EFs were used for CO2, CH4 and N2O emission
estimation.
Uncertainties and Time-Series Consistency:
The AD for manufacturing industry sector are completely taken from the national energy balance tables.
Uncertainties in the AD were determined by experts of MENR. AD uncertainties were given under
subcategories.
EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 page 2.38. Uncertainty values were
considered as 7% for CO2 and 100% (mid value in the range) for CH4 and N2O. The same uncertainties
were used for all subcategories of 1A2 except 1A2a.
Source-Specific QA/QC and Verification:
Quality control for 1A2 category was performed on the basis of QA/QC plan. Country specific carbon
content of fuels is checked with IPCC default values to ensure that they are in range. Reasonability of
IEFs are compared with the previous annual submission and with the 2006 IPCC Guidelines.
The table shows the change in the CO2 IEFs in the time series for liquid and solid fuels.
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Table 3.29 CO2 implied emission factors for 1A2 category
Year
Liquid
Solid Gaseous
1990
77.8
117.7
55.5
1995
79.4
117.9
55.5
2000
79.9
105.5
55.5
2005
81.8
103.5
55.5
2010
85.0
106.4
55.6
2011
84.7
104.2
56.6
2012
87.0
106.0
55.5
2013
88.9
105.6
55.5
2014
91.2
103.9
55.5
2015
92.0
99.0
55.7
2016
93.1
92.5
55.7
2017
93.2
97.7
55.6
2018
94.3
97.4
55.3
2019
93.8
99.1
53.7
2020
94.3
97.2
55.7
2021
92.8
98.1
55.4
It can be seen on the table that CO2 IEF for liquid fuels is increasing in the time series. This is because
the share of petroleum coke usage has been increased since 1990 while the share of other petroleum
products has been decreased since 1990.
On the other hand, it can be seen that CO2 IEF for solid fuels is decreasing in the time series. This is
because the share of lignite has been decreased since 1990 while the share of coking coal and coke has
been increased since 1990.
Recalculation:
1.A.2.a and 1.A.2.f recalculated due to the revision EF parameters for the year 2018. Recalculation
effected 2018 emission as 0.002% for 1.A.2.f and 1.4% for 1.A.2.a.
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Planned Improvement:
Prior to 2011 several manufacturing sectors that have their own categories (pulp, paper & print; nonmetallic minerals; food processing, beverages & tobacco) were not fully separated out in the national
energy balance and therefore some or all of the emissions from these categories were reported under
section 1A2g. This is because in the calculation of 1A2 subcategories the national energy balance tables
are used and national energy balance tables are not created as time series. All relevant institutions are
working together in order to overcome this inconsistency problem.
3.2.5.1. Iron and steel industries (Category 1.A.2.a)
Source Category Description:
The source categories cover emissions from the iron and steel industries including primary and
secondary steel producers and rolling mill plants.
Currently there are, 3 integrated facilities producing primary steel and 27 EAF mills producing secondary
steel in Türkiye. The share of GHG emissions as CO2 eq. from 1A2a in total 1A2 was 8.8% in 2021 while
it was 18.0% in 1990.
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Table 3.30 Fuel combustion emissions from iron and steel industry, 1990-2021
Fuel Share in
CO2
CH4
N2O CO2 eq. consumption
1.A.2
Year
(kt)
(kt)
(kt)
(kt)
(TJ)
(%)
6 686
0.10
0.017
6 678
51 756
1990
18.0
5 591
0.10
0.017
5 584
46 104
1995
14.0
6 566
0.09
0.016
6 559
49 855
2000
11.3
5 482
0.06
0.009
5 478
37 766
2005
8.7
3 657
0.08
0.012
3 652
47 148
2010
7.0
3 990
0.06
0.006
3 987
56 485
2011
7.6
4 380
0.05
0.005
4 377
50 211
2012
7.2
4
638
0.06
0.006
4
635
59
556
2013
8.7
4 992
0.06
0.006
4 989
61 286
2014
9.2
5 287
0.07
0.011
5 282
71 979
2015
8.9
4 190
0.06
0.008
4 186
63 997
2016
7.0
4 327
0.07
0.009
4 322
71 184
2017
7.2
4 273
0.12
0.016
4 265
70 018
2018
7.1
4 620
0.08
0.010
4 615
75 977
2019
8.5
5 633
0.09
0.010
5 627
83 337
2020
9.3
5 823
0.09
0.010
5 818
87 842
2021
8.8
Total emissions from iron and steel subcategory was increased by 191 kt CO2 eq. from 2020 to 2021
(3.4% of increase) due to increase of fuel consumption.
Methodological Issues:
GHG emissions from 1A2a sector were calculated by using 2006 IPCC T1 and T2 approaches by TurkStat.
Fuel consumption data were taken from the national energy balance tables in both kt and ktoe units.
Country specific CO2 EF are used when available, otherwise default CO2 EF are used. All CH4 and N2O
EFs are default.
Integrated iron and steel plants are energy intensive and complex plants. All emission sources were
identified together with experts from integrated facilities and emissions are allocated under appropriate
CRF categories. Allocation is made in the following way;
Emissions from electricity generation in auto-producer is considered under Energy1.A.1.a public electricity and heat production category (based on the reallocation of
autoproducers as explained above under source category description of section 3.2.5),
Emissions from the heating of coke ovens (for coke production) is considered under
Energy-1.A.1.c (manufacture of solid fuels) category,
Emissions from the heating of rolling mills and other miscellaneous combustion emissions
are considered under Energy-1.A.2.a iron and steel industry category,
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All carbonaceous fuels (including coke as reducing agent) used in blast furnaces and
sinter production are considered under IPPU-2.C.1 iron &steel production.
Uncertainties and Time-Series Consistency:
Plant specific AD is used for integrated iron and steel production facilities. The AD for EAFs is taken
from the national energy balance tables. Uncertainties in the AD were determined by experts of MENR
and TurkStat. AD uncertainties were determined as 10 % for liquid, gaseous, and solid fuels.
EFs uncertainty was determined by sector experts from TurkStat. Uncertainty values were determined
as 25% for CO2. EFs uncertainty for CH4 and N2O was taken from 2006 IPCC Guidelines Vol.2 page 2.38
Table 2.12 and considered as 100% (mid value in the range).
Source-Specific QA/QC and Verification:
Quality control for 1A2a category was performed on the basis of QA/QC plan. Emission trends are
analyzed. If there is a high fluctuation in the series, then AD and emission calculation are re-examined.
Recalculations:
There is recalculation due the the minor changes of EF parameters and resulted as 1.4% change in
2018 emissions.
Planned Improvement:
There is no planned improvement specific to this category.
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3.2.5.2. Non-ferrous metal (Category 1.A.2.b)
Source Category Description:
The share of GHG emissions as CO2 eq. from 1.A.2.b in total manufacturing industry fuel combustion
was 1.3% in 2021 while it was 2.9% in 1990.
Table 3.31 Fuel combustion emissions from non-ferrous metals, 1990-2021
Share in
Fuel
1.A.2
CO2
CH4
N2O
CO2 eq. consumption category
Year
(kt)
(kt)
(kt)
(kt)
(TJ)
(%)
1990
1 084
0.05
0.009
1 088
13 187
2.9
1995
1 750
0.08
0.014
1 756
22 300
4.4
2000
1 945
0.10
0.016
1 952
25 668
3.4
2005
2 219
0.08
0.013
2 225
33 266
3.5
2010
1 151
0.02
0.003
1 153
20 089
2.2
2011
754
0.02
0.002
755
13 016
1.4
2012
1 171
0.03
0.003
1 173
20 393
1.9
2013
759
0.02
0.002
760
13 379
1.4
2014
987
0.02
0.002
989
17 371
1.8
2015
1 197
0.03
0.004
1 199
20 103
2.0
2016
1 404
0.05
0.006
1 407
22 925
2.3
2017
1 134
0.04
0.005
1 136
18 034
1.9
2018
807
0.03
0.004
809
12 650
1.4
2019
771
0.03
0.003
773
13 016
1.4
2020
693
0.02
0.003
694
11 410
1.2
2021
866
0.03
0.004
868
14 381
1.3
The increase in total emissions of 1.A.2.b category from 2020 to 2021 is 173 kt CO2 eq. (25% of
increase).
Methodological Issues:
GHG emissions from 1.A.2.b sector were calculated by using 2006 IPCC Tier 1 and Tier 2 approaches
by TurkStat. Fuel consumption data were taken from the national energy balance tables in both kt and
ktoe units.
Country specific CO2 EFs are used for emission estimation. CH4 and N2O emissions from liquid, solid and
gaseous fuels have been estimated by using 2006 IPCC default EFs. GHG emissions from biomass were
estimated by using 2006 IPCC default EFs.
Uncertainties and Time-Series Consistency:
The AD were taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 21.21% for liquid, gaseous and solid fuels.
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EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 page 2.38. Uncertainty values were
considered as 7% for CO2 and 100% (mid value in the range) for CH4 and N2O.
Source-Specific QA/QC and Verification:
Quality control for 1.A.2.b category was performed on the basis of QA/QC plan. Emission trends are
analyzed. If there is a high fluctuation in the series, then AD and emission calculation are re-examined.
CO2, CH4 and N2O IEFs for all fuels are in the range of 2006 IPCC Guidelines but are changing based on
fuel mix used in the sector
Recalculation:
There is recalculation for the year 2018 due to the revision of the country specific emission factor for
solid fuels. Recalculation effected 2018 emission as 0.9%.
Planned Improvement:
There is no planned improvement specific to this category.
3.2.5.3. Chemicals (Category 1.A.2.c)
Source Category Description:
The source category includes manufacture of chemicals, fertilizer, basic pharmaceutical products and
rubber and plastic manufacturing. The share of GHG emissions as CO2 eq. from 1.A.2.c in total
manufacturing industry was 12.5% in 2021 while it was 13.1% in 1990.
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Table 3.32 Fuel combustion emissions from chemicals, 1990-2021
Share in
Fuel
1.A.2
CO2
CH4
N2O
CO2 eq. consumption category
Year
(kt)
(kt)
(kt)
(kt)
(TJ)
(%)
4 875
0.24
0.040
4 893
62 789
1990
13.2
4 948
0.17
0.030
4 962
71 612
1995
12.4
3 751
0.15
0.027
3 762
51 629
2000
6.5
5 334
0.16
0.026
5 346
82 163
2005
8.5
2 889
0.14
0.023
2 900
40 314
2010
5.5
3 132
0.12
0.016
3 139
49 224
2011
6.0
4 635
0.16
0.023
4 646
74 005
2012
7.6
3 929
0.19
0.027
3 942
57 487
2013
7.4
3
692
0.19
0.026
3
705
54
713
2014
6.8
6 672
0.26
0.034
6 689
106 985
2015
11.2
6 054
0.26
0.035
6 071
97 036
2016
10.1
5 306
0.18
0.023
5 317
87 051
2017
8.8
7 010
0.33
0.044
7 032
111 968
2018
11.8
6 385
0.30
0.040
6 404
101 747
2019
11.7
6 820
0.30
0.041
6 840
107 599
2020
11.4
8 275
0.32
0.043
8 296
134 076
2021
12.5
The increase in total emissions of 1.A.2.c category from 2020 to 2021 is 1 426 kt CO2 eq. (21.3% of
increase). The increase in GHG emission of this category is related to the increase in production of main
contributing sectors.
Methodological Issues:
GHG emissions from 1.A.2.c category were calculated using 2006 IPCC T1 and T2 approaches by
TurkStat. Fuel consumption data were taken from the national energy balance tables in both kt and
ktoe units.
Data on waste incineration for energy recovery have been compiled by TurkStat via official letter. The
amount of waste incinerated and NCVs as MJ/kg by waste types were compiled from the facilities. Plant
specific waste incineration data and NCVs were used in the GHG estimation.
Country specific CO2 EFs are used for emission estimation. GHG emissions from waste incineration were
estimated by using 2006 IPCC default EFs. CH4 and N2O emissions from liquid, solid and gaseous fuels
have been estimated by using 2006 IPCC default EFs.
Uncertainties and Time-Series Consistency:
The AD was taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 15.81% for liquid, gaseous and solid fuels.
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For other fossil fuels it was considered 2% as indicated in table 2.15 of 2006 IPCC Guidelines Vol.2.
Since AD for waste incineration have been taken directly from the petrochemical facility, uncertainty
level for survey data was considered and to be conservative the maximum uncertainty value was used.
EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 page 2.38. Uncertainty values were
considered as 7% for CO2 and 100% was taken (mid value in the range) for CH4 and N2O.
Source-Specific QA/QC and Verification:
Quality control for 1A2c category was performed on the basis of QA/QC plan. Emission trends are
analyzed. If there is a high fluctuation in the series, then AD and emission calculation are re-examined.
Also country specific carbon content of fuels is checked with IPCC default values to ensure they are in
the range. Reasonability of IEFs is compared with the previous annual submission and with the 2006
IPCC Guidelines.
Recalculation:
There is no recalculation.
Planned Improvement:
There is no planned improvement specific to this category.
3.2.5.4. Pulp, paper and print (Category 1.A.2.d)
Source Category Description:
The fuel consumption for production of pulp and paper products was separated in the national energy
balance tables in 2011. Therefore, emissions from this sector was evaluated under the 1.A.2.g other
industries category before 2011. In 2015 national energy balance, print sector is also covered under
1.A.2.d which is included under 1.A.2.g previously. The share of GHG emissions as CO2 eq. from 1.A.2.d
in total manufacturing industry fuel combustion was 1.9% in 2021.
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Table 3.33 Fuel combustion emissions from pulp, paper and print, 1990-2021
Share in
Fuel
1.A.2
CO2
CH4
N2O CO2 eq. consumption category
Year
(kt)
(kt)
(kt)
(kt)
(TJ)
(%)
19902010
NO,IE
NO,IE
NO,IE
NO,IE
NO,IE
NO,IE
774
0.04
0.005
776
11 127
2011
1.5
740
0.04
0.006
743
9 972
2012
1.2
764
0.04
0.005
766
11 118
2013
1.4
885
0.05
0.007
888
12 315
2014
1.6
960
0.06
0.008
963
12 946
2015
1.6
1 072
0.06
0.008
1 076
15 156
2016
1.8
939
0.05
0.007
942
13 014
2017
1.6
977
0.07
0.010
982
13 303
2018
1.6
1
019
0.06
0.009
1
024
14
181
2019
1.9
1 264
0.08
0.012
1 270
17 481
2020
2.1
1 275
0.09
0.013
1 281
17 234
2021
1.9
The increase in total emissions of 1.A.2.d category from 2020 to 2021 is 11 kt CO2 eq. (0.9% of
increase).
Methodological Issues:
GHG emissions from 1.A.2.d sector were calculated using 2006 IPCC T1 and T2 approaches by TurkStat.
Fuel consumption data were taken from the national energy balance tables in both kt and ktoe units.
Country specific CO2 EFs are used for emission estimation. CH4 and N2O emissions from liquid, solid and
gaseous fuels have been estimated using 2006 IPCC default EFs. GHG emissions from biomass were
estimated using 2006 IPCC default EFs.
Uncertainties and Time-Series Consistency:
The AD were taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 18% for liquid, gaseous and solid fuels.
EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 page 2.38. Uncertainty values were
considered as 7% for CO2 and 100% (mid value in the range) for CH4 and N2O.
Source-Specific QA/QC and Verification:
Quality control for 1.A.2.d category was performed on the basis of QA/QC plan. Emission trends are
analyzed. If there is a high fluctuation in the series, then AD and emission calculation are re-examined.
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Recalculation:
There is no recalculation in this sector.
Planned Improvement:
There is no planned improvement specific to this category.
3.2.5.5. Food processing, beverages and tobacco (Category 1.A.2.e)
Source Category Description:
The source category includes food processing, manufacturing of beverages, tobacco industry and sugar
industry. In the national energy balance tables, the fuel consumption for food processing sector was
separated in 2011. For 1990-2010 period only sugar industry, 2011-2014 period all food processing
industry were covered under this category but fuel consumption for beverages and tobacco industry
cannot be separated and was considered under the section other industries (1.A.2.g). In 2015 national
energy balance table, the beverages and tobacco industry are also included under 1.A.2.e category.
The share of GHG emissions as CO2 eq. from 1.A.2.e in total 1.A.2 GHG emissions was 7.8% in 1990
while it was 9.6% in 2021.
Table 3.34 Fuel combustion emissions from 1A2e category, 1990-2021
Share
Fuel in 1.A.2
CO2
CH4
N2O CO2 eq. consumption category
Year
(kt)
(kt)
(kt)
(kt)
(TJ)
(%)
2 892
0.24
0.037
2 909
27 656
1990
7.8
1
676
0.13
0.037
1
690
16
894
1995
4.2
2 130
0.19
0.056
2 152
20 673
2000
3.7
2 108
0.16
0.045
2 125
22 373
2005
3.4
877
0.05
0.012
882
12 244
2010
1.7
3 364
0.21
0.054
3 386
43 421
2011
6.4
3 515
0.21
0.054
3 536
46 695
2012
5.8
3 591
0.19
0.046
3 609
50 942
2013
6.8
3 310
0.19
0.047
3 328
46 330
2014
6.1
4 342
0.26
0.066
4 368
58 490
2015
7.3
4 943
0.28
0.069
4 971
69 245
2016
8.3
4 902
0.28
0.071
4 930
67 426
2017
8.2
5 047
0.49
0.099
5 089
77 611
2018
8.5
5 156
0.36
0.083
5 190
75 449
2019
9.5
5 838
0.41
0.097
5 877
83 228
2020
9.8
6 299
0.39
0.100
6 338
86 835
2021
9.6
Total GHG emission in 1.A.2.e category increased 461 kt CO2 eq. (7.8% of increase) from 2020 to 2021.
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Methodological Issues:
GHG emissions from 1.A.2.e sector were calculated by using 2006 IPCC T1 and T2 approaches by
TurkStat. Fuel consumption data were taken from the national energy balance tables in both kt and
ktoe units.
Country specific CO2 EFs are used for emission estimation. CH4 and N2O emissions from liquid, solid and
gaseous fuels have been estimated by using 2006 IPCC default EFs.
Uncertainties and Time-Series Consistency:
The AD were taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 18% for solid fuels, 5.00% for Liquid fuels
and 14.14% for gaseous fuels.
EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 page 2.38. Uncertainty values were
considered as 7% for CO2 and 100% was taken (mid value in the range) for CH4 and N2O.
Source-Specific QA/QC and Verification:
Quality control for 1A2e category was performed on the basis of QA/QC plan. Emission trends are
analyzed. If there is a high fluctuation in the series, then AD and emission calculation are re-examined.
Recalculation:
There is no recalculation in this sector.
Planned Improvement:
There is no planned improvement specific to this category.
3.2.5.6. Non-metallic minerals (Category 1.A.2.f)
Source Category Description:
Glass, cement and ceramic production is covered under this category. For 1990-2010 period only cement
industry was covered under this category and fuel consumption for glass and ceramic production were
considered under the other industries (1.A.2.g) for that period.
In Türkiye, some cement plants have waste incineration license which is given by MoEU. They use waste
as alternative fuels and also raw material. Wastes co-incinerated by license are: waste plastics, used
tires, waste oils, industrial sludge, tank bottom sludge and sewage sludge, etc. Waste incineration has
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been carried out since 2004 in cement industry. Waste incineration emissions from cement industry are
covered under this category.
1.A.2.f category is energy intensive sector. The share of GHG emissions as CO2 eq. from 1.A.2.f in total
manufacturing industry GHG emission was 49.4% in 2020 while it was 22.2% in 1990.
Table 3.35 Fuel combustion emissions from non-metallic minerals, 1990-2021
Share in
Fuel
1.A.2
CO2
CH4
N2O CO2 eq. consumption category
Year
(kt)
(kt)
(kt)
(kt)
(TJ)
(%)
8 216
0.64
0.100
8 262
85 781
1990
22.2
8 750
0.61
0.097
8 794
86 732
1995
22.0
9
204
0.63
0.100
9
249
94
531
2000
16.0
14 810
0.99
0.158
14 882
152 922
2005
23.6
21 240
1.66
0.258
21 359
209 775
2010
40.8
25 214
1.84
0.283
25 345
273 446
2011
48.2
27 797
2.00
0.309
27 939
298 718
2012
45.8
26 240
1.88
0.292
26 374
277 274
2013
49.8
28 122
1.89
0.295
28 257
309 282
2014
51.9
29 810
2.03
0.315
29 955
332 379
2015
50.3
31 482
2.09
0.330
31 633
360 842
2016
52.7
32 430
2.05
0.323
32 578
362 747
2017
54.1
30 049
2.44
0.370
30 220
351 235
2018
50.6
25 292
2.29
0.342
25 451
303 022
2019
46.6
29 440
2.54
0.382
29 618
351 842
2020
49.2
32 495
3.25
0.478
32 718
393 005
2021
49.4
The increase in total GHG emission of 1.A.2.f category is 3 100 kt CO2 eq. (10.5% of increase) from
2020 to 2021.
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Methodological Issues:
GHG emissions from 1.A.2.f sector were calculated by using 2006 IPCC T1 and T2 approaches by
TurkStat. Fuel consumption data were taken from the national energy balance tables in both kt and
ktoe units.
Data on waste incineration for energy recovery have been compiled by TurkStat via survey until 2015
inventory year, after 2015 the waste incineration data were supplied by General Directorate of
Renewable Energy. The amount of waste incinerated and NCVs as MJ/kg by waste types were compiled
from the facilities. Plant specific waste incineration data and NCVs were used in the GHG estimation.
Country specific CO2 EFs are used for emission estimation. GHG emissions from waste incineration and
biomass were estimated by using 2006 IPCC default EFs. CH4 and N2O emissions from liquid, solid and
gaseous fuels have been estimated by using 2006 IPCC default EFs.
Uncertainties and Time-Series Consistency:
The AD were taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 25.5% solid fuels, 27.8%for liquid fuels, and
29.2% for gaseous fuels.
For other fossil fuels and biomass, it was considered 2% as indicated in table 2.15 of 2006 IPCC
Guidelines Vol.2. Since AD for waste and sewage sludge incineration data have been taken directly from
the cement producers uncertainty level for survey data were considered and to be conservative the
maximum uncertainty value was used.
EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 page 2.38. Uncertainty values were
considered as 7% for CO2 and 100% (mid value in the range) for CH4 and N2O.
Source-Specific QA/QC and Verification:
Quality control for 1.A.2.f category was performed on the basis of QA/QC plan. Emission trends are
analyzed. If there is a high fluctuation in the series, then AD and emission calculation are re-examined.
CO2, CH4 and N2O IEFs for all fuels are in the range of 2006 IPCC guidelines but are changing based on
fuel mix used in the sector.
The emissions from this sector is compared with the production data of cement, glass and ceramics
industry. The emissions and production data is found to be consisting with each in concerning the time
series.
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Recalculation:
There is recalculation in 2018 emission and resulted as 0.002% change for this years
Planned Improvement:
There is no planned improvement specific to this category.
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3.2.5.7. Other industries (Category 1.A.2.g)
Source Category Description:
The manufacturing industry sectors which are not specified above are covered in this category. Based
on the improvements in the sectoral breakdown of national energy balance the coverage of this category
varies over times. As explained under section 3.2.5.4 and 3.2.5.5 some of the categories are included
under 1.A.2.g category until 2011. In 2016 national energy balance tables provide complete sectoral
breakdown of all economic activities, the coverage of this category is in line with CRF categorization.
The share of GHG emissions as CO2 eq. from 1.A.2.g in total manufacturing industry fuel combustion
was 16.5% in 2020 while it was 35.9% in 1990.
Table 3.36 Fuel combustion emissions from other industries, 1990-2021
Share in
Fuel
1.A.2
CO2
CH4
N2O CO2 eq. consumption category
Year
(kt)
(kt)
(kt)
(kt)
(TJ)
(%)
1990
13 258
0.91
0.145
13 324
145 738
35.9
1995
17 135
0.97
0.158
17 207
208 427
43.0
2000
34 068
2.75
0.422
34 263
387 385
59.1
2005
32 781
2.40
0.364
32 949
414 903
52.3
2010
22 310
1.05
0.158
22 383
309 794
42.8
2011
15 154
0.64
0.101
15 200
215 309
28.9
2012
18 587
0.79
0.123
18 643
260 761
30.5
2013
12 854
0.54
0.087
12 894
178 856
24.3
2014
12 248
0.53
0.080
12 285
178 853
22.6
2015
11 097
0.52
0.076
11 133
162 800
18.7
2016
10 699
0.50
0.072
10 733
156 710
17.9
2017
10 925
0.50
0.070
10 959
161 044
18.2
2018
11 215
0.77
0.106
11 266
177 276
18.9
2019
11 039
0.97
0.135
11 103
171 165
20.3
2020
10 185
1.05
0.145
10 255
159 883
17.0
2021
10 845
0.99
0.136
10 910
177 337
16.5
Total GHG emission in 1.A.2.g category increased 656 kt CO2 eq. (6.4% of increase) from 2020 to 2021.
Methodological Issues:
GHG emissions from 1.A.2.g sector were calculated by using 2006 IPCC T1 and T2 approaches by
TurkStat. Fuel consumption data were taken from the national energy balance tables in both kt and
ktoe units.
Country specific CO2 EFs are used for emission estimation. CH4 and N2O emissions from liquid, solid and
gaseous fuels have been estimated by using 2006 IPCC default EFs.
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Uncertainties and Time-Series Consistency:
The AD were taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 70.71% for liquid, gaseous and solid fuels.
EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 page 2.38. Uncertainty values were
considered as 7% for CO2 and 100% (mid value in the range) for CH4 and N2O.
Source-Specific QA/QC and Verification:
Quality control for 1.A.2.g category was performed on the basis of QA/QC plan.CO2, CH4 and N2O IEFs
for all fuels are in the range of 2006 IPCC Guidelines.
Recalculation:
There is recalculation for the year 2019 due to the revision of AD. Recalculation effected 2019 emission
as 0.12%.
Planned Improvement:
There is no planned improvement specific to this category.
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3.2.6. Transport (Category 1.A.3)
Estimation of emissions in Transport sector are carried out in the sub-categories listed below:
Domestic Aviation (1.A.3.a)
Road Transportation (1.A.3.b)
Railways (1.A.3.c)
Domestic water-borne Navigation (1.A.3.d)
Pipeline (other transportation) (1.A.3.e.i)
Emissions from this category were 238.2% higher in 2021 than in 1990, and on average emissions
increased by more than 7.4% annually.
In 2021, transport sector contributed to 91.2 Mt CO2 eq. emissions (Figure 3.13). GHG emissions (in
CO2 eq.) from transport sector as a share of total fuel combustion was 23.2% in 2021 while it was 20%
in 1990.
GHG emissions by transport sector and transport modes are given in Table 3.37 and 3.38 respectively.
As shown in Figure 3.14, road transportation is the major CO2 source contributing to 94.8% of transport
emissions in 2021. Contribution of domestic aviation is 3.1%, domestic water-borne navigation is 1.2%,
and railways are 0.4% in 2021. The share of pipeline transportation is 0.4%.
Figure 3.13 GHG emissions for transportation sector, 1990-2021
100
(Mt. CO2 eq.)
90
80
70
60
50
40
30
20
0
104
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
10
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Table 3.37 GHG emissions from transport sector, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
CO2
(kt.)
26 251
33 180
35 490
41 044
44 383
46 367
61 249
67 478
72 084
74 263
80 208
82 954
82 788
80 745
79 033
89 319
CH4
(kt.)
4.0
5.5
8.9
8.6
11.4
11.5
12.6
13.0
13.6
14.5
15.4
15.4
15.9
16.0
15.2
16.4
N2O
(kt.)
2.1
2.7
2.5
2.6
2.4
2.5
3.2
3.6
3.8
3.9
4.2
4.4
4.4
4.3
4.3
4.9
CO2 eq.
(kt.)
26 969
34 113
36 465
42 041
45 392
47 386
62 525
68 865
73 559
75 789
81 841
84 659
84 502
82 427
80 680
91 200
1
1
1
1
1
1
1
1
364
463
503
578
630
657
862
948
013
047
129
182
182
153
124
272
TJ
617
044
352
712
304
982
220
734
762
749
546
246
683
518
064
385
Table 3.38 GHG emissions by transport mode, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Road Domestic
Domestic
Other
transportation aviation Railways navigation transportation
24 777
923
721
509
39
29 760
2 775
768
726
83
31 850
3 099
713
623
180
35 532
4 089
757
1 299
364
39 941
2 862
517
1 682
390
40 899
3 344
532
2 242
370
56 310
3 727
492
1 614
381
62 889
3 754
505
1 154
563
66 967
4 090
562
1 348
593
69 309
4 205
480
1 147
647
75 595
4 281
374
970
621
78 706
3 838
413
944
869
78 907
3 688
435
931
657
76 720
3 509
400
1 217
581
76 601
2 164
323
1 264
328
86 499
2 856
356
1 128
361
Turkish GHG Inventory Report 1990-2021
Total
26 969
34 113
36 465
42 041
45 392
47 386
62 525
68 865
73 559
75 789
81 841
84 770
84 617
82 428
80 680
91 200
105 105
1
Energy
Figure 3.14 GHG emission trend by transport mode, 1990-2021
100
(Mt. CO2 eq.)
90
80
70
60
50
40
30
20
road
civil aviation
railways
navigation
pipeline
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
10
total
Throughout the time series, road transportation was the dominant source of emissions in the category,
responsible for between 83% (2004) and 92% (1990). The second largest source was domestic aviation,
ranging from 3% (1990) and 12% (2007). Between 2004 and 2009, when the share of emissions from
road transportation was at their lowest, the share from domestic aviation was the highest.
When analyzed in detail (Figure 3.15), there are different factors influencing GHG emissions resulting
from domestic aviation. Fuel consumption rose steadily in domestic aviation sector up to year 1999.
Because of economic reasons, fuel consumption values declined from 1999 to 2002. However, the
rearrangement policy of MoTI resulted in a sudden improvement in civil aviation sector. Then again, the
number of flights and fuel consumption started to increase. However, while the number of flights
annually increased, fuel consumption and GHG emissions showed inter-annual variation following
parallel trends. Especially, from 2007 to 2010 fuel consumption and GHG emissions declined by
approximately 50% while the number of flights increased by roughly 35%. This decoupling could
partially be explained with renewal of the Turkish air fleet and the global economic crisis, but the main
reason of decoupling could be determined with improving data quality in domestic aviation sector.
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Another breaking point in emissions was in 2019-2020 period. The number of flights and fuel
consumption decreased in 2020 due to pandemic conditions. As a result, GHG emissions declined
approximately 40% compared to 2019.
Figure 3.15 Comparison of number of flights, fuel consumption and GHG emissions of civil
aviation, 1990-2021
number of flights
fuel consumption (t)
CO2 eq GHG (t)
1 000 000
9 000
900 000
8 000
800 000
7 000
700 000
6 000
600 000
5 000
500 000
4 000
400 000
3 000
300 000
2 000
200 000
1 000
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
100 000
The other transportation mode needed to be analyzed is road transportation (Figure 3.16). In road
transportation until the year 1997, only diesel oil and gasoline were used. Utilization of LPG started in
1997 and consumption increased steadily. Then, diesel consumption and LPG consumption increased
while gasoline consumption declined. From 2007 to 2010, diesel consumption decreased probably
because of the global economic crisis. After that, there is remarkable rise in diesel consumption. When
analyzed in detail, it is determined that data of diesel used in agriculture sector have not been separated
from those used in road transportation since 2011. That is why there was a large increase in GHG
emissions resulting from diesel between 2011 (27 035 kt. CO2 eq.) and 2021 (59 736 kt. CO2 eq.), an
increase of 121%.
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Figure 3.16 Emission distributions by fuel types in road transportation, 1990-2021
(Mt. CO2 eq.)
80
70
60
50
40
30
20
Diesel
Gasoline
LPG
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
10
Biodiesel and natural gas
As seen from the figure 3.17, million passenger kilometers has been on an increasing trend over the
years. Especially, from 2008 onward the increase has been significant year by year. The reason behind
this is the number of cars has increased which leads to increase in the number of people traveling by
road. This trend reversed due to pandemic conditions in 2020. However, passenger-km by road has
recovered in 2021 and almost reached the 2019 values.
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Figure 3.17 Passenger-km by road, 1998-2021 (1)
400 000
(million passenger km)
350 000
300 000
250 000
200 000
150 000
100 000
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
50 000
(1) https://data.oecd.org/transport/passenger-transport.htm
Figure 3.18 represents million passenger kilometers by rail. In recent years, Türkiye has put a lot of
emphasis on redeveloping and modernizing the rail infrastructure which has had an effect on the number
of passenger kilometers over the years. The modernization of the rail infrastructure requires a temporary
stoppage of railway transport until the infrastructure construction is complete. That is the reason of the
fluctuation in emissions from 2011 to 2020. But in 2020 the number of passenger kilometers decreased
significantly in railway sector which is affected by the covid-19 pandemic. However, passenger-km by
railway has started to recover in 2021.
Figure 3.18 Passenger-km by railway, 1998-2021 (2)
16 000
(million passenger km)
14 000
12 000
10 000
8 000
6 000
4 000
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
2 000
(2) https://data.oecd.org/transport/passenger-transport.htm
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Source Category Description:
The source category comprises GHG emissions resulting from transport sector as follows; aviation,
railways, road transportation, navigation and pipeline transport (other transportation). In addition to
these, international aviation and international navigation were also included in this category. Among
these categories;
Domestic aviation in terms of CO2 emissions from jet fuel (level and trend),
Road transportation in terms of CO2 emissions from diesel, LPG, gasoline and other ones (biofuel
and natural gas) (level and trend),
Domestic navigation in terms of CO2 emissions from diesel and fuel oil,
Emissions from civil aviation were covered as international aviation and domestic aviation under
(1.A.3.a.i) and (1.A.3.a.ii) categories.
Road transportation is the largest contributor to transport emissions and estimations were made under
a wide variety of vehicle types using not only gasoline but also diesel fuel and LPG. It is covered under
category (1.A.3.b).
Emissions from railways were reported under category (1.A.3.c).
Emission estimates from the navigation section cover international water-borne navigation (1.A.3.d.i)
and domestic navigation-coastal shipping (1.A.3.d.ii).
Pipeline transportation emissions are reported under the category other transportation (1.A.3.e.i).
Methodological Issues:
Türkiye implements Tier 1 and Tier 2 methodologies to estimate GHG emissions of mobile sources for
the time series 1990-2019, as shown in equation below. The general method is presented here, and
any specific circumstances in the implementation of the method is described separately for each
category.
𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 = �[𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹� ∗ 𝐸𝐸𝐸𝐸� ]
�
Where:
Emission = Emissions of CO2 (kg)
Fuela = fuel sold (TJ)
EFa = emission factor (kg/TJ). This is equal to the carbon content of the fuel multiplied by 44/12.
a = type of fuel (e.g. petrol, diesel, natural gas, LPG etc.)
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All EFs were taken from the 2006 IPCC Guidelines.
The IPCC methods used in transport sector calculations are listed in Table 3.39.
Table 3.39 Method used in the calculation of GHG emissions by transport modes
Modes of transport
Domestic aviation
CO2 CH4
√
√
N2O
√
Tier I
X
Tier II
X
Road transportation
√
√
√
X
X
Railways
√
√
√
X
X
Domestic navigation
√
√
√
X
X
Pipeline transportation
√
√
√
X
X
For the transport source category (1.A.3), the following data sources were used to estimate and
calculate emissions:
Fuel consumption values for source categories (1.A.3.a.i), (1.A.3.a.ii), (1.A.3.b), (1.A.3.c),
(1.A.3.d.i), (1.A.3.d.ii) and (1.A.3.e.i) were provided by MENR in the form of the national energy
balance tables, MAPEG and Petroleum Pipeline Corporation.
Air traffic data is provided by Directorate of General (DG) of State Airports Authority for National
Aviation (1.A.3.a.ii). Emissions were estimated by using IPCC T2 methodology explained in IPCC
Guidelines for National GHG Inventories (IPCC, 2006). The calculation methodology is based on
the national energy consumption data and air traffic data for each airport in terms of aircraft
type. For the activities, default EFs were used. Air traffic data which consists of landing and
take-off (LTO) cycles and cruise is processed for all 55 airports in Türkiye. All activities below
914 m were included in LTO cycle; movements over 914 m altitude were covered in the cruise
phase. Domestic flights for all aircraft types have been accounted considering estimated
individual fuel consumption values. The necessary EFs for LTO and cruise for each type of
aircraft have been chosen from IPCC reference manual.
The emissions from road transportation were calculated by using IPCC Tier 1&2 methodology.
Other values for database improvement were provided from DG of Highways, DG of Turkish
State Railways and DG of Civil Aviation.
Source-Specific QA/QC and Verification:
The IPCC Good Practice Guidance is used for the QA/QC procedures of National GHG Emission Inventory.
For the quality control purposes, GHG emissions, estimated by using T2 approach, were compared with
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emissions estimated by using T1 approach. If the difference between the emission values obtained by
both methods is less than 5%, calculations were considered to be appropriate.
3.2.6.1. Civil aviation (Category 1.A.3.a)
The domestic aviation source category was a key category in 2021, in terms of both the level and trend
analysis of CO2 emissions from the jet fuel.
Figure 3.19 and Figure 3.20 illustrate the total emissions and the emissions of CH4 and N2O increasing
trends as CO2 eq. CO2 eq. emissions have increased approximately 209% since 1990 and reached to
2.85 Mt CO2 in 2021. The calculated amounts of CH4 and N2O emissions were 1.26 kt. CO2 eq. and 29.29
kt. CO2 eq. in 2021 respectively.
Figure 3.19 GHG emissions for domestic aviation, 1990-2021
7 000
(kt. CO2 eq.)
6 000
5 000
4 000
3 000
2 000
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2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1 000
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Figure 3.20 CH4 and N2O emissions for domestic aviation, 1990-2021
70
(kt. CO2 eq.)
60
50
40
30
20
CH4
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
10
N2O
Methodological issues:
Emissions were estimated by using the IPCC T2 methodology explained in the 2006 IPCC Guidelines. In
the Tier 2 method, it is necessary to divide the operations of aircraft into landing and take-off (LTO)
and cruise phases, as implemented through equations below. The calculation methodology is based on
the national energy consumption data and air traffic data for each airport in terms of aircraft type.
Collection of activity data:
Air traffic data which consists of LTO cycles and cruise is provided by Directorate of General of State
Airports Authority for all civil airports in Türkiye. The number of LTO values for all aircraft types were
provided for each airport. All activities below 914 m were included as LTO cycles; movements over
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914 m altitude were covered in the cruise phase. Domestic flights for all aircraft types have been
accounted considering estimated individual fuel consumption values in the year 2021 total number of
LTO’s in domestic travel for all aircraft types is 738 352. Passenger and freight traffic from 2006 to 2021
is also given in Figure 3.21 and Figure 3.22 respectively. Figure 3.23 shows the number of domestic
LTOs for Turkish airports from 1990 to 2021.
Figure 3.21 Passenger traffic, 2006-2021
250
(million)
200
150
100
50
0
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
domestic
114
international
transit
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Figure 3.22 Freight traffic, 2006-2021
4 500 000
(tonnes)
4 000 000
3 500 000
3 000 000
2 500 000
2 000 000
1 500 000
1 000 000
500 000
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
domestic
international
total
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EFs for all aircraft types were obtained from 2006 IPCC Guidelines for National GHG Inventories (2006
IPCC Guidelines). Default values were applied for aircrafts where specific data is not available. In the
light of these explanations, the total fuel consumption for domestic aviation is 0.895 Mt. To calculate
the LTO fuel consumption, Türkiye multiplied the number of LTOs by the relevant LTO fuel consumption
factors. The calculated total LTO fuel consumption is 0.49 Mt. To estimate cruise fuel consumption,
Türkiye subtracts LTO fuel consumption from total fuel consumption for each year of the time series. In
2021, cruise fuel consumption is 0.41 Mt.
Figure 3.23 Number of domestic LTO, 1990-2021
1 000 000
900 000
800 000
700 000
600 000
500 000
400 000
300 000
200 000
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
100 000
Choice of Emission Factor:
LTO fuel consumption factors, as well as default CO2, CH4 and N2O emission factors for all aircraft types
were obtained from the 2006 IPCC Guidelines (Table 3.6.9). Default emission factor values were applied
for aircrafts where specific data are not available. The resulting CO2 emission values of 1.55 Mt and 1.28
Mt were reported for LTO and cruise respectively. CO2, CH4 and N2O emission values are given in Table
3.40.
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Table 3.40 GHG emissions from domestic aviation, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
CO2
(kt)
914
2 748
3 068
4 048
2 833
3 308
3 688
3 715
4 047
4 162
4 237
3 798
3 648
3 472
2 141
2 825
CH4
(kt)
0.01
0.04
0.04
0.05
0.04
0.04
0.05
0.05
0.05
0.06
0.06
0.06
0.07
0.06
0.04
0.05
N2O
(kt)
0.03
0.09
0.10
0.13
0.09
0.12
0.13
0.13
0.14
0.14
0.14
0.13
0.13
0.12
0.07
0.098
CO2 eq.
(kt)
923
2 775
3 099
4 089
2 862
3 344
3 727
3 754
4 090
4 205
4 281
3 838
3 688
3 509
2 164
2 856
13
38
43
57
40
47
52
52
57
58
59
53
52
49
30
39
TJ
030
670
296
276
043
199
686
467
243
824
884
259
217
140
233
926
Table 3.41 GHG emissions for LTO and cruise in domestic aviation, 2021
(kt.)
CO2
CH4
N2O
Jet kerosene
Total
2 825
0.05
0.098
895
LTO
1 547
0.05
0.058
489
Cruise
1 279
-
0.041
406
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Table 3.42 IEFs of domestic aviation 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Activity
TJ
13 030
38 670
43 296
57 276
40 043
47 199
52 686
52 467
57 243
58 824
59 884
53 259
52 217
49 140
30 233
39 926
CO2
t/TJ
70.13
71.06
70.86
70.68
70.75
70.09
69.99
70.81
70.70
70.75
70.75
71.32
69.86
70.66
70.81
70.78
IEFs
CH4
kg/TJ
0.96
0.95
0.86
0.80
0.95
0.92
0.88
0.92
0.90
0.98
0.99
1.12
1.27
1.22
1.31
1.26
N2O
kg/TJ
2.29
2.29
2.31
2.31
2.36
2.46
2.45
2.45
2.44
2.39
2.39
2.43
2.43
2.43
2.45
2.46
Uncertainties and Time-Series Consistency:
The AD was taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 5.48% liquid fuels.
EF uncertainty for CO2 was considered as 5% as indicated in 2006 IPCC Guidelines Vol. 2 page 3.69.
For CH4 and N2O mid value of default uncertainty given in 2006 IPCC Guidelines as 80% and 85% were
considered respectively.
Recalculation:
There is no recalculation for this category.
Planned Improvement:
Work on data quality regarding fuel consumption and air traffic will be continued in co-operation with
experts from related institutions.
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Energy
1
3.2.6.2. Road transportation (Category 1.A.3.b)
Road Transportation source category was a key category, in terms of emission level of CO2 from diesel,
LPG and gasoline in 2021. This category was also a key category in terms of emission trend of CO2 from
LPG, gasoline and diesel. The results according to IPCC Tier 1&2 were in Table 3.43.
Table 3.43 GHG emissions from road transportation, 1990-2021
CO2
CH4
N2O CO2 eq.
Year
(kt.)
(kt.)
(kt.)
(kt.)
TJ
1990
24 143
3.9
1.804
24 777
335 589
1995
28 942
5.3
2.301
29 760
404 093
2000
30 988
8.8
2.158
31 850
439 986
2005
34 668
8.4
2.195
35 532
488 494
2010
39 033
11.2
2.106
39 941
554 362
2011
39 995
11.2
2.093
40 899
567 688
2012
55 142
12.4
2.882
56 310
775 067
2013
61 607
12.8
3.224
62 889
864 602
2014
65 608
13.4
3.434
66 967
921 018
2015
67 889
14.3
3.561
69 309
955 968
2016
74 055
15.2
3.887
75 595 1 041 071
2017
77 094
15.2
4.132
78 706 1 095 446
2018
77 289
15.7
4.116
78 907 1 100 570
2019
75 131
15.8
4.005
76 720 1 072 046
2020
75 024
15.0
4.035
76 600 1 066 461
2021
84 699
16.2
4.680
86 499 1 206 164
In road transportation, gasoline, diesel, LPG, natural gas and biodiesel were used as fuel. Road
transportation being the major source within the transportation sector contributed 86.5 Mt of CO2 eq.
in 2021 (Figure 3.24). Emissions of CH4 reached 0.41 Mt CO2 eq. and N2O reached 1.40 Mt CO2 eq. in
2021 (Figure 3.25). Emissions from the consumption of biofuels were taken into consideration for CH4
and N2O emissions.
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Figure 3.24 GHG emissions for road transportation, 1990-2021
100
(Mt. CO2 eq.)
90
80
70
60
50
40
30
20
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
10
CO2 emissions according to fuel types are illustrated in Figure 3.26. Most important portion of CO2
emission is occurred from diesel fuel consumption, which is about 78% of total emissions of road
transportation.
Figure 3.25 CH4 and N2O emissions for road transportation, 1990-2021
1 600
(kt. CO2 eq.)
CH4
N2O
1 400
1 200
1 000
800
600
400
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2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
200
120
1
Energy
Figure 3.26 CO2 emission distributions by fuel types (%), 2021
1
11
10
Diesel
Gasoline
Lpg
Biofuel&natural gas
78
Methodological issues:
CO2 emissions were calculated by multiplying estimated fuel consumption by a default or countryspecific, depending on the fuel emission factor i.e., a Tier 1 or Tier 2 method. Country-specific carbon
contents for diesel and natural gas are used. CO2 emissions resulting from those fuel types were
estimated with Tier 2. CO2 resulting from gasoline, LPG and CH4 and N2O emissions were estimated by
applying default emission factors from the 2006 IPCC Guidelines.
Collection of Activity Data:
Fuel data used in the road transportation are taken from the national energy balance tables issued by
MENR.
Choice of Emission Factor:
To estimate CO2 emissions, Türkiye applies the country specific (diesel, natural gas) and default carbon
contents as contained in the 2006 IPCC Guidelines.
Source-Specific QA/QC and Verification:
Fuel consumption data in road transportation provided by the MENR were compared with those of DG
of Mining and Petroleum Affairs, reported to IEA.
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To verify data documentation, the assumptions and selection criteria on data, EFs and other calculation
parameters as well as the completeness of inventory dossiers were checked for correspondence with
the 2006 IPCC Guidelines.
In addition, GHG emissions from road transportation were also calculated by using COPERT V program
for the years 2016, 2017 and 2018. COPERT V results were compared with the results regarding current
methodology (Tier 1, Tier 2) and in terms of CH4, COPERT result was found by far less than results
obtained by using current methodology due to usage of default emission factors. Moreover, results
obtained from COPERT V were also compared with CRF values of several countries (e.g., Denmark,
United Kingdom, Greece, Italy) using COPERT methodology. Considered comparison of implied emission
factors, values were found almost in line with each other.
Table 3.44 Comparison of COPERT and current methodology for GHG emissions from road
transportation, 2016-2018
CO2 (kt)
CH4 (kt)
N2O (kt)
CO2 eq. (kt)
Tier 1 COPERT
Tier 1 COPERT
Tier 1&2 COPERT
Year
Tier 2 COPERT
2016
74 055
74 663
15.2
4.952
3.9
2.637
75 595
75 573
2017
77 094
77 289
78 701
15.2
5.677
4.1
2.807
78 706
79 679
79 015
15.7
5.230
4.1
2.866
78 907
80 000
2018
With this calculation results obtained from COPERT for the years 2016-2018.
Uncertainties and Time-Series Consistency:
The AD was taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 10.05% for liquid fuels.
EF uncertainty for CO2 was considered as 5% (max. value of given range) as indicated in 2006 IPCC
Guidelines Vol. 2 page 3.29. For CH4 and N2O mid value of default uncertainty given in 2006 IPCC
Guidelines as 250% were considered.
Recalculations:
There is no recalculation for this category.
Planned Improvement:
There is no planned improvement for this sector.
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3.2.6.3. Railways (Category 1.A.3.c)
The railways source category was not a key category in 2021. Figure 3.27 and Figure 3.28 show the
total, CH4 and N2O emissions as CO2 eq. respectively. CO2 eq. emissions have declined 50.6% since
1990. The emissions calculated for railways is 0.356 Mt CO2 eq. in 2021.
Table 3.45 GHG emissions from railway, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
CO2
(kt)
651
688
638
678
462
476
441
452
503
429
335
369
388
358
289
318
CH4
(kt)
0.03
0.04
0.04
0.04
0.03
0.03
0.02
0.03
0.03
0.02
0.02
0.02
0.02
0.02
0.02
0.02
N2O
(kt)
0.23
0.27
0.25
0.26
0.18
0.19
0.17
0.18
0.20
0.17
0.13
0.15
0.15
0.14
0.11
0.13
CO2 eq.
(kt)
721
768
713
757
517
532
492
505
562
480
374
413
435
400
323
356
Turkish GHG Inventory Report 1990-2021
8
9
8
9
6
6
6
6
6
5
4
5
5
4
3
4
TJ
670
348
686
230
296
485
001
154
843
848
561
105
373
946
995
404
123 123
0
124
CH4
Turkish GHG Inventory Report 1990-2021
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
90
1992
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
0
1991
900
1990
1
Energy
Figure 3.27 GHG emissions for railways, 1990-2021
(kt. CO2 eq.)
800
700
600
500
400
300
200
100
Figure 3.28 CH4 and N2O emissions from railways, 1990-2021
(kt. CO2 eq.)
80
70
60
50
40
30
20
10
N2O
124
Energy
1
Methodological issues:
The IPCC Tier 1&2 approach has been used to estimate CO2, CH4 and N2O emissions for this
subcategory. The Tier 1 approach has been used to estimate CH4 and N2O emissions.
Collection of Activity Data:
Energy consumption values for railways were provided by MENR in the form of national energy balance
tables.
Choice of Emission Factor:
To estimate CO2 emissions, Türkiye applies the country specific carbon content. Türkiye does not modify
the emission factors for CH4 and N2O to consider engine design parameters.
Source-Specific QA/QC and Verification:
In terms of calculations made by alternative methods; verification on this category was made by using
different AD (passenger/km) and different EFs provided in the document ‘‘Structure of Costs and
Charges Review – Environmental Costs of Rail Transport Final Report to the Office of Rail Regulation
(August 2005)’’. As a result of the verification, it was observed that the results obtained were almost
identical in each calculation methodology. In addition, fuel consumption values obtained from Energy
Balance Table were compared with those reported to IEA.
Uncertainties and Time-Series Consistency:
The AD was taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 2% for liquid fuels.
EF uncertainty for CO2 was derived from 2006 IPCC Guidelines Vol. 2 table 3.4.1 as 1.5% for liquid
fuels. For CH4, EF uncertainties were derived as 105% for liquid fuels. For N2O EFs uncertainties were
derived as 142% for liquid fuels.
Recalculations:
There is no recalculation for this category.
Planned Improvement:
There is no planned improvement for this category.
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3.2.6.4. Water-borne navigation (Category 1.A.3.d)
The domestic water borne navigation source category was not a key category in 2021. The data
availability is limited in this sub-sector. In domestic water-borne navigation diesel and residual fuel oil
were consumed as a fuel.
Domestic water-borne navigation contributed 1.26 Mt of CO2 in 2021. While CH4 2.69 kt. CO2 eq. and
N2O emissions were 9.17 kt. CO2 eq. (Figure 3.29 and 3.30). Overall, between 1990 and 2021 emissions
from water-borne navigation increased by 121.7%.
Table 3.46 GHG emissions from domestic navigation, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
126
CO2
(kt)
504
719
617
1 286
1 664
2 218
1 598
1 142
1 334
1 136
960
934
921
1 204
1 251
1 116
CH4
(kt)
0.05
0.07
0.06
0.12
0.16
0.21
0.15
0.11
0.13
0.11
0.09
0.09
0.09
0.12
0.12
0.11
N2O
(kt)
0.01
0.02
0.02
0.03
0.05
0.06
0.04
0.03
0.04
0.03
0.03
0.03
0.03
0.03
0.03
0.03
CO2 eq.
(kt)
509
726
623
1299
1682
2242
1614
1154
1348
1147
970
944
931
1 217
1 264
1 128
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6
9
8
17
22
30
21
15
18
15
12
12
12
16
17
15
TJ
624
444
167
225
658
058
670
486
083
369
958
836
650
653
265
390
126
1
Energy
Figure 3.29 GHG emissions from domestic water-borne navigation, 1990-2021
2 500
(kt. CO2 eq.)
2 000
1 500
1 000
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
500
Figure 3.30 CH4 and N2O emissions from domestic water-borne navigation, 1990-2021
20
(kt. CO2 eq.)
CH4
N2O
18
16
14
12
10
8
6
4
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
2
Methodological issues:
The IPCC Tier 1&2 approach has been used to estimate CO2, CH4 and N2O emissions for this
subcategory. The Tier 1 approach has been used to estimate CH4 and N2O emissions.
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Collection of Activity Data:
Energy consumption values for domestic navigation were provided by MENR in the form of national
energy balance tables.
Choice of emission factor:
For CO2 estimation, country-specific carbon contents were used. The EFs for CH4 and N2O are taken
from IPCC 2006/CORINAIR and set to 7 and 2 kg per TJ respectively.
Source-Specific QA/QC and Verification:
On the energy balance table provided by the MENR, diesel and fuel oil consumption values were
compared with the values provided by MoTI DG of Maritime, as well as the Annual Activity Report results
of Energy Market Regulatory Authority and with the “Domestic Navigation” fuel consumption amount
values which DG of Mining and Petroleum Affairs regularly reports to the IEA.
Uncertainties and Time-Series Consistency:
The AD was taken from MENR. AD uncertainties were determined as 15% for liquid fuels.
EF uncertainty for CO2 was considered as 1.5% for liquid fuels as indicated in 2006 IPCC Guidelines Vol.
2 page 3.54. It was considered as 50% for CH4 and 140% for N2O.
Recalculations:
There is no recalculation for this category.
Planned Improvement:
There is no planned improvement for this category.
3.2.6.5. Pipeline transport (Category 1.A.3.e.i)
This category covers combustion related emissions from the operation of pump stations and
maintenance of pipelines. Transport via pipelines includes transport of gases, liquids, slurry and other
commodities via pipelines. In Türkiye, natural gas is used to carry out operations mentioned above.
Pipeline transport contributed 0.36 Mt of CO2 in 2021. Table 3.47 shows the trend in GHG emissions
from pipeline transport.
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Table 3.47 The trend in GHG emissions from pipeline transport, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
CO2
(kt)
39
83
178
360
386
371
377
557
587
662
617
868
656
581
328
360
CH4
(kt)
0.0007
0.0015
0.0032
0.0065
0.0069
0.0066
0.0068
0.0100
0.0106
0.0117
0.0111
0.0156
0.0119
0.0108
0.0061
0.0065
N2O
(kt)
0.00007
0.00015
0.00032
0.00065
0.00069
0.00066
0.00068
0.00100
0.00106
0.00117
0.00111
0.00156
0.00119
0.00108
0.00061
0.00065
CO2 eq.
(kt)
39
83
179
360
387
371
378
557
588
663
617
869
657
582
328
361
1
3
6
6
6
6
10
10
11
11
15
11
10
6
6
TJ
705
489
217
487
945
552
796
025
575
897
073
601
873
824
109
501
Figure 3.31 GHG emissions from pipeline transport, 1990-2021
1 000
16 000
(kt. CO2 eq.)
900
14 000
800
12 000
700
10 000
600
8 000
500
400
6 000
300
4 000
200
2 000
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
100
GHG emissions
TJ
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Methodological issues:
In emissions calculation, the 2006 IPCC Guidelines Tier 1&2 approaches are used. CO2 emissions were
calculated by multiplying estimated fuel consumption by a country-specific emission factor. CH4 and N2O
emissions were estimated by applying default emission factors from the 2006 IPCC Guidelines.
Collection of Activity Data:
Fuel consumption data for pipeline transport were provided by energy balance table provided by the
MENR.
Choice of emission factor:
For CO2 estimation, country-specific carbon content was used. In addition, default CH4 (1 kg/TJ) and
N2O (0.1 kg/TJ) emission factors were obtained from the 2006 IPCC Guidelines.
Source-Specific QA/QC and Verification:
On the energy balance table provided by the MENR, natural gas data were compared with the value
provided by Petroleum Pipeline Corporation.
Recalculations:
There is no recalculation for this category.
3.2.6.6. Off road transportation (Category 1.A.3.e.ii)
GHG emissions from off road vehicles used for agricultural activities is included under 1.A.4.c category.
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1
3.2.7. Other sectors (Category 1.A.4)
Source Category Description:
The emissions that are included in this category mainly arise from fuel consumption in
commercial/institutional, residential and agriculture/forestry/fisheries. The source category (1.A.4.a)
and (1.A.4.b) are considered together since they are not presented separately in the national energy
balance tables until 2015. The source category 1.A.4.c includes the emission from the agricultural
activities but does not include forestry and fisheries.
The source category 1.A.4 is a key category in terms of emission level and emission trend of CO2 from
solid, liquid and gaseous fuels in 2021. The source category is also a key category in terms of emission
trend of CH4 from solid fuels and biomass.
The share of GHG emissions as CO2 eq. from other sectors in total fuel combustion was 19% in 2021
while it was 25.0% in1990. It was 13% of total GHG emissions in 2021.
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Table 3.48 Fuel combustion emissions from other sectors (1A4), 1990-2021
Share in fuel
combustion
Fuel
(1A)
CO2
CH4
N2O CO2 eq. consumption
category
Year
(kt)
(kt)
(kt)
(kt)
(TJ)
(%)
1990
29 277
133
3.7
33 707
646 591
25.0
1995
33 297
126
4.3
37 722
713 541
23.2
2000
33 693
108
4.6
37 764
737 948
18.0
2005
38 826
100
4.7
42 709
771 973
17.9
2010
62 070
152
6.4
67 773
973 007
24.2
2011
69 279
132
7.0
74 656
1078 816
24.8
2012
57 465
138
2.2
61 586
896 880
19.7
2013
52 999
114
1.8
56 384
879 983
18.8
2014
52 668
112
2.0
56 079
876 746
17.7
2015
62 494
63
4.2
65 327
1010 607
19.4
2016
62 413
62
4.2
65 201
1020 656
18.5
2017
70 272
73
4.3
73 391
1112 130
19.5
2018
60 102
61
4.1
62 869
977 068
17.2
2019
66 284
68
4.3
69 269
1085 732
19.5
2020
71 915
78
4.6
75 225
1152 101
21.0
2021
72 256
71
4.4
75 350
1170 999
19.2
Total GHG emission in 1A4 category increase 526 kt CO2 eq. (0.7% of increase) from 2020 to 2021.
Methodological Issues:
GHG emissions from 1A4 sector were calculated by using 2006 IPCC T1 and T2 approaches by TurkStat.
Fuel consumption data were taken from the national energy balance tables in both kt and ktoe units.
Country specific CO2 EF are used when available, otherwise default CO2 EF are used. Same CO2 EFs are
used from the summary table 3.8 (from 1.A Fuel combustion sector). All CH4 and N2O EF are also default.
The default CH4 and N2O EF for 1A4 sector are tabulated below.
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Table 3.49 N2O and CH4 emission factors of fuels used in others sector (1A4).
Sub Sectors
1A4a sub sector
Coal products
LPG
Other petroleum
products
Wood
Natural gas
1A4b, 1A4c sub sectors
Coal products
LPG
Other petroleum
products
Wood
Other primary solid
biomass
Natural gas
Emission Factors
CH4 (kg/TJ)
N2O(kg/TJ)
Source
10
5
10
1.5
0.1
0.6
Table 2.4
Table 2.4
Table 2.4
300
5
4
0.1
Table 2.4
Table 2.4
300
5
10
1.5
0.1
0.6
Table 2.5
Table 2.5
Table 2.5
300
300
4
4
Table 2.5
Table 2.5
5
0.1
Table 2.5
Recalculation:
There is recalculation in N2O emissions from 1.A.4.A for the years 2015-2020 due to a minor error. It is
resulted in changes between 0.02% and 0.11% for these years.
3.2.7.1. Commercial/Institutional (Category 1.A.4.a)
The fuel consumption of commercial/institutional is not separated in the energy balance tables until
2015, it is given under residential sector for 1990-2014 period. Emissions are given under 1.A.4.a
category in 2015 for the first time and they are included under (1.A.4.b) for 1990-2014 periods.
The share of GHG emissions as CO2 eq. from 1.A.4.a in total other sector is 21.2% in 2019.
Table 3.50 Fuel combustion emissions from 1.A.4.a category, 1990-2021
Share in
Fuel
1.A.4
CO2
CH4
N2O CO2 eq. consumptio
category
Year
(kt)
(kt)
(kt)
(kt)
n (TJ)
(%)
IE
IE
IE
IE
IE
IE
1990-2014
23 217
23 353
300 630
2015
2.3
0.3
35.7
22 004
22 139
298 757
2016
2.3
0.3
34.0
20 540
20 647
279 840
2017
2.0
0.2
28.1
13 484
13 539
208 743
2018
1.3
0.1
21.5
14 620
14 678
231 304
2019
1.4
0.1
21.2
13 581
13 637
209 304
2020
1.3
0.1
18.1
13
895
13
949
217
861
2021
1.3
0.1
18.5
Total GHG emission in 1.A.4.a category increased 312 kt CO2 eq. (2.3% of increase) from 2020 to 2021.
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Methodological Issues:
GHG emissions from 1.A.4.a sector were calculated by using 2006 IPCC T1 and T2 approaches by
TurkStat. Fuel consumption data were taken from the national energy balance tables in both kt and
ktoe units.
Country specific CO2 EFs are used for emission estimation. CH4 and N2O emissions from liquid, solid and
gaseous fuels have been estimated by using 2006 IPCC default EFs.
Uncertainties and Time-Series Consistency:
The AD were taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 7.07% for liquid fuels, 14.14% for solid fuels,
and 5% for gaseous fuels.
EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 page 2.38. Uncertainty values were
considered as 7% for CO2 and 100% (mid value in the range) for CH4 and N2O.
Source-Specific QA/QC and Verification:
Quality control for 1A4a category was performed on the basis of QA/QC plan. Since only 2015 and 2016
estimation is available for this category, emission trends could not be analyzed.
IEF for CO2, CH4, and N2O are in the range of 2006 IPCC default EFs.
Recalculation:
Emissions from this sector were recalculated due to the errors in calculations
Planned Improvement:
There is no planned improvement
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1
3.2.7.2. Residential (Category 1.A.4.b)
Residential and commercial/institutional fuel consumptions are not separable in the national energy
balance tables until 2015. Therefore, emissions from residential and commercial/institutional category
are included under 1.A.4.b for periods 1990-2014. After 2015 only residential sector is covered under
1.A.4.b category. Therefore, there is a sharp decrease in 2015 due to the separation of the commercial
and institutional category.
The share of GHG emissions as CO2 eq. from 1.A.4.b category in total other sectors is 63.1% in 2019
while it was 80.8% in 1990.
Table 3.51 Fuel combustion emissions from residential sector, 1990-2021
Share in
Fuel
1.A.4
CO2
CH4
N2O CO2 eq. consumptio category
Year
(kt)
(kt)
(kt)
(kt)
n (TJ)
(%)
1990
23 507
132
1.45
27 249
566 764
80.8
1995
25 958
125
1.41
29 507
611 993
78.2
2000
25 191
107
1.25
28 248
620 325
74.8
2005
29 731
99
1.08
32 529
646 141
76.2
2010
49 119
152
1.24
53 277
793 813
78.6
2011
54 168
131
1.04
57 746
869 556
77.3
2012
54 457
138
1.06
58 223
855 118
94.5
2013
50 649
114
0.93
53 767
846 990
95.4
2014
49 623
112
0.91
52 700
833 597
94.0
2015
30 479
60
0.60
32 157
587 205
49.2
2016
31 721
59
0.57
33 360
600 881
51.2
2017
40 620
71
0.60
42 571
705 283
58.0
2018
37 192
59
0.49
38 826
636 194
61.8
2019
41 922
66
0.53
43 729
717 860
63.1
2020
48 240
76
0.59
50 313
802 223
66.9
2021
48 408
69
0.55
50 295
814 229
66.7
Total GHG emission in 1.A.4.b category decreased 18 kt CO2 eq. (0.04% of decrease) from 2020 to
2021.
Methodological Issues:
GHG emissions from 1.A.4.b sector were calculated by using 2006 IPCC T1 and T2 approaches by
TurkStat. Fuel consumption data were taken from the national energy balance tables in both kt and
ktoe units.
Country specific CO2 EFs are used for emission estimation. CH4 and N2O emissions from liquid, solid and
gaseous fuels have been estimated by using 2006 IPCC default EFs. GHG emissions from biomass were
estimated by using 2006 IPCC default EFs.
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Uncertainties and Time-Series Consistency:
The AD were taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 7.07% for liquid fuels, 14.14% for solid fuels,
5% for gaseous fuels and 300% for biomass.
EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 page 2.38. Uncertainty values were
considered as 7% for CO2 and 100% (mid value in the range) for CH4 and N2O.
Source-Specific QA/QC and Verification:
Quality control for 1A4b category was performed on the basis of QA/QC plan. Emission trends are
analyzed. If there is a high fluctuation in the series, then AD and emission calculation are re-examined.
CO2, CH4 and N2O IEFs for all fuels are in the range of 2006 IPCC Guidelines.
Recalculation:
There is no recalculation in this sector
Planned Improvement:
There is no planned improvement in this sector.
3.2.7.3. Agriculture/Forestry/Fisheries (Category 1.A.4.c)
Source Category Description:
The source category is only including the emission from the consumption of fuel in agricultural activities.
The AD of this sub-category generally is consistent during the period 1990-2011, increasing gradually.
However, there was a drop in 2012 due to a classification problem with diesel oil consumption. Before
2012, diesel fuel was distributed in accordance with the definitions given below:
Diesel oil (sulfur content up to 10 mg/kg) is used for road transportation
Rural diesel (maximum sulfur content of 1000 mg/kg) is used in agricultural sector.
Based on this definition, diesel oil consumption in road transportation and agriculture was separated.
But "Technical Regulation Notification on Types of Diesel" entered into force by being published on
Official Gazette No. 27312 dated 08.07.2009 and restricted diesel oil sulfur content up to 10 mg/kg. The
deadline for implementation is extended to April 2011. After April 2011, it is not possible to separate
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the different use of diesel fuel. So in 2012 energy balance table, some of diesel oil used in agricultural
sector is included in road transportation. Due to this fact, a sharp increase in diesel consumption in road
transportation and a sharp decrease in fuel consumption of Agriculture/Forestry/Fisheries sector were
observed. MENR worked on agricultural association for modeling the agricultural diesel oil consumption.
MENR disaggregated the diesel oil consumption data in agriculture sector by a comparison method in
which total crop harvested area and petroleum products consumption data of similar countries are
weighted to derive an indicator for Türkiye.
More than 90% of GHG emissions from agricultural sector is related to off road vehicles. The share of
GHG emissions as CO2 eq. from 1.A.4.c category in total other sectors is 15.2% in 2021 while it was
19.2% in 1990.
Table 3.52 Fuel combustion emissions from agriculture sector, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
CO2
(kt)
5 770
7 340
8 501
9 095
12 951
15 112
3 008
2 350
3 045
8 797
8 688
9 112
9 426
9 742
10 095
9 952
CH4
(kt)
0.33
0.42
0.49
0.52
0.74
0.87
0.17
0.14
0.18
0.51
0.51
0.53
0.55
0.57
0.59
0.58
N2O
(kt)
2.28
2.90
3.36
3.60
5.12
5.96
1.18
0.88
1.11
3.38
3.36
3.52
3.57
3.71
3.91
3.82
CO2 eq.
(kt)
6 458
8 216
9 516
10 180
14 496
16 910
3 364
2 617
3 379
9 817
9 702
10 173
10 504
10 862
11 274
11 106
Fuel
consumption
(TJ)
79 826
101 548
117 623
125 832
179 194
209 260
41 762
32 992
43 149
122 772
121 018
127 007
132 130
136 568
140 574
138 909
Share in
1.A.4
category
(%)
19.2
21.8
25.2
23.8
21.4
22.7
5.5
4.6
6.0
19.0
18.4
15.6
17.1
16.0
15.5
15.2
Total GHG emission in 1.A.4.c category decreased 168 kt CO2 eq. (1.5% of decrease) from 2020 to
2021.
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Methodological Issues:
GHG emissions from 1.A.4.c sector were calculated by using 2006 IPCC T1 and T2 approaches by
TurkStat. Fuel consumption data were taken from the national energy balance tables in both kt and
ktoe units.
Country specific CO2 EFs are used for emission estimation for both stationary and mobile source
categories. CH4 and N2O emissions from liquid, solid and gaseous fuels have been estimated by using
2006 IPCC default EFs for both stationary and mobile source categories.
Uncertainties and Time-Series Consistency:
The AD were taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 14.14% for liquid fuels and 7% for gaseous
fuels.
EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 page 2.38. Uncertainty values were
considered as 7% for CO2 and 100% (mid value in the range) for CH4 and N2O.
Source-Specific QA/QC and Verification:
Quality control for 1.A.4.c category was performed on the basis of QA/QC plan. Emission trends are
analyzed. If there is a high fluctuation in the series, then AD and emission calculation are re-examined.
CO2, CH4 and N2O IEFs for all fuels are in the range of 2006 IPCC Guidelines.
Recalculation:
There is no recalculation in this sector
Planned Improvement:
There is no planned improvement in this sector.
3.2.8. Other (Category 1.A.5)
No other sectors were covered under energy sector. Emissions from fuel delivered to the military is
included under category 1.A.4.b for 1990-2014 periods and 1.A.4.a (for stationary) and 1.A.3 (for
mobile) since 2015.
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3.3.
1
Fugitive Emission from Fuels (Category 1.B)
Source Category Description:
Fugitive emissions from extraction, processing, storage and transport of fossil fuels were covered under
this category. CH4 emission from coal mining, CH4, CO2, N2O and NMVOC emissions from exploration,
production/processing, transport/transmission, refining and storage of oil and natural gas were covered.
Table 3.53 Fugitive emissions from fuels, 1990-2021
(kt)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
CO2
220
209
168
142
156
151
144
146
145
155
158
157
174
183
195
210
CH4
172
153
239
224
323
357
369
335
403
214
337
262
299
380
335
399
N2O
0.0031
0.0029
0.0023
0.0019
0.0021
0.0020
0.0019
0.0020
0.0020
0.0021
0.0021
0.0021
0.0024
0.0025
0.0027
0.0028
CO2 eq.
4 510
4 023
6 145
5 752
8 226
9 065
9 381
8 524
10 216
5 496
8 596
6 699
7 662
9 676
8 581
10 188
CO2 and CH4 are the main fugitive emissions in this category. CH4 was emitted mainly from coal mining
while CO2 was emitted from venting and flaring. Fugitive emissions as CO2 eq. have become 10 188
ktons in 2021. 36% of fugitive emissions as CO2 eq. were from oil and gas systems and 64% were from
solid fuels in the same year.
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Table 3.54 Fugitive emissions from fuels by subcategory, 1990-2021
(kt CO2 eq.)
Oil and
Solid
natural
Year
Total
fuels
gas
1990
4 510
3 598
912
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
4
6
5
8
9
9
8
10
5
8
6
7
9
8
10
023
145
752
226
065
381
524
216
496
596
699
662
676
581
188
2
4
3
6
6
6
6
7
2
5
3
4
6
5
6
985
836
941
151
662
851
324
318
733
896
681
885
770
558
493
1
1
1
2
2
2
2
2
2
2
3
2
2
3
3
038
309
811
075
403
530
199
898
763
700
017
777
906
023
695
Methodological Issues:
GHG emissions from 1.B sector were calculated by using 2006 IPCC T1 approaches by TurkStat.
Domestic production data for coal, oil and natural gas were taken from the national energy balance
tables in kt. MENR provided domestic coal production in underground and surface mining details.
Pipeline transmission amount of oil and natural gas and natural gas storage were provided by, Petroleum
Pipeline Company (BOTAŞ) (which is state own enterprise and authority for crude oil and natural gas
transportation and pipeline operation). Petroleum refining data were taken from Turkish Petroleum
Refineries Co. (TÜPRAŞ). For LPG and gasoline distribution, consumption values presented in the
national energy balance tables were used as AD.
Fugitive GHG emissions were estimated by using 2006 IPCC default EFs.
3.3.1. Solid fuels (Category 1.B.1)
Source Category Description:
This source category covers CH4 emissions which occur during the surface and underground extraction
of solid fuels and post-mining activities as well as abandoned underground mines. The emissions due
to combustions of those fuels to support production activities is not included in this section. Under this
category only fugitive CH4 emissions are calculated.
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1
Fugitive emissions from coal mining has increased to 37.4 t CO2 eq. in 2021 due to the increase in the
underground mining activities with respect to previous year.
Table 3.55 Fugitive emissions from solid fuels, 1990-2021
(kt)
Year
CO2
CH4
N2O CO2 eq.
1990
NE
144
NO,NE
3 598
1995
NE
119
NO,NE
2 985
2000
NE
193
NO,NE
4 836
2005
NE
158
NO,NE
3 941
2010
NE
246
NO,NE
6 151
2011
NE
266
NO,NE
6 662
2012
NE
274
NO,NE
6 851
2013
NE
253
NO,NE
6 324
2014
NE
293
NO,NE
7 318
2015
NE
109
NO,NE
2 733
2016
NE
236
NO,NE
5 896
2017
NE
147
NO,NE
3 681
2018
NE
195
NO,NE
4 885
2019
NE
271
NO,NE
6 770
2020
NE
222
NO,NE
5 558
2021
NE
260
NO,NE
6 493
In 2021 the amount of coal mined have been increased by 15.7% and become 86 466 ktons. In 2021,
the emissions from coal mining activities have been increased by 14% and become 6 493 ktons CO2 eq.
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Energy
Figure 3.32 Domestic coal production 1990-2021
000
000
000
000
000
000
000
000
000
000
Underground
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
(kt)
1990
100
90
80
70
60
50
40
30
20
10
Surface
Figure 3.33 CH4 emissions from coal mining, 1990-2021
300
(kt)
250
200
150
100
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
50
Underground
142
Surface
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Table 3.56 Fugitive emissions from abandoned coal mines,1990-2021
(kt)
Year
CO2
CH4
CO2 eq.
1990
NE
11.5
288
1995
NE
8.2
205
2000
NE
10.2
256
2005
NE
13.3
332
2010
NE
8.3
208
2011
NE
11.6
291
2012
NE
14.2
355
2013
NE
20.1
503
2014
NE
17.2
430
2015
NE
15.2
380
2016
NE
17.5
438
2017
NE
15.5
387
2018
NE
14.0
350
2019
NE
12.8
320
2020
NE
11.9
296
2021
NE
11.1
276
Methodological Issues:
GHG emissions from 1.B.1 sector were calculated by using 2006 IPCC T1 approaches by TurkStat.
Domestic coal production data were taken from the national energy balance tables. MENR provided
domestic coal production in underground and surface mining details.
Fugitive GHG emissions from coal mines were estimated by using 2006 IPCC default EFs. Both mining
and post mining fugitive emissions from underground and surface mines were estimated.
The fugitive emissions from abandoned underground mines are calculated with tier 2 methodology
shown below.
Methane Emissions = (Number of coal mines abandoned remaining unflooded) x (Fraction of gassy
mines) x (Average emission rate) x (Emission factor) x (Conversion factor) See eqn. 4.1.11 in 2006 IPCC
Guidelines Volume 1. All parameter used in this equation are default values.
Fraction of gassy mines is 100%
Average emission rate is 5.735 m3/year
Emission factor is calculated as EF = (1+aT)b where a and b are default values for either lignite or
hard coal and T is the years elapsed since abandonment. The coefficients used in the calculations is
given below.
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Energy
Table 3.57 Coefficients used in the calculation of abandoned coal mines methane
emission
Coal type
a
b
Hard coal
3.72
-0.42
Lignite
0.27
-1
(Source: see eqn 4.1.12 and table 4.1.9 in 2006 IPCC Guidelines Volume 1)
Uncertainties and Time-Series Consistency:
The AD were taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 16.6% for coal production.
Default EFs uncertainty for coal mining was taken from 2006 IPCC Guidelines Vol.2 Table 4.1.2 and
Table 4.1.4. CH4EFs uncertainty value was determined as 557%.
Source-Specific QA/QC and Verification:
Quality control for 1.B.1 category was performed on the basis of QA/QC plan. Emission trends are
analyzed. If there is a high fluctuation in the series, then AD and emission calculation are re-examined.
CH4IEFs are in the range of 2006 IPCC Guidelines.
Recalculation:
There is no recalculation in this sector
Planned Improvement:
Since the category is a key category in terms of emission trend of CH4, the tiers in CH4 estimation needs
to be increased. Detailed investigation has been performed to find out the availability of country specific
or basin specific EFs within both general directorates for lignite and hard coal structured under the
MENR, namely, DG Turkish Lignite Enterprises and DG Turkish Hard Coal Enterprises. However,
information for the generation of country-specific EFs are not available centrally in those coal authorities.
Therefore, it is necessary to communicate and cooperate with mining enterprises directly to search the
availability of required information for T2 estimation of CH4.
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3.3.2. Oil and natural gas (Category 1.B.2)
Source Category Description:
This source category covers fugitive CO2, N2O, CH4 emissions from exploration, production (processing),
transport (transmission), refining and storage of oil and natural gas. Three sub-source categories, oil
(1.B.2.a), natural gas (1.B.2.b) and venting and flaring (1.B.2.c) were covered under this category.
This source category is a key category in terms of emission level and trend of CH4emission. CO2
emissions are mainly coming from oil production. About 95% of CO2 emissions from oil and gas systems
are venting and flaring emissions during oil extraction and production. CH4 emissions are mainly coming
from oil production and pipeline transmission and distribution of natural gas. In parallel to the increase
in natural gas transmission and distribution, the greenhouse gas emissions in 1.B.2 category has
increased from 912 kt CO2 eq. in 1990 to 3 695 kt in 2021.
Table 3.58 Fugitive emissions from oil and natural gas systems,1990-2021
(kt)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
CO2
220
209
168
142
156
151
144
146
145
155
158
157
174
183
195
210
CH4
27.6
33.1
45.6
66.8
76.7
90.1
95.4
82.1
110.1
104.3
101.7
114.4
104.1
108.9
113.1
139.4
N2O
0.0031
0.0029
0.0023
0.0019
0.0021
0.0020
0.0019
0.0020
0.0020
0.0021
0.0021
0.0021
0.0024
0.0025
0.0027
0.0029
CO2 eq.
912
1 038
1 309
1 811
2 075
2 403
2 530
2 199
2 898
2 763
2 700
3 017
2 777
2 906
3 023
3 695
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Turkish GHG Inventory Report 1990-2021
2018
2019
2020
2021
2020
2021
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
2019
200
2017
400
2018
600
2016
800
2017
1 000
2016
(million sm3)
2015
Figure 3.35 Natural gas production, 1990-2021
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1 200
1992
1990
6 000
1991
1990
1
Energy
Figure 3.34 Oil production, 1990–2021
(1000 m3)
5 000
4 000
3 000
2 000
1 000
146
1
Energy
Figure 3.36 Natural gas transmission by pipeline, 1990-2021
80 000
(million sm3)
70 000
60 000
50 000
40 000
30 000
20 000
2019
2020
2021
2020
2021
2018
2019
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
10 000
Figure 3.37 Fugitive emissions from oil and gas system, 1990-2021
4 000
(kt CO2 eq.)
3 500
3 000
2 500
2 000
1 500
1 000
Turkish GHG Inventory Report 1990-2021
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
500
147 147
1
Energy
Methodological Issues:
GHG emissions from 1.B.2 sector were calculated by using 2006 IPCC T1 approaches by TurkStat.
Domestic production data for oil and natural gas were taken from the national energy balance tables in
kt. Pipeline transmission amount of oil and natural gas and data related to storage of natural gas were
provided by BOTAŞ, Petroleum Pipeline Company (which is a state own enterprise and authority for
crude oil and natural gas transportation and pipeline operations). Petroleum refining data were taken
from Turkish Petroleum Refineries Co. (TÜPRAŞ). For LPG and gasoline distribution, consumption values
for those fuels were used from the national energy balance tables.
Fugitive GHG emissions from oil and natural gas systems were estimated by using 2006 IPCC Guidelines
default EFs. Since the category is a key category in terms of emission level and trend of CH4, the tiers
in estimating CH4 emission need to be increased. Detailed investigation has been performed to find out
the availability of country specific EF. It is necessary to communicate and cooperate with related
authorities directly to search the availability of required information for Tier 2 estimation of CH4. It is
planned to continue with investigations.
Uncertainties and Time-Series Consistency:
The AD were taken from the national energy balance tables. Uncertainties in the AD were determined
by experts of MENR. AD uncertainties were determined as 7% for oil and gas systems.
Default EFs uncertainty for oil and gas systems was taken from 2006 IPCC Guidelines Vol.2 Table 4.2.4.
Oil and gas systems EFs uncertainty values were determined as 334% for CO2, 356% for CH4, and
224% for N2O.
Source-Specific QA/QC and Verification:
Quality control for 1.B.2 category was performed on the basis of QA/QC plan. Emission trends are
analyzed. If there is a high fluctuation in the series, then AD and emission calculation are re-examined.
IEFs are controlled and they are all in the range of 2006 IPCC default values.
Recalculation:
There is no recalculation in this category.
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1
Planned Improvement:
In order to increase the tiers for CH4 emission estimation, availability of detailed information have been
searched. It is planned to continue the investigation to find out the availability or possibility of availability
of appropriate data for higher tiers.
3.4.
CO2 Transport and Storage (Category 1.C)
Source Category Description:
This source category covers only fugitive CO2 from pipeline transportation of CO2. This source category
is not a key category. CO2 emissions were calculated on the basis of pipeline length as 0.126 kt for
whole 1990-2017 period.
Methodological Issues:
CO2 emissions from 1C sector were calculated by using 2006 IPCC Tier 1 approaches by TurkStat.
Pipeline length was obtained from Turkish Petroleum Incorporation. Pipeline length has not changed
with respect to the previous inventory year. Fugitive CO2 emissions from CRF category 1C were
estimated by using 2006 IPCC Guidelines default EFs.
Uncertainties and Time-Series Consistency:
The AD were taken from Turkish Petroleum Incorporation. AD uncertainty was considered 2% as
indicated in Table 2.15 of 2006 IPCC Guidelines Vol.2. Since AD have been taken directly from the
company uncertainty level for survey data were considered and to be conservative the maximum
uncertainty value was used.
EFs uncertainty was taken from 2006 IPCC Guidelines Vol.2 Table 5.2. Uncertainty values were
considered as 200% for CO2.
Recalculation:
There is no recalculation in this category.
Planned Improvement:
There is no planned improvement for this category.
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Industrial Processes and Product Use
4. INDUSTRIAL PROCESSES AND PRODUCT USE (CRF Sector 2)
4.1.
Sector Overview
The GHG emissions from industrial processes and product use are released as a result of manufacturing
processes. It means this category includes only emissions from processes and not from fuel combustion
used to supply energy for carrying out the processes. For that reason, emissions from industrial processes
are referred to as non-combustion.
Industrial processes whose contribution to CO2 emissions were identified as key category are production
of cement, lime and iron and steel, HFCs from product uses as ODS substitutes, and other process uses
of carbonates in different industrial activities.
The total GHG emissions from industrial processes and product use is 75 135.8 CO2 eq. for the year 2021
which is 14.5% of the total emissions including LULUCF sector and 13.3% of all emissions excluding
LULUCF in Türkiye.
The most important GHG emission sources of IPPU in 2021 were cement production with 7.8% and iron
and steel production 2.1% shares of the total national GHG emissions excluding LULUCF.
Table 4.1 Industrial processes and product use sector emissions, 2021
(kt CO2 eq.)
GHG sources and sink categories
Industrial processes and product use
A. Mineral industry
B. Chemical industry
CH4
N2O
HFCs/
PFCs/SF6
65 735
17
2 023
7 361
75 136
50 616
NA
NA
NA
50 616
CO2
Total
2 114
NO,IE,NA
2 023
NA
4 137
12 836
17
NA
57
12 909
170
NA,NE
NA,NE
NA
170
NA
NA
NA
65
65
F. Product uses as ODS substitutes
NA
NA
NA
7 210
7 210
G. Other product manufacture and use
NA
NA
NA
29
29
NE,NA
NE,NA
NA
NA
NE,NA
C. Metal industry
D. Non-energy products from fuels and
solvent use
E. Electronic Industry
H. Other
The main gas emitted by the IPPU sector was CO2, contributing 87.5% (65 735 kt) of the sector emissions
in 2021. HFCs, PFCs and SF6 contributed 9.8% (7 361 kt CO2 eq.) while the share of N2O emissions was
2.7% (2 023 CO2 eq.) and CH4 emissions was 0.02% (17 kt CO2 eq.).
150
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150
Industrial Processes and Product Use
Table 4.2 Industrial processes and product use emissions by gas, 1990- 2021
(kt CO2 eq.)
Years
CO2
CH4
N2O
HFCs
PFCs
SF6
Total
1990
21 312
8
1 064
NO
473
NO
22 856
1995
24 102
8
1 004
NO
409
NO
25 523
2000
24 804
9
847
116
409
13
26 199
2005
31 325
9
1 353
1 147
399
18
34 251
2010
43 889
10
1 653
3 054
388
65
49 060
2011
48 346
11
1 741
3 433
363
67
53 961
2012
49 879
13
1 776
4 257
271
69
56 266
2013
52 788
13
1 786
4 471
200
69
59 327
2014
53 043
14
1 808
4 930
187
75
60 057
2015
53 259
15
1 454
4 818
91
82
59 719
63 754
2016
57 290
17
1 219
5 111
37
80
2017
60 052
16
1 156
5 256
25
123
66 628
2018
60 713
17
1 823
5 040
10
134
67 738
2019
51 120
16
2 017
5 677
17
156
59 003
2020
59 261
16
2 006
6 498
10
172
67 962
2021
65 735
17
2 023
7 210
7
144
75 136
Table 4.3 presents the development of the emissions for the IPPU sector. Total emissions from industrial
process and product use increased by 228.7% between 1990 (22 856.1 kt CO2 eq.) and 2021 (75 135.8
kt CO2 eq.).
Table 4.3 Overview of industrial processes and product use sector emissions, 1990-2021
A. Mineral
industry
Year
(kt CO2 eq.)
(%)
B. Chemical
industry
(kt CO2 eq.)
(%)
C. Metal
industry
(kt CO2 eq.)
(%)
D. Non-energy
products from
fuels and solvent
use
(kt CO2 eq.)
(kt CO2 eq.)
(%)
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
13
17
18
23
34
36
37
40
40
40
43
46
46
38
47
424
548
418
246
087
237
315
539
885
304
821
473
212
547
078
58.7
68.8
70.3
67.9
69.5
67.2
66.3
68.3
68.1
67.5
68.7
69.8
68.2
65.3
69.3
1
1
1
1
1
2
2
2
2
2
2
1
3
3
3
629
476
061
944
903
752
968
579
784
792
159
897
346
144
091
7.1
5.8
4.1
5.7
3.9
5.1
5.3
4.3
4.6
4.7
3.4
2.8
4.9
5.3
4.5
7
6
6
7
9
10
11
11
10
11
12
12
12
11
11
620
296
313
451
519
617
051
135
984
457
439
731
805
381
047
33.3
24.7
24.1
21.8
19.4
19.7
19.6
18.8
18.3
19.2
19.5
19.1
18.9
19.3
16.3
183
203
277
446
432
854
606
534
399
266
146
152
206
138
134
0.8
0.8
1.1
1.3
0.9
1.6
1.1
0.9
0.7
0.4
0.2
0.2
0.3
0.2
0.2
22
25
26
34
49
53
56
59
60
59
63
66
67
59
67
856
523
199
251
060
961
266
327
057
719
754
628
738
003
962
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
2021
50 616
67.4
4 137
5.5
12 909
17.2
170
0.2
75 136
100.0
Turkish GHG Inventory Report 1990-2021
(%)
Industrial
Processes and
Product Use
Total
151151
Industrial Processes and Product Use
Table 4.3 Overview of industrial processes and product use sector emissions, 1990-2021 (cont’d)*
Year
1990
1995
2000
E. Electronic industry
(kt CO2 eq.)
(%)
-
0.0
-
F. Product uses as ODS
substitutes
(kt CO2 eq.)
-
(%)
0.0
-
0.0
Industrial Processes
and Product Use
Total
G. Other product
manufacture and use
(kt CO2 eq.)
-
(%)
(kt CO2 eq.)
(%)
22 856
100.0
0.0
-
0.0
0.0
25 523
100.0
116
0.4
13
0.1
26 199
100.0
0.0
1 147
3.3
18
0.1
34 251
100.0
0.0
2005
-
2010
42
0.1
3 054
6.2
23
0.0
49 060
100.0
2011
42
0.1
3 433
6.4
25
0.0
53 961
100.0
2012
42
0.1
4 257
7.6
26
0.0
56 266
100.0
2013
42
0.1
4 471
7.5
27
0.0
59 327
100.0
2014
42
0.1
4 930
8.2
33
0.1
60 057
100.0
2015
42
0.1
4 817
8.1
40
0.1
59 719
100.0
2016
42
0.1
5 111
8.0
36
0.1
63 754
100.0
2017
45
0.1
5 256
7.9
73
0.1
66 628
100.0
2018
57
0.1
5 040
7.4
71
0.1
67 738
100.0
2019
58
0.1
5 676
9.6
58
0.1
59 003
100.0
2020
59
0.1
6 498
9.6
57
0.1
67 962
100.0
2021
65
0.1
7 210
9.6
29
0.0
75 136
100.0
*The icon “-“ indicates notation keys “NO, NA, IE” as shown in the table.
Figure 4.1 Emissions from industrial processes and product use by subsector, 2021
C. Metal
industry 17.2
A. Mineral
industry 67.4
F. Product
uses as ODS
substitutes
9.6
B. Chemical
industry 5.5
The mineral industry contributed 67.4% of the IPPU sector’s emissions, the metal industry contributed
17.2%, product uses as ODS substitutes contributed 9.6%, while the chemical industry contributed 5.5%
in 2021.
The average shares of the mineral industry, metal industry and chemical industry between the years
1990-2021 are 67.9%, 22.6% and 4.7%, respectively.
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Industrial Processes and Product Use
The increases in sectoral emissions observed over the longer term are principally due to growth in
emissions associated with the mineral industry, predominantly cement production, and metal industry,
primarily iron and steel production. The increases in emissions in these sectors are because of the
industrial growth and the increased demand for construction materials.
Each source category’s contribution to total emissions and to sectoral trends within the IPPU sector
between 1990 and 2021 is shown in Figure 4.2.
Figure 4.2 Emissions from industrial processes and product use by subsector, 1990–2021
80 000
(kt CO2 eq.)
70 000
60 000
50 000
40 000
30 000
20 000
A.
C.
E.
G.
Mineral industry
Metal industry
Electronic Industry
Other product manufacture and use
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
10 000
B. Chemical industry
D. Non-energy products from fuels and solvent use
F. Product uses as ODS substitutes
4.2. Mineral Industry (Category 2.A)
Non-fuel CO2 emissions from cement and lime production and from limestone and dolomite use, glass
production as well as emissions from ceramics production, soda ash use and non-metallurgical magnesia
production are reported in this category.
Figure 4.3 presents the share of CO2 emissions in this category for the year 2021. The dominant sector is
cement production having a 87.4% share of CO2 emissions in the mineral industry. The second and third
sectors are other process uses of carbonates and lime production having 5.6% and 5.4% share of CO2
emissions. Glass production is responsible for 1.6% of emissions in the mineral industry.
Turkish GHG Inventory Report 1990-2021
153153
Industrial Processes and Product Use
Figure 4.3 Share of CO2 emissions from mineral production, 2021
Lime production
5.4%
Cement
production
87.4%
Glass production
1.6%
Other process uses of
carbonates
5.6%
4.2.1.
Cement production (Category 2.A.1)
Source Category Description:
Cement production causes CO2 emissions due to calcination reaction of limestone during production and
these emissions are reported under 2.A.1 CRF category. Moreover, cement production is an energy
intensive process. Heating up the kiln with its load to such a high temperature is extremely energy
consuming. Most of the kilns in Türkiye uses coal, petroleum coke, lignite as the primary energy source.
The emissions due to combusting of these fuels to heat up the kilns are included in 1.A.2f CRF category.
In cement production, limestone is fed to the cement kiln and heated up to 1400-1500 °C to produce
lime. At this temperature calcium carbonate (CaCO3) breaks into lime (CaO) and carbon dioxide (CO2).
The reaction is shown below.
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶� → 𝐶𝐶𝐶𝐶𝐶𝐶 + 𝐶𝐶𝐶𝐶�
Then, silica containing materials are combined with the lime to make the clinker. Clinker is the most
important intermediate product for cement production. It is also traded as a commodity. Cement is
produced by mixing and grinding the clinker with small amount of gypsum and potentially other materials
(e.g slag). All the CO2 emissions are released from the kilns during the clinker production step.
Figure 4.4 below shows the trend at clinker production and the related CO2 emissions between 1990 and
2021.
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154
Industrial Processes and Product Use
Figure 4.4 Trend at clinker, cement production and related CO2 emissions, 1990-2021
90 000
(kt)
Cement
Production
80 000
70 000
60 000
Clinker
Production
50 000
40 000
30 000
CO2 emissions
20 000
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
10 000
Türkiye started cement production in 1911 and Türkiye was a cement importer till 1970s. Türkiye started
exporting cement in 1978. By 2021, Türkiye is the Europe's biggest cement producer with its 84 million
tons of clinker production capacity and the production plants are distributed all over the country because
transportation costs in the cement sector is quite high. In Türkiye mostly portland cement is produced.
Slag cement, puzzolan added cement and their modifications are also produced.
As can be seen from the figures above, CO2 emissions increased by 323.4% between 1990 and 2021.
Construction sector and cement export are the strongest drivers in the cement sector. Except some minor
reductions in 2001 due to Türkiye's economic recessions and in 2015 due to conflict at Türkiye's southern
neighborhood (Syria and Iraq), cement industry showed a continuous growth untill 2018. In 2018 and
2019 cement production decreased due to contraction in domestic demand. In 2021 clinker production
was 84 025 kt and it caused 44 227 kt of CO2 emission. By 2021, cement production increased by 8,9%
with respect to 2020.
Methodological Issues:
Estimation of CO2 emissions is accomplished by applying a country-specific EF, in tonnes of CO2 released
per tonnes of clinker produced, to the annual national clinker output, corrected with the fraction of clinker
that is lost from the kiln in the form of cement kiln dust (CKD). This is the T2 methodology in the 2006
IPCC Guidelines as illustrated below.
Turkish GHG Inventory Report 1990-2021
155155
Industrial Processes and Product Use
CO2 emissions = MCl ∙ EFCl ∙ CFCKD
Where:
CO2 Emissions = emissions of CO2 from cement production, tonnes
MCl = weight (mass) of clinker produced, tonnes
EFCl = emission factor for clinker, tonnes CO2/tonne clinker
CFCKD = emissions correction factor for CKD, dimensionless
Collection of activity data
There are 54 cement plants in Türkiye. Most of the cement plants are members of Turkish Cement
Manufacturers’ Association (TurkCimento) and they report their activity data to TurkCimento on monthly
basis and TurkCimento publish the data as industry specific statistics on their website. Annual amount
of national clinker production of Türkiye is gathered from the clinker production statistics of the
TurkCimento website. The activity data of plants that are not member of TurkCimento, are collected with
survey.
Choice of emission factor
In the 2016 inventory, data for the carbonate content in clinker was gathered from the production plants
for the years 1990-2015. It was determined that the average weight percentage of CaO varies between
64% - 66% throughout the time series and was 65.8% in 2015. The corresponding EF in 2015 is
0.515913. This study reveals that CaO content does not vary through the years and was not iterated
again for the latest inventory. Türkiye applies the IPCC default CKD correction factor of 1.02. In the
following table, all the activity data and emission factors used for the emission calculation in the time
series are shown. In addition, annual CO2 emissions from clinker production are tabulated.
156
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156
Industrial Processes and Product Use
Table 4.4 CO2 emissions from cement production, 1990-2021
Clinker
Production
(kt)
Cemet
Production
(kt)
Cao Content
(%)
CO2 EF
CKD
CO2
Emission
(kt)
1990
20 252
24 416
64.4
0.506
1.02
10 445
1995
27 094
33 140
65.2
0.511
1.02
14 133
2000
28 950
35 953
65.5
0.514
1.02
15 184
2005
36 382
42 787
65.6
0.515
1.02
19 117
2010
56 798
67 447
65.9
0.517
1.02
29 977
2011
59 579
69 643
66.0
0.518
1.02
31 454
2012
59 508
69 466
65.9
0.517
1.02
31 372
2013
64 482
76 484
65.7
0.516
1.02
33 913
2014
65 594
74 768
65.7
0.516
1.02
34 498
2015
65 433
74 401
65.7
0.516
1.02
34 441
2016
71 298
78 437
65.7
0.516
1.02
37 528
2017
74 985
83 735
65.7
0.516
1.02
39 469
2018
74 880
75 746
65.7
0.516
1.02
39 413
2019
61 458
59 511
65.7
0.516
1.02
32 349
2020
77 539
75 172
65.7
0.516
1.02
40 813
2021
84 025
81 881
65.7
0.516
1.02
44 227
Year
Uncertainties and Time-Series Consistency:
The uncertainty value of the AD was estimated to be ±5% with error propagation equations. Although
aggregated plant production data was used for the calculation, plant specific production data also
gathered and their summation is compared with the aggregated production data that TurkCimento
supplied and it is found that they are close for 2015. The uncertainty value of the EF is 2% due to chemical
analysis of clinker to determine CaO percentage and default factor used for CKD.
Moreover, Monte Carlo analysis has been carried out for the CO2 emissions from cement production for
2020 submission and it resulted with -5.35% to +5.37% combined uncertainty. Further information about
Monte Carlo analysis of cement production can be seen in Uncertainty chapter (Annex 2).
Source-Specific QA/QC and Verification:
Clinker production data is gathered by the TurkCimento and reported monthly on their website. The
activity data of plants that are not member of TurkCimento, are collected with questionnaire. However,
TurkCimento do not report on CaO contents in the clinker. The annual average CaO contents of all the
cement factories are asked by a questionnaire and meanwhile clinker production amount of the factories
is also asked for quality assurance purpose in 2017. Details of this study can be found in inventory
submitted in 2018.
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Industrial Processes and Product Use
Moreover, the clinker production data gathered from the TurkCimento and PRODCOM (Turkish national
industrial production statistics) are compared and found to be consistent. In 2018, one of the clinker
production plant visited and discussed on CKD data. According to the researches, due to the production
system is sealed, it was assumed there is no kiln dust. So, in its emission calculation, plants do not report
CKD to the Ministry of Environment, Urbanization and Climate Change. However, there is not enough
information for other plants.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
A QA work was conducted by an external reviewer from CITEPA (Technical Reference Center for Air
Pollution and Climate Change) for this category in January 2020.
Recalculation:
No recalculations have been made to emissions from this category.
Planned improvements:
In the next years it is planned to collect data on plant specific CKD and carbonate content in clinker for
updating country specific emission factor of clinker.
4.2.2. Lime production (Category 2.A.2)
Source Category Description:
The word lime refers to product obtained by calcining the limestone. The production of lime involves a
series of steps which include quarrying the raw material, crushing and sizing, and calcination. Limestone
is a naturally occurring and abundant rock that consists of high levels of calcium carbonate (and maybe
some magnesium carbonate). Lime production begins by extracting limestone from quarries. Then
limestone enters into a crusher and screened to obtain small pieces of limestone. Then the crushed and
sized limestone particles are heated in the kiln. Heating up the limestone causes the calcination of the
calcium carbonate molecules (and magnesium carbonate molecules if any). CO2 is generated during the
calcination stage, when limestone (CaCO3) are burned at high temperature (900-1200°C) in a kiln to
produce quicklime (CaO) and CO2 is released in the atmosphere. Magnesium carbonate (MgCO3) breaks
into MgO and CO2 in the same manner.
158
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Industrial Processes and Product Use
The calcination reactions are shown below in the chemical equations.
CaCO3 → CaO + CO2
MgCO3 → MgO + CO2
Lime production results in CO2 emissions due to calcination reaction of limestone during production and
these emissions are reported under 2.A.2 CRF category. Moreover, lime production is an energy intensive
process. Heating up the kiln with its load to such a high temperature is extremely energy consuming.
Most of the kilns in Türkiye uses coal, petroleum coke, lignite as the primary energy source. The emissions
due to combusting of these fuels to heat up the kilns are included in 1.A.2.f CRF category.
In Türkiye lime is produced by a wide range of technology from old fashioned kilns to computer controlled
plants. Most of the lime plants in Türkiye are technologically new or modified to best available
technologies. The old technology lime plants are minority in Türkiye and their number is decreasing every
year. Lime producers can be divided into two sub-categories, producers for the market and producers for
their own internal consumption. Sugar refiners, soda ash manufacturers, and iron steel manufacturers
produce lime for their own use. Sugar refiners and soda ash producers however use the produced CO2 in
their process steps and CO2 is absorbed. Therefore, lime production of the sugar refiners and soda ash
producers do not contribute to the greenhouse gas inventory.
For sugar refining process, according to the information provided from Türkşeker which currently operates
15 sugar factories with capacities ranging from 1750 to 8500 tons of beet per day, lime used in treatment
process is produced in the lime quarries at the factory sites. Limestone and coke mixture is supplied to
the lime kiln. After limestone decomposes into lime and CO2, lime is quenched with water and lime milk
is prepared to be used to remove impurities from raw sugar juice. The CO2 drawn from the upper part of
the furnace is used to precipitate the excess lime used in the treatment.4 The CO2 emitted is reabsorbed
into the lime cake and emissions are balanced by the CO2 sink in sugar production.
Almost all of the lime produced in Türkiye is quick lime and dolomitic lime. There is also some minor
amount of hydraulic lime production in Türkiye. However, it is known to be negligible amount of
production with respect to total lime production.
The figure 4.5 shows the trend at lime production and the related CO2 emissions between 1990 and 2021.
The lime produced in Türkiye is mostly used in the manufacturing and construction sector. Emissions
from lime production are increased by 22.3% between 1990 and 2021. It is seen in the graph, emissions
are decreased remarkably in 1992, in 2000-2001 period and in 2008-2009 period due to slow down of
4
Türkşeker website, Sugar production technology, https://www.turkseker.gov.tr/?ModulID=3&MenuID=55
Turkish GHG Inventory Report 1990-2021
159159
Industrial Processes and Product Use
the construction sector and economic recessions. The emissions from lime production seems to be going
to increase in the future since manufacturing and construction sectors grow overall and the demand for
lime increases.
Figure 4.5 CO2 emissions from lime production, 1990-2021
3000
(kt)
2500
2000
1500
1000
2019
2020
2021
2016
2017
2018
2013
2014
2015
2009
2010
2011
2012
2006
2007
2008
2002
2003
2004
2005
1999
2000
2001
1995
1996
1997
1998
1992
1993
1994
0
1990
1991
500
Methodological Issues:
The formula below is used to calculate emission from lime production.
Where:
CO2 emissions = (Mql – Mcl) ∙ EFql + Mdl ∙ EFdl
CO2 emissions = emissions of CO2 from lime production, tonnes
Mql = Production of quick lime
Mcl= Amount of captive lime (non emissive quick lime production)
Mdl= Production of dolomitic lime
EFql = Emission factor for quick lime
EFdl= Emission factor for dolomitic lime
In sugar industry lime is produced for sugar refining. Both the quick lime and the CO2 is used for
precipitating the impurities in the sugar. In the Turkish inventory it is assumed that all the CO2 produced
in lime production for sugar refining is precipitating and no CO2 is emitted. Also in the soda ash production
with solvay process, lime is produced and the resulting CO2 is used in the process as an intermediate
product. It is assumed that all the CO2 produced from limestone in the soda ash production process is
captured and no CO2 emitted. Therefore, the lime produced for sugar industry and the soda ash
production industry is deducted from the national lime production data and the emissions are calculated
accordingly. Consistent with the use of the Tier 1 method, Türkiye does not make any corrections to
estimated emissions to account for emissions from production of hydrated lime or lime kiln dust.
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Industrial Processes and Product Use
Collection of activity data
Quick lime (CaO) production data are collected from the Lime Producers Association (KISAD). KISAD
gathers about 88% (by 2015) of all the lime production data either by asking to member production
plants or searching for the activity reports of other producers. The remaining 12% is estimated by KISAD
using the lime import and export data and related activity data in the industry. In addition, sectoral lime
consumption data is also taken from KISAD and therefore the amount of captive lime (lime produced for
sugar industry and soda ash production industry) is obtained. The dolomitic lime is mostly used in the
steel production. The dolomitic lime consumption data were collected from steel plants and the sum is
assumed to be the national dolomitic lime production data.
Table 4.5 Lime production and CO2 emissions, 1990-2021
Year
Quick Lime
Production
Quick Lime
produced for
synthetic soda
ash production
1990
4 000
233
1995
4 090
334
Quick Lime
produced for
sugar industry
182
(kt)
Dolomitic lime
production
County
specific
emission
factor
CO2
Emissions
47
0.617
2 249
64
0.638
2 357
1 645
140
2000
3 241
473
272
72
0.637
2005
3 584
506
224
106
0.646
1 925
147
0.687
1 711
2 031
2010
3 225
703
195
2011
3 819
747
301
171
0.685
2012
4 621
666
356
180
0.688
2 615
2 486
2013
4 400
715
300
174
0.695
2014
4 443
704
315
171
0.694
2 507
158
0.693
2 429
2 660
2015
4 325
683
313
2016
4 695
713
328
167
0.693
2017
4 868
863
342
189
0.693
2 684
188
0.693
2 787
2 565
2018
4 984
871
300
2019
4 750
917
320
169
0.693
2020
4 964
790
320
177
0.693
2 807
203
0.693
2 751
2021
5 024
940
340
Choice of emission factor
Country specific emission factor is used for quick lime whereas default emission factor is used for dolomitic
lime (0.77 tonnes CO2 per tonne lime) from the 2006 IPCC Guidelines. For calculating the country specific
emission factor of quick lime, factories are asked for their amount of production and the CaO content of
their product in 2016. By averaging on weight basis, the country specific CaO content of quick lime is
calculated. Due to the stable trend in CaO content, this study was not iterated for the latest inventory
and the 2015 value was used for the 2016-2021 inventories.
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Uncertainties and Time-Series Consistency:
There is uncertainty due to not collecting data from each of the production plant but estimating some
amount of the production. In addition, there is uncertainty associated with assuming the dolomitic lime
production is equal to the consumption of dolomitic lime in steel industry. Overall ±10% uncertainty for
the activity data is estimated.
The uncertainty value of the EF is estimated to be ±2 % based on the 2006 IPCC Guidelines.
Monte Carlo simulation was carried out to estimate uncertainty in CO2 emissions from lime category.
Combined uncertainty in CO2 emissions in 2018 is estimated at -16.87% to +17.92%. Further information
about Monte Carlo analysis can be seen in Uncertainty chapter (Annex 2).
Source-Specific QA/QC and Verification:
Plant specific lime production data from KISAD is compared with ILA (International Lime Association)
Although ILA report is based on the sales, KISAD data and ILA data are found to be consistent. ILA
reports 4 700 kt of lime sales in Türkiye while KISAD reports 4 750 kt of lime production in Türkiye in
20195.
In addition, Türkiye's 8th five years’ development plan released an annex special to building materials.
One part of this report was allocated for the lime production in Türkiye and it includes historical lime
production data for the years 1994-1998 which are exactly the same with our lime production data for
those years in the time series.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
Moreover, a QA work was conducted by an external reviewer from CITEPA (Technical Reference Center
for Air Pollution and Climate Change) for this category in January 2020.
Recalculations:
No recalculations have been made for this sector except for a rounding correction to the activity data for
lime in 2019 and 2020.
5
162
https://www.internationallime.org/world-lime-production/
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Planned Improvement:
It is planned to obtain a country specific emission factor for dolomitic lime in next submissions.
4.2.3. Glass production (Category 2.A.3)
Source Category Description:
A variety of raw materials are involved during glass production. Limestone, dolomite and soda ash are
the carbonates that compose the majority of raw materials. These carbonates emit CO2 when heated
(calcined) during the glass production and it is reported under 2.A.3 CRF category. Glass makers also use
a certain amount of recycled scrap glass (cullet). Cullet usage decreases the raw material consumption
and hence it reduces the costs and CO2 emissions. During glass production carbon based fuels are burnt
in order to melt the glass batch and as a result of this CO2 emissions, which are reported under 1.A.2.f
CRF category, are emitted.
Turkish glass industry produces various type of glasses with different chemical and physical properties.
Türkiye's glass sector comprises the three main categories: container (household goods and bottles), float
glass and fiber glass. The majority of the glass production is container and flat glass in all the time series.
Turkish glass industry has roots back to the establishment of Paşabahçe in 1935 with a production
capacity of only 3 kt. Türkiye glass industry production reached 4.8 Mt in 2021 and it was 3.4 Mt in 2015.
Since the Turkish glass industry does not have an advantage in terms of raw material and energy costs
compared to its European peers, capacity utilization rates of the industry are the key indicator of the
competitive edge and profitability. The industry depicted a tremendous growth trend either through
capacity additions or through new product initiations between 1990 (1.13 Mt molten glass produced) and
2021 (4.8 Mt molten glass produced), increasing 328%.
The trend in CO2 emissions from glass production is given in the Figure 4.6. The emissions are increasing
in general due to increasing glass production in Türkiye. The time series shows a considerable decrease
in 2009 due to effects of global economic recession in that year.
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Industrial Processes and Product Use
Figure 4.6 CO2 emissions from glass production, 1990-2021
900
(kt)
800
700
600
500
400
300
200
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
100
Methodological Issues:
Estimation is based on the T3 method described in the 2006 IPCC Guidelines. Specifically, the calculation
based on accounting for the carbonate input to the glass melting furnace
𝐶𝐶𝐶𝐶� 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 = �(𝑀𝑀� ∙ 𝐸𝐸𝐸𝐸� ∙ 𝐹𝐹� )
�
Where:
CO2 emissions = emissions of CO2 from glass production, tonnes
EFi = emission factor for particular carbonate i,tonnes CO2/tonne carbonate
Mi =weight or mass of the carbonate i consumed (mined), tones
Fi = fraction calcination achieved for the carbonate i, fraction
Collection of activity data
Türkiye produces float glass, container glass (including household glassware) and fiberglass for insulation.
Total glass production of Türkiye is done by 6 companies. Activity data of molten glass production by
glass type and carbonate input directly from the plants for all the years 1990-2021.
In the following table, total CO2 emissions and glass production by type are given.
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Table 4.6 Molten glass production and CO2 emissions by type of glass, 1990-2021
(kt)
Year
Total Glass
Production
Float Glass
1990
1 129
650
1995
1 290
2000
1 934
2005
Container
(households
+bottles)
Fiberglass
CO2
Emissions
456
23
111
625
643
22
120
974
922
38
199
2 175
1 016
1 085
74
280
2010
2 800
1 452
1 294
54
402
2011
3 169
1 746
1 348
75
464
2012
3 106
1 525
1 499
82
467
2013
3 186
1 624
1 485
77
476
2014
3 560
1 876
1 618
66
520
2015
3 444
1 661
1 718
65
526
2016
3 982
1 996
1 934
52
588
2017
4 375
2 305
2 023
48
686
2018
4 494
2 253
2 207
34
663
2019
4 498
2 102
2 330
66
734
2020
4 349
1 856
2 433
60
697
2021
4 834
2 152
2 608
75
807
According to the figures in table above, glass production shows a steady increase by the year 2002 after
the economic recession years of 1999-2001 of Türkiye (1 681kt in 1999 and 1 870 kt in 2002). The
production decreased in the year 2009 (2 174 kt) due to the global economic recession. In 2020 total
glass production slightly decrease and become 4 349 kt in 2020. In 2021 glass production was 4 834 kt
and it caused 807.1 kt of CO2 emission. By 2021, glass production increased by 11.2% with respect to
2020.
Choice of emission factor
CO2 emissions are calculated using the 2006 IPCC Guidelines Volume 3 default EFs for the carbonates
(Table 2.1). The emission factors for each type of carbonate are given below.
Table 4.7 EFs for carbonates, 1990-2021
Carbonate
Sodium carbonate or soda ash
Limestone
Dolomite
EF (tonnes CO2/tonne
carbonates)
0.41492
0.43971
0.47732
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Uncertainties and Time-Series Consistency:
Due to emissions from glass production are estimated based on the carbonate input (Tier 3), the emission
factor uncertainty is relatively low because the emission factor is based on a stoichiometric ratio. There
may be some uncertainty associated with assuming that there is 100 percent calcination of the carbonate
input (1%). Emission factor uncertainty is assumed as 3% while the emission factor for activity data is
assumed %3 under the Tier 3 approach.
Uncertainty for CO2 emissions from category 2.A.3 was quantified using the Monte Carlo simulation for
2020 submission. The Monte Carlo analysis resulted with (-9.63%,+9.82%) combined uncertainty.
Further information about Monte Carlo analysis can be seen in Uncertainty chapter (Annex 2).
Source-Specific QA/QC and Verification:
The data used in Glass Production category is collected directly from these plants by questionaire for all
the years 1990-2021.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye. A QA work was conducted by an external reviewer from CITEPA (Technical
Reference Center for Air Pollution and Climate Change) for this category in January 2020.
Recalculation:
A new plant’s data which has launced operation by the year 2018 included in the calculations resulted
with an average increase of 16 kt CO2 between the years 2018-2020.
Planned Improvements:
No further improvements are planned regarding this source.
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4.2.4. Other process uses of carbonates (Category 2.A.4)
The category, other process uses of carbonates, is a key category. In this category, emissions from
ceramics, bricks and roof tile production, other uses of soda ash and non-metallurgical magnesia
production are reported.
Figure 4.7 CO2 emissions from other uses of carbonates, 1990-2021
b. Other uses of
soda ash
2.6%
c. Nonmetallurgical
magnesium
production
11.8%
a. Ceramics
85.6%
Figure 4.7 shows the share of CO2 emissions in other uses of carbonates for 2021. The major sector is
ceramics production having a 85.6% ( 2 423.4 kt) share of CO2 emissions of other uses of carbonates.
The second sector is non-metallurgical magnesium production shares 11.8% (335.3 kt) and third other
uses of soda ash sector shares 2.6% (72.6 kt) of CO2 emissions of other uses of carbonates.
4.2.4.1. Ceramics (Category 2.A.4.a)
Source Category Description:
Ceramics production is a source of CO2 emissions since raw materials like limestone and magnesite are
calcined during manufacturing. Moreover, ceramic production is an energy intensive process. Heating up
the ceramics to such a high temperature for calcination is extremely energy consuming. Most of the
ceramic manufacturers in Türkiye use natural gas for this purpose. The emissions due to combusting of
fuels to heat up the ceramics are included in 1.A.2.f CRF category.
Ceramics include the production of vitrified clay pipes, refractory products, expanded clay products, wall
and floor tiles, table and ornamental ware, sanitary ware, bricks and tile.
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CO2 emissions from ceramic production show an increasing trend for the years 1990-2017 overall. In
2021, ceramic production and the resulting CO2 emissions decreased by 24.7% with respect to 2017.
Figure 4.8 CO2 emissions, by raw materials type, from ceramics, 1990-2021
3 500
(kt)
3 000
Clay
2 500
Magnesite
2 000
Dolomite
1 500
Limestone
Calcite
1 000
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
500
Methodological Issues:
The T2 method is used to estimate emissions from the ceramics industry. The method requires
consumption data for each of the raw materials consumed, and multiplying by the respective emission
factor for the carbonate to estimate CO2 emissions.
𝐶𝐶𝐶𝐶� 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 = �(𝑀𝑀� ∙ 𝐸𝐸𝐸𝐸� )
Where:
CO2 emissions = emissions of CO2from other process uses of carbonates, tonnes
Mi = mass of limestone or dolomite respectively (consumption), tonnes.
EFi = emission factor for carbonate calcination, tonnes CO2/tonne carbonate
Collection of activity data
Calcite, limestone, dolomite, magnesite and hydro-magnesite are consumed as raw materials in the
ceramics industry. Production of ceramic tile and sanitary ware and carbonate consumption data (see the
following table) are gathered from the Turkish Ceramics Federation for the time series 1990-2018. The
amount of bricks and tile are gathered by Turkish Statistical Institute for the years 1990-1999 and 2005-
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Industrial Processes and Product Use
2021. Data gaps for the years 2000-2004 is estimated. In this calculation following assumptions are made
by using one of the plant data,
1 m3 brick= 600 kg,
1 brick = 4 kg,
1 tile = 3 kg,
Kg clay = 1.3*kg bricks and tile
Table 4.8 Raw material consumption and production, 1990-2021
Raw Material (kt)
Calcite
Limestone
Dolomit
Product (kt)
Magnesitehydro
magnesite
Clay
Ceramic
Tile
Sanitary
ware
Bricks
and Tile
Total
Product
(kt)
1990
7
278
7
240
5 832
884
47
4 486
5 417
1995
15
544
15
469
6 712
1 819
78
5 163
7 060
2000
25
968
25
834
6 675
2 975
114
5 135
8 224
2005
37
1 464
37
1 262
7 685
4 437
237
5 911
10 585
2010
35
1 373
35
1 184
13 211
4 165
220
10 162
14 547
2011
37
1 458
37
1 257
19 296
4 420
245
14 843
19 508
2012
40
1 572
40
1 355
35 064
4 760
260
26 972
31 992
2013
47
1 842
47
1 588
51 828
5 610
270
39 868
45 748
2014
43
1 685
43
1 453
46 289
5 100
280
35 607
40 987
2015
46
1 786
46
1 540
30 327
5 280
300
23 329
28 909
2016
47
1 854
47
1 598
31 069
5 610
310
23 899
29 819
2017
49
1 912
49
1 675
47 482
5 755
352
36 525
42 632
2018
241
1 912
127
1 675
31 109
6 030
350
23 930
30 310
2019
241
1 912
127
1 675
20 091
6 030
350
15 454
21 834
2020
241
1 912
127
1 675
18 528
6 030
350
14 252
20 632
2021
241
1 912
127
1 675
17 598
6 030
350
13 537
19 917
Choice of emission factor
Default EFs provided in table 2.1 of the 2006 IPCC Guidelines are applied to the total raw material
consumption for the entire time series to estimate emissions. The following table shows the default
emission factors used in the calculations. EF for clay is calculated by using 7% CS carbon content of clay
and default emission factor of calcite and limestone. To determine the average carbon content in clay,
11 plants were asked their raw material analysis result. This reveal that average carbon content in clay is
around 7%.
Table 4.9 Carbonate EFs for all years in the time series
Carbonate
Calcite and limestone
EF (tonnes CO2/ton carbonate)
0.43971
Dolomite
0.47732
Magnesite
0.52197
Clay
0.03077
Source: Table 2.1 of the 2006 IPCC Guidelines, Vol. 3
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CO2 emissions from each raw material are given in the table below and in Figure 4.8.
Table 4.10 CO2 emissions from raw material consumption, 1990-2021
(kt)
Year
Calcite
Limestone
Dolomite
Magnesite
Clay
Total
1990
3.3
122.2
3.6
125.1
179.5
433.7
1995
6.7
239.1
7.2
244.7
206.6
704.4
2000
10.9
425.4
11.8
435.4
205.5
1 088.9
2005
16.4
643.6
17.8
658.7
236.5
1 573.1
2010
15.4
603.9
16.7
618.0
406.6
1 660.7
2011
16.4
641.0
17.8
656.0
593.9
1 925.1
2012
17.7
691.3
19.2
707.5
1079.3
2 514.9
2013
20.7
809.8
22.5
828.7
1595.3
3 276.9
2014
18.9
740.9
20.5
758.2
1424.7
2 963.4
2015
20.1
785.4
21.8
803.7
933.5
2 564.4
2016
20.8
815.3
22.6
834.3
956.3
2 649.3
2017
21.5
840.7
23.3
874.3
1461.5
3 221.3
2018
106.1
840.7
60.6
874.3
957.5
2 839.2
2019
106.1
840.7
60.6
874.3
618.4
2 500.1
2020
106.1
840.7
60.6
874.3
570.3
2 452.0
2021
106.1
840.7
60.6
874.3
541.7
2 423.4
Uncertainties and Time-Series Consistency:
As the EF is the stoichiometric ratio reflecting the amount of CO2 released upon calcination of the
carbonate, the EF uncertainty in this category is relatively low. There is some uncertainty associated with
assuming a fractional purity of limestone and dolomite in cases where only carbonate rock data are
available (±1-5%).
AD uncertainties are greater than the uncertainties associated with EFs. Although there is a significant
amount of roof tiles and bricks production in Türkiye, unfortunately there is no verified activity data for
this type of production. Only ceramic tiles and sanitary ware productions were taken into account.
Therefore, for this category AD uncertainty is considered as 30% while the EF uncertainty is considered
2% which is in line with the 2006 IPCC Guidelines, Volume 3 (page 2.39).
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Category 2.A.4.a employed a Monte Carlo uncertainty analysis which causes a combined uncertainty
range (-19.24%, +20.79%) for CO2 emissions in 2020 submission. Detailed explanation of Approach 2
method is in Uncertainty part of this inventory report (Annex 2).
Source-Specific QA/QC and Verification:
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
Additionally, a QA work was conducted by an external reviewer from CITEPA (Technical Reference Center
for Air Pollution and Climate Change) for this category in January 2020.
Recalculations
Due to total bricks and tiles production data updated in PRODCOM database, emissions from ceramics
category show an average decrease of 2 kt CO2 between the years 2005-2020.
Planned Improvements
Ceramic production data were gathered from Turkish Ceramics Federation until the federation had judicial
issues regarding data collection from its members in 2020. As a result of this situation, TurkStat launched
studies for estimating emissions of ceramics sector from other data sources. Calculations will be examined
in next submissions.
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4.2.4.2. Other uses of soda ash (Category 2.A.4.b)
Source Category Description:
In this category, emissions from soda ash consumption are considered. CO2 emissions from soda ash used
in glass manufacturing industry are included in Glass Production. There are no other uses of soda ash
included elsewhere in the Turkish Inventory.
Since soda ash is an important intermediate product primarily for the glass industry and detergent industry
and it is used in many other industries. Soda ash consumption increased dramatically between 1990 (315
kt) and 2021 (1 050 kt) as the Turkish industry grew. During the 2001 and 2008 economic recessions,
soda ash consumption decreased remarkably. Since 2010 consumption has increased driven by the
growth of the glass industry in particular and the growth of Turkish industry in general.
In 2021 the GHG release due to the apparent consumption of soda ash is 73 kt of CO2.
Figure 4.9 CO2 emissions from other use of soda ash, 1990-2021
250
(kt)
200
150
100
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
50
Methodological Issues:
Türkiye does not collect annual statistics on soda ash consumption by industry; instead the apparent
consumption of soda ash is calculated by adding imports data to production data and then subtracting
exports and the usage in the glass sector. In this methodology it is assumed that all of the apparent
consumption of soda ash is emissive.
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Collection of activity data
Apparent consumption is calculated by the following formula.
Total Consumption = Soda ash production +Imports – Exports
Apparent Consumption = Total Consumption – Use in Glass Industry
Total production values are gathered from the two soda ash producer plants while foreign trade statistics
are provided by TurkStat. The data for the amount of soda ash used in the glass sector is estimated from
the glass production data which was obtained from glass producer plants.
Choice of emission factor
The default EF (0.41492 tonnes CO2 /tonnes product) taken from Table 2.1 of the 2006 IPCC Guidelines,
Volume 3, Chapter 2 is applied for the full time series.
Total consumption, use in glass industry, apparent consumption and CO2 emissions from soda ash
consumption are given in the following table.
Table 4.11 Activity data for the other use of soda ash and CO2 emissions, 1990-2021
(kt)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Total
Consumption
315
385
601
749
807
939
918
915
944
897
1 017
914
1 180
1 168
848
1 050
Use in Glass
Industry
116
125
221
301
441
509
510
520
561
623
637
746
733
800
742
875
Apparent
Consumption
199
259
380
448
366
430
409
395
383
274
380
168
447
368
106
175
CO2 Emissions
83
108
158
186
152
178
170
164
159
114
158
70
186
153
44
73
Uncertainties and Time-Series Consistency:
AD uncertainty for this source is considered ±10% due to using national statistics and using a general
apparent consumption calculation formula. Because a default EF based on stoichiometry is used for the
emission calculation, uncertainty for the EF is defined as ±2%.
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Industrial Processes and Product Use
Moreover, Monte Carlo analysis has been carried out for the CO2 emissions from other uses of soda ash
production for 2020 submission and it resulted with a range of -30.14% to +29.94% combined
uncertainty. Further information about Monte Carlo analysis of other uses of soda ash production can be
seen in Uncertainty chapter (Annex 2).
Source-Specific QA/QC and Verification:
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
There are three plants in Türkiye producing soda ash. The production data of these two plants and Turkish
soda ash export data are compared together and the data are found to be consistent.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
A QA work was conducted by an external reviewer from CITEPA (Technical Reference Center for Air
Pollution and Climate Change) for this category in January 2020.
Recalculations:
Due to a new glass producer data included in the calculations, the recalculation of emissions from other
uses of soda ash resulted with an average decrease of 6.8 kt CO2 between the years 2018-2020.
Planned Improvements:
No further improvements are planned regarding this source.
4.2.4.3. Non metallurgical magnesia production (Category 2.A.4.c)
Source Category Description:
This source category should include emissions from magnesia (MgO) production that are not included
elsewhere. Magnesite (MgCO3) is one of the key inputs into the production of magnesia, and ultimately
fused magnesia. There are three major categories of magnesia products: calcined magnesia, dead burned
magnesia (periclase) and fused magnesia. Calcined magnesia is used in many agricultural and industrial
applications (e.g., feed supplement to cattle, fertilizers, electrical insulations and flue gas
desulphurisation). Deadburned magnesia is used predominantly for refractory applications, while fused
magnesia is used in refractory and electrical insulating markets.
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Magnesia (MgO) is produced by calcining magnesite (MgCO3) which results in the release of CO2 as shown
in the chemical reaction below;
𝑀𝑀𝑀𝑀𝑀𝑀𝑀𝑀� → 𝑀𝑀𝑀𝑀𝑀𝑀 + 𝐶𝐶𝐶𝐶�
Depending on the calcination temperature, calcined magnesia or deadburned magnesia is produced.
Deadburned magnesia requires higher temperatures and its purity is higher than calcined magnesia in
terms of MgO. Fused magnesia is produced in the electrical arc furnaces at very high temperatures and
it is the purest among all. The figure below shows the CO2 emissions from total magnesia production
between 1990 and 2021.
Figure 4.10 CO2 emissions from magnesia production, 1990-2021
400
(kt)
350
300
250
200
150
100
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
50
Methodological Issues:
Türkiye implements Tier 1 method. CO2 emissions are calculated by using magnesia production (calcined
production + deadburned magnesia) as AD and multiplied by the default IPCC EF. There is no significant
amount of fused magnesia production in Türkiye.
Collection of Activity Data
The magnesia production data are collected from the magnesia producers. There are seven plants that
are producing magnesia in Türkiye. Each of them were asked for their activity data by a questionnaire.
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Industrial Processes and Product Use
Choice of Emission Factor
The default IPCC EF (0.52197 tonnes CO2 / tonne carbonate) taken from Table 2.1 of the 2006 IPCC
Guidelines, Volume 3, Chapter 2, is applied for all the time series.
Table 4.12 Magnesia production and CO2 emissions, 1990-2021
(kt)
Year
Magnesia production
CO2 Emissions
1990
196.8
102.7
1995
242.5
126.6
2000
273.7
142.8
2005
316.6
165.3
2010
353.7
184.6
2011
353.2
184.4
2012
340.3
177.6
2013
426.8
222.8
2014
454.1
237.0
2015
441.4
230.4
2016
455.1
237.6
2017
658.1
343.5
2018
621.0
324.1
2019
473.1
247.0
2020
506.5
264.4
2021
642.3
335.3
Uncertainties and Time-Series Consistency:
AD is collected from the companies and all the 7 biggest producers are asked for their activity data.
Therefore, the activity data uncertainty is 10%. Because the IPCC default EF is used for the emissions
calculation, the uncertainty for the EF is defined as ±2%.
Additionally, an uncertainty analysis using the Monte Carlo technique was carried out to estimate
emissions of CO2 for 2.A.4.c category (Non metallurgical magnesia production) in 2020 submission.
Combined uncertainty in CO2 emissions in 2018 is estimated at the range of (-30.14%,+30.29%). For
more detailed explanations please refer to Annex 2.
Source-Specific QA/QC and Verification:
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
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Industrial Processes and Product Use
Furthermore, a QA work was conducted by an external reviewer from CITEPA (Technical Reference Center
for Air Pollution and Climate Change) for this category in January 2020.
Recalculation:
No recalculations have been made to emissions from this category.
Planned improvement:
No further improvements are planned regarding this source.
4.3. Chemical Industry (Category 2.B)
In 2021, the chemical industry was responsible for 5.5% of the total carbon dioxide equivalent emissions
from the industrial processes and product use sector. Between 1990 (1 629 kt CO2 eq) and 2021 (4 137
kt CO2 eq.), total carbon equivalent emissions increased by 154%. The increase in emissions is driven
exclusively by the increase in CO2 emissions from ammonia production, soda ash production and N2O
emissions from nitric acid production.
Figure 4.11 depicts the share of CO2 equivalent emissions from chemical industry. The CO2 eq. emissions
from nitric acid production are (48.9%), followed by ammonia production (36%) and soda ash production
(14.9%). Carbide use and petrochemical production are much smaller contributors to emissions (0.21%
and 0.03%, respectively).
There is no production of adipic acid, caprolactam, glyoxal, glyoxylic acid, or titanium dioxide produced
in Türkiye, therefore emissions are reported as “NO” for these subcategories.
Figure 4.11 CO2 emissions from chemical industry, 2021
Petrochemicals and carbon black
production
0.03%
Nitric acid
production
48.90%
Soda ash
production
14.87%
Carbide
production
0.21%
Ammonia
production
35.99%
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4.3.1. Ammonia production (Category 2.B.1)
Source Category Description:
Ammonia is a major industrial chemical and the most important nitrogenous material produced. Ammonia
gas is used directly as a fertilizer, in heat treating, paper pulping, nitric acid and nitrates manufacture,
nitric acid ester and nitro compound manufacture, explosives of various types, and as a refrigerant.
Amines, amides, and miscellaneous other organic compounds, such as urea, are made from ammonia.
Natural gas is used as the feedstock for ammonia production in Turkish production plants. CO2 is formed
during reforming of natural gas for obtaining hydrogen and then it is reacted with nitrogen to synthesis
ammonia. The overall reforming reaction and ammonia synthesis reactions are given below.
Overall reforming reaction:
0.88CH4 + 1.26 Air + 1.24 H2O → 0.88CO2 + N2 +3H2
Ammonia synthesis reaction:
N2 + 3H2 → 2NH3
Ammonia production requires the combustion of fuels for the energy demand of the process. Besides
being used as feedstock, natural gas is also used for meeting the energy requirement of the process.
Both the emissions due to the ammonia production process and the fuel combustion for the energy
demand are included in 2.B.1 CFR category. To avoid double counting, the total quantities of natural gas
used in ammonia production is subtracted from the quantity reported under energy use in the energy
sector.
IGSAS is one of three ammonia plants in Türkiye which started its operation in 1977. In 1993 second
ammonia plant Gemlik Gubre and in 2020 third ammonia plant ETI Gubre started its operations. IGSAS
also produces urea by using CO2 gas as feedstock. CO2 is separated from the synthesis gas in the
decarbonising step within the ammonia production process. Then, some of the CO2 gas is used in the
urea production process and the remaining gas is released to atmosphere. The chemical reaction that
produces urea is:
2NH3 + CO2 → NH3 COONH4 → CO (NH2)2 + H2O
The figure 4.12 shows the CO2 emissions from ammonia production as well as the amount of CO2
recovered.
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Industrial Processes and Product Use
Overall, between 1990 (425 kt CO2 eq.) and 2021 (1 489 kt CO2 eq.), emissions from ammonia production
increased by 250.5%. There are large inter-annual changes in CO2 emissions from ammonia production.
Rapid increases in emissions can be seen shortly after periods of economic downturns.
In Türkiye; due to economic factors, there was no ammonia production in 2007 and 2009 as shown in
the figure below. During these two years, ammonia was imported to meet domestic demand.
Figure 4.12 CO2 emissions and removals from ammonia production, 1990-2021
2000
1800
CO2 Emission (kt)
1600
CO2 Removal (kt)
1400
Net CO2 emissions
1200
1000
800
600
400
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
200
Methodological Issues:
In Türkiye all of the three ammonia production plants use natural gas as feedstock. Tier 2 method is used
in accordance with the 2006 IPCC Guidelines. As an initial step, the total fuel requirement (both as
feedstock and as combusted fuel for energy demand) is estimated by determining the total quantity of
ammonia produced and the fuel requirement per unit of output. In order to calculate CO2 emissions; the
total fuel requirement is multiplied by the country-specific carbon content and the carbon oxidation factor.
Where:
𝑇𝑇𝑇𝑇𝑇𝑇 = �(𝐴𝐴𝐴𝐴� ∙ 𝐹𝐹𝐹𝐹� )
�
TFR= total natural gas requirement, GJ
APj = ammonia production using natural gas in process type j, tonnes
FRj = fuel requirement per unit of output in process type j, GJ/tonne ammonia produced
𝐸𝐸��� = �(𝑇𝑇𝑇𝑇𝑇𝑇 ∙ 𝐶𝐶𝐶𝐶𝐶𝐶 ∙ 𝐶𝐶𝐶𝐶𝐶𝐶 ∙ 44/12) − 𝑅𝑅��
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Industrial Processes and Product Use
Where:
ECO2 = emissions of CO2, kg
TFR= total fuel requirement for natural gas, GJ
CCF= carbon content factor of natural gas, kg C/GJ
COF= carbon oxidation factor of natural gas, fraction
RCO2 = CO2 recovered for downstream use (urea production), kg
Collection of activity data
Ammonia production and fuel requirement data are obtained from producers on annual basis. The survey
on ammonia production is sent to the producer companies every year. The producers inform that
ammonia production and natural gas consumption data are measured by on-line flow meters in the
process whereas urea production data is calculated from the raw material consumption.
Due to the fact that there are only three ammonia producers in Türkiye, activity data are confidential.
Therefore, production data are given as 1990=100 and all years are reported relative to ammonia
production in 1990.
The total amount of urea produced in ammonia plants is shown in the following table where the urea
production data and the ammonia production data are given with respect to 1990=100 by years.
Therefore, one can compare the urea production and the ammonia production by years. Türkiye assumes
0.733 tonnes of CO2 are required per tonnes of urea produced. This value is taken from the 2006 IPCC
Guidelines.
Table 4.13 Ammonia production and CO2 emissions, 1990-2021
180
Year
Ammonia
Production
(1990=100)
Urea
Production
(1990=100)
CO₂
Emission
(kt)
CO₂
Removal
(kt)
Net CO₂
Emission
(kt)
1990
100
100
915
491
425
1995
82
85
764
415
2000
15
14
158
70
2005
104
77
945
378
2010
21
17
201
82
2011
122
77
1232
376
2012
142
65
1360
321
2013
97
54
908
263
2014
107
35
993
174
2015
157
64
1503
314
2016
105
44
1002
215
2017
82
65
844
319
2018
150
74
1413
364
2019
97
68
893
333
2020
97
76
916
371
2021
183
75
1856
367
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88
567
119
856
1039
645
818
1190
787
525
1050
560
545
1489
180
Industrial Processes and Product Use
Choice of emission factor
Türkiye applies the carbon content of natural gas and an oxidation factor to the total fuel requirement to
estimate emissions. The carbon content of the natural gas is provided by BOTAS (Petroleum Pipeline
Corporation) and it is the same as that used in the energy sector.
Uncertainties and Time-Series Consistency:
Because a country specific EF is used for the calculation of emissions from ammonia production,
uncertainty is taken as ±5%. Consistent with the 2006 IPCC Guidelines, due to the use of plant specific
activity data, the uncertainty value for AD is considered as ±2%.
In 2020 submission, uncertainty for CO2 emissions from category 2.B.1 was quantified using the Monte
Carlo simulation. The MC analysis resulted with (-7.46%,+7.54%) combined uncertainty. Detailed
information is in Annex 2.
Source-Specific QA/QC and Verification:
There are three ammonia producers in the Turkish market. All producers utilize natural gas to produce
ammonia and use the same process. Hence their implied emission factors are comparable. When
compared they are found consistent. Furthermore, total ammonia production data of Türkiye obtained
from the producers is checked with data from PRODCOM every year.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
Moreover, a QA work was conducted by an external reviewer from CITEPA (Technical Reference Center
for Air Pollution and Climate Change) for this category in January 2020.
Recalculation:
A correction in carbon content factor of natural gas results increase in emissions from ammonia production
for the years 2018 and 2019 with 11.1 kt CO2 and 14.9 kt CO2 respectively.
Planned Improvement
No further improvements are planned regarding this source.
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4.3.2. Nitric acid production (Category 2.B.2)
Source Category Description:
Nitrous oxide (N2O) is emitted during the production of nitric acid which is a raw material mainly in the
manufacturing of nitrogenous-based fertilizer. Nitric acid is also used in the production of explosives, for
metal etching and in the processing of ferrous metals.
In Türkiye; these are four nitric acid plants, IGSAS is in operation since 1961, Toros Tarım since 1972,
Gemlik Gubre since 2006 and BAGFAS since 2015. These are medium pressure combustion plants. Some
of these plants indicate their use of a selective catalytic reduction system.
N2O emissions were relatively stable between 1990 (3.57 kt N2O) and 2004 (2.4 kt N2O). Emissions from
nitric acid production is not stable between 2005 and 2009 as can be seen from the figure 4.13, this is
due to a new nitric acid plant starts production in 2006. Moreover, one of the nitric acid plants starts
using an abatement technology in 2008 which decreases its emission factor. N2O emissions reached in
2021 (6.79 kt N2O). In 2016 and 2017 N2O emissions was 4.09 kt and 3.9 kt it is much less than year
2014 due to dramatic decrease of production in one big capacity nitric acid plant.
Figure 4.13 N2O emissions from nitric acid productions, 1990-2021
8
7
kt
6
5
4
3
2
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
1
Methodological Issues:
N2O emissions from nitric acid production are not a key category in Türkiye. N2O emissions are calculated
using the T1 method in the 2006 IPCC Guidelines. Total nitric acid production is multiplied by an emission
factor as shown below.
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Industrial Processes and Product Use
Where:
EN2O = EF ∙ NAP
EN2O = N2O emissions, kg
EF = N2O emission factor (default), kg N2O/tonne nitric acid produced
NAP = nitric acid production, tonnes
Collection of activity data
Nitric acid production data were obtained from plants. A questionnaire is sent to nitric acid production
plants every year and the production data is filled by the operators. Production data are reported for
100% concentration HNO3 and the quantities are determined by flow meters measuring the nitric acid
production flow through the pipelines and a totalizer sums up to give the annular production data.
Choice of emission factor
There are four nitric acid production plants, IGSAS, Toros Tarım, Gemlik Gubre and BAGFAS. Emission
factors are determined according to their usage of abatement technology and its efficiency. However, the
emission factors for each plant and the total nitric acid production cannot be revealed due to
confidentiality reasons between the years 1990 and 2015. Total nitric acid production is given in the table
below.
Table 4.14 Nitric acid production and N2O emissions, 1990-2021
Year
Nitric acid production
Total N2O emission (kt)
1990
C
3.57
1995
C
3.37
2000
C
2.84
2005
C
4.54
2010
C
5.55
2011
C
5.84
2012
C
5.96
2013
C
5.99
2014
C
6.07
2015
863
4.88
2016
771
4.09
2017
778
3.88
2018
1 066
6.12
2019
2020
2021
1 303
1 300
1 349
6.77
6.73
6.79
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Uncertainties and Time-Series Consistency:
The 2006 IPCC Guidelines recommended default uncertainty value of ± 20% is used for the EF, consistent
with the value in Table 3.3 for medium pressure combustion plants.
Türkiye applies the default IPCC uncertainty value for AD uncertainty of ± 2%, which is in line with the
2006 IPCC Guidelines Volume 3 (page 3.25).
Category 2.B.2 (Nitric acid production) employed a Monte Carlo uncertainty analysis which causes a
combined uncertainty as ±20.59% for N2O emissions in 2020 submission. Detailed explanation of
Approach 2 method is in Uncertainty part of this inventory report (Annex 2).
Source-Specific QA/QC and Verification:
Plant specific nitric acid production data, which are collected from the plants by an annual questionnaire
for this inventory calculations, are compared with TurkStat PRODCOM -Turkish national industrial
production statistics- and found consistent. According to the monitoring, reporting and verifying
regulation, nitric acid plants are obliged to report their emissions to the Ministry of Environment,
Urbanization and Climate Change by measuring their emissions with N2O gas monitoring device.
Calculated and reported emissions are compared.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
Furthermore, a QA work was conducted by an external reviewer from CITEPA (Technical Reference Center
for Air Pollution and Climate Change) for this category in January 2020.
Recalculation:
Inconsistent activity data of a nitric asit producer changed retrospectively which results an average
increase in emissions of 0.56 kt N2O for the years 2005, 2006, 2007, 2008, 2010, 2011, 2014, 2015, 2016
and 2017.
Planned Improvements:
No further improvement are planned regarding this source.
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4.3.3. Adipic acid production (Category 2.B.3)
There is no adipic acid production in Türkiye during the period 1990-2021.
4.3.4. Caprolactam, glyoxal and glyoxylic acid production (Category 2.B.4)
There is no caprolactam, glyoxal and glyoxylic acid production in Türkiye during the period 1990-2021.
4.3.5. Carbide production (Category 2.B.5)
Source Category Description:
The production of carbide can result in emissions of CO2, CH4, CO and SO2. Silicon carbide is a significant
artificial abrasive. It is produced from silica sand or quartz and petroleum coke. Calcium carbide is used
in the production of acetylene and as a reductant in electric arc furnaces. The acetylene is used for
welding applications. Therefore, use of acetylene also results in emissions and it is accounted in the IPPU.
Calcium carbide is produced by the reaction of metallurgical coke and lime under electric arc according
to the reaction given below.
CaO + 3C → CaC2 + CO (+ ½ O2 → CO2)
Calcium carbide is used either as a reductant in the steel making process or the feedstock for acetylene
production in Türkiye. Afterwards acetylene is used as fuel in the welding applications. The combustion
of acetylene in welding applications give emissions according to the reaction given below and it is
accounted in IPPU sector.
CaC2 + 2H2O → Ca(OH)2 + C2H2 (+ 2.5 O2 → 2CO2 + H2O)
In Türkiye there is no silicon carbide production. Calcium carbide has been produced in Türkiye till 2015.
The amount of coke used is deducted from the Energy part of the NIR to avoid double count.
CO2 emissions from calcium carbide production and usage of carbide in acetylene was 59 kt CO2 in 1990.
Year by year carbide production decreased and in 2015 the carbide production and usage of carbide in
acetylene production emissions was 12.1 kt CO2. Finally, in 2016 the production line of carbide was closed
due to economic reasons. And use of carbide in acetylene continued and resulted 8.5 kt CO2 emissions in
2021.
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Figure 4.14 CO2 emissions due to carbide production, 1990-2021
70
60
kt
50
40
30
20
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
10
Methodological Issues:
Carbide production is not a key category. Calcium carbide was produced in Türkiye by a single plant till
2015 and then the production line was closed. The calculation of emissions is based on plant-specific
data.
Where:
ECO2 = AD • EF
ECO2 = emissions of carbon dioxide
AD = activity data on carbide production
EF = CO2 emission factor.
The use of calcium carbide also leads to the emissions and it is calculated by the Tier 1 methodology
suggested in the guideline. The amount calcium carbide used is multiplied with the proper emission factor
suggested in the guideline.
Collection of activity data
The calcium carbide production period of a single plant which finalize its production in 2015, the calcium
carbide production data was directly obtained from the producer on an annual basis by a questionnaire.
Both amount of carbide produced and amount of raw material used as metallurgical coke data were
obtained. However, emissions were calculated by using the carbide production data.
Confidential production data are provided relative to 1990, along with CO2 emissions from calcium carbide
production as can be seen in the table below.
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Table 4.15 Calcium carbide production and CO2 emissions, 1990-2021
Calcium Carpide
Production
(1990=100)
Calcium carpide
use (kt)
CO2 Emissions
from carbide
production (kt)
CO2 Emissions
(kt)
1990
100.0
15.9
41.5
59.0
1995
24.2
6.9
10.0
17.6
2000
43.3
13.6
18.0
32.9
2005
27.1
10.8
11.2
23.1
2010
19.8
9.4
8.2
18.6
2011
28.0
10.7
11.6
23.4
2012
28.8
8.1
11.9
20.9
2013
27.5
9.4
11.4
21.7
2014
25.4
9.0
10.5
20.5
2015
13.9
5.7
5.8
12.1
2016
0.0
7.0
0.0
7.7
2017
0.0
6.9
0.0
7.6
2018
0.0
5.7
0.0
6.2
2019
0.0
7.4
0.0
8.2
2020
0.0
6.9
0.0
7.5
2021
0.0
7.7
0.0
8.5
Years
Choice of emission factor
Due to confidentiality the emission factor of the carbide production cannot be revealed.
Uncertainties and Time-Series Consistency:
The greatest contributor to the uncertainty is that the assumption made upon all of the carbide is used
for producing acetylene gas. Depending on the expert judgement the uncertainty value of the EF is taken
±20% while the default uncertainty value of the activity data is taken as 5% consistent with the 2006
IPCC Guidelines. (Volume 3 Page 3.45).
In 2020 submission combined uncertainty estimates of Carbide production (Category 2.B.5) are quantified
using the Monte Carlo simulation. Uncertainty in Category 2.B.5 CO2 emissions in 2018 are estimated at
-20.55% to +20.87% with Approach 2 method. For more details, please refer to the Uncertainty chapter
at the end of the Inventory report in Annex 2.
Source-Specific QA/QC and Verification:
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
Plant-specific production data are compared with national statistics data available from PRODCOM
(National Industrial Production Statistics) and found consistent.
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In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
Moreover, a QA work was conducted by an external reviewer from CITEPA (Technical Reference Center
for Air Pollution and Climate Change) for this category in January 2020.
Recalculation:
No recalculations have been made to emissions from this category.
Planned Improvements
No further improvements are planned regarding this source.
4.3.6. Titanium dioxide production (Category 2.B.6)
There is no titanium dioxide production in Türkiye during the period 1990-2021.
4.3.7. Soda ash production (Category 2.B.7)
Source Category Description:
Soda ash (sodium carbonate, Na2CO3) is a white crystalline solid that is used as a raw material in a large
number of industries including glass manufacture, soap and detergents, pulp and paper production and
water treatment. CO2 is emitted from the use of soda ash and these emissions are accounted for as a
source under the relevant using industry as discussed in Volume 3, Chapter 2 in the 2006 IPCC Guidelines.
CO2 is also emitted during production of soda ash, with the quantity emitted dependent on the industrial
process used to manufacture soda ash.
Emissions of CO2 from the production of soda ash vary substantially with the manufacturing process. Four
different processes may be used commercially to produce soda ash. Three of these processes,
monohydrate, sodium sesquicarbonate (trona) and direct carbonation, are referred to as natural
processes. The fourth, the Solvay process, is classified as a synthetic process. Calcium carbonate
(limestone) is used as a source of CO2 in the Solvay process.
There are three soda ash plants in Türkiye. One of these plants produces soda ash by utilizing trona and
began operation in 2009, while the other produce synthetic soda ash (solvay process) and began
operation in 1969. Third one started production in 2018.
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In the Solvay process, sodium chloride brine, limestone, metallurgical coke and ammonia are the raw
materials used in a series of reactions leading to the production of soda ash. Ammonia, however, is
recycled and only a small amount is lost. From the series of reactions CO2 is generated during calcination
of limestone. The generated CO2 is captured, compressed and directed to Solvay precipitating towers for
consumption in a mixture of brine (aqueous NaCl) and ammonia. Although CO2 is generated as a byproduct, the CO2 is recovered and recycled for use in the carbonation stage and in theory the process is
neutral, i.e., CO2 generation equals uptake.
Soda ash production by utilizing trona started in 2009 while emissions from soda ash production using
the solvay process are not estimated due to the carbon neutral characteristic of the process. Therefore;
for the years 1990-2008, emissive soda ash production is reported as not occurring. In the figure below
you can see the trend of the CO2 emissions from soda ash productions. In the year 2009 a small amount
of CO2 emitted due to plant was not working full capacity due to start up. In 2021 emissions from soda
ash decreased by 15.9% with respect to previous year and it was 615 kt of CO2.
Figure 4.15 CO2 Emissions resulting from soda ash production 2009-2021
700
600
(kt)
500
400
300
200
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
0
2009
100
Methodological Issues:
The natural production process of soda ash results in CO2 emissions. Türkiye applies a Tier 1 method, for
this non-key category, quantifying emissions based on the plant-specific activity data and default emission
factor, and using the following formula:
Where:
𝐸𝐸�� =AD ∙ EF
ECO2 = emissions of carbon dioxide in tonnes
AD = quantity of soda ash produced (from trona) in tonnes
EF = emission factor per unit of soda ash produced
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Collection of activity Data
The amount of soda ash produced is is directly taken from the plants. Data are acquired on a yearly basis
and it is based on a questionnaire which is sent to the plants.
The production trend and emissions can be seen from the table below.
Table 4.16 Soda ash production and CO2 emissions, 1990-2021
Soda ash production
by utilizing Trona
(2009=100)
CO2 Emissions (kt)
1990-2008
NO
NO
2009
100
24
2010
451
110
2011
538
132
2012
535
131
2013
511
125
2014
554
135
2015
549
134
2016
588
144
2017
850
208
2018
1 905
466
2019
2 278
557
2020
2 170
531
2021
2 514
615
Year
Choice of emission Factor
The EF is confidential. The EF was held constant over the time series.
Uncertainties and Time-Series Consistency:
Türkiye assumes that the uncertainty of the EF is 1% and the uncertainty of the AD is ±5% in consistent
with the 2006 IPCC Guidelines (2006 IPCC Guidelines, Volume 3 page 3.55).
Moreover, Monte Carlo analysis has been carried out for the CO2 emissions from soda ash production for
2020 submission and it resulted with -5.10% to +5.15% combined uncertainty. Further information about
Monte Carlo analysis of soda ash production can be seen in Uncertainty chapter (Annex 2).
Source-Specific QA/QC and Verification:
On the PRODCOM soda ash production data is available since 2009. PRODCOM data and plant specific
data are compared and found consistent. Moreover, according to the 2006 IPCC Guidelines the emission
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from soda ash production can be calculated by either using the soda ash production data or using the
trona consumption data. The emissions are calculated and reported using the soda ash production data.
However, for quality control purpose the emissions is also calculated based on the trona consumption.
The plant mines the trona by solving it underwater and then pumps it into the process. The amount of
solution pumped and its purity is known by the plant. Therefore, the amount of trona utilized is calculated
and reported by the plant. When the two methods are compared 12% difference is found for 2017.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
In addition, a QA work was conducted by an external reviewer from CITEPA (Technical Reference Center
for Air Pollution and Climate Change) for this category in January 2020.
Recalculation:
No recalculations have been made to emissions from this category.
Planned Improvements
No further improvements are planned regarding this source.
4.3.8. Petrochemical and carbon black production (Category 2.B.8)
Source Category Description:
The petrochemical industry uses fossil fuels (e.g., natural gas) or petroleum refinery products (e.g.,
naphtha) as feedstocks. Within the petrochemical industry and carbon black industry, primary fossil fuels
(natural gas, petroleum, coal) are used for non-fuel purposes in the production of petrochemicals and
carbon black. The use of these primary fossil fuels may involve combustion of part of the hydrocarbon
content for heat raising and the production of secondary fuels (e.g., off gases).
Türkiye reports CO2 emissions from petrochemicals production. There is a single petrochemical producer
in Türkiye and the company name is PETKIM. Carbon black was produced by PETKIM till 2001, however
it was at a different production site and this production site was closed in 2001.
During the production of petrochemicals various gases are generated. However PETKIM has a closed
circuit that collects all the process gases, which includes greenhouses gases and combustible gases, and
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uses it as fuel. This fuel is named fuel gas and emissions due to the combustion of fuel gas is included in
the energy sector. However, some of the fuel gas is combusted in the flare stacks and the emissions from
the flare stacks are included in the IPPU category.
The figures below show the CO2 emissions from flare stacks from the petrochemicals production at main
production site of PETKIM between 1990 and 2021 and also carbon black production emissions at Kocaeli
production site between 1990 and 2001.
Since PETKIM has a closed system for its stacks, all the methane emissions are assumed to be collected
in the fuel gas. Hence it is covered in the energy sector.
Table 4.17 CO2 emissions from flaring in petrochemical sector, 1990-2021
(kt)
CO2 emissions
from carbon
black production
CO2 emissions from
flaring
1990
80.1
1.35
81.5
1995
104.7
1.35
106.1
2000
91.9
1.35
93.2
2005
NO
1.35
1.35
2010
NO
1.35
1.35
2011
NO
1.35
1.35
2012
NO
1.35
1.35
2013
NO
1.35
1.35
2014
NO
1.35
1.35
2015
NO
1.35
1.35
2016
NO
1.32
1.32
2017
NO
1.35
1.35
2018
NO
1.19
1.19
2019
NO
1.35
1.35
2020
NO
1.35
1.35
2021
NO
1.35
1.35
Year
Total CO2 emissions
in petrochemical
industry
Methodological Issues:
CO2 emissions are calculated by multiplying the amount of fuel gas burnt with the
Where:
192
ECO2= Mfuel gas x Carbon content of fuel gas x 44/12
ECO2= CO2 emissions from production of petrochemical in tonnes
M fuel gas = Amount of fuel gas combusted as the flare gas in tonnes
44/12 = The molar weight ratio of carbondioxide to carbon
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CO2 emissions from carbon black production are calculated by Tier 1 methodology. The annual production
amount is multiplied by the default CO2 mission factor.
ECO2 = Mcarbon black x Carbon Black CO2 EF
Carbon black production also causes CH4 emissions. CH4 emissions are calculated by Tier 1 methodology.
The annual production amount is multiplied by the default CH4 emission factor.
ECH4 = Mcarbon black x Carbon Black CH4 EF
Collection of activity data
There is a single producer of petrochemicals in Türkiye. The amount of fuel gas combusted in the flare
stacks is asked to the producer by an annual questionnaire. The amount of fuel gas combusted is
confidential since there is one single company producing petrochemicals.
Choice of emission factor
The fuel gas composition is asked to the producer. The volumetric gas composition data is gathered and
it is used to calculate the carbon content of fuel gas. Since there is one single company in Türkiye in the
field of petrochemical production its fuel gas characteristic is confidential.
Uncertainties and Time-Series Consistency:
As 2006 IPCC Guidelines recommended default uncertainty values is used as ±10% for EF and AD based
on expert judgement and table 3.27 in the 2006 IPCC Guidelines, Volume 3.
Uncertainty in CO2 emissions from category 2.B.8 was quantified using the Monte Carlo simulation in 2020
submission. Combined uncertainty in CO2 emissions in 2018 is estimated with a symmetrical normal
distribution as ±14.29%. Further information about Monte Carlo analysis of petrochemical and carbon
black production can be seen in Uncertainty chapter (Annex 2).
Source-Specific QA/QC and Verification:
A site visit was done to the PETKIM in 2017 by the TurkStat's inventory compilers. During this site visit
all the process flow charts were examined and discussed with PETKIM engineers in order to understand
emission pathways and ensure all emissions are included and not double counted.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
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QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
A QA work was conducted by an external reviewer from CITEPA (Technical Reference Center for Air
Pollution and Climate Change) for this category in January 2020.
Recalculation:
No recalculations have been made to emissions from this category.
Planned Improvements
No further improvements are planned regarding this source.
4.3.9. Fluorochemical production (Category 2.B.9)
There is no fluorochemical production in Türkiye during the period 1990-2021.
4.4.
Metal Industry (Category 2.C)
In 2021, the metal industry was responsible for 12 909 kt CO2 eq., 17.2% of total emissions from the
industrial processes and product use sector. The vast majority of emissions in the metal industry (92.3%)
are from iron and steel production. Zinc industry was responsible for 578.9 kt CO2 eq., 4.5% of metal
emissions, ferroalloys production 193 kt CO2 eq., 1.5% of metal emissions and aluminium production was
responsible for 124.6 kt CO2 eq., 1% of metal emissions. Magnesium production was responsible for 88.3
kt CO2 eq. contributed 0.7% and lead production was responsible for 10 kt CO2 eq. contributed 0.1% of
sector emissions (see Figure 4.16).
Between 1990 (7 620.3 kt CO2 eq.) and 2021 (12 909 kt CO2 eq.), emissions from the metal industry
increased by 69.4%, again driven in large part by the iron and steel industry, which increased by 71.5%
during the time period, from 6 946.7 kt CO2 eq. in 1990 to 11 914.2 kt CO2 eq. in 2021. This increase in
emissions was partially offset by the elimination of PFC emissions in aluminium production (PFC emissions
were 472.8 kt CO2 eq. in 1990 and it is 6.8 kt CO2 eq. in 2021).
Emissions from secondary Zinc production are included for the first time in this submission. Additionally,
primary magnesium production data have been gathered and included between the years 2016-2021 for
this submission.
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Figure 4.16 Emissions from metal industry, 2021
Zinc
4.5%
Ferroalloys
1.5%
Iron and steel
92.3%
Aluminum
1.0%
Magnesium
0.7%
Lead
0.1%
4.4.1. Iron and steel production (Category 2.C.1)
Source Category Description:
Iron and steel production processes result in CO2 and CH4 emissions to be covered under the IPPU
category since carbon is used in the reduction process of iron oxides.
In Türkiye currently there are three integrated iron and steel production plants. These facilities include
sinter production units, blast furnaces for pig iron production, and basic oxygen furnaces. Besides these
plants, there are electric arc furnace mills operating in Türkiye. However, there is no direct reduced iron
(DRI) production in Türkiye. Emissions from the combustion of carbon containing fuels (i.e. natural gas,
fuel oil) for energy purposes are included in the energy chapter of this report.
The integrated steel production plants demand iron ore. These plants meet their need from both domestic
and foreign markets. In Türkiye there is currently one plant producing pellet iron in order to supply the
iron ore demand of the integrated steel plants.
Blast furnace units for pig iron production are the most emissive units among the iron and steel production
processes. Iron oxide reduces into iron metal when reacted with carbon monoxide in the blast furnaces
as shown in the reactions represented in equations below.
Fe2O3 + 3CO → 2Fe + 3CO2
3 Fe2O3(s) + CO(g) → 2 Fe3O4(s) + CO2(g)
Fe3O4(s) + CO(g) → 3 FeO(s) + CO2(g)
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Carbon monoxide is generated in the blast furnace from the carbon containing fuels (mainly coke) as can
be seen in equation below. Coke provides the necessary carbon for both the reduction reactions as well
the heat needed for melting the iron and the impurities. Besides, coke provides mechanical strength for
the blast furnace burden.
2 C(s) + O2(g) → 2 CO(g)
Limestone is used in the blast furnaces for removing acidic impurities from the ore. When limestone is
heated up to about 1500 °C it releases carbon dioxide and left as CaO by the reaction shown in equation
below. Then CaO reacts with the acidic impurities and deposits at the bottom of the blast furnace.
CaCO3(s) →CaO(s) + CO2(g)
Sinter production is also an emissive process within the iron and steel industry. Sinter plants in Türkiye
are within the integrated steel plants. Sintering is a heat treatment process that agglomerates iron ore
fines and metallurgical wastes (i.e. collected dusts, sludge) into larger, stronger and porous particles
necessary for blast furnaces charging. The sintering process involves the heating of iron ore fines by
burning coke fines to produce a semi-molten mass that solidifies into porous pieces of sinter. Coke gas is
usually used to ignite the sinter blend. This process also involves reduction of some iron oxides into iron
metal within the iron ore fines. Therefore, the same reactions given above for the reduction of iron oxides
also works for the sintering process and causes CO2 release. During the sintering process high
temperatures are achieved and limestone is calcined and release CO2 emissions.
Basic Oxygen Furnaces (BOF) are also a part of the integrated steel plants. BOF processes the product of
the blast furnace which is molten iron to produce steel. The BOF process also emits CO2. The process
involves oxygen blowing into the molten iron and stirring it. The oxygen reacts with impurities to purify
molten iron and also reacts with dissolved carbon leaving as CO2. This process converts iron into steel.
Electric Arc Furnaces (EAF) is another process unit for producing steel. Unlike BOF, only scrap iron and
steel is used in the EAF to produce steel. The scrap metal is melted using high voltage electric arcs. There
would be iron oxides in the feed of the EAF. Therefore, these iron oxides should be reduced to iron with
the same reactions given above that cause CO2 emissions. Metallurgical coke, petroleum coke, graphite,
anthracite, carbon granules and natural gas may be used as the carbon source. Besides that, oxygen is
blown into the molten steel in order to remove excess carbon and other impurities and to improve steel
quality. This process step also releases CO2 emissions due to reaction of oxygen and carbon.
Iron and steel production is classified as heavy industry and it requires vast amount of energy. All of the
integrated steel plants in Türkiye recycle exhaust gases of the Blast Furnaces and Basic Oxygen Furnaces
to meet up their energy requirement. These gases are collected and burnt in order to heat up the coke
ovens, produce the high pressure steam requirement of the plant, pre heat the blast furnace air, produce
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electricity, heat up the rolls and for other small issues. Their emissions are covered in the energy sector
of this report. Besides, integrated iron and steel production plants produce lime for their own consumption
and lime production also causes CO2 emission and it is covered in lime production part of IPPU.
In Türkiye there are currently 3 integrated iron and steel plants and 26 electric arc furnaces mills
operating. The table below presents 2.C.1 category CO2 emissions between 1990 and 2021, and figure
4.17 shows the 2.C.1 category CO2 emissions cumulatively revealing the emissions trend in the iron and
steel production.
Table 4.18 CO2 emissions allocations in 2.C.1 category, 1990-2021
Emissions from
pellet
production
(kt)
Total
emissions in
2.C.1 CRF
category
Year
Emissions from Iron
and Steel Production
(integrated plants)
Emissions from
Steel Production
(EAF plants)
Emissions from
sinter production
1990
5 522
353
1 033
31
6 939
1995
4 048
605
988
26
5 668
2000
3 800
648
1 242
28
5 718
2005
4 449
1 057
1 358
34
6 898
2010
5 858
1 488
1 480
45
8 870
2011
6 433
1 800
1 642
45
9 920
2012
6 824
1 891
1 703
46
10 464
2013
6 892
1 760
1 867
44
10 564
2014
6 845
1 691
1 890
47
10 472
2015
7 235
1 458
1 985
46
10 725
2016
8 140
1 555
1 961
47
11 704
2017
7 871
1 849
2 150
45
11 914
2018
7 831
1 837
2 220
45
11 933
2019
6 857
1 629
2 067
46
10 600
2020
6 438
1 713
1 936
46
10 133
2021
7 486
2 058
2 306
47
11 898
Figure 4.17 CO2 emissions allocations within the 2.C.1 CRF category, 1990-2021
14 000
(kt)
12 000
10 000
Emissions from pellet
production
8 000
Emissions from sinter
production
6 000
4 000
Emissions from Steel
Production (EAF plants)
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2 000
Emissions from Iron and
Steel Production
(integrated plants)
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CO2 emissions from iron and steel production in 2021 was 11.9 million tons and it increased by 71.5%
since 1990. Beginning by the year 2000 steel production have increased and Türkiye became the world's
7th biggest6 crude steel producer reaching 40.6 million tons by 2021. In 2021 steel production increased
by 15%. Steel production capacity of Türkiye is over 50 million tons.
Methodological Issues:
For the calculation of CO2 emissions from iron and steel production and sinter production in the integrated
plants, the 2006 IPCC Tier 3 method is used.
The Tier 3 methodology equation for calculating CO2 emissions from iron, steel and sinter production in
the integrated plants is as follows:
Where:
ECO2 = emissions of CO2 to be reported in IPPU Sector, tonnes
a = input material a
b = output material b
Qa = quantity of input material a
Ca = carbon content of material a
Qb = quantity of output material b
Cb = carbon content of material b
44/12 = stoichiometric ratio of CO2 to C
For the calculation of CO2 emissions from pellet production, the 2006 IPCC Tier 1 method is used where
total amount of pellet produced is multiplied with the emission factor.
Where:
ECO2, non-energy = P ∙ EFp
ECO2, non-energy = emissions of CO2 to be reported in IPPU Sector, tonnes
P = quantity of pellet produced nationally, tonnes
EFp = emission factor, tonnes CO2/tonne pellet produced
6
198
https://worldsteel.org/media-centre/press-releases/2021/global-crude-steel-output-decreases-by-0-9-in-2020/
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CO2 emissions from steel production in EAFs are calculated by applying the Tier 2 method which is the
carbon balance calculation on an aggregated national level. The equation is given below:
The CH4 emissions from sinter production are calculated using Tier 1 methodology. This is multiplication
of the production data with the default emission factor as suggested in the 2006 IPCC Guidelines, the
equations are shown below.
ECH4, non-energy = SI ∙ EFSI
Where:
ECH4, non-energy = emissions of CH4 to be reported in IPPU Sector, kg
SI = quantity of sinter produced nationally, tonnes
EFSI = emission factor, kg CH4/tonne sinter produced
In Türkiye almost all of the by-product gases are collected and burnt for energy recovery. Therefore, it is
assumed that no methane is emitted due to the pig iron production under 2C1 CRF category.
Figure 4.18 shows the allocations of the emissions from integrated iron and steel plants between Energy
and IPPU sectors.
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Figure 4.18 Allocations of the emissions from integrated iron and steel plants
Collection of activity data
To estimate CO2 and CH4 emissions at integrated facilities, Türkiye collects activity data via annual basis
questionnaire from each of the three facilities. All the solid materials are weighted by scales whereas
gaseous materials are measured by flowmeters and the annual values are calculated by a computer
programmed totalizer.
Pellet is produced by a single company beside an iron mine in Türkiye. The activity data is obtained from
this company.
The quantity data of crude steel production and raw material consumption at electric arc furnaces is
obtained from Turkish Steel Producers Association by an annual basis questionnaire.
Each of the integrated facility keeps an energy balance table where all the fuel consumptions and
generations are recorded annually. These tables are the main data source for the fuel consumptions. The
consumption of non-fuel materials, (e.g. limestone, dolomite), are asked by a questionnaire.
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Sinter, pellet production and steel production by plant type are included in the table below.
Table 4.19 Sinter, pellet and iron & steel production by plant type, 1990-2021
(kt)
Year
1990
Total pellet
production
1 032
Total sinter
production
4 507
Steel production
(BOF)
4 401
Steel production
(EAF)
4 955
Total steel
production
9 356
1995
855
4 285
4 259
8 501
12 760
2000
948
5 007
5 372
9 096
14 468
2005
1 120
5 355
6 254
14 847
21 101
2010
1 493
5 845
8 444
20 905
29 349
2011
1 495
6 361
9 023
25 275
34 298
2012
1 543
7 356
9 500
26 560
36 059
2013
1 480
7 617
10 111
24 723
34 834
2014
1 550
7 928
10 483
23 752
34 235
2015
1 547
8 567
11 215
20 482
31 697
2016
1 565
9 834
11 545
21 846
33 392
2017
1 501
9 342
11 795
25 963
37 758
2018
1 513
9 798
11 734
25 799
37 533
2019
1 547
9 101
11 002
22 884
33 887
2020
1 524
8 866
11 283
24 056
35 338
2021
1 568
9 553
11 721
28 902
40 622
Figure 4.19 Comparing emissions (kt CO2 eq.) and steel production (kt) from BOFs anf EAFs
(kt)
30 000.0
25 000.0
20 000.0
15 000.0
10 000.0
0.0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
5 000.0
BOF Emissions (CO₂ eq.)
EAF Emissions (CO₂ eq.)
BOF Steel production
EAF Steel production
The CO2 eq. emissions and total steel production (kt) of integrated plants (BOF) and Electric Arc Furnaces
(EAF) are shown in the figure 4.19. In 2021, the BOFs produced 28.9% and EAFs produced 71.1% of
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total iron and steel whereas the BOFs contributed 82.7% and EAFs contributed 17.3% of total emissions
from iron and steel production.
Choice of emission factor
To estimate CO2 emissions from integrated facilities, Türkiye collects any available plant-specific data on
carbon content for integrated facilities and for the remaining materials the material-specific carbon
content values from Table 4.3 of the 2006 IPCC Guidelines are applied for the entire time series. To
determine carbon content, the facilities make laboratory analysis for the product iron and steel, for the
process gases and for the coals used in the plant.
In order to estimate CO2 emissions from EAFs, Türkiye collects raw material consumption and steel
production data. These input and output data are aggregated on national level and multiplied by the
default carbon contents for each raw material. However, the raw material consumption data is not
available before the year 2013. Hence the average implied emission factor found to be 0.0712 t CO2 /t
steel produced between 2013 and 2016, and this factor is applied for the previous years.
To estimate CO2 emissions from pellet production, the default emission factor (0.03 t CO2/t pellet) from
the 2006 IPCC Guidelines used for the entire time series.
To estimate CH4 emissions from sinter production, the default emission factor (0.07 kg CH4/t sinter) from
the 2006 IPCC Guidelines applied.
Emission factors used in the calculations are provided in the table below.
Table 4.20 Emission factors iron and steel production
Activity
CO2 EF
Pellet production (used in all-time series)
EAF steel production
Activity
0.03 t/t pellet
0.0712 t/t steel
CH4 EF
Sinter production (used in all-time series)
0.07 kg/t sinter
Uncertainties and Time-Series Consistency:
Uncertainties for the activity data and the emission factors are estimated to be 10% and 8%, respectively.
Because especially the activity data and the emission factors regarding the process gases (coke oven gas,
blast furnace gas, oxygen steel furnace gas) are quite uncertain.
An uncertainty analysis using the Monte Carlo technique was carried out to estimate emissions of CO2
and CH4 for 2.C.1 category and also to other IPPU categories in 2020 inventory year. Combined
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uncertainty in CO2 emissions in 2018 is estimated at the range of -29.05% to +29.32%, CH4 emissions is
estimated as -13.04% to +11.59% in 2020 submission. Further information is given in Uncertainty part
at the end of this inventory report (Annex 2).
Source-Specific QA/QC and Verification:
There are three integrated iron and steel plants in Türkiye and plant specific data are gathered from these
plants. These integrated steel plants were built as public economic enterprises and all of them have been
privatized until 2006. Due to significant improvements on data recording after privatization, the integrated
steel plants data are reliable after 2006. The integrated steel plants have similar steel production
techniques therefore their data can be compared to each other. Coke consumed/steel produced, coke
breeze consumed/sinter produced ratios are compared to each other in order to identify potential
inconsistencies and reporting errors.
Moreover,Turkish inventory team had site visits and held meetings with experts from the field on
integrated steel plants in 2016. Through the site visits and the meetings, process flow charts and data
reporting issues were discussed in order to identify potential inconsistencies and reporting errors.
In addition, carbon mass balance is done over each of the three integrated plant by considering all carbon
containing material input and output to the factories. So that the total emissions (both IPPU and Energy)
of the three plants are calculated. Then it is compared with the summation of each emission categories
(1.A.1.a, 1.A.1.c, 1.A.2.a, and 2.C.1) for iron and steel production. The comparison result is given in the
below.
Emissions calculated by carbon mass balance over integrated plants = 21 203 kt,
Summed up emissions for each CRF category for integrated plants = 19 884 kt,
Percentage of equivalence = 93.3%.
The percentage of equivalence is 96% when the data of the three integrated plants are aggregated
together, and on the plant basis the percentage of equivalence is at least 94%. The percentage of
equivalence shows that the calculated emissions are reliable, but still it can be improved.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
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Furthermore, a QA work was conducted by an external reviewer from CITEPA (Technical Reference Center
for Air Pollution and Climate Change) for this category in January 2020.
Recalculations:
Steel production data of an integrated plant for the years 1990 and 1995 are corrected due to availability
of retrospective data from Turkish Steel Producers Association. Limestone used in BOF data corrected by
one of the integrated plant and recalculated for the years 2018-2020. Furthermore, carbon content of
BOF and Blast Furnace gas data backcasted and recalculated.
These changes results, average recalculation calculated as 62.3 kt CO2 increase for the period of 19902020 and 1.3 kt CO2 increase for 2020. With respect to previous year, the currently submitted values for
the years 1990-2020 show an increase of 0.98% average recalculation rate.
Planned Improvements:
There is no further planned improvement in this sector.
4.4.2. Ferroalloys production (Category 2.C.2)
Source Category Description:
Ferroalloy is the term used to describe concentrated alloys of iron and one or more metals such as silicon,
manganese, chromium, molybdenum, vanadium and tungsten. Silicon metal production is usually included
in the ferroalloy group because silicon metal production process is quite similar to the ferrosilicon process.
These alloys are used for deoxidising and altering the material properties of steel. Ferroalloy facilities
manufacture concentrated compounds that are delivered to steel production plants to be incorporated in
alloy steels. Silicon metal is used in aluminium alloys, for production of electronics. Ferroalloy production
involves a metallurgical reduction process that results in significant CO2 emissions.
In Türkiye there are currently two ferrochrome producer. These two producer are using electric arc
furnaces to melt scrap iron and chromite ore in the pot. Some metallurgical coke is added in the pot to
reduce chromite and produce ferrochrome.
Between 2011 and 2014 some amount of ferrosilicon manganese was also produced. However, plants
are closed due to the high production costs.
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In this category; emissions from ferrochromium and ferrosilicon manganese production are considered.
Other types of ferroalloys are not produced in Türkiye on industrial scale.
Although Türkiye is rich in terms of chrome mines, ferrochrome production is relatively low. This is due
to high prices of energy in Türkiye. CO2 emissions from ferroalloys production are driven by mainly
ferrochrome production which is strongly depended on the energy prices. There was a decline in emissions
between 2000 (47.6 kt CO2) and 2004 (11 kt CO2) owing to one of the ferrochromium producers was
slowed down and finally out of operation during its privatization period. CO2 emissions generally climbed
until 2008 (92 kt CO2) with economic growth before decreasing again in 2009 (59 kt CO2) due to global
economic recession and low demand on steel. There was then a steep increase between 2009 and 2013
(184 kt CO2, an increase in emissions of 210%) due to two new investments on production of ferrosilica
manganese. However ferrosilica manganese production plants were closed in 2012 and 2013 due to high
energy costs. In 2021, CO2 emissions from ferroalloy production was 193 kt.
Figure 4.20 CO2 emissions from ferroalloys production, 1990-2021
200
180
CO2 emission (kt)
160
140
120
100
80
60
40
20
0
Methodological Issues:
Türkiye reports CO2 emissions from ferroalloys production following the IPCC Tier 1 approach, as shown
in equation below. Ferroalloys production is not a key category.
CO2 emissions from ferroalloys production
𝐸𝐸��� = �(𝑀𝑀𝑀𝑀� ∙ 𝐸𝐸𝐸𝐸� )
�
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Where:
ECO2 = CO2 emissions, tonnes
MPi = production of ferroalloy type i, tonnes
EFi = generic emission factor for ferroalloy type i, tonnes CO2/ tonne specific ferroalloy product
Collection of activity data
Activity data are obtained from the two ferrochrome producers by a production survey on the yearly basis
by TurkStat. Both the ferro-chromium production data and the reductant agent consumption data are
gathered for all the time series. The coke used in the ferro chromium production is deducted from the
total coke consumption of Türkiye in the energy sector to avoid a double counting.
Choice of emission factor
Türkiye applies the default CO2 emission factors for ferro-chromium (1.3 t CO2/t product) from the 2006
IPCC Guidelines.
Table 4.21 Ferroalloys production and emissions, 1990-2021
Total ferroalloy
production
(1990=100)
CO2
Emission
(kt)
1990
100
62
1995
97
60
2000
77
48
2005
53
32
2010
Years
206
138
85
2011
196
121
2012
184
113
2013
298
184
2014
205
126
2015
204
126
2016
219
135
2017
226
139
2018
276
170
2019
250
154
2020
240
148
2021
313
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Source-Specific QA/QC and Verification:
Ferroalloy production data was gathered directly from the plants. There are two ferro chrome producers
in Türkiye. Both of them supply ferro alloy production and coke consumption data. The production and
consumption ratios of the two producers are compared and found consistent. Furthermore, PRODCOM
data for ferro alloy production compared every year and found consistent.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
Moreover, a QA work was conducted by an external reviewer from CITEPA (Technical Reference Center
for Air Pollution and Climate Change) for this category in January 2020.
Uncertainties and Time-Series Consistency:
Since the calculations are based on default Tier 1EFs and company derived production data, uncertainty
values of EF are considered 25% and AD are 5% as recommended in Table 4.9 of 2006 IPCC Guidelines.
Moreover, Monte Carlo analysis has been carried out for the CO2 emissions from ferroalloys production in
2020 submission and it resulted with a range of -25.15% to +25.52% combined uncertainty with means
of recommended Approach 1 uncertainties. Further information about Monte Carlo analysis of other uses
of ferroalloys production can be seen in Uncertainty chapter (Annex 2).
Recalculation:
There is no recalculation in this sector in this submission.
Planned Improvements:
There are no planned improvements in this category.
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4.4.3. Aluminium production (Category 2.C.3)
Source Category Description:
Türkiye estimates CO2 and PFCs (CF4 and C2F6) emissions from primary aluminium production. Primary
aluminium is aluminium tapped from electrolytic cells or pots during the electrolytic reduction of
metallurgical alumina (aluminium oxide). It thus excludes alloying additives and recycled aluminium.
Primary aluminium is molten or liquid metal tapped from the pots and that is weighed before transfer to
a holding furnace or before further processing.
Eti Aluminium is Türkiye’s only producer of primary aluminium and it is the country’s only fully integrated
producer which takes in untreated ore downstream and then has the capacity to fulfill every process
requirement to the finished product. The company has its own bauxite ore mines located just 20
kilometers away from the factory and this is the starting point of its operations.
Eti Aluminium’s Seydişehir Aluminium Plant, located in the Central Anatolia region of Türkiye, is an
integrated primary aluminium production plant. From here the company is able to convert aluminium ore
into metallic aluminium by first processing the ore and then shaping it through the use of casting, rolling
and extrusion systems.
The integrated production process itself consists of five main production phases. These are bauxite
mining, alumina production, liquid aluminium production, the alloying and casting of the liquid aluminium,
and the last but by no means least, the production of semi and/or end products through the use of the
aforementioned casting, rolling and extrusion processes.
Most carbon dioxide emissions result from the electrolysis reaction of the carbon anode with alumina
(Al2O3). The consumption of prebaked carbon anodes and Søderberg paste is the principal source of
process related carbon dioxide emissions from primary aluminium production. PFCs are formed during a
phenomenon known as the ‘anode effect’ during liquid aluminium production via electrolysis. Eti
Aluminium used Søderberg cells till the modernization of the aluminium production plant in 2015. In 2015
all of the Søderberg cells were replaced with the prebaked cells.
The CO2 emissions from aluminium productions is shown in figure 4.21. Overall between 1990 (99.2 kt
CO2 eq) and 2021 (117.8 kt CO2 eq.) emissions have increased by 18.8% due to increasing aluminium
production of Türkiye. In 1993 aluminium production decreased remarkably because of the excessive
world aluminium stocks prior to the world economic recession of 1994. CO2 emissions remained generally
stable until a similar trend was seen in 2008 (111.8 kt), 2009 (51.2 kt) and 2010 (96.4 kt) similarly
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because of the world economic recession in 2008. In 2021, CO2 emissions remained stable with respect
to 2020.
Figure 4.21 CO2 emissions from aluminium production, 1990-2021
140
kt
120
100
80
60
40
20
0
CF4 and C2F6 emissions are reported in the Table 4.22, fluctuations in the trend are due to Anode Effect
parameter changes as well as primary aluminium production trend.
From the year 2006, PFCs emissions from the aluminium production plant are estimated using T3
methodology.
Eti Aluminium have communicated that after privatization in 2005, there has been great savings in energy
consumption in 2006, at the same time there has been a decreasing trend in the number of anode effects.
As it can be seen from the table below, reductions in PFCs emissions have occurred after 2006.
Methodological Issues:
CO2 emissions from primary aluminium production are calculated by the T3 method for the entire time
series. Eti Aluminium, the only primary aluminium producer in Türkiye, switched its production process in
the mid of 2015. The company is now using Prebaked smelters. Before that Søderberg process was used
to produce aluminium. For 1990-2014 CO2 emissions come from only Søderberg cells. However, in 2015
Søderberg cells were switched to Prebaked cells. In 2016 CO2 emissions come from only Prebaked cells.
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CO2 emissions from Søderberg cells
Where:
ECO2 = CO2 emissions from paste consumption, tonnes CO2
MP = total metal production, tonnes Al
PC = paste consumption, tonnes/tonne Al
CSM = emissions of cyclohexane soluble matter, kg/tonne Al
BC = binder content in paste, wt %
Sp = sulphur content in pitch, wt %
Ashp = ash content in pitch, wt %
Hp = hydrogen content in pitch, wt %
Sp = sulphur content in calcined coke, wt %
Ashc = ash content in calcined coke, wt %
CD = carbon in skimmed dust from Søderberg cells, tonnes C/tonne Al
44/12 = CO2 molecular mass: carbon atomic mass ratio, dimensionless
CO2 emissions from Prebaked cells
Where:
ECO2 = CO2 emissions from paste consumption, tonnes CO2
MP = total metal production, tonnes Al
NAC = net prebaked anode consumption per tonne of aluminium, tonnes C / tonne Al
Ca = carbon content in baked anodes, wt %
44/12 = CO2 molecular mass: carbon atomic mass ratio, dimensionless
PFC emissions
PFCs are formed during a phenomenon known as the ‘anode effect’. PFCs emissions have been estimated
from the primary aluminium production multiplied for the relative (CF4, C2F6), following a PFC emission
by slope method (Tier 2 and Tier 3) IPCC methodology.
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Due to the process change in Eti Aluminium, the company has switched to the Prebake cells just in 2015
after using Søderberg process for long years. This technology change has leaded to changing the
coefficient numbers and the difference between 2014-2015 has occurred because of this reason. Also
PFC, C2F6 and CF4 emission factors are recalculated in Eti Aluminium Facility in 2015-2016, calculation
made by using the current coefficients in the Greenhouse Gas Monitoring Reporting Communiqué of
MoEUCC and it can be seen from the table that there is a decrease trend between years 2016-2018. In
the same years, total production value has also decreased. In 2021 emission values have decreased for
both gasses, compared to the previous year.
In the following table PFCs, CF4 and C2F6 are reported.
Table 4.22 PFCs, CF4 and C2F6 emissions 1990-2021
(kt CO2 eq.)
Year
PFCs
CF4
C2F6
1990
1995
472.804
434.7635
38.040
409.326
376.3931
32.933
2000
409.246
376.3197
32.927
2005
399.265
367.1413
32.124
2010
387.558
356.3761
31.182
2011
362.642
333.4646
29.177
2012
271.325
249.4952
21.830
2013
199.968
183.8793
16.089
2014
186.639
171.6230
15.016
2015
91.359
84.0086
7.351
2016
37.363
31.1425
6.221
2017
25.164
20.9742
4.190
2018
10.084
8.4046
1.679
2019
17.095
14.2483
2.846
2020
10.371
8.6444
1.727
2021
6.779
5.6503
1.129
As shown in the table emission values of PFCs, CF4 and C2F6 decreased after 2015, compared to previous
years. Because Aluminium production system was changed from Søderberg to Prebaked smelted in 2015.
PFCs are formed during a phenomenon known as the ‘anode effect’ during liquid aluminium production
via electrolysis. There has been a decreasing trend in the number of anode effects after switching to
prebaked smelter system.
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Collection of activity data
To estimate CO2 emissions, the parameters below are obtained from the single producer. The data are
obtained from the producer company by an annual questionnaire. However, plant specific data can only
be obtained for the years 2005-2015, and for 1990-2004 the default parameters are used as the emission
factors and national statistics are used as the production data. The paste consumption data for 19902004 is assumed to be constant and same with the 2005 data. Total aluminium production is given in
table 4.23 below.
Table 4.23 Aluminium production emissions, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Aluminium
Production
(1990=100)
100
115
114
109
98
103
79
59
55
83
143
137
133
142
146
145
CO2
emissions
(kt)
99.2
114.4
112.7
102.2
96.4
100.3
76.4
55.3
54.9
74.7
117.3
108.4
107.3
112.1
117.7
117.8
Choice of emission factor
Some of the CO2 emission factors are provided by the facility while some are used as default values. In
the tables below the emission factors used in the formula for Søderberg cells and Prebaked cells can be
found.
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Table 4.24 Emission factors for aluminium production with Søderberg cells, 2005-2015
Emission factor
Type of data
Value
PC (Paste consumption)
Plant specific
Confidential
CSM (Emissions of cyclohexane soluble matter)
Default
4 kg/tonne Al
BC (Binder content in paste)
Plant specific
Confidential
Sp (Sulphur content in pitch)
Plant specific
Confidential
Ashp (Ash content in pitch)
Plant specific
Confidential
Hp (Hydrogen content in pitch)
Default
3.3 wt %
Cc (Carbon content in calcined coke)
Plant specific
Confidential
Ashc (Ash content is calcined coke)
Plant specific
Confidential
CD (Carbon in skimmed dust from Søderberg cells)
Plant specific
Confidential
Note: For 1990-2004 PC value assumed to be constant and same with the 2005 data. All other parameters are default for the years 1990-2004
Table 4.25 Emission factors for aluminium production with Prebaked cells, 2015-2021
Emission factor
Type of data
Value
NAC (Net Prebaked Anode Consumption)
Plant specific
Confidential
Ca (Carbon content in baked anodes)
Plant specific
Confidential
Note that the company, Eti Aluminium, switched to the Prebake cells just in 2015 after using Søderberg
process for long years. The system is not fully developed yet. NAC value is not measured but it is
estimated by the process engineers of the company.
For the calculation of PFCs emissions, the company yearly supply data for the following parameters, from
1990:
Primary aluminium production (tonnes);
Anode effect (minute/day);
CF4 Slope coefficient;
C2F6 Slope coefficient;
CF4EF (kg CF4/tonnes aluminium);
C2F6EF (kg C2F6/tonnes aluminium).
Uncertainties and Time-Series Consistency:
For CO2 emissions, the uncertainty values of the T2 method is considered ±5% for the EF and ±1% for
AD, as recommended in 2006 IPCC Guidelines Volume 3 (page 4.56). AD are relatively low as there is
very little uncertainty in the data on annual production of aluminium and information is provided directly
from the single producer. The CO2 emission factor is also low as the mechanisms leading to emissions
are well known. On the other hand, for F-gases, uncertainty values of T3 are considered 5% for EF and
2% for AD as recommended in 2006 IPCC Guidelines Volume 3 (page 4.56).
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Category 2.C.3 employed a Monte Carlo uncertainty analysis which causes a combined uncertainty range
(-5.15%,+5.16%) for CO2 emissions in 2020 submission. Detailed explanation of Approach 2 method is
in Uncertainty part of this inventory report (Annex 2).
Source-Specific QA/QC and Verification:
Within the scope of the Turkish National Greenhouse Gas Emission Inventory Improvement Project,
Türkiye's only primary aluminium producer, Eti Alüminyum A.Ş., was visited on July 2017 and detailed
information on production processes and data recording systems were obtained. The emission calculation
methodology, the parameters used in the formulation and the data gathered were discussed with sector
experts. The methodology, the parameters and the data were also approved by the sector experts.
The production data is gathered from the producer and aggregated national implied emission factors are
compared with IPCC default values. Due to the data confidentiality the IEFs cannot be tabulated in here.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
A QA work was conducted by an external reviewer from CITEPA (Technical Reference Center for Air
Pollution and Climate Change) for this category in January 2020.
Recalculation:
Emission calculations from PFC gases under the aluminium sector have been revised and recalculated
according to the 2006 IPCC guidelines instead of 1996 IPCC guidelines.
Planned Improvements:
No further improvements are planned.
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4.4.4. Magnesium production (Category 2.C.4)
Magnesium is mainly used in electronics, defense, automotive and aircraft industries for its lightness and
strength.
Türkiye estimates CO2 and SF6 emissions emissions from magnesium metal production for the first time
in this submission. While metallic magnesium derived from mineral source, CO2 released during calcination
of carbanate-based ores.
Kar Mineral Madencilik is Türkiye’s only producer of primary magnesium, launched its operation in 2016.
Kar Mineral Madencilik uses Pigdeon method from dolomite mine for primary producing of magnesium
metal.
The magnesium production consist of eight main production phases. These are dolomite mining, crushing,
calcination, grinding, pelleting, reduction, rafination and casting.
Since all molten magnesium spontaneously burns in the presence of atmospheric oxygen, production and
casting of all magnesium metal requires a protection system to prevent burning. The Magnesium
production industry uses SF6 as a cover gas to prevent the oxidation of molten magnesium.
Methodological Issues:
Türkiye implements Tier 1 method for calculation of CO2 emissions from magnesium production. Primary
production data collected from the plant as activity data and multiplied by the default IPCC EF.
Where:
𝑬𝑬𝑪𝑪𝑪𝑪𝑪𝑪 = ( 𝑷𝑷𝒅𝒅 ∙ 𝑬𝑬𝑬𝑬𝒅𝒅 ). 𝟏𝟏𝟏𝟏�𝟑𝟑
ECO2 = CO2 emissions from primary magnesium production, Gg
Pd = national primary magnesium production from dolomite, tonnes
EFd =Default emission factor for CO2 emissions from primary magnesium production from
dolomite, tonne CO2 /tonne primary Mg produced
Tier 2 method for calculation of SF6 is implemented which assumes that all SF6 is consumed is
subsequentlyemitted. Consuption of SF6 data is gathered directly from the plant.
𝑬𝑬𝑺𝑺𝑺𝑺𝑺𝑺 = 𝑪𝑪𝑺𝑺𝑺𝑺𝑺𝑺
ESF6 = SF6 emissions from magnesium casting, tonnes
CSF6 = consumption of SF6 in magnesium smelters and foundries, tonnes
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Industrial Processes and Product Use
Consumed SF6 which is also assumed to be equal to emissions reported by the plant. There was no use
of other cover gases (HFC-134a or FK 5-1-12) hence emissions were not reported for these alternatives.
Collection of activity data
Primary magnesium production data is directly reported by the plant annually. Dolomite used as raw
material for production of magnesium. The production trend and emissions can be seen from the table
below.
Table 4.26 CO2 emissions from magnesium production, 2016-2021
Year
Magnesium Production
(2016=100)
CO2
NO
100.0
720.2
370.7
779.8
1153.4
1099.4
NO
3.5
25.2
13.0
27.3
40.4
38.5
1990-2015
2016
2017
2018
2019
2020
2021
SF6 data is reported by the plant annually. Other cover gases (HFC-134a or FK 5-1-12) do not used by
the plant. SF6 emissions from magnesium casting processes and CO2 eq. values can be seen from the
table below.
Table 4.27 SF6 emissions from magnesium casting, 2016-2021
Year
ESF6
SF6 Emissions (kt-CO2 eq)
2016
0.040
0.912
2017
0.196
4.469
2018
0.260
5.928
2019
1.768
40.310
2020
2.444
55.723
2021
2.184
49.795
Choice of emission factor
Türkiye applies default IPCC EF for primary magnesium producing which takes into account the type of
raw material used. According to IPPC guideline Table 4.19 EF for dolomite is 5.13 tonnes CO2
emission/tonne primary magnesium produced.
For magnesium casting processes Türkiye implement Tier 2 method that assumes all SF6 consumed is
emitted. Annual consumed SF6 data gathered directly from the plant.
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Uncertainties and Time-Series Consistency:
The 2006 IPCC Guidelines recommended uncertainty value of 5% is used for the AD since the magnesium
production data are gathered directly from the single production plant. Uncertainty value of default EF is
estimated 10% based on the expert judgement.
The uncertainty estimate is 5% according to IPCC guideline for the SF6 consumption for magnesium
casting data which gathered from purchase registers is reported directly by the plant.
Source-Specific QA/QC and Verification:
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
Recalculation:
There is no recalculation for this year's inventory.
Planned Improvements:
No further improvements are planned.
4.4.5. Lead production (Category 2.C.5)
Source Category Description
There are two primary processes for the production of rough lead bullion from lead concentrates. The
first type is sintering/smelting, which consists of sequential sintering and smelting steps and constitutes
roughly 78% of world-wide primary lead production. The second type is direct smelting, which eliminates
the sintering step and constitutes the remaining 22% of primary lead production in the developed world.
However, in Türkiye there is no primary lead production. Türkiye is producing lead by only smelting the
recycled lead from vehicles' old batteries. There are over 25 million registered road motor vehicles and
there is huge amount of vehicle batteries to be recycled every year in Türkiye. Therefore, there are many
lead batteries recycling companies in Türkiye.
In lead recycling the batteries are crushed and then the scrap lead and plastic contents are separated by
floating. Then the lead is put into a smelting furnace with some reductant agent (natural gas, fuel oil or
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metallurgical coke), silica, and iron. The furnace is heated up and the lead is melted in the furnace. During
this process oxides are carbonated and leave the furnace as CO2.
Methodological Issues:
Lead production is not a key category in Türkiye, and due to lack of data, the Tier 1 is applied to calculate
CO2 emissions by multiplying process specified to lead production data, as shown in equation below.
Where:
ECO2 = S ∙ EF s
ECO2 = CO2 emissions from lead production, tonnes
S= quantity of lead produced from secondary materials, tonnes
EFS = emission factor for secondary materials, tonne CO2 / tonne lead produced
The lead production data is known for only 1990-1996. Besides that, the amount of vehicle batteries
recycled is known for the years 2007 and 2021. There is no data between 1997 and 2006. The specialists
from the production field indicated that lead production amount is 60% of the vehicle batteries recycled
by weight and this assumption is used for the estimation of secondary lead production. The amount of
lead produced between 1997 and 2006 is estimated by interpolation.
Collection of activity data
There are many companies in Türkiye recycling vehicle batteries for lead recovery. Since old batteries are
classified as dangerous waste, it is statistically overseen. The amount of vehicle batteries recycled is
known for the years 2007-2021. The data is gathered from TurkStat data bases and Ministry of
Environment, Urbanization and Climate Change. It is assumed that 60% of the waste battery weight is
recycled as lead. This assumption is based on the experts who work in the lead smelting industry. 19901996 lead production data is found in the 8th five years development plan of Türkiye. The data for the
years 1997-2006 are estimated by interpolation. In the table below the amount of vehicle batteries
recycled and consequently the amount of lead produced in the smelting process is shown. The emissions
from lead production is also shown in the same table.
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Table 4.28 Lead production and CO2 emissions from lead production, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Recycled waste
batteries
(kt)
No Data
No Data
No Data
No Data
55.0
59.4
59.5
69.0
61.3
71.4
66.4
73.9
72.6
73.5
78.5
83.6
Lead production
from waste
batteries
(kt)
11.0
11.1
18.5
24.8
33.0
35.6
35.7
41.4
36.8
42.9
39.8
44.3
43.5
44.1
47.1
50.1
CO2
emissions
(kt)
2.2
2.2
3.7
5.0
6.6
7.1
7.1
8.3
7.4
8.6
8.0
8.9
8.7
8.8
9.4
10.0
Choice of emission factor
Emission factor of 0.20 tonne of CO2 / tonne of lead produced is used in the calculations. This is the
process type specific emission factor for the treatment of secondary raw materials in the 2006 IPCC
Guidelines, Table 4.21.
Uncertainties and Time-Series Consistency:
National production data for the amount of vehicle batteries are used as the activity data and it is
estimated that 60% by weight of the amount of batteries recycled is recovered as lead. Due to this
assumption the activity data has an uncertainty of 25% relying on the expert judgement. The process
type emission factor has an uncertainty of 20% by default.
In 2020 submission, uncertainty in CO2 emissions from category 2.C.5 was quantified using the Monte
Carlo simulation for other IPPU sub-categories. Combined uncertainty in CO2 emissions from lead
production in 2018 is estimated at -22.87% to +24.60%. Further information about Monte Carlo analysis
of lead production can be seen in Uncertainty chapter (Annex 2).
Source-Specific QA/QC and Verification:
The weight data of recycled batteries is gathered from Ministry of Environment, Urbanization and Climate
Change (MoEUCC). The same data is also produced by TurkStat. When this two data sets from different
sources are compared they are found consistent.
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Industrial Processes and Product Use
In order to estimate the amount of lead produced using the amount of batteries recycled data, the biggest
two lead smelter company were asked and the production engineers and environmental responsibles
gave necessary information. One company responsible declared 55-60% of lead recovery, the other
company declared 65% of lead recovery from the old vehicle batteries by weight. Therefore, these
information is consistent with the assumption that 60% of lead is recovered by weight.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
A QA work was conducted by an external reviewer from CITEPA (Technical Reference Center for Air
Pollution and Climate Change) for this category in January 2020.
Recalculation:
There is no recalculation for this year's inventory.
Planned Improvements:
No further improvements are planned at this time.
4.4.6. Zinc production (Category 2.C.6)
Source Category Description:
Zinc production in Türkiye consist of secondary processes, currently there is no primary zinc production.
There was a single primary production plant (CINKUR), located in Kayseri, produced primary zinc between
the years 1968 and 1999. The plant was producing zinc by utilizing zincoxide ore by pyrometallurgical
(Imperial Smelting Furnace) process until it closed in 1999.
Zinc consumed in variety of areas including galvanizing where zinc coating is applied to steel in order to
prevent corrosion, zinc alloys production, agricultural fertilizers, chemicals and paint industries.
Türkiye estimates CO2 emissions from secondary zinc production first time in this submission. Secondary
zinc production began in 1999 with single plant which stopped its operations for the years 2003, 2004
and 2009. Second plant launced operation in 2010 and three of them started their operations in 2015.
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For secondary zinc production, electric arc furnace (EAF) dust, which captured during the recycling of
galvanized steel, is main raw material. Flotation residuals from zinc mines are also used in production of
secondary zinc.
In the Waelz kiln process, EAF dust and mine residuals enters a kiln along with a reducing agent
(metallurgical coke or anthracite) and limestone at a temperature of 1200-1300 C. As the feed material
moves down the kiln, zinc transformed to gas and turned to Waelz oxide which is captured, cooled and
leached in order to produce zinc concentrate. The use of carbon-containing reducing agent in hightemperature fuming process results in non-energy CO2 emissions. Emissions from fuels consumed for
energy purposes during the production of zinc are accounted for in the Energy chapter.
Methodological Issues:
Estimations are based on the Tier 1 method described in the 2006 IPCC Guidelines. In order to calculate
CO2 emissions from primary zinc production, the default EF is multiplied with zinc production data as
shown in the equation below.
ECO2 = Zn ∙ EFdefault
Where:
ECO2 = CO2 emissions from primary zinc production, tonnes
Zn = quantity of zinc produced, tonnes
EF default = Default emission factor, tonnes CO2/ tonne zinc produced
CO2 emissions from secondary zinc production calculated as shown in the equation below.
ECO2 = WK ∙ EFWK
ECO2 = CO2 emissions from secondary zinc production, tonnes
WK = quantity of zinc produced by Waelz kiln process, tonnes
EF default = emission factor for Waelz kiln process, tonnes CO2/ tonne zinc produced
Collection of activity data
To estimate CO2 emissions from secondary zinc production, production data obtained from the plants by
a questionnaire in which retrospective data also demanded.
For primary zinc production the plant stopped its activities in 1999. And it changed its owners many times
from then. The newest owners of the plant have no information dating back to those years. Fortunately,
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Industrial Processes and Product Use
the capacity utilization rate and the total zinc production capacity of the plant is found in the records of
the ministry of state responsible for privatization (2001). By multiplying the production capacity of the
plant with the capacity utilization rate, the production data of the plant are estimated for 1990-1999.
The table below shows the amount of primary and secondary zinc production and CO2 emissions.
Table 4.29 Zinc productions and CO2 emission (kt), 1990-2021
Years
Primary Zinc
Production
Emissions from
Primary Zinc
Production CO2
Secondary
Zinc
Production
Emissions from
Secondary Zinc
Production CO2
Total Emissions
from Zinc
Production CO2
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
22.0
20.4
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
37.8
35.1
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
3.7
1.3
17.0
26.2
28.9
30.3
33.7
113.9
113.7
133.7
147.6
110.9
141.2
158.2
NO
NO
13.7
4.6
62.2
95.8
105.6
110.7
123.2
417.0
416.2
489.3
540.3
406.0
516.9
578.9
37.8
35.1
13.7
4.6
62.2
95.8
105.6
110.7
123.2
417.0
416.2
489.3
540.3
406.0
516.9
578.9
NO = Not Occurred
Figure 4.22 CO2 emissions from primary and secondary zinc production, 1990-2021
600
kt
500
400
300
200
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
100
Primary Zinc Production
222
Secondary Zinc Production
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Choice of emission factor
Default emission factor of 1.72 tonne of CO2/tonne of zinc produced is used in the primary zinc production
calculations. This is the default emission factor in the 2006 IPCC Guidelines, Table 4.24 based on
weighting of 60% Imperial Smelting and 40% Waelz Kiln. For the calculation of emissions from secondary
zinc production, Waelz kiln process emission factor of 3.66 tonne of CO2/tonne of zinc produced is used.
Uncertainties and Time-Series Consistency:
Uncertainty value for EF is considered 50% as recommended in the 2006 IPCC Guidelines Volume 3 Table
4.25 due to the use of default EF. Since production data gathered directly from the plants, the uncertainty
value for AD is considered 5%.
Source-Specific QA/QC and Verification:
Experts from zinc trader and waelz oxide producer companies in Türkiye are personally communicated
and by this way it is verified that Türkiye's only primary zinc producer was CINKUR and it was closed in
1999. CINKUR's zinc production data is also found in the 8th five years development plan of Türkiye
(2001) and it is stated that CINKUR is roughly producing 20.000 tons zinc/year which is in line with our
calculated production data for the years between 1990 and 1996.
CO2 emissions from secondary zinc production is estimated first time in this submission. Secondary zinc
production data which are collected from the plants via questionnaire for this inventory calculations, are
compared with PRODCOM and found consistent.
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
A QA work was conducted by an external reviewer from CITEPA (Technical Reference Center for Air
Pollution and Climate Change) for this category in January 2020.
Recalculation:
Türkiye estimates CO2 emissions from secondary zinc production first time in this submission. In 1999
both primary and secondary zinc is produced and CO2 emissions from zinc production increased by 3.7
kt. For the years between 2000-2002, 2005-2008 and 2010-2021 emission values are added from
secondary zinc production for the first time.
Planned Improvements:
The activities of secondary zinc producers will continue to be examined in next submissions.
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4.5. Non-Energy Products from Fuels and Solvent Use (Category 2.D)
4.5.1. Lubricant use (Category 2.D.1)
Source Category Description:
Lubricants are mostly used in industrial and transportation applications. Lubricants are produced either
at refineries through separation from crude oil or at petrochemical facilities. They can be subdivided into
(a) motor oils and industrial oils, and (b) greases, which differ in terms of physical characteristics (e.g.,
viscosity), commercial applications, and environmental fate.
The use of lubricants in engines is primarily for their lubricating properties and associated emissions are
therefore considered as non-combustion emissions and reported in the IPPU Sector.
Methodological Issues:
Detailed activity data on lubricants are not available in Türkiye and CO2 emissions calculation is based on
the amount of lubricant consumption is obtained from IEA - Eurostat - UNECE Energy Questionnaire - Oil
table of Türkiye. Total consumption data for all lubricants (i.e. no separate data for oil and grease) is
calculated by subtracting exports-imports and stock changes from production data. T1 method which is
formulated by Equation 5.2 in 2006 IPCC Guidelines is used to calculate CO2 emission. Lubricant
consumption data and the weighted average oxidation during use (ODU) factor and default carbon
content factor for lubricants as a whole is used as default value for the calculation. The amount of lubricant
consumed in terms of kt converted to in terms of TJ by multiplying it with a factor (40.2). The following
table shows the amount of lubricant used and the CO2 emissions, from 1990 to 2021.
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Table 4.30 The Amount of lubricant used and CO2 emissions, 1990-2021
(kt)
Year
Lubricant use
CO2
1990
297
175.1
1995
339
199.9
2000
460
271.2
2005
667
393.3
2010
713
420.4
2011
1 416
834.9
2012
998
588.4
2013
894
527.1
2014
654
385.6
2015
432
254.7
2016
229
135.0
2017
243
143.3
2018
328
193.4
2019
211
124.4
2020
203
119.5
2021
277
163.1
As activity data is calculated by subtracting exports-imports and stock changes from production data,
fluctuations between some of the years are through the changes of these indicators. Due to decreasing
import of lubricant in 2015 from 421 ktons to 199 ktons in 2016, resulted 47% decrease in activity data.
Uncertainties and Time-Series Consistency:
Because the default ODU factors developed are very uncertain, as they are based on limited knowledge
of typical lubricant oxidation rates, the default uncertainty for EF is 50%. For AD uncertainty value is
considered to be 25%.
An uncertainty analysis using the Monte Carlo technique was carried out to estimate emissions of CO2
for 2.D.1 category and also to other IPPU categories in 2020 inventory year. Combined uncertainty of
CO2 emissions in 2018 is estimated at the range of -51.96% to +59.43%. Please refer to Annex 2 for
more detailed information.
Source-Specific QA/QC and Verification:
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
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Industrial Processes and Product Use
A QA work was conducted by an external reviewer from CITEPA (Technical Reference Center for Air
Pollution and Climate Change) for this category in January 2020.
Recalculation:
There is no recalculation for this submission
Planned Improvements:
No further improvements are planned at this time.
4.5.2. Paraffin wax use (Category 2.D.2)
Source Category Description:
The category, as defined here, includes such products as petroleum jelly, paraffin waxes and other waxes,
including ozokerite (mixtures of saturated hydrocarbons, solid at ambient temperature). Paraffin waxes
are separated from crude oil during the production of light (distillate) lubricating oils. Paraffin waxes are
categorized by oil content and the amount of refinement.
Waxes are used in a number of different applications. Paraffin waxes are used in applications such as:
candles, corrugated boxes, paper coating, board sizing, food production, wax polishes, surfactants (as
used in detergents) and many others. Emissions from the use of waxes derive primarily when the waxes
or derivatives of paraffin are combusted during use (e.g., candles), and when they are incinerated with
or without heat recovery or in wastewater treatment (for surfactants).
Methodological Issues:
Detailed activity data on paraffin wax use are not available in Türkiye and CO2 emissions calculation is
based on the amount of paraffin waxes consumed in a country which is obtained from IEA - Eurostat UNECE Energy Questionnaire - Oil table of Türkiye. Total consumption data for paraffin waxes is calculated
by subtracting exports-imports and stock changes from production data. Tier 1 method formulated as
Equation 5.4 in 2006 IPCC Guidelines is used with default carbon content and ODU factor. The following
table shows the amount of paraffin wax used and resulting CO2 emissions, 1990 to 2021.
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Industrial Processes and Product Use
Table 4.31 The Amount of paraffin wax used and CO2 emissions, 1990-2021
(kt)
Year
Paraffin wax use
CO2
1990
14
8.3
1995
5
2.9
2000
10
5.9
2005
89
52.5
2010
19
11.2
2011
32
18.9
2012
29
17.1
2013
11
6.5
2014
23
13.6
2015
20
11.8
2016
19
11.2
2017
14
8.3
2018
22
13.0
2019
23
13.6
2020
25
14.6
2021
11
6.7
As activity data is calculated by subtracting exports-imports and stock changes from production data,
fluctuations between some of the years are through the changes of these indicators. Due to increasing
import of lubricant in 2014 resulted 109% increase in activity data.
Uncertainties and Time-Series Consistency:
Uncertainty values of AD is considered to be 25%, on the other hand since the ODU factor is highly
dependent on specific country conditions and policies, the default EF exhibits an uncertainty of 100%
according to the 2006 IPCC Guidelines.
Additionally, an uncertainty analysis using the Monte Carlo technique was carried out to estimate
emissions of CO2 for 2.D.2 category (Paraffin wax use) in 2020 inventory year. Combined uncertainty in
CO2 emissions in 2018 is estimated at the range of (-98.46%,+107.31%). For more detailed information
please refer to Annex 2.
Source-Specific QA/QC and Verification:
In this submission for minimizing calculation errors, emission calculation was done by using two different
software and results were compared.
QA/QC procedures are implemented for each category in order to verify and improve the inventory under
the QA/QC plan of Türkiye.
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Industrial Processes and Product Use
Moreover, a QA work was conducted by an external reviewer from CITEPA (Technical Reference Center
for Air Pollution and Climate Change) for this category in January 2020.
Recalculation:
There is no recalculation for this submission
Planned Improvements:
No further improvements are planned.
4.6. Electronics Industry (Category 2.E)
A research for this category, has been done by taking into consideration of relevant sectors and gases.
According to the results, it has been appeared that F-gases have not been used in the manufacturing
processes of these sectors. However, it is founded that some gases have been used with the aim of
research and development.
Source category description
The sub-sector only consists of the following sub-application: 2.E.5- Other, other electronic uses.
Methodological issues
This section is composed of results of the research which has been conducted by the Ministry of
Environment, Urbanization and Climate Change. As it is stated above, results show that F-gases are not
used in the manufacturing of flat panel display, photovoltaic products and semiconductors. This
information has been gathered by contacting with largest companies within the relevant sectors.
However, it is observed that CF4, CHF3 and SF6 are used for the research and development in the area of
semiconductor products. Therefore, these gases are reported under the category of 2.E.5 “other
electronic uses”.
According to the research, these gases were started to be used in 2010. For reporting of emission, it is
assumed that same amount of gas was used for each year. This assumption is made by considering the
expert judgement. MoEUCC has made survey with the leading company of Türkiye, which has R&D
department in electronic industry and the numbers assessed due to the results of survey.
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Industrial Processes and Product Use
Table 4.32 shows the consumption amount of each gases which are consumed for the research and
development purpose.
Table 4.32 Consumption of each gases, 2010-2021
(kg)
Years
CF4
HFC-23
SF6
2010
1.2
6
1 848
2011
1.2
6
1 848
2012
1.2
6
1 848
2013
1.2
6
1 848
2014
1.2
6
1 848
2015
1.2
6
1 848
2016
1.2
6
1 848
2017
1.28
6.4
1 984.7
2018
1.31
6.56
2 501.7
2019
1.32
6.61
2 524.2
2020
1.34
6.72
2 569.6
2021
1.49
7.46
2 852.3
Türkiye's economy grew 11 percent in 2021 and the value of consumption of each gas has determined
for 2021 by using the value of economic grew.
Recalculation:
There is no recalculation for this submission.
Planned Improvements:
No further improvements are planned.
4.7. Product Use as Substitutes for ODS (Category 2.F)
Source Category Description:
Production of fluorochemicals does not exist in Türkiye. Therefore, all demand for these gases is met by
imports.
The sub sector emissions of fluorinated substitutes for ODS consist of the following sub application;
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Industrial Processes and Product Use
2F3 emissions from fire protection
2F6 emissions from other applications
Methodological Issues:
The methodology used to estimate HFCs emissions from the sub-sector has been based on the 2006 IPCC
Guidelines, using the model provided by the IPCC, which calculate emissions following T1 method.
Inventory calculations have been based on the raw trade data (import and export) provided for each gas
by Ministry of Trade.
It should be noted that HFCs are being used as alternatives to CFCs since 1999. Since then it is thought
that HFCs are used in different industrial sectors. However due to lack of information, it is assumed that
most of HFCs gases, excluding HFC-227ea that is used only in fire extinguishers, are used in refrigeration
and air conditioning sector. Due to this reason, these gases are calculated according to the calculation
assumptions for refrigeration and air conditioning but calculation results are reported under “Other
Applications” title in 2F category.
As it is written in 2006 IPCC Guidelines, following assumptions are used in a hybrid Tier 1a/b approach
for calculations;
Servicing of equipment containing the refrigerant does not commence until 3 years after the
equipment is installed.
Emissions from banked refrigerants average 3% annually across the whole refrigeration and air
conditioning application area.
In a market, two thirds of the sales of a refrigerant are used for servicing and one third is used
to charge new equipment.
The average equipment lifetime is 15 years.
The complete transition to a new refrigerant technology will take place over a 10 years period.
For calculation of HFC-227ea, expert judgements are considered. According to the information which is
obtained from discussion with experts who are working under the Protection of Ozon Layer Division of
MoEUCC and Turkish Fire Protection and Training Foundation (TUYAK) which is representative of fire
sector, HFC-227ea is mostly consumed in fire protection application in Türkiye. Regarding to this
information, this gas is reported under “2F3 Fire Protection” category. As it is stated in the 2006 IPCC
Guideline, HFCs in this application area, are emitted over a period longer than one year. To consider this,
spreadsheet which is proposed by guideline is used for calculation.
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Industrial Processes and Product Use
Uncertainties and Time-Series Consistency:
Table 4.33 and Figure 4.23 present total HFCs emissions from 1999 to 2021. Increasing trend in emissions
is clearly observed from these presentations. The reason behind this can be explained by the prohibition
of CFCs in the country. Since 1999, HFCs have been used as substitution of CFCs (Values of 1999 has
been calculated due to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories).
Table 4.33 Total HFCs emissions, 1999-2021
Year
HFCs Emissions
(kt CO2 eq.)
HFCs Emissions (tonnes)
2000
81.3
115.7
2005
808.6
1 146.9
2010
2 412.4
3 054.3
2011
2 949.9
3 432.7
2012
3 654.4
4 256.9
2013
4 030.0
4 471.1
2014
4 490.6
4 929.6
2015
4 522.5
4 817.5
2016
4 806.7
5 110.9
2017
4 955.5
5 256.3
2018
4 929.9
5 040.2
2019
5 857.9
5 676.5
2020
6 508.4
6 497.6
2021
7 635.8
7 209.7
Figure 4.23 Total HFCs emissions, 1999-2021
9000
(tonnes)
8000
7000
6000
5000
4000
3000
2000
1000
0
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
Above presentation shows aggregated emissions caused by HFCs including HFC-23, HFC-32, HFC-41,
HFC-43-10mee, HFC-125, HFC-134, HFC-134a, HFC-143, HFC-143a, HFC-152a, HFC-227ea, HFC-236fa,
Turkish GHG Inventory Report 1990-2021
231231
Industrial Processes and Product Use
HFC-245ca, and HFC-365 mfc. Moreover, table below separately indicates emissions from these gases for
specific years. All emission values are presented in tonnes and for each gas emissions are calculated
related to Tier 1a/1b method of IPCC. Inventory calculations have been based on the raw trade data
(import and export) provided for each gas by Ministry of Trade and the change in graph is consistent with
number of import and export.
Table 4.34 HFCs Emissions
(tonnes)
Substance
2000 2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
HFC-23
0.02
0.29
0.57
0.63
5.40
4.70
4.10
3.66
5.33
4.70
3.58
3.18
2.97
2.52
HFC-32
NO
NO
NO
NO
0.01
0.01
0.5
0.6
0.7
3.5
86.9
179.3
323.7
600.1
HFC-41
NO
NO
0.03
0.02
0.03
0.03
0.02
0.02
0.02
0.01
0.08
NO
NO
NO
HFC-4310mee
NO
NO
NO
0.04
0.08
0.07
0.15
0.12
0.51
0.88
1.65
3.20
2.97
2.84
HFC-125
NO
NO
0.7
1.2
3.6
6.7
15.3
25.5
21.7
27
30.5
35.7
27.9
102.2
HFC-134
NO
NO
NO
0.00
0.01
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
HFC-134a
80.4
791.4
2,066.3
HFC-143
NO
NO
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
NO
NO
HFC-143a
NO
NO
NO
NO
0.00
0.00
0.00
2.83
2.41
2.05
1.74
1.48
1.26
30.57
HFC-152a
0.78
14
331.4
642.2
HFC-236fa
NO
NO
0.68
1.66
3.07
4.12
4.11
4.09
6.03
6.77
9.45
9.58
11.80
13.83
HFC-245ca
NO
NO
0.02
1.14
0.97
0.82
2.65
2.26
1.92
1.63
1.42
1.24
0.99
5.58
HFC-245fa
NO
NO
NO
NO
NO
NO
12
25.20
29.05
30.51
28.16
23.93
32.85
29.79
HFC-365mfc
NO
NO
0.12
1.10
1.08
0.92
0.78
0.66
0.56
0.48
0.41
1.04
0.19
1.08
HFC-227ea
0.13
2.87
12.67
16.55
20.45
26.06
33.23
39.33
47.58
56.61
67.10
78.33
92.14
102.31
2,285.4 2,770.4 2,877.5 3,143.3 3,000.0 3,153.4 3,215.9 2,978.3 3,303.5 3,778.3
849.4 1,109.1 1,274.5 1,418.2 1,537.6 1,605.6 1,720.6 2,217.5 2,233.4
3,775.9
2,969.1
The calculation method is IPCC T1 for all substances given above.
Inventory calculations have been based on the raw trade data (import and export) provided for each gas
by Ministry of Trade and the change in emission values are consistent with number of import and export.
232
232
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Figure 4.24 HFC-227ea Emissions (tonnes), 2000-2021
120
100
80
60
40
20
0
2000
2005
2010
2013
2014
2015
2016
2017
2018
2019
2020
2021
Recalculation:
Recalculations have been carried out for the years 2014-2021, to take account of calculation error of
data, because of the calculation worksheet updated problem.
Planned Improvement:
No further improvements are planned.
4.8. Other Product Manufacture and Use (Category 2.G)
Source Category Description:
The sub-sector other product manufacture and use consists of the following sub- applications:
2.G.1- SF6 Emissions from electrical equipment
Methodological Issues:
It is assumed that SF6 is used only in electrical instruments, mainly in circuit breakers. Emission results
are reported based on the import and export data of SF6. However, custom code for this gas was
established in 2013 and trade data is available only for 2013-2021. Therefore, trend of electricity
consumption is used for the prediction of imported gas for previous years.
Turkish GHG Inventory Report 1990-2021
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Industrial Processes and Product Use
Data for electricity consumption is obtained from the Turkish Electricity Transmission Corporation and the
trade data for SF6 is provided by Ministry of Trade. Table 4.35 shows the distribution of electricity
consumption, SF6 consumption (import and export values) and emissions of SF6 which is emitted from
the circuit breakers used in Electricity industry. The IPCC default values of emission factors (including
natural leakage and emissions of operation, maintenance, and disposal) are 2.6% for the EU, 0.7% for
Japan, and 2.0% as a global average and calculation made by using the global average value.
Table 4.35 SF6 Consumption and Electricity Consumption
Years
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Electricity
consumption
(GWh)
98
130
172
186
194
198
207
216
225
249
254
257
261
286
296
263
051
100
923
045
375
233
495
020
863
273
193
692
SF6 net consumption
(tonnes)
29.260
38.776
51.215
55.397
58.024
58.953
71.826
87.055
80.002
160.277
156.591
127.774
125.464
64.130
SF6 Emissions
(tonnes)
0.585
0.775
1.024
1.107
1.160
1.179
1.436
1.741
1.600
3.205
3.131
2.555
2.509
1.282
There is no information about the number and the capacity of the used, imported or exported equipment
and the number of destroyed equipment. The imported gas amount has been assumed as 2% emitted in
related year. Import and export data is provided by Ministry of Trade. In 2021, SF6 net consumption
decreased dramatically, continuing the downward trend which began in 2017. In addition, a decrease in
SF6 emissions was also observed compared with the previous years. This may be in part due to a
preference for the 36 kV vacuum breaker over the 36 kV SF6 gas breaker in the procurement tenders held
in recent years.
234
Turkish GHG Inventory Report 1990-2021
234
Industrial Processes and Product Use
Figure 4.25 SF6 emissions, 1996-2021
3.5
3
2.5
2
1.5
1
0.5
0
1996
1999
2002
2005
2008
2011
2014
2017
2020
Uncertainties and Time-Series Consistency:
Uncertainties of SF6 was estimated using expert judgement as described in IPCC Good Practice Guidance
and Uncertainty Management (2000) Reference.
Source-Specific QA/QC and Verification:
During the preparation of the inventory submission activities related to source specific quality control
were mainly focused on completeness and consistency of emission estimates and on proper use of
notation keys in the CRF tables according to QA/QC plan. Aggregated national EFs are compared with
IPCC default values.
Recalculation:
The consumption of SF6 in Mg production between the years 2016-2021 is accounted in the magnesium
production sector.
Planned Improvement:
No further improvements are planned.
Turkish GHG Inventory Report 1990-2021
235235
Agriculture
5. AGRICULTURE (CRF Sector 3)
5.1. Sector Overview
Agricultural activities will most likely coexist with the existence of human beings on this planet, and
agricultural production is indispensable to the continuance of life. Effects of climate change are observed
by concentration of GHGs for many sectors including agriculture which generally comes second in size
after the energy sector. The total emission value calculated for the agriculture sector is 72 Mt CO2 eq. for
the year 2021 which is 13.9% of the total emission value including the LULUCF sector and 12.8% of all
emissions excluding the LULUCF sector for Türkiye. The agricultural sector is divided into ten categories
from 3.A to 3.J in the CRF tables. These categories are listed in Table 5.1 briefly for gases emitted from
each of these sources.
Table 5.1 Categories of the agriculture sector and emitted gases
CRF Categories
CO2
CH4
N 2O
NOx
CO
NMVOC
x
xb
xb
x
xb
xb
SO2
3.A
Enteric fermentation
x
3.B
Manure management
x
3.C
Rice cultivation
x
3.D
Agricultural soils
3.E
Prescribed burning of
savannas
x
x
xc
xc
xc
xc
3.F
Field burning of
agricultural residues
x
x
xb
xb
xb
xb
3.G
Liming
x
3.H
Urea application
x
3.I
Other carbon-containing
fertilizers
x
3.J
Other
a
xa
to be reported under LULUCF Sector.
b
Emissions of this gas from this category are likely to be emitted and a methodology is provided in the EMEP/EEA Guidebook.
Emissions of this air pollutant from this category are likely to be emitted and the methodology may be included in the EMEP/EEA Guidebook in
the future.
C
236
Turkish GHG Inventory Report 1990-2021
236
Agriculture
The percentage of emissions from this sector as percentage of total national GHG emissions (excluding
LULUCF) gradually declined from around 21% to 10.6% in most of the years between 1990 and 2009
before levelling off and thereafter gaining momentum. With the aim to give a clear view on the weights
of the categories within the sector, the following Table 5.2 presents emission and percentage values for
the year 2021.
Table 5.2 Agriculture sector emissions and overall percentages by categories, 2021
3 Agriculture
CH4
N2O
CO2
Total
(kt CO2 eq.)
(kt CO2 eq.)
(kt)
(kt CO2 eq.)
(%)
39 332
31 442
1 302
72 075
100.0
34 953
48.5
9 144
12.7
269
0.4
26 249
36.4
A. Enteric fermentation
34 953
B. Manure management
3 988
C. Rice cultivation
5 155
269
D. Agricultural soils
26 249
E. Prescribed burning of savannas
F. Field burning of agricultural residues
NO
121
37
159
G. Liming
NE*
H. Urea application
1 302
1 302
I. Other carbon-containing fertilizers
NO
J. Other
NO
GHG Percentage Shares
0.2
54.6
43.6
1.8
1.8
100.0
*The emission level from source category 3.G Liming is considered to be insignificant according to Paragraph 37(b) of 24/CP.19.
Figures in the table may not add up to the totals due to rounding.
Table 5.3 clearly presents the developments of the emissions for the agriculture sector. The overall
emission value for the sector increased from approximately 46.1 Mt CO2 eq. to around 72 Mt CO2 eq. (an
increase of 56.5%) during the 32 years period after 1990. The biggest increase among the categories in
absolute terms for the emissions is observed in the enteric fermentation category where the emissions
increased by around 12.6 Mt CO2 eq. (56.1%) from 22.4 Mt CO2 eq. to 35 Mt CO2 eq. for the same period.
The primary reason for this increase is the change in activity data (AD). Other significant increases in this
thirty-two years period are seen in agricultural soils, manure management, and urea application where
the figures are 8.9 Mt CO2 eq. (51.6%), 3.7 Mt CO2 eq. (68.2%), and 0.8 Mt CO2 eq. (183%), respectively.
Increases in emissions from enteric fermentation and manure management are largely a result of changes
in activity data. Emissions for rice cultivation increased by around 0.2 Mt CO2 eq. (169.1%) whereas the
emissions for field burning of agricultural residues between 1990 and 2021 resulted in a decrease of
54.3%.
Turkish GHG Inventory Report 1990-2021
237237
Agriculture
Table 5.3 Overview of the agriculture sector emissions, 1990‒2021
A. Enteric
fermentation
B. Manure
management
C. Rice
cultivation
Agriculture
total
Year
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
(%)
(kt CO2 eq.)
(%)
1990
22 397
48.6
5 436
11.8
100
0.2
46 054
100
1995
21 815
49.5
5 523
12.5
113
0.3
44 080
100
2000
19 234
45.4
5 142
12.1
128
0.3
42 332
100
2005
19 680
46.4
4 781
11.3
183
0.4
42 439
100
2010
20 946
47.2
5 391
12.1
202
0.5
44 409
100
2011
22 847
48.7
5 639
12.0
204
0.4
46 901
100
2012
25 790
49.0
6 425
12.2
249
0.5
52 662
100
2013
26 906
48.2
6 769
12.1
231
0.4
55 858
100
2014
27 154
48.3
7 068
12.6
229
0.4
56 219
100
2015
26 947
48.0
6 956
12.4
240
0.4
56 133
100
2016
26 984
45.8
7 060
12.0
243
0.4
58 894
100
2017
30 110
47.6
7 697
12.2
234
0.4
63 262
100
2018
32 136
49.2
8 508
13.0
252
0.4
65 338
100
2019
33 368
49.1
8 597
12.6
263
0.4
68 022
100
2020
34 615
47.3
9 060
12.4
262
0.4
73 154
100
2021
34 953
48.5
9 144
12.7
269
0.4
72 075
100
(kt CO2 eq.)
Figures in the table may not add up to the totals due to rounding.
Table 5.3 Overview of the agriculture sector emissions, 1990‒2021 (continued)
D. Managed
soils
F. Field
burnıng
Agriculture
total
Year
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
(%)
(kt CO2 eq.)
(%)
1990
17 314
37.6
347
0.8
460
1.0
46 054
100
1995
15 871
36.0
332
0.8
426
1.0
44 080
100
2000
16 870
39.9
340
0.8
617
1.5
42 332
100
2005
16 880
39.8
302
0.7
613
1.4
42 439
100
2010
17 006
38.3
219
0.5
645
1.5
44 409
100
2011
17 421
37.1
233
0.5
558
1.2
46 901
100
2012
19 334
36.7
224
0.4
640
1.2
52 662
100
2013
20 905
37.4
240
0.4
807
1.4
55 858
100
2014
20 764
36.9
215
0.4
788
1.4
56 219
100
2015
21 006
37.4
174
0.3
811
1.4
56 133
100
2016
23 147
39.3
164
0.3
1 295
2.2
58 894
100
2017
23 607
37.3
165
0.3
1 450
2.3
63 262
100
2018
23 022
35.2
163
0.2
1 257
1.9
65 338
100
2019
24 342
35.8
165
0.2
1 288
1.9
68 022
100
2020
27 389
37.4
171
0.2
1 657
2.3
73 154
100
2021
26 249
36.4
159
0.2
1 302
1.8
72 075
100
Figures in the table may not add up to the totals due to rounding.
238
H. Urea
application
(kt CO2 eq.)
Turkish GHG Inventory Report 1990-2021
238
Agriculture
Furthermore, in relative terms, the biggest category in the agriculture sector is enteric fermentation
having a 48.5% share for 2021, so it dominates the sector. In all reported years, 1990-2021, this
category had an average share of 47.6% in the agriculture sector, starting with a share of 48.6% in
1990. The second biggest category is agricultural soils having a proportion of 36.4% for 2021 decreased
from 37.4% in 2020. While having a percentage share of agricultural soils of 40.2% in 2004, its average
share for the entire reporting period of thirty-two years is around 37.9%. Manure management’s share
presents somehow a more stable increasing trend, starting from 11.8% in 1990 and reaching 12.7% in
2021 while having an average of 12.1% for all reporting years. For 2021, remaining categories, which
are rice cultivation, field burning of agricultural residuals, and urea application, had emission shares of
0.4%, 0.2%, and 1.8%, respectively. Though the share increased by around 72% for rice cultivation
and 80.8% for urea application, the absolute terms were small and relative weights of these two
categories were low for the period 1990-2021. Despite these increasing values, the share for field
burning of agricultural residues decreased from 0.8% to 0.2% for the reporting period. A graphical
representation is given below in Figure 5.1, which presents the overall cumulative distribution and the
trend for the reporting period of the agriculture sector. Other sources are calculated by the summation
of emission figures from rice cultivation, field burning, and urea application.
Figure 5.1 Cumulative emissions of agricultural categories, 1990‒2021
80 000
(kt CO2 eq.)
70 000
60 000
50 000
Other Sources
40 000
Turkish GHG Inventory Report 1990-2021
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
Enteric fermentation
1992
10 000
1991
Manure management
1990
20 000
2008
Agricultural soils
30 000
239 239
Agriculture
Additionally, it should be noted that prescribed burning of savannas (CRF Category 3.E) does not occur
in Türkiye and is therefore not reported in this National Inventory Report whereas liming (CRF Category
3.G) is considered to be insignificant according to Paragraph 37(b) of 24/CP.19. Other carbon-containing
fertilizers (CRF Category 3.I) are not occurring while the final category, other (CRF Category 3.J) in the
agriculture sector, is an option to be used only if necessary. Figure 5.2 shows an overview of category
shares and methods used for the agriculture sector.
Figure 5.2 Category shares and methods used in the agriculture sector, 2021
T1 - Field burning of T1 - Urea application
1.8%
agricultural residues
0.2%
Tier 1 - Agricultural soils
36.4%
T1 - Rice cultivation
0.4%
Tier 2 - Enteric
fermentation (Cattle)
37.9%
T1 - Enteric fermentation
(Sheep)
8%
T1 - Manure
management
12.7%
T1 - Enteric fermentation
(Other animals) 2.6%
The methods used for the emission estimations in the agriculture sector except for cattle in enteric
fermentation are Tier 1 (T1). The only Tier 2 (T2) method used in this sector is for emissions due to
enteric fermentation of cattle which has a value of 27 290 kt CO2 eq. This amount equals to around
37.9% of total emissions in the agriculture sector and 78.1% of total emissions in enteric fermentation
which is the biggest subcategory in enteric fermentation as presented in Figure 5.2.
240
Turkish GHG Inventory Report 1990-2021
240
Agriculture
Table 5.4 Agriculture sector emissions ‒ comparison between 2020 and 2021
Source Category
3. Agriculture Sector
2020
2021
Change
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
73 154
100
72 075
100
-1 078
-1.5
3.A
Enteric Fermentation
34 615
47.3
34 953
48.5
339
1
3.B
Manure Management
9 060
12.4
9 144
12.7
83
0.9
3.C
Rice Cultivation
262
0.4
269
0.4
8
3
3.D
Agricultural Soils
27 389
37.4
26 249
36.4
-1 140
-4.2
3.F
Field Burning
171
0.2
159
0.2
-13
-7.5
3.H
Urea Application
1 657
2.3
1 302
1.8
-355
-21.4
Figures in the table may not add up to the totals due to rounding. Note that two source categories, CRF 3.E and 3.I, are not occurring (NO), while
another source category, CRF 3.G Liming, is not estimated (NE) because it is considered to be insignificant.
The emission values between the latest of two reporting years, 2020 and 2021, are presented in Table
5.4 and in order to present a different perspective on the size changes of major agricultural categories,
Figure 5.3 is also given. Major agricultural categories, enteric fermentation, manure management, and
agricultural soils, are responsible for more than 97% of the emissions in the sector. Additionally, the
main changes in minor agricultural categories are shown in Figure 5.4.
Turkish GHG Inventory Report 1990-2021
241 241
Agriculture
Figure 5.3 Trends in major agriculture categories
40 000
(kt CO2 eq.)
35 000
30 000
25 000
20 000
15 000
10 000
5 000
Enteric Fermentation
Manure Management
1990
2000
2010
Agricultural Soils
2021
Figure 5.4 Trends in minor agriculture categories
1400
(kt CO2 eq.)
1200
1000
800
600
400
200
0
Rice Cultivation
Field Burning of Agricultural
Residues
1990
242
2000
2010
Urea Application
2021
Turkish GHG Inventory Report 1990-2021
242
Agriculture
GHG emission values and their percentage shares in the agriculture sector, CH4, N2O and CO2, are
presented in Table 5.5. After its initial increase in 1991, emission values for CH4 decreased in the eleven
years (except in 1996 and 1999) until 2002. Thereafter, the overall increasing trend could be split into
two phases: a moderate one until 2009 and a stronger one after 2009. Overall, the percentage share
of CH4 increased from 54.5% in 1990 to 54.6% in 2021.
The average share of N2O emissions were around 44.8% with respect to yearly total agricultural
emission values. The emission values for N2O were 20 480 kt CO2 eq. (44.5%) in 1990 and increased
to an estimated value of 31 442 kt CO2 eq. while taking a smaller share of 43.6% of total agricultural
emissions in 2021. N2O emissions are due to manure management and agricultural soils source
categories in the agricultural sector.
CO2 emissions result only from urea application; have the smallest share in this sector, and ranges
between 0.9% and 2.3% for the period 1990-2021. The highest absolute value of CO2 emissions
occurred in 2020 with 1 657 kt, while it has the smallest value in 1995 with 426 kt depending on the
amount of urea applied. The corresponding value for the latest reporting year accounts for a share of
1.8%.
Table 5.5 Overview of GHGs in the agriculture sector, 1990‒2021
CH4
N2O
CO2
Total
Year
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
(kt)
(%)
(kt CO2 eq.)
1990
25 114
54.5
20 480
44.5
460
1.0
46 054
1995
24 707
56.1
18 947
43.0
426
1.0
44 080
2000
21 955
51.9
19 759
46.7
617
1.5
42 332
2005
22 053
52.0
19 773
46.6
613
1.4
42 439
2010
23 786
53.6
19 978
45.0
645
1.5
44 409
2011
25 681
54.8
20 662
44.1
558
1.2
46 901
2012
29 048
55.2
22 975
43.6
640
1.2
52 662
2013
30 316
54.3
24 734
44.3
807
1.4
55 858
2014
30 712
54.6
24 720
44.0
788
1.4
56 219
2015
30 351
54.1
24 972
44.5
811
1.4
56 133
2016
30 464
51.7
27 134
46.1
1 295
2.2
58 894
2017
33 818
53.5
27 995
44.3
1 450
2.3
63 262
2018
36 399
55.7
27 682
42.4
1 257
1.9
65 338
2019
37 578
55.2
29 157
42.9
1 288
1.9
68 022
2020
39 006
53.3
32 491
43.0
1 657
2.3
73 154
2021
39 332
54.6
31 442
43.6
1 302
1.8
72 075
Figures in the table may not add up to the totals due to rounding. Source categories for CH4 and N2O emissions are presented in Table 5.9 and
5.10, respectively, whereas the only source category for CO2 emissions is urea application (CRF category 3.H) which emits carbon dioxide
reported under the agriculture sector.
The activity data used for the compilation of the GHG inventory are provided mainly by TurkStat’s
databases distributed by its Central Dissemination System on the following website accessible on
https://biruni.tuik.gov.tr/medas/?kn=101&locale=en which is also accessible at www.turkstat.gov.tr.
Turkish GHG Inventory Report 1990-2021
243 243
Agriculture
Livestock population data are critical activity data for the required calculations. Animal population
numbers shown in Table 5.6 are provided by TurkStat for the entire time series, 1990-2021. There are
differences among population sizes (cattle, sheep and swine), between the numbers used for the
estimations of GHG emissions and official numbers submitted to the Food and Agriculture Organization
of the United Nations (FAO). The FAO data are slightly old and do not consider the most recent TurkStat
data, which is used for the inventory submission. Therefore, the AD of the GHG inventory are more
recent and accurate compared to FAO. Moreover, FAO has some assumptions on TurkStat data.
Although the data are updated each year by TurkStat, FAO has still continued to use its assumptions.
Therefore, the data sent by TurkStat, which are also used for GHG inventory, are the most accurate
data available for inventory calculations.
Data on livestock production have been collected from District Offices of the Ministry of Agriculture and
Forestry at the end of the year. Since 2014, data on livestock numbers have been collected and
published two times a year. The data, entered into an online database by the district offices, have been
analyzed together with the Ministry of Agriculture and Forestry. Prepared data are sent to the Ministry
for controlling process. Once again controlled data are analyzed by Agricultural Production Statistics
Group at TurkStat and will then become ready for publishing after final analysis and controls.
Livestock population numbers are given for livestock species in Table 5.6. As the numbers show, both
dairy and non-dairy cattle, domestic sheep, poultry and goats have significantly high population numbers
with respect to other livestock species. Five columns, which are dairy cattle, non-dairy cattle, sheep
merino, goats, and poultry, have positive differences between 1990 and 2021 with population increasing
around 0.9 million (14.7%), 5.6 million (102.2%), 3.2 million (374%), 1.4 million (13%) and 295.9
million (289.3%), respectively. It is remarkable that poultry numbers had more than tripled in 32 years
from around 102.3 million to over 398 million. Contrary to these developments, the change for the
reporting period of 32 years was as much as -88.7% for the swine population and -90.1% for mules
and asses. Similarly, other changing percentages observed for camels, domestic sheep, buffalo, and
horses are -39.8%, 3.7%, -50%, -83.7%, respectively. The figures also presents a decreasing trend for
few livestock species for the reporting period of 1990-2021. During the reporting period, our country's
population is increasingly living in urban areas rather than in rural areas which reduced the demand for
some of the animals in small households living in rural areas. Moreover, a few animal categories used
for carrying goods previously in rural areas, are not needed any more extensively for this purpose. Thus
the demand for a few livestock species decreased.
244
Turkish GHG Inventory Report 1990-2021
244
Agriculture
Table 5.6 Livestock population numbers in Türkiye, 1990‒2021
(thousand)
Year
Dairy
Cattle
NonDairy
Cattle
1990
5 893
5 485
39 711
842
10 926
371
513
1 187
14.0
102 255
1995
5 886
5 903
32 985
806
9 111
255
415
900
7.0
135 251
2000
5 280
5 481
27 719
773
7 201
146
271
588
4.0
264 451
2005
3 998
6 528
24 552
752
6 517
105
208
423
2.7
322 917
2010
4 362
7 008
22 003
1 086
6 293
85
155
260
2.8
238 973
2011
4 761
7 625
23 811
1 221
7 278
98
151
248
3.1
241 499
2012
5 431
8 484
25 893
1 533
8 357
107
141
236
4.3
257 505
2013
5 607
8 808
27 485
1 799
9 226
118
136
227
4.5
270 202
2014
5 609
8 614
29 034
2 106
10 345
122
131
212
4.1
298 030
2015
5 536
8 458
29 302
2 206
10 416
134
123
198
3.2
316 332
2016
5 432
8 648
28 833
2 151
10 345
142
120
190
2.9
333 541
2017
5 969
9 975
31 257
2 420
10 635
161
114
176
3.1
348 144
2018
6 338
10 705
32 513
2 682
10 922
178
108
165
3.3
359 218
2019
6 581
11 107
34 199
3 077
11 205
184
102
156
3.1
348 785
2020
6 775
11 190
38 580
3 547
11 986
192
90
133
2.0
386 081
2021
6 759
11 091
41 183
3 995
12 342
186
84
118
2.6
398 115
Sheep
Domestic
Sheep
Merino
Goats
Buffalo
Horses
Mules
and
Asses
Swine,
Camels
Poultry
Note that dairy cattle population for the year 2003 is taken as the average of population figures for 2002 and 2004 after carefully
discussed/scrutinized with the Agricultural Statistics Department at TurkStat in order to ensure comparability for the entire time series. This
was necessary because of a different methodology applied regarding dairy cattle for the year 2003. Non-dairy cattle figures were adjusted
accordingly.
Time series for cattle population with its subcategories in our country are presented in Table 5.7.
Livestock production can result in CH4 emissions from enteric fermentation and also in CH4 and N2O
emissions from livestock manure management systems. Cattle as a livestock category is a significant
source of CH4 in our country because of their large population and high CH4 emission rate due to their
ruminant digestive system.
In Türkiye there are three dairy cattle types categorized as culture cattle, hybrid cattle and domestic
cattle as shown in Table 5.8. Culture dairy cattle is a dairy cattle type having higher milk yields compared
to domestic dairy cattle whereas milk yields values of hybrid cattle are between them. Hybrid cattle are
breeds of culture and domestic dairy cattle. Culture dairy cattle population is increasing by years except
for the years 1997, 1998, 2002-2004 and 2021. But, in general, the culture dairy cattle population has
a positive trend in the period 1990-2021, which has a percentage increase of 41.3% from 9% in 1990
to 50.3% in 2021 within dairy cattle population. For hybrid cattle population, which was around 2.8
million in 2021 despite being 1.9 million in 1990, a big increase or decrease in percentage share cannot
be observed throughout the same period, though the final three reporting years identified a total
increase of around 0.1 million. The share of domestic cattle among dairy cattle was 58.1% in 1990 but
this ratio reduced to 7.7% in 2021. As seen in Table 5.7, non-dairy cattle number increased by
approximately 5.6 million from around 5.5 million in 1990 to more than 11.1 million in 2021 and its
share in total number of cattle increased from 48.2% to 62.1% between 1990 and 2021. Furthermore,
Turkish GHG Inventory Report 1990-2021
245 245
Agriculture
Figure 5.5 presents three types of dairy cattle as well as non-dairy cattle population numbers for the
period of 1990-2021 in a straightforward chart.
Figure 5.5 Population numbers for cattle categories, 1990‒2021
Dairy Cattle (Culture)
246
Dairy Cattle (Hybrid)
Dairy Cattle (Domestic)
Turkish GHG Inventory Report 1990-2021
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
(million)
1990
12
11
10
9
8
7
6
5
4
3
2
1
Non-Dairy Cattle
246
Agriculture
Table 5.7 Subcategories of cattle population, 1990‒2021
Total Cattle
Year
Dairy Cattle
Non-Dairy Cattle
(population)
(population)
(%)
(population)
(%)
1990
11 377 057
5 892 550
51.8
5 484 507
48.2
1995
11 789 000
5 885 586
49.9
5 903 414
50.1
2000
10 761 000
5 279 573
49.1
5 481 427
50.9
2005
10 526 440
3 998 095
38.0
6 528 345
62.0
2010
11 369 800
4 361 842
38.4
7 007 958
61.6
2011
12 386 337
4 761 150
38.4
7 625 187
61.6
2012
13 914 912
5 431 403
39.0
8 483 509
61.0
2013
14 415 257
5 607 278
38.9
8 807 979
61.1
2014
14 223 109
5 609 249
39.4
8 613 860
60.6
2015
13 994 071
5 535 779
39.6
8 458 292
60.4
2016
14 080 155
5 431 720
38.6
8 648 435
61.4
2017
15 943 586
5 969 051
37.4
9 974 535
62.6
2018
17 042 506
6 337 906
37.2
10 704 600
62.8
2019
17 688 139
6 580 834
37.2
11 107 305
62.8
2020
17 965 482
6 775 321
37.7
11 190 161
62.3
2021
17 850 543
6 759 168
37.9
11 091 375
62.1
Figures in the table may not add up to the totals due to rounding. Note also the footnote to Table 5.6.
Table 5.8 Subcategories of dairy cattle population, 1990‒2021
Total
Culture
Hybrid
Domestic
Year
(population)
(population)
(%)
(population)
(%)
(population)
(%)
1990
5 892 550
530 330
9.0
1 941 170
32.9
3 421 050
58.1
1995
5 885 586
870 246
14.8
2 392 621
40.7
2 622 719
44.6
2000
5 279 573
904 850
17.1
2 335 119
44.2
2 039 604
38.6
2005
3 998 095
925 613
23.2
1 717 310
43.0
1 355 172
33.9
2010
4 361 842
1 626 416
37.3
1 787 010
41.0
948 416
21.7
2011
4 761 150
1 868 281
39.2
1 962 711
41.2
930 158
19.5
2012
5 431 403
2 211 245
40.7
2 263 400
41.7
956 758
17.6
2013
5 607 278
2 314 282
41.3
2 395 898
42.7
897 098
16.0
2014
5 609 249
2 427 915
43.3
2 428 709
43.3
752 625
13.4
2015
5 535 779
2 500 881
45.2
2 314 063
41.8
720 835
13.0
2016
5 431 720
2 542 164
46.8
2 235 503
41.2
654 053
12.0
2017
5 969 051
2 940 907
49.3
2 426 763
40.7
601 381
10.1
2018
6 337 906
3 185 954
50.3
2 554 949
40.3
597 003
9.4
2019
6 580 834
3 249 038
49.4
2 745 272
41.7
586 524
8.9
2020
6 775 321
3 398 270
50.2
2 808 168
41.4
568 883
8.4
2021
6 759 168
3 398 164
50.3
2 842 183
42.0
518 821
7.7
Figures in the table may not add up to the totals due to rounding. Note also the footnote to Table 5.6.
Table 5.3, given previously, presents a detailed perspective on the agriculture sector emissions for the
reporting period. GHG emissions from livestock are CH4 in enteric fermentation and CH4 and N2O in
manure management. Rice cultivation leads to CH4 emissions, agricultural soils to N2O emissions, field
burning of crop residues to CH4 and N2O emissions. Urea application is the only category directly
resulting in CO2 emissions reported under the agriculture sector in our country. An overview of emission
Turkish GHG Inventory Report 1990-2021
247 247
Agriculture
factors and parameters related to emission calculations from the agriculture sector is shown in Annex 3
of the NIR.
Methane (CH4)
Emissions from enteric fermentation, manure management, rice cultivation and field burning of
agricultural residues include methane. The agriculture sector in our country produced 1573.3 kt CH4
(39.3 Mt CO2 eq.) emissions, which equals 54.6% of agricultural emissions or 61,4% of Türkiye’s CH4
emissions (without LULUCF), or 7% of Türkiye’s total emissions in 2021. CH4 emissions had increased
by 14 218 kt CO2 eq. (56.6%) from its 1990 level of 25 114 kt CO2 eq. to 39 332 kt CO2 eq. in 2021.
This increase is mainly a result of increases in CH4 emissions from enteric fermentation of 12 557 kt CO2
eq., from manure management of 1 636 kt CO2 eq., and from rice cultivation of 169 kt CO2 eq. The
total increase as high as 14 218 kt CO2 eq. is responsible for 54.6% of 26 022 kt CO2 eq. overall increase
in emissions from the agricultural sector between 1990 and 2021.
Enteric fermentation is the single dominant category leading to 89.2% in 1990 and 88.9% in 2021 of
all CH4 emissions of the agriculture sector. Enteric fermentation was followed by manure management
with 9.4% in 1990 and 10.1% in 2021. CH4 emissions from field burning of agricultural residues are
1.1% in 1990 and 0.3% in 2021 of all CH4 emissions from the agriculture sector. CH4 emissions share
of rice cultivation is 0.4% and 0.7% for 1990 and 2021, respectively. An overview of CH4 emissions are
presented in the following table.
Table 5.9 Overview of CH4 emissions in the agriculture sector, 1990‒2021
CH4 Emissions
3.A
3.B
Year
(kt CO2 eq.)
(%)
(kt CO2 eq.)
1990
22 397
89.2
1995
21 815
88.3
2000
19 234
2005
3.C
Total
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
(kt CO2 eq.)
2 352
9.4
100
0.4
265
1.1
25 114
2 526
10.2
113
0.5
254
1.0
24 707
87.6
2 334
10.6
128
0.6
260
1.2
21 955
19 680
89.2
1 959
8.9
183
0.8
231
1.0
22 053
2010
20 946
88.1
2 471
10.4
202
0.8
167
0.7
23 786
2011
22 847
89.0
2 452
9.5
204
0.8
178
0.7
25 681
2012
25 790
88.8
2 837
9.8
249
0.9
171
0.6
29 048
2013
26 906
88.8
2 996
9.9
231
0.8
184
0.6
30 316
2014
27 154
88.4
3 163
10.3
229
0.7
164
0.5
30 712
2015
26 947
88.8
3 031
10.0
240
0.8
133
0.4
30 351
2016
26 984
88.6
3 112
10.2
243
0.8
126
0.4
30 464
2017
30 110
89.0
3 348
9.9
234
0.7
126
0.4
33 818
2018
32 136
88.3
3 886
10.7
252
0.7
124
0.3
36 399
2019
33 368
88.8
3 820
10.2
263
0.7
126
0.3
37 578
2020
34 615
88.7
3 999
10.3
262
0.7
131
0.3
39 006
2021
34 953
88.9
3 988
10.1
269
0.7
121
0.3
39 332
Figures in the table may not add up to the totals due to rounding.
248
3.F
(%)
Turkish GHG Inventory Report 1990-2021
248
Agriculture
Nitrous Oxide (N2O)
Nitrous oxide is a GHG with a high global warming potential. Overall, excluding LULUCF, N2O emissions
accounted for around 7.1% of Türkiye's GHG emissions in 2021. Emissions from manure management,
agricultural soils, and field burning of agricultural residues include N2O gas. Agriculture as a sector
produced 105.51 kt N2O emissions (31.4 Mt CO2 eq.), which equals 43.6% of agricultural emissions or
78% of Türkiye’s N2O emissions (excluding LULUCF) or 5.6% of Türkiye’s total emissions in 2021. N2O
emissions have increased by 10 962 kt CO2 eq. (53.5%) from 20 480 kt CO2 eq. (1990) to 31 442 kt
CO2 eq. (2021).
The source category agricultural soils is the dominant source of N2O emissions, responsible for 84.5%
and 83.5% of total agricultural N2O emissions for the years 1990 and 2021, respectively. Regarding N2O
emissions, agricultural soils were followed by manure management with 15.1% in 1990 and 16.4% in
2021, and field burning of agricultural residues with 0.4% in 1990 and 0.1% in 2021. While a percentage
as high as 81.5% of the augmentation in nitrous oxide emissions is a result of increases of N2O emissions
in agricultural soils by 8 935 kt CO2 eq., manure management is responsible for the remaining increase
of 18.9% with 2 071 kt CO2 eq. in N2O emissions. N2O emissions of field burning of agricultural residues
show a decrease of 54.3% (0.1% of Agricultural N2O emissions by an amount of 37 kt CO2 eq.) between
1990 and 2021. The net increase of 10 962 kt CO2 eq. of N2O emissions added up to 42.1% of the
overall increase of 26 022 kt CO2 eq. emissions in the agriculture sector between 1990 and 2021. An
overview of N2O emissions is presented in the next table.
Table 5.10 Overview of N2O emissions in the agriculture sector, 1990‒2021
N2O Emissions
3.B
3.D
3.F
Total
Year
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
(kt CO2 eq.)
1990
3 084
15.1
17 314
84.5
82
0.4
20 480
1995
2 997
15.8
15 871
83.8
78
0.4
18 947
2000
2 809
14.2
16 870
85.4
80
0.4
19 759
2005
2 822
14.3
16 880
85.4
71
0.4
19 773
2010
2 921
14.6
17 006
85.1
52
0.3
19 978
2011
3 187
15.4
17 421
84.3
55
0.3
20 662
2012
3 588
15.6
19 334
84.2
53
0.2
22 975
2013
3 772
15.3
20 905
84.5
57
0.2
24 734
2014
3 905
15.8
20 764
84.0
51
0.2
24 720
2015
3 925
15.7
21 006
84.1
41
0.2
24 972
2016
3 948
14.5
23 147
85.3
39
0.1
27 134
2017
4 349
15.5
23 607
84.3
39
0.1
27 995
2018
4 622
16.7
23 022
83.2
38
0.1
27 682
2019
4 776
16.4
24 342
83.5
39
0.1
29 157
2020
5 062
15.6
27 389
84.3
40
0.1
32 491
2021
5 155
16.4
26 249
83.5
37
0.1
31 442
Figures in the table may not add up to the totals due to rounding.
Turkish GHG Inventory Report 1990-2021
249 249
Agriculture
5.2. Enteric Fermentation (Category 3.A)
Source Category Description:
Enteric fermentation is a digestive process whereby carbohydrates are broken down by micro-organisms
into simple molecules. The main product is CH4 gas. Animals produce CH4 during and/or after feed
intake. The largest source of CH4 emissions in the agricultural sector in our country is enteric
fermentation. It is the biggest source of total carbon dioxide equivalent emissions in the agriculture
sector with 48.6% (22.4 Mt CO2 eq.) in 1990 and with 48.5% (35 Mt CO2 eq.) in 2021.
In 2021, enteric fermentation contributed as high as 34 953 kt CO2 eq., responsible for nearly half of
agricultural emissions as stated above and 6.2% of Türkiye’s total CO2 eq. emissions. Dairy and nondairy cattle contributed 27 290 kt CO2 eq. (78.1%) of emissions to the enteric fermentation category
and sheep (domestic and merino) contributed 5 797 kt CO2 eq. (16.6%) of emissions to this category.
This source category in 2021 resulted in a value of 12 557 kt CO2 eq. (56%) of increased emissions
compared to 1990 levels (22 397 kt CO2 eq).
CH4 emissions from enteric fermentation, which are presented by main livestock species in Table 5.11,
fluctuate over time. This source category is a key category according to level and trend assessment.
Enteric fermentation emissions declined by 24.2% (5.4 Mt CO2 eq.) between 1990 and 2002. The decline
in emissions in the early 1990s was primarily occurred by a fall in cattle and sheep numbers; however,
the emissions had begun to increase as the numbers of cattle began to rise by late 2004, reflecting
changing relative returns to each industry. Due to governmental support, the numbers of many
significant livestock species have been increasing in recent years, thereby resulting also in an increase
in CH4 emissions for these subcategories. Between 2004 and 2021, emissions from enteric fermentation
increased by 84.3% (16 Mt CO2 eq).
There have been changes in the relative sources of emissions within enteric fermentation (Table 5.11)
since 1990. The largest increase occurred from non-dairy cattle emissions due to an increase in its
population numbers. In 2021, non-dairy cattle were responsible for 13 154 kt CO2 eq., increased by
7 294 kt CO2 eq. (124.5%) from the 1990 level of 5 860 kt CO2 eq. Despite a slight increase of 15% in
dairy cattle population for the period of 1990-2021, this subcategory is responsible for 14 136 kt CO2
eq. in 2021, still an increase of 5 106 kt CO2 eq. (56.5%) above its 1990 level of 9 030 CO2 eq. A closer
look at the changes in the composition structure of dairy cattle (culture, hybrid, and domestic cattle)
revealed a reasonable explanation for the same period. The dairy cattle population was 5.9 million in
total for 1990, which consisted of culture cattle (0.53 million), hybrid cattle (1.94 million), and domestic
cattle (3.42 million). The respective figures for the year 2021 were 6.76 million in total for dairy cattle
consisting of culture cattle (3.4 million), hybrid cattle (2.8 million), and domestic cattle (0.5 million).
250
Turkish GHG Inventory Report 1990-2021
250
Agriculture
The share of culture dairy cattle type had increased significantly in numbers while domestic dairy cattle
experienced a reduction both in absolute and relative terms presented in Table 5.8. Population numbers
of livestock species for the period 1990-2021 are shown in Table 5.6. While Figure 5.6 presents the
percentage shares for the subcategories of enteric fermentation emission sources for the latest reporting
year, on the next page, Table 5.11 presents CH4 emissions of enteric fermentation regarding livestock
species for the period, 1990-2021.
Figure 5.6 Enteric Fermentation Emission Sources, 2021
Tier 1 – Other Animals
5%
Tier 1 – Sheep
17%
Tier 2 – Cattle
78%
Turkish GHG Inventory Report 1990-2021
251 251
Agriculture
Table 5.11 Enteric fermentation CH4 emissions, 1990‒2021
Year
Dairy
Cattle
1990
9 030
5 860
4 964
137
1 366
510
231
297
3
22 397
1995
9 431
6 226
4 123
131
1 139
351
187
225
2
21 815
2000
8 592
5 680
3 465
126
900
201
122
147
1
19 234
2005
7 490
7 839
3 069
122
815
144
94
106
1
19 680
2010
8 653
8 327
2 750
177
787
116
70
65
1
20 946
2011
9 523
8 973
2 976
198
910
134
68
62
2
22 847
2012
10 935
10 053
3 237
249
1 045
148
64
59
2
25 790
2013
11 333
10 410
3 436
292
1 153
162
61
57
2
26 906
2014
11 440
10 168
3 629
342
1 293
168
59
53
2
27 154
2015
11 351
9 983
3 663
358
1 302
184
55
49
2
26 947
2016
11 197
10 241
3 604
350
1 293
195
54
47
2
26 984
2017
12 410
11 751
3 907
393
1 329
222
51
44
2
30 110
2018
13 218
12 716
4 064
436
1 365
245
49
41
2
32 136
2019
13 705
13 147
4 275
500
1 401
253
46
39
2
33 368
2020
14 145
13 232
4 822
576
1 498
265
41
33
2
34 615
2021
14 136
13 154
5 148
649
1 543
255
38
29
2
34 953
Sheep
Domestic
Sheep
Merino
Goats
Buffalo
Figures in the table may not add up to the totals due to rounding.
252
(kt CO2 eq.)
NonDairy
Cattle
Turkish GHG Inventory Report 1990-2021
Horses
Mules
and
Asses
Swine,
Camels
Total
252
Agriculture
Methodological Issues:
Türkiye applies T1 method to estimate CH4 emissions from enteric fermentation for all livestock
populations except cattle for which T2 method is applied. The T2 method is applied by using mainly
country-specific parameters. Necessary data for T2 calculations are mainly gathered from TurkStat
Agricultural Statistics Department, Ministry of Agriculture and Forestry, academic sources. The results
for cattle in enteric fermentation are presented both in Figure 5.6 and Table 5.11. Moreover, Tables
5.12 and 5.13 present key country-specific parameters regarding T2 calculation; except for methane
conversion factor which is a default value shown in the 2006 IPCC Guidelines. The annual population
numbers for livestock species are included in Table 5.6 above. The AD (the population of livestock
species) are obtained from TurkStat livestock statistics. TurkStat collects livestock data as explained in
the sector overview. T2 cattle emissions are calculated according to equations 10.3, 10.4, 10.6, 10.8,
10.13, 10.14, 10.15, 10.16 and 10.21 presented in the 2006 IPCC Guidelines, Volume 4, Chapter 10.
Sheep are categorized as merino and domestic sheep in our country. For domestic sheep IPCC default
EF for developing countries (5.0 kg CH4 head-1 year-1) is used. Merino sheep are also a kind of domestic
sheep fed for their wool. The weight of merino sheep is higher compared to domestic sheep and their
feeding rate is also higher than domestic ones. For these reasons, EF for merino sheep is chosen as a
higher value compared to domestic sheep. The EF of merino sheep is taken as an average value (6.5
kg CH4 head-1 year-1) from the IPCC default EF for developing countries (5.0 kg CH4 head-1 year-1) and
developed countries (8.0 kg CH4/head/year). The country-specific typical animal mass values are 50
kg/head and 60 kg/head for domestic sheep and merino sheep, respectively. It is clear that emission
levels for merino sheep currently calculated are conservative since the approximate EF for merino sheep
is 5.73 kg CH4/head/year obtained by the quotient of the weight figures (60 kg/50kg) raised to the
power of 0.75 and then multiplied by the EF for domestic sheep (5.0 kg CH4 head-1 year-1). As stated
clearly in the 2006 IPCC Guidelines (Vol.4, Chapter 10, page 10.24), this approximate figure can only
be used to assess the significance of the emissions from a livestock species. The EF value for merino
sheep is clearly higher than the calculated approximate EF value.
Uncertainties and Time-Series Consistency:
The AD for this sector are gathered from agricultural statistics of TurkStat. Uncertainties for the activity
data are determined by TurkStat experts and uncertainty values for EFs are taken from the IPCC
Guidelines. The calculated AD uncertainty figure is 8.74% whereas the EF uncertainty value is 11.99%
figured out by using Equation 3.2 in the IPCC Guidelines Vol. 1.
Turkish GHG Inventory Report 1990-2021
253 253
Agriculture
Source category
3.A
Gas
CH4
Comments on time series consistency
All EFs for cattle are not constant over the entire time series
because they are estimated mainly according to the split of
culture, hybrid and domestic. Since the population numbers for
cattle change over the reporting period, the respective EFs also
reflect this change. EFs for all other livestock species are
constant.
Source-Specific QA/QC and Verification:
The 2006 IPCC Guidelines are used for the QA/QC procedures of the National GHG emission inventory.
The National Inventory System QA/QC Plan prepared by TurkStat is a significant tool for implementing
QA/QC procedures for the Inventory. AD for this source category are gathered mainly from the
Agricultural Statistics Department of TurkStat. The respective AD used for calculations are published
also as official statistics by TurkStat which have their own QA/QC procedures. Emission trends are
analyzed. If there is a high fluctuation in the series, then AD and emission calculations are re-examined.
Moreover, a QA work was conducted by a Project Engineer from CITEPA for this category in January
2020.
Recalculation:
There was no recalculation exercised regarding emission estimates from this source category in this
submission.
254
Turkish GHG Inventory Report 1990-2021
254
Agriculture
Table 5.12 Key T2 parameters and estimated emissions for dairy cattle, 1990‒2021
Dairy Cattle
Mass
(kg)
GE intake
(MJ/head/
day)
CH4
Conversion
rates, Ym
(%)
Milk
yield
(kg/day)
Digestibility
of feed
(%)
361.2
350.4
143.8
6.50
3.70
64.19
377.2
377.4
150.3
6.50
4.32
65.54
2000
343.7
389.0
152.7
6.50
4.53
66.14
2005
299.6
404.1
175.8
6.50
6.87
66.61
2010
346.1
440.9
186.1
6.50
7.80
67.83
2011
380.9
446.8
187.7
6.50
7.94
68.05
2012
437.4
451.5
188.9
6.50
8.06
68.24
2013
453.3
454.6
189.6
6.50
8.14
68.40
2014
457.6
461.0
191.4
6.50
8.30
68.66
2015
454.0
464.2
192.4
6.50
8.38
68.70
2016
447.9
467.9
193.4
6.50
8.47
68.80
2017
496.4
474.1
195.1
6.50
8.61
68.99
2018
528.7
476.4
195.7
6.50
8.66
69.06
2019
548.2
475.9
195.4
6.50
8.65
69.11
2020
565.8
477.7
195.9
6.50
8.69
69.16
2021
565.4
478.9
196.2
6.50
8.73
69.23
Year
CH4
Emissions
(kt)
1990
1995
Table 5.13 Key T2 parameters and estimated emissions for non-dairy cattle, 1990‒2021
Non-dairy Cattle
CH4
GE intake Conversion
(MJ/head/
rates, Ym
(%)
day)
Year
CH4
Emissions
(kt)
Mass
(kg)
Digestibility
of feed
(%)
1990
234.4
180.6
100.3
6.50
60.77
1995
249.0
192.3
99.0
6.50
62.08
2000
227.2
194.5
97.2
6.50
62.54
2005
313.6
253.9
112.7
6.50
64.56
2010
333.1
279.2
111.5
6.50
65.84
2011
358.9
281.2
110.4
6.50
65.97
2012
402.1
287.5
111.2
6.50
66.23
2013
416.4
289.0
110.9
6.50
66.33
2014
406.7
293.6
110.8
6.50
66.55
2015
399.3
296.4
110.7
6.50
66.61
2016
409.6
297.6
111.1
6.50
66.72
2017
470.0
296.4
110.5
6.50
66.86
2018
508.6
300.1
111.5
6.50
66.99
2019
525.9
300.1
111.1
6.50
67.03
2020
529.3
304.5
110.9
6.50
67.09
2021
526.2
305.2
111.3
6.50
67.18
Planned Improvement:
Türkiye considers the possibility of using Tier 2 method for estimating enteric fermentation emissions
from sheep in the next submissions.
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5.3. Manure Management (Category 3.B)
Source Category Description:
In Türkiye, manure management systems (MMS) distribution data are a result of the combination of
various sources, including expert opinions, comparison of countries in the Mediterranean basin, MoAF
data, TurkStat data etc. resulting in a country-specific MMS distribution presented in Table 5.19.
This source category contains two types of emissions, CH4 and N2O, and for both of these emissions,
the source category is a key category according to level assessment. According to trend assessment,
while the source category is key category only for N2O emissions with LULUCF, it is also key category
for N2O and CH4 emissions without LULUCF.
In 2021, emissions including CH4 and N2O from the manure management category reached 9 144 kt
CO2 eq. This number represented 12.7% of emissions of the agriculture sector. Emissions from this
source category in 2021 increased by 3 707 kt CO2 eq., nearly 68.2% above its 1990 level of 5 436 kt
CO2 eq. Similarly, the increase is calculated as 1 636 kt CO2 eq. for CH4 emissions and 2 071 kt CO2 eq.
for N2O emissions and increasing percentages are 70% and 67.1%, respectively, for the period 19902021.
Manure management emissions can also be described as direct emissions consisting of CH4 and N2O
emissions with a share of 79.6% (7280 kt CO2 eq.) and indirect emissions consisting only of N2O
emissions with a share of 20.4% (1 864 kt CO2 eq.). It is also significant to note that there are two
types of indirect N2O emissions to be calculated under manure management, which are due to nitrogen
volatilization and nitrogen leaching and run-off. The indirect N2O emissions share of 20.4% is only a
result of the amount of manure nitrogen that is lost due to volatilization of NH3 and NOx. Indirect
emissions due to leaching and run-off from manure are calculated as 158 kt CO2 eq. for the latest
reporting year. This emission level is considered insignificant and reported as NE according to 24/CP.19
paragraph 37(b). While the following Figure 5.7 presents emission shares of manure management
subcategories for the latest reporting year, Table 5.11 combines and presents the emission figures from
manure management for the entire reporting period.
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Figure 5.7 Manure Management Emission Sources, 2021
Indirect N2O
20%
CH4 – Cattle
40%
N2O - Other Animals
5%
N2O – Sheep
10%
CH4 – Sheep 2%
N2O – Cattle
21%
CH4 – Other Animals 2%
Regarding MMS, TurkStat has asked academicians for their views on the topic, investigated countries in
the Mediterranean Basin whose the agriculture sector would resemble of our country’s, searched
internally through some of our regional offices, looked for field experiences gained throughout the years
within TurkStat and also scrutinized agriculture-related data which have not been published so far in
order to come up with a distribution that would reflect our country-specific conditions better.
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Table 5.14 Overview of emissions from manure management, 1990‒2021
Manure management source category
Agriculture
Total
Total
Year
(kt CO2 eq.)
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
1990
46 054
5 436
11.8
2 352
5.1
2 190
4.8
895
1.9
1995
44 080
5 523
12.5
2 526
5.7
2 072
4.7
925
2.1
2000
42 332
5 142
12.1
2 334
5.5
1 836
4.3
973
2.3
2005
42 439
4 781
11.3
1 959
4.6
1 754
4.1
1 069
2.5
2010
44 409
5 391
12.1
2 471
5.6
1 851
4.2
1 070
2.4
2011
46 901
5 639
12.0
2 452
5.2
2 033
4.3
1 154
2.5
2012
52 662
6 425
12.2
2 837
5.4
2 296
4.4
1 292
2.5
2013
55 858
6 769
12.1
2 996
5.4
2 418
4.3
1 354
2.4
2014
56 219
7 068
12.6
3 163
5.6
2 500
4.4
1 405
2.5
2015
56 133
6 956
12.4
3 031
5.4
2 503
4.5
1 422
2.5
2016
58 894
7 060
12.0
3 112
5.3
2 501
4.2
1 446
2.5
2017
63 262
7 697
12.2
3 348
5.3
2 759
4.4
1 590
2.5
2018
65 338
8 508
13.0
3 886
5.9
2 929
4.5
1 692
2.6
2019
68 022
8 597
12.6
3 820
5.6
3 044
4.5
1 732
2.5
2020
73 154
9 060
12.4
3 999
5.5
3 224
4.4
1 837
2.5
2021
72 075
9 144
12.7
3 988
5.5
3 291
4.6
1 864
2.6
CH4
Direct N2O
Indirect N2O
Indirect N2O emissions from manure management include only emissions due to atmospheric deposition. Manure management indirect N2O
emissions due to leaching and run-off are considered to be insignificant because of its calculated emission level of 158 kt CO2 eq. for the latest
reporting year. This level is well-below the threshold level specified in Paragraph 37(b) of 24/CP.19. The indirect N2O emissions level from nitrogen
leaching and run-off is estimated by applying Equations 10.28 and 10.29 (Chapter 10, Volume 4, 2006 IPCC Guidelines). Given our country’s
rather dry climatic conditions, a FracLeachMS value of 4.5% is used in the calculations for all solid storage and dry lot manure systems as
appropriate. 4.5% is the mid-range value between 3% and 6% which is considered to be more suitable in drier climates as explained on page
10.56 of the 2006 IPCC Guidelines. Figures in the table may not add up to the totals due to rounding.
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Methane Generation
Livestock manure is primarily composed of organic material and water. Anaerobic and facultative
bacteria decompose the organic material under anaerobic conditions. Several biological and chemical
factors influence methane generation from manure. The amount of CH4 produced during decomposition
is influenced by the climate and the manner in which the manure is managed. The management system
determines key factors that affect CH4 production including contact with oxygen, water content, pH, and
nutrient availability. Climate factors include temperature and rainfall. Optimal conditions for CH4
production include an anaerobic, water-based environment, a high level of nutrients for bacterial
growth, a neutral pH (close to 7.0), warm temperatures, and a moist climate.
Manure management CH4 emissions contributed 3 988 kt CO2 eq. (43.6% of the manure management
category) which constituted 5.5% of agricultural emissions in 2021 whereas the respective share in
1990 was 5.1%, around 0.4 per cent below the current reporting value.
With respect to all CH4 emissions of the agriculture sector, the second highest CH4 emission source
category was manure management for all reporting years with a share value of 9.4% and 10.1% for
1990 and 2021, respectively, and an average share value of 9.9% for the reporting period, 1990-2021.
Nitrous Oxide Generation
Production of N2O reported in the manure management category occurs during storage and treatment
of manure before it is applied to land.
N2O emissions contributed 5 155 kt CO2 eq. (56.4% of the manure management category) which
represented 7.2% of agricultural emissions in 2021 whereas the respective share in 1990 was 6.7%,
less than the current percentage of 2021.
With respect to all N2O emissions of the agriculture sector, the second highest N2O emission source
category was manure management after agricultural soils category for all reporting years. N2O emissions
of manure management accounted for 15.1% and 16.4% of all N2O emissions in the agriculture sector
in 1990 and 2021, respectively.
Direct N2O emissions from MMS can occur via combined nitrification (under aerobic conditions) and
denitrification (an anaerobic process) of nitrogen contained in the manure. The emission of N2O from
manure during storage and treatment depends on the nitrogen and carbon content of manure, on the
duration of the storage and type of treatment.
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Indirect N2O emissions result from volatile nitrogen losses that occur primarily in the forms of ammonia
and NOx. Indirect emissions occur from the deposition of volatilized nitrogen from manure management
systems and via runoff and leaching of nitrogen into soils.
The following figure on CH4 and N2O emissions of manure management and the agriculture sector gives
a view on tendencies. As indicated above, CH4 and N2O from manure management are only a fraction
of total CH4 and N2O emissions from the agriculture sector (10.1% and 16.4%, respectively) and
therefore these are not a key driver in the overall trends in the agriculture sector. However, the trends
for these gases in this category generally reflect the overall trend of the same gases in the agriculture
sector. Figure 5.8 shows a trend comparison of these two gas emissions.
Figure 5.8 Comparing CH4 and N2O emission trends, 1990‒2021
45 000
(kt CO2 eq.)
40 000
35 000
30 000
25 000
20 000
15 000
10 000
CH₄ Manure Management
N₂O Manure Management
CH₄ Agriculture Total
N₂O Agriculture Total
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
5 000
Typical animal mass values, Nrates and Nitrogen excretion rates (Nex) are crucial parameters in
estimating emissions from manure management. Table 5.15 and Table 5.16 present these values for
animal categories for the entire reporting period 1990-2021.
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Table 5.15 Typical animal mass, Nrate and Nex values for cattle and poultry, 1990‒2021
Year
Mass
(kg)
Dairy Cattle
Non-dairy Cattle
Nratea
Nexb
Mass
Nratea
Nexb
Mass
(kg)
(kg)
Poultry
Nratea
Nexb
1990
350.4
0.47
60.38
180.6
0.34
22.41
2.22
0.81
0.65
1995
377.4
0.47
65.12
192.3
0.34
23.87
2.14
0.81
0.63
2000
389.0
0.47
67.15
194.5
0.34
24.14
2.02
0.81
0.60
2005
404.1
0.47
69.79
253.9
0.34
31.51
2.18
0.81
0.65
2010
440.9
0.47
76.25
279.2
0.34
34.64
2.28
0.81
0.68
2011
446.8
0.47
77.27
281.2
0.34
34.90
2.30
0.82
0.68
2012
451.5
0.47
78.10
287.5
0.34
35.67
2.29
0.82
0.68
2013
454.6
0.47
78.64
289.0
0.34
35.87
2.30
0.82
0.68
2014
461.0
0.47
79.77
293.6
0.34
36.43
2.30
0.82
0.68
2015
464.2
0.47
80.33
296.4
0.34
36.79
2.28
0.82
0.68
2016
467.9
0.47
80.97
297.6
0.34
36.93
2.28
0.82
0.68
2017
474.1
0.47
82.06
296.4
0.34
36.78
2.29
0.81
0.68
2018
476.4
0.47
82.47
300.1
0.34
37.24
2.32
0.81
0.69
2019
475.9
0.47
82.37
300.1
0.34
37.25
2.34
0.81
0.70
2020
477.7
0.47
82.69
304.5
0.34
37.79
2.36
0.81
0.70
2021
478.9
0.47
82.90
305.2
0.34
37.87
2.36
0.81
0.70
All mass values are live weight figures and these figures are country-specific. Country-specific figures for cattle are gathered from a variety of
sources including the Ministry for Agriculture and Forestry and TurkStat data. Country-specific poultry mass data ara gathered from the Ministry for
Agriculture and Forestry.
a
Unit for Nrate is kg N/ (1000 kg animal mass × day).
b
Unit for Nex is kg N/ (head × yr).
Table 5.16 Typical animal mass, Nrate and Nex values for some livestock species
Mass
Nrateb
Nex
Years
Livestock species
1990 ‒ 2021
Sheep (domestic)
1990 ‒ 2021
1990 ‒ 2021
1990 ‒ 2021
Buffalo
380
0.32
44.38
1990 ‒ 2021
Horses
238
0.46
39.96
1990 ‒ 2021
Mules & Asses
130
0.46
21.83
1990 ‒ 2021
Swinea
28
0.402
4.11
1990 ‒ 2021
Camels
217
0.46
36.43
(kg)
(kg N/head/yr)
50
1.17
21.35
Sheep (merino)
60
1.01
22.12
Goats
45
1.37
22.50
All mass figures are live weight figures. Mass values given for sheep (domestic and merino) and goats were country-specific values. Mass values
given for buffalo, horses, swine, camels, and mules & asses were all default values presented in the 2006 IPCC Guidelines Vol.4.
a
According to the footnote given on page 10.59, Table 10.19 of the 2006 IPCC Guidelines Vol.4 Chapter 10, nitrogen excretion for swine is based
on an estimated country population of 90% market swine and 10% breeding swine. Thus, the Nrate is calculated as given and used in the related
Nex calculation: (90% × 0.42)+(10% × 0.24)=0.402 (Nrate value for swine).
b
Unit for Nrate is kg N/ (1000 kg animal mass × day).
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Methodological Issues:
Türkiye applies T1 method according to the 2006 IPCC Guidelines to estimate methane and nitrous
oxide emissions from manure management for all livestock types. CH4 and N2O emissions from manure
management are key category according to level assessment.
The annual population for each livestock category is included in Table 5.6 above. The AD (the population
of animals) provider is TurkStat livestock statistics for the entire time series 1990-2021. TurkStat collects
livestock data as explained in the Sector Overview. In addition, our country uses the national animal
population numbers and allocates the population for each animal subcategory into cool, temperate and
warm climate regions in the following manner. First, the animal population numbers are listed according
to their respective provinces in our country. Second, all provinces are allocated to one of the three
mentioned climate regions concerning their yearly average temperature values. Finally, all population
numbers of each animal subcategory within each of the climate regions, namely cool, temperate and
warm, are added up before calculating the weighted average with respect to population numbers of the
total animal subcategory.
The CH4 EFs are default IPCC T1 factors except for cattle. In Türkiye, there are three dairy cattle types
categorized as culture cattle, hybrid cattle and domestic cattle. For 2021, the average milk production
of culture cattle is around 3 862 kg head-1 yr-1. Hence, the EF for culture cattle is taken as the average
of EFs of Western Europe and Asia with respect to milk yield of these cattle, and the mean of milk
production of Western Europe (6 000 kg head-1 yr-1) and Asia (1 650 kg head-1 yr-1) is 3 825 kg head-1
yr-1. In a similar manner, domestic cattle's EF was taken as Asia EF, and hybrid cattle's EF is taken as
the average of culture and domestic cattle EF. The average milk production of domestic cattle is 1 303
kg head-1 yr-1 and this value is closer to the Asia average milk production value of 1 650 kg head-1 yr-1.
The average milk production of Hybrid cattle is 2 723 kg head-1 yr-1 and this value is close to the mean
of 3 825 and 1 650 kg head-1 yr-1 which is 2 737 kg head-1 yr-1. Furthermore, domestic dairy cattle have
almost similar properties with Asian cattle like milk yield. Since the T1 method regarding cattle still
applies for agricultural categories other than enteric fermentation, the explanation given is still valid for
other agricultural categories like manure management.
In order to select appropriate EFs, animal population data, collected from TurkStat databases, are
categorized according to their provinces with respective annual temperature figures. CH4 and N2O
emission factors are default 2006 IPCC T1 factors.
The annual average temperatures of the provinces are taken into account in order to select the EFs for
manure management. All temperature data are taken directly from the General Directorate of
Meteorology. Table 5.17 presents default EFs based on the 2006 IPCC Guidelines for National
Greenhouse Gas Inventories Vol.4 for cattle types and swine for each region according to temperature
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classification. Considering annual average air temperature, provinces are categorized between cool (0oC
- 14oC) and temperate (15oC - 25oC) climate region. Similar to the methods applied in enteric
fermentation, the IPCC default emission factors selected for cattle were based on the IPCC default
factors for Western Europe and Asia (see Table 10.14, Vol.4 of the 2006 IPCC Guidelines). The EF for
domestic cattle and non-dairy cattle were assumed to be similar with cattle in Asia because their milk
yield values were similar for the former and the weight figures were similar for the latter. The EF for
culture cattle was estimated as the mean of the emission factors for dairy cattle from Western Europe
and Asia, for the same temperature zone (e.g., at <10o C Türkiye estimates that culture cattle have an
EF of 15 kg CH4/head/year, which is the average of 21 kg CH4/head/year and 9 kg CH4/head/year from
Western Europe and Asia, respectively). The EF for hybrid cattle is the mean of domestic and culture
cattle.
For swine, the EFs for Asia from the 2006 IPCC Guidelines (Table 10.14 of Volume 4, Chapter 10) were
selected, because of similar body weights.
The EFs for sheep and other livestock, shown in the 2006 IPCC Guidelines, are also broken into two
climate regions and shown in Table 5.18. Türkiye does not have a province with an annual average
temperature above 25°C; therefore, the warm climate region does not exist in the country.
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Table 5.17 Manure management CH4 emission factors for cattle and swine
(kg CH4/head/year)
Cool EF (< 15 °C)
Temperate EF (15-25 °C)
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Dairy Cattle
(Culture)
15.0
16.5
17.5
19.0
20.5
23.5
25.5
27.5
29.5
32.0
34.5
37.5
40.0
43.5
47.0
50.5
Dairy Cattle
(Hybrid)
12.0
13.3
13.8
15.0
16.3
18.3
19.8
21.3
22.8
24.5
26.3
28.8
30.5
33.3
35.5
38.3
Dairy Cattle
(Domestic)
9
10
10
11
12
13
14
15
16
17
18
20
21
23
24
26
Non-Dairy
Cattle
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
3. Swine
2
2
2
2
2
3
3
3
3
4
4
4
5
5
5
6
1. Cattle
Table 5.18 Manure management CH4 emission factors for sheep and other livestock
(kg CH4/head/year)
Cool EF (< 15 °C)
Temperate EF (15-25 °C)
2. Sheep
Sheep (Domestic)
0.100
0.150
Sheep (Merino)
0.145
0.215
Buffalo
1.00
2.00
Camels
1.28
1.92
Goats
0.11
0.17
Horses
1.09
1.64
Mules and asses
0.60
0.90
Poultry
0.01
0.02
4. Other livestock
Furthermore, Table 5.19 presents the Manure Management System (MMS) used according to countryspecific values. These figures are able to reflect Türkiye's conditions in an improved way leading to
improved emission estimations. Note also that 50% of burned manure is reported under the Energy
sector category 1.A.4.b – fuel combustion activities (residential), while the remaining 50% is calculated
and reported under pasture, range and paddock according to the rules given under section 10.5.2 of
the 2006 IPCC Guidelines, Vol.4.
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Table 5.19 Manure Management System Distribution, 1990‒2021
(%)
MS
Dairy Cattle
(Culture)
Dairy Cattle
(Hybrid)
Dairy Cattle
(Domestic)
Non-Dairy
Cattle
Liquid
system
Solid storage
Dry lot
Pasture, range
and paddock
Burned for fuel
or as waste
10.0
50.0
6.0
30.0
4.0
10.0
50.0
6.0
30.0
4.0
10.0
50.0
6.0
30.0
4.0
10.0
50.0
6.0
30.0
4.0
96.0
4.0
Swine
Sheep
(Domestic)
Sheep
(Merino)
40.0
60.0
40.0
60.0
Buffalo
60.0
Camels
40.0
Horses
25.0
15.0
60.0
Goats
Mules and
Asses
10.0
10.0
80.0
25.0
15.0
60.0
6.0
30.0
Poultry
manure
4.0
60.0
Chickens
20.0
Ducks & Geese
100.0
Turkeys
20.0
80.0
80.0
Note that "Other" shown in the CRF Tables relates entirely to poultry manure. Anaerobic lagoon, daily spread, composting and digesters (four
different MMS types) were considered as either not occurring or negligible. Definite data on MMS are not available and the table was prepared in
order to serve the estimations for CRF 3.B source category based on a variety of data sources.
Uncertainties and Time-Series Consistency:
The approach to produce quantitative uncertainty estimates was used as described in the 2006 IPCC
Guidelines for determining uncertainties of that category in total emissions.
The AD for this sector are gathered from agricultural statistics of TurkStat. Uncertainties for activity data
are determined by TurkStat experts and uncertainty values for EFs are taken from the IPCC Guidelines.
The calculated AD uncertainty figure is 14.1% both for CH4 and N2O gases whereas EF uncertainty
values are 30% and 50% for CH4 and N2O gases, respectively, as presented in the 2006 IPCC Guidelines.
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Source category
3.B
Gas
CH4, N2O
Comments on time series consistency
CH4 EFs are selected according to the yearly mean temperature
values of the 81 provinces. N2O EFs are mainly constant over
the entire time series except for cattle (dairy & other) and
poultry which reflect the weighted average of their
subcategories over the reporting period.
Source-Specific QA/QC and Verification:
The 2006 IPCC Guidelines were used for the QA/QC procedures of National GHG emission inventory. A
National Inventory System QA/QC Plan prepared by TurkStat is also a significant tool for implementing
QA/QC principles for the Inventory. AD for this source category are gathered mainly from the Agricultural
Statistics Department of TurkStat. The respective AD, used for calculations, are also published as official
statistics by TurkStat which have their own QA/QC procedures. Emission trends are analyzed. If there
is a high fluctuation in the series, then AD and emission calculation are re-examined. Moreover, a QA
work was conducted by a Project Engineer from CITEPA for this category in January 2020.
Recalculation:
There was no recalculation exercised regarding emission estimates from this source category in this
submission.
Planned Improvement:
All data and methodologies are kept under review and an upgrade from T1 to T2 will be considered for
the future.
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5.4. Rice Cultivation (Category 3.C)
Source Category Description:
GHG emissions from rice production are the result of the CH4 gas released by anaerobic digestion of
organic substances in the paddy fields. The aforementioned CH4 gas emissions are calculated according
to the approach shown in the 2006 IPCC Guidelines which are estimated by IPCC's default emission
factors. The annual amount of CH4 emitted from a given area of rice is a function of the number and
duration of crops grown, water regimes before and during the cultivation period, and organic and
inorganic soil amendments. Soil type, temperature, fertilizer application, rice cultivar also affect CH4
emissions. CH4 emissions from rice cultivation are not a key category. Figure 5.9 presents total annual
harvested area in hectare (line drawn in blue - left axis) and total CH4 emissions emitted in kt (line
drawn in dark red - right axis) for rice cultivation covering the period 1990-2021.
Figure 5.9 Harvested area and emitted CH4 for rice cultivation, 1990‒2021
140 000
(Harvested area, ha)
(CH4, kt)
120 000
12
10
100 000
8
80 000
6
60 000
4
40 000
2
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
20 000
0
Rice cultivation contributed 10.77 kt CH4 (269.3 kt CO2 eq.) emissions or 0.37% of total agricultural
emissions in 2021 whereas the respected value for the year 1990 was around 4 kt CH4 (100.1 kt CO2
eq.) emissions or 0.22% of total sector emissions.
Overall, emissions from rice cultivation increased by 169.2 kt CO2 eq. (169.1%) for the entire reporting
period and the increase was calculated around 32% between the years 2011 and 2021.
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Agriculture
Table 5.20, given below, presents the activity data and estimated emissions of this source category in
detail.
Table 5.20 Irrigated area and estimated emissions for rice cultivation, 1990‒2021
Continuously
Flooded
Total
Single Aeration
Multiple Aeration
(kt CO2 eq.)
(kt CO2 eq.)
Year
(kt CO2 eq.)
Area (ha)
(kt CO2 eq.)
1990
100.08
46 348
51.84
17 276
16.08
8 693
32.16
20 379
1995
112.51
49 955
62.85
21 203
16.71
8 434
32.95
20 318
2000
127.96
57 859
71.20
24 800
20.42
10 694
36.35
22 365
2005
182.98
84 909
96.05
32 926
35.04
18 949
51.89
33 034
2010
201.88
98 966
86.23
29 856
39.80
21 900
75.86
47 210
2011
204.08
99 383
93.73
32 456
38.95
21 449
71.40
45 479
2012
248.91
119 664
120.32
41 613
44.29
24 647
84.30
53 405
2013
230.53
110 592
111.64
38 670
41.45
23 018
77.44
48 905
2014
229.37
108 649
114.59
39 628
45.20
25 395
69.59
43 626
2015
239.85
115 856
115.71
40 057
41.58
23 355
82.56
52 444
2016
242.83
116 056
120.66
41 763
42.80
23 912
79.38
50 381
2017
233.65
109 505
121.81
42 153
42.60
23 778
69.24
43 575
2018
252.22
120 137
125.12
43 178
45.84
25 606
81.26
51 353
2019
262.86
126 419
127.74
44 053
45.94
25 817
89.17
56 549
2020
261.53
125 398
127.58
43 942
47.08
26 551
86.87
54 905
2021
269.33
129 475
130.04
44 740
48.38
27 206
90.91
57 530
Area (ha)
Figures in the table may not add up to the totals due to rounding.
268
Intermittently Flooded
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Area (ha)
Area (ha)
268
Agriculture
Methodological Issues:
Harvested area data for rice cultivation are taken from TurkStat agricultural statistics and area records
are available for all districts of Türkiye since 1990. T1 method is used for calculation, and the emission
factor and scaling factors are taken from the 2006 IPCC Guidelines. The cultivation period of rice
production in Türkiye is around 130 days. The methods mainly used in our country includes continuously
flooded, intermittently flooded with single aeration and intermittently flooded with multiple aeration.
Accordingly, disaggregated case parameters are used for these methods from the 2006 IPCC Guidelines.
Initially, the required data are gathered from TurkStat's regional offices. Mainly based on these data, in
addition to data received from the Ministry of Agriculture and Forestry, values of scaling factors
according to the 2006 IPCC Guidelines are determined for both SFw and SFp parameters. Due to the
large geographical diversity of our country, all values for disaggregated scaling factors are used.
Moreover, information on cultivation period for rice production is also obtained from regional offices of
TurkStat and all different periods are taken into account. The default CH4 baseline emission factor (EFc)
applied is 1.30 CH4/ha/day for rice cultivation emission calculations, a non-key category, under T1
method. Organic amendments are not used or, if any, used in negligible amounts. This, in turn, reduces
the value of the related scaling factor (SFo) to 1, a multiplicative identity, given by Equation 5.3 on
page 5.50 of the 2006 IPCC Guidelines Vol.4. Furthermore, scaling factors (SFs,r) for other related
variables are not available, and as a result not used, which is in line with the information provided on
page 5.48 presented in the 2006 IPCC Guidelines Vol.4. Accordingly, emissions from this source category
are calculated and reported taking into account the country-specific conditions.
Uncertainties and Time-Series Consistency:
The AD for this sector are gathered from agricultural statistics of TurkStat, and the information about
water regime, water regime prior to rice cultivation and cultivation periods, which are crucial in
determining appropriate scaling factors, are obtained from regional offices of TurkStat for all provinces
and their districts in Türkiye. The AD for this sector are gathered from agricultural statistics of TurkStat
and the related AD uncertainty figure is considered to be 5%. Uncertainty value for the EF is calculated
as 76.73% according to the information shown in the 2006 IPCC Guidelines.
An Approach 2 uncertainty analysis using the Monte Carlo technique was carried out on the methodology
used to estimate emissions of methane from rice cultivation category. The Monte Carlo uncertainty
range for CH4 emissions from rice cultivation is similar to Approach 1, the error propagation method and
mean estimates of combined MC simulation uncertainty were between -68.98% and +70.43% in 2017.
For more detailed information about Monte Carlo method, refer to the uncertainty section in the
annexes.
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Agriculture
Source category
3.C
Gas
Comments on time series consistency
CH4
EFs reflect the subcategories of the methods applied for rice
cultivation. The calculations reflect different types of water
regimes applied in the country. A list of EFs and related
parameters used for emission calculations are listed in Annex 3
of the National Inventory Report.
Source-Specific QA/QC and Verification:
The 2006 IPCC Guidelines were used for the QA/QC procedures of National GHG emission inventory. A
National Inventory System QA/QC Plan prepared by TurkStat is also a significant tool for implementing
QA/QC principles for the Inventory. AD for this source category are mainly gathered from the Agricultural
Statistics Department of TurkStat. The respective AD, used for calculations, are also published as official
statistics by TurkStat which have their own QA/QC procedures. Emission trends are analyzed. Moreover,
a QA work was conducted by a Project Engineer from CITEPA for this category in January 2020.
Recalculation:
There was no recalculation exercised regarding emission estimates from this source category in this
submission.
Planned Improvement:
All data and methodologies are kept under review. There are no further planned improvements in this
source category.
270
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270
Agriculture
5.5. Agricultural Soils (Category 3.D)
Source Category Description:
This source, which is a key category, contains N2O emissions from synthetic fertilizers, organic fertilizers
and crop residues. In this section N2O emissions from pasture, range and paddock manure, cultivation
of organic soils, and indirect emissions, which consist of atmospheric deposition and nitrogen leaching
and run-off, are estimated too. The complete time series regarding emissions are submitted in this
submission. Both direct and indirect N2O emissions from this source category are key categories
according to the level and trend assessment (with and without LULUCF).
Agriculture soils produced 88.1 kt N2O (26.2 Mt CO2 eq.) emissions in 2021 and agriculture soils is the
largest source category of N2O emissions in Türkiye. This figure represented 83.5% of N2O emissions
in the Agriculture sector, around 65.1% of Türkiye’s N2O emissions (without LULUCF), and close to 37%
of agricultural emissions. Emissions were 8 935 kt CO2 eq. (51.6%) above the 1990 level of 17 314 kt
CO2 eq. in 2021 - the latest reporting year. Direct N2O emissions increased by 8 050 kt CO2 eq. (53%)
whereas indirect N2O emissions increased by 885 kt CO2 eq. (41.4%) for the given period 1990-2021.
The increase is a result of the emission changes of direct and indirect N2O emissions from managed
soils. The total change of direct N2O emissions is a result of increases in the subcategories inorganic N
fertilizers, a subcategory of organic N fertilizers, urine and dung deposited by grazing animals, crop
residues, and also decreases in cultivation of organic soils and two subcategories of organic N fertilizers.
Direct N2O emissions due to mineralization/immobilization related to loss/gain of soil organic carbon in
the agriculture sector did not occur for the entire reporting period.
Several subcategories contribute to emissions from agricultural soils from direct and indirect pathways
(Tables 5.21 – 5.24). Direct N2O emissions occur directly from the soils to which N has been added or
released; indirect emissions arise from volatilization (evaporation or sublimation) and subsequent
redeposition of NH3 or NOx or result from leaching and runoff of soil N within water (IPCC, 2006). A
precise overview is also presented in Figure 5.10 and Table 5.21 for direct and indirect N2O emissions.
The abbreviations used in this figure are listed on the headings of Tables 5.22 and 5.24.
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Agriculture
Figure 5.10 Sub-categories of Agricultural Soils Emission Sources, 2021
FOS
0.3%
N2O(ATD)
10.6%
FCR
12.6%
FSN
31.9%
FPRP
27.7%
272
N2O(L)
0.9%
FON
16%
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272
Agriculture
Table 5.21 Overview of N2O emissions from managed soils, 1990‒2021
Agricultural soils
Year
Agriculture
Total
Total
Direct N2O
Indirect N2O
(kt CO2 eq.)
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
(kt CO2 eq.)
(%)
1990
46 054
17 314
37.6
15 176
33.0
2 138
4.6
1995
44 080
15 871
36.0
13 951
31.6
1 920
4.4
2000
42 332
16 870
39.9
14 925
35.3
1 946
4.6
2005
42 439
16 880
39.8
14 996
35.3
1 883
4.4
2010
44 409
17 006
38.3
15 153
34.1
1 853
4.2
2011
46 901
17 421
37.1
15 506
33.1
1 915
4.1
2012
52 662
19 334
36.7
17 184
32.6
2 150
4.1
2013
55 858
20 905
37.4
18 590
33.3
2 314
4.1
2014
56 219
20 764
36.9
18 425
32.8
2 340
4.2
2015
56 133
21 006
37.4
18 656
33.2
2 350
4.2
2016
58 894
23 147
39.3
20 587
35.0
2 560
4.3
2017
63 262
23 607
37.3
20 977
33.2
2 631
4.2
2018
65 338
23 022
35.2
20 424
31.3
2 598
4.0
2019
68 022
24 342
35.8
21 593
31.7
2 749
4.0
2020
73 154
27 389
37.4
24 297
33.2
3 092
4.2
2021
72 075
26 249
36.4
23 226
32.2
3 023
4.2
Figures in the table may not add up to the totals due to rounding.
Table 5.22 Categories of Direct N2O emissions of agricultural soils, 1990‒2021
(kt CO2 eq.)
Direct N2O Emissions from Managed Soils
Year
Total
N2O
Emissions
from
Managed
Soils
Total
Inorganic
N
Fertilizers
(FSN)
Organic N
Fertilizers
(FON)
Urine and
Dung
Deposited
by Grazing
Animals
(FPRP)
1990
17 314
1995
Crop
Residues
(FCR)
Loss/
Gain of
soil
organic
matter
(FSOM)
Cultivation
of
Organic
Soils
(FOS)
15 176
5 618
2 773
5 118
1 585
NO
82
15 871
13 951
4 934
2 609
4 690
1 635
NO
82
2000
16 870
14 925
6 456
2 433
4 183
1 771
NO
82
2005
16 880
14 996
6 427
2 360
3 994
2 134
NO
82
2010
17 006
15 153
6 292
2 351
4 001
2 427
NO
82
2011
17 421
15 506
5 897
2 555
4 382
2 589
NO
82
2012
19 334
17 184
6 706
2 857
4 916
2 625
NO
82
2013
20 905
18 590
7 419
3 008
5 208
2 874
NO
82
2014
20 764
18 425
6 991
3 128
5 465
2 759
NO
82
2015
21 006
18 656
6 961
3 150
5 497
2 965
NO
82
2016
23 147
20 587
8 881
3 156
5 493
2 976
NO
82
2017
23 607
20 977
8 264
3 463
5 993
3 175
NO
82
2018
23 022
20 424
7 153
3 667
6 326
3 195
NO
82
2019
24 342
21 593
7 879
3 800
6 569
3 263
NO
82
2020
27 389
24 297
9 612
4 077
7 061
3 463
NO
82
2021
26 249
23 226
8 370
4 198
7 282
3 295
NO
82
FSOM refers to mineralization/immobilization associated with loss/gain of soil organic matter and related activity data are taken from CRF Table 4.B.
The notation key NO was used for FSOM for the entire reporting period because the related activity data do not show a carbon loss from cropland
remaining cropland. Activity data (Area of organic soils) required for the calculation of emissions from FOS are taken from the data available in CRF
Table 4.B and CRF Table 4.C. Figures in the table may not add up to the totals due to rounding.
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Agriculture
Table 5.23 Subcategories of Organic N fertilizers emissions, 1990‒2021
(kt CO2 eq.)
Year
Total N2O
Emissions
from
Managed
Soils
Total
Direct
N2O
Emissions
from
Managed
Soils
1990
17 314
1995
15 871
2000
Organic N Fertilizers (FON)
Organic N
Fertilizers
(FON)
Animal
Manure
Applied
to Soils
Sewage
Sludge
Applied
to Soils
Other
Organic
Fertilizers
Applied to
Soils
15 176
2 773
2 769
3
1
13 951
2 609
2 605
3
1
16 870
14 925
2 433
2 419
12
2
2005
16 880
14 996
2 360
2 348
11
1
2010
17 006
15 153
2 351
2 347
3
1
2011
17 421
15 506
2 555
2 551
3
1
2012
19 334
17 184
2 857
2 853
3
1
2013
20 905
18 590
3 008
3 004
3
1
2014
20 764
18 425
3 128
3 125
2
1
2015
21 006
18 656
3 150
3 147
2
1
2016
23 147
20 587
3 156
3 153
2
1
2017
23 607
20 977
3 463
3 460
2
1
2018
23 022
20 424
3 667
3 663
2
2
2019
24 342
21 593
3 800
3 797
2
1
2020
27 389
24 297
4 077
4 075
1
2
2021
26 249
23 226
4 198
4 193
2
3
Other organic fertilizers applied to soils consist only of compost applied to soils. There is no data available and no indication
for the use of other organic fertilizers other except compost. Figures in the table may not add up to the totals due to rounding.
Table 5.24 Categories of Indirect N2O emissions of agricultural soils, 1990‒2021
(kt CO2 eq.)
Indirect N2O Emissions from Managed Soils
Year
Total N2O
Emissions
from
Managed
Soils
1990
17 314
1995
2000
Total
Atmospheric
Deposition
N2O(ATD)
Nitrogen
Leaching and
Run-off
N2O(L)
2 138
1 977
161
15 871
1 920
1 774
146
16 870
1 946
1 789
157
2005
16 880
1 883
1 726
157
2010
17 006
1 853
1 695
158
2011
17 421
1 915
1 754
161
2012
19 334
2 150
1 972
178
2013
20 905
2 314
2 121
193
2014
20 764
2 340
2 148
191
2015
21 006
2 350
2 156
194
2016
23 147
2 560
2 345
215
2017
23 607
2 631
2 413
218
2018
23 022
2 598
2 387
211
2019
24 342
2 749
2 526
223
2020
27 389
3 092
2 839
253
2021
26 249
3 023
2 782
241
Figures in the table may not add up to the totals due to rounding.
274
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274
Agriculture
Direct N2O emissions from agricultural soils are a result of addition of nitrogen in the form of inorganic
nitrogen fertilizers, organic nitrogen fertilizers (predominantly in the form of animal manure), inputs
from above-ground and below-ground crop residues and from forages during pasture renewal,
mineralization of cropland soil organic matter loss, urine and dung deposited by grazing animals, and
cultivation of organic soils. These combined direct N2O soil emissions contributed 23 226 kt CO2 eq.
(88.5%) to emissions from the Agricultural soils category and around 32% of emissions under the total
Agriculture sector in 2021. This is an increase of 8 050 kt CO2 eq. (53%) from the 1990 reported figure
of 15 176 kt CO2 eq.
A major direct source of N2O emissions from agricultural soils is an outcome of the use of synthetic
fertilizer. Around thirty-four per cent (34.2%) of increase in direct emissions from agricultural soils,
observed between 1990 and 2021, is a result of an increase in synthetic fertilizers application.
Widespread increase in the use of such nitrogen-based fertilizers has been driven by the need for greater
crop yields and more intensive farming practices. In 2021, N2O emissions from synthetic nitrogen
fertilizers contributed 8 370 kt CO2 eq. (31.9%) to emissions from the managed soils category. This is
an increase of 2 752 kt CO2 eq. (49%) from the 1990 level of 5 618 kt CO2 eq. Nitrogen emissions of
synthetic fertilizer contributed 11.6% to the total emissions under the agriculture sector for the latest
reported year.
In 2021, N2O emissions from organic N fertilizers contributed 4 198 kt CO2 eq. (16%) to emissions from
the agricultural soils category and 5.8% of emissions under the total agriculture sector. Activity data (as
dry matter) for sewage sludge and compost are both received within TurkStat. The country-specific
nitrogen content value for sewage sludge is taken as 5.15% calculated as an average according to the
values presented in a specific research study (Topaç and Başkaya, 2008), while the nitrogen content
for compost is taken as 1%. The only source of emissions due to other organic fertilizers is compost
because there are neither activity data available on possibly other organic fertilizers except for compost
data nor an indication of such an activity.
An increase of 1 424 kt CO2 eq. (51.4%) is observed from the 1990 level of 2 773 kt CO2 eq. of N2O
emissions due to organic nitrogen fertilisers of which sewage sludge applied to soils marks a slightly
peculiar trend observable on Table 5.23. Since Türkiye applied the Tier 1 methodology, emissions are
directly linked to activity data changes. In the initial years, the number of municipal wastewater
treatment plants increased in our country leading to an increase in emissions thereof. Thereafter, three
factors could be given which resulted in a reduction of these emissions: First, increase in number of
landfilling sites affected the trend in sewage sludge applied to soils. Second, new legislations which set
criteria on sewage sludge for its use on agricultural soils limited the use of sewage sludge on soils.
Third, some wastewater treatment plants using sewage sludge extensively before, changing their
treatment methods.
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Agriculture
As observed from Table 5.22, N2O emissions from urine and dung deposited by grazing animals
contributed 7 282 kt CO2 eq. (28%) to emissions from the agricultural soils category and 10.1% of
emissions under the total agriculture sector in 2021. This is an increase of 2 164 kt CO2 eq. (42.3%)
from the 1990 level of 5 118 kt CO2 eq. Moreover, N2O emissions from crop residues contributed 3 295
kt CO2 eq. (12.6%) to emissions from the agricultural soils category and 4.6% of emissions under the
total agriculture sector. This is a value of more than twofold presenting an increase of 1 710 kt CO2 eq.
(107.9%) from the 1990 level of 1 585 kt CO2 eq.
Emission calculations from cultivation of organic soils are directly based on related LULUCF sector data
entered into CRF Tables 4.B and 4.C while the related activity data source is the new LULUCF reporting
system (LRS) in Türkiye for which further information is presented in the LULUCF sector overview
section.
Indirect N2O emissions were calculated as 3 023 kt CO2 eq. for 2021. Indirect N2O emissions through
atmospheric deposition amounted to 2 782 kt CO2 eq. (10.6%) from the agricultural soils category and
3.9% of emissions under the entire agriculture sector for 2021. This is an increase of 805 kt CO2 eq.
(40.7%) from the 1990 level of 1 977 kt CO2 eq. Indirect N2O emissions through leaching and runoff
added 241 kt CO2 eq. (0.9%) to emissions from the agricultural soils category in 2021 and 0.3% of
emissions under the total agriculture sector.
Briefly, agricultural soils emissions have increased by nearly 51.6% (around 9 Mt CO2 eq.) between
1990 and 2021. The increase is a result of the emission changes of direct and indirect N2O emissions
from managed soils. The former, direct N2O emissions increased by around 8 Mt CO2 eq. and the latter,
indirect N2O emissions, by 1 Mt CO2 eq. for the given period, 1990-2021. The total net increase of 8 Mt
CO2 eq. of direct N2O emissions is a result of changes in inorganic N fertilizers, organic N fertilizers,
urine and dung deposited by grazing animals, crop residues subcategories. The related figures of
changes for 1990-2021 concerning these five subcategories mentioned are 2 752 kt (49%), 1 424 kt
(51.4%), 2 164 kt (42.3%), and 1 710 kt (107.9%), respectively. Estimations from cultivation of organic
soils are constant at 82 kt CO2 eq. Organic N fertilizers are further subdivided into three groups, namely
animal manure, sewage sludge, and other organic fertilizers (which consists entirely of compost), all
applied to soils. The increase in animal manure applied to soils is 1 424 kt (51.4%) from 2 769 kt to 4
193 kt whereas the two other organic N fertilizer subcategories decreased as presented in Table 5.23.
On the other hand, the total increase of 1 Mt CO2 eq. of indirect N2O emissions is divided into two
categories, atmospheric deposition and nitrogen leaching and run-off. The related figures of changes
for these subcategories are 805 kt (40.7%) and 80 kt (49.8%) for the period of 1990-2021, respectively.
276
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Agriculture
Methodological Issues:
N2O emissions are calculated by using the IPCC T1 approach. The AD used in emission calculations are
taken from agricultural statistics of TurkStat. The N2O EFs are IPCC T1 default factors.
When a crop is harvested, a portion of the crop is left in the field to decompose. The remaining plant
matter is a nitrogen source that undergoes nitrification and denitrification and can thus contribute to
N2O production. Crop residue emission calculations follow the principles shown in the 2006 IPCC
Guidelines. N2O emissions are now calculated according to all cultivated plants in Türkiye. Both
aboveground and belowground crop residues are included. Crop yields vary from year to year, as well
as cultivated areas, which cause fluctuations in crop residue emissions. It should be further added that
the default EF used for crop residues is 0.01 (kg N2O–N)/(kg N) except for the EF used for flooded rice
which is 0.003 (kg N2O–N)/(kg N). This difference in EFs used in calculations for crop residues emissions
is the reason which leads to inconstant implied emission factors over the reporting period. The following
table summarizes the crop headings for which N2O emissions due to crop residues are calculated in our
country.
Table 5.25 Crop data used for crop residue calculations
Major Crop Types
Individual Crops
Grains
Beans & Pulses
Tubers
Root crops, other
Maize
Sorghum
Wheat
Soybean
Rice
Dry bean
Barley
Potato
N-fixing forages
Oats
Peanut
Non-N-fixing forages
Millet
Alfalfa
Grass-clover mixtures
Source category
3.D.1
Rye
Gas
N2O
Comments on time series consistency
All EFs are constant over the entire time series for FSN, FOS and all subcategories of FON . The same EF for FCR is used except for flooded rice and
the EF for FPRP is chosen according to livestock species.
In the 2016 Assessment Review Report of Türkiye, published on 24 April 2017, a recommendation was
made by the Expert Review Team to investigate the actual leaching conditions in Türkiye and estimate
the most likely FracLEACH-(H) for its national conditions and include justification of the FracLEACH-(H) value
used in its NIR. The ERT also noted that taking into account the dry conditions in Türkiye and the use
of a FracLEACH-(H) of 0.3, a likely overestimation is taking place. To address this recommendation and use
a more precise FracLEACH-(H) value this issue was evaluated. As a result, a revised country-specific
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Agriculture
FracLEACH-(H) value of 0.015 is calculated and used with respect to the footnote of Table 11.3 shown in
the 2006 IPCC Guidelines Volume 4. While calculating this parameter, following steps are implemented:
First, the Climate Map (Figure 5.11) was used as a reference data source while keeping in mind that in
this data source, the entire 12 months in a year (including also the dry months of June, July and August)
are taken into account, not 9 months as mentioned in the footnote of Table 11.3 shown in the 2006
IPCC Guidelines Vol.4. Secondly, soil water-holding capacity is assumed to be zero as a conservative
approach. In other words, if rainfall exceeds the potential evapotranspiration then it is assumed that
surface runoff or leaching occurs. In general conditions, there is a soil layer (shallow or deep) that hold
water and disable surface runoff but it is not possible to make an assessment on the water capacity of
soils for the whole country. Thirdly, it is assumed that leaching/run-off occurs in all wet areas shown in
the Climate Map but deos not occur in the dry areas of the country. Thus, a ratio between wet and dry
areas has been determined and multiplied by 0.3 to result in 0.015 as a FracLEACH-(H) value7. This newly
calculated value has been used since the submission of the 1990-2016 Inventory.
According to the 2006 IPCC Guidelines, a climate map of Türkiye (Figure 5.11) was prepared before
and this map was used to estimate a country-specific FracLEACH-(H) value. Four sub-climate types have
been identified based on the 2006 IPCC Guidelines that use basic climatic parameters of temperature,
potential evapotranspiration and precipitation. The Climate map given below is taken from the IPCC
Climate Zones which is also presented as Figure 3A.5.1 on page 3.38 of the 2006 IPCC Guidelines
Volume 4.
Figure 5.11 Climate Map of Türkiye
7
278
Please refer to section related to the agriculture sector of Annex 3 in this NIR for calculation details.
Turkish GHG Inventory Report 1990-2021
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Agriculture
Regarding emission calculations from crop residues, TurkStat received country-specific data on renewal
fractions and fractions removed from the MoAF. Renewal fraction for a yearly crop is 1 by definition of
1/X (where X is 1 year). This figure is used for most of the crops presented in the classification of Table
11.2 on pages 11.17-11.18 of the 2006 IPCC Guidelines Vol. 4 (since almost all crops are yearly crops).
A fraction of 0.25 (as a result of 1/X where X is 4 years) was used only for the following major crop
types and individual crops according to the information received from the Ministry of Agriculture and
Forestry: perennial grasses, grass-clover mixtures, alfalfa.
Fraction removed values are given for all major crop types and individual crops as received from the
Ministry of Agriculture and Forestry as follows: first for major crop types: grains (0.75), beans & pulses
(0.80), tubers (0.00), root crops and other (0.00), N-fixing forages (0.80), non-N-fixing forages (1.00),
perennial grasses (0.90), grass-clover mixtures (0.90); and second for Individual crop types: alfalfa
(0.90), maize, millet, soya bean and dry bean (0.80), wheat, rice, barley, oats, sorghum and rye (0.75),
peanuts (0.70); potato (0.00). The use of these data set helped in order to reflect the country-specific
conditions in an improved way. It should be further noted that default factor values shown in Table 11.2
of the 2006 IPCC Guidelines Vol.4 were used to calculate emissions from crop residues according to the
T1 method. Default factors used for FCR calculations include dry matter fraction of harvested product,
N-content of above-ground residues, ratio of below-ground residues to above-ground biomass, and N
content of below-ground residues. Additionally, default slope and intercept figures regarding aboveground residue dry matter from the same table are also used in the calculations.
Uncertainties and Time-Series Consistency:
The AD for this sector are gathered from agricultural statistics of TurkStat except for data on synthetic
fertilizer consumption amounts, which is obtained from the MoAF. By using Equation 3.1 and 3.2 in the
2006 IPCC Guidelines Vol. 1, uncertainties for the AD are calculated as 18.51% by TurkStat for N2O
Emissions from Managed Soils. In a similar manner, the respective EF uncertainty for this category is
figured out as 94.65% after taking the default uncertainties in the 2006 IPCC Guidelines into
consideration.
Source-Specific QA/QC and Verification:
The 2006 IPCC Guidelines are used for the QA/QC procedures of the National GHG emissions inventory.
A National Inventory System QA/QC Plan prepared by TurkStat is also a significant tool for implementing
QA/QC principles for the Inventory. AD for this source category are gathered mainly from the Agricultural
Statistics Department of TurkStat. Data used for calculations are published also as official statistics by
TurkStat which have their own QA/QC procedures. Emission trends are analyzed. If there is a high
fluctuation in the series, then AD and emission calculation are re-examined.
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It should be further noted that the activity data for synthetic fertilizer are also almost entirely consistent
with the data available on International Fertilizer Association's (IFA) website. Moreover, a QA work was
conducted by a Project Engineer from CITEPA for this category in January 2020.
Recalculation:
Minor revisions are a result of transmission errors in the calculation of field burning emissions affecting
calculations of crop residues emissions for 2019. For this source category, the recalculation has a
decreasing effect of -0.0007% (0.202 kt CO2 eq.) for the year 2019.
Planned Improvement:
All data and methodologies are kept under review and further possible improvements are being
considered for the future.
5.6. Prescribed Burning of Savannas (Category 3.E)
This source category of agriculture emissions is not relevant to Türkiye.
5.7. Field Burning of Agricultural Residues (Category 3.F)
Source Category Description:
The burning of residual crop material releases CH4, N2O, CO, NOx and NMVOC gases of which CO, NOx
and NMVOC are gases leading to indirect GHG gas emissions. The resulting atmospheric release of
agricultural residues is not considered to be a net carbon dioxide source, as carbon is being absorbed
again during the growing season. This source category is not a key category. Emission values due to
field burning of crop residues are presented in Table 5.3 for all thirty-two reporting years. After
consultations with the Ministry of Forestry and Agriculture (MoAF) and our own research, wheat, barley,
maize and rice cultivation areas in Türkiye were found to be included in field burning. As field burning
is illegal and widely under control, it is becoming rare. Also, the machinery is usually able to manage
the excess straw left on fields after harvesting. As presented in detail in Table 5.26, CH4 and N2O
emissions amounted to 121 kt CO2 eq. and 37 kt CO2 eq., respectively, for this source category in 2021.
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Table 5.26 Emissions from field burning of agricultural residues, 1990 and 2021
Changes from
1990 to 2021
Emissions
(kt CO2 eq.)
Category
Percentages of the
agricultural sector
(%)
1990
(%)
2021
(%)
(kt CO2 eq.)
(%)
1990
2021
347
100
159
100
-188
-54.2
0.75
0.22
CH4
265
76
121
76
-144
-54.3
0.58
0.17
N2O
82
24
37
24
-45
-54.9
0.18
0.05
Field burning of
agricultural residues
Figures in the table may not add up to the totals due to rounding.
In 2021, field burning of agricultural residues contributed 159 kt CO2 eq. This emission value represented
0.22% of all agricultural emissions. Total field burning CO2 eq. emissions presented a decreasing trend
because of prohibitive legislative measures undertaken. CH4 and N2O emissions from field burning have
mostly a negative trend except for some years. Prohibiting measures and increase of public awareness
related to field burning are key in this decreasing trend and relevant authorities impose also fines on
misconduct. Additionally, the use of advanced agricultural machinery assisting farmers in handling crop
residues more easily, could also be considered as another factor leading to the reduction of field burning
practices. The respective percentage change from this source category is -54.3% for the period of 19902021.
Methodological Issues:
Activity data used in the emission estimation are taken from TurkStat agricultural statistics. The
emissions are calculated according to the 2006 IPCC Guidelines, Volume 4, Equation 2.27 presented in
Chapter 2. Crop residue per hectare is multiplied with area of both cereal and then with fraction burned,
combustion factor and the related emission factor. Both CO2 and N2O emissions are calculated using the
IPCC Tier 1 approach. The values calculated for CH4 and N2O emissions were converted to their CO2
equivalents by multiplying the values with their respective global warming potential factors. Other
emission values under this source category, NOx, CO, and NMVOC, are not estimated. Most of the
farmers obey the rules, prohibiting stubble burning leaving some farmers still practising crop residue
burning.
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Uncertainties and Time-Series Consistency:
The AD for this sector were gathered from agricultural statistics of TurkStat. Uncertainty values
concerning AD for two GHG sources under this source category, namely CH4 and N2O, are each
estimated to be 50% whereas uncertainty values concerning EF for these gases are estimated to be
40% as recommended in the 2006 IPCC Guidelines.
Source category
3.F
Gas
Comments on time series consistency
CH4, N2O
All EFs are constant over the entire time series
Source-Specific QA/QC and Verification:
The 2006 IPCC Guidelines are used for the QA/QC procedures of National GHG emission inventory in
order to attain quality objectives. A National Inventory System QA/QC Plan prepared by TurkStat is also
a significant tool for implementing QA/QC principles for the Inventory. AD for this source category are
gathered mainly from the Agricultural Statistics Department of TurkStat. Data used for calculations are
also published as official statistics by TurkStat which have their own QA/QC procedures. Calculations
are implemented every year during preparation phase of the NIR. If errors or inconsistencies are found,
they are documented and corrected accordingly. Regarding field burning of agricultural residues, a more
representative data for burned fractions were received from MoAF. Annual checks are undertaken
whether new scientific articles for updating emission factors have been published in Türkiye. Moreover,
a QA work was conducted by a Project Engineer from CITEPA for this category in January 2020.
Recalculation:
Minor revisions are a result of transmission errors for 2020. For this source category, the recalculation
has a decreasing effect of -1.08% (1.87 kt CO2 eq.) for the year 2020.
Planned Improvement:
All data and methodologies are kept under review and there are no further planned improvements
regarding this source.
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5.8. Liming (Category 3.G)
Possible data sources are considered for this mandatory category. Three factors are possibly more
important than others which explain the use of carbonate limestone applied to soils in our country. First,
soils with lower pH values are present mainly in the Black Sea Region and Marmara Region. Second, it
is not an inexpensive method to reduce acidity of soils for agricultural producers by using carbonate
limestone. Third, there are also non-carbon containing materials available, which are suitable to be
applied on soils in order to reduce acidity. Our research is almost decisive in estimating CO2 emissions
amounted to far less than 100 kt for 2015 due to liming applied on soils. Hence, this category is
considered as insignificant according to 24/CP.19, annex I, paragraph 37(b). This source category is
reported as not estimated in the CRF.
5.9. Urea Application (Category 3.H)
Source Category Description:
Adding urea to soils during fertilisation leads to a loss of CO2 that was fixed in the industrial production
process (IPCC, Vol.4, 2006). Urea (CO(NH2)2) is converted into ammonium (NH4+), hydroxyl ion (OH-)
and bicarbonate (HCO3-), in the presence of water and urease enzymes. Similar to the soil reaction
following addition of lime, bicarbonate that is formed evolves into CO2 and water (IPCC, Vol.4, 2006).
CO2 emissions from applied urea led to emissions as high as 1 302 kt CO2 in 2021 which is an amount
representing 1.8% of agricultural emissions. Emissions from the urea application in 2021 were 842 kt
CO2 (183%) above its 1990 level of 460 kt CO2. This source category, CO2 emissions from urea
application, is not a key category.
Observed recent increases (except in 2018 and 2021) in the use of urea application is a result of its use
as a substitute for nitrogen-based fertilizers. Türkiye has limited the use of nitrogen-based fertilizers
since June 2016 leading to a shift in farmers’ preferences.
Emissions values due to urea application are shown in Table 5.3 for the period of 1990-2021 in the
sector overview section. Figure 5.12 presents the annual amount of urea application in kt (line drawn
in blue - left axis) and CO2 emissions emitted in kt (line drawn in dark red - right axis). A direct
relationship between the two values is observed in the figure. In addition, an overall sharp increasing
trend can be seen in the last ten years except for the years 2018 and 2021 which reflect decreases.
Changes in estimations are directly linked to changes in activity data for the consumption of urea.
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Figure 5.12 Urea application and emitted CO2, 1990‒2021
(CO2, kt)
(Urea applied, kt)
2500
2000
1800
2000
1600
1400
1500
1200
1000
1000
800
600
500
400
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
0
1990
1991
1992
1993
1994
1995
1996
200
0
Methodological Issues:
Emissions associated with the application of urea are calculated by using T1 approach (equation 11.13;
IPCC, 2006), using the default EF for carbon conversion of 0.20. This value equals the carbon content
of the atomic weight of urea. In order to calculate CO2-C emissions resulting from urea application, the
annual total amount of urea applied to the soils in the country is determined. Related AD, required for
the calculation are taken from the website of MoAF under the title of "Chemical fertilizer production,
consumption, import and export statistics" which is updated every year for the subsequent year. The
data time series starts from the year 1981 and our country uses directly the consumption data presented
as
the
related
activity
data
which
is
accessible
on
the
following
link:
https://www.tarimorman.gov.tr/Konular/Bitkisel-Uretim/Bitki-Besleme-ve-Tarimsal-Teknolojiler/BitkiBesleme-Istatistikleri#
Uncertainties and Time-Series Consistency:
Under the IPCC (2006) T1 methodologies, the default EFs are used, which assume conservatively that
all carbon in the urea is emitted as CO2 into the atmosphere. The default EF is assumed to be certain
under this theoretical assumption. A default 10% uncertainty is applied regarding the AD used in the
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emission calculation of urea application, whereas the uncertainty of the EF is taken as 50% as presented
in the IPCC Guidelines under the related section.
An uncertainty analysis using the Monte Carlo technique was carried out to estimate emissions of CO2
from urea application in this inventory year. Combined uncertainty in CO2 emissions in 2017 is estimated
between -13.54% and +14.70%. The Monte Carlo uncertainty range for CO2 emissions from urea
application is lower than Approach 1 results and the main reason for this difference is explained in
Annex 2.
Source-Specific QA/QC and Verification:
The 2006 IPCC Guidelines are used for the QA/QC procedures of the National GHG emission inventory.
A National Inventory System QA/QC Plan, prepared by TurkStat, is a significant tool for implementing
QA/QC principles for the Inventory. AD for this source category are obtained from the MoAF. Data used
for calculations are a part of official statistics, which have their own QA/QC procedures. Specially, the
time series was checked for consistency. As a general QC check, the multiplications of activity data and
emission factors were double-checked for CO2 emissions from urea application. Emission trends are
analyzed. If there is a high fluctuation in the series, then AD and emission calculation are re-examined.
It should be further noted that the activity data for urea applied are almost entirely consistent with the
data available on the website of the International Fertilizer Industry Association (IFA). Moreover, a QA
work was conducted by a Project Engineer from CITEPA for this category in January 2020.
Recalculation:
Two very minor revisions are a result of update in activity data for 2011 and 2020. For this source
category, the first recalculation has a decreasing effect of -0.000039% (0.00022 kt CO2 eq.) for the year
2011 and the second recalculation has an increasing effect of 0.00000838% (0.000139 kt CO2 eq.) for
the year 2020.
Planned Improvement:
All data and methodologies are kept under review. There are no further planned improvements in this
source category.
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5.10. Other Carbon-Containing Fertilizers (Category 3.I)
This source category of agriculture emissions is not relevant to Türkiye.
5.11. Other (Category 3.J)
There are no other activities to be considered under this sector.
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6. LULUCF (CRF Sector 4)
6.1. Sector Overview
The LULUCF sector of Türkiye is a net removal dominated by forests. The 23 Mha of forest area removed
a net 34 Mt of CO2 eq. from the atmosphere in 2021. Other land uses are net emissions while accounting
equals to 5 percent of forest land removals. The total removals of the sector when HWP was added has
been 47,1 Mt of CO2 eq. representing a 29 percent decrease compared to 1990. The reason for the
decrease in the trend for the last 3 years was intense wood harvest policies to meet of demand of the
wood industry of Türkiye and mega forest fires in 2021. These intense harvest policies also caused
decreasing in annual increment values per hectare.
Figure 6.1 The trend of LULUCF sector net removals including HWP 1990-2021
0
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
-20 000
-40 000
-80 000
-47,146
-56,948
-62,720
-69,752
-74,959
-73,110
-72,807
-76,877
-76,488
-73,385
-75,582
-71,880
-70,849
-67,917
-71,780
-71,455
-71,778
-69,687
-71,159
-69,282
-70,784
-68,052
-71,192
-70,612
-70,449
-67,128
-67,766
-68,014
-66,603
-67,474
-67,373
-66,511
-60 000
kt CO2 eq
-100 000
A. Forest land
G. Harvested wood products
4. Land use, land-use change and forestry
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The LULUCF sector methodologies related to activity data have entirely been modified with the support
of EU funded project entitled “Technical Assistance for Developed Analytical Basis for Land Use, Land
Use Change and Forestry (LULUCF) Sector” started in August 2017. The project was completed in July
2019 but so far provided significant improvements on;
i.
Developing spatially explicit land use matrices for the land uses and conversions starting from
1990,
ii.
Capacity building in relevant inventory agencies,
iii.
Development of a Program of Works, Annual Work Plan and Compendium,
iv.
A new system to calculate and report GHG emissions/removals in LULUCF sector,
v.
Activity data disaggregated into 8 Ecoregions and 28 Forest Administrative regions for higher
level accuracy,
vi.
Updated NIR.
The details of the project can be seen on the project web page https://www.lulucf-tr.org/
The new LULUCF reporting system (LRS) of Türkiye is composed of below elements:
▪
A spatially explicit land cover-driven AD produced by an experienced international company.
The system uses tracks all land cover with satellite images since 1990 and detects all changes
on an annual basis. Each 1 hectare unit of land (1 ha) is tracked for the reporting period and
calculated for emissions and removals on a consistent approach
▪
Updated land use definitions
▪
A new system of reporting that is capable of performing calculations; harmonizing spatial data
with EF data, archiving, and tools to enhance QA/QC
▪
Re-assessed EFs by a team of experts
▪
An EF database and Reference Library were developed and used. The system enables experts
to update the EFs and coefficients on a continuous basis
▪
A database has been developed to query all land covers and changes. Thus, land cover database
on Satellite images can be checked and verified anytime
The LRS is managed and used by a group of national experts for different elements. This means that
the inventory is prepared by more than 10 experts each focusing on a different item. This enables
sharing of responsibility and improvement potential.
The new system increased the transparency significantly by using AD produced by an international
remote sensing company, and a renewed NIR. Furthermore, the new spatially explicit land use tracking
system improved completeness, accuracy and consistency because the same methodology has been
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Land Use, Land Use Change and Forestry
used for the whole reporting period and for all land uses with around 90 percent accuracy. The new
reporting system caused significant changes in emissions and removals. The main categories of removals
have been FL-FL and HWPs. The outcome of the key category analysis for 2021 was listed in Table 6.1.
Table 6.1 Key categories identification in the LULUCF sector (Tier 1)
CATEGORIES OF EMISSIONS AND REMOVALS
Gas
2021
4.A.1
Forest Land Remaining Forest Land
CO2
Key (L,T)
4.G
Harvested Wood Products
CO2
Key (L,T)
Within the new reporting system, a national EF database together with a reference library has been
established. They are very similar to the IPCC EF database in structure and include all data used in the
inventory even the default coefficients.
The context and management of the EF database are as follows;
Emission factors are the second set of data, needed for estimation of GHG emissions and removals. An
emission factor (EF) is defined as the average emission rate of a given GHG for a given source, relative
to units of activity (IPCC 1996). Emission factors can be collected from various sources, from national
and international statistics and monitoring, databases, research studies, scientific papers, technical
reports etc. The use of appropriate emission factor is essential as wrong selection may lead to underor overestimation of emissions and removals. In general, the IPCC guidelines include a large list of
emission factors, which can be used when Tier 1 methods are selected for estimation. Moreover, there
exists an emission factor database (EFDB: https://www.ipcc-nggip.iges.or.jp/EFDB/main.php) of the
IPCC, which also includes a large set of emission factors, relevant to the LULUCF.
The following approach is implemented for updating the national EF database:
▪
Check for improvement of EF database on annual basis (e.g. new EF gathered, higher Tier
method selected, category become key source etc.).
▪
Collect country-specific emission and stock change factors for all key categories.
▪
Collect all relevant default emission factors of the IPCC for other categories (non-key).
▪
Assign appropriate specific emission and stock change factors to each corresponding category.
▪
Add and update EF database when new or improved emission factors are obtained or
determined, respectively.
▪
Store a reference of the EF in the archive (data source, uncertainty, background data etc.).
▪
Record the person and reason whenever your update the EF database.
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The EF database is embedded in the reporting system on the main computer and has the below table
format;
Land-use definitions and the classification systems used and their correspondence to the
land use, land-use change and forestry categories
The Land Use definitions of Türkiye have been updated with the new land monitoring system. The
country has been divided into 8 ecological zones based on international and national literature. The
ecoregions assessment has provided the possibility to disaggregate calculations into more homogenous
regions and use more specific EFs and coefficients. The Ecozones identified by Serengil (2018) and their
relationship with climate types are given below (Figure 6.2. and Table 6.2.)
Figure 6.2 The ecoregions in Türkiye (Serengil, 2018)
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Table 6.2 Ecozones in Türkiye and their relationships with climate classifications
(Serengil, 2018)
Ecozone
1
Temperate deciduous Black Sea Coastal
forest
& mixed forest
2 coniferous and mixed
forest
Mediterranean coastal zone
3 deciduous and coniferous
forest
5
Temperate
deciduous,
coniferous and mixed
forest
Aegean Inland deciduous Mediterranean
forest, shrubs
East Anatolian deciduous
Temperate deciduous
forest zone
& mixed forest
Legend
Warm Temp Moist
Warm Temp Dry
Warm Temperate Moist-Dry
Mediterranean
Inland Temperate Warm Temp Dry
Mountain Climate
Mediterranean
Inland Temperate Warm Temp Dry
Climate
Temperate deciduous Semi Dry Steppe
& mixed forest
Map
Climate Zone
Coastal Zone
forest, shrubs
8 East Anatolian steppe
Temperate
forest, shrubs
zone
IPCC Climate Type
Black Sea Inland
Mediterranean
Mediterranean
and coniferous forest
Zone
Mediterranean
Mediterranean Mountain
6 Central Anatolian steppe
7
Climate Type
Euxine-Colchic deciduous
North Anatolian deciduous,
4
Biome
Climate
Warm-Cool Temp Dry
Temperate
Continental
Warm Temp Dry
Climate
Temperate
Continental
grassland, shrubs
Mountainous
and steppe
Climate
Cool Temp Moist-Dry
The new definitions of land uses have been explained below. The former forest definition in 2018
submission was the national legal definition. The national definition had a threshold just for the minimum
area which is 3 ha. The application of the new definition and spatially explicit land tracking system did
not change the forest area drastically but the share of productive forest in forest land category increased.
The difference between the old and the new systems has been discussed in Forest land category below.
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Forest Land: Forest Land category has been disaggregated into 2 major subcategories;
Productive Forest: Tree and woodland communities of more than 1 ha with a crown closure of
over 10 percent, which are grown by both human efforts and naturally are regarded as Forests.
Other Wooded Forest (OWF): The same definition applies except for the crown closure. The
crown closure for OWF is between 1 to 10 percent. The wooded land with crown closures of
less than 1 percent is allocated under grassland.
Cropland: The following land uses are included in the croplands.
▪
Arable land (Non-irrigated arable land, Permanently irrigated land)
▪
Permanent crops (Vineyards, Fruit trees and berry plantations, Olive groves)
▪
Poplar plantations in or near the agricultural area
Grassland: All woody/herbaceous vegetation is defined as grassland. The grasslands include shrubs
and trees that provide a crown closure of less than 1 percent. The demand for grazing areas is high in
the country and differentiation between managed and unmanaged is not technically possible thus all
grasslands are accepted as managed.
Wetlands: This category is divided into two as managed and unmanaged. Only flooded land (dams,
irrigation dams and reservoirs) and peatlands are included in the managed wetland definition. Natural
systems like rivers and lakes are classified under unmanaged wetlands.
Settlements: Artificial surfaces are reported under Settlements. These include;
▪
Urban fabric (continuous, discontinuous fabric)
▪
Industrial, commercial and transport units (Industrial or commercial units, Road and rail
networks and associated land, Port areas, Airports)
▪
Mine, dump and construction sites (Mineral extraction sites, Dump sites, Construction sites, )
▪
Artificial, non-agricultural vegetated areas (Green spaces like parks and cemeteries that are not
classified as forest, sport and leisure facilities)
Other Land: Open spaces with little or no vegetation are defined under Other Land. These include;
292
▪
Beaches, dunes, sands
▪
Bare rocks,
▪
Sparsely vegetated areas
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Information on approaches used for representing land areas and on land-use databases
used for the inventory preparation
In the previous submission, there was inconsistency between activity data of forestry and other land
uses. The AD related to forest land was collected from a tabular database called ENVANIS. The ENVANIS
system is the major data source of forest management in Türkiye and provides both area data,
increment and other relevant data related to the forests. It bases on 10 years rotation period field
measurements that are implemented on 10 percent of the forests in the country. The ENVANIS system
provides high accuracy information on stand parameters but has some disadvantages for GHG
inventories. These disadvantages are;
The forest area in the ENVANIS system uses a national legal forest definition and is not
compatible with land cover maps i.e. CORINE. Thus it is not possible to establish a consistent
land use matrix with a combination of ENVANIS and spatial databases that base on land cover.
As 10 percent of the country forests are sampled and measured every year the data given in
ENVANIS represents only this amount of updated data.
The types of conversions are unknown. The forest area increase or decrease is reported but the
land use that forest is converted is not. Thus an assumption was made that these area areas
are all grassland.
The new system uses data from Forestry Statistics such as annual increment but not the area data.
Below are the specifications of the satellite based system that has been produced just to be used for
GHG calculations.
The New Satellite Based Land Cover Monitoring System (SBLMS)
A satellite Earth Observation based on AD monitoring system for LULUCF for the entire territory of
Türkiye is developed. The system relies on wall-to-wall spatially explicit mappings to analyze LULUCF
activity data and changes for the period from 1990 to 2015. The system delivers complete annual land
use and land use change matrices, allowing for consistent spatially explicit assessment in high spatial
resolution (30m, 1 ha MMU). The matrices report on land use and land use change between the six
IPCC Guidelines land use categories and related 11 subcategories. With this system every unit of land
is univocally assigned to only one land use category, eliminating double counting or omissions. By
providing consistent information on all land use and land use change categories, inconsistencies in
previous submissions in land use representation derived from CORINE Land Cover and ENVANIS have
been overcome.
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Figure 6.3 The temporal structure of the SBLMS with the satellites used
Following similar approaches of other Mediterranean countries, this is achieved through
▪
detailed mapping of the selected reference years (here 1990, 2000 and 2015) from time series
high-resolution satellite images,
▪
the determination of changes between these reference years and,
▪
an assessment of the intermediate years through advanced analyses.
Table 6.3 Classification approach for all categories and subcategories under SBLMS
Category Proposed classification approaches
294
Category
Classification Approach
Forest
The identification of deciduous and coniferous forests is based on time-series analysis, where
phonological changes are used to differentiate between these two classes. Copernicus HRL
Forest layers 2015 and 2012 are used as ground truth. Following this differentiation a local filter
with a size of 1ha will be applied, where areas without dominant tree type are classified as
mixed forest.
Cropland
Separation of cropland and grassland is a complex task in image classification and requires
multitemporal data analyses and reference ground truth data. Annual crops have been
identified due to their vegetation phenology (periodic change of vegetation status). Perennial
crops on the other hand are hard to differentiate from forest areas, due to similar spectral
characteristics compared to other woody vegetation. Therefore, ancillary information is needed
to assist in the identification of perennial croplands (e.g.. LPIS for 2015). The global NASA Crop
layer and CORINE are used to prepare samples for both crop sub-categories. A fully automated
classification approach for 25 years over entire Türkiye cannot reliably detect different crop
types, so statistical information (e.g. TUIK) can instead be used to calculate crop type ratios that
are then applied to the detected crop areas, assuming the area estimates in the TUIK database
are representative for the entire country.
Grassland
Grassland areas are classified by the spectral characteristics detected over time. The
differentiation between woody grasslands and herbaceous grasslands is based on spectral
classification as well as ruleset to improve accuracy. Woody grasslands, for example, are likely
to be found around forests, so their proximity to a forest boundary has been taken into
consideration. For consistency woody grasslands that have a crown closure of 1 to 10 percent
are merged with Other Forested Areas category.
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Wetland
Open (artificial) waterbodies are readily detectable with satellite data given their sudden
appearance at a fixed point in time (e.g. construction of a dam) and their permanence following
that date. Different indices (e.g. Normalized Difference Water Index (NDWI)) are used to
efficiently delineate wetlands. Auxiliary data on dam constructions are needed to improve
detection accuracy.
Settlement
For the identification of settlement areas, indices like the NDVI are used, as they highlight both
vegetated and non-vegetated areas. The HRL and CORINE datasets have been used to provide
ground truth.
Other land
Areas which are covered by bare soil, sand, rocks, and salt marshes will be classified as other
land. Permanent snow and ice will also fall under this category, should they be present in Türkiye
in any given year.
Land use baseline establishment
For each of the three reference years (1990, 2000 and 2015) a land cover map has been produced by
applying the classification procedures described above. The outputs have further been refined using
existing datasets for Türkiye, especially for the differentiation of perennial crops. Due to the different
types and amounts of data available for the different time steps, specific methodologies have been
applied to achieve consistent outputs over the entire 1990-2015 period.
2015 is the most recent reference year for mapping and AD reporting in this project. With the Copernicus
program, the availability of high resolution satellite imagery has dramatically improved and the
monitoring system can utilize this wealth of information by including both Sentinel 2 (10-20m) and
Landsat 8 (30m) imagery in the production process. In addition to the high availability of satellite
imagery, an extensive list of highly accurate, spatially explicit information products have been used to
support the mapping in 2015. These include LPIS, Copernicus High Resolution Layers (HRL) for Forest,
Wetlands, Grassland, and Settlements, other global data layers (e.g. USGS Global Crop Maps) and other
auxiliary data.
Mapping of the intermediate reference year 2000 is primarily based on Landsat 7 with support from
Landsat 5 imagery. CORINE is used as auxiliary data.
The reference year 1990 is the base year for UNFCCC reporting and relies primarily on Landsat 5 imagery
for mapping. Considering the 20-year-transition rule, it was anticipated that the time from 1970 until
1990 be reviewed for the definition of the 1990 map (see D4.2.1). The Landsat satellite program started
in 1972, however, satellite data is only sparsely available for Türkiye until the 1980s and the assessment
of approaches chosen by other Mediterranean countries shows that the primary input for 1990 base
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maps is national forest statistics. The Turkish national forest inventory is available for 1972, however, it
is not spatially explicit and uses an incompatible definition for forest which means that it is of very
limited use in an assessment of the 1970-1990 period. In order to overcome these high uncertainties,
some countries (e.g. Greece) have chosen to report 1990 as is and commence with any land use changes
from then on. In our approach, we used the 1990 land cover/land use map on Landsat 5 imagery as
the base year.
The monitoring system uses an accurate approach by performing change detection for intermediate
years through breakpoint analyses of spectral indices calculated from all satellite data available for the
intermediate period. This method provides accurate estimates of changes and their change years, and
together with the 3 national land cover/land use maps, provides the basis for the annual matrices.
Figure 6.4 Change detection approach between reference years
The satellite based land monitoring system is planned to be continued and improved in the coming
years.
Land Use Matrixes
Land uses and transitions between the 6 land use types and 11 land use subcategories have been
calculated in annual land use/land use change matrixes for all 25 years (without any interpolation in
between). Further, the last 6 years (2016, 2017, 2018, 2019, 2020 and 2021) have been extrapolated.
All transitions are reported as transitions for 20 years following the transition event. Land categories
and subcategories have been further disaggregated into 8 ecozones and 28 forest regional directorates.
The ecozones have been explained above in Table 6.2. The outline of the core matrix is illustrated in
Table 6.4.
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Table 6.4 A sample land use matrix (2015)
FROM:
Initial area
Total
unmanaged
land
Other land
Settlements
Wetlands
(unmanaged)
Wetlands
(managed)
Grassland
(unmanaged)
Grassland
(managed)
Cropland
Forest land
(unmanaged)
Forest land
(managed)
TO:
(kha)
Forest land (managed)
(2)
Forest land (unmanaged)(2)
Cropland(2)
Grassland (managed)(2)
22723.46
NO
2.31
NO
4.37
4.41
NO
0.39
NO
0.44
2.16
NO 22735.23
NO
NO
NO 26871.50
NO
0.10
NO
NO
NO
1.86
NO
NO
NO
1.63
NO
1.32
NO
NO
NO 26878.71
61.81
NO
5.32 23974.34
NO
1.06
NO
0.70
1.51
NO 24044.74
Grassland (unmanaged)(2)
Wetlands (managed)(2)
NO
NO
NO
NO
NO
0.19
NO
0.09
NO
NO
NO
465.68
NO
NO
NO
0.03
NO
0.24
NO
NO
Wetlands (unmanaged)(2)
NO
NO
NO
NO
NO
NO
1344.22
NO
NO
NO
1344.22
Settlements(2)
NO
NO
NO
NO
NO
0.00
NO
1383.70
0.01
NO
1383.71
NO
0.46
0.18
NO
NO
NO
NO 26881.83 23979.13
NO
NO
NO
0.26
NO
469.25
NO
NO
1344.22
0.06
NO
1386.55
1672.49
NO
1677.73
NO
NO
3.02
0.00
2.84
4.13
Other land(2)
Total unmanaged land (3)
Final area
Net change
(4)
0.14
NO
22787.72
52.50
3.12
-65.61
NO
466.23
NO 1673.60
NO
NO
NO 78526.44
NO
0.00
Accuracy Assessment
For the land cover and land use datasets of the years 1990, 2000 and 2015, a scientifically sound
thematic accuracy assessment has been carried out following best-practice standards according to ISO
19157 Geographic information - Data quality, the CEOS guidelines for Calibration and Validation and the
QA4EO principles. This involves the following core design principles:
▪
Sampling design: A probability sampling design is used to generate a stratified random point
sample that is statistically viable for all sampled categories and sub-categories at a confidence
interval of 95%.
▪
Response design: The samples are then validated against higher quality data that includes aerial
imagery (e.g. Google and Bing maps) for 2015; 15m pan-sharpened Landsat 7 imagery for 2000
and Landsat 5 imagery for 1990, in addition to other independent aerial or very high resolution
satellite imagery, other map products or local auxiliary data.
▪
Analysis: The outcomes are presenting uncertainty measures on the area and area changes of
the land use categories in the form of a confusion matrix (Table 6.5) that provides information
on overall thematic accuracy, class-specific user’s and producer’s accuracies, and Kappa
coefficients at a confidence interval of 95%. User accuracy and Producer accuracy are defined
as follows:
User accuracy is a measure of commission error: Represents the probability that a pixel classified into a
given category actually represents that category on the ground. Producer accuracy is a measure of
omission error. This value represents how well reference pixels of the ground cover type are classified.
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Table 6.5 Confusion Matrix
Completeness
As regards the inventory completeness, sinks and sources that have been reported with notation keys
NA, NO, IE and NE in the CRF tables are listed below:
Table 6.6 Completeness Table
Sink/source category
Pool
GHG
Reported as
Mandatory
Forest land remaining forest land
Soil
CO2
NO
No
Explanation
It is assumed that carbon stocks of
soils in Forest Land Remaining Forest
Land do not change.
Forest land remaining forest land
Land converted to Forest land
Dead
CO2
NO
No
It is assumed that carbon stocks of
wood and
DOM in Forest Land Remaining
litter
Forest Land do not change.
Dead
CO2
NO
Yes
wood
The DW carbon stocks in case of land
conversion are assumed to be not
changing and DW carbon stocks in all
land use are assumed to be zero. The
IPCC 2006 does not provide a default
value for DW C stocks.
Forest
land,
Biomass
Burning- Biomass
CO2,
CH4 NO
Yes
and N2O
Controlled Burning
Controlled Burning is not applied in
Forest land.
Forest lands, drained soils
Biomass
Non-CO2
NE
Yes
No available data on drainage
Drained wetlands
Biomass
Non-CO2
NO
Yes
Wetland drainage is not performed in
Türkiye.
Croplands,
grasslands,
wetlands Biomass
and settlements, biomass burning
298
CO2,
CH4 NA,NO,IE
Yes
No available data
and N2O
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6.2. Forest Land (4.A)
Source Category Description:
The forest land category includes CSC from Forest Land Remaining Forest Land (FL-FL) and Land
Converted to Forest Land (L-FL) subcategories. Tier 2 methods that are combinations of national EFs
and IPCC methods have been applied except for some default coefficients (i.e. CF, root to shoot ratio).
The AD in these subcategories have entirely been changed. The previous submissions used to base on
ENVANIS statistics for AD and increment values. With the spatially explicit land tracking system the
increment values are taken from Forestry Statistics but AD has entirely been changed. The
improvements in this category with the new reporting system and consequences are as follows;
▪
The forest definition has been changed to one that is more suitable for GHG inventories. The
previous national definition was a legal definition that do not include a threshold for crown
closure. All land uses have been disaggregated into ecozones but forests have also been split
into 28 regional forestry directorates. This will enable to implementation of mitigation actions
more effectively among forestry directorates.
▪
Now the forest land has been split into 4 subcategories that are coniferous, deciduous, mixed
forest and other forested land (OFL). OFL are forest areas with crown closure between 1 to 10
percent. The previous forest definition included a minimum area of 3 ha. The new system
defines all forests with a minimum area of 1 ha.
▪
The previous system was based on Forestry Statistics which was available since 2007. The
period before 2007 was extrapolated basis on 1972 and 1999’s forest inventory. With the new
system, consistent land use and land use change AD has been available for the whole reporting
period. The AD base on satellite images and has 1 ha spatial resolution.
▪
The previous system was not able to identify land conversions between forests and other land
uses (i.e. L-FL, FL-CL, FL-GL) and it was assumed that conversions occur only from and to
grasslands. Now all land conversions have been tracked with high accuracy and
emissions/removals have been reported.
▪
The previous system was based on reports from regional forestry districts and was not subject
to verification while the new system enables verification of the satellite based maps from other
sources (i.e. Land Parcel Identification System, CORINE).
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▪
The crown closure data from Forestry Statistics was based on subjective observations while the
new system enabled objective automatic identification.
▪
The AD of the previous system was derived from the management unit of GDF while AD has
been produced by an international remote sensing company. This strengthens the objectiveness
of the AD.
▪
As a consequence of changes in definition and AD development methodology, the total forest
did not change significantly but productive forest areas that have crown closure of more than
10 percent increased significantly. As a result of this, the removals due to the increase in
aboveground biomass increased drastically. The increment data taken from Forestry Statistics
puts forward large increases in increment between 2011 and 2018 which may be caused by
rehabilitation projects in the early 2000s. The productivity of the stands increased as the stands
reached the fast-growing young ages in the 2010s. The changes in increment for forest types
are given below;
Table 6.7 Annual increment rates of forest types in Türkiye
(m³/ha)
Year
300
Deciduous
Coniferous
Mixed
OFL
1990
3.15
2.99
3.07
0.26
1995
3.20
3.03
3.11
0.27
2000
3.25
3.08
3.16
0.27
2005
3.30
3.13
3.21
0.23
2010
3.35
3.39
3.37
0.22
2011
3.48
3.45
3.47
0.21
2012
3.48
3.45
3.47
0.21
2013
3.48
3.45
3.47
0.21
2014
3.48
3.45
3.47
0.21
2015
3.25
3.56
3.40
0.22
2016
3.25
3.56
3.40
0.22
2017
3.25
3.56
3.40
0.22
2018
3.27
3.58
3.42
0.22
2019
3.27
3.56
3.41
0.21
2020
3.22
3.53
3.38
0.21
2021
3.17
3.49
3.33
0.21
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Information on Land Classification and Activity Data
Detailed information has been provided under section 6.3.
Land-use definitions and the classification systems
In the previous submissions before 2019 national forest definition was used. With the 2019 submission,
the forest definition has been changed to a definition in line with the definitions of the Food and
Agriculture Organization of the United Nations. The EU and FAO compliant forest definition of 10%
crown cover, 1 ha MMU and 5m tree height is applied to all sub-categories. The lands below 10 percent
crown closure are classified under other forested land (OFL) as a subcategory under forest land.
Agriculturally used tree crops are classified under perennial croplands and are not part of the forest
definition.
The forests have further been classified as coniferous, deciduous and mixed forests. The mixed forests
consist of both coniferous and deciduous trees with neither species clearly dominating the stand.
Table 6.8 Forest area (kha) changes in Türkiye, 1990-2021
Tabular (old system)
Productive
Other
Year
forest
Forested Land
1990
10 494
10 075
1995
10 546
2000
Spatially explicit land tracking (new system)
Productive
Other Forested
forest
Land
Total
20 569
19 721
3 258
22 979
10 125
20 672
19 699
3 248
22 955
10 643
10 218
20 861
19 664
3 242
22 908
2005
10 662
10 586
21 248
19 637
3 218
22 865
2010
11 203
10 334
21 537
19 583
3 184
22 783
2015
12 704
9 639
22 343
19 606
3 181
22 787
2016
12 704
9 639
22 343
19 658
3 182
22 840
2017
12 983
9 638
22 621
19 583
3 183
22 766
2018
12 983
9 638
22 621
19 602
3 184
22 786
2019
13 083
9 656
22 740
19 610
3 184
22 794
2020
13 264
9 668
22 933
19 603
3 194
22 797
2021
13 500
9 610
23 110
19 700
3 203
22 903
Total
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The increment data is provided by the Management Department of the Forest Service (GDF) via Forestry
Statistics. The Forestry Statistics database collects and processes data from forest management plans
as the plans are renewed every ten years. Since 2007, the Forestry Statistics database, a forest
resources inventory based on forest management units is used. This database covers the data of areas,
annual increment, commercial volume and growing stock of each forest management unit by the
species, management types, form of stand, purpose, etc. Therefore, a comparison of forest area, annual
increment and growing stock, between two subsequent years, has been possible since 2007. The
comparison of removals by forestry sector, according to the forest area, growing stock changes and
annual increment since 1990 is given in Table 6.8, 6.10 and 6.11.
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Databases to Identify Forests
There are only two documents (1972 and 1999 inventory) relevant to the national forest inventory
results in Türkiye before 2002. The first document showing the 1972 situation was presented in 1980,
and the second was prepared at the end of 1999. Because of the absence of regular national forest
inventory works in Türkiye, both of the results were obtained based on the summaries of management
plans data renewed every ten years interval. The data provided by the first inventory (1972) has been
shown in Table 6.9. The growing stock and annual increment data since 1990 have been presented in
Tables 6.10 and 6.11.
Table 6.9 Forest inventory, 1972 (Source: GDF)
Areas
Productivea
Type
Degradedb
Total
ha
%
ha
%
ha
%
High Forest
6 176 899
30.58
4 757 708
23.55
10 934 607
54.13
Coppice
2 679 558
13.27
6 585 131
32.60
9 264 689
45.87
Total
8 856 457
43.85
11 342 839
56.15
20 199 296
100.00
Growing stock
Productivea
Type
m3
High Forest
758 732 197
Coppicec
88 300 818
Total
847 033 015
Degradedb
%
m3
Total
%
m3
%
81.10
54 349 847
5.81
813 082 044
86.91
9.44
34 129 288
3.65
122 430 106
13.09
90.54
88 479 135
9.46
935 512 150
100.00
Annual volume increment
Productivea
Type
High Forest
Coppicec
Total
Degradedb
Total
m3
%
m3
%
m3
%
20 791 672
74.09
1 343 744
4.79
22 135 416
78.88
4 813 197
17.15
1 114 592
3.97
5 927 789
21.12
25 604 869
91.24
2 458 336
8.76
28 063 205
100.00
a) Crown closure between 0.11–1.00.
b) Crown closure between 0.01–0.10.
c) 0.75 coefficient was used to convert the stere volume to a m3 volume.
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Table 6.10 Growing stock, 1990-2021 (Source: GDF)
Productive1
Degraded2
Productive
Coppices
(thousand m³)
Degraded
3
total
High Forest
3
Year
High Forest
Coppices
total
Total
1990
984 907
64 986
1 049 893
43 622
12 038
19 976
1 105 553
1995
1 028 346
67 957
1 096 303
45 618
12 589
20 890
1 154 509
2000
1 087 582
72 002
1 159 584
48 334
13 338
22 134
1 221 256
2005
1 177 849
71 551
1 249 400
51 045
12 661
23 655
1 313 106
2010
1 328 437
59 097
1 387 534
49 351
12 286
19 415
1 449 171
2015
1 552 821
33 695
1 586 516
59 997
11 954
71 951
1 658 467
2016
1 540 723
29 215
1 569 939
60 895
10 377
71 271
1 641 210
2017
1 601 931
13 728
1 615 659
64 991
4 314
69 306
1 684 964
2018
1 601 931
13 728
1 615 659
64 991
4 314
69 306
1 684 964
2019
1 595 828
14 013
1 609 841
64 791
4 723
69 514
1 679 356
2020
1 614 281
14 013
1 628 295
64 037
4 722
68 759
1 697 055
2021
1 639 227
14 013
1 653 240
63 731
4 722
68 454
1 721 695
1) Crown closure between 0.11–1.00.
2) Crown closure between 0.01–0.10.
3) 0.75 coefficient was used to convert the stere volume to a m3 volume.
Table 6.11 Annual volume increment, 1990-2021 (Source: GDF)
Productive1
Degraded2
Productive
Years
High Forest
(m³)
Degraded
Coppices3
total
High Forest
Coppices3
total
Total
1990
28 263 488
3 594 725
31 858 213
1 292 180
761 076
2 053 256
33 911 468
1995
28 997 951
3 697 360
32 695 311
1 329 099
782 820
2 111 919
34 807 230
2000
31 047 474
3 985 847
35 033 320
1 432 875
843 943
2 276 819
37 310 139
2005
33 282 485
4 025 038
37 307 523
1 495 502
922 183
2 417 685
39 725 208
2010
37 857 085
3 089 208
40 946 293
1 468 070
792 878
2 260 948
43 207 241
2015
46 011 103
1 511 832
47 522 935
1 484 455
585 191
2 069 646
49 592 580
2016
43 669 510
1 277 030
44 946 540
1 539 688
487 331
2 027 019
46 973 559
2017
45 516 439
755 697
46 272 136
1 728 694
252 728
1 981 422
48 253 588
2018
44 247 096
762 981
45 010 077
1 713 433
276 490
1 989 923
47 000 000
2019
44 447 096
762 981
45 210 077
1 713 433
276 490
1 989 923
47 200 000
2020
44 647 096
762 981
45 410 077
1 713 498
276 425
1 989 923
47 400 000
2021
44 863 388
762 981
45 626 369
1 697 206
276 425
1 973 631
47 600 000
1) Crown closure between 0.11–1.00 (productive forest).
2) Crown closure between 0.01–0.10 (degraded).
3) 0.75 coefficient was used to convert the stere volume to a m3 volume.
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5
Evaluation of Table 6.9, 6.10, and 6.11 can be outlined as below:
1. The growing stocks and annual volume increments of the coppice forests reduced while high
forests increased constantly. The highest amount of decrease in growing stock/annual
increment has occurred in degraded coppices due to converting the coppices into high forests.
2. The total amount of growing stocks and annual volume increment in the coniferous and
deciduous forests per hectare have slightly decreased.
The considerable reasons for these changes can be:
1. The changing approaches on the forestry applications towards multi-functional use of forest
resources in the framework of sustainable forest management concept,
2. Converting coppices into the high forests,
3. The reforestation of unstocked areas in and around forests and rehabilitation of degraded
forests by the GDF.
4. Intense harvest policies also caused decreasing in annual increment values per hectare.
All the factors focused on above have played an affecting role inthese changes. Almost entire of Turkish
forests can be categorized in the temperate climate zone.
CSC in Forest Land Remaining Forest Land
The carbon stock change in FL-FL subcategory has been net removals during the reporting period. The
driver of this situation was the increment of forests. The increment of the forests in the country
increased for the reporting period constantly while increased faster for some years. The steep increase
between 2009 and 2019 was due to the difference in increment (m3/ha) for 2014 (Ivdec=3.26,
Ivcon=3.31, Ivmixed=3.29, Ivdeg=0.22) and 2019 (Ivdec=3.27, Ivcon=3.56, Ivmixed=3.41, Ivdeg=0.21). This
might have been caused by extensive rehabilitation campaigns during the 2000s. However, after 2019,
annual increment values have been decreasing due to most of the intensive wood harvesting activities
being applied in productive forests. The increment data is derived from all management units of the
country as explained in the methodology section.
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The removals of the forest land remaining forest land subcategory have been decreased for the last 3
years. The main reason is the increase of the fellings for industrial roundwood due to intense wood
harvest policies. The industrial roundwood production amounts have been increased respectively by
15,5 million m3 for 2017 to 19 million m3 for 2018, 22 million m3 for 2019, 30 million m3 for 2020 and
33 million m3 for 2021. In addition, approximately 10 million CO2 eq. emission estimated for Forest Land
Remaining Forest Land category due to mega fire in 2021 in Türkiye.
Figure 6.5 Gains and losses in Forest land Remaining Forest land subcategory (FL-FL)
30 000
25 000
20 000
kt C
15 000
10 000
5 000
0
-5 000
-10 000
-20 000
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
-15 000
Gains
Losses
CSC in Land Converted to Forest Land
The CSC in Land Converted to Forest land category is not a key category anymore with the new reporting
system. The main reason for the drop in L-FL removals is due to a change in forest definition. As
explained in the section 6.2 the forest definition has been changed to a physical definition while it used
to be a legal national definition. As a consequence of this, the AD for land converted to forest land
decreased substantially. The CSC in L-FL subcategory moved from net loss to net gain during the
reporting period through large fluctuations are observed (Figure 6.6). The large loss in CSC in 1992 was
due to a relatively larger conversion from grassland to forest. As explained in the methodology section
below the conversion from grassland to forest land causes a loss in living biomass carbon for the first
year.
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Figure 6.6 Gains and losses in Land Converted to Forest land subcategory (L-FL)
L-FL
25
20
15
kt C
10
5
0
-5
- 15
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
- 10
Gains
Losses
As seen from the graph above (Figure 6.6) the L-FL gains increased until 2011 and stabilized since then.
There have been 3 types of transitions that occurred during the reporting period;
▪
Grassland Converted to Forest land
▪
Other land Converted to Forest land
▪
Cropland (Perennial) Converted to Forest land
Between 1991 and 1996 the conversions were around 4000 ha per year, then dropped below 2000
between 1997 to 2000 and then rise again until 2010. The conversions to Forest land drop to a band
around 2000 since then.
Figure 6.7 Area data for Land Converted to Forest land subcategory
9
8
7
5
CL-FL
4
GL-FL
3
OL-FL
2
1
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Area kha
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As seen in Figure 6.7 the major conversion path in L-FL subcategory is the conversion from Grassland
to Forest land. The driver of this conversion type is the afforestation/reforestation of grasslands in or
around the forests.
Table 6.12 Area of Land converted to forest land
(kha)
Year
GL-FL
CL-FL
OL-FL
Year
GL-FL
CL-FL
OL-FL
1990
0.00
0.00
0.00
2006
7.35
0.22
0.77
1991
3.40
0.07
0.56
2007
4.28
0.17
0.57
1992
6.71
0.14
1.00
2008
5.51
0.18
1.01
1993
2.97
0.08
0.45
2009
3.63
0.10
0.34
1994
3.28
0.08
0.32
2010
5.84
0.18
0.56
1995
3.32
0.10
0.41
2011
2.15
0.08
0.25
1996
2.89
0.09
0.30
2012
2.56
0.13
0.29
1997
1.02
0.04
0.11
2013
0.86
0.05
0.08
1998
1.24
0.06
0.23
2014
1.34
0.06
0.15
1999
0.63
0.07
0.28
2015
1.45
0.09
0.14
2000
0.30
0.03
0.10
2016
1.68
0.08
0.18
2001
2.77
0.07
0.24
2017
1.58
0.08
0.17
2002
5.67
0.21
0.68
2018
1.38
0.07
0.15
2003
2.77
0.11
0.35
2019
1.49
0.08
0.16
2004
6.07
0.24
0.74
2020
1.52
0.08
0.16
2005
3.47
0.15
0.40
2021
0.56
0.04
0.18
Methodological Issues:
Forest Land Remaining Forest land
The calculations in FL category are based on 8 ecozones and 28 forestry regional directorates. The soil
C stocks for each ecozone have been calculated by TAGEM (General Directorate of Agricultural Research)
based on the soil database since the 2019 submission.
Above- and below-ground biomass
Gain-Loss Method (Tier 2) is used to estimate annual change in carbon stocks in living above- and
below-ground biomass, considering the country-specific data on mean annual increment, volume of
commercial cutting, fuelwood removal and loss due to disturbances, national biomass expansion factors
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(BCEFI, BCEFR) and basic wood densities (D), and default root-to-shoot ratios (R) and carbon fractions
(CF). The below equations have been used in estimations;
2006 IPCC equations: Vol 4., Ch. 2: 2.7 / 2.9 / 2.10 / 2.11 / 2.12 / 2.13 / 2.14
The estimation approach was as follows;
i.
The area of each forest stratum with corresponding mean annual increment has been multiplied
by national BCFI coefficients, IPCC 2006 default root-to-shoot ratios, and IPCC 2006 default CF
coefficients to get annual biomass gain (∆CG).
The increment data is provided by the Forest Management Department via the ENVANIS system and
they are updated every year for four forest types;
▪
Deciduous forest
▪
Coniferous forest
▪
Mixed forest
▪
Degraded forest
The increment data used are given in Table for some years.
ii.
Annual carbon loss (∆CL) as a sum of wood removals (i.e. commercial cutting), fuelwood
removal and disturbance (i.e. forest fires) by each forest stratum has been calculated. In the
calculation of annual carbon losses in biomass due to disturbances (Disturbance), the annual area
affected by disturbances has been used (see Equation 2.14).
The data used in this step is received from relevant departments (Production and Marketing, Fire etc.)
of the GDF.
The annual biomass loss is a sum of losses from commercial round wood felling, fuelwood gathering
and other losses in forest land was calculated by using the following Equation 2.11 of AFOLU Guidance.
Biomass gains and biomass losses are estimated separately. For example, commercial round wood
felling has been calculated in a different column as well as fuelwood gathering and other losses
according to Equation 2.12, Equation 2.13 and Equation 2.14 respectively. The calculations of biomass
losses are consistent with the IPCC 2006 Guidance for AFOLU (Vol 4).
2006 IPCC equations: Vol 4., Ch. 2: 2.11 / 2.12 / 2.13 / 2.14 / 2.17 /2.24 / 2.27
The FG data in eq. 13 is obtained from the GDF (Forestry Statistic 2021). According to GDF’s data,
percentage of the illegal cutting is 67, also the fuelwood gathering is 33.
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In eq. 2.14 to calculate the losses from wildfires the BW covers the dead organic matter. It is assumed
that all dead organic matter is burned in wildfires in this category. It is also assumed that average
biomass during wildfires is burned with 44 percent of burning productivity (GDF 2008-2016).
iii.
All biomass gains and losses have been summed up from strata to get estimates for FF.
iv.
Annual change in carbon stock in biomass has been estimated as a difference between ∆CG and
∆CL.
Table 6.13 The Average basic wood density and national BCEF’s factors (Tolunay, 2013)
Vegetation
type
Coniferous
Deciduous
Basic wood
density
(tonnes/m3)
BCEFI
(tonnes/m3)
BCEFs
(tonnes/m3)
BCEFR
(tonnes/m3)
0.446
0.541
0.563
0.612
0.541
0.709
0.717
0.797
Soil and dead organic matter
Currently, no changes in CSC in deadwood, litter and soil (Tier 1 assumption) are reported due to lack
of data related to any change in soil and DOM carbon stocks in FL-FL.
Land Converted to Forest land
The annual increments and coefficients used for Land Converted to Forest Land were;
Table 6.14 Coefficients used to calculate CS and CSC in L-FL
Root to Shoot Ratio
Forest Type
Annual Increment
m /ha
3
BCEFI
tonnes d.m. below-ground
CF tonnes
biomass/tonnes above-
C/tonnes dm
ground d.m. biomass
Forest Deciduous
0.691
0.7092
0.463
0.483
Forest Coniferous
0.691
0.5412
0.403
0.513
Forest Mixed
0.691
0.6252
0.483
0.493
Forest Degraded
0.691
0.6252
0.443
0.493
1Forest
Management Department
2Tolunay
3IPCC
310
(2013)
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The conversion period is accepted as 20 years. It is assumed that there is no change in the dead wood
carbon stocks for land converted to forest land categories.
The DOM C stock is assumed to accumulate in 20 years conversion time to reach a steady state given
in Table 6.15 below (Tolunay and Çömez, 2008) :
Table 6.15 Carbon stocks in DOM used for all forest areas in Türkiye
DOM
(tonnes/ha)
Coniferous
7.51
± 6.61 (n=601)
Deciduous
3.09
± 1.58 (n=368)
The below soil C stock values have been applied in case of land use conversions. The stock values have
been calculated by the Research Units of Ministry of Agriculture and Forestry.
Table 6.16 SOC stocks of forests disaggregated for ecozones
C stock
Ecozone
Forest land (tC/ha)
Mediterranean Mountain zone
SOC ref
51.53
46.96
46.08
37.77
East Anatolian steppe
48.41
47.99
East Anatolian deciduous forest zone
45.14
41.30
Euxine-Colchic deciduous forest
51.90
49.66
Central Anatolian steppe
49.92
40.41
Aegean Inland deciduous and coniferous forest
50.88
42.53
55.05
54.57
Mediterranean coastal zone deciduous and
coniferous forest
North Anatolian deciduous, coniferous and
mixed forest
Reference to the 2006 IPCC equations: Vol 4., Ch. 2: 2.16 / 2.19
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Uncertainties and Time-Series Consistency:
According to para 15 of 24/CP19 Annex I Parties shall quantitatively estimate the uncertainty of the
data used for all source and sink categories using at least Approach 1, and report uncertainties for at
least the base year (1990) and last reported year (2021), as well as the trend uncertainty between
these two years.
There are two approaches presented in the 2006 IPCC guidelines, which use simple error propagation
equations and Monte Carlo or similar techniques, respectively. The first approach has been used with
the equations IPCC (2006) equations: Vol. 1, Ch. 3: 3.1 / 3.2.
Uncertainty of input data is provided by underlying systems. Uncertainty of activity data is derived for
11x11 land categories for the latest reported year 2015. Under the current stage of finalization of land
use mapping, still, preliminary values of the uncertainty of activity data are estimated in the range of
5% for land remaining in the same category and 10% for land being in conversion among various land
categories.
Uncertainty (in %, consistent with 2006 IPCC Guidelines) for CSCs is provided according to various
underlying national sources and references.
Uncertainty propagation tracks GHG inventory calculation, i.e. from the most detailed input activity data
and CSC/EF to GHG estimates at the land use subcategory and LULUCF sector. Uncertainty is propagated
following Tier 1 with Eq. 3.2 of 2006 IPCC Guidelines where uncertain data is added or subtracted, and
Eq. 3.1 of 2006 IPCC Guidelines where uncertain data is multiplied or divided.
Estimation of GHG inventory uncertainty covers completely the national territory for the year 1990 as
the base year and last reported year (2021). Wherever CSC in a C pool is reported as NO or NA such
estimates are not included in the Tier 1 propagation of uncertainty.
For all C pools subject to 20 year transition the uncertainty estimation considers aggregation of two
terms:
a) uncertainty associated with the CSC for the area in the first year of the conversion which involves
the uncertainty of C stocks in land use from before and after conversion, and the uncertainty of CSC in
the first year after the conversion, and,
b) uncertainty for the rest of the area reported under respective conversion cumulated from previous
years.
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Table 6.17 shows the relative uncertainty for CSC overall for land subcategories.
Table 6.17 Uncertainty calculation results for the whole LULUCF sector
Summary
BY* (1990)
LRY** (2021)
4A1
51%
50%
4A2
0%
57%
4B1
7%
10%
4B2
0%
47%
4C1
0%
0%
4C2
0%
149%
4D1
0%
0%
4D2
0%
86%
4E1
0%
0%
4E2
0%
26%
4F1
0%
0%
4F2
0%
18%
Table 4(I)
0%
0%
Table 4(II)
0%
0%
Table 4(III)
0%
75%
Table 4(IV)
0%
387%
Table 4(V)
54%
54%
50.80%
51.14%
LULUCF sector
*BY: Base Year ; ** LRY:Last Reported Year
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The summary table for the uncertainty in Forest land categories (FL-FL and L-FL) is as follows;
Table 6.18 Uncertainty summary table for Forest land subcategories
BY (1990)
LRY (2021)
4A1 – FL-FL
51%
50%
ΔCC in Living Biomass
51%
50%
Annual Loss Living Biomass (ΔCL)
33%
34%
Annual Gain Living Biomass (ΔCG)
35%
35%
Net C stock change in Litter (ΔCC)
NA
NA
Net C stock change in Dead Wood (ΔCC)
NA
NA
Net C stock change in SOM (ΔCC)
NA
NA
4A2 – L-FL
0%
57.1%
ΔCC in Living Biomass
NA
4.9%
Annual Loss Living Biomass (ΔCL)
NA
22.6%
Annual Gain Living Biomass (ΔCG)
NA
4.9%
Net C stock change in Dead Wood (ΔCC)
NA
NA
Net C stock change in Litter (ΔCC)
NA
300.7%
Net C stock change in SOM (ΔCC)
NA
47.0%
Forest land Remaining Forest land
Land Converted to Forest land
Two forest inventories were carried out by the GDF for 1972 and 1999. Forestry Statistics has been
started since 2007. The data on growing stocks and annual increments during the 1990-2007 period
were calculated by interpolation among data from these three inventories (1972, 1999 and 2007). Thus,
the annual increases of growing stocks and volume increments were assumed as linear. The Forestry
Statistics tables have been published annually by GDF since 2007.
The time series consistency of area data has been significantly increased by using the same satellite
images and methods as explained above. The statistics on the forest fires and commercial round wood
production for the same period and fuelwood gathering data were also provided by Forestry Statistics.
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Source-Specific QA/QC and Verification:
The QA/QC procedure has been realized in the framework of a plan developed and carried out by
TurkStat the national inventory agency. The sector specific QA/QC has been realized by the LULUCF
experts in and out of the agencies.
Recalculation:
The Forest Land Remaining Forest Land Category was recalculated due to an update of the annual
increment values for the years between 1990-2019 with increment borer by the ongoing National Forest
Inventory Program of GDF. Updated annual increment values by field measurement are reported in
Table 6.7. Annual increment values were also changed in the Forestry Statistics for whole time series.
All the changes by recalculating are demonstrated in Table 6.19.
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Table 6.19 Changes by the recalculation of Forest Land Remaining Forest Land
subcategory
Recalculated Values
Old Values
Changes(%)
Year
(ktonnes CO2)
(ktonnes CO2)
1990
-52 830.00
-63 604.96
20.40
1991
-54 395.61
-65 080.08
19.64
1992
-54 130.19
-64 723.50
19.57
1993
-54 333.53
-64 854.30
19.36
1994
-56 160.99
-66 605.68
18.60
1995
-54 962.96
-65 327.37
18.86
1996
-55 773.70
-65 327.89
17.13
1997
-59 000.17
-67 725.27
14.79
1998
-60 329.95
-68 223.84
13.08
1999
-61 614.21
-68 690.78
11.49
2000
-57 890.32
-64 375.54
11.20
2001
-61 443.38
-67 313.82
9.55
2002
-68 857.54
-65 536.58
-4.82
2003
-70 265.57
-66 806.09
-4.92
2004
-69 597.62
-65 608.20
-5.73
2005
-69 355.58
-66 598.59
-3.98
2006
-70 281.17
-66 926.69
-4.77
2007
-68 870.02
-66 142.25
-3.96
2008
-63 966.66
-62 383.80
-2.47
2009
-67 380.21
-65 078.58
-3.42
2010
-67 613.57
-65 874.37
-2.57
2011
-69 387.58
-67 507.44
-2.71
2012
-67 152.58
-65 695.42
-2.17
2013
-67 912.29
-67 473.50
-0.65
2014
-68 099.07
-67 109.02
-1.45
2015
-87 668.69
-62 936.81
-28.21
2016
-85 232.65
-62 370.60
-26.82
2017
-90 194.56
-65 323.21
-27.58
2018
-84 849.21
-60 188.20
-29.06
2019
-75 310.53
-53 999.27
-28.30
As explained above the area based AD in the Forest land sector moved from ENVANIS to a spatially
explicit land tracking system. This enabled the production of a consistent land use matrix that
determines the land use and conversions with 1 ha accuracy. On the other hand, removals from L-FL
decreased significantly with the new system. The reason for this was the change in AD.
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Planned Improvement:
The Forest Land is the major category. The removals are based on the increment data while emissions
are on the harvest. An improvement plan has been developed for the sector in the framework of the
LULUCF project. The plan has three basic scales; short (ST), medium (MT) and long terms (LT).
Short term
(2023)
Long term
(2026+)
Medium term
(2025)
The planned improvements for Forest Land category are;
▪
Re-evaluation of the emission/other factors used for living biomass, DOM, and mineral soils (ST,
MT) based on Mediterranean Emission/Other factors Database by the collaboration program of
ONF-GDF.
▪
Estimation of carbon stocks for carbon pools for which emissions are currently not reported,
namely deadwood, litter and mineral soil (MT)
▪
Preparation of input forest data and parameters for some of the existing forest models (e.g.
CBM) to be able for running simulations and making projections of forest development under
different scenarios (MT, LT)
▪
Development and establishment of National Forest Inventory (NFI) based on permanent sample
plot system (LT)
▪
Use a higher Tier level in reporting (MT, LT).
▪
Develop and use allometric equations instead of currently used national BCEF coefficients (MT,
LT).
▪
Preparement of the land use matrix for 2020 or beyond.
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6.3. Croplands (4.B)
Source Category Description:
Estimation of emissions and removals from cropland follows the 2006 IPCC guidelines (Volume 4, Ch.
5). Currently, there are two strata for different crops in Türkiye, namely annual and perennial crops.
Besides, emissions are estimated due to cultivation of organic soil and direct N2O emission from N
mineralization associated with loss of soil organic matter due to land use change or management of
mineral soils.
Figure 6.8 The changes in net emissions and removals in CL-CL and L-CL subcategories
600
500
kt CO2 eq
400
300
200
100
0
-100
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
-200
L - CL
CL - CL
The cropland category is net emissions due to conversions to cropland. The CL-CL subcategory becomes
removals in some years and emissions in others. The main reason for this is the rate of conversions
between annual and perennial crops. The perennial crops are assumed to have larger C stocks compared
to annual crops as explained in the methodology section below. Cropland remaining Cropland and Land
converted to Cropland has been reported under this category.
CSC in aboveground, belowground, organic and mineral soil pools have been calculated and reported.
The Cropland category was a large source in the last submission but has diminished with the change in
emission factors and activity data.
The Cropland covers all perennial and annual crops in agricultural lands. Orchards and poplars are
included in this category.
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Information on Land Classification and Activity Data
The CL-CL area decreases during the reporting period due to conversions to other land uses but stabilize
after around 2010 and increases after 2015 as lands in L-CL are added after 2010 (20 years transition
period).
Figure 6.9 The change in area of CL-CL
27200
27150
27100
Area kha
27050
27000
26950
26900
26850
26800
26750
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
26700
CL -CL
Figure 6.10 The change in area of L-CL
250
150
100
50
0
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Area kHa
200
L-CL
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On the other hand, the area of L-CL increases but not with the same ratio as conversions from croplands.
Thus the cropland area in total decreases during the reporting period.
Land-use definitions and the classification systems
Activity data for cropland remaining cropland have been subdivided into annual and perennial crops.
Cropland category includes all annual and perennial crops including orchards including olives, vineyards
and poplar plantations; the change in all carbon pools has been assumed to be not changing for annual
and perennial crops. The increase in biomass stocks in a single year is assumed to equal biomass losses
from harvest and mortality in that same year. However, CSC have been calculated in case of conversions
between annual and perennial croplands.
Methodological Issues:
Annual cropland remaining annual cropland
Above- and below-ground biomass
For annual crops increase in biomass stocks in a single year is assumed to equal biomass losses from
harvest and mortality in that same year (IPCC 2006).
Dead organic matter
According to Tier 1 method, there is no need to estimate the carbon stock changes for DOM.
Mineral and organic soils
Currently, there is no specific data on management systems in the country to apply reference carbon
stocks and stock change factors. Emissions from organic soil are estimated using the default equation
and emission factors.
Reference to 2006 IPCC equations: Vol. 4., Ch. 2: 2.24 / 2.25 / 2.26
Perennial cropland remaining perennial cropland
Above- and below-ground biomass
At present, the Gain-Loss method has been applied to estimate CSC in biomass pools. The accumulation
rate and rotation period for perennial crops were assumed according to values used by the inventory of
Italy. If perennial crops, such as vineyards, orchards and olive groves can be disaggregated regarding
spatially-explicit activity data, then default values for carbon stocks at maturity, rotation periods,
biomass accumulation rates etc. for these crops can be obtained from the MediNet Biomass Report
(Canaveira et al., 2018). Canaveira P, Manso S, Pellis G, Perugini L, De Angelis P, Neves R, Papale D,
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Paulino J, Pereira T, Pina A, Pita G, Santos E, Scarascia-Mugnozza G, Domingos T, and Chiti T (2018).
Biomass Data on Cropland and Grassland in the Mediterranean Region. Final Report for Action A4 of
Project MediNet. Available at https://www.lifemedinet.com/documents. Reference to 2006 IPCC
equation: Vol. 4., Ch. 2: 2.7
Since the size of loss due to harvesting is usually not available for perennial woody biomass, the CSC in
living biomass has been assumed to be compensated with the harvest of the trees. Hence C gains due
to the increment of the perennial trees are neutralized by the loss due to cutting of the trees at
100/rotation period of the total perennial crops area. The rotation period of perennial croplands is
assumed to be 20 years, with 15 tons C/ha when mature. Thus the increment is 0.75 tons C/ha/yr.
Dead organic matter
According to Tier 1 method the carbon stock changes for DOM has not been estimated. If specific
national data on different crop and climate types and management practices or periodic inventories are
improved then Gain-Loss or Stock-Difference method, respectively, can be applied.
Mineral and organic soils
Currently, there is no specific data on management systems in the country to apply reference carbon
stocks and stock change factors. Tier 1 method can be applied when these data become available.
Emissions from organic soil have been estimated using a default equation and emission factor.
Reference to 2006 IPCC equations: Vol. 4., Ch. 2: 2.24 / 2.25 / 2.26
Annual cropland converted to perennial cropland
The 2006 IPCC guidelines do not include any specific method for conversions between annual and
perennial cropland. As carbon accumulation rates and soil carbon stocks in these two cropland
subcategories are different, more accurate estimation of emissions and removals is needed.
Annual CSC in biomass has been estimated using the equation below:
Annual change in biomass = conversion area for a transition period of 20 years * ΔCgrowth + annual area
of currently converted land * ΔCconversion
ΔCconversion = Cafter - Cbefore
Cafter = carbon stock immediately after conversion (at Tier 1 assume Cafter = 0)
Cbefore = carbon stock of annual crop before conversion (IPCC default value = 5 t C ha-1)
ΔCgrowth = carbon accumulation rate of perennial crops (0.75 t C ha-1 yr-1)
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The biomass loss is accounted only for the year of conversion, thus ΔCconversion must be multiplied by
annual area (i.e. area in the year of conversion).
Reference to 2006 IPCC equations: Vol. 4., Ch. 2: 2.15 / 2.16
The calculation spreadsheet for annual-perennial conversion is as follows;
Table 6.20 Coefficients and CS values used in annual/perennial conversions in cropland
category
Ecozones
Mediterranean Mountain
zone
NAI Y1
Loss Y1
ΔCG
ΔCL
(tC/yr/ha)
(tC/yr/ha)
0.75
BAFTER
BBEFORE
CSC Y1
NAI Y2
(tC/yr)
(tC/yr
(tC/ha/yr)
(tC/ha/yr)
0
0
5
-4.25
0.75
0.75
0
0
5
-4.25
0.75
0.75
0
0
5
-4.25
0.75
0.75
0
0
5
-4.25
0.75
0.75
0
0
5
-4.25
0.75
0.75
0
0
5
-4.25
0.75
0.75
0
0
5
-4.25
0.75
0.75
0
0
5
-4.25
0.75
Mediterranean coastal
zone deciduous and
coniferous forest
East Anatolian steppe
East Anatolian deciduous
forest zone
Euxine-Colchic deciduous
forest
Central Anatolian steppe
Aegean Inland deciduous
and coniferous forest
North Anatolian
deciduous, coniferous
and mixed forest
As seen from Table CS for annual crops is 5 tC/ha and is lost in the first year of conversion while the
planted seedlings grow with 0.75 tC/ha per year for the next 20 years until the land is allocated as CLCL.
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Dead organic matter
According to Tier 1 method, carbon stock changes for DOM are assumed to be not changing.
Mineral and organic soil
According to Tier 2 method country-specific carbon stocks have been used to estimate annual change
in organic carbon stocks in mineral soil. Country-specific carbon stocks have been calculated by the
TAGEM (General Directorate of Agricultural Research) and used for both cropland subcategories in case
of conversion, default equation, assuming a transition period of 20 years has been used. Emissions from
organic soil should be estimated using a default equation and emission factors.
Reference to 2006 IPCC equations: Vol. 4., Ch. 2: 2.24 / 2.25 / 2.26
The below default coefficients have been employed to calculate CSC in mineral soils in case of
conversions (between cropland subcategories or LULUCF land use categories) CS for annual and
perennial croplands. The SOC of perennial crops has been assumed to be same as SOCref.
Table 6.20a Coefficients and soil CS values used in annual/perennial conversions in
cropland category
SOC ref
CSannualcrops
CSperennialcrops
(tC/ha)
(tC/ha)
(tC/ha)
46.96
40.22
46.96
37.77
29.62
37.77
East Anatolian steppe
47.99
38.90
47.99
East Anatolian deciduous forest zone
41.30
30.44
41.30
Euxine-Colchic deciduous forest
49.66
38.68
49.66
Central Anatolian steppe
40.41
32.14
40.41
42.53
30.99
42.53
54.57
34.29
54.57
Ecozone
Mediterranean Mountain zone
Mediterranean coastal zone deciduous
and coniferous forest
Aegean Inland deciduous and
coniferous forest
North Anatolian deciduous, coniferous
and mixed forest
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Perennial cropland converted to annual cropland
Annual CSC in biomass on areas of conversion from perennial cropland to annual cropland has been
estimated by the same equation as for the opposite management change with the difference that only
annual area of currently converted land is considered here because the gains of the annual crop during
land use changes to annual cropland are accounted only once.
The estimation of CSC in biomass has been performed using the equation below:
Annual change in biomass = annual area of currently converted land *(ΔCconversion + ΔCgrowth)
ΔCconversion = Cafter - Cbefore
Cafter = carbon stock immediately after conversion (at Tier 1 assume Cafter = 0)
Cbefore = carbon stock of annual/perennial crop before conversion (15 t C ha-1)
ΔCgrowth = carbon accumulation rate of annual/perennial crop (IPCC default value = 5 t C ha-1)
Dead organic matter
According to Tier 1 method, carbon stock changes for DOM are assumed to be not changing.
Mineral and organic soil
According to Tier 2 method country-specific carbon stocks have been used to estimate annual change
in organic carbon stocks in mineral soil. Country-specific carbon stocks have been calculated by the
TAGEM (General Directorate of Agricultural Research) and used for both cropland subcategories in case
of conversion, default equation, assuming a transition period of 20 years has been used. Emissions from
organic soil should be estimated using a default equation and emission factors.
Reference to 2006 IPCC equations: Vol. 4., Ch. 2: 2.24 / 2.25 / 2.26
Land converted to cropland
Above- and below-ground biomass
Changes in biomass carbon stocks have been estimated according to Tier 1/Tier 2 method with spatiallyexplicit activity data. Conversions from all other land uses (e.g. from forest land, grassland etc.) to
cropland are likely to occur in the country. The principle of estimating the CSC in biomass in land
converted to cropland is the same as described in the subcategories annual cropland converted to
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Land Use, Land Use Change and Forestry
perennial and vice versa, depending on conversion to which cropland subcategory happened (i.e. annual
or perennial cropland).
Below calculation algorithms have been applied for land conversions to Cropland;
In case of forest land converted to annual and perennial cropland;
Table 6.21 Coefficients and CS values used in L-CL category
For FL-CLannual
Ecozone
i.e.
Mediterranean
Mountain zone
CF
Forest
Deciduous
Forest
Coniferous
Forest Mixed
Forest
Degraded
ΔCG
ΔCL
BAFTER
BBEFORE
CSC Y1
CSC Y2
(tC/ha/yr)
(tC/yr/ha)
(tC/yr/ha)
(tC/yr/ha)
(tC/ha)
(tC/ha/yr)
0.48
5.00
0
0
41.97
-36.97
0
0.51
5.00
0
0
64.80
-59.80
0
0.49
5.00
0
0
52.35
-47.35
0
0.49
5.00
0
0
4.051
0.95
0
0.48
0.75
0
0
41.97
-41.22
0.75
0.51
0.75
0
0
64.80
-64.05
0.75
0.49
0.75
0
0
52.35
-51.60
0.75
0.49
0.75
0
0
4.05
-3.30
0.75
For FL-CLperennial
i.e.
Mediterranean
Mountain zone
Forest
Deciduous
Forest
Coniferous
Forest Mixed
Forest
Degraded
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In case of grassland converted to annual and perennial cropland;
For GL-CLannual
Ecozone
ΔCG
ΔCL
BAFTER
BBEFORE
CSC Y1
CSC Y2
(tC/yr/ha)
(tC/yr/ha)
(tC/yr/ha)
(tC/ha)
(tC/ha/yr)
(tC/ha/yr)
5.00
0
0
1.86
3.14
0
0.75
0
0
1.86
-1.11
0.75
i.e.
Mediterranean
GL-CLann
Mountain zone
For GL-CLannual
i.e.
Mediterranean
GL-CLper
Mountain zone
In case of wetland (managed/unmanaged) converted to annual and perennial cropland;
For WLmanaged/unmanaged-CLannual
ΔCG
Ecozone
i.e.
Mediterranean
Mountain zone
i.e.
Mediterranean
Mountain zone
WLmanCLann
WLunma
n-CLann
ΔCL
BAFTER
BBEFORE
CSC Y1
CSC Y2
(tC/ha/yr)
(tC/yr/ha)
(tC/yr/ha)
(tC/yr/ha)
(tC/ha)
(tC/ha/yr)
5.00
0
0
1.86
3.14
0
5.00
0
0
1.86
3.14
0
For WLmanaged/unmanaged-CLperennial
i.e.
Mediterranean
Mountain zone
i.e.
Mediterranean
Mountain zone
WLmanCLper
WLunma
n-CLper
0.75
0
0
1.86
-1.11
0.75
0.75
0
0
1.86
-1.11
0.75
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In case of settlement converted to annual and perennial cropland;
For SL-CLannual
Ecozone
i.e.
Mediterranean
Mountain zone
SLCLann
ΔCG
ΔCL
BAFTER
BBEFORE
CSC Y1
CSC Y2
(tC/yr/ha)
(tC/yr/ha)
(tC/yr/ha)
(tC/ha)
(tC/ha/yr)
(tC/ha/yr)
5.00
0
0
5.03
-0.03
0
0.75
0
0
5.03
-4.28
0.75
For SL-CLperennial
i.e.
Mediterranean
Mountain zone
SLCLper
In case of other land converted to annual and perennial cropland;
For OL-CLannual
Ecozone
i.e.
Mediterranean
Mountain zone
OLCLann
ΔCG
ΔCL
BAFTER
BBEFORE
CSC Y1
CSC Y2
(tC/yr/ha)
(tC/yr/ha)
(tC/yr/ha)
(tC/ha)
(tC/ha/yr)
(tC/ha/yr)
5
0
5
0
0
0
0.75
0
0
0
0.75
0.75
For OL-CLperennial
i.e.
Mediterranean
Mountain zone
OLCLper
Dead organic matter
A Tier 1 method takes into account the estimation of CSC in dead organic matter only for major
conversion categories (e.g. forest land to cropland). It is assumed that all dead organic matter is
removed in the year of conversion, so there is no accumulation in land converted to cropland afterwards.
Reference to 2006 IPCC equation: Vol. 4., Ch. 2: 2.23,
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Table 6.22 Coefficients and CS values used in L-CL category
For FL-CLannual/perennial
Ecozone
i.e. Mediterranean
Forest
Mountain zone
Deciduous
Forest
Coninferous
Forest Mixed
Forest
Degraded
CSC LT
CSC DW
CSC DOM
(tC/ha)
(tC/ha)
(tC/ha)
0.50
-3.09
-0.49
-3.58
0.37
0.50
-7.51
-0.36
-7.87
0.37
0.50
-5.30
-0.42
-5.72
0.37
0.50
0.00
-0.03
-0.03
CFlitter
CFdw
0.37
Mineral and organic soil
The Tier 2 method has been applied here, as country-specific reference carbon stocks were available
for all land categories. The general approach, assuming the 20-year transition period after which the
soil reaches a new equilibrium, has been used for land use changes to cropland. In case organic soil is
subject to this type of land-use change, emissions have been estimated using the default emission factor
and method.
Reference to 2006 IPCC equations: Vol. 4., Ch. 2: 2.24 / 2.25 / 2.26
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Land Use, Land Use Change and Forestry
In case of forest land (FL) converted to annual and perennial cropland;
Table 6.23 Coefficients and soil CS values used in L-CL category
C stock
Ecozone
C stock
Forest land
SOC
Cropland
CSC Y1
NAI Y2
(tC/ha)
ref
(tC/ha)
(tC/ha/yr)
(tC/ha/yr)
51.53
46.96
40.22
-0.57
-0.57
46.08
37.77
29.62
-0.82
-0.82
FL-CLann
48.41
47.99
38.90
-0.48
-0.48
FL-CLann
45.14
41.30
30.44
-0.74
-0.74
FL-CLann
51.90
49.66
38.68
-0.66
-0.66
FL-CLann
49.92
40.41
32.14
-0.89
-0.89
FL-CLann
50.88
42.53
30.99
-0.99
-0.99
FL-CLann
55.05
54.57
34.29
-1.04
-1.04
Mediterranean Mountain zone FL-CLper
51.53
46.96
46.96
-0.23
-0.23
46.08
37.77
37.77
-0.42
-0.42
FL-CLper
48.41
47.99
47.99
-0.02
-0.02
FL-CLper
45.14
41.30
41.30
-0.19
-0.19
FL-CLper
51.90
49.66
49.66
-0.11
-0.11
FL-CLper
49.92
40.41
40.41
-0.48
-0.48
FL-CLper
50.88
42.53
42.53
-0.42
-0.42
FL-CLper
55.05
54.57
54.57
-0.02
-0.02
Forest Type
FL-CLannual
Mediterranean Mountain zone FL-CLann
Mediterranean coastal zone
deciduous
and
coniferous FL-CLann
forest
East Anatolian steppe
East
Anatolian
deciduous
forest zone
Euxine-Colchic
deciduous
forest
Central Anatolian steppe
Aegean Inland deciduous and
coniferous forest
North Anatolian deciduous,
coniferous and mixed forest
FL-CLperennial
Mediterranean coastal zone
deciduous
and
coniferous FL-CLper
forest
East Anatolian steppe
East
Anatolian
deciduous
forest zone
Euxine-Colchic
deciduous
forest
Central Anatolian steppe
Aegean Inland deciduous and
coniferous forest
North Anatolian deciduous,
coniferous and mixed forest
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In case of grassland (GL) converted to annual and perennial cropland;
C stock
C stock
Grassland
Cropland
(tC/ha)
(annual) (tC/ha)
46.96
42.26
37.77
East Anatolian steppe
CSC Y1
NAI Y2
(tC/ha/yr)
(tC/ha/yr)
40.22
-0.10
-0.10
33.99
29.62
-0.22
-0.22
47.99
43.19
38.90
-0.21
-0.21
East Anatolian deciduous forest zone
41.30
37.17
30.44
-0.34
-0.34
Euxine-Colchic deciduous forest
49.66
44.69
38.68
-0.30
-0.30
Central Anatolian steppe
40.41
36.37
32.14
-0.21
-0.21
42.53
38.28
30.99
-0.36
-0.36
54.57
49.11
34.29
-0.74
-0.74
46.96
42.26
46.96
0.23
0.23
37.77
33.99
37.77
0.19
0.19
East Anatolian steppe
47.99
43.19
47.99
0.24
0.24
East Anatolian deciduous forest zone
41.30
37.17
41.30
0.21
0.21
Euxine-Colchic deciduous forest
49.66
44.69
49.66
0.25
0.25
Central Anatolian steppe
40.41
36.37
40.41
0.20
0.20
42.53
38.28
42.53
0.21
0.21
54.57
49.11
54.57
0.27
0.27
SOC ref
Ecozone
GL-CLannual
Mediterranean Mountain zone
Mediterranean coastal zone deciduous
and coniferous forest
Aegean Inland deciduous and coniferous
forest
North Anatolian deciduous, coniferous
and mixed forest
GL-CLperennial
Mediterranean Mountain zone
Mediterranean coastal zone deciduous
and coniferous forest
Aegean Inland deciduous and coniferous
forest
North Anatolian deciduous, coniferous
and mixed forest
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In case of wetland (WL) (Managed/Unmanaged) converted to annual and perennial cropland;
C stock
Parameters/C stock in year
SOC ref Wetlands
(tC/yr/ha)
C stock
Cropland
CSC Y1
NAI Y2
(tC/ha/yr) (tC/ha/yr)
(tC/ha)
(annual) (tC/ha)
46.96
42.26
40.22
-0.10
-0.10
37.77
33.99
29.62
-0.22
-0.22
East Anatolian steppe
47.99
43.19
38.90
-0.21
-0.21
East Anatolian deciduous forest zone
41.30
37.17
30.44
-0.34
-0.34
Euxine-Colchic deciduous forest
49.66
44.69
38.68
-0.30
-0.30
Central Anatolian steppe
40.41
36.37
32.14
-0.21
-0.21
42.53
38.28
30.99
-0.36
-0.36
54.57
49.11
34.29
-0.74
-0.74
46.96
42.26
46.96
0.23
0.23
37.77
33.99
37.77
0.19
0.19
East Anatolian steppe
47.99
43.19
47.99
0.24
0.24
East Anatolian deciduous forest zone
41.30
37.17
41.30
0.21
0.21
Euxine-Colchic deciduous forest
49.66
44.69
49.66
0.25
0.25
Central Anatolian steppe
40.41
36.37
40.41
0.20
0.20
42.53
38.28
42.53
0.21
0.21
54.57
49.11
54.57
0.27
0.27
WL-CLannual
Mediterranean Mountain zone
Mediterranean coastal zone deciduous
and coniferous forest
Aegean Inland deciduous and
coniferous forest
North Anatolian deciduous, coniferous
and mixed forest
WL-CLperennial
Mediterranean Mountain zone
Mediterranean coastal zone deciduous
and coniferous forest
Aegean Inland deciduous and
coniferous forest
North Anatolian deciduous, coniferous
and mixed forest
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In case of settlements (SL) converted to annual and perennial cropland;
C stock
Ecozones
C stock
Settlements SOC ref
(tC/ha)
Cropland
(annual) (tC/ha)
CSC Y1
NAI Y2
(tC/ha/yr) (tC/ha/yr)
SL-CLannual
Mediterranean Mountain zone
20.14
46.96
40.22
1.00
1.00
20.14
37.77
29.62
0.47
0.47
20.14
47.99
38.90
0.94
0.94
20.14
41.30
30.44
0.51
0.51
Euxine-Colchic deciduous forest
20.14
49.66
38.68
0.93
0.93
Central Anatolian steppe
20.14
40.41
32.14
0.60
0.60
20.14
42.53
30.99
0.54
0.54
20.14
54.57
34.29
0.71
0.71
20.14
46.96
46.96
1.34
1.34
20.14
37.77
37.77
0.88
0.88
20.14
47.99
47.99
1.39
1.39
20.14
41.30
41.30
1.06
1.06
Euxine-Colchic deciduous forest
20.14
49.66
49.66
1.48
1.48
Central Anatolian steppe
20.14
40.41
40.41
1.01
1.01
20.14
42.53
42.53
1.12
1.12
20.14
54.57
54.57
1.72
1.72
Mediterranean
coastal
zone
deciduous and coniferous forest
East Anatolian steppe
East Anatolian deciduous forest
zone
Aegean
Inland
deciduous
and
coniferous forest
North
Anatolian
deciduous,
coniferous and mixed forest
SL-CLperennial
Mediterranean Mountain zone
Mediterranean
coastal
zone
deciduous and coniferous forest
East Anatolian steppe
East Anatolian deciduous forest
zone
Aegean
Inland
deciduous
and
coniferous forest
North
Anatolian
deciduous,
coniferous and mixed forest
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In case of otherland (OL) converted to annual and perennial cropland;
C stock
Ecozones
C stock
Otherland SOC ref
(tC/ha)
Cropland
(annual) (tC/ha)
CSC Y1
NAI Y2
(tC/ha/yr)
(tC/ha/yr)
OL-CLannual
Mediterranean Mountain zone
12.78
46.96
40.22
1.37
1.37
12.78
37.77
29.62
0.84
0.84
East Anatolian steppe
12.78
47.99
38.90
1.31
1.31
East Anatolian deciduous forest zone
12.78
41.30
30.44
0.88
0.88
Euxine-Colchic deciduous forest
12.78
49.66
38.68
1.30
1.30
Central Anatolian steppe
12.78
40.41
32.14
0.97
0.97
12.78
42.53
30.99
0.91
0.91
12.78
54.57
34.29
1.08
1.08
12.78
46.96
46.96
1.71
1.71
12.78
37.77
37.77
1.25
1.25
East Anatolian steppe
12.78
47.99
47.99
1.76
1.76
East Anatolian deciduous forest zone
12.78
41.30
41.30
1.43
1.43
Euxine-Colchic deciduous forest
12.78
49.66
49.66
1.84
1.84
Central Anatolian steppe
12.78
40.41
40.41
1.38
1.38
12.78
42.53
42.53
1.49
1.49
12.78
54.57
54.57
2.09
2.09
Mediterranean coastal zone deciduous
and coniferous forest
Aegean Inland deciduous and
coniferous forest
North Anatolian deciduous, coniferous
and mixed forest
OL-CLperennial
Mediterranean Mountain zone
Mediterranean coastal zone deciduous
and coniferous forest
Aegean Inland deciduous and
coniferous forest
North Anatolian deciduous, coniferous
and mixed forest
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Uncertainties and Time-Series Consistency:
The time series consistency has been ensured via the new land tracking system as explained in section
6.3.
The same methodology to estimate uncertainty has been employed as 6.4.5 and the below summary
table has been produced.
Table 6.24 Uncertainty summary table for Cropland subcategories
BY (1990)
LRY (2021)
7.3%
9.9%
0.0%
12.6%
Net C stock change in DOM (ΔCC)
NA
NA
Net C stock change in SOM (ΔCC)
7.3%
15.3%
4B2 – L-CL
0%
47%
ΔCC in Living Biomass
NA
46%
Annual Loss Living Biomass (ΔCL)
NA
NA
Annual Gain Living Biomass (ΔCG)
NA
NA
NA
42%
NA
64%
Cropland Remaining Cropland
4B1 – CL-CL
Net C stock change in Living Biomass
(ΔCC)
Land Converted to Cropland
Net C stock change in Dead Organic
Matter (ΔCC)
Net C stock change in SOM (ΔCC)
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5
Source-Specific QA/QC and Verification:
The QA/QC procedure has been realized in the framework of a plan developed and carried out by
TurkStat the national inventory agency. The sector specific QA/QC has been realized during the LULUCF
project activities mentioned above. The calculation procedures have been checked and discussed with
the LULUCF experts in and out of the agencies.
Recalculation:
There is no recalculation for this submission in this category.
Planned Improvement:
The planned improvements for Cropland category are;
▪
Increase from Tier 1 to Tier 2 method in estimating the carbon stock change in living biomass
in Land converted to cropland (MT)
▪
Collection, sampling and/or modelling of carbon stocks in mineral soil at a larger spatial scale
(e.g. consider potential use of National Geospatial Soil Fertility and Soil Organic Carbon
Information System) (MT)
▪
Data collection about management systems (land use, tillage, input) for Cropland remaining
cropland, also through use of existing generalised maps of dominant crops in Türkiye (MT)
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6.4. Grassland (4.C)
Source Category Description:
Grasslands are all lands with non woody vegetation subject to grazing. CSC in grasslands is assumed to
be not changing if management is not changed. Actually, there are grassland rehabilitation projects
implemented in the country but conservatively we assumed no change in biomass. We plan to report
these projects as the grassland monitoring system becomes available. Emissions from organic soils are
reported assuming that all grasslands are managed. Default EFs are used in this procedure but the AD
is disaggregated for climate types.
Figure 6.11 The change in net emissions in Grassland category
1000
900
800
CO2 eq
700
600
500
400
300
200
100
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
0
Grasland
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Figure 6.12 The change in area of GL-GL
24300
24250
24200
Area kHa
24150
24100
24050
24000
23950
23900
23850
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
23800
GL -GL
Figure 6.13 The change in area of L-GL
80
70
Area kHa
60
50
40
30
20
10
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
0
L - GL
Methodological Issues:
Grassland remaining grassland (GL-GL)
All carbon pools in GL-GL are assumed to be not changing and thus reported as NO except emissions
from organic soils. A 3.01 k ha of organic soils have been reported in GL-GL subcategory. This caused
a 0.03 k t CO2 eq. of emissions every year during the reporting period. The management in these areas
is not known exactly but is considered as managed to be conservative.
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Land converted to grassland (GL-GL)
Above- and below-ground biomass
Table 6.25 Coefficients and living biomass CS values for L-GL subcategories
Ecozones
NAI Y1
Loss Y1
ΔCG
ΔCL
Forest type
(tC/yr/ha) (tC/yr/ha)
BAFTER
BBEFORE
(tC/yr/ha) (tC/yr/ha)
CSC Y1
(tC/ha/yr)
Forest land converted to Grassland
i.e.
Mediterranean
Mountain zone
Forest
Deciduous
Forest
Coniferous
Forest Mixed
Forest
Degraded
1.86
0
0
41.97
-40.11
1.86
0
0
64.80
-62.94
1.86
0
0
52.35
-50.49
1.86
0
0
4.05
-2.19
0
0
5
-3.14
1.86
0
0
15
-13.14
1.86
0
0
1.86
0.00
1.86
0
0
5.03
-3.17
1.86
0
0
0
1.86
Cropland (annual) converted to Grassland
Croplandannual
1.86
Cropland (perennial) converted to Grassland
Croplandperennial
Wetland converted to Grassland
Grassland
Settlements converted to Grassland
Settlements
Otherland converted to Grassland
Other land
Dead organic matter
CSC converted to wetlands for forest lands are calculated based on the below coefficients and EF. The
CSC for other conversions are assumed to be not occurring.
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Table 6.26 Coefficients and DOM CS values for L-GL subcategories
Ecozones
Forest type
CF litter
CF Dead
Wood
CSC LT
CSC DW
CSC DOM
(tC/ha/yr) (tC/ha/yr) (tC/ha/yr)
Forest land converted to Grassland
i.e.
Forest
Mediterranean
Deciduous
Mountain zone
Forest
Coniferous
Forest Mixed
Forest
Degraded
0.37
0.50
-3.09
-0.49
-3.58
0.37
0.50
-7.51
-0.36
-7.87
0.37
0.50
-5.30
-0.42
-5.72
0.37
0.50
0.00
-0.03
-0.03
Mineral and organic soil
The CSC in mineral soils have been calculated based on national stock values determined by General
Directorate of Agricultural Research. The default conversion duration of 20 years has been applied.
Table 6.27 Coefficients and soil CS values for L-GL subcategories
Ecozone
Mediterranean
Mountain zone
SOC
ref
C stock
Grassland
(tC/ha)
Forest
land
Cropland
Cropland
(Annual) (perennial)
C stock
C stock
C stock
(tC/ha)
(tC/ha)
(tC/ha)
Wetland
Settl.
Otherl.
C stock
C stock
C stock
(tC/ha)
(tC/ha) (tC/ha)
46.96
42.26
51.53
40.22
46.96
42.26
20.14
12.78
37.77
33.99
46.08
29.62
37.77
33.99
20.14
12.78
47.99
43.19
48.41
38.90
47.99
43.19
20.14
12.78
41.30
37.17
45.14
30.44
41.30
37.17
20.14
12.78
49.66
44.69
51.90
38.68
49.66
44.69
20.14
12.78
40.41
36.37
49.92
32.14
40.41
36.37
20.14
12.78
Mediterranean
coastal zone
deciduous and
coniferous forest
East Anatolian
steppe
East Anatolian
deciduous forest
zone
Euxine-Colchic
deciduous forest
Central Anatolian
steppe
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Table 6.27 Coefficients and soil CS values for L-GL subcategories (Cont'd)
Aegean Inland
deciduous and
42.53
38.28
50.88
30.99
42.53
38.28
20.14
12.78
54.57
49.11
55.05
34.29
54.57
49.11
20.14
12.78
coniferous forest
North Anatolian
deciduous,
coniferous and
mixed forest
Uncertainties and Time-Series Consistency:
The time series consistency has been ensured via the new land tracking system as explained in section
6.3.
The same methodology to estimate uncertainty has been employed as 6.4.5 and the below summary
table has been produced.
Table 6.28 Uncertainty summary table for Grassland subcategories
BY (1990)
LRY (2021)
0
0
ΔCC in Living Biomass
NO
NA
Annual Loss Living Biomass (ΔCL)
NA
NA
Annual Gain Living Biomass (ΔCG)
NA
NA
Net C stock change in DOM (ΔCC)
NO
NA
Net C stock change in SOM (ΔCC)
0.00
NA
4C2 – L-GL
0%
149%
ΔCC in Living Biomass
NA
32%
Annual Loss Living Biomass (ΔCL)
NA
NA
Annual Gain Living Biomass (ΔCG)
NA
NA
Net C stock change in DOM (ΔCC)
NA
190%
Net C stock change in SOM (ΔCC)
NA
149%
Grassland Remaining Grassland
4C1 – GL-GL
Land Converted to Grassland
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Source-Specific QA/QC and Verification:
The QA/QC procedure has been realized in the framework of a plan developed and carried out
by TurkStat the national inventory agency. The sector specific QA/QC has been realized during the
LULUCF project activities mentioned above. The calculation procedures have been checked and
discussed with the LULUCF experts in and out of the agencies.
Recalculation:
There is no recalculation for this submission in this category.
Planned Improvement:
The planned improvements for Grassland category are;
▪
Re-evaluation of the estimation of emissions due to drainage of organic soil (MT)
▪
Check for the size of emission factors for the subcategory Land converted to grassland (MT)
▪
Verification of assumptions by surveying national research studies and papers (ST, MT)
▪
Data collection about management systems (land use, management, input) for Grassland
remaining grassland (MT, LT)
▪
Estimation of carbon stock changes in mineral soil for Grassland remaining grassland, using a
default method (applying SOCREF and stock change factors) (MT)
▪
Modelling of carbon stocks in mineral soil at a larger spatial scale (e.g. considering potential use
of National Geospatial Soil Fertility and Soil Organic Carbon Information System) (MT, LT)
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6.5. Wetlands (4.D)
Source Category Description:
Emissions/removals from wetlands remaining wetlands are currently assumed to be not occurring. Two
subcategories are currently included under the wetlands remaining wetlands in the CRF table 4.D of
Türkiye, namely peat extraction remaining peat extraction and flooded land remaining flooded land.
All carbon pools in WL-WL, except peat extraction, are assumed to be unchanged, and thus reported
as NO. Information is given in Tables 29 and 30. Because OL-WL emissions are calculated at a negligible
level, they are reported with the notation key “NE” in accordance with paragraph 37(b) of the UNFCCC
Annex I inventory reporting guide.
Since the biomass and soil organic carbon emission coefficients we used in Grassland areas were the
same as the biomass and soil organic carbon emission coefficients we used for wetlands areas, it was
assumed that there was no gain or loss. Therefore, it is reported as NO. With the biomass and soil
organic carbon emission coefficients we used for wetlands areas, it is considered that the gain is
relatively low for cropland areas. It is entered as NE in the CRF because it is assumed that the loss is
not significant in CL-WL transformations.
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Figure 6.14 The emissions/removals from wetlands category
800
700
kt CO2 eq
600
500
400
300
200
100
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
0
Wetlands
As seen from the figure above the emissions in L-WL were around 100 kt CO2 eq. and stable. In 2013
the emissions peaked and then dropped in 2015 and even turned to be a slight removal. In 2016 and
2017 the emissions rise again. The driver of the fluctuations in emissions was caused by emissions from
living biomass pools due to land conversions. The emission declined again in 2018-2019-2020.
Estimation of emissions and removals from wetlands follows the 2006 IPCC guidelines (Volume 4, Ch.
7) and 2013 Wetlands Supplement. Wetlands include any land that is covered or saturated by water for
all or part of the year, and that does not fall into the Forest Land, Cropland, or Grassland categories
(IPCC 2006). In wetlands category emissions are estimated only for managed wetlands due to human
activity, such as drainage, rewetting, dam construction etc.
Information on Land Classification and Activity Data
The wetland managed until 2015 has steadily increased, mostly resulting in emissions.
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Figure 6.15 a The change in area of managed wetlands
1900
1850
Area kHa
1800
1750
1700
1650
1600
1550
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
1500
Wetlands
Figure 6.15 b The change in area of unmanaged wetlands
1352
1350
1348
Area kHa
1346
1344
1342
1340
1338
1336
1334
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
1332
Wetlands
Land-use definitions and the classification systems
All human made reservoirs are included in the managed wetlands category while natural water bodies
are in the unmanaged wetlands subcategory.
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Methodological Issues:
Wetland remaining wetland (WL-WL)
All carbon pools in WL-WL except peat extraction are assumed to be not changing and thus reported as
NO. The activity data used in peat extraction is based on permitted area for extraction by the ministry
and depth. We assumed that all permitted area has been subject to production. The on and off site
emissions have been estimated at Tier 1 level with default EFs (IPCC Vol. Chapter 7. Table 7.4, 7.5,
Temperate zone, nutrient poor).
Reference to 2006 IPCC equations: Vol. 4., Ch. 7: 7.2 / 7.3 /7.4 /7.5
Land converted to wetland (L-WL)
Above- and below-ground biomass
Table 6.29 Coefficients and living biomass CS values for L-WL subcategories
Ecozones
Forest type
NAI Y1
Loss Y1
ΔCG
ΔCL
(tC/yr/ha)
(tC/yr/ha)
1.86
0
0
41.97
-40.11
1.86
0
0
64.80
-62.94
1.86
0
0
52.35
-50.49
1.86
0
0
4.05
-2.19
0
0
5
-3.14
1.86
0
0
15
-13.14
0.00
0
1.86
1.86
0.00
1.86
0
0
5.03
-3.17
1.86
0
0
0
1.86
BAFTER
BBEFORE
CSC Y1
(tC/yr/ha) (tC/yr/ha) (tC/ha/yr)
Forest land converted to Wetland
i.e. Mediterranean Forest
Mountain zone
Deciduous
Forest
Coniferous
Forest Mixed
Forest
Degraded
Cropland (annual) converted to Wetland
Croplandannual
1.86
Cropland (perennial) converted to Wetland
Grassland converted to Wetland
Settlements converted to Wetland
Otherland converted to Wetland
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Dead organic matter
CSC converted to wetlands for forest lands are calculated based on the below coefficients and EF. The
CSC for other conversions are assumed to be not occurring. It is assumed that there is no DOM in nonForestland.
Table 6.30 Coefficients and DOM CS values for L-WL subcategories
Ecozones
Forest type
CF Dead
CSC LT
Wood
(tC/ha/yr)
0.37
0.50
-3.09
-0.49
-3.58
0.37
0.50
-7.51
-0.36
-7.87
0.37
0.50
-5.30
-0.42
-5.72
0.37
0.50
0.00
-0.03
-0.03
CF litter
CSC DW
CSC DOM
(tC/ha/yr) (tC/ha/yr)
Forest land converted to Wetland
i.e.
Mediterranean
Mountain zone
Forest
Deciduous
Forest
Coniferous
Forest Mixed
Forest
Degraded
Mineral and organic soil
The CSC in mineral soils have been calculated based on national stock values determined by General
Directorate of Agricultural Research. The default conversion duration of 20 years has been applied.
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Table 6.31 Coefficients and soil CS values for L-WL subcategories
SOC
Ecozone
ref
Mediterranean
Mountain zone
C stock
Wetlands
(tC/ha)
Forest
land
Cropland
Cropland
(Annual) (perennial)
C stock
C stock
C stock
(tC/ha)
(tC/ha)
(tC/ha)
Grassland
Settl.
Otherl.
C stock
C stock
C stock
(tC/ha)
(tC/ha)
(tC/ha)
46.96
42.26
51.53
40.22
46.96
42.26
20.14
12.78
37.77
33.99
46.08
29.62
37.77
33.99
20.14
12.78
47.99
43.19
48.41
38.90
47.99
43.19
20.14
12.78
41.30
37.17
45.14
30.44
41.30
37.17
20.14
12.78
49.66
44.69
51.90
38.68
49.66
44.69
20.14
12.78
40.41
36.37
49.92
32.14
40.41
36.37
20.14
12.78
42.53
38.28
50.88
30.99
42.53
38.28
20.14
12.78
54.57
49.11
55.05
34.29
54.57
49.11
20.14
12.78
Mediterranean coastal
zone deciduous and
coniferous forest
East Anatolian steppe
East Anatolian
deciduous forest zone
Euxine-Colchic
deciduous forest
Central
Anatolian
steppe
Aegean
Inland
deciduous
and
coniferous forest
North
Anatolian
deciduous, coniferous
and mixed forest
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Uncertainties and Time-Series Consistency:
The time series consistency has been ensured via the new land tracking system as explained in section
6.3. The same methodology to estimate uncertainty has been employed as 6.4.5 and the below
summary table has been produced.
Table 6.32 Uncertainty summary table for Wetland subcategories
BY (1990)
LRY (2021)
4D1 – WL-WL
0%
0
ΔCC in Living Biomass
NA
NA
Annual Loss Living Biomass (ΔCL)
NA
NA
Annual Gain Living Biomass (ΔCG)
NA
NA
Net C stock change in DOM (ΔCC)
NA
NA
Net C stock change in SOM (ΔCC)
NA
NA
4D2 – L-WL
0%
86%
ΔCC in Living Biomass
NA
33%
Annual Loss Living Biomass (ΔCL)
NA
NA
Annual Gain Living Biomass (ΔCG)
NA
NA
Net C stock change in DOM (ΔCC)
NA
195%
Net C stock change in SOM (ΔCC)
NA
183%
Wetland Remaining Wetland
Land Converted to Wetland
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Source-Specific QA/QC and Verification:
The QA/QC procedure has been realized in the framework of a plan developed and carried out by
TurkStat the national inventory agency. The sector specific QA/QC has been realized during the LULUCF
project activities mentioned above. The calculation procedures have been checked and discussed with
the LULUCF experts in and out of the agencies.
Recalculation:
There is no recalculation for this submission in this category.
Planned Improvement:
The planned improvements for Wetland category are;
▪
Use of Wetlands Supplement more effectively (ST, MT)
▪
Review all existing national and international databases related to wetlands (e.g. Ramsar
Convention on Wetlands, FAOSTAT, Wetlands International, NGO data etc.) (MT)
▪
Expert judgment (e.g. by national soil scientist) about different types of managed wetlands that
are likely to occur in Türkiye (ST, MT)
▪
Collection of activity data regarding specific types of managed wetlands (MT)
▪
Sampling of SOC and estimation of carbon stocks for major soil types of wetlands (MT, LT)
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6.6. Settlements (4.E)
Source Category Description:
The carbon stock change in settlements remaining settlements has been estimated to be not changing.
Land converted to settlements caused emissions to increase until 2010 and then stabilise.
The major driver of the emissions has been conversions from other land uses that resulted in loss of
carbon.
Figure 6.16 The change in net emissions in settlements
500
450
400
kt CO2 eq
350
300
250
200
150
100
50
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
0
Settlements
Information on Land Classification and Activity Data
The area of settlements is increasing constantly with the conversions mainly from cropland and
grassland.
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Figure 6.17 The change in area of settlements
1000
950
Area kHa
900
850
800
750
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
700
SL - SL
Land-use definitions and the classification systems
The emission factors and coefficients for calculating GHG emissions and removals in this category are
based on the results of a national research project entitled “Development of a climate change-ecosystem
services software to support sustainable land planning works” funded by the Scientific and Technical
Research Council of Türkiye with the Project Number 112Y096.
The method we used to develop EFs for Settlements category is based on a modelling study while
representativeness is weak because the study is conducted only in Istanbul. At least 2-3 similar studies
are needed to have higher representativeness. The methodological level is Tier 3 in this estimation
because we performed a gridded spatial analysis modelling approach.
Methodological Issues:
Settlements remaining settlements (SL-SL)
All carbon pools in SL-SL are assumed to be not changing thus reported as NO.
The CS values used in other categories have also been used in this category. The forest land living
biomass C stocks have been taken from ENVANIS, croplands from both IPCC 2006 and neighbouring
countries, grasslands from Serengil et al. (2015). Thus below EFs have been used.
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The CS of settlements has been calculated based on the above values in the context of the TUBITAK
112Y096 project. The following methodology has been applied;
The study area (740 km2) has been divided into 500*500 meter grids,
The land uses in each grid have been determined from SPOT6 2013 satellite image with a
1.5*1.5 meter resolution using supervised classification,
The accuracy check has been performed with 1000 plots with over 90 percent accuracy,
The land use in each grid has been multiplied by carbon stocks given in Table 6.20.
The impervious areas in each grid have been grouped under 5 classes that are >20 percent,
>40 percent, >60 percent, and >80 percent. The project area has been classified into 4
settlement intensity classes in this way (Table 6.33).
Table 6.33 Total carbon stocks calculated for various settlements intensity classes
(Serengil et al., 2015)
Settlement class
Settlement intensity
(SC)
(% imperviousness)
Sample size
(t C /ha)
σ(t C /ha)
(#)
1
>20
85.27
74.19
1 145
2
>40
51.87
41.85
697
3
>60
32.04
25.32
438
4
>80
17.26
13.73
258
The weighted average for settlement land cover has been calculated as 25.17 t C/ha in total 20.14 Mg
C/ha in biomass, and 5.03 Mg C/ha in soil pools.
The settlement intensity and CS in the study are of the TUBITAK 112Y096 is given in Figure 6.18 and
Figure 6.19
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Figure 6.18 Impervious areas in the study area (Alibeyköy, Sazlıdere and Kağıthane
watersheds in Istanbul)
Figure 6.19 Carbon intensity in the study area (Alibeyköy, Sazlıdere and Kağıthane
watersheds in Istanbul)
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Land converted to settlements (L-SL)
Above- and below-ground biomass
Table 6.34 Coefficients and living biomass CS values for L-SL subcategories
Ecozones
NAI Y1
Loss Y1
ΔCG
ΔCL
(tC/yr/ha)
(tC/yr/ha)
Forest Deciduous
5.03
0
0
41.97
-36.94
Forest Coniferous
5.03
0
0
64.80
-59.77
Forest Mixed
5.03
0
0
52.35
-47.32
Forest Degraded
5.03
0
0
4.05
0.98
0
0
5
0.03
5.03
0
0
15
-9.97
5.03
0
0
1.86
3.17
5.03
0
0
1.86
3.17
5.03
0
0
0
5.03
Forest type
BAFTER
BBEFORE
CSC Y1
(tC/yr/ha) (tC/yr/ha) (tC/ha/yr)
Forest land converted to Settlements
i.e.
Mediterranean
Mountain zone
Cropland (annual) converted to Settlements
Croplandannual
5.03
Cropland (perennial) converted to Settlements
Grassland converted to Settlements
Wetlands converted to Settlements
Otherland converted to Settlements
Dead organic matter
CSC converted to settlements from forest lands are calculated based on the below coefficients and EF.
The CSC for other conversions are assumed to be not occurring. It is assumed that there is no DOM in
non-Forestland.
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Table 6.35 Coefficients and DOM CS values for L-SL subcategories
Ecozones
Forest type
CF litter
CF Dead
Wood
CSC LT
CSC DW
CSC DOM
(tC/ha/yr) (tC/ha/yr) (tC/ha/yr)
Forest land converted to Wetland
i.e. Mediterranean
Mountain zone
Forest Deciduous
0.37
0.50
-3.09
-0.49
-3.58
Forest Coniferous
0.37
0.50
-7.51
-0.36
-7.87
Forest Mixed
0.37
0.50
-5.30
-0.42
-5.72
Forest Degraded
0.37
0.50
0.00
-0.03
-0.03
Mineral and organic soil
The CSC in mineral soils have been calculated based on national stock values determined by General
Directorate of Agricultural Research. The default conversion duration of 20 years has been applied.
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Table 6.36 Coefficients and soil CS values for L-SL subcategories
Ecozone
Mediterranean
Mountain zone
SOC
ref
C stock
Settl.
(tC/ha)
Forest
Cropland
Cropland
land
(Annual)
(perennial)
C stock
C stock
C stock
(tC/ha)
(tC/ha)
(tC/ha)
Grassland
Wetland
Otherl.
C stock
C stock
C stock
(tC/ha)
(tC/ha)
(tC/ha)
46.96
20.14
51.53
40.22
46.96
42.26
42.26
12.78
37.77
20.14
46.08
29.62
37.77
33.99
33.99
12.78
47.99
20.14
48.41
38.90
47.99
43.19
43.19
12.78
41.30
20.14
45.14
30.44
41.30
37.17
37.17
12.78
49.66
20.14
51.90
38.68
49.66
44.69
44.69
12.78
40.41
20.14
49.92
32.14
40.41
36.37
36.37
12.78
42.53
20.14
50.88
30.99
42.53
38.28
38.28
12.78
54.57
20.14
55.05
34.29
54.57
49.11
49.11
12.78
Mediterranean coastal
zone deciduous and
coniferous forest
East Anatolian steppe
East Anatolian
deciduous forest zone
Euxine-Colchic
deciduous forest
Central Anatolian
steppe
Aegean Inland
deciduous and
coniferous forest
North Anatolian
deciduous, coniferous
and mixed forest
Uncertainties and Time-Series Consistency:
The time series consistency has been ensured via the new land tracking system as explained in section
6.3.
The same methodology to estimate uncertainty has been employed as 6.4.5 and the below summary
table has been produced.
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Table 6.37 Uncertainty summary table for Settlement subcategories
BY (1990)
LRY (2021)
4E1 – SL-SL
0%
0
ΔCC in Living Biomass
NA
NA
Annual Loss Living Biomass (ΔCL)
NA
NA
Annual Gain Living Biomass (ΔCG)
NA
NA
Net C stock change in DOM (ΔCC)
NA
NA
Net C stock change in SOM (ΔCC)
NA
NA
4E2 – L-SL
0%
26%
ΔCC in Living Biomass
NA
24%
Annual Loss Living Biomass (ΔCL)
NA
NA
Annual Gain Living Biomass (ΔCG)
NA
NA
Net C stock change in DOM (ΔCC)
NA
97%
Net C stock change in SOM (ΔCC)
NA
27%
Settlement Remaining Settlement
Land Converted to Settlement
Source-Specific QA/QC and Verification:
The QA/QC procedure has been realized in the framework of a plan developed and carried out by
TurkStat the national inventory agency. The sector specific QA/QC has been realized during the LULUCF
project activities mentioned above. The calculation procedures have been checked and discussed with
the LULUCF experts in and out of the agencies.
Recalculation:
There is no recalculation for this submission in this category.
Planned Improvement:
The planned improvements for Settlement category are;
▪
Update carbon stock changes for all relevant carbon pools for each land use conversion to
settlements (MT, LT)
▪
Extend the study mentioned in the methodology section to other settlement areas and thus
update the CS values (MT, LT)
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6.7. Other land (4.F)
Source Category Description:
Other land category is a net emission due to land converted to other land. However, the amount of land
converted to Other land is quite low. It is assumed that other land may have organic carbon in soils but
not in living biomass.
Methodological Issues:
The same conversion principles apply to Other land category. The coefficients and EFs use are as
follows;
Table 6.38 The coefficients and EF used in Other land category
EF
Living Biomass
DOM
Soil
Other land
0
0
12.78
The C stocks for living biomass and DOM are assumed to be zero while mineral soil carbon stock is
12.78 based on calculations of General Directorate of Agricultural Research.
Uncertainties and Time-Series Consistency:
The time series consistency has been ensured via the new land tracking system as explained in section
6.3.
The same methodology to estimate uncertainty has been employed as 6.4.5 and the below summary
table has been produced.
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Table 6.39 Uncertainty summary table for Otherland subcategories
BY (1990)
LRY (2021)
4F1 – OL-OL
0%
0
ΔCC in Living Biomass
NA
NA
Annual Loss Living Biomass (ΔCL)
NA
NA
Annual Gain Living Biomass (ΔCG)
NA
NA
Net C stock change in DOM (ΔCC)
NA
NA
Net C stock change in SOM (ΔCC)
NA
NA
4F2 – L-OL
0%
18%
ΔCC in Living Biomass
NA
31%
Annual Loss Living Biomass (ΔCL)
NA
NA
Annual Gain Living Biomass (ΔCG)
NA
NA
Net C stock change in DOM (ΔCC)
NA
139%
Net C stock change in SOM (ΔCC)
NA
19%
Other land Remaining Other land
Land Converted to Other land
6.8. Direct N2O emissions from N inputs to managed soils (4(I))
Source Category Description:
Emissions and removals from this category as not been calculated since the activity data for N inputs
can not be differentiated for the sectors and land uses.
Methodological Issues:
The NO notation key has been used for wetlands and other land. The IE notation key has been used
for forest land and settlements since we presume that N inputs are common in urban areas and some
specific forestry applications (i.e. nurseries) but are included in the amount used for croplands.
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Uncertainties and Time-Series Consistency:
The time series consistency has been ensured via the new land tracking system as explained in section
6.3.
The same methodology to estimate uncertainty has been employed as 6.4.5 and the below summary
table has been produced.
Table 6.40 Uncertainty summary table for 4 (I) category
360
Summary
BY (1990)
LRY(2021)
Table 4(I)
0%
0%
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6.9. Emissions and removals from drainage and rewetting and other
management of organic and mineral soils (4(II))
Source Category Description:
There is no reliable data for drainage/rewetting and other management of organic and mineral soils.
The category has been reported as NO.
Uncertainties and Time-Series Consistency:
The time series consistency has been ensured via the new land tracking system as explained in section
6.3.
The same methodology to estimate uncertainty has been employed as 6.4.5 and the below summary
table has been produced.
Table 6.41 Uncertainty summary table for 4 (II) category
Summary
BY (1990)
LRY (2021)
Table 4(II)
0%
0%
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6.10. N2O emissions from N mineralization/immobilization associated with
loss/gain of soil organic matter resulting from change of land use or
management of mineral soils (4(III))
Source Category Description:
N2O emissions from N mineralization/immobilization associated with loss/gain of soil organic matter
resulting from change of land use or management of mineral soils have been estimated and reported,
according to the 2006 IPCC Guidelines, under this category. N2O emissions from land use conversions
are derived from mineralization of soil organic matter resulting from the conversions that result in C
losses.
Because N2O emissions from mineralization from other lands in CRF table 4(III) are calculated to be
negligible, they are shown with the notation key “NE” in accordance with paragraph 37(b) of the UNFCCC
Annex I inventory reporting guide.
Methodological Issues:
Equation 11.8 in IPCC (2006) has been used to calculate the mineralised N resulting from loss of soil
organic C stocks in mineral soils through Land-use Change or Management Practices. The emissions
due to loss of soil organic C were calculated and reported for all conversions. Gains have not been
calculated since IPCC 2006 Guidelines suggest Tier 3 methods in order to calculate gains.
A default value of 15 as the C:N ratio of the soil organic matter has been used for conversions involving
land-use change from forest or grassland to cropland. A default value of 10 has been used for
conversions or management changes on cropland remaining cropland.
The parameters used in calculations are;
Table 6.42 EFs used for N2O emissions
Parameter (for 1 tC lost)
C/N=15 (all)
C/N=10 (CL)
15
10
EF1 (kgN2O-N/kg N )
0.01
0.01
Factor (N2O-N) to (N2O)
1.57
1.57
0.001047619
0.001571429
C/N ratio
Aggregated factor (t N2O)
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Uncertainties and Time-Series Consistency:
The time series consistency has been ensured via the new land tracking system as explained in section
6.3.
The same methodology to estimate uncertainty has been employed as 6.4.5 and the below summary
table has been produced.
Table 6.43 Uncertainty summary table for 4 (III) category
Summary
BY (1990)
LRY (2021)
Table 4(I)
0%
75%
Recalculation:
There is no recalculation for this submission in this category.
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6.11. Indirect N2O emissions from managed soils (4(IV))
Source Category Description:
The estimation of indirect N2O emissions follows the 2006 IPCC guidelines (Volume 4, Ch. 11). The
indirect N2O emissions from N leaching and runoff from managed soils are estimated based on annual
amount of N mineralised in mineral soils associated with loss of soil organic matter due to land-use
change (i.e. from direct N2O emissions). Default emission factors have been used accordingly.
Reference to 2006 IPCC equation: Vol. 4., Ch. 11: 11.10
Methodological Issues:
The atmospheric deposition as indirect N2O Emissions from Managed Soils has been reported as IE in
this category as sources of N can not be differentiated from Croplands and Grasslands thus reported
under 3D(b). However, Nitrogen Leaching and Runoff has been estimated by using the default EFs of
IPCC 2006.
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Table 6.44 EFs used for N2O emissions
Parameter
Values
Volatilization fraction: Frac GASF
0.2
((kg NH3–N + NOx–N) (kg Napplied) –1)
EF4(kg N2O–N (kg NH3–N + NOX–Nvolatilised)-1)
0.01
FracLEACH-(H) [N losses by leaching/runoff for regions
0.3
EF5 [leaching/runoff], kg N2O–N (kg N leaching/runoff)
0.0075
Uncertainties and Time-Series Consistency:
The time series consistency has been ensured via the new land tracking system as explained in section
6.3.
The same methodology to estimate uncertainty has been employed as 6.4.5 and the below summary
table has been produced.
Table 6.45 Uncertainty summary table for 4 (IV) category
Summary
BY (1990)
LRY (2021)
Table 4(I)
0%
387%
Recalculation:
There is no recalculation for this submission in this category.
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6.12. Biomass Burning (4(V))
Estimated effect of mega forest fires in Türkiye in 2021 was 10 460 kton CO2 eq. emission for Forest
Land category from 134.8 kha burned forest area.
Source Category Description:
Several types of country-specific data have been collected to estimate emissions from biomass burning.
The most important input variable is activity data (i.e. area burnt) that is collected each year. The
second important variable to be collected is above-ground biomass of lands that were affected by
wildfires. In addition, Türkiye also collects country-specific data on types of wildfires, carbon pools
affected and the fraction of biomass lost in wildfires.
Methodological Issues:
To calculate emissions from wildfires;
▪
Average above-ground biomass of those forest types (coniferous, deciduous, mixed and OFL)
that were affected by wildfires were calculated on an annual basis.
▪
Average fraction of biomass lost in wildfires was estimated.
Emission estimation due to biomass burning follows the 2006 IPCC guidelines (Volume 4, Ch. 2 and Ch.
4). Currently, CO2 emissions from biomass burning are estimated as part of annual carbon loss in
biomass (i.e. Ldisturbance). A generic approach for estimating the amount of carbon lost from
disturbances is applied, based on area affected by disturbance (i.e. area burnt), average above-ground
biomass on area burnt and average fraction of biomass lost in wildfires. Non-CO2 emissions from
biomass burning have also been estimated by applying a generic methodology for each greenhouse gas
through use of default emission factors (i.e. for CO, CH4, N2O, NOx and NMVOC).
Field burning of agricultural residues is estimated under the Agriculture sector (CRF table 3.F).
Controlled burning is not a practice used in Türkiye. Thus reported as NO. Wildfires in wetlands are
reported as NO. Most of the wildfires in the GL areas are caused by forest fires and they are reported
as NA because the activity data cannot be reached clearly.
Reference to the 2006 IPCC equations: Vol. 4., Ch. 2: 2.14 / 2.27
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The EFs and coefficients used are as follows;
Table 6.46 EFs used for Biomass burning emissions
Parameters
Year
1990
1995
2000
2005
2010
2015
2018
2019
2020
2021
ABG Dec (tDM/ha)
98.50
102.49
107.61
127.34
128.00
112.87
106.88
96.84
95.05
79.93
ABG Con (tDM/ha)
71.09
73.98
77.67
83.75
86.12
85.79
87.88
90.34
85.80
72.23
ABG Mixed (tDM/ha)
84.80
88.23
92.64
105.55
107.06
99.33
97.38
93.59
90.42
76.08
ABG Degraded (tDM/ha)
5.78
6.02
6.32
6.52
5.57
4.64
4.19
5.78
5.94
4.39
R For Dec
0.23
0.23
0.23
0.23
0.23
0.23
0.23
0.23
0.23
0.23
R For Con
0.29
0.29
0.29
0.29
0.29
0.29
0.29
0.29
0.29
0.29
R For Mix
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
0.26
R For Deg
0.43
0.43
0.43
0.43
0.43
0.43
0.43
0.43
0.43
0.43
LB total Dec (tDM/ha)
127.07
132.22
138.82
164.27
165.12
145.60
137.88
124.92
122.61
103.11
LB total Con (tDM/ha)
87.45
90.99
95.53
103.01
105.93
105.53
108.09
111.12
105.54
88.85
LB total Mixed (tDM/ha)
106.84
111.18
116.73
132.99
134.90
125.16
122.70
117.92
113.94
95.87
LB total Degraded (tDM/ha)
8.27
8.60
9.03
9.32
7.96
6.64
5.99
8.26
8.50
6.29
LT Dec (tDM/ha)
8.35
8.35
8.35
8.35
8.35
8.35
8.35
8.35
8.35
8.35
LT Con (tDM/ha)
20.30
20.30
20.30
20.30
20.30
20.30
20.30
20.30
20.30
20.30
LT Mix (tDM/ha)
14.32
14.32
14.32
14.32
14.32
14.32
14.32
14.32
14.32
14.32
LT Deg (tDM/ha)
0.00
5.00
10.00
15.00
20.00
25.00
27.00
28.00
29.00
30.00
DW Dec (tDM/ha)
0.99
1.02
1.08
1.27
1.28
1.13
1.07
0.97
0.95
0.80
DW Con (tDM/ha)
0.71
0.74
0.78
0.84
0.86
0.86
0.88
0.90
0.86
0.72
DW Mix (tDM/ha)
0.85
0.88
0.93
1.06
1.07
0.99
0.97
0.94
0.90
0.76
DW Deg (tDM/ha)
0.06
0.06
0.06
0.07
0.06
0.05
0.04
0.06
0.06
0.04
Burned share Dec
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
Burned share Con
0.90
0.90
0.90
0.90
0.90
0.90
0.90
0.90
0.90
0.90
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Table 6.46 EFs used for Biomass burning emissions (Cont'd)
Parameters
1990
1995
2000
2005
2010
2015
2018
2019
2020
2021
Burned share Mix
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
Burned share Deg
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
105.00
109.35
115.03
129.25
132.07
125.52
125.41
124.27
118.97
100.35
0.44
0.44
0.44
0.44
0.44
0.44
0.44
0.44
0.44
0.44
46.20
48.11
50.61
56.87
58.11
55.23
55.18
54.68
52.35
44.15
11.11
8.11
8.11
8.11
8.11
7.96
7.96
7.96
7.96
7.96
Total stock available for
burning (tDM/ha)
Cf (combustion factor,
Extra tropical forest)
FLremFL Amount burnt
(tDM/ha)
convFL Amount
burnt
(tDM/ha)
Uncertainties and Time-Series Consistency:
The time series consistency has been ensured via the new land tracking system as explained in section
6.3.
The same methodology to estimate uncertainty has been employed as 6.4.5 and the below summary
table has been produced.
Table 6.47 Uncertainty summary table for 4 (V) category
Summary
BY (1990)
LRY (2021)
Table 4(I)
54%
54%
Recalculation:
There is no recalculation for this submission in this category.
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6.13. Harvested Wood Products (4.G)
Source Category Description:
Carbon stock changes of the HWP category calculations have been revised and recalculated in this
submission. The previous computation was done in the context of a study by Bouyer and Serengil
(2014). The revision involved below changes;
▪
The approach has been reviewed by international experts and modified based on their
suggestions,
▪
Paper has been added as the third product since 2019 submission (for 1990-2017),
▪
A KP analogical approach has been employed. Export and import amounts have been taken into
account,
Figure 6.20 Emissions and removals in HWP pool
2000
Emissions/removals from HWP (Gg CO2)
0
-2000
-4000
-6000
-8000
-10000
-12000
-14000
-16000
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
-18000
WP_domestic (Gg CO2)
SW_domestic (Gg CO2)
PP_domestic (Gg CO2)
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Methodological Issues:
The following methodology has been applied in calculations;
The activity data on various forest products (sawnwood, wood panels and paper) variables for HWP has
been downloaded from the FAO database: http://www.fao.org/faostat/en/#data/FO. It is assumed that
paperboard is part of the paper category. The data on production of industrial roundwood (production,
import, export) and production of wood pulp (production, import, export) have been obtained from the
FAO database and annual fraction (i.e. share) of domestic harvest calculated accordingly.
Approach B has been used for HWP calculations. General method to estimate annual change in carbon
stock in “products in use” based on first order decay function and half-life is used. Domestic consumption
is computed from production data (domestic harvest) plus imports minus exports. The annual fraction
of the feedstock coming from domestic harvest for the HWP categories sawnwood and wood-based
panels has been estimated. Also, the annual fraction of domestically produced wood pulp as feedstock
originating from domestic harvest for the production of the HWP category paper and paperboard (IPCC
2014) is estimated.
Annual carbon stock inflow from domestic wood production for each category was extrapolated
backward by applying equation 12.6 to get figures for period before 1961 because FAO statistics start
from 1961 (annual rate of increase for industrial roundwood production can be used from table 12.3;
for Europe the U value = 0.0151).
Country specific wood density values have been used.
Reference to 2014 IPCC equations: Ch. 2: 2.8.1 / 2.8.2
Reference to 2014 IPCC table: Ch. 2: 2.8.1
Reference to 2006 IPCC equation: Vol. 4., Ch. 12: 12.6
Default half-lives from Table 2.8.2 were used for each HWP category in the FOD constant (k) and the
estimation from the year 1900 to present has been performed. Annual CSC in the HWP pool was
calculated as difference between subsequent years for the whole reporting period, i.e. base year to
present (ΔCi = Ci – Ci-1).
Reference to 2006 IPCC equation: Vol. 4., Ch. 12: 12.1
Reference to 2014 IPCC table: Ch. 2: 2.8.2
Recalculation:
There is no recalculation on Harvested Wood Products category for this submission.
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Waste
7. WASTE (CRF Sector 5)
7.1. Sector Overview
The waste sector includes CH4 emissions from solid waste disposal, CH4 and N2O emissions from
biological treatment of solid waste, CO2, CH4 and N2O emissions from open burning of waste and, CH4
and N2O emissions from wastewater treatment and discharge. Emissions from waste incineration are
included in the inventory but reported in the energy sector since the purpose of waste incineration is
energy recovery.
Total waste emissions for the year 2021 are 14.7 Mt CO2 eq., or 2.6% of total GHG emissions (without
LULUCF). Within the sector, 63.5% of the emissions were from solid waste disposal, followed by 36.3%
from wastewater treatment and discharge, 0.17% from biological treatment of solid waste and 0.05%
from open burning of waste.
The major GHG emissions from the waste sector are CH4 emissions, which represent 83.9% of total
emissions from this sector in 2021, followed by N2O emissions with 16.1% and a very small percent of
CO2 as 0.02%.
Table 7.1 CO2 equivalent emissions for the waste sector, 2021
(kt CO2 eq.)
GHG source and
sink categories
CO2
CH4
N2O
Total
5. Waste
3.6
12 327.0
2 367.3
14 698.0
A. Solid waste disposal
NA
9 337.6
NA
9 337.6
B. Biological treatment of solid waste
NA
14.5
10.3
24.8
C. Incineration and open burning of waste
3.6
3.1
0.6
7.3
D. Wastewater treatment and discharge
NA
2 971.8
2 356.4
5 328.2
E. Other
NO
NO
NO
NO
Waste emissions are 32.6% (3.6 Mt CO2 eq.) higher in 2021 than they were in 1990 and 9.9% (1.6 Mt
CO2 eq.) lower than in 2020 as seen in Figure 7.1.
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Figure 7.1 Total GHG emissions of waste sector, 1990-2021
20
18
(Mt CO2 eq.)
16
14
12
10
8
6
4
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
2
Total emissions in the waste sector gradually increased between 1990 (11 081 kt CO2 eq.) and 2021
(14 698 kt CO2 eq.) driven largely by the steady rise in emissions from solid waste disposal between
1990 and 2011 followed by a decrease in emissions since from solid waste disposal after 2011. Emissions
from solid waste disposal increased by 91.6% (6 162 kt CO2 eq.) between 1990 and 2011, before
decreasing by 27.6% between 2011 and 2021 (3 554 kt CO2 eq.). Methane recovery in solid waste
disposal sites is reported as of 2002 (37 kt CO2 eq.) and increasing to 9 946 kt CO2 eq. in 2021. The
decline in recent total emissions is mainly due to the increase in methane recovery between 2011 (985
kt CO2 eq.) and 2021, an increase of 910%. For the full discussion of trends for individual categories,
see the category-specific discussions below.
Methodological tiers and EFs used to estimate emissions from waste sector are summarized by
categories in Table 7.2.
Table 7.2 Summary of methods and emission factors used
GHG source and
sink categories
CO2
CH4
N2O
Method Emission
applied
factor
Method Emission
applied
factor
Method Emission
applied
factor
5. Waste
T2
CS,D
T1,T2
CS,D
T1
D
A. Solid waste disposal
NA
NA
T2
CS,D
NA
NA
B. Biological treatment of solid waste
NA
NA
T1
D
T1
D
C. Incineration and open burning of waste
T2
CS,D
T1
D
T1
D
D. Wastewater treatment and discharge
NA
NA
T2
CS
T1
D
D: IPCC Default, CS: Country Specific, NA: Not Applicable, T1: Tier 1, T2: Tier 2
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6
7.2. Solid Waste Disposal (Category 5.A)
Source Category Description:
This category includes emissions from solid waste disposal sites (SWDS). The category consists of two
waste disposal practices in Türkiye:
Managed waste disposal sites,
Unmanaged waste disposal sites.
There are no semi-aerobic managed waste disposal sites (5.A.1.b) in Türkiye and all managed waste
disposal sites are categorized under anaerobic managed waste disposal sites (5.A.1.a). Unmanaged
waste disposal sites (5.A.2) cannot be classified into deep and shallow due to lack of knowledge. The
category covers CH4 emissions from two types of waste in municipal SWDS in Türkiye:
Municipal solid waste (MSW),
Industrial waste,
Sewage sludge, and
Clinical waste.
According to the clinical waste management practices and regulations in Türkiye, clinical waste which
is collected separately from health institutions is disposed of in SWDS or incinerated. Almost all of the
clinical waste is sterilized prior to disposal in SWDS. Hazardous wastes are disposed in separated lots in
SWDS. Hazardous wastes are not taken into account in this source category because these types of
wastes are not producing methane. Industrial waste including hazardous and clinical waste is usually
incinerated and considered in the category of Public Electricity and Heat Production (1.A.1.a).
The total amount of waste disposed in the SWDS has increased through the years mainly due to
population growth (Table 7.7). The number of managed SWDS has also increased over the years (Table
7.4) and the share of managed SWDS as a fraction of total SWDS surpassed unmanaged SWDS as of
from 2012 onwards, particularly due to improved landfill management practices, including landfill gas
recovery.
Since 2004, Türkiye has carried out many actions related to waste management and regulatory policies.
The first legal regulation in this field in Türkiye was the Solid Waste Control Regulation (14.03.1991)
which provided for and guided practices in the collection and removal of domestic and industrial waste.
Revisions of the regulation to harmonize it with the EU Landfill policy were carried out in 2010
(26.03.2010). Waste Management Action Plan covering 2008-2012 was prepared by the former Ministry
of Environment and Forestry (MoEF), using the outcomes of the EU funded Environmental Heavy Cost
Investment Planning (EHCIP) Project, solid waste master plan projects and the EU Integrated
Environmental Adaptation Strategy (NES) (2007-2023). The former Ministry of Environment and
Turkish GHG Inventory Report 1990-2021
373 373
6
Waste
Urbanization (MoEU) published the National Waste Management and Action Plan (2016-2023) in
December 2017, in order to set goals for local authorities in all 81 provinces towards an integrated
waste management system, which will require more recovering, recycling and energy production from
waste and accordingly limit the number of landfills needed as it is aimed at in circular economies. All
these waste management policies and actions in Türkiye have reduced the share of GHG emissions from
the waste sector.
Methodological Issues:
Methane Emissions from Solid Waste Disposal
CH4 emissions from solid waste disposal is a key category according to both a level and a trend
assessment. СН4 emissions of MSW, industrial waste, sewage sludge and clinical waste emissions are
estimated from municipal SWDS in Türkiye. The IPCC T2 First Order Decay (FOD) method recommended
in the 2006 IPCC Guidelines for National GHG Inventories is used with default parameters and countryspecific AD on current and historical waste disposal at SWDS to estimate CH4 emissions. Closed SWDS
continue to emit CH4. This is automatically accounted for in the FOD method because historical waste
disposal data are used. The CH4 emissions from solid waste disposal for a single year can be estimated
based on Equation 3.1 in 2006 IPCC, Volume 5, Chapter 3 as given in the equation below.
𝐶𝐶𝐶𝐶� 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 = �� 𝐶𝐶𝐶𝐶� 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔�,� − 𝑅𝑅� � ⦁(1 − 𝑂𝑂𝑂𝑂� )
�
Where:
CH4 Emissions = CH4 emitted in year T, Gg
T = inventory year
x = waste category or type/material
RT = recovered CH4 in year T, Gg
OXT = oxidation factor in year T, (fraction)
The CH4 generated by each category of waste disposed is added to get total CH4 generated in each
year. Finally, emissions of CH4 are calculated by subtracting the CH4 gas recovered from the disposal
site.
The total amount of CH4 generated, CH4 recovered and net CH4 emissions from solid waste disposal sites
are estimated as given in Table 7.3 and Figure 7.2.
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Waste
Table 7.3 CH4 generated, recovered and emitted from SWDS, 1990-2021
Year
CH4 Recovered
CH4 Generated
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
(kt)
CH4 Emitted
Managed
Unmanaged
Managed
Unmanaged
NO
NO
NO
1.7
36.3
39.4
68.6
109.5
128.4
127.6
169.7
214.3
236.8
282.6
305.8
396.2
NO
NO
NO
NO
NO
NO
NO
4.4
4.0
4.0
3.0
7.9
6.5
7.0
2.2
1.6
NO
5.6
45.9
105.5
143.2
160.4
153.7
136.6
142.8
168.3
153.8
139.6
146.5
131.5
136.9
73.6
269.2
299.5
337.3
357.0
359.4
355.3
352.7
344.0
338.3
334.0
330.0
321.4
317.7
309.9
307.6
299.9
269.2
305.1
383.3
464.1
538.8
555.0
574.9
594.5
613.5
633.9
656.6
683.1
707.5
731.0
752.4
771.4
Figure 7.2 CH4 emissions from solid waste disposal, 1990-2021
800
(kt)
700
600
500
400
300
200
CH₄ generated
CH₄ recovered
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
100
CH₄ emitted (net emissions)
Net methane emissions tend to decrease with the increase in methane recovery amount due to the
increase in the capacity and number of methane recovery facilities producing electricity/heat energy
from landfill gas in Türkiye.
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Waste
Choice of Activity Data
For calculating CH4 generated; municipal solid waste AD, industrial waste AD, sewage sludge AD and
clinical waste AD are needed. As is described in more detail below, for MSW, industrial waste, sewage
sludge and clinical waste, national data are used where possible, depending on availability of all ADs. If
national data are not available for a specific inventory year, population data and waste per capita data
are used to estimate national data on MSW generation. By the same logic, GDP data and waste
generation rate data are used as drivers for estimating industrial waste generation and some missing
data imputation methods were implied for sludge and clinical waste data when any year’s data is
missing.
The percentage of waste generated which goes to SWDS (% to SWDS) and composition of waste going
to SWDS are also used for the calculations.
The distribution of site types is used for calculating a weighted average methane correction factor (MCF).
The other parameters needed for the FOD model are; degradable organic carbon (DOC), fraction of
DOC which decomposes (DOCF), methane generation rate constant (k), fraction of methane (F) and
oxidation factor (OX).
The justification for the selection of parameters by Türkiye is further described below.
Municipal Solid Waste Activity Data
The annual data of MSW disposed in the municipal SWDS (the amount of MSW both in managed and
unmanaged landfills) are collected by TurkStat from Municipal Waste Statistics Survey which is applied
to all municipalities. However, the survey could not be conducted on a regular basis before 2006, and
since 2006 has started to be held biennially. The data for years 1994-1998, 2001-2004, 2006, 2008,
2010, 2012, 2014, 2016, 2018 and 2020 are available. For 2021, the survey data is not available. The
specific data collected by TurkStat are the amount of MSW is weighed, generally based on waste delivery
vehicle capacity. 2005 data of MSW disposed in managed SWDS is gathered via Waste Disposal and
Recovery Facilities Statistics Survey by TurkStat. In Türkiye, managed SWDS are in operation since 1992
(See Table 7.4). In 1992 and 1993, there was only one managed SWDS according to the results of
Municipal Waste Statistics Survey. Therefore, the waste disposal amounts of that site for those years
are used for emission estimations (see Table 7.6). Missing data for the years not surveyed for total MSW
delivered to SWDS are estimated by regression model. For distribution of MSW to managed and
unmanaged landfills between 1990 and 2020, the missing data for the remaining years are estimated
by linear interpolation. 2021 data of MSW disposed in managed SWDS is estimated by trend
extrapolation.
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Waste
Data are generally available from the statistical surveys described above (noting the need to resolving
data gaps for intervening years when survey data were not available). Data on MSW generation were
not available prior to 1994. Recognizing that, in accordance with the 2006 IPCC Guidelines, data on
MSW generation are needed for at least the last 50 years, Türkiye has made assumptions to collect the
full time series of data. As described further below, between 1950 and 1993, the amount of waste
generated is estimated based on the waste per capita ratio in 1994 and mid-year population data for
each year.
The total number of managed SWDS has increased by years as shown in Table 7.4 below.
Table 7.4 Number of managed SWDS, 1992-2020
1992
1993
1994
1995
1996
1997
1998
2000
2001
2002
1
1
2
6
6
8
8
10
12
12
2003
2004
2005
2006
2008
2010
2012
2014
2016
2018
2020
15
16
18
22
37
52
80
113
134
159
174
Source: (1) TurkStat, Municipal Waste Statistics, 1992-2010
(2) TurkStat, Waste Disposal and Recovery Facilities Statistics, 2012-2020
Amount of municipal waste by disposal methods are given in Table 7.5.
Table 7.5 Amount of municipal waste by disposal methods, 1994-2020
Year
1994
1995
1996
1997
1998
2001
2002
2003
2004
2006
2008
2010
2012
2014
2016
2018
2020
Municipality's
dumping site
14 479.2
17 174.9
17 519.5
16 805.1
16 852.8
14 569.8
16 310.0
16 566.5
16 415.8
14 941.2
12 677.1
11 001.2
9 771.0
9 935.6
9 094.9
6 520.7
5 492.8
Controlled
landfill site
809.0
1 444.0
2 847.0
4 363.8
5 257.9
8 304.2
7 047.0
7 431.8
7 001.5
9 428.3
10 947.4
13 746.9
15 484.2
17 807.4
19 337.9
21 643.8
22 443.5
Composting
plant
192.1
158.9
178.8
180.4
166.3
218.1
383.1
325.9
350.7
254.9
275.7
194.5
154.7
126.5
146.5
122.9
117.5
Burning
in an
open area
442.1
405.0
437.9
625.1
386.1
343.6
220.5
258.5
101.6
246.5
239.3
133.9
104.8
4.3
10.2
6.1
19.0
Lake and
river
disposal
557.6
370.4
370.3
384.4
374.9
100.9
196.8
228.5
154.7
69.8
47.7
44.0
33.4
15.8
0.5
0.5
0.5
Burial
523.4
828.9
823.6
1 446.9
852.4
481.7
499.9
597.0
426.5
144.5
100.5
34.3
94.3
7.3
6.7
2.0
6.9
(kt)
Other (1)
753.3
527.3
303.3
365.8
1 039.1
1 115.4
715.8
709.3
562.7
194.7
73.1
122.1
202.3
113.8
41.1
65.3
98.0
Source: TurkStat, Municipal Waste Statistics
(1) Data refers to disposals by using as filling material and dumping onto land.
Turkish GHG Inventory Report 1990-2021
377 377
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Waste
The amount of waste disposed in unmanaged SWDS consists of the amount of waste disposed to
municipality's dumping sites, burial and other. Annual municipal solid waste at the SWDS and distribution
of waste by waste management type are given in Table 7.6.
Table 7.6 Annual MSW and distribution of waste by management type, 1990-2021
Annual MSW at the SWDS
(kt)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Total
15
19
23
25
24
26
25
25
27
27
28
28
28
28
28
28
Managed
518.4
975.1
894.1
947.4
904.4
319.0
551.8
267.0
864.2
415.0
480.5
837.0
231.7
633.6
041.2
417.9
1
7
7
13
14
15
16
17
18
19
20
21
22
22
22
Distribution of waste
(%)
Unmanaged
NO
444.0
288.8
078.2
746.9
615.5
484.2
645.8
807.4
572.7
337.9
490.9
643.8
043.7
443.5
843.4
15
18
16
18
11
11
10
8
10
8
9
8
6
6
5
5
Managed
Unmanaged
0.0
7.2
30.5
27.3
55.2
55.5
60.6
65.9
63.9
67.7
67.9
71.1
76.7
77.0
80.0
80.4
100.0
92.8
69.5
72.7
44.8
44.5
39.4
34.1
36.1
32.3
32.1
28.9
23.3
23.0
20.0
19.6
518.4
531.1
605.3
869.2
157.5
703.5
067.6
621.2
056.8
842.3
142.6
346.1
587.9
590.0
597.7
574.6
Population Data: Historical data are obtained from TurkStat's Mid-year Population Estimations and
Projections from 1990 onwards as given in Table 7.7.
Table 7.7 Mid-year population, 1990-2021
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
Population
55
56
56
57
58
59
60
61
62
63
64
65
66
66
67
68
120
055
986
913
837
756
671
582
464
364
269
166
003
795
599
435
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
Year
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Population
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
295
158
052
039
142
224
176
148
182
218
278
313
407
579
385
147
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
Source: TurkStat, Mid-year Population Estimations and Projections
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Waste
6
Waste Per Capita: To calculate waste per capita (kg/cap/yr), the amount of MSW generated and midyear population data are used. The amount of MSW generated for the surveyed years (1994-1998,
2001-2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018 and 2020) are obtained from TurkStat's
Municipal Waste Statistics. The estimations of TurkStat are used for the years 1999, 2000, 2005, 2007,
2009, 2011, 2013, 2015, 2017, 2019 and 2021. Due to lack of historical MSW generated data, the waste
per capita of 1994 (398.5 kg/cap/yr) is used for 1950-1993.
Waste per capita for 1990-2021 are given in Table 7.8.
Table 7.8 Waste per capita, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
MSW
Generated
(kt)
21 966.7
27 234.1
30 617.0
31 351.9
29 733.0
30 862.0
30 786.0
30 920.0
31 230.0
31 283.0
33 763.5
34 173.0
34 532.6
35 017.4
34 757.8
35 022.1
Population
(millions)
55.1
59.8
64.3
68.4
73.1
74.2
75.2
76.1
77.2
78.2
79.3
80.3
81.4
82.6
83.4
84.1
Turkish GHG Inventory Report 1990-2021
Waste per capita
(kg/cap/yr)
398.5
455.8
476.4
458.1
406.5
415.8
409.5
406.1
404.6
399.9
425.9
425.5
424.2
424.0
416.8
416.2
379 379
6
Waste
% to SWDS: To calculate percentage of MSW generated which goes to SWDS, the amount of MSW
generated and MSW landfilled data are used. The amount of MSW landfilled for the surveyed years
(1994-1998, 2001-2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018 and 2020) are obtained from
TurkStat's Municipal Waste Statistics Survey. The estimations of TurkStat are used for the years 1999,
2000, 2005, 2007, 2009, 2011, 2013, 2015, 2017, 2019 and 2021. Due to lack of MSW generated data,
% to SWDS of 1994 (70.6%) is used for 1950-1993.
% to SWDS obtained by dividing the amount of MSW landfilled by MSW generated are given for 19902021 in Table 7.9.
Table 7.9 Percentage of MSW disposed in the SWDS, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
380
MSW Generated
(kt)
21 966.7
27 234.1
30 617.0
31 351.9
29 733.0
30 862.0
30 786.0
30 920.0
31 230.0
31 283.0
33 763.5
34 173.0
34 532.6
35 017.4
34 757.8
35 022.1
MSW Landfilled
(kt)
15 518.4
19 975.1
23 894.1
25 947.4
24 904.4
26 319.0
25 551.8
25 267.0
27 864.2
27 415.0
28 480.5
28 837.0
28 231.7
28 633.6
28 041.2
28 417.9
Turkish GHG Inventory Report 1990-2021
% to SWDS
(%)
70.6
73.3
78.0
82.8
83.8
85.3
83.0
81.7
89.2
87.6
84.4
84.4
81.8
81.8
80.7
81.1
380
Waste
6
Waste Composition Data: The waste composition data was previously only available for 1993, 2006
and 2014. To improve the quality of the inventory, an additional question on waste composition data
was added to the TurkStat's Municipal Waste Statistics Survey, and the results of the survey as of 2016
were used in the calculations. For 1993, the source of the data is TurkStat, Environmental Statistics,
Household Solid Waste Composition and Tendency Survey Results, 1993. The results of this survey on
a national scale are also published in OECD Environmental Data, Compendium 2006-2008. The 2006
data was developed under the Solid Waste Master Plan Project of MoEF and published in Waste
Management Action Plan, 2008-2012; MoEF. The source of the 2014 waste composition data is National
Waste Management and Action Plan, 2016-2023; MoEU. The source of the 2016, 2017, 2018, 2019 and
2020 waste composition data is TurkStat's Municipal Waste Statistics Survey as mentioned above. This
survey is conducted biennially, but the waste composition data is compiled annually by inquiring the
previous year’s data.
Waste composition data for the remaining years were estimated by time series analysis methods. For
missing value imputation R programming language was used. Since, it is not possible to generate
missing years before 1993 with interpolation. Thus, for providing time series consistency, time series
analysis methods were tried and compared with splicing techniques of IPCC guidelines. After the
comprehensive study carried out for imputation of missing years, two of the time series analysis methods
were found statistically better than the others. These are Linear Weighted Moving Average (LWMA) and
Exponential Weighted Moving Average (EWMA). An exponential moving average is calculated similarly
to a linear weighted moving average, but uses an exponentially weighted multiplier. Both of them are
calculated by adding the moving average of a certain share of the current value to the previous value.
They assign more meaning to the recent values and less to the period's beginning.
LWMA: Weights decrease in arithmetical progression. The observations directly next to a central value
i, have weight 1/2, the observations one further away (i-2,i+2) have weight 1/3, the next(i-3,i+3) have
weight 1/4, ...
EWMA: uses weighting factors which decrease exponentially. The observations directly next to a central
value i, have weight 1/2^1, the observations one further away (i-2,i+2) have weight 1/2^2, the next
(i-3,i+3) have weight 1/2^3, ...
(The R Project for Statistical Computing- “Time Series Missing Value Imputation”, Package ‘imputeTS’,
Version: 2.7, June 20, 2018)
As a result, LWMA method was preferred because the values of both the first years and the last years
were the same in the EWMA method.
Table 7.10 contains these statistically estimated data with the official waste composition data.
Turkish GHG Inventory Report 1990-2021
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Waste
Table 7.10 Waste composition data, 1990-2021
(%)
Year
Food
Garden
Paper
Wood
Textile
Plastics
Metal
Glass
Other
58.29
0.95
7.90
0.00
3.81
2.81
1.00
2.76
22.48
64.00
0.00
6.00
0.00
4.00
3.00
1.00
2.00
20.00
1995
58.00
1.00
8.00
0.00
3.80
2.80
1.00
2.80
22.60
2000
48.00
2.67
11.33
0.00
3.47
2.47
1.00
4.13
26.93
36.45
5.31
14.69
0.00
2.98
2.64
1.06
5.56
31.31
34.00
5.00
16.00
0.00
3.00
2.00
1.00
6.00
33.00
2010
41.35
5.92
12.06
0.00
2.95
3.93
1.19
4.69
27.92
2011
46.34
5.98
11.44
0.00
2.10
6.23
1.52
4.51
21.88
2012
51.11
6.41
9.52
0.00
1.81
7.80
1.71
3.88
17.77
50.84
6.45
9.36
0.00
1.93
7.58
1.67
3.82
18.33
48.70
6.84
8.11
0.00
2.90
5.86
1.37
3.38
22.84
1990
1993
(1)
2005
2006
(2)
2013
2014
(3)
2015
52.37
5.67
10.47
0.00
1.09
9.17
1.95
4.34
14.94
2016
(4)
55.13
5.68
11.87
0.00
0.00
11.02
2.28
4.70
9.32
2017
(4)
53.75
3.91
11.91
0.00
0.00
11.36
2.33
5.22
11.53
2018
(4)
54.62
4.96
10.89
0.00
0.00
12.32
2.15
5.13
9.93
2019
(4)
52.71
3.44
9.77
1.24
1.86
11.09
2.09
4.92
12.86
2020
(4)
52.09
2.43
10.26
1.07
1.75
11.30
2.74
5.74
12.62
2021
(5)
52.09
2.43
10.26
1.07
1.75
11.30
2.74
5.74
12.62
(1) TurkStat, Environmental Statistics, Household Solid Waste Composition and Tendency Survey Results, 1993
(2) MoEF, Waste Management Action Plan, 2008-2012
(3) MoEU, National Waste Management and Action Plan, 2016-2023
(4) TurkStat, Municipal Waste Statistics Survey Results, 2016-2020
(5) Assumed the same as 2020 data
Industrial Waste Activity Data
The annual data of industrial waste disposed in the municipal SWDS are collected by TurkStat's
Manufacturing Industry Establishments Water, Wastewater and Waste Statistics Survey which is applied
to manufacturing industry establishments having 50 or more employees. However, the survey could not
be conducted on a regular basis before 2008, and since 2008 has started to be held biennially. The data
are available for the years 1994-1997, 2000, 2004, 2008, 2010, 2012, 2014, 2016, 2018 and 2020. The
missing data for the remaining years between 1994 and 2020 were estimated by linear interpolation.
2021 data was assumed the same as in 2020.
Data are available from the statistical surveys described above (noting the need to resolving data gaps
for intervening years when survey data were not available). Data on industrial waste generation were
not available prior to 1994. Recognizing that, in accordance with the 2006 IPCC Guidelines, data on
industrial waste generation are needed for at least the last 50 years, Türkiye has made assumptions to
collect the full time series of data. As described further below, between 1950 and 1993, the amount of
waste generated is estimated based on the waste generation rate in 1994 and GDP data for each year.
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The amount of degradable organic material from industrial waste disposed at SWDS is taken into
account since only those industrial wastes which are expected to contain DOC and fossil carbon should
be considered for the purpose of emission estimations from SWDS. Excluding the industrial waste that
is already included in the Municipal Waste Statistics (to avoid double counting), Türkiye concluded that
there are no separately managed industrial waste disposal practices in the SWDS. For this reason, the
distribution of industrial waste by waste management type is 100% unmanaged for the whole time
series.
The amount of industrial waste disposed of in unmanaged SWDS consists of dumping onto land, burial
and disposals to the Organized Industrial Zones.
Annual industrial waste at the SWDS and distribution of waste by waste management type are given in
Table 7.11.
Table 7.11 Annual IW and distribution of waste by management type, 1990-2021
Annual IW at the SWDS
(kt)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Total
12.9
6.7
10.4
2.7
4.2
4.5
4.7
5.7
6.1
4.0
2.1
2.8
3.4
4.4
5.5
6.5
Managed
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
Unmanaged
12.9
6.7
10.4
2.7
4.2
4.5
4.7
5.7
6.1
4.0
2.1
2.8
3.4
4.4
5.5
6.5
Turkish GHG Inventory Report 1990-2021
Distribution of waste
(%)
Managed
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Unmanaged
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
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GDP Data: Historical data for Gross Domestic Product (GDP) by production approach are obtained from
TurkStat's National Accounts from 1923 onwards. Compared to the previous submission, 2019 and 2020
GDP data have been revised by the TurkStat. GDP data in current prices used for emission estimations
are given in Table 7.12.
Table 7.12 GDP by production approach, 1990-2021
(million USD)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
GDP
149 195
149 156
156 656
177 332
131 639
168 080
181 077
188 735
277 668
254 119
273 085
202 503
238 145
316 561
407 021
504 754
Year
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
GDP
552 367
683 020
782 865
651 543
777 461
837 924
877 676
958 125
939 923
867 071
869 241
859 055
797 221
759 289
717 092
807 106
Source: TurkStat, National Accounts
Waste Generation Rate: To calculate waste generation rate (kt/million USD GDP/yr), between 1950
and 1994, the amount of industrial waste (IW) generated and GDP data are used. As noted above, the
amount of IW generated for the surveyed years (1994-1997, 2000, 2004, 2008, 2010, 2012, 2014,
2016, 2018 and 2020) are obtained from TurkStat's Manufacturing Industry Establishments Water,
Wastewater and Waste Statistics Survey. Missing data for the years not surveyed (1998, 1999, 20012003, 2005-2007, 2009, 2011, 2013, 2015, 2017 and 2019) are estimated by linear interpolation. For
2021, waste generation rate is calculated by assuming that IW generated in 2021 is the same as in
2020. Due to lack of historical IW generated data, the waste generation rate of 1994 (0.09 kt/million
USD GDP/yr) is used for 1950-1993 (see Table 7.13).
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% to SWDS: To calculate the percentage of industrial waste generated which goes to SWDS, the
amount of industrial waste generated and industrial waste landfilled data are used. The amount of
industrial waste landfilled for the surveyed years (1994-1997, 2000, 2004, 2008, 2010, 2012, 2014,
2016, 2018 and 2020) are obtained from TurkStat's Manufacturing Industry Establishments Water,
Wastewater and Waste Statistics Survey. 2021 data is estimated by trend extrapolation. Due to lack of
industrial waste generated data, the percentage of industrial waste sent to SWDS in 1994 (0.1%) is
used for 1950-1993.
The percentage of industrial waste to SWDS is obtained by dividing the amount of industrial waste
landfilled by industrial waste generated data.
Industrial waste AD are given in detail in Table 7.13.
Table 7.13 Industrial waste activity data, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
GDP
(million USD)
149 195.0
168 080.0
273 085.5
504 753.8
777 460.5
837 924.3
877 675.6
958 125.3
939 922.9
867 071.4
869 240.6
859 055.3
797 221.0
759 288.9
717 091.6
807 105.6
Waste
generation rate
(kt/million USD/yr)
0.09
0.07
0.06
0.04
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.03
0.03
0.03
0.03
Total IW
(kt)
13 615.4
12 492.8
17 058.9
18 286.1
13 366.5
14 086.6
14 420.3
15 890.2
15 733.5
15 370.1
16 266.7
20 366.0
22 881.1
23 532.4
23 867.9
23 867.9
% to SWDS
(%)
0.10
0.05
0.06
0.01
0.03
0.03
0.03
0.04
0.04
0.03
0.01
0.01
0.01
0.02
0.02
0.03
Total to
SWDS
(kt)
12.9
6.7
10.4
2.7
4.2
4.5
4.7
5.7
6.1
4.0
2.1
2.8
3.4
4.4
5.5
6.5
Methane Correction Factor (MCF)
Due to the assumption that all managed SWDS are categorized under anaerobic managed SWDS, the
default MCF from the 2006 IPCC Guidelines for anaerobic managed SWDS (1.0) is taken for managed
SWDS. Since there is no information about classification of deep (>=5 meters waste and/or high water
table) or shallow (<5 meters waste) for unmanaged waste disposal sites, Türkiye has used the average
of the default MCFs for unmanaged-deep (0.8) and unmanaged-shallow (0.4) in the absence of countryspecific information for unmanaged waste disposal practices (0.6).
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A weighted average of MCF from the estimated distribution of site types is needed for the calculation
CH4 emissions from solid waste disposal sites. Calculated values for the MCF are given in Table 7.14.
Table 7.14 Weighted averages of MCF, 1990-2021
(weighted average fraction)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
MCF for MSW
0.60
0.63
0.72
0.71
0.82
0.82
0.84
0.86
0.86
0.87
0.87
0.88
0.91
0.91
0.92
0.92
MCF for IW
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
0.60
MCF for SS
0.60
0.60
0.82
0.79
0.74
0.74
0.75
0.75
0.76
0.77
0.77
0.79
0.81
0.80
0.79
0.78
MCF for CW
0.00
0.00
0.00
0.78
0.88
0.90
0.92
0.91
0.90
0.91
0.92
0.89
0.88
0.89
0.85
0.82
Choice of Emission Factor and Other Parameters
2006 IPCC default values are selected for utilization in the IPCC Waste Model using the FOD method
with the starting year 1950.
Degradable Organic Carbon (DOC): Degradable organic carbon (DOC) is the organic carbon in
waste that is accessible to biochemical decomposition. IPCC default values for the DOC content of main
components (waste types/material) used in the model are listed in Table 7.15. For sewage sludge 0.05
is taken and for clinical waste 0.15 is used according to Table 2.6 in the 2006 IPCC, Volume 5, Chapter
2.
Table 7.15 DOC values by individual waste type
(weight fraction, wet basis)
Waste Type
DOC
386
Food waste
Garden
Paper
Wood
Textiles
0.15
0.20
0.40
0.24
0.24
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DOC by weight is calculated from the degradable portion of the MSW based on Equation 3.7 in the 2006
IPCC, Volume 5, Chapter 3 and the IPCC defaults are taken from Table 2.4 in the 2006 IPCC, Volume
5, Chapter2.
% 𝐷𝐷𝐷𝐷𝐷𝐷 (𝑏𝑏𝑏𝑏 𝑛𝑛𝑛𝑛𝑛𝑛 𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤ℎ𝑡𝑡)
= (0.15 𝑥𝑥 𝐴𝐴) + (0.20 𝑥𝑥 𝐵𝐵) + (0.40 𝑥𝑥 𝐶𝐶) + (0.24 𝑥𝑥 𝐷𝐷) + (0.24 𝑥𝑥 𝐸𝐸)
Where:
A = fraction of food waste in MSW
B = fraction of garden waste in MSW
C = fraction of paper in MSW
D = fraction of wood in MSW
E = fraction of textiles in MSW
The calculated values of DOC by weight for the inventory years of 1990-2021 are listed below in Table
7.16.
Table 7.16 DOC by weight, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
%DOC
13.01
13.01
13.10
13.12
12.92
13.23
13.19
13.13
Year
2014
2015
2016
2017
2018
2019
2020
2021
%DOC
12.61
13.44
14.15
13.61
13.54
13.49
13.29
13.29
Fraction of Degradable Organic Carbon Which Decomposes (DOCf): In the absence of countryspecific information, the recommended IPCC default value for DOCf (0.5) is used for the entire time
series.
Methane Generation Rate Constant (k): IPCC default methane generation rate constants are
selected according to the IPCC climate zone definitions in the model. Default k values for dry temperate
are listed below and applied for the entire time series.
Table 7.17 Dry temperate k values by waste type
(years-1)
Waste Type
k
Food waste
Garden
Paper
Wood
Textiles
0.06
0.05
0.04
0.02
0.04
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Fraction of Methane in Generated Landfill Gas (F): Most waste in SWDS generates a gas with
approximately 50% CH4. The IPCC default value for the fraction of CH4 in landfill gas (0.5) is used for
the entire time series.
Oxidation Factor (OX): The oxidation factor reflects the amount of CH4 from SWDS that is oxidized
in the soil or other material covering the waste. The IPCC default value for OX is zero for managed,
unmanaged and uncategorized SWDS and this is the value applied by Türkiye for the entire time series.
Methane Recovery
The recovery of methane and its subsequent utilization is also considered in the inventory. Methane
recovery from landfill gas started to be implemented in Türkiye in 2002. Therefore, the quantity of
recovered methane is subtracted from the methane produced beginning in the year 2002. In 2013,
Waste Disposal and Recovery Facilities Survey, 2012 was applied to all waste disposal and recovery
facilities having a license or a temporary license, and regardless of license, to controlled landfill sites,
incineration plants and composting plants operated by or on behalf of municipalities. Based on the
information obtained from the survey, TurkStat sends official letters to each facility recovering methane
for requesting the quantity of methane gas and electricity/heat production for the entire operating
period of the facility every year. The facilities estimate the quantity of methane recovered by measuring
of gas recovered. The obtained information on the quantity of produced electricity/heat is used for
cross-check of the quantity of methane recovered.
The coverage of the facilities is followed and updated depending on availability of new information; such
as information obtained from the facility, the information from the most recent (biennial) survey (i.e.
Waste Disposal and Recovery Facilities Survey, 2020). The emissions from energy production from the
recovered CH4 gas in SWDS were included in the category of Public Electricity and Heat Production
(1.A.1.a).
The number of managed and unmanaged SWDS with landfill gas recovery and the amount of recovered
methane, by year, are given in Table 7.18.
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Table 7.18 Methane recovery, 1990-2021
Year
1990-2001
2002
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Number of
managed SWDS
with landfill gas
recovery
Number of
unmanaged SWDS
with landfill gas
recovery
Recovered
methane in
managed SWDS
(kt)
Recovered
methane in
unmanaged SWDS
(kt)
NA
1
1
5
8
13
15
17
24
34
36
NA
NA
NA
NA
NA
NA
1
1
1
1
1
NO
1.5
1.7
36.3
39.4
68.6
109.5
128.4
127.6
169.7
214.3
NO
NO
NO
NO
NO
NO
4.4
4.0
4.0
3.0
7.9
48
51
1
2
236.8
282.6
6.5
7.0
66
63
1
1
305.8
396.2
2.2
1.6
An additional question about landfill gas flaring was added to the Waste Disposal and Recovery Facilities
Survey, 2014 and was also asked through the most recent survey, Waste Disposal and Recovery
Facilities Survey, 2020. There is no official data on landfill gas flaring. It will be also considered in the
upcoming inventory in case that new information is obtained.
Sewage Sludge
Sewage sludge is estimated by TurkStat with official data. This sludge is domestic wastewater treatment
sludge from municipal wastewater treatment plants. Data on sludge quantity are compiled on wet basis
and converted to dry matter by using the coefficients included in the guidelines of the European Union
Statistical Office (EUROSTAT). And for the emissions calculations dry basis is used. The source of sewage
sludge is TurkStat’s Municipal Wastewater Statistics Survey. In this survey, disposal methods named
‘Dumping on to land’, ‘Municipal dumping sites’, ‘Controlled landfill sites’, ‘Buried’ and ‘Other disposal’
are added together and assumed as the total sludge that stored in SWDS and each sludge amount can
be seen from Table 7.37 in Wastewater Treatment and Discharge section (Category 5.D).
Methane emissions from sewage sludge and activity data are listed below in Table 7.19 and Table 7.20,
respectively.
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Table 7.19 CH4 generated from SS at SWDS, 1990-2021
(kt)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Total
NO
0.004
0.055
0.419
1.087
1.227
1.358
1.479
1.576
1.650
1.711
1.757
1.793
1.817
1.837
1.852
Managed
NO
NO
0.029
0.269
0.613
0.673
0.731
0.787
0.834
0.875
0.908
0.936
0.963
0.990
1.010
1.025
Unmanaged
NO
0.004
0.026
0.151
0.474
0.554
0.627
0.693
0.742
0.776
0.802
0.821
0.830
0.827
0.826
0.827
Table 7.20 Annual SS and distribution of waste by management type, 1990-2021
Annual SS at the SWDS
(kt)
Year
1990-94
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
390
Total
1.5
2.4
58.0
184.6
283.3
280.2
277.0
250.5
223.9
210.0
196.1
180.4
164.6
161.7
158.8
155.8
Managed
NO
NO
32.0
88.8
98.8
100.0
101.1
96.3
91.5
87.3
83.0
84.2
85.4
80.5
75.6
70.7
Unmanaged
1.5
2.4
26.0
95.7
184.5
180.2
175.9
154.1
132.4
122.7
113.1
96.2
79.2
81.2
83.2
85.2
Turkish GHG Inventory Report 1990-2021
Distribution of waste
(%)
Managed
0.0
0.0
55.1
48.1
34.9
35.7
36.5
38.5
40.9
41.6
42.3
46.7
51.9
49.8
47.6
45.3
Unmanaged
100.0
100.0
44.9
51.9
65.1
64.3
63.5
61.5
59.1
58.4
57.7
53.3
48.1
50.2
52.4
54.7
390
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6
Clinical Waste
Data have been collected according to the manual for the implementation of regulation (EC) no
2150/2002 on waste statistics and to the framework of the OECD/EUROSTAT core set of environmental
data and indicators. For the reference year 2016 and before, data was produced based on the results
of the survey conducted by TurkStat which was applied to the health institutions listed in Medical Waste
Control Regulation as producers of large quantities of waste (university hospitals and their clinics,
general purpose hospitals and their clinics, maternity hospitals and their clinics and military hospitals
and their clinics) as Waste Statistics of Health Institutions.
Since 2017, Medical Waste Statistics have been prepared and published annually using medical waste
data from the health institutions (university, maternity and general purpose hospitals and their clinics)
included in the administrative records of the Ministry of Environment, Urbanization and Climate Change
(MoEUCC). Within the scope of the Official Statistics Program (2022-2026), it was decided that the press
release, which was previously published jointly by TurkStat and MoEUCC, will be published only by the
MoEUCC as of 2022. However, since the statistics for 2021 have not yet been published by the MoEUCC,
the amount of medical waste disposed of in landfills has been estimated by extrapolation.
Methane emissions caused by clinical waste are quite small as seen in Table 7.21.
Table 7.21 CH4 generated from CW at SWDS, 1990-2021
(kt)
Year
1990-2003
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Total
IE
0.2
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
Managed
IE
0.1
0.4
0.5
0.6
0.7
0.8
0.8
0.9
1.0
1.1
1.2
1.3
1.4
Unmanaged
IE
0.1
0.2
0.2
0.2
0.2
0.2
0.3
0.3
0.3
0.3
0.3
0.3
0.4
As can be seen from Table 7.22, values before 2003 were entered as "IE". The reason why those years
were entered as "Included Elsewhere" is the clinical waste data were gathered by TurkStat in those
years included in SWDS statistics via Municipal Waste Statistics Survey prior to 2003 because clinical
waste was not collected separately before 2003. After 2003, clinical waste was collected separately by
municipalities.
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Table 7.22 Annual CW and distribution of waste by management type, 1990-2021
Annual CW at the SWDS
(kt)
Year
1990-2002
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Total
IE
47.7
54.4
58.8
63.2
65.1
67.0
67.7
68.5
78.4
82.6
83.0
99.4
115.7
Managed
IE
21.1
38.1
44.6
51.0
50.8
50.7
52.5
54.4
56.3
58.2
60.1
62.0
63.9
Unmanaged
IE
26.6
16.3
14.2
12.2
14.3
16.3
15.2
14.0
22.0
24.3
22.9
37.4
51.8
Distribution of waste
(%)
Managed
NA
44.3
70.1
75.8
80.7
78.1
75.6
77.6
79.5
71.9
70.5
72.4
62.4
55.2
Unmanaged
NA
55.7
29.9
24.2
19.3
21.9
24.4
22.4
20.5
28.1
29.5
27.6
37.6
44.8
Uncertainties and Time-Series Consistency:
Uncertainty values for AD are estimated as 10.0% and 30.0% for managed and unmanaged SWDS,
respectively. The uncertainty values reflect the uncertainty associated with some of the assumptions
made by Türkiye in estimating underlying activity data for municipal solid waste, industrial waste,
sewage sludge and clinical waste. Although waste statistics on the amount of MSW generated are not
available for all years after 1990, the periodic availability of survey data reduces the uncertainty of these
data. The assumption that waste generation per capita prior to 1994 is constant likely overestimates
the MSW generation for this time period. Further, estimating MSW generation based on population does
not account for the fact that not all of the population may be serviced with waste collection. Combined
uncertainty values of EFs are estimated as 30.8% and 38.1% for managed and unmanaged SWDS
based on Table 3.5 in 2006 IPCC, Volume 5, Chapter3.
In 2019 submission Monte Carlo simulation is applied to waste sector entirely. The uncertainty estimate
was performed by integrating the Monte Carlo simulation straight to the FOD model. According to
Approach 2 (Monte Carlo method) results, the combined uncertainty range for CH4 emissions from
managed SWDS is -34.93% to +34.82% while for unmanaged SWDS is -46.85% to +47.31% in 2017.
Detailed information is in Annex 2.
The estimates are calculated in a consistent manner over time series.
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Source-Specific QA/QC and Verification:
QA/QC procedures are implemented for each category in order to verify and improve the inventory
under the QA/QC plan of Türkiye.
The data used in Solid Waste Disposal (CRF Category 5.A) are derived from waste statistics database
of TurkStat. TurkStat is producing all its statistics according to the European Code of Practice Principles.
Therefore, high quality data are used in the emission estimates of this category.
Moreover, a QA work was conducted by an external reviewer (expert from CITEPA - Technical Reference
Center for Air Pollution and Climate Change) for this category in December 2019.
As part of sector-specific QA/QC, waste and GHG experts from TurkStat made a plant visit to one of the
largest facilities in landfill gas recovery in December 2022.
Recalculation:
The revision of 2019 and 2020 GDP data by TurkStat resulted in changes in total industrial waste in the
SWDS, which led to minor recalculation in CH4 emissions from unmanaged SWDS for 2020.
Mainly, methane recovery data from some landfill gas recovery facilities has been recalculated for the
years 2014-2016 and 2018-2020 as a result of ongoing verification and comparison activities for the
quantity of methane in the recovered landfill gas.
The amount of sewage sludge for 2018 and 2020 has been recalculated due to the correction made in
the total of “other disposal” in unmanaged landfills. 2017 and 2019 AD were also affected by this
correction, as they were estimated by the interpolation method. These have resulted in recalculations
in methane emissions from sewage sludge in 2018-2020.
In summary, total CH4 emissions from solid waste disposal sites have been recalculated between the
years 2014 and 2020. Compared to the previous inventory submission, CH4 emissions from Solid Waste
Disposal decreased by 1.1 per cent (125 kt CO2 eq.) in 2020, mainly due to increase of methane
recovery. There is no recalculation for 1990.
Planned Improvement:
As noted above, a question has been asked about the flaring of landfill gas in the Waste Disposal and
Recovery Facilities Survey, 2020. According to the results of the survey, it has been determined that
there is no flaring at the waste disposal sites in Türkiye. The results of the next survey (Waste Disposal
and Recovery Facilities Survey, 2022) will be assessed, and if appropriate, the results incorporated into
the next inventory submission(s).
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7.3. Biological Treatment of Solid Waste (Category 5.B)
Source Category Description:
This category includes emissions from composting and anaerobic digestion of organic waste. Türkiye
reports CH4 and N2O emissions from composting of municipal solid waste (5.B.1). Türkiye has no
information available on the existence of anaerobic digestion of organic waste. Therefore, consistent
with the 2006 IPCC Guidelines, Türkiye assumes that there is no anaerobic digestion in the country.
However, this treatment process will be also considered and reported in coming years depending on
availability of any information.
The total biological treatment of solid waste emissions for both gases increased by 54.4% (8.7 kt CO2
eq.) between 1990 (16.1 kt CO2 eq.) and 2021 (24.8 kt CO2 eq.).
Methodological Issues:
To estimate both CH4 and N2O emissions for composting, Türkiye multiples the mass of organic waste
composted by a default emission factor (the IPCC T1 method), as recommended in the 2006 IPCC
Guidelines for National GHG Inventories. The CH4 and N2O emissions of biological treatment can be
estimated using the default method based on Equations 4.1 and 4.2 in 2006 IPCC, Volume 5, Chapter
4 as given below.
𝐶𝐶𝐶𝐶� 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 = �(𝑀𝑀� ⦁ 𝐸𝐸𝐸𝐸� ) ⦁ 10�� − 𝑅𝑅
�
Where:
CH4 Emissions = total CH4 emissions in inventory year, Gg CH4
Mi = mass of organic waste treated by biological treatment type i, Gg
EF = emission factor for treatment i, g CH4/kg waste treated
i = composting or anaerobic digestion
R = total amount of CH4 recovered in inventory year, Gg CH4
𝑁𝑁� 𝑂𝑂 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 = �(𝑀𝑀� ⦁ 𝐸𝐸𝐸𝐸� ) ⦁ 10��
�
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Where:
N2O Emissions = total N2O emissions in inventory year, Gg N2O
Mi = mass of organic waste treated by biological treatment type i, Gg
EF = emission factor for treatment i, g N2O/kg waste treated
i = composting or anaerobic digestion
Collection of Activity Data
The amount of municipal solid waste delivered to composting plants (1994-1998, 2001-2004, 2006,
2008, 2010, 2012, 2014, 2016, 2018 and 2020) are available in TurkStat's Municipal Waste Statistics as
provided in Table 7.5. Remaining years are estimated with linear interpolation method except 19901993 period. For this beginning period, data was considered the same as for 1994. However, this data
is the "amount of waste delivered to composting plants" not the "amount of waste treated by composting
plants". Using this data directly will cause overestimation problem. On the other hand, the composted
waste data are available in TurkStat's Municipal Waste Statistics for the years 2006, 2008 and 2010,
and in TurkStat's Waste Disposal and Recovery Facilities Statistics for the years 2005, 2012, 2014, 2016,
2018 and 2020. For aforementioned years, composted waste amounts are taken into account instead
of delivered amounts. The 2005 survey data is the oldest reliable data since it is asked to both
municipalities and composting plants. Thus, for 2005, The ‘fraction of waste composted’ is calculated
as the "amount of waste treated by composting plants" divided by the "amount of waste delivered to
composting plants" in order to understand the “amount of waste treated by composting plants" is how
much smaller than "amount of waste delivered to composting plants" to estimate the earlier years before
2001. Because after 2001, TurkStat has the composted waste data of the composting plant with the
largest share. The “amount of waste treated by composting plants" is approximately the half of the
"amount of waste delivered to composting plants" in 2005 (0.49). This ‘fraction of waste composted’ is
used as a multiplier for 1990-2000 period with the "amount of waste delivered to composting plants"
survey data.
Since 2001, the composting plant with the largest share is located in Istanbul, which is the largest city
of Türkiye in terms of population. The data of this composting plant has been collected directly by
sending official letters to the facility itself. These data of the biggest composting plant are not used
directly for the total amount of waste composted because at that time it would have caused
underestimation problem. Those available data are used as surrogate data (as one of the recommended
splicing techniques in 2006 IPCC Guidelines) with the survey data mentioned above, to avoid
overestimation problem resulting from using the "amount of waste delivered to composting plants”
survey data for generating a complete time series.
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To summarize the activity data described in detail above, 1990-2000 data were estimated by using the
‘fraction of waste composted’. 2001-2013 data were obtained by estimating from surrogate data.
However, if available, survey data were used instead of surrogate data estimations (2005 and 2012).
As of 2015, the official data on the amount of waste treated by composting plants were started to be
compiled directly from the relevant facilities for the years without survey (2015, 2017, 2019 and 2021).
Thus, a complete time series was obtained with the available survey data (2014, 2016, 2018 and 2020).
The number of facilities operating each year and the total capacity of composting plants for each year
in Türkiye is indicated below.
Table 7.23 Number and total capacity of composting plants, 1994-2021
# of composting
plants with
installed capacity
# of operating
composting
plants
Capacity
(thousand
tonnes/year)
1994-1998
2001
2
3
NA
NA
245
299
2002
2003
4
5
NA
NA
664
667
2004
2005
5
4
NA
NA
667
606
2006
2008
4
4
NA
NA
605
551
2010
2012
5
6
NA
6
556
389
2014
2015
4
4
3
3(3)
310
310
2016
2017
7
7
5
5(3)
424
424
2018
2019
8
8
6
6(3)
483
483
2020
2021
9
9
8
6(3)
651
651
Year
Source: (1) TurkStat, Municipal Waste Statistics, 1994-2010
(2) TurkStat, Waste Disposal and Recovery Facilities Statistics, 2012-2020
(3) Administrative records obtained by official letters
The number of composting plants with installed capacity and the operating ones are provided separately
for available years in Table 7.23. Since the official data (number of facilities) of the survey indicates the
number of composting plants with installed capacity, not those active ones in the relevant press releases,
precise information on the number of facilities operating by year is not available before 2012. For years
without survey (2015, 2017, 2019 and 2021), the number and total capacity of composting plants with
installed capacity are assumed to be the same as the previous year.
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Choice of Emission Factor
EFs of 4.0 g CH4/kg waste treated (on a wet weight basis) and 0.24 g N2O/kg waste treated (on a wet
weight basis) are selected for the estimates of CH4 and N2O emissions respectively, based on Table 4.1
in the 2006 IPCC Guidelines, Volume 5, Chapter 4.
The total annual amount of waste treated (as wet weight) by composting plants and emissions from
composting are provided in Table 7.24.
Table 7.24 Activity data, CH4 and N2O emissions from composting, 1990-2021
Year
1990-94
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Amount of waste
treated by
composting
plants
93.7
77.5
97.9
165.4
174.6
169.6
158.9
120.4
128.0
135.4
140.3
134.1
119.2
127.6
119.5
144.7
(kt)
CH4
Emissions
0.37
0.31
0.39
0.66
0.70
0.68
0.64
0.48
0.51
0.54
0.56
0.54
0.48
0.51
0.48
0.58
N2O
Emissions
0.022
0.019
0.023
0.040
0.042
0.041
0.038
0.029
0.031
0.032
0.034
0.032
0.029
0.031
0.029
0.035
As seen in Figure 7.3, Figure 7.4 and Figure 7.5, the fluctuations of CH4 and N2O emissions from
composting depend mainly on fluctuations of the amount of waste treated by composting plants (AD).
Emissions were relatively stable between 1990 and 2000 due to the same number of operating facilities
during that period. A remarkable increase was observed when the dominant facility became operational
after 2001. Fluctuations have been observed in recent years due to the change in the number of facilities
operating in those years, as provided in Table 7.23.
CH4 emissions have a maximum value of 0.88 kt in 2003 while having a minimum value of 0.31 kt in
1995. Likewise, N2O emissions have a maximum value of 0.053 kt in 2003 while having a minimum
value of 0.019 kt in 1995.
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0.00
398
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2020
2021
2020
2021
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
2019
0.01
2019
0.02
2018
0.03
2018
0.04
2017
0.05
2016
(kt)
2017
Figure 7.5 N2O emissions from composting, 1990-2021
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
0.06
1992
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
1990
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
0
1991
250
1990
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Waste
Figure 7.3 Amount of waste treated by composting plants, 1990-2021
(kt)
200
150
100
50
Figure 7.4 CH4 emissions from composting, 1990-2021
(kt)
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Uncertainties and Time-Series Consistency:
The uncertainty value for AD is estimated as 10.0% based on Table 3.5 in the 2006 IPCC Guidelines,
Volume 5, Chapter 3. The uncertainty value of the EF is considered as 20.0% for both CH4 and N2O EFs
since there is no sufficient information in 2006 IPCC.
The Biological treatment of solid waste category employed a Monte Carlo uncertainty analysis which
causes a combined uncertainty range ±22.2% for CH4 emissions and +50% for N2O emissions in 2019
submission. Detailed explanation of Approach 2 method is in Uncertainty part of this inventory report
(Annex 2).
The estimates are calculated in a consistent manner over time series.
Source-Specific QA/QC and Verification:
QA/QC procedures are implemented for each category in order to verify and improve the inventory
under the QA/QC plan of Türkiye.
The data used in Biological Treatment of Solid Waste (CRF Category 5.B) are derived from waste
statistics database of TurkStat. TurkStat is producing all its statistics according to the European Code of
Practice Principles. Therefore, high quality data are used in the emission estimates of this category.
Moreover, a QA work was conducted by an external reviewer (expert from CITEPA - Technical Reference
Center for Air Pollution and Climate Change) for this category in December 2019.
Recalculation:
There is no recalculation for this category in this submission.
Planned Improvement:
Emissions and amount of CH4 for energy recovery from anaerobic digestion at biogas facilities (5.B.2)
will be included in next inventory submissions depending on the availability of such treatment processes.
Türkiye continues to monitor the available waste statistics and any other information to determine the
existence of biogas facilities with anaerobic digestion. At this time, no such information exists, but when
it becomes available, Türkiye intends to estimate these emissions.
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7.4. Incineration and Open Burning of Waste (Category 5.C)
Source Category Description:
This category includes emissions from open burning of waste. The category covers CO2, CH4 and N2O
emissions from open burning of waste (5.C.2) which is divided into waste of biogenic origin (5.C.2.1)
and waste of non-biogenic origin (5.C.2.2). Only municipal solid waste is open burned in Türkiye
(5.C.2.2.a). CO2 emissions from waste of biogenic origin are reported but not counted as part of the
national total GHG emissions. Unlike CO2, emissions of CH4 and N2O from biogenic derived wastes are
estimated and accounted for under the waste sector.
Emissions from waste incineration (5.C.1) are included in the inventory but reported in the energy sector
since the purpose of waste incineration is for energy recovery. Emissions from MSW of biogenic origin
(5.C.1.1.a) and MSW of non-biogenic origin (5.C.1.2.a) are not occurring since MSW is not incinerated
in the incineration plants in Türkiye.
Emissions from incineration of industrial solid waste of biogenic origin (5.C.1.1.b.i) and industrial solid
waste of non-biogenic origin (5.C.1.2.b.i) are included in public electricity and heat production (1.A.1.a),
chemicals (1.A.2.c) and other (1.A.2.g) sub-categories in the energy sector.
Emissions from incineration of clinical waste of biogenic origin (5.C.1.1.b.ii) and clinical waste of nonbiogenic origin (5.C.1.2.b.ii) are included in public electricity and heat production (1.A.1.a).
Emissions from open burning of waste declined 93% (97.8 kt CO2 eq.) between 1990 to 2021. The main
reason of this negative trend is the decreasing amount of waste open-burned by years, especially with
a sharp decline in 2014 after the law of Ministry of Environment, Urbanization and Climate Change.
Methodological Issues:
The IPCC Tier 2a method recommended in the 2006 IPCC Guidelines for National GHG Inventories is
applied to estimate CO2 emissions. As elaborated below, Türkiye multiplies the amount of waste types
open-burned (wet weight) by the dry matter content, the fossil carbon fraction and an oxidation factor.
To estimate CH4 and N2O emissions, IPCC default emission factors are multiplied by the amount of
waste open-burned (the IPCC T1 method in the 2006 IPCC Guidelines).
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CO2 Emissions
The CO2 emissions from open burning of waste are estimated on the basis of waste types/material (such
as paper, wood, plastics) in the waste open-burned as given in Equation 5.2 in the 2006 IPCC Guidelines,
Volume 5, Chapter 5.
𝐶𝐶𝐶𝐶� 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 = 𝑀𝑀𝑀𝑀𝑀𝑀 ⦁ ��𝑊𝑊𝑊𝑊� ⦁ 𝑑𝑑𝑑𝑑� ⦁ 𝐶𝐶𝐶𝐶� ⦁ 𝐹𝐹𝐹𝐹𝐹𝐹� ⦁ 𝑂𝑂𝑂𝑂� � ⦁ 44/12
�
Where:
CO2 Emissions = CO2 emissions in inventory year, Gg/yr
MSW = total amount of municipal solid waste as wet weight open-burned, Gg/yr
WFj = fraction of waste type/material of component j in the MSW (as wet weight openburned)
dmj = dry matter content in the component j of the MSW open-burned, (fraction)
CFj = fraction of carbon in the dry matter (i.e., carbon content) of component j
FCFj = fraction of fossil carbon in the total carbon of component j
OFj = oxidation factor, (fraction)
44/12 = conversion factor from C to CO2
j = component of the MSW open-burned such as paper/cardboard, textiles, food
waste, wood, garden (yard) and park waste, disposable nappies, rubber and leather,
plastics, metal, glass, other inert waste.
The biogenic CO2 emissions from open burning should not be included in national total emission
estimates according to the information given in 2006 IPCC, Volume 5, Chapter 5, Section 5.1 as in Table
7.25. Total CO2 emissions from open burning fluctuate between 1990-2021 as shown in Figure 7.6.
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Table 7.25 CO2 emissions from open burning of waste, 1990-2021
(kt)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Total
26.59
25.96
20.98
11.87
11.21
14.09
14.42
7.37
0.48
1.07
1.84
1.54
1.24
2.38
3.62
3.65
Biogenic
0.288
0.285
0.345
0.235
0.142
0.123
0.088
0.045
0.003
0.006
0.011
0.009
0.006
0.011
0.017
0.017
Non-biogenic
26.59
25.96
20.98
11.87
11.21
14.09
14.42
7.37
0.48
1.07
1.84
1.54
1.24
2.38
3.62
3.65
Figure 7.6 CO2 emissions from open burning of waste, 1990-2021
45
40
(kt)
35
30
25
20
15
10
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
5
CH4 Emissions
The calculation of CH4 emissions is based on the amount of waste open-burned and on the related
emission factor as given in Equation 5.4 in the 2006 IPCC Guidelines, Volume 5, Chapter 5.
𝐶𝐶𝐶𝐶� 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 = �(𝐼𝐼𝐼𝐼� ⦁ 𝐸𝐸𝐸𝐸� ) ⦁ 10��
�
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Where:
CH4 Emissions = CH4 emissions in inventory year, Gg/yr
IWi = amount of solid waste of type i open-burned, Gg/yr
EFi = aggregate CH4 emission factor, kg CH4/Gg of waste
10-6 = conversion factor from kilogram to gigagram
i = category or type of waste open-burned, specified as follows:
MSW: municipal solid waste, ISW: industrial solid waste, HW: hazardous waste,
CW: clinical waste, SS: sewage sludge, others (that must be specified)
Estimated results of CH4 emissions are given in Table 7.26 and Figure 7.7. The CH4 emissions show a
decreasing trend with the same fluctuations as with AD between 1990 and 2021 as can be seen in
Figure 7.9 below.
Table 7.26 CH4 emissions from open burning of waste, 1990-2021
(kt)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Total
2.69
2.63
2.25
1.18
0.87
0.79
0.68
0.36
0.03
0.04
0.07
0.05
0.04
0.08
0.12
0.12
Biogenic
1.81
1.76
1.39
0.67
0.52
0.51
0.46
0.24
0.02
0.03
0.05
0.04
0.03
0.06
0.08
0.08
Non-biogenic
0.88
0.87
0.85
0.52
0.35
0.29
0.22
0.12
0.01
0.01
0.02
0.02
0.01
0.03
0.04
0.04
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Figure 7.7 CH4 emissions from open burning of waste, 1990-2021
4.50
(kt)
4.00
3.50
3.00
2.50
2.00
1.50
1.00
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0.00
1990
0.50
N2O Emissions
The calculation of N2O emissions is based on the amount of waste open-burned and a default emission
factor as given in Equation 5.5 in the 2006 IPCC Guidelines, Volume 5, Chapter 5.
𝑁𝑁� 𝑂𝑂 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 = �(𝐼𝐼𝐼𝐼� ⦁ 𝐸𝐸𝐸𝐸� ) ⦁ 10��
Where:
�
N2O Emissions = N2O emissions in inventory year, Gg/yr
IWi = amount of open-burned waste of type i, Gg/yr
EFi = N2O emission factor (kg N2O/Gg of waste) for waste of type i
10-6 = conversion from kilogram to gigagram
i = category or type of waste open-burned, specified as follows:
MSW: municipal solid waste, ISW: industrial solid waste, HW: hazardous waste,
CW: clinical waste, SS: sewage sludge, others (that must be specified)
Estimated results of N2O emissions from open burning of waste are given in Table 7.27 and Figure 7.8.
As with CH4 emissions, N2O emissions have a decreasing trend with the same fluctuations as of AD
between 1990 and 2021 as can be seen in Figure 7.9 below.
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Table 7.27 N2O emissions from open burning of waste, 1990-2021
(kt)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Total
0.0377
0.0369
0.0337
0.0190
0.0135
0.0119
0.0098
0.0051
0.0004
0.0006
0.0009
0.0008
0.0006
0.0012
0.0018
0.0019
Biogenic
0.0191
0.0187
0.0158
0.0082
0.0060
0.0057
0.0050
0.0026
0.0002
0.0003
0.0005
0.0004
0.0003
0.0006
0.0009
0.0009
Non-biogenic
0.0185
0.0182
0.0179
0.0109
0.0075
0.0062
0.0048
0.0026
0.0002
0.0003
0.0004
0.0004
0.0003
0.0006
0.0009
0.0009
Figure 7.8 N2O emissions from open burning of waste, 1990-2021
0.07
(kt)
0.06
0.05
0.04
0.03
0.02
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0.00
1990
0.01
Collection of Activity Data
Activity data for open burning of MSW are estimated using the total amount of MSW open-burned (19941998, 2001-2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018 and 2020) as obtained from TurkStat's
Municipal Waste Statistics Survey as given in Table 7.5 and applying an estimate of the composition of
MSW.
To calculate the total amount of MSW open-burned for the years not surveyed (1999, 2000, 2005, 2007,
2009, 2011, 2013, 2015, 2017 and 2019) the total amount of MSW open-burned as a fraction of the
MSW generated data is calculated for the available years (MSW generated data are given in Table 7.8).
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Open-burned % in generated MSW for the years 1999, 2000, 2005, 2007, 2009, 2011, 2013, 2015,
2017 and 2019 are estimated by linear interpolation. Due to lack of historical data for MSW openburned, the open-burned % of 1994 (1.89%) is used for 1990-1993. Since the trend extrapolation
should not be used, the open-burned % of 2021 was assumed the same as in 2020 to avoid
underestimation. As a result, the total amount of MSW open-burned is calculated for the entire timeseries and provided in Table 7.28 and Figure 7.9.
Table 7.28 The fraction and amount of MSW open-burned, 1990-2021
Fraction of MSW
open-burned
(%)
1.89
1.49
1.13
0.58
0.45
0.40
0.34
0.18
0.01
0.02
0.03
0.02
0.02
0.04
0.05
0.05
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Amount of MSW
open-burned
(kt)
414.22
405.03
345.52
182.05
133.88
121.98
104.75
54.72
4.28
6.86
10.17
8.18
6.13
12.69
19.02
19.17
Figure 7.9 Total amount of MSW open-burned, 1990-2021
700
(kt)
600
500
400
300
200
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2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
100
406
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Waste
Country-specific values on the total waste amount (Table 7.28) and the waste fraction for each
component for MSW are needed to apply Tier 2a. To calculate the country-specific waste fraction, time
series of MSW composition data (see Table 7.10) are used. Default dry matter content, total carbon
content and fossil carbon fraction of different MSW components are given in Table 7.29 which is based
on Table 2.4 in the 2006 IPCC Guidelines, Volume 5, Chapter 2.
Table 7.29 Default dry matter content, total carbon content and fossil carbon fraction
(%)
Dry matter
content in % of
wet waste
Total carbon
content in % of
dry weight
Fossil carbon
fraction in % of
total carbon
MSW Component
Origin
Paper/cardboard
Biogenic
90.0
46.0
1.0
Textiles
Non-biogenic
80.0
50.0
20.0
Food waste
Biogenic
40.0
38.0
-
Wood
Biogenic
85.0
50.0
-
Garden and park waste
Biogenic
40.0
49.0
0.0
Plastics
Non-biogenic
100.0
75.0
100.0
Metal
Non-biogenic
100.0
NA
NA
Glass
Non-biogenic
100.0
NA
NA
Other, inert waste
Non-biogenic
90.0
3.0
100.0
Choice of Emission Factor
Dry matter content (dm), total carbon content (CF) and fossil carbon fraction (FCF) in MSW are
calculated using Equations 5.8, 5.9 and 5.10 respectively as given in the 2006 IPCC Guidelines, Volume
5, Chapter 5. All different waste fractions (WF) are given in Table 7.10 and the fractions of carbon
content given in Table 7.29 above are used related to CO2 emission factors. A default oxidation factor
in % of carbon input (OF) is selected for MSW as 58.0% based on Table 5.2 in 2006 IPCC, Volume 5,
Chapter 5.
The CH4 emissions from open burning of waste are estimated using an EF of 6500 g CH4 / t wet weight
for both biogenic and non-biogenic origin of MSW as reported in the 2006 IPCC Guidelines, Volume 5,
Chapter 5, Section 5.4.2.
The N2O emissions from open burning of waste are estimated using an EF of 150 g N2O / t dry weight
for MSW according to the 2006 IPCC Guidelines, Volume 5, Chapter 5, Table 5.6. Since the related EF
refers to dry weight, the weight of waste open-burned is converted from wet weight to dry weight as
reported in the 2006 IPCC Guidelines, Volume 5, Chapter 5, Section 5.3.3 for MSW of both biogenic and
non-biogenic origin.
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Uncertainties and Time-Series Consistency:
The uncertainty value for AD is estimated as 30.4%. The uncertainty value of the CO2 EF is considered
as 40.0%. Since default values for CH4 and N2O EFs are used, the uncertainty values of ± 100% are
estimated for both EFs as recommended in the 2006 IPCC Guidelines, Volume 5, Chapter 5, Section
5.7.1.
An uncertainty analysis using the Monte Carlo technique was carried out to estimate emissions of CO2
for 5.C category and also to other waste categories in 2019 submission. Combined uncertainty in CO2
emissions in 2017 is estimated at ±41.88%, CH4 emissions is estimated as -85.71% to +114.29% and
in N2O emissions is estimated as -72.73% to +100%. Further information is given in Uncertainty part
at the end of this inventory report (Annex 2).
The estimates are calculated in a consistent manner over time series.
Source-Specific QA/QC and Verification:
QA/QC procedures are implemented for each category in order to verify and improve the inventory
under the QA/QC plan of Türkiye.
The data used in Incineration and Open Burning of Waste (CRF Category 5.C) are derived from the
waste statistics database of TurkStat. TurkStat is producing all its statistics according to the European
Code of Practice Principles. Therefore, high quality data are used in the emission estimates of this
category.
Moreover, a QA work was conducted by an external reviewer (expert from CITEPA - Technical Reference
Center for Air Pollution and Climate Change) for this category in December 2019.
Recalculation:
There is no recalculation for this category in this submission.
Planned Improvement:
There are no planned improvements in this category.
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6
7.5. Wastewater Treatment and Discharge (Category 5.D)
Source Category Description:
This category includes CH4 and N2O emissions from wastewater treatment and discharge systems.
Wastewater originates from domestic, commercial and industrial sources by treatment and disposal
systems. Because of the IPCC methodology, emissions from commercial wastewater are estimated as
part of domestic wastewater. Treatment and disposal types for domestic and industrial wastewater are
separated into collected and uncollected systems. Each system is divided into untreated and treated
systems. For collected systems; sea, river and lake discharge, and stagnant sewer are the untreated
systems. Aerobic and anaerobic treatments are the main treated systems of sewered to plants. For
uncollected systems; septic system is considered as treated and sea, river and lake discharge as
untreated practices in Türkiye.
CH4 emissions are estimated for both domestic wastewater (5.D.1) and industrial wastewater (5.D.2).
N2O emissions from 5.D.2 are also reported in 5.D.1.
Wastewater treatment and discharge emissions increased by 26% (1 098 kt CO2 eq.) for the period
1990-2021, also increased by 3% (159 kt CO2 eq.) between 2020 and 2021. Methane recovery in
domestic wastewater treatment increased by 411% (565 kt CO2 eq.) between 1998 (137 kt CO2 eq.)
and 2021 (702 kt CO2 eq.).
Methodological Issues:
Methane Emissions from Wastewater
Methane Emissions from Domestic Wastewater
The IPCC T2 method of the 2006 IPCC Guidelines is applied to estimate CH4 emissions from domestic
wastewater. CH4 emissions are estimated using Equation 6.1 in the 2006 IPCC Guidelines, Volume 5,
Chapter 6.
𝐶𝐶𝐶𝐶� 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 = ���𝑈𝑈� ⦁ 𝑇𝑇�,� ⦁ 𝐸𝐸𝐸𝐸� �� ( 𝑇𝑇𝑇𝑇𝑇𝑇 − 𝑆𝑆) − 𝑅𝑅
�,�
Where:
CH4 Emissions = CH4 emissions in inventory year, kg CH4/yr
TOW = total organics in wastewater in inventory year, kg BOD/yr
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S = organic component removed as sludge in inventory year, kg BOD/yr
Ui = fraction of population in income group in inventory year
Ti,j= degree of utilisation of treatment/discharge pathway or system, j, for each income
group fraction in inventory year
i = income group: rural, urban high income and urban low income
j = each treatment/discharge pathway or system
EFj = emission factor, kg CH4 / kg BOD
R = amount of CH4 recovered in inventory year, kg CH4/yr
Total CH4 emissions are estimated based on country-specific information on the total organics in
wastewater minus the total amount of sludge and multiplying by the IPCC default emission factor,
corrected for country-specific fractions of urban/rural populations and the fraction of the wastewater
utilizing the various discharge pathways. The amount of methane generated, methane recovered and
net methane emissions are estimated as given in Table 7.30 and Figure 7.10.
Table 7.30 CH4 generated, recovered and emitted from domestic wastewater, 1990-2021
(kt)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
410
CH4
Generated
103.2
109.7
115.6
119.6
121.1
122.4
123.5
111.6
112.7
113.9
115.2
116.5
118.4
119.5
120.5
121.4
CH4
Recovered
NO
NO
6.9
11.9
16.8
21.5
24.4
25.1
34.3
36.1
36.4
37.3
31.0
31.2
30.7
28.1
Turkish GHG Inventory Report 1990-2021
CH4
Emitted
103.2
109.7
108.6
107.7
104.3
100.9
99.0
86.5
78.5
77.8
78.8
79.2
87.4
88.3
89.8
93.3
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Figure 7.10 CH4 emissions from domestic wastewater, 1990-2021
140
(kt)
120
100
80
60
40
CH₄ generated
CH₄ recovered
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
20
CH₄ emitted (net emissions)
The key drivers for the decreasing trend in net emissions are the increasing of methane recovery after
the beginning year of 1998. Despite having an increasing trend normally, the main reasons for the sharp
decreases in generated methane in the years of 2008 and 2013 are the administrative division changes
in the proportion of urban and rural population in 2008 and 2013.
Collection of Activity Data
To calculate CH4 emissions from domestic wastewater, total organics in wastewater (TOW) and organic
component removed as sludge (S) are needed. The TOW is calculated using Equation 6.3 in the 2006
IPCC Guidelines, Volume 5, Chapter 6.
Where:
𝑇𝑇𝑇𝑇𝑇𝑇 = 𝑃𝑃 ⦁ 𝐵𝐵𝐵𝐵𝐵𝐵 ⦁ 0.001 ⦁ 𝐼𝐼 ⦁ 365
TOW = total organics in wastewater in inventory year, kg BOD/yr
P = country population in inventory year, (person)
BOD = country-specific per capita BOD in inventory year, g/person/day,
0.001 = conversion from grams BOD to kg BOD
I = correction factor for additional industrial BOD discharged into sewers (for collected the
default is 1.25, for uncollected the default is 1.00.)
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The total population is used to calculate TOW and S values. For the entire time series, the total
population is taken from Turkstat’s Mid-year Population Estimations and Projections. The total
population is then divided into the rural and urban fractions to better characterize the discharge
pathways for the domestic wastewater. For the years 1990 and 2000, rural and urban population are
available from General Population Censuses. The results of Address Based Population Registration
System are used from 2007 to 2021 to split the rural and urban population. Rural and urban population
fractions are used to interpolate fractions of rural and urban population for the missing years. The
figures are given in Table 7.31.
Table 7.31 Fraction of population and total, rural, urban population, 1990-2021
Year
Fraction
of rural
Fraction
of urban
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
41.0
38.0
35.1
31.1
23.7
23.2
22.7
8.7
8.2
7.9
7.7
7.5
7.7
7.2
7.0
6.8
59.0
62.0
64.9
68.9
76.3
76.8
77.3
91.3
91.8
92.1
92.3
92.5
92.3
92.8
93.0
93.2
Total
population
55
59
64
68
73
74
75
76
77
78
79
80
81
82
83
84
120
756
269
435
142
224
176
148
182
218
278
313
407
579
385
147
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
000
Rural
population
22
22
22
21
17
17
17
6
6
6
6
6
6
5
5
5
592
732
557
293
362
222
076
588
367
176
101
012
291
962
862
735
114
684
058
571
715
484
420
471
326
615
802
149
257
131
196
295
Urban
population
32
37
41
47
55
57
58
69
70
72
73
74
75
76
77
78
527
023
711
141
779
001
099
559
814
041
176
300
115
616
522
411
886
316
942
429
285
516
580
529
674
385
198
851
743
869
804
705
The urban population consists of the total population of province and district centers and, rural
population consists of the total population of towns and villages. The proportions of the population living
in the province and district centers were 91.3% in 2013 and 93.2% in 2021 while this figure was 77.3%
in 2012. The main reason for this sharp rise was the establishment of 14 new metropolitan municipalities
and enlarging the municipal borders by abolition of towns and villages in all of the 30 metropolitan
provinces in 2013.
TOW is calculated using a country-specific per capita BOD as 53 g/person/day for wastewater collected
by sewers. The source of this BOD is Derivation of Factors for Pollution Loads Discharged to Receiving
Bodies by Municipalities, İpek Turtin Uzer, Turkish Statistical Institute Expertness Thesis, Ankara, 2010.
This study includes a country-specific per capita BOD for receiving bodies as 25 g/person/day. Countryspecific per capita BOD for sludge removed is calculated as 28 g/person/day by using these data to be
able to calculate organic component removed as sludge (S). Correction factor (I) is taken as the default
value of 1.0. TOW and S values for domestic wastewater are calculated as given in Table 7.32.
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6
Table 7.32 Total organics in wastewater (TOW) and organic component removed as
sludge (S) for domestic wastewater, 1990-2021
(kt BOD/yr)
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
TOW
066.3
156.0
243.3
323.9
414.9
435.9
454.3
473.1
493.1
513.1
533.6
553.7
574.8
597.5
613.1
627.8
S
563.3
610.7
656.8
699.4
747.5
758.6
768.3
778.2
788.8
799.4
810.2
820.8
832.0
844.0
852.2
860.0
Choice of Emission Factor
As given in Equation 6.2 in the 2006 IPCC Guidelines, Volume 5, Chapter 6, CH4 EFs for each domestic
wastewater treatment/discharge pathway or system are calculated by multiplying the default maximum
CH4 producing capacity (Bo) for domestic wastewater (0.6 kg CH4/kg BOD) by the methane correction
factor (MCF) for each type of treatment and discharge pathway or system, which is given in the 2006
IPCC Guidelines, Volume 5, Chapter 6, Table 6.3.
Where:
𝐸𝐸𝐸𝐸� = 𝐵𝐵� ⦁ 𝑀𝑀𝑀𝑀𝑀𝑀�
EFj = emission factor, kg CH4/kg BOD
j = each treatment/discharge pathway or system
Bo = maximum CH4 producing capacity, kg CH4/kg BOD
MCFj = methane correction factor (fraction)
To calculate country-specific values for the degrees of treatment utilization (T), by population class, the
results of TurkStat's Municipal Wastewater Statistics Survey, 2012 and Sectoral Water and Wastewater
Statistics Survey, 2012 are used. The degrees of utilizations are given in Table 7.33.
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Table 7.33 Degrees of treatment utilization (T) by population class
Treatment or discharge system or pathway
Rural
Urban
T (%)
To sea, river and lake
0.43
To aerobic plant, not well managed
0.44
To septic systems
10.72
To sea, river and lake
15.43
To aerobic plant, well managed
44.01
To aerobic plant, not well managed
1.82
To anaerobic digester for sludge
20.83
To septic systems
6.31
Total
100.00
Weighted CH4 EFs are calculated using CH4 EFs by each type of treatment and discharge pathway or
system and the fractional usage of different treatment systems by population class. Weighted CH4 EFs
for domestic wastewater with background data are given in Table 7.34.
Table 7.34 MCF, EFs, utilization degrees and weighted EFs by population class
Type of treatment and discharge
path way or system
MCF
CH4 EF
T (Rural)
T (Urban)
0.10
0.06
0.0043
0.1543
Centralized, aerobic, well managed
0.00
0.00
Centralized, aerobic, not well managed
0.30
0.18
Anaerobic digester for sludge
0.80
0.48
Septic system
0.50
0.30
Untreated system
Sea, river, lake discharge
Treated system
414
0.4401
0.0044
0.0182
0.2083
0.1072
0.0631
Total
0.12
0.88
Weighted CH4 EFs (kg CH4/kg BOD)
0.29
0.15
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6
Methane Recovery
The recovery of methane and its subsequent utilization is also considered in the inventory. Methane
recovery from biogas started to be implemented in Türkiye in 1998. Therefore, the quantity of recovered
methane is subtracted from the methane produced beginning in the year 1998. In 2013, Municipal
Wastewater Statistics Survey, 2012 was applied to all municipalities. Based on the information obtained
from the survey, TurkStat sends official letters to each facility recovering methane for requesting the
quantity of methane gas and electricity/heat production for the entire operating period of the facility
every year. The facilities estimate the quantity of methane recovered by measuring of gas recovered.
The obtained information on the quantity of produced electricity/heat is used for cross-check of the
quantity of methane recovered.
The coverage of the facilities is followed and updated depending on availability of new information; such
as information obtained from the facility, the information from the most recent (biennial) survey (i.e.
Municipal Wastewater Statistics Survey, 2020). The emissions of energy production from the recovered
CH4 gas in biogas facilities were included in the category of Public Electricity and Heat Production
(1.A.1.a).
The number of biogas facilities in wastewater treatment plants and the amount of recovered methane
by year are given in Table 7.35.
Table 7.35 Methane recovery, 1990-2021
Year
1990-97
1998
1999
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Number of
biogas facilities
NA
1
1
1
4
8
13
14
18
19
20
23
23
27
26
25
22
Recovered
methane (kt)
NO
5.5
6.2
6.9
11.9
16.8
21.5
24.4
25.1
34.3
36.1
36.4
37.3
31.0
31.2
30.7
28.1
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Waste
Sewage Sludge Balance
Sewage sludge is domestic wastewater treatment sludge originating from urban wastewater treatment
plants operated by municipalities. Thus, the sewage sludge data are collected by TurkStat from
Municipal Wastewater Statistics Survey which is applied to all municipalities. Data on the amount of
sludge is compiled on a wet basis and converted to dry matter using coefficients in the guidance
documents of the European Union Statistical Office (EUROSTAT). Also, data are compiled in accordance
with the OECD / EUROSTAT - Wastewater statistics, environmental data and indicators data set.
As mentioned in Solid Waste Disposal section (Category 5.A), the disposal methods named ‘Dumping
onto land’, ‘Municipal dumping sites’, ‘Controlled landfill sites’, ‘Buried’ and ‘Other disposal’ are added
together and assumed as the total sludge that stored in SWDS.
For the sewage sludge balance, the amount of sewage sludge by disposal and recovery methods, please
refer to Table 7.36.
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81 795
12 512
17 118
12 433
11 412
10 255
9 261
10 349
3 423
2004
2006
2008
2010
2012
2014
2016
2018
2020
0
0
0
0
0
0
0
0
0
0
1 095
54
0
0
0
10
321
14 460
6 710
7 023
39 637
19 456
10 112
9 480
2 954
2 760
521
274
45
2 029
0
40
150
0
Dumping
onto land
38 971
36 135
62 733
41 214
107 989
92 741
58 026
65 044
12 345
13 218
31 189
28 356
10 125
1 871
1 931
1 783
1 494
(3) Includes other recovery operations.
0
5
0
0
0
0
0
20 000
48
180
4
50
297
0
0
0
0
Municipal Released
dumping sites into lake
(2) Includes other disposal operations, temporary storage, land treatment, surface impoundment etc.
(1) Data on sludge amount is in dry matter.
Source: TurkStat, Municipal Wastewater Statistics
91 104
2003
49 555
1998
26 445
34 397
1997
2002
12 322
1996
47 152
13 309
1995
2001
12 546
Agricultural Released
use into sea
1994
Year
1 040
10
0
105
22
2 018
3 074
2 161
1 000
0
0
7 300
0
0
0
0
0
135 782
143 494
93 939
53 486
29 952
13 020
2 082
0
0
0
1
0
0
0
0
0
0
75 571
85 382
83 005
91 539
101 143
98 843
104 846
85 606
92 085
57 518
55 789
40 431
6 627
26
20
0
0
Released Incineration with
Controlled
into river energy recovery landfill sites
(t)
207
4 464
278
4 670
2 517
10 243
12 890
38 281
2 154
10 302
8 378
1 500
487
2
10
0
0
29 561
31 932
43 057
46 884
45 906
71 402
67 350
31 772
36 128
0
37 560
467
0
112
2
56
26
417
15 310
23
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Other
Other
Buried disposal(2) recovery(3)
Table 7.36 Amount of sewage sludge by disposal and recovery methods, 1994-2020 (1)
Waste
6
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Methane Emissions from Industrial Wastewater
This section deals with estimating CH4 emissions from on-site industrial wastewater treatment. The IPCC
T2 method of the 2006 IPCC Guidelines is applied to estimate CH4 emissions from industrial wastewater.
CH4 emissions are estimated using Equation 6.4 in the 2006 IPCC Guidelines, Volume 5, Chapter 6.
𝐶𝐶𝐶𝐶� 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 = �[(𝑇𝑇𝑇𝑇𝑇𝑇� − 𝑆𝑆� ) 𝐸𝐸𝐸𝐸� − 𝑅𝑅� ]
�
Where:
CH4 Emissions = CH4 emissions in inventory year, kg CH4/yr
TOWi = total organically degradable material in wastewater from industry i in inventory year,
kg COD/yr
i = industrial sector
Si = organic component removed as sludge in inventory year, kg COD/yr
EFi = emission factor for industry i, kg CH4/kg COD
for treatment/discharge pathway or system(s) used in inventory year
Ri = amount of CH4 recovered in inventory year, kg CH4/yr
Specifically, the country-specific information on the total organically degradable material in wastewater,
by industry, is multiplied by a specific emission factor that takes into account the relative use of various
treatment/discharge pathways. There is no recovery of methane from industrial wastewater and sludge
removal is assumed to be zero. Amount of methane emissions, by industry, are estimated as given in
Table 7.37 and Figure 7.11.
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Table 7.37 CH4 emissions from industrial wastewater by sector, 1990-2021
(kt)
Year
Total
Meat &
poultry
Organic
chemicals
Petroleum
refineries
Plastics
& resins
Pulp & paper
(combined)
Starch
production
1990-94
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
8.37
12.01
12.82
14.80
14.32
16.50
18.68
18.85
19.02
20.00
20.97
22.86
24.75
25.02
25.29
25.56
1.37
1.79
1.47
1.90
2.03
2.42
2.81
2.79
2.76
3.24
3.72
3.91
4.10
4.23
4.37
4.50
0.54
1.62
2.38
1.03
0.36
0.50
0.63
0.67
0.71
1.03
1.34
1.34
1.34
1.34
1.35
1.36
0.12
0.12
0.15
0.13
0.11
0.15
0.19
0.19
0.19
0.20
0.22
0.24
0.25
0.28
0.30
0.33
0.70
0.75
0.48
1.54
1.14
1.99
2.84
2.88
2.92
2.98
3.05
3.49
3.93
3.86
3.80
3.74
4.56
5.43
4.55
1.25
2.41
2.52
2.64
2.74
2.85
2.82
2.79
2.93
3.06
3.54
4.02
4.50
1.09
2.29
3.80
8.96
8.26
8.91
9.57
9.58
9.60
9.72
9.84
10.96
12.07
11.76
11.45
11.14
Figure 7.11 CH4 emissions from industrial wastewater, 1990-2021
30
(kt)
25
20
15
10
Starch Production
Petroleum Refineries
Pulp & Paper
Organic Chemicals
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
5
Plastics & Resins
Meat & Poultry
Collection of Activity Data
To calculate CH4 emissions from industrial wastewater, total organically degradable material in
wastewater for each industry (TOWi) is used as AD and calculated by applying Equation 6.6 in the 2006
IPCC Guidelines, Volume 5, Chapter 6.
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𝑇𝑇𝑇𝑇𝑇𝑇� = 𝑃𝑃� ⦁ 𝑊𝑊� ⦁ 𝐶𝐶𝐶𝐶𝐶𝐶�
Where:
TOWi = total organically degradable material in wastewater for industry i, kg COD/yr
i = industrial sector
Pi = total industrial product for industrial sector i, t/yr
Wi = wastewater generated, m3/t
product
CODi = chemical oxygen demand (industrial degradable organic component in wastewater),
kg COD/m3
Organic component removed as sludge (S) is assumed to be zero in the inventory years. The amount
of industrial wastewater treated for the following major industrial sectors are obtained from TurkStat's
Manufacturing Industry Establishments Water, Wastewater and Waste Statistics Survey for the years
1994-1997, 2000, 2004, 2008, 2010, 2012, 2014, 2016, 2018 and 2020. Missing data for the years not
surveyed (1998, 1999, 2001-2003, 2005-2007, 2009, 2011, 2013, 2015, 2017 and 2019) are estimated
by linear interpolation. Based on the ERT recommendation in the latest review (Report on the individual
review of the inventory submission of Turkey submitted in 2021), 2021 AD has been estimated by trend
extrapolation method. Therefore, TOWi for 2021 are not assumed to be the same as in the previous
year, ensuring that this assumption does not lead to an over or underestimation of emissions.
The amount of industrial wastewater treated by industrial sectors are given in Table 7.38.
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Table 7.38 Amount of industrial wastewater discharged by sector, 1990-2021
(thousand m3/yr)
Year
1990-94
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Total
110
164
178
184
164
201
239
241
244
264
285
753
593
484
002
314
980
646
879
112
574
035
Meat &
poultry
25
33
27
35
38
45
52
52
52
61
70
749
752
591
758
282
624
967
494
020
040
059
Organic
chemicals
Petroleum
refineries
Plastics &
resins
13
41
61
26
9
12
16
17
18
26
34
9
9
11
9
8
11
14
14
14
15
16
14
15
10
32
23
41
59
59
60
62
63
771
583
139
501
372
791
211
277
342
429
516
155
239
423
728
421
620
819
636
452
670
887
574
739
014
198
862
503
145
995
844
250
655
Pulp &
paper
(combined)
39
46
39
10
20
21
22
23
24
24
23
072
583
011
691
628
649
670
535
399
180
961
Starch
production
8
17
29
69
63
68
73
73
74
75
75
432
697
306
127
750
792
834
944
054
005
956
308 713
332 391
73 634
77 208
34 434
34 351
18 197
19 507
72 778
81 901
25 115
26 268
84 556
93 156
337 462
342 533
79 707
82 205
34 544
34 738
21 490
23 474
80 607
79 312
30 364
34 460
90 750
88 345
347 604
84 703
34 931
25 457
78 017
38 556
85 939
TOWi is calculated by applying COD values for each industrial sector as given in Table 7.39, that are
based on Table 6.9 in the 2006 IPCC Guidelines, Volume 5, Chapter 6 and the results are given in Table
7.40.
Table 7.39 COD values by industry type
Industry type
COD (kg/m3)
Meat & Poultry
4.1
Organic Chemicals
3.0
Petroleum Refineries
1.0
Plastics & Resins
3.7
Pulp & Paper (combined)
9.0
Starch Production
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Table 7.40 TOWi in wastewater by industry sector, 1990-2021
(kt COD/yr)
Organic
chemicals
Petroleum
refineries
Plastics &
resins
Pulp &
paper
(combined)
Starch
production
Year
Total
Meat &
poultry
1990-94
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
1
1
1
1
1
1
1
1
645.9
926.8
989.2
142.5
104.9
273.4
441.8
454.9
468.0
543.2
618.4
105.6
138.4
113.1
146.6
157.0
187.1
217.2
215.2
213.3
250.3
287.2
41.3
124.7
183.4
79.5
28.1
38.4
48.6
51.8
55.0
79.3
103.5
9.2
9.2
11.4
9.7
8.4
11.6
14.8
14.6
14.5
15.7
16.9
53.9
58.2
37.1
119.1
88.3
153.6
218.8
222.0
225.1
230.3
235.5
351.6
419.2
351.1
96.2
185.7
194.8
204.0
211.8
219.6
217.6
215.7
84.3
177.0
293.1
691.3
637.5
687.9
738.3
739.4
740.5
750.1
759.6
1
1
1
1
1
764.3
910.1
930.9
951.8
972.6
301.9
316.6
326.8
337.0
347.3
103.3
103.1
103.6
104.2
104.8
18.2
19.5
21.5
23.5
25.5
269.3
303.0
298.2
293.5
288.7
226.0
236.4
273.3
310.1
347.0
845.6
931.6
907.5
883.4
859.4
Choice of Emission Factor
As given in Equation 6.5 in the 2006 IPCC Guidelines, Volume 5, Chapter 6, CH4 EFs for each industrial
wastewater treatment/discharge pathway or system are calculated by multiplying the default maximum
CH4 producing capacity (Bo) for industrial wastewater (0.25 kg CH4/kg COD) by the methane correction
factor (MCF) for each type of treatment and discharge pathway or system which is given in the 2006
IPCC Guidelines, Volume 5, Chapter 6, Table 6.8.,
Where:
𝐸𝐸𝐸𝐸� = 𝐵𝐵� ⦁ 𝑀𝑀𝑀𝑀𝑀𝑀�
EFj = emission factor for each treatment/discharge pathway or system, kg CH4/kg COD,
j = each treatment/discharge pathway or system
Bo = maximum CH4 producing capacity, kg CH4/kg COD
MCFj = methane correction factor (fraction)
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Weighted CH4 EFs are calculated by multiplying CH4 EFs for each type of treatment and discharge
pathway or system and fractional usage of the different treatment systems. Weighted CH4 EF for
industrial wastewater with background data are given in Table 7.41.
Table 7.41 MCF, EFs, fractional usages and weighted EF for industrial wastewater
Type of treatment and discharge
pathway or system
MCF
CH4 EF
Fractional
usage
0.10
0.03
0.173
Aerobic treatment plant, well managed
0.00
0.00
0.668
Aerobic treatment plant, not well managed
0.30
0.08
0.088
Anaerobic digester for sludge
0.80
0.20
0.025
Anaerobic reactor
0.80
0.20
0.030
Septic system
0.50
0.13
0.016
Untreated system
Sea, river, lake discharge
Treated system
Total
1.00
Weighted CH4 EF (kg CH4/kg COD)
0.01
Nitrous Oxide Emissions from Wastewater
Türkiye applies the default method from the 2006 IPCC Guidelines to estimate N2O emissions from
domestic wastewater. N2O emissions from domestic wastewater effluent are estimated using Equation
6.7 in the 2006 IPCC Guidelines, Volume 5, Chapter 6. Specifically, N2O emissions are assumed to equal
the amount of nitrogen discharged to aquatic environments, multiplied by an emission factor.
𝑁𝑁� 𝑂𝑂 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 = 𝑁𝑁�������� ⦁ 𝐸𝐸𝐸𝐸�������� ⦁ 44/28
Where:
N2O emissions = N2O emissions in inventory year, kg N2O/yr
NEFFLUENT = nitrogen in the effluent discharged to aquatic environments, kg N/yr
EFEFFLUENT = emission factor for N2O emissions from discharged to wastewater, kg N2O-N/kg N
The factor 44/28 is the conversion of kg N2O-N into kg N2O.
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N2O emissions from centralized wastewater treatment plants with nitrification and denitrification steps
are also taken into account by subtracting the amount of nitrogen associated with N2O emissions from
these plants from the total nitrogen discharged in the wastewater effluent. N2O emissions from such
plants are estimated using Equation 6.9 in 2006 IPCC, Volume 5, Chapter 6.
Where:
𝑁𝑁� 𝑂𝑂������ = 𝑃𝑃 ⦁ 𝑇𝑇����� ⦁ 𝐹𝐹������� ⦁ 𝐸𝐸𝐸𝐸�����
N2OPLANTS = total N2O emissions from plants in inventory year, kg N2O/yr
P = human population
TPLANT = degree of utilization of modern, centralized WWT plants, %
FIND-COM = fraction of industrial and commercial co-discharged protein (default = 1.25),
EFPLANT = emission factor, 3.2 g N2O/person/year
The estimation results are given in Table 7.42. As can be seen in Figure 7.12, total N2O emissions
increased by 63.5% from 1990 to 2021. N2O emissions from centralized WWT plants for 1990-2000
period are reported as "NO" because the nitrogen removal is not available before 2001. TPLANT values
for 2001-2021 are reported in CRF table 5.D, under additional information.
Türkiye reports N2O emissions from industrial wastewater as "IE" in CRF table 5.D. As discussed further
below, N2O emissions from industrial wastewater (category 5.D.2) discharged into sewers is included in
the N2O emissions from domestic wastewater (category 5.D.1).
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Table 7.42 N2O emissions from wastewater, 1990-2021
(kt)
Year
N2O emissions
from wastewater
effluent
N2O emissions
from centralized
WWT plants
Total
N2O
emissions
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
4.84
5.24
5.44
5.68
6.12
6.27
6.47
6.55
6.66
6.92
6.92
7.13
7.24
7.33
7.55
7.77
NO
NO
NO
0.03
0.08
0.08
0.08
0.09
0.10
0.11
0.11
0.12
0.13
0.14
0.14
0.14
4.84
5.24
5.44
5.71
6.21
6.36
6.56
6.64
6.76
7.03
7.03
7.25
7.38
7.46
7.69
7.91
Figure 7.12 N2O emissions from wastewater, 1990-2021
9
8
(kt)
7
6
5
4
3
2
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
0
1990
1
Collection of Activity Data
The activity data that are needed for estimating N2O emissions are nitrogen content in the wastewater
effluent, country population and average annual per capita protein generation (kg/person/yr).
The total nitrogen in the effluent is estimated using Equation 6.8 in the 2006 IPCC Guidelines, Volume
5, Chapter 6.
𝑁𝑁�������� = (𝑃𝑃 ⦁ 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 ⦁ ��� ⦁ 𝐹𝐹������� ⦁ 𝐹𝐹������� ) − 𝑁𝑁������
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Where:
NEFFLUENT = total annual amount of nitrogen in the wastewater effluent, kg N/yr
P = human population
Protein = annual per capita protein consumption, kg/person/yr
FNPR = fraction of nitrogen in protein, kg N/kg protein
FNON-CON = factor for non-consumed protein added to the wastewater
FIND-COM = factor for industrial and commercial co-discharged protein into the sewer system
NSLUDGE= nitrogen removed with sludge, kg N/yr
Per capita protein consumption in Türkiye has been obtained from the FAOSTAT’s website
(http://www.fao.org/faostat/en/#data/FBS/visualize). The link has re-checked for up-to-date data of
recent years, and it is found that the new Food Balances are available after 2018. 2018-2020 data have
been updated on the link. These revised data are used instead of the data in the previous submission.
2021 data is extrapolated due to lack of data.
Population and annual per capita protein consumption data are given in Table 7.43.
Table 7.43 Population and per capita protein consumption, 1990-2021
Year
1990
1995
2000
2005
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Population (1)
(1000's persons)
55
59
64
68
73
74
75
76
77
78
79
80
81
82
83
84
Per capita protein
consumption (2)
(kg/person/yr)
120
756
269
435
142
224
176
148
182
218
278
313
407
579
385
147
39.88
39.89
38.44
37.70
37.77
38.13
39.25
39.46
39.24
40.24
39.66
40.35
40.46
40.34
41.15
41.95
Source: (1) TurkStat, Mid-year Population Estimations and Projections
(2) FAOSTAT, Food Balance Sheets
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Additional relevant parameters to calculate total nitrogen in the effluent are given in Table 7.44. Default
values from the 2006 IPCC Guidelines, Volume 5, Chapter 6, Table 6.11 are used for the fraction of
nitrogen in protein (0.16 kg N/kg protein), the fraction of non-consumed protein (1.4), and the fraction
of industrial and commercial co-discharged protein (1.25). As discussed above for domestic wastewater,
Türkiye assumes that there is zero sludge removed. Regarding the fraction of non-consumed protein,
Türkiye has applied the value for developed countries using garbage disposals.
Table 7.44 Parameters for estimation of nitrogen in effluent, 2021
Fraction of
nitrogen in
protein
Fraction of
non-consumed
protein
Fraction of industrial
and commercial codischarged protein
Nitrogen
removed
with sludge
(FNPR)
(FNON-CON)
(FIND-COM)
(NSLUDGE)
(kg N/kg protein)
0.16
(kg)
1.40
1.25
0.00
Choice of Emission Factor
To estimate N2O emissions from wastewater effluent, the IPCC default N2O EF (EFEFFLUENT) is selected
as 0.005 kg N2O-N/kg-N from the 2006 IPCC Guidelines, Volume 5, Chapter 6, Table 6.11.
The IPCC default EF (EFPLANTS) to estimate N2O emissions from centralized wastewater treatment plants
of 3.2 g N2O/person/year as given in the 2006 IPCC Guidelines, Volume 5, Chapter 6, Table 6.11 is
applied. To estimate N2O emissions from such plants, the country-specific values of the degree of
utilization of modern, centralized WWT plants (TPLANT) are calculated for the whole time series.
Uncertainties and Time-Series Consistency:
Domestic Wastewater Treatment and Discharge: For CH4 emissions, the uncertainty for AD is estimated
as 5.0% and for CH4 EF it is calculated as 37.7% by using default uncertainty ranges provided in the
2006 IPCC Guidelines, Volume 5, Chapter 6, Table 6.7.
For N2O emissions, the uncertainty for AD is estimated as 30.0%. The uncertainty value of the N2O EF
is calculated as 42.4% by using uncertainty values of 30.0% for both EFEFFLUENT and EFPLANTS based on
expert judgment since there is no sufficient information in the related section of the 2006 IPCC.
Industrial Wastewater Treatment and Discharge: For CH4 emissions, the uncertainty for AD is estimated
as 11.2% and for CH4 EF it is calculated as 39.1% by using default uncertainty ranges provided in the
2006 IPCC Guidelines, Volume 5, Chapter 6, Table 6.10.
The estimates are calculated in a consistent manner over time series.
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In 2019 submission, Monte Carlo analysis has been carried out for the CH4 and N2O emissions from
Wastewater treatment and discharge, for the year 2017. Combined uncertainty in CH4 emissions is was
estimated at -40.16% to +40.77% for Domestic wastewater sub-category and-32.71% to 41.28% for
Industrial wastewater sub-category while N2O combined uncertainty range is -24.38% to+25.56%. More
detailed information is in Annex 2.
Source-Specific QA/QC and Verification:
QA/QC procedures are implemented for each category in order to verify and improve the inventory
under the QA/QC plan of Türkiye.
The data used in Wastewater Treatment and Discharge (CRF Category 5.D) are derived from waste
statistics database of TurkStat. TurkStat is producing all its statistics according to the European Code of
Practice Principles. Therefore, high quality data are used in the emission estimates of this category.
Moreover, a QA work was conducted by an external reviewer (expert from CITEPA - Technical Reference
Center for Air Pollution and Climate Change) for this category in December 2019.
Recalculation:
Methane recovery data from some biogas facilities has been recalculated for the years 2016-2020 as a
result of ongoing verification and comparison activities for the quantity of methane in the recovered
biogas.
With the update of the 2018 and 2019 data and the availability of 2020 data from FAOSTAT, revised
protein supply data were used instead of the previous AD and therefore, recalculation was made for per
capita protein consumption data for the years 2018-2020.
Total recalculation of CH4 emissions for Wastewater Treatment and Discharge subsector (CRF Category
5.D) resulted with an increase of 6.2 kt CO2 eq. (0.2%) in 2020. For N2O emissions, the recalculation
caused an increase by 24.7 kt CO2 eq. (1.1%) in 2020. There is no recalculation for 1990 for both gases.
Planned Improvement:
Türkiye is planning to improve the parameters used in the estimation of CH4 emissions, both for the
degree of treatment utilization by population class (domestic wastewater) and for the fraction usage for
different types of wastewater treatment and discharge pathways (industrial wastewater) for the entire
time series.
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6
7.6. Other (Category 5.E)
There are no other activities to be considered under this category.
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Other / Indirect Carbon Dioxide and Nitrous Oxide Emissions
8. OTHER
Türkiye does not report any emissions under the category 'Other'.
9. INDIRECT CARBON DIOXIDE AND NITROUS OXIDE
EMISSIONS
Türkiye does not report on indirect carbon dioxide and nitrous oxide emissions.
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Recalculations and Improvements
10. RECALCULATIONS AND IMPROVEMENTS
Recalculations:
Every year the inventory team reviews the latest inventory, checks the entire time series from 1990
onwards and tries to determine the conditions that are not meet the TACCC criteria. Based on the
outcomes of the examination some AD revisions, reallocation of emissions or error corrections are made
as compared to previous submission.
Also the ERT recommendations are one of the most important reasons for recalculations. A remote
centralized review of the 2021 inventory submission of Türkiye was organized by the UNFCCC Secretariat
from 4 to 9 October 2021. The Report on the individual review of the inventory submission of Turkey
submitted in 2021 was published on 5 May 2022. Mainly, the recalculations have been made based on
the ERT findings of this report in relevant categories in addition to our own improvements. All kind of
recalculations are described in the Chapters 3-7 in detail, and the reasons for recalculations are also
summarized below.
In energy sector;
For the sectors, 1.A.1.b, 1.A.1.c, 1.A.2.a, 1.A.2.f, 1.A.4.a were recalculated due to the change in activity
data and some minor error in calculations.
In IPPU sector;
Glass production activity data of a new plant included in the calculations and this caused recalculations
in 2.A.3 and 2.A.4.b sectors.
2.A.4.a production data changes in PRODCOM database reflected to calculations.
For 2.B.1 Ammonia production carbon content factor of natural gas for the years 2018 and 2019 are
corrected.
For 2.B.2 inconsistent activity data of a nitric asit producer changed retrospectively.
2.C.1 Steel production data of an integrated plant for the years 1990 and 1995 are corrected due to
availability of retrospective data from Turkish Steel Producers Association. Limestone used in BOF data
corrected by one of the integrated plant and recalculated for the years 2018-2020 and carbon content
of BOF and Blast Furnace gas data backcasted and recalculated.
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Recalculations and Improvements
Emission calculations from PFC gases under the aluminium sector have been revised and recalculated
according to the 2006 IPCC guidelines instead of 1996 IPCC guidelines.
CO2 and SF6 emissions from magnesium production and CO2 emissions from secondary zinc production
estimated for the first time in this submission.
For 2.C.6 in 1999 both primary and secondary zinc is produced and CO2 emissions from zinc production
increased by 3.7 kt. For the years between 2000-2002, 2005-2008 and 2010-2021 emission values are
added from secondary zinc production for the first time.
For 2.F recalculations have been carried out for the years 2014-2021, to take account of calculation
error of data, because of the calculation worksheet updated problem.
For 2.G. the consumption of SF6 in Mg production between the years 2016-2021 is accounted in the
magnesium production sector.
In agriculture sector;
Two very minor revisions in activity data for Urea Application are the reasons for the recalculation of
this category. The first recalculation has a decreasing effect of -0.000039% (0.00022 kt CO2 eq.) for
the year 2011 and the second recalculation has an increasing effect of 0.00000838% (0.000139 kt CO2
eq.) for the year 2020.
Minor revisions in Field burning category are a result of transmission errors for 2020. The recalculation
has a decreasing effect of -1.08% (1.87 kt CO2 eq.) for the year 2020.
Minor revisions are a result of transmission errors in the calculation of field burning emissions affecting
calculations of crop residues emissions for 2019. For this source category, the recalculation has a
decreasing effect of -0.0007% (0.202 kt CO2 eq.) for the year 2019.
In LULUCF sector;
The Forest Land Remaining Forest Land Category was recalculated due to an update of the annual
increment values for the years between 1990-2019 with increment borer by the ongoing National Forest
Inventory Program of GDF.
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Recalculations and Improvements
In waste sector;
For Category 5.A, the revision of 2019 and 2020 GDP data by TurkStat resulted in changes in total
industrial waste in the SWDS, which led to minor recalculation in CH4 emissions from unmanaged SWDS
for 2020. Mainly, methane recovery data from some landfill gas recovery facilities has been recalculated
for the years 2014-2016 and 2018-2020 as a result of ongoing verification and comparison activities for
the quantity of methane in the recovered landfill gas. The amount of sewage sludge for 2018 and 2020
has been recalculated due to the correction made in the total of “other disposal” in unmanaged landfills.
2017 and 2019 AD were also affected by this correction, as they were estimated by the interpolation
method. These have resulted in recalculations in methane emissions from sewage sludge in 2018-2020.
For Category 5.D, methane recovery data from some biogas facilities has been recalculated for the years
2016-2020 as a result of ongoing verification and comparison activities for the quantity of methane in
the recovered biogas. With the update of the 2018 and 2019 data and the availability of 2020 data from
FAOSTAT, revised protein supply data were used instead of the previous AD and therefore, recalculation
was made for per capita protein consumption data for the years 2018-2020.
Turkish GHG Inventory Report 1990-2021
433 433
Recalculations and Improvements
The reasons and the implications of recalculations by CRF category are given in the below table for 1990
and 2020.
Table 10.1 Recalculations made in the current submission and their implications to the
emission level, 1990 and 2020
CRF category
Reasons for recalculation
1. Energy
1990
2020
1990 2020
-66
-1 010
-0.03 -0.19
-75
-1033
-0.03
-0.20
A.1 Energy industries
Changes in AD and methods
A.2 Manufacturing
industries and
construction
Changes in AD
8
37
0.00
0.01
A.4 Other sectors
Changes in AD
NO
-14
NO
0.00
-127
1 200
-0.06
0.23
-0.12
-32
0.00
-0.01
-127
587
-0.06
0.11
NO
645
NO
0.12
2. IPPU
434
Implication to
the CRF
category level
(kt CO2 eq.)
Implication
to the total
emission
w/o
LULUCF
(%)
A. Mineral industry
Adding activity data of a new glass plant.
Changes reflected to activity data of 2.A.4.a
which observed in PRODCOM database.
C. Metal industry
Steel production data of an integrated plant
for the years 1990 and 1995 are corrected.
Limestone used in BOF data corrected by one
of the integrated plant and recalculated for
the years 2018-2020, and carbon content of
BOF and Blast Furnace gas data updated
according to reporting of integrated plants.
Emission calculations from PFC gases under
the aluminium sector have been revised and
recalculated according to the 2006 IPCC GLs.
CO2 and SF6 emissions from magnesium
production and CO2 emissions from secondary
zinc production estimated for the first time in
this submission.
For 2.C.6 in 1999 both primary and secondary
zinc is produced and CO2 emissions from zinc
production recalculated. For the years
between 2000-2002, 2005-2008 and 20102021 emission values are added from
secondary zinc production for the first time.
F. Product uses as
ODS substitutes
Calculation errors corrected for the years 20142021.
Turkish GHG Inventory Report 1990-2021
434
Recalculations and Improvements
Table 10.1 Recalculations made in the current submission and their implications to the
emission level, 1990 and 2020 (cont’d)
CRF category
Reasons for recalculation
3. Agriculture
Implication to
the CRF
category level
(kt CO2 eq.)
Implication
to the total
emission w/o
LULUCF
(%)
1990
2020
1990
2020
NO
-2
NO
0.00
F. Field burning of
agricultural residues
Minor transmission error
NO
-2
NO
0.00
H. Urea application
Minor revision on AD
NO
0.00
NO
0.00
-10 775
NO
-4.91
NO
-10 775
NO
-4.91
NO
NO
-94
NO
-0.02
4. Land use, land-use
change and forestry
A. Forest land
The Forest Land Remaining Forest Land
Category was recalculated due to an
update of the annual increment values
for the years between 1990-2019 with
increment borer by the ongoing National
Forest Inventory Program of GDF.
5. Waste
A. Solid waste disposal
Minor revision of GDP data.
Correction of methane recovery data.
Correction of sewage sludge data.
NO
-125
NO
-0.02
D. Wastewater
treatment and
discharge
Correction of methane recovery data.
Revision of per capita protein
consumption data.
NO
31
NO
0.01
-194
94
-0.09
0.02
-10 969
94
-5.00
0.02
Total CO2 equivalent
emissions without
land use, land-use
change and forestry
Total CO2 equivalent
emissions with land
use, land-use change
and forestry
Figures in the table may not add up to the totals due to rounding.
Turkish GHG Inventory Report 1990-2021
435 435
Recalculations and Improvements
Planned Improvements:
Considerable improvements have been made in this submission. However, there are still areas to be
improved mainly related to using higher tiers, especially for key categories. Planned improvements are
summarized as follows:
In energy sector;
Emissions from petroleum refining sector recalculated by using reported MRV data for the years 20182021. It is planned to recalculate the emissions from 1990-2017 by using this data with appropriate
methods.
Prior to 2011 several manufacturing sectors that have their own categories (Pulp, Paper & Print; Nonmetallic minerals; Food processing, beverages & tobacco) were not fully separated out in the national
energy balance and therefore some or all of the emissions from these categories were reported under
section 1A2g. This is because in the calculation of 1A2 subcategories the national energy balance tables
are used and national energy balance tables are not created as time series. All relevant institutions are
working together in order to overcome this inconsistency problem.
Prior to 2015 1A4a and 1A4b categories were not separated out in the national energy balance and
therefore all of the emissions from these categories were reported under section 1A4b. However, since
2015 they are separated. All relevant institutions are working together in order to overcome this
inconsistency problem and allocate 1A4a and 1A4b categories in time series.
MENR worked on agricultural association for modeling the agricultural diesel oil consumption and the
disaggregation of diesel oil consumption was achieved in 2015 national energy balance tables. However
national energy balance tables are not in time series therefore the allocation problem still exists between
2012 and 2014. All relevant institutions are working together and make planning in order to overcome
this inconsistency problem.
Since the 1.B.1 category is a key category in terms of emission trend of CH4, the tiers in CH4 estimation
needs to be increased. Detailed investigation has been performed to find out the availability of country
specific or basin specific EFs within both general directorates for lignite and hard coal structured under
the MENR, namely, DG Turkish Lignite Enterprises and DG Turkish Hard Coal Enterprises. However,
information for the generation of country-specific EFs are not available centrally in those coal authorities.
Therefore, it is necessary to communicate and cooperate with mining enterprises directly to search the
availability of required information for T2 estimation of CH4.
436
Turkish GHG Inventory Report 1990-2021
436
Recalculations and Improvements
For 1.B.2 In order to increase the tiers for CH4 emission estimation, availability of detailed information
have been searched. It is planned to continue the investigation to find out the availability or possibility
of availability of appropriate data for higher tiers.
In IPPU sector;
For cement production, it is planned to collect data on plant specific CKD for the next submissions.
For lime production; it is planned to obtain a country specific emission factor for dolomitic lime in next
submissions.
In Ceramic sector, production data were gathered from Turkish Ceramics Federation until the federation
had judicial issues regarding data collection from its members in 2020. As a result of this situation,
TurkStat launched studies for estimating emissions of ceramics sector from other data sources.
Calculations will be examined in next submissions.
For Product Use as Substitutes for ODS and Other Product Manufacture and Use (2.G) sectors
improvements in the sectors data will be done within the scope of "Technical Assistance for Increased
Capacity for Transposition and Capacity Building on F-Gases" project which has started in June 2017
and lasted in Aug 2020. After the adaptation of data base system, more detailed data will be collected
and improvements in the sector will be done.
Data generated from the Monitoring, reporting, verification (MRV) system for GHG emissions in which
more than 700 plants submit their verified annual emissions data in energy and industrial sectors
according to the regulations of the Ministry of Environment, Urbanization and Climate Change, will be
examined by TurkStat in various quality aspects (coverage, accuracy, completeness, consistency).
In agriculture sector;
Türkiye considers the possibility of using Tier 2 method for estimating enteric fermentation emissions
from sheep in the future and also searches for country specific parameters related to using Tier 2
method in manure management.
In LULUCF sector;
In Forestland category all activity data is planned to update by field measurements of National Forest
Inventory Programme of the GDF such as this submission. The annual increment data is also planned
to be disaggregated for ecozones in the medium term. The soil and dead organic matter carbon stocks
will be updated as more national studies are available.
Turkish GHG Inventory Report 1990-2021
437 437
Recalculations and Improvements
In Cropland category perennial crops is planned to be disaggregated for major species including olives,
vineyards etc. if a method that can be embedded into the current system can be developed. Related to
management of annual croplands there are area data available but has not been estimated in this
submission. The removals/emissions from cropland management including reduced tillage is planned to
be reported not in the short term but in medium or long term.
In Grassland category it will be possible to estimate CSC in soils when range rehabilitation data is
available. There are several studies going on in grasslands in the country. The results will be
incorporated into estimates as they become available.
Türkiye is a partner of ICP Forests program. The ICP forest project’s soil analysis in Türkiye was initiated
in January 2015 and planned to be finished by 2019. But it is not completed yet. The results of this
project may enable us to improve soil and litter carbon stocks.
The EU funded project entitled “The Technical Assistance for Developed an Analytical Basis for the
LULUCF Sector Project” has been started in 2017 and finish in July in 2019. The project provided a
spatially explicit land use tracking system. In this regard it is planned to implement a new project in the
long term.
In waste sector;
In the scope of TurkStat's Waste Disposal and Recovery Facilities Survey, it will be determined whether
there is any flaring on waste disposal sites (CRF Category 5.A). Based on the gathered information,
flaring would be included in next submission.
Emissions and amount of methane for energy recovery from anaerobic digestion at biogas facilities (CRF
Category 5.B.2) will be included in next inventory submissions depending on the availability of such
treatment processes.
In Wastewater Treatment and Discharge (CRF Category 5.D), Türkiye is planning to improve the
parameters used in the estimation of CH4 emissions, both for the degree of treatment utilization by
population class (domestic wastewater) and for the fraction usage for different types of wastewater
treatment and discharge pathways (industrial wastewater) for the entire time series.
438
Turkish GHG Inventory Report 1990-2021
438
Key Categories
Annex 1: Key Categories
This annex presents the results of Approach 1 key category analysis and results for the latest Turkish
GHG inventory submission. The 2006 IPCC Guidelines for National GHG Inventories (2006 IPCC
Guidelines) recommend as good practice the identification of key categories of emissions and removals.
The objective is to assist inventory agencies in their prioritization efforts to improve overall estimates.
A key category is defined as “one that is prioritized within the national inventory system because its
estimate has a significant influence on a country’s total inventory of greenhouse gases in terms of the
absolute level of emissions and removals, the trend in emissions and removals, or uncertainty in
emissions and removals” (2006 IPCC Guidelines); this term is used in reference to both source and sink
categories.
The Approach 1 Level and Trend Assessment described in the 2006 IPCC Guidelines Vol.1, Chapter 4 is
used to identify key categories from two perspectives: their contribution to the overall emissions and
their contribution to the emission trend. The level assessment analyses the emission contribution that
each category makes to the national total (with and without LULUCF). The trend assessment uses each
category’s relative contribution to the overall emissions, but assigns greater weight to the categories
whose relative trend departs from the overall trend (with and without LULUCF). In this assessment,
trends are calculated as the absolute changes between base year and most recent inventory year.
The percent contributions to both levels and trends in emissions are calculated and sorted in descending
order. A cumulative total is calculated for both approaches. A cumulative contribution threshold of 95%
for both level and trend assessments is a reasonable approximation of 90% uncertainty for the T1
method of determining key categories (2006 IPCC Guidelines). This threshold has therefore been used
in this analysis to define an upper boundary for key category identification. Therefore, when source and
sink contributions are sorted in decreasing order of importance, those largest ones that together
contribute to 95% of the cumulative total are considered quantitatively to be key categories.
Level contribution of each source or sink is calculated according to Equation 4.1. available in 2006 IPCC
Guidelines while trend assessments are calculated according to the Equation 4.2. and 4.3.
In the 2021 inventory key category analysis, there were 31 key categories of emissions and removals
shown on the next page in Table A1.
Turkish GHG Inventory Report 1990-2021
439 439
440
1.A.1 Fuel combustion - Energy Industries - Liquid Fuels
1.A.1 Fuel combustion - Energy Industries - Solid Fuels
1.A.1 Fuel combustion - Energy Industries - Gaseous Fuels
1.A.2 Fuel combustion - Manufacturing Industries and Construction - Liquid Fuels
1.A.2 Fuel combustion - Manufacturing Industries and Construction - Solid Fuels
1.A.2 Fuel combustion - Manufacturing Industries and Construction - Gaseous Fuels
1.A.2 Fuel combustion - Manufacturing Industries and Construction - Other Fossil Fuels
1.A.3.a Domestic Aviation
1.A.3.b Road Transportation
1.A.4 Other Sectors - Liquid Fuels
1.A.4 Other Sectors - Solid Fuels
1.A.4 Other Sectors - Gaseous Fuels
1.A.4 Other Sectors - Biomass
1.B.1 Fugitive emissions from Solid Fuels
1.B.2.b Fugitive Emissions from Fuels - Oil and Natural Gas - Natural Gas
2.A.1 Cement Production
2.A.2 Lime Production
2.A.4 Other Process Uses of Carbonates
2.C.1 Iron and Steel Production
2.F.6 Other Applications
3.A Enteric Fermentation
3.B Manure Management
3.B Manure Management
3.D.1 Direct N2O Emissions From Managed Soils
3.D.2 Indirect N2O Emissions From Managed Soils
4.A.1 Forest Land Remaining Forest Land
4.G Harvested Wood Products
4(V) Biomass Burning
5.A Solid Waste Disposal
5.D Wastewater Treatment and Discharge
5.D Wastewater Treatment and Discharge
KEY CATEGORIES OF EMISSIONS AND REMOVALS
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CH4
CH4
CH4
CO2
CO2
CO2
CO2
Aggregate F-gases
CH4
CH4
N2O
N2O
N2O
CO2
CO2
CO2
CH4
CH4
N2O
Gas
Table A1 Key category analysis summary, 2021
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Turkish GHG Inventory Report 1990-2021
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
440
Criteria used
Key
for key
Key category
category
source
including
excluding
identification
LULUCF
LULUCF
L
T
Key Categories
1.A.1.
1.A.3.b.
1.A.1.
2.A.1.
1.A.4.
3.A.
4.A.1.
1.A.2.
1.A.2.
3.D.a.
1.A.4.
4.G.
1.A.4.
2.C.1.
1.A.2.
5.A.
2.F.6.
1.B.1
1.A.1.
3.B.
3.B.
3.D.b.
5.D.
2.A.4.
1.A.3.a.
2.A.2.
1.B.2.b
5.D.
2.B.2.
1.A.2.
2.B.1.
1.A.3.b.
3.H.
1.A.4.
Energy industries
Road Transportation
Energy industries
Cement Production (Mineral Products)
Other sectors
Enteric fermentation
Forest Land Remaining Forest Land
Manufacturing industries and construction
Manufacturing industries and construction
Direct N2O emissions from managed soils
Other sectors
Harvested Wood Products
Other sectors
Iron and Steel Production
Manufacturing industries and construction
Solid waste disposal
Other applications
Fugitive Emissions from Solid fuels
Energy industries
Manure management
Manure management
Indirect N2O Emissions from managed soils
Wastewater treatment and discharge
Other process uses of carbonates
Domestic Aviation
Lime Production (Mineral Products)
Natural Gas
Wastewater treatment and discharge
Nitric acid production
Manufacturing industries and construction
Ammonia Production
Road Transportation
Urea application
Other sectors
Sector
Turkish GHG Inventory Report 1990-2021
Solid fuels
Other fossil fuels
Liquid fuels
Liquid fuels
Liquid fuels
Solid fuels
Solid fuels
Gaseous fuels
Gaseous fuels
Gaseous fuels
Solid fuels
CO2
CO2
CO2
CO2
CO2
CH4
CO2
CO2
CO2
N2O
CO2
CO2
CO2
CO2
CO2
CH4
HFC
CH4
CO2
N2O
CH4
N2O
CH4
CO2
CO2
CO2
CH4
N2O
N2O
CO2
CO2
N2O
CO2
CH4
105 822
84 699
45 660
44 227
41 361
34 953
-34 770
28 644
25 118
23 226
18 811
-15 725
12 084
11 898
10 281
9 338
6 880
6 493
6 448
5 155
3 988
3 023
2 972
2 831
2 826
2 751
2 486
2 356
2 023
1 830
1 489
1 395
1 302
1 177
105
84
45
44
41
34
34
28
25
23
18
15
12
11
10
9
6
6
6
5
3
3
2
2
2
2
2
2
2
1
1
1
1
1
822
699
660
227
361
953
770
644
118
226
811
725
084
898
281
338
880
493
448
155
988
023
972
831
826
751
486
356
023
830
489
395
302
177
Table A2 Key category analysis level assessment with LULUCF, 2021
Fuel
GAS 2021 Emission ABS (Emission)
17.09
13.68
7.37
7.14
6.68
5.65
5.62
4.63
4.06
3.75
3.04
2.54
1.95
1.92
1.66
1.51
1.11
1.05
1.04
0.83
0.64
0.49
0.48
0.46
0.46
0.44
0.40
0.38
0.33
0.30
0.24
0.23
0.21
0.19
Cont. (%)
441
17.09
30.77
38.15
45.29
51.97
57.62
63.23
67.86
71.91
75.67
78.70
81.24
83.20
85.12
86.78
88.29
89.40
90.45
91.49
92.32
92.96
93.45
93.93
94.39
94.85
95.29
95.69
96.07
96.40
96.69
96.93
97.16
97.37
97.56
Cumulative
Key Categories
441
1.A.4.
1.A.3.d.
2.A.3.
1.A.1.
4.C.2.
4.A.1.
4.F.2.
1.A.1.
2.B.7.
1.B.2.c
2.C.6.
4.B.2.
1.A.4.
4.A.1.
4.E.2.
1.B.2.a
1.A.3.b.
1.A.3.e.
4.A.2.
2.F.3.
1.A.3.c.
3.C.
4.D.2.
1.B.2.c
2.C.2.
2.D.1.
4.B.1.
1.A.2.
3.F.
2.C.3.
1.A.4.
1.A.4.
4.(IV).2.
1.A.4.
N2O
CO2
CO2
N2O
CO2
CH4
CO2
N2O
CO2
CH4
CO2
CO2
CH4
N2O
CO2
CH4
CH4
CO2
CO2
HFC
CO2
CH4
CO2
CO2
CO2
CO2
CO2
N2O
CH4
CO2
CH4
N2O
N2O
N2O
1 141
1 053
807.1
736.3
712.4
696.2
685.8
639.5
615.1
591.2
578.9
486.7
479.9
459.1
420.8
407.4
405.4
360.3
-332.2
329.4
318.3
269.3
225.6
202.3
193.0
163.1
-124.3
122.3
121.2
117.8
93.3
84.8
78.1
76.3
1 141
1 053
807.1
736.3
712.4
696.2
685.8
639.5
615.1
591.2
578.9
486.7
479.9
459.1
420.8
407.4
405.4
360.3
332.2
329.4
318.3
269.3
225.6
202.3
193.0
163.1
124.3
122.3
121.2
117.8
93.3
84.8
78.1
76.3
Table A2 Key category analysis level assessment with LULUCF, 2021 (cont’d)
Fuel
GAS 2021 Emission ABS (Emission)
Other sectors
Liquid fuels
Domestic Navigation
Gas/diesel oil
Glass Production
Energy industries
Solid fuels
Land Converted to Grassland
Forest Land Remaining Forest Land
Land Converted to Other Land
Energy industries
Gaseous fuels
Soda ash production
Venting and flaring
Zinc Production
Land Converted to Cropland
Other sectors
Biomass
Forest Land Remaining Forest Land
Land Converted to Settlements
Oil
Road Transportation
Other transportation
Land Converted to Forest Land
Fire protection
Railways
Rice cultivation
Land Converted to Wetlands
Venting and flaring
Ferroalloys Production
Lubricant Use
Cropland Remaining Cropland
Manufacturing industries and construction
Solid fuels
Field burning of agricultural residues
Aluminium Production
Other sectors
Gaseous fuels
Other sectors
Solid fuels
Indirect N2O Emissions from nitrogen leaching and run-off
Other sectors
Biomass
Sector
0.18
0.17
0.13
0.12
0.12
0.11
0.11
0.10
0.10
0.10
0.09
0.08
0.08
0.07
0.07
0.07
0.07
0.06
0.05
0.05
0.05
0.04
0.04
0.03
0.03
0.03
0.02
0.02
0.02
0.02
0.02
0.01
0.01
0.01
442
Turkish GHG Inventory Report 1990-2021
442
97.74
97.91
98.05
98.16
98.28
98.39
98.50
98.61
98.70
98.80
98.89
98.97
99.05
99.12
99.19
99.26
99.32
99.38
99.44
99.49
99.54
99.58
99.62
99.65
99.68
99.71
99.73
99.75
99.77
99.79
99.80
99.82
99.83
99.84
Cont. (%) Cumulative
Key Categories
1.A.1.
1.A.2.
2.E.5.
1.A.1.
1.A.3.d.
2.C.4.
1.A.2.
2.C.4.
1.A.3.c.
3.F.
1.A.2.
1.A.3.a.
2.G.1.
1.A.1.
1.A.2.
4.B.2.
1.A.4.
1.A.2.
1.A.4.
1.A.1.
2.C.1.
1.A.2.
5.B.
1.A.2.
5.B.
2.C.5.
4.C.2.
1.A.2.
1.A.3.d.
2.B.5.
1.A.2.
1.A.1.
Energy industries
Manufacturing industries and construction
Other
Energy industries
Domestic Navigation
Magnesium Production
Manufacturing industries and construction
Magnesium production
Railways
Field burning of agricultural residues
Manufacturing industries and construction
Domestic Aviation
Electrical equipment
Energy industries
Manufacturing industries and construction
Land Converted to Cropland
Other sectors
Manufacturing industries and construction
Other sectors
Energy industries
Iron and Steel Production
Manufacturing industries and construction
Biological treatment of solid waste
Manufacturing industries and construction
Biological treatment of solid waste
Lead Production
Land Converted to Grassland
Manufacturing industries and construction
Domestic Navigation
Carbide production
Manufacturing industries and construction
Energy industries
Sector
Turkish GHG Inventory Report 1990-2021
Liquid fuels
Biomass
Other fossil fuels
Gas/diesel oil
Gaseous fuels
Other fossil fuels
Gaseous fuels
Liquid fuels
Liquid fuels
Solid fuels
Gaseous fuels
Gaseous fuels
Biomass
Biomass
Biomass
Residual fuel oil
Other fossil fuels
Solid fuels
CO2
CH4
SF6
N2O
CO2
SF6
N2O
CO2
N2O
N2O
CH4
N2O
SF6
CH4
N2O
N2O
N2O
N2O
CH4
CH4
CH4
N2O
CH4
CH4
N2O
CO2
N2O
CH4
N2O
CO2
CH4
CH4
74.1
68.5
65.0
63.5
62.7
49.8
49.6
38.5
37.5
37.5
31.2
29.3
29.2
28.6
26.7
25.1
22.2
19.1
19.1
18.8
16.7
15.7
14.5
11.3
10.3
10.0
10.0
9.9
8.7
8.5
8.1
7.7
74.1
68.5
65.0
63.5
62.7
49.8
49.6
38.5
37.5
37.5
31.2
29.3
29.2
28.6
26.7
25.1
22.2
19.1
19.1
18.8
16.7
15.7
14.5
11.3
10.3
10.0
10.0
9.9
8.7
8.5
8.1
7.7
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
443
99.85
99.87
99.88
99.89
99.90
99.90
99.91
99.92
99.92
99.93
99.94
99.94
99.95
99.95
99.95
99.96
99.96
99.96
99.97
99.97
99.97
99.98
99.98
99.98
99.98
99.98
99.99
99.99
99.99
99.99
99.99
99.99
Table A2 Key category analysis level assessment with LULUCF, 2021 (cont’d)
Fuel
GAS 2021 Emission ABS (Emission) Cont. (%) Cumulative
Key Categories
443
Total
4.D.2.
1.B.2.a
1.A.1.
5.C.
1.B.2.b
5.C.
1.A.3.d.
1.A.1.
2.B.8.
1.A.3.a.
1.A.1.
1.B.2.c
1.A.1.
4.A.2.
5.C.
1.A.3.d.
1.A.3.c.
4.A.2.
1.A.3.e.
1.A.3.e.
1.A.3.d.
1.C.
2.E.5.
4.C.1.
2.E.5.
1.A.1.
1.A.2.
1.A.4.
Land Converted to Wetlands
Oil
Energy industries
Incineration and open burning of waste
Natural Gas
Incineration and open burning of waste
Domestic Navigation
Energy industries
Petrochemical and carbon black production
Domestic Aviation
Energy industries
Venting and flaring
Energy industries
Land Converted to Forest Land
Incineration and open burning of waste
Domestic Navigation
Railways
Land Converted to Forest Land
Other transportation
Other transportation
Domestic Navigation
CO2 Transport and storage
Other
Grassland Remaining Grassland
Other
Energy industries
Manufacturing industries and construction
Other sectors
Sector
444
Turkish GHG Inventory Report 1990-2021
Biomass
Biomass
Biomass
Residual fuel oil
Residual fuel oil
Other fossil fuels
Other fossil fuels
Gas/diesel oil
Liquid fuels
Liquid fuels
N2O
CO2
N2O
CO2
CO2
CH4
CH4
CH4
CO2
CH4
N2O
N2O
CH4
CH4
N2O
N2O
CH4
N2O
N2O
CH4
CH4
CO2
HFC
CO2
PFC
CO2
CO2
CO2
517 243.99
4.4
4.1
4.1
3.6
3.4
3.1
2.6
2.5
1.4
1.3
0.9
0.9
0.6
0.6
0.6
0.5
0.5
0.4
0.2
0.2
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.0
619 146.05
4.4
4.1
4.1
3.6
3.4
3.1
2.6
2.5
1.4
1.3
0.9
0.9
0.6
0.6
0.6
0.5
0.5
0.4
0.2
0.2
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.0
Table A2 Key category analysis level assessment with LULUCF, 2021 (cont’d)
Fuel
GAS 2021 Emission ABS (Emission)
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Cont. (%)
444
99.99
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
Cumulative
Key Categories
1.A.1.
1.A.3.b.
1.A.1.
2.A.1.
1.A.4.
3.A.
1.A.2.
1.A.2.
3.D.a.
1.A.4.
1.A.4.
2.C.1.
1.A.2.
5.A.
2.F.6.
1.B.1
1.A.1.
3.B.
3.B.
3.D.b.
5.D.
2.A.4.
1.A.3.a.
2.A.2.
1.B.2.b
5.D.
2.B.2.
1.A.2.
2.B.1.
1.A.3.b.
3.H.
1.A.4.
Energy industries
Road Transportation
Energy industries
Cement Production (Mineral Products)
Other sectors
Enteric fermentation
Manufacturing industries and construction
Manufacturing industries and construction
Direct N2O emissions from managed soils
Other sectors
Other sectors
Iron and Steel Production
Manufacturing industries and construction
Solid waste disposal
Other applications
Fugitive Emissions from Solid fuels
Energy industries
Manure management
Manure management
Indirect N2O Emissions from managed soils
Wastewater treatment and discharge
Other process uses of carbonates
Domestic Aviation
Lime Production (Mineral Products)
Natural Gas
Wastewater treatment and discharge
Nitric acid production
Manufacturing industries and construction
Ammonia Production
Road Transportation
Urea application
Other sectors
Sector
Turkish GHG Inventory Report 1990-2021
Solid fuels
Other fossil fuels
Liquid fuels
Liquid fuels
Solid fuels
Liquid fuels
Solid fuels
Gaseous fuels
Gaseous fuels
Gaseous fuels
Solid fuels
CO2
CO2
CO2
CO2
CO2
CH4
CO2
CO2
N2O
CO2
CO2
CO2
CO2
CH4
HFC
CH4
CO2
N2O
CH4
N2O
CH4
CO2
CO2
CO2
CH4
N2O
N2O
CO2
CO2
N2O
CO2
CH4
105
84
45
44
41
34
28
25
23
18
12
11
10
9
6
6
6
5
3
3
2
2
2
2
2
2
2
1
1
1
1
1
822
699
660
227
361
953
644
118
226
811
084
898
281
338
880
493
448
155
988
023
972
831
826
751
486
356
023
830
489
395
302
177
105
84
45
44
41
34
28
25
23
18
12
11
10
9
6
6
6
5
3
3
2
2
2
2
2
2
2
1
1
1
1
1
822
699
660
227
361
953
644
118
226
811
084
898
281
338
880
493
448
155
988
023
972
831
826
751
486
356
023
830
489
395
302
177
Table A3 Key category analysis level assessment without LULUCF, 2021
Fuel
GAS 2021 Emission ABS (Emission)
18.75
15.01
8.09
7.84
7.33
6.19
5.08
4.45
4.12
3.33
2.14
2.11
1.82
1.65
1.22
1.15
1.14
0.91
0.71
0.54
0.53
0.50
0.50
0.49
0.44
0.42
0.36
0.32
0.26
0.25
0.23
0.21
Cont. (%)
445
18.75
33.76
41.85
49.68
57.01
63.20
68.28
72.73
76.85
80.18
82.32
84.43
86.25
87.90
89.12
90.27
91.42
92.33
93.04
93.57
94.10
94.60
95.10
95.59
96.03
96.45
96.80
97.13
97.39
97.64
97.87
98.08
Cumulative
Key Categories
445
1.A.4.
1.A.3.d.
2.A.3.
1.A.1.
1.A.1.
2.B.7.
1.B.2.c
2.C.6.
1.A.4.
1.B.2.a
1.A.3.b.
1.A.3.e.
2.F.3.
1.A.3.c.
3.C.
1.B.2.c
2.C.2.
2.D.1.
1.A.2.
3.F.
2.C.3.
1.A.4.
1.A.4.
1.A.4.
1.A.1.
1.A.2.
2.E.5.
1.A.1.
1.A.3.d.
2.C.4.
1.A.2.
2.C.4.
446
Turkish GHG Inventory Report 1990-2021
Biomass
Biomass
Residual fuel oil
Gaseous fuels
Solid fuels
Biomass
Other fossil fuels
Solid fuels
Solid fuels
Biomass
Solid fuels
Gaseous fuels
Liquid fuels
Gas/diesel oil
N2O
CO2
CO2
N2O
N2O
CO2
CH4
CO2
CH4
CH4
CH4
CO2
HFC
CO2
CH4
CO2
CO2
CO2
N2O
CH4
CO2
CH4
N2O
N2O
CO2
CH4
SF6
N2O
CO2
SF6
N2O
CO2
1 141
1 053
807.1
736.3
639.5
615.1
591.2
578.9
479.9
407.4
405.4
360.3
329.4
318.3
269.3
202.3
193.0
163.1
122.3
121.2
117.8
93.3
84.8
76.3
74.1
68.5
65.0
63.5
62.7
49.8
49.6
38.5
1 141
1 053
807.1
736.3
639.5
615.1
591.2
578.9
479.9
407.4
405.4
360.3
329.4
318.3
269.3
202.3
193.0
163.1
122.3
121.2
117.8
93.3
84.8
76.3
74.1
68.5
65.0
63.5
62.7
49.8
49.6
38.5
Table A3 Key category analysis level assessment without LULUCF, 2021 (cont’d)
Fuel
GAS 2021 Emission ABS (Emission)
Other sectors
Domestic Navigation
Glass Production
Energy industries
Energy industries
Soda ash production
Venting and flaring
Zinc Production
Other sectors
Oil
Road Transportation
Other transportation
Fire protection
Railways
Rice cultivation
Venting and flaring
Ferroalloys Production
Lubricant Use
Manufacturing industries and construction
Field burning of agricultural residues
Aluminium Production
Other sectors
Other sectors
Other sectors
Energy industries
Manufacturing industries and construction
Other
Energy industries
Domestic Navigation
Magnesium Production
Manufacturing industries and construction
Magnesium production
Sector
0.20
0.19
0.14
0.13
0.11
0.11
0.10
0.10
0.09
0.07
0.07
0.06
0.06
0.06
0.05
0.04
0.03
0.03
0.02
0.02
0.02
0.02
0.02
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
Cont. (%)
446
98.28
98.47
98.61
98.74
98.85
98.96
99.07
99.17
99.26
99.33
99.40
99.46
99.52
99.58
99.63
99.66
99.70
99.72
99.75
99.77
99.79
99.81
99.82
99.83
99.85
99.86
99.87
99.88
99.89
99.90
99.91
99.92
Cumulative
Key Categories
1.A.3.c.
3.F.
1.A.2.
1.A.3.a.
2.G.1.
1.A.1.
1.A.2.
1.A.4.
1.A.2.
1.A.4.
1.A.1.
2.C.1.
1.A.2.
5.B.
1.A.2.
5.B.
2.C.5.
1.A.2.
1.A.3.d.
2.B.5.
1.A.2.
1.A.1.
2.C.3.
2.D.2.
1.B.2.a
1.A.1.
5.C.
1.B.2.b
5.C.
1.A.3.d.
1.A.1.
2.B.8.
Railways
Field burning of agricultural residues
Manufacturing industries and construction
Domestic Aviation
Electrical equipment
Energy industries
Manufacturing industries and construction
Other sectors
Manufacturing industries and construction
Other sectors
Energy industries
Iron and Steel Production
Manufacturing industries and construction
Biological treatment of solid waste
Manufacturing industries and construction
Biological treatment of solid waste
Lead Production
Manufacturing industries and construction
Domestic Navigation
Carbide production
Manufacturing industries and construction
Energy industries
Aluminium Production
Paraffin Wax Use
Oil
Energy industries
Incineration and open burning of waste
Natural Gas
Incineration and open burning of waste
Domestic Navigation
Energy industries
Petrochemical and carbon black production
Sector
Turkish GHG Inventory Report 1990-2021
Gas/diesel oil
Liquid fuels
Liquid fuels
Liquid fuels
Biomass
Other fossil fuels
Gas/diesel oil
Gaseous fuels
Other fossil fuels
Gaseous fuels
Gaseous fuels
Gaseous fuels
Liquid fuels
Liquid fuels
Solid fuels
Biomass
N2O
N2O
CH4
N2O
SF6
CH4
N2O
N2O
N2O
CH4
CH4
CH4
N2O
CH4
CH4
N2O
CO2
CH4
N2O
CO2
CH4
CH4
PFC
CO2
CO2
N2O
CO2
CO2
CH4
CH4
CH4
CO2
37.5
37.5
31.2
29.3
29.2
28.6
26.7
22.2
19.1
19.1
18.8
16.7
15.7
14.5
11.3
10.3
10.0
9.9
8.7
8.5
8.1
7.7
6.8
6.7
4.1
4.1
3.6
3.4
3.1
2.6
2.5
1.4
37.5
37.5
31.2
29.3
29.2
28.6
26.7
22.2
19.1
19.1
18.8
16.7
15.7
14.5
11.3
10.3
10.0
9.9
8.7
8.5
8.1
7.7
6.8
6.7
4.1
4.1
3.6
3.4
3.1
2.6
2.5
1.4
Table A3 Key category analysis level assessment without LULUCF, 2021 (cont’d)
Fuel
GAS 2021 Emission ABS (Emission)
0.01
0.01
0.01
0.01
0.01
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Cont. (%)
447
99.92
99.93
99.94
99.94
99.95
99.95
99.96
99.96
99.96
99.97
99.97
99.97
99.98
99.98
99.98
99.98
99.98
99.99
99.99
99.99
99.99
99.99
99.99
99.99
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
Cumulative
Key Categories
447
Total
1.A.3.a.
1.A.1.
1.B.2.c
1.A.1.
5.C.
1.A.3.d.
1.A.3.c.
1.A.3.e.
1.A.3.e.
1.A.3.d.
1.C.
2.E.5.
2.E.5.
1.A.1.
1.A.2.
1.A.4.
448
Biomass
Biomass
Biomass
Residual fuel oil
Residual fuel oil
Other fossil fuels
Other fossil fuels
CH4
N2O
N2O
CH4
N2O
N2O
CH4
N2O
CH4
CH4
CO2
HFC
PFC
CO2
CO2
CO2
564 389.75
1.3
0.9
0.9
0.6
0.6
0.5
0.5
0.2
0.2
0.1
0.1
0.1
0.0
0.0
0.0
0.0
564 389.75
1.3
0.9
0.9
0.6
0.6
0.5
0.5
0.2
0.2
0.1
0.1
0.1
0.0
0.0
0.0
0.0
Table A3 Key category analysis level assessment without LULUCF, 2021 (cont’d)
Fuel
GAS 2021 Emission ABS (Emission)
Domestic Aviation
Energy industries
Venting and flaring
Energy industries
Incineration and open burning of waste
Domestic Navigation
Railways
Other transportation
Other transportation
Domestic Navigation
CO2 Transport and storage
Other
Other
Energy industries
Manufacturing industries and construction
Other sectors
Sector
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Cont. (%)
Turkish GHG Inventory Report 1990-2021
448
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
Cumulative
Key Categories
4.A.1.
1.A.1.
1.A.4.
1.A.1.
1.A.3.b.
1.A.2.
1.A.2.
1.A.4.
2.A.1.
1.A.2.
4.G.
3.A.
1.A.4.
3.D.a.
1.A.1.
5.A.
1.A.4.
2.C.1.
5.D.
2.F.6.
2.A.2.
1.B.2.b
3.B.
3.D.b.
1.B.1
2.A.4.
3.B.
1.A.3.c.
1.A.4.
2.C.3.
5.D.
1.A.2.
1.A.3.a.
1.A.4.
Forest Land Remaining Forest Land
Energy industries
Other sectors
Energy industries
Road Transportation
Manufacturing industries and construction
Manufacturing industries and construction
Other sectors
Cement Production (Mineral Products)
Manufacturing industries and construction
Harvested Wood Products
Enteric fermentation
Other sectors
Direct N2O emissions from managed soils
Energy industries
Solid waste disposal
Other sectors
Iron and Steel Production
Wastewater treatment and discharge
Other applications
Lime Production (Mineral Products)
Natural Gas
Manure management
Indirect N2O Emissions from managed soils
Solid fuels
Other process uses of carbonates
Manure management
Railways
Other sectors
Aluminium Production
Wastewater treatment and discharge
Manufacturing industries and construction
Domestic Aviation
Other sectors
Sector
Turkish GHG Inventory Report 1990-2021
Biomass
Other fossil fuels
Solid fuels
Biomass
Liquid fuels
Solid fuels
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Gaseous fuels
Fuel
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CH4
CO2
N2O
CO2
CH4
CH4
CO2
CH4
HFC
CO2
CH4
N2O
N2O
CH4
CO2
CH4
CO2
CH4
PFC
N2O
CO2
CO2
N2O
Gas
-34 769.50
105 821.85
41 360.99
45 659.89
84 698.63
28 643.76
25 118.37
12 083.73
44 226.79
10 281.13
-15 725.04
34 953.37
18 810.95
23 225.97
6 447.94
9 337.64
479.90
11 897.51
2 971.81
6 880.25
2 750.94
2 485.56
5 155.27
3 023.00
6 493.45
2 831.22
3 988.27
318.31
1 177.33
6.78
2 356.43
1 830.30
2 825.83
76.27
2021
913.74
359.72
2 248.73
143.70
3 084.28
2 137.50
3 598.18
618.97
2 352.09
651.19
1 023.23
472.80
1 440.99
-63 752.02
26 085.75
93.89
5 024.67
24 142.97
22 199.68
1 557.79
14 433.04
10 444.54
13 246.53
-2 906.72
22 396.72
14 749.94
15 176.02
5 954.30
6 729.60
2 263.35
6 938.83
2 789.04
1990
Table A4 Key category analysis trend assessment with LULUCF, 2021
0.182
0.163
0.144
0.120
0.104
0.076
0.075
0.072
0.072
0.069
0.058
0.056
0.051
0.039
0.025
0.021
0.016
0.014
0.012
0.011
0.008
0.008
0.006
0.006
0.006
0.005
0.005
0.004
0.004
0.004
0.003
0.003
0.003
0.003
Trend
12.22
10.92
9.65
8.03
7.00
5.11
5.06
4.86
4.81
4.65
3.87
3.74
3.45
2.64
1.66
1.40
1.09
0.91
0.79
0.75
0.55
0.51
0.43
0.43
0.39
0.33
0.32
0.27
0.27
0.25
0.22
0.20
0.18
0.17
Cont
449
12.22
23.15
32.80
40.83
47.83
52.94
58.01
62.86
67.67
72.32
76.19
79.93
83.38
86.02
87.68
89.08
90.17
91.08
91.87
92.61
93.17
93.67
94.11
94.54
94.93
95.27
95.59
95.86
96.13
96.38
96.59
96.79
96.97
97.14
Cum.
Key Categories
449
1.A.1.
1.A.3.d.
2.A.3.
1.A.3.d.
1.B.2.a
4.A.1.
2.B.1.
1.A.1.
2.C.6.
3.F.
1.A.4.
2.B.2.
4.A.2.
4.A.1.
4.C.2.
4.F.2.
1.B.2.c
1.B.2.c
2.B.7.
1.A.3.e.
3.H.
2.D.1.
4.B.2.
4.E.2.
1.A.3.b.
2.B.8.
1.A.3.b.
2.F.3.
5.C.
3.F.
4.B.1.
2.B.5.
1.A.3.c.
2.C.3.
450
Liquid fuels
Solid fuels
Gas/diesel oil
Gaseous fuels
Residual fuel oil
Fuel
N2O
CO2
CO2
CO2
CH4
CH4
CO2
N2O
CO2
CH4
N2O
N2O
CO2
N2O
CO2
CO2
CH4
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CH4
CO2
N2O
HFC
CH4
N2O
CO2
CO2
N2O
CO2
Gas
2021
639.50
62.70
807.11
1 053.50
407.39
696.23
1 488.76
736.29
578.89
121.19
1 141.09
2 023.13
-332.21
459.10
712.43
685.80
591.16
202.32
615.14
360.33
1 301.63
163.07
486.66
420.85
405.44
1.35
1 394.77
329.44
3.11
37.45
-124.28
8.50
37.53
117.78
Turkish GHG Inventory Report 1990-2021
67.31
81.93
0.69
58.99
68.71
99.16
96.49
81.49
537.71
39.29
459.95
175.11
126.99
217.58
2.57
282.87
111.30
220.75
419.87
74.60
424.76
96.71
37.84
265.12
692.17
1 063.63
20.70
49.19
1990
Table A4 Key category analysis trend assessment with LULUCF, 2021 (cont’d)
Energy industries
Domestic Navigation
Glass Production
Domestic Navigation
Oil
Forest Land Remaining Forest Land
Ammonia Production
Energy industries
Zinc Production
Field burning of agricultural residues
Other sectors
Nitric acid production
Land Converted to Forest Land
Forest Land Remaining Forest Land
Land Converted to Grassland
Land Converted to Other Land
Venting and flaring
Venting and flaring
Soda ash production
Other transportation
Urea application
Lubricant Use
Land Converted to Cropland
Land Converted to Settlements
Road Transportation
Petrochemical and carbon black production
Road Transportation
Fire protection
Incineration and open burning of waste
Field burning of agricultural residues
Cropland Remaining Cropland
Carbide production
Railways
Aluminium Production
Sector
0.002
0.002
0.002
0.002
0.002
0.002
0.002
0.002
0.002
0.002
0.002
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.000
0.000
0.000
0.000
Trend
0.15
0.14
0.13
0.13
0.13
0.12
0.12
0.12
0.12
0.11
0.10
0.09
0.09
0.08
0.08
0.07
0.07
0.07
0.07
0.06
0.06
0.06
0.05
0.05
0.04
0.04
0.04
0.04
0.04
0.03
0.03
0.03
0.03
0.03
Cont
450
97.29
97.43
97.56
97.68
97.81
97.94
98.06
98.18
98.30
98.41
98.51
98.60
98.69
98.77
98.85
98.92
99.00
99.06
99.13
99.19
99.25
99.31
99.36
99.41
99.45
99.50
99.54
99.57
99.61
99.64
99.67
99.70
99.73
99.75
Cum.
Key Categories
4.D.2.
1.A.4.
5.C.
1.A.4.
2.C.2.
1.A.4.
1.A.2.
1.A.2.
3.C.
4.(IV).2.
1.A.1.
2.E.5.
1.A.1.
5.C.
1.A.2.
1.A.1.
1.A.2.
1.A.1.
2.C.4.
1.A.2.
1.A.4.
1.A.2.
2.C.4.
1.A.2.
2.G.1.
2.D.2.
4.B.2.
1.A.2.
1.A.3.a.
1.A.2.
5.B.
1.A.1.
2.C.5.
5.B.
Fuel
Land Converted to Wetlands
Other sectors
Gaseous fuels
Incineration and open burning of waste
Other sectors
Solid fuels
Ferroalloys Production
Other sectors
Liquid fuels
Manufacturing industries and construction
Liquid fuels
Manufacturing industries and construction
Solid fuels
Rice cultivation
Indirect N2O Emissions from nitrogen leaching and run-off
Energy industries
Other fossil fuels
Other
Energy industries
Biomass
Incineration and open burning of waste
Manufacturing industries and construction
Gaseous fuels
Energy industries
Liquid fuels
Manufacturing industries and construction
Solid fuels
Energy industries
Gaseous fuels
Magnesium Production
Manufacturing industries and construction
Biomass
Other sectors
Gaseous fuels
Manufacturing industries and construction
Liquid fuels
Magnesium production
Manufacturing industries and construction
Biomass
Electrical equipment
Paraffin Wax Use
Land Converted to Cropland
Manufacturing industries and construction
Gaseous fuels
Domestic Aviation
Manufacturing industries and construction
Other fossil fuels
Biological treatment of solid waste
Energy industries
Solid fuels
Lead Production
Biological treatment of solid waste
Sector
CO2
CH4
CO2
N2O
CO2
CH4
N2O
N2O
CH4
N2O
CO2
SF6
N2O
N2O
N2O
N2O
CH4
CH4
SF6
N2O
N2O
CH4
CO2
CH4
SF6
CO2
N2O
CH4
N2O
N2O
CH4
CH4
CO2
N2O
Gas
225.61
93.28
3.65
84.78
192.97
19.10
19.13
122.32
269.33
78.14
74.11
65.03
63.48
0.55
26.69
4.06
68.45
28.57
49.80
49.62
22.24
8.08
38.52
31.22
29.23
6.68
25.11
11.33
29.29
15.71
14.47
18.84
10.03
10.35
2021
Turkish GHG Inventory Report 1990-2021
9.37
5.71
2.20
6.70
0.70
8.88
8.25
0.00
0.05
12.66
11.23
0.84
12.59
40.84
2.16
0.21
26.59
61.00
61.56
30.81
30.11
72.60
100.08
1990
Table A4 Key category analysis trend assessment with LULUCF, 2021 (cont’d)
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
Trend
0.02
0.02
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Cont
451
99.78
99.80
99.81
99.83
99.84
99.85
99.86
99.87
99.88
99.89
99.90
99.91
99.91
99.92
99.92
99.93
99.94
99.94
99.95
99.95
99.96
99.96
99.97
99.97
99.97
99.98
99.98
99.98
99.98
99.98
99.99
99.99
99.99
99.99
Cum.
Key Categories
451
4.C.2.
1.A.3.d.
1.A.2.
1.A.1.
1.A.3.d.
1.A.1.
4.A.2.
1.B.2.b
4.D.2.
4.A.2.
1.A.3.c.
1.A.3.d.
1.A.3.d.
1.B.2.a
1.B.2.c
2.C.1.
1.A.3.a.
1.A.1.
1.A.1.
1.C.
1.A.3.e.
1.A.3.e.
2.B.8.
2.E.5.
4.C.1.
4.D.1.1.
2.E.5.
452
Total
Other fossil fuels
Other fossil fuels
Gas/diesel oil
Residual fuel oil
Gas/diesel oil
Other fossil fuels
Liquid fuels
Residual fuel oil
Biomass
Fuel
N2O
N2O
CH4
CH4
N2O
CH4
CH4
CO2
N2O
N2O
CH4
CH4
CH4
CO2
N2O
CH4
CH4
N2O
CH4
CO2
N2O
CH4
CH4
HFC
CO2
CO2
PFC
Gas
Turkish GHG Inventory Report 1990-2021
0.03
0.01
0.00
0.13
0.02
0.02
0.05
1.02
0.86
0.53
0.63
2.38
0.91
7.89
0.31
1.79
0.00
3.05
2.15
0.00
1.55
0.25
1990
517 243.99 153 015.20
0.01
0.11
0.03
10.02
8.69
9.88
2.51
0.49
7.66
0.56
3.37
4.37
0.37
0.46
2.55
0.14
4.12
0.85
16.72
1.26
0.94
0.59
0.13
0.19
0.16
2021
Table A4 Key category analysis trend assessment with LULUCF, 2021 (cont’d)
Land Converted to Grassland
Domestic Navigation
Manufacturing industries and construction
Energy industries
Domestic Navigation
Energy industries
Land Converted to Forest Land
Natural Gas
Land Converted to Wetlands
Land Converted to Forest Land
Railways
Domestic Navigation
Domestic Navigation
Oil
Venting and flaring
Iron and Steel Production
Domestic Aviation
Energy industries
Energy industries
CO2 Transport and storage
Other transportation
Other transportation
Petrochemical and carbon black production
Other
Grassland Remaining Grassland
Peat Extraction Remaining Peat Extraction
Other
Sector
1.49
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
Trend
100.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Cont
452
99.99
99.99
99.99
99.99
99.99
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
Cum.
Key Categories
1.A.4.
1.A.1.
1.A.1.
1.A.2.
1.A.4.
1.A.2.
1.A.3.b.
3.A.
1.A.2.
1.A.4.
2.A.1.
3.D.a.
1.A.1.
5.A.
2.C.1.
1.A.4.
5.D.
2.A.2.
3.B.
1.B.1
2.F.6.
3.D.b.
1.B.2.b
3.B.
1.A.4.
1.A.3.c.
5.D.
2.A.4.
2.C.3.
1.A.4.
1.A.2.
2.B.2.
1.B.2.a
1.A.3.d.
Turkish GHG Inventory Report 1990-2021
Residual fuel oil
Biomass
Other fossil fuels
Solid fuels
Biomass
Liquid fuels
Gaseous fuels
Solid fuels
Gaseous fuels
Solid fuels
Gaseous fuels
Solid fuels
Liquid fuels
Liquid fuels
Fuel
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CH4
CO2
CO2
CO2
N2O
CO2
CH4
CO2
CH4
CH4
CO2
N2O
CH4
HFC
N2O
CH4
CH4
CH4
CO2
N2O
CO2
PFC
N2O
CO2
N2O
CH4
CO2
Gas
1
2
2
2
2
2
5
6
6
3
2
3
1
41
105
45
28
12
10
84
34
25
18
44
23
6
9
11
360.99
821.85
659.89
643.76
083.73
281.13
698.63
953.37
118.37
810.95
226.79
225.97
447.94
337.64
897.51
479.90
971.81
750.94
155.27
493.45
880.25
023.00
485.56
988.27
177.33
318.31
356.43
831.22
6.78
76.27
830.30
023.13
407.39
62.70
2021
1 063.63
419.87
282.87
2 137.50
143.70
2 352.09
1 023.23
651.19
1 440.99
618.97
472.80
359.72
26
5
22
14
13
24
22
1
14
10
15
5
6
6
2
2
2
3
3
93.89
085.75
024.67
199.68
433.04
246.53
142.97
396.72
557.79
749.94
444.54
176.02
954.30
729.60
938.83
263.35
789.04
248.73
084.28
598.18
1990
Table A5 Key category analysis trend assessment without LULUCF, 2021
Other sectors
Energy industries
Energy industries
Manufacturing industries and construction
Other sectors
Manufacturing industries and construction
Road Transportation
Enteric fermentation
Manufacturing industries and construction
Other sectors
Cement Production (Mineral Products)
Direct N2O emissions from managed soils
Energy industries
Solid waste disposal
Iron and Steel Production
Other sectors
Wastewater treatment and discharge
Lime Production (Mineral Products)
Manure management
Solid fuels
Other applications
Indirect N2O Emissions from managed soils
Natural Gas
Manure management
Other sectors
Railways
Wastewater treatment and discharge
Other process uses of carbonates
Aluminium Production
Other sectors
Manufacturing industries and construction
Nitric acid production
Oil
Domestic Navigation
Sector
0.187
0.177
0.149
0.130
0.114
0.108
0.103
0.103
0.096
0.087
0.079
0.072
0.040
0.036
0.027
0.024
0.019
0.014
0.013
0.013
0.012
0.011
0.010
0.009
0.007
0.006
0.006
0.006
0.006
0.004
0.003
0.003
0.003
0.003
Trend
10.90
10.27
8.68
7.54
6.63
6.30
6.00
6.00
5.60
5.07
4.61
4.19
2.35
2.11
1.57
1.42
1.11
0.80
0.74
0.73
0.71
0.66
0.56
0.55
0.39
0.36
0.36
0.33
0.32
0.22
0.19
0.19
0.18
0.18
Cont
453
10.90
21.17
29.85
37.39
44.02
50.32
56.32
62.32
67.91
72.98
77.58
81.77
84.12
86.23
87.80
89.22
90.33
91.13
91.87
92.60
93.31
93.97
94.53
95.07
95.46
95.82
96.17
96.50
96.82
97.05
97.24
97.43
97.60
97.78
Cum.
Key Categories
453
1.A.4.
1.A.1.
3.F.
2.A.3.
1.A.1.
1.A.3.d.
2.C.6.
1.A.3.a.
2.B.1.
1.B.2.c
2.D.1.
1.B.2.c
1.A.3.e.
2.B.7.
2.B.8.
3.F.
5.C.
1.A.3.b.
2.B.5.
1.A.3.c.
2.C.3.
2.F.3.
3.H.
1.A.4.
1.A.4.
5.C.
1.A.2.
1.A.4.
1.A.2.
1.A.2.
2.C.2.
1.A.1.
5.C.
1.A.1.
454
Turkish GHG Inventory Report 1990-2021
Liquid fuels
Other fossil fuels
Solid fuels
Liquid fuels
Liquid fuels
Solid fuels
Gaseous fuels
Solid fuels
Solid fuels
Gas/diesel oil
Liquid fuels
Gaseous fuels
Fuel
N2O
N2O
CH4
CO2
N2O
CO2
CO2
CO2
CO2
CO2
CO2
CH4
CO2
CO2
CO2
N2O
CH4
CH4
CO2
N2O
CO2
HFC
CO2
CH4
N2O
CO2
N2O
CH4
N2O
CH4
CO2
CO2
N2O
N2O
Gas
2021
1 141.09
639.50
121.19
807.11
736.29
1 053.50
578.89
2 825.83
1 488.76
202.32
163.07
591.16
360.33
615.14
1.35
37.45
3.11
405.44
8.50
37.53
117.78
329.44
1 301.63
93.28
84.78
3.65
122.32
19.10
19.13
68.45
192.97
74.11
0.55
4.06
1990
11.23
12.59
459.95
0.21
61.00
26.59
72.60
30.81
30.11
40.84
61.56
81.49
81.93
67.31
96.49
58.99
68.71
99.16
692.17
2.57
265.12
111.30
96.71
220.75
37.84
913.74
424.76
217.58
175.11
126.99
39.29
Table A5 Key category analysis trend assessment without LULUCF, 2021 (cont’d)
Other sectors
Energy industries
Field burning of agricultural residues
Glass Production
Energy industries
Domestic Navigation
Zinc Production
Domestic Aviation
Ammonia Production
Venting and flaring
Lubricant Use
Venting and flaring
Other transportation
Soda ash production
Petrochemical and carbon black production
Field burning of agricultural residues
Incineration and open burning of waste
Road Transportation
Carbide production
Railways
Aluminium Production
Fire protection
Urea application
Other sectors
Other sectors
Incineration and open burning of waste
Manufacturing industries and construction
Other sectors
Manufacturing industries and construction
Manufacturing industries and construction
Ferroalloys Production
Energy industries
Incineration and open burning of waste
Energy industries
Sector
0.003
0.003
0.003
0.002
0.002
0.002
0.002
0.002
0.002
0.002
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
Trend
0.17
0.17
0.15
0.14
0.13
0.13
0.13
0.13
0.11
0.09
0.08
0.07
0.07
0.06
0.06
0.05
0.05
0.04
0.04
0.04
0.04
0.03
0.03
0.02
0.02
0.02
0.02
0.02
0.02
0.01
0.01
0.01
0.01
0.01
Cont
454
97.95
98.12
98.26
98.40
98.53
98.66
98.79
98.92
99.02
99.11
99.19
99.26
99.33
99.39
99.45
99.49
99.54
99.58
99.62
99.66
99.69
99.73
99.76
99.78
99.80
99.82
99.84
99.85
99.87
99.88
99.89
99.89
99.90
99.91
Cum.
Key Categories
2.E.5.
1.A.1.
1.A.2.
1.A.2.
1.A.1.
1.A.4.
2.C.4.
1.A.2.
2.C.4.
2.D.2.
1.A.3.b.
1.A.2.
3.C.
2.G.1.
5.B.
1.A.2.
5.B.
1.A.3.a.
1.A.2.
1.A.1.
1.A.3.d.
2.C.5.
1.A.1.
1.A.3.d.
1.A.2.
2.C.1.
1.A.1.
1.B.2.b
1.B.2.a
1.A.3.c.
1.B.2.c
1.A.3.d.
1.A.3.d.
1.A.3.a.
Other
Energy industries
Manufacturing industries and construction
Manufacturing industries and construction
Energy industries
Other sectors
Magnesium Production
Manufacturing industries and construction
Magnesium production
Paraffin Wax Use
Road Transportation
Manufacturing industries and construction
Rice cultivation
Electrical equipment
Biological treatment of solid waste
Manufacturing industries and construction
Biological treatment of solid waste
Domestic Aviation
Manufacturing industries and construction
Energy industries
Domestic Navigation
Lead Production
Energy industries
Domestic Navigation
Manufacturing industries and construction
Iron and Steel Production
Energy industries
Natural Gas
Oil
Railways
Venting and flaring
Domestic Navigation
Domestic Navigation
Domestic Aviation
Sector
Turkish GHG Inventory Report 1990-2021
Residual fuel oil
Gas/diesel oil
Biomass
Solid fuels
Gas/diesel oil
Other fossil fuels
Other fossil fuels
Liquid fuels
Residual fuel oil
Gaseous fuels
Biomass
Biomass
Biomass
Gaseous fuels
Liquid fuels
Gaseous fuels
Gaseous fuels
Fuel
SF6
N2O
N2O
CH4
CH4
N2O
SF6
N2O
CO2
CO2
N2O
CH4
CH4
SF6
CH4
CH4
N2O
N2O
N2O
CH4
N2O
CO2
CH4
N2O
CH4
CH4
CH4
CO2
CO2
CH4
N2O
CH4
CH4
CH4
Gas
65.03
63.48
26.69
8.08
28.57
22.24
49.80
49.62
38.52
6.68
1 394.77
31.22
269.33
29.23
14.47
11.33
10.35
29.29
15.71
2.51
0.49
10.03
18.84
8.69
9.88
16.72
7.66
3.37
4.12
0.46
0.85
0.14
2.55
1.26
2021
3.05
2.15
2.20
5.71
1.79
0.00
7.89
0.00
0.25
2.38
0.86
0.91
0.63
0.53
0.31
9.37
0.70
6.70
8.88
8.25
537.71
0.00
100.08
0.84
12.66
2.16
0.05
1990
Table A5 Key category analysis trend assessment without LULUCF, 2021 (cont’d)
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
Trend
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Cont
455
99.92
99.92
99.93
99.93
99.94
99.95
99.95
99.96
99.96
99.96
99.97
99.97
99.97
99.98
99.98
99.98
99.98
99.99
99.99
99.99
99.99
99.99
99.99
99.99
99.99
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
Cum.
Key Categories
455
1.A.1.
1.A.1.
1.C.
1.A.3.e.
2.B.8.
1.A.3.e.
2.E.5.
2.E.5.
456
Total
Other fossil fuels
Other fossil fuels
Fuel
N2O
CH4
CO2
N2O
CH4
CH4
HFC
PFC
Gas
0.00
0.13
0.02
0.05
0.02
1990
564 389.75 219 526.15
0.16
0.11
0.01
0.94
0.59
0.13
0.19
2021
Table A5 Key category analysis trend assessment without LULUCF, 2021 (cont’d)
Energy industries
Energy industries
CO2 Transport and storage
Other transportation
Petrochemical and carbon black production
Other transportation
Other
Other
Sector
1.72
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
Trend
100.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Cont
456
Cum.
100.00
100.00
100.00
100.00
100.00
100.00
100.00
100.00
Key Categories
Turkish GHG Inventory Report 1990-2021
Uncertainty
Annex 2: Uncertainty
In 2019 submission, on the recommendation of the UNFCCC expert review team (ERT) in 2018, Turkish
Statistical Institute has undertaken a tier 2 uncertainty analysis. Therefore, the country has estimated
uncertainties both with Approach 1 and Approach 2 (Monte Carlo Simulation) methods. Approach 1 is
based on equations for error propagation, and Approach 2, corresponds to the application of Monte
Carlo (MC) analysis. In the IPCC Good Practice Guidance, two methodologies (Tier 1 and Tier 2) for
combining uncertainties are defined. Tier 1 uses error propagation equations. The equations are
appropriate, when uncertainties are relatively small, have normal distributions and have no significant
covariance. Tier 2 is more sophisticated method using Monte Carlo simulation. However, according to
the IPCC Good Practice Guidance (Penman et al. 2000), countries performing an uncertainty analysis
according to Tier 2 should also report the Tier 1 results. The country considered the uncertainy results
in both approaches for prioritizing category improvements. Especially sectors with large AD or EF
uncertainties, even if they are not key categories, have been treated as key categories and more precise
information has been collected on those sub-categories primarily. In order to do this, both Approach 1
and Approach 2 results are evaluated together. Table A6 shows Approach 1 results using Table 3.2 of
Volume 1 of the 2006 IPCC Guidelines for the current submission.
In the 2020 submission, Approach 2 was implemented to whole IPPU sector for 2018 emission levels
with SPSS Modeler 18.2 software. In the 2019 submission, Approach 2 was implemented to whole waste
sector and some specific sub-sectors in energy, IPPU and agriculture sector. (The main reasons of
selected categories are their large shares of in total emissions and it is thought that first uncertainty
method calculations require quality control for some of them primarily in order to provide category
improvements.) MC simulation results are presented in Table A7.1 and A7.2.
In Monte Carlo simulation, random numbers are selected from each distribution (for example, from
probability distributions of activity data and emission factors) with means of uncertainties of Approach
1, and the total emissions are calculated ten thousand to one hundred thousand of times to obtain the
probability distribution of total emissions depending on the opinion of the expert conducting the study.
In this MC simulation for emission uncertainties, the selected precisions were obtained after about
100,000 trials.
Monte Carlo simulation allows the use of asymmetrical distributions. Normal distribution is the most
widely used distribution for uncertainties. It is symmetrical around the mean and defined for all values.
However, because emissions cannot be negative, normal distribution is used only in the cases where
Turkish GHG Inventory Report 1990-2021
457 457
Uncertainty
uncertainty is lower than ±100%. Normal distribution is a two parametric distribution and can therefore
be completely described with the 95% confidence interval. Moreover, some subcategories are defined
with the probability density function of lognormal distribution (e.g. urea application and biological
treatment of solid waste because of single-sided uncertainty distribution of ADs or EFs). Lognormal
distribution is positively skewed, and it is defined only for positive values, which makes it very useful in
describing emissions. Lognormal distribution is a transformation of normal distribution and is therefore
also a two parametric distribution. A combination of Monte Carlo and Bootstrap simulation was applied
also to some categories, with respect to specific data availability assuming a normal distribution for
activity data and for the emission factor of natural gas. In 2020 submission, for entire IPPU sector, all
distributions assumed were as normal distribution.
According to the Good Practice Guidance and Uncertainty Management in National Greenhouse Gas
Emission Inventories, quality control is “a system of routine technical activities, to measure and control
the quality of the inventory as it is being developed”. The QC system is designed to provide routine and
consistent checks to ensure data integrity, correctness and completeness, to identify and address errors
and emissions and to document and archive inventory material and record all QC activities. Therefore,
Monte Carlo is a way of QC procedure. And, for the categories with a high uncertainty, generally, further
improvements are planned whenever sectoral studies can be carried out.
Throughout the entire time series, the uncertainties associated with annual estimates are expressed as
a 95% confidence interval, bound by 2.5th and 97.5th percentiles of the Monte Carlo run outputs as can
be seen at the end of this chapter from uncertainty histograms.
458
Turkish GHG Inventory Report 1990-2021
458
1.A.1.a.
1.A.1.a.
1.A.1.a.
1.A.1.a.
1.A.1.b.
1.A.1.b.
1.A.1.b.
1.A.1.c.
1.A.1.c.
1.A.2.a.
1.A.2.a.
1.A.2.a.
1.A.2.b.
1.A.2.b.
1.A.2.b.
1.A.2.c.
1.A.2.c.
1.A.2.c.
1.A.2.c.
1.A.2.d.
1.A.2.d.
1.A.2.d.
1.A.2.e.
1.A.2.e.
1.A.2.e.
1.A.2.f.
1.A.2.f.
1.A.2.f.
1.A.2.f.
1.A.2.g.
1.A.2.g.
1.A.2.g.
1.A.3.a.
1.A.3.b.
1.A.3.b.
Public Electricity and Heat Production
Public Electricity and Heat Production
Public Electricity and Heat Production
Public Electricity and Heat Production
Petroleum Refining
Petroleum Refining
Petroleum Refining
Manufacture of solid fuels
Manufacture of solid fuels
Iron and Steel Production
Iron and Steel Production
Iron and Steel Production
Non-Ferrous Metals
Non-Ferrous Metals
Non-Ferrous Metals
Chemicals
Chemicals
Chemicals
Chemicals
Pulp, Paper and Print
Pulp, Paper and Print
Pulp, Paper and Print
Food Processing, Beverages and Tobacco
Food Processing, Beverages and Tobacco
Food Processing, Beverages and Tobacco
Non-metallic minerals
Non-metallic minerals
Non-metallic minerals
Non-metallic minerals
Other Industries
Other Industries
Other Industries
Domestic Aviation
Road Transportation
Road Transportation
Source Category
Fuel
Liquid fuels
Solid fuels
Gaseous fuels
Other fossil fuels
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Other fossil fuels
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Other fossil fuels
Liquid Fuels
Solid Fuels
Gaseous Fuels
Jet kerosene
Gasoline
Diesel oil
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
Gas
Emissions
in 2021
Turkish GHG Inventory Report 1990-2021
4 860.3
7 786.9
611.2
913.7
8 377.4
15 765.5
2 626.3
5 587.5
1.9
420.7
2 471.7
2 588.1
1 342.6
944.6
927.8
156.3
14.7
1 938.0
1 823.3
4 854.8
2 289.4
3 650.2
24 147.7
5 024.7
2 346.5
45.2
2 051.4
3 721.7
22.1
151.2
692.3
49.9
1 971.7
6 253.7
0.6
16.9
724.3
534.2
57.1
3 301.5
2 940.4
9 265.6
16 628.7
4 770.5
1 829.7
824.3
3 814.9
6 205.5
2 825.8
8 867.0
66 375.9
931.3
103 358.9
43 536.8
74.1
5 516.6
116.4
2 123.1
Gg CO2 eq Gg CO2 eq
Emissions
in 1990
1.0
1.0
1.0
18.0
2.0
2.0
2.0
2.0
2.0
10.0
10.0
10.0
21.2
21.2
21.2
15.8
15.8
15.8
2.0
18.0
18.0
18.0
5.0
18.0
14.1
27.8
25.5
29.2
2.0
70.7
70.7
70.7
5.5
10.1
10.1
4.1
3.4
1.1
9.6
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
5.0
5.0
5.0
4.2
3.5
1.5
20.4
7.3
7.3
7.3
7.3
7.3
12.2
12.2
12.2
22.3
22.3
22.3
17.3
17.3
17.3
7.3
19.3
19.3
19.3
8.6
19.3
15.8
28.7
26.4
30.0
7.3
71.1
71.1
71.1
7.4
11.2
11.2
AD
EF Combined
Unc. Unc.
Unc.
%
%
%
Table A6 Approach 1 Uncertainty assessment
0.0
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.7
0.1
0.0
0.0
0.3
0.7
0.0
0.0
2.1
H(1)
%
0.1
0.1
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.1
0.1
I(2)
%
0.0
0.7
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.4
J(3)
%
0.3
0.5
0.2
0.0
0.1
0.0
0.1
0.0
0.2
0.3
0.7
0.2
0.1
0.0
0.0
0.4
0.1
0.1
0.0
0.0
0.0
0.0
0.1
0.2
0.1
0.0
0.1
0.2
0.1
0.7
1.0
0.2
0.0
0.6
0.4
K(4)
%
0.0
1.0
0.4
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.2
0.3
0.0
0.0
0.1
0.0
0.3
0.9
0.0
0.0
0.1
0.1
0.0
0.5
0.4
2.4
3.9
1.3
0.0
0.5
2.5
4.1
0.1
0.8
6.2
L(5)
%
0.1
1.1
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.5
0.1
0.0
0.0
0.0
0.2
0.1
0.9
0.0
0.0
0.0
0.0
0.0
0.4
0.2
5.7
15.4
1.7
0.0
0.8
7.3
16.5
0.0
1.1
38.2
M(6)
%
459
Uncertainty
459
460
1.A.3.b.
1.A.3.b.
1.A.3.c.
1.A.3.c.
1.A.3.d.
1.A.3.d.
1.A.3.e.
1.A.4.a.
1.A.4.a.
1.A.4.a.
1.A.4.b.
1.A.4.b.
1.A.4.b.
1.A.4.c.
1.A.4.c.
1.B.2.a.
1.B.2.b.
1.B.2.c.
1.C
2.A.1.
2.A.2.
2.A.3.
2.A.4.
2.B.1.
2.B.5.
2.B.7.
2.B.8.
2.C.1.
2.C.2.
2.C.3.
2.C.4.
2.C.5.
2.C.6.
2.D.1.
2.D.2.
Road Transportation
Road Transportation
Railways
Railways
Domestic Navigation
Domestic Navigation
Pipeline Transportation
Commercial/institutional
Commercial/institutional
Commercial/institutional
Residential
Residential
Residential
Agriculture/Forestry/Fisheries
Agriculture/Forestry/Fisheries
Oil
Natural gas
Venting and flaring
Transport of CO2
Cement Production (Mineral Products)
Lime Production (Mineral Products)
Glass Production
Other process uses of carbonates
Ammonia Production
Carbide production
Soda ash production
Petrochemical and carbon black production
Iron and Steel Production
Ferroalloys Production
Aluminium Production
Magnesium Production
Lead Production
Zinc Production
Lubricant Use
Paraffin Wax Use
Source Category
LPG
Gaseous fuels
Liquid fuels
Solid fuels
Residual fuel oil
Gas/diesel oil
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Gaseous fuels
Fuel
Gas
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
Turkish GHG Inventory Report 1990-2021
2.2
37.8
175.1
8.3
81.5
6 938.8
61.6
99.2
2.4
0.3
217.6
0.1
10 444.5
2 248.7
111.3
619.0
424.8
59.0
8 663.4
14 749.9
93.9
5 769.6
589.5
61.7
282.9
220.8
39.3
Gg CO2 eq
Gg CO2 eq
62.7
1 053.5
360.3
1 267.8
3 488.7
9 138.8
1 154.0
15 322.2
31 932.3
9 662.0
289.9
4.1
3.4
202.3
0.1
44 226.8
2 750.9
807.1
2 831.2
1 488.8
8.5
615.1
1.4
11 897.5
193.0
117.8
38.5
10.0
578.9
163.1
6.7
9 301.7
154.0
318.3
Emissions
in 2021
Emissions
in 1990
10.1
10.0
2.0
0.0
15.0
15.0
5.0
7.1
14.1
5.0
7.1
14.1
5.0
14.1
7.0
7.0
7.0
7.0
2.0
5.0
10.0
3.0
30.0
2.0
5.0
5.0
10.0
10.0
5.0
1.0
5.0
25.0
5.0
20.0
20.0
%
AD
Unc.
5.0
7.0
1.5
14.0
3.0
1.5
7.0
7.0
7.0
7.0
7.0
7.0
7.0
5.0
7.0
50.0
50.0
50.0
50.0
2.0
2.0
2.0
2.0
5.0
20.0
1.0
10.0
8.0
25.0
5.0
10.0
20.0
50.0
50.0
100.0
11.2
12.2
2.5
14.0
15.3
15.1
8.6
10.0
15.7
8.6
10.0
15.7
8.6
15.0
9.9
50.5
50.5
50.5
50.0
5.4
10.2
3.6
30.1
5.4
20.6
5.1
14.1
12.8
25.5
5.1
11.2
32.0
50.2
53.9
102.0
EF Combined
Unc.
Unc.
%
%
Table A6 Approach 1 Uncertainty assessment (cont’d)
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.3
0.1
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
H(1)
%
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.2
0.2
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
I(2)
%
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.2
0.1
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
J(3)
%
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.4
1.3
1.6
1.4
0.3
0.0
0.0
0.0
0.2
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.6
0.0
0.0
0.0
0.0
0.1
0.1
0.0
K(4)
%
0.9
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.5
0.4
0.1
2.0
1.5
1.3
0.0
0.0
0.0
0.0
0.0
2.0
0.3
0.0
0.8
0.0
0.0
0.0
0.0
1.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
L(5)
%
460
0.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.4
1.7
6.5
4.3
1.7
0.0
0.0
0.0
0.0
0.0
4.2
0.1
0.0
0.6
0.0
0.0
0.0
0.0
1.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
M(6)
%
Uncertainty
1.A.1.a.
1.A.1.a.
1.A.1.a.
1.A.1.a.
1.A.1.a.
1.A.1.b.
1.A.1.b.
1.A.1.b.
1.A.1.c.
1.A.1.c.
1.A.2.a.
1.A.2.a.
1.A.2.a.
1.A.2.a.
1.A.2.b.
1.A.2.b.
1.A.2.b.
1.A.2.c.
1.A.2.c.
1.A.2.c.
1.A.2.c.
1.A.2.c.
1.A.2.d.
3.H.
4.A.
4.B.
4.C.
4.D.
4.E.
4.F.
4.G.
5.C.
Public Electricity and Heat Production
Public Electricity and Heat Production
Public Electricity and Heat Production
Public Electricity and Heat Production
Public Electricity and Heat Production
Petroleum Refining
Petroleum Refining
Petroleum Refining
Manufacture of solid fuels
Manufacture of solid fuels
Iron and Steel Production
Iron and Steel Production
Iron and Steel Production
Iron and Steel Production
Non-Ferrous Metals
Non-Ferrous Metals
Non-Ferrous Metals
Chemicals
Chemicals
Chemicals
Chemicals
Chemicals
Pulp, Paper and Print
Total CO2
Urea application
Forest land
Cropland
Grassland
Wetlands
Settlements
Other land
Harvested wood products
Incineration and open burning of waste
Source Category
Liquid fuels
Solid fuels
Gaseous fuels
Other fossil fuels
Biomass
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Liquid fuels
Solid fuels
Gaseous fuels
Biomass
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Other fossil fuels
Biomass
Liquid fuels
Fuel
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
Gas
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
Turkish GHG Inventory Report 1990-2021
2.5
2.9
0.4
0.9
0.3
0.0
0.4
1.8
0.7
1.8
1.2
5.3
2.2
0.3
0.0
0.5
1.7
0.0
0.0
0.4
0.3
0.0
5.1
2.8
0.0
0.1
0.0
0.3
18.4
27.6
0.6
7.7
2.2
0.1
1.0
84 977.7 404 283.1
-2 906.7
26.6
1 301.6
-35 101.7
362.4
712.5
225.6
420.8
685.8
-15 725.0
3.6
Gg CO2 eq
Gg CO2 eq
459.9
-63 731.3
0.7
0.0
0.0
Emissions
in 2021
Emissions
in 1990
6.0
1.0
3.0
0.9
0.9
2.0
2.0
2.0
2.0
2.0
10.0
10.0
10.0
10.0
21.2
21.2
21.2
15.8
15.8
15.8
2.0
15.8
18.0
10.0
75.7
47.9
148.7
85.9
25.7
15.6
23.3
30.4
%
AD
Unc.
25.0
25.0
25.0
25.0
25.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
50.0
4.5
4.2
10.2
3.9
4.0
3.8
3.2
40.0
25.7
25.0
25.2
25.0
25.0
100.0
100.0
100.0
100.0
100.0
100.5
100.5
100.5
100.5
102.2
102.2
102.2
101.2
101.2
101.2
100.0
101.2
101.6
51.0
75.8
48.0
149.0
86.0
26.0
16.0
23.5
50.2
EF Combined
Unc.
Unc.
%
%
Table A6 Approach 1 Uncertainty assessment (cont’d)
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
26.5
0.0
0.0
0.0
0.0
0.0
0.5
0.0
H(1)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
I(2)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.1
0.0
J(3)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
5.3
0.0
0.0
0.0
0.0
0.0
0.1
0.0
K(4)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
24.6
0.2
1.0
0.2
0.1
0.1
3.4
0.0
L(5)
%
461
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
631.2
0.0
1.0
0.0
0.0
0.0
11.5
0.0
M(6)
%
Uncertainty
461
462
1.A.2.d.
1.A.2.d.
1.A.2.d.
1.A.2.e.
1.A.2.e.
1.A.2.e.
1.A.2.e.
1.A.2.f.
1.A.2.f.
1.A.2.f.
1.A.2.f.
1.A.2.f.
1.A.2.g.
1.A.2.g.
1.A.2.g.
1.A.2.g.
1.A.3.a.
1.A.3.b.
1.A.3.b.
1.A.3.b.
1.A.3.b.
1.A.3.b.
1.A.3.c.
1.A.3.c.
1.A.3.d.
1.A.3.d.
1.A.3.e.
1.A.4.a.
1.A.4.a.
1.A.4.a.
1.A.4.b.
1.A.4.b.
1.A.4.b.
1.A.4.b.
1.A.4.c.
Pulp, Paper and Print
Pulp, Paper and Print
Pulp, Paper and Print
Food Processing, Beverages and
Food Processing, Beverages and
Food Processing, Beverages and
Food Processing, Beverages and
Non-metallic minerals
Non-metallic minerals
Non-metallic minerals
Non-metallic minerals
Non-metallic minerals
Other Industries
Other Industries
Other Industries
Other Industries
Domestic Aviation
Road Transportation
Road Transportation
Road Transportation
Road Transportation
Road Transportation
Railways
Railways
Domestic Navigation
Domestic Navigation
Pipeline Transportation
Commercial/institutional
Commercial/institutional
Commercial/institutional
Residential
Residential
Residential
Residential
Agriculture/Forestry/Fisheries
Source Category
Tobacco
Tobacco
Tobacco
Tobacco
Solid fuels
Gaseous fuels
Biomass
Liquid fuels
Solid fuels
Gaseous fuels
Biomass
Liquid fuels
Solid fuels
Gaseous fuels
Other fossil fuels
Biomass
Liquid Fuels
Solid Fuels
Gaseous Fuels
Biomass
Jet kerosene
Gasoline
Diesel oil
Liquefied petroleum gases (LPG)
Gaseous fuels
Biomass
Liquid fuels
Solid fuels
Residual fuel oil
Gas/diesel oil
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Biomass
Liquid fuels
Fuel
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
Gas
Turkish GHG Inventory Report 1990-2021
22.5
1 023.2
0.2
2 263.4
8.3
0.8
0.0
0.6
0.5
0.0
0.3
75.6
20.9
4.7
17.7
0.3
2.4
13.6
0.0
0.4
5.5
0.1
2.6
0.2
2.9
8.5
20.6
2.3
1 168.9
72.0
479.9
13.9
7.2
42.9
2.2
9.9
19.0
0.7
9.5
2.8
11.9
1.3
80.0
89.5
228.6
6.4
0.9
0.5
18.0
18.0
18.0
5.0
18.0
14.1
5.0
27.8
25.5
29.2
2.0
2.0
70.7
70.7
70.7
2.0
5.5
10.0
10.0
10.0
10.0
10.0
5.0
5.0
15.0
15.0
5.0
7.1
14.1
5.0
7.1
14.1
5.0
300.0
200.0
%
Gg CO2 eq Gg CO2 eq
1.8
0.2
0.2
0.1
8.3
1.3
AD
Unc.
Emissions
in 2021
Emissions
in 1990
Table A6 Approach 1 Uncertainty assessment (cont’d)
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
80.0
250.0
250.0
250.0
250.0
250.0
105.0
135.0
50.0
50.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
250.0
101.6
101.6
101.6
100.1
101.6
101.0
100.1
103.8
103.2
104.2
100.0
100.0
122.5
122.5
122.5
100.0
80.2
250.2
250.2
250.2
250.2
250.2
105.1
135.1
52.2
52.2
100.1
100.3
101.0
100.1
100.3
101.0
100.1
316.2
320.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
EF Combined
Unc.
Unc. H(1)
%
% %
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
I(2)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
J(3)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.5
0.0
4.7
0.0
K(4)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
1.3
0.0
L(5)
%
462
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
2.3
0.0
23.7
0.0
M(6)
%
Uncertainty
1.A.1.a.
1.A.1.a.
1.A.1.a.
1.A.1.a.
1.A.1.a.
1.A.1.b.
1.A.1.b.
1.A.1.b.
1.A.1.c.
1.A.1.c.
1.A.2.a.
1.A.2.a.
1.A.2.a.
1.A.2.a.
1.A.4.c.
1.B.1.a.
1.B.2.a.
1.B.2.b.
1.B.2.c.
2.B.8.
2.C.1.
3.A.
3.B.
3.C.
3.F.
4.A.
5.A.1.
5.A.2.
5.B.
5.C.
5.D.1
5.D.2
Fuel
Public Electricity and Heat Production
Public Electricity and Heat Production
Public Electricity and Heat Production
Public Electricity and Heat Production
Public Electricity and Heat Production
Petroleum Refining
Petroleum Refining
Petroleum Refining
Manufacture of solid fuels
Manufacture of solid fuels
Iron and Steel Production
Iron and Steel Production
Iron and Steel Production
Iron and Steel Production
Total CH4
Liquid fuels
Solid fuels
Gaseous fuels
Other fossil fuels
Biomass
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Liquid fuels
Solid fuels
Gaseous fuels
Biomass
Agriculture/Forestry/Fisheries
Gaseous fuels
Coal mining and handling
Oil
Natural gas
Venting and flaring
Petrochemical and carbon black production
Iron and Steel Production
Enteric fermentation
Manure management
Rice cultivation
Field burning of agricultural residues
Forest land
Managed waste disposal
Unmanaged waste disposal sites
Biological treatment of solid waste
Incineration and open burning of waste
Domestic wastewater
Industrial wastewater
Source Category
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
CO2 eq
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
Gas
16.7
34 953.4
3 988.3
269.3
121.2
696.8
1 839.2
7 498.4
14.5
3.1
2 332.8
639.0
Turkish GHG Inventory Report 1990-2021
0.0
1.5
4.2
0.8
4.1
8.5
95.2
2.6
0.4
0.1
0.8
2.0
0.0
1.3
735.7
638.4
0.9
63.5
2.7
0.2
1.1
42 563.7 64 717.0
6 729.6
9.4
67.3
2 579.8
209.2
3 598.2
419.9
143.7
127.0
0.0
7.9
22 396.7
2 352.1
100.1
265.1
76.1
%
6.0
1.0
3.0
0.9
0.9
2.0
2.0
2.0
10.0
2.0
10.0
10.0
10.0
2.0
7.0
16.6
7.0
7.0
7.0
10.0
10.0
8.7
14.1
5.0
50.0
23.5
10.0
30.0
10.0
30.4
5.0
11.2
Gg CO2 eq Gg CO2 eq
0.7
6 493.4
407.4
2 485.6
591.2
AD
Unc.
Emissions
in 2021
Emissions
in 1990
75.0
75.0
75.0
75.0
75.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
150.0
100.0
100.0
100.0
30.0
5.0
12.0
30.0
76.7
40.0
1.7
30.8
38.1
20.0
100.0
37.7
39.1
75.2
75.0
75.1
75.0
75.0
100.0
100.0
100.0
100.5
100.0
100.5
100.5
100.5
100.0
100.2
150.9
100.2
100.2
100.2
31.6
11.2
14.8
33.1
76.9
64.0
23.6
32.4
48.5
22.4
104.5
38.0
40.7
EF Combined
Unc.
Unc.
%
%
Table A6 Approach 1 Uncertainty assessment (cont’d)
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.6
0.0
0.2
0.0
0.0
0.0
1.0
0.1
0.0
0.0
0.0
0.0
0.5
0.0
0.0
0.0
0.0
H(1)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
I(2)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
J(3)
%
0.0
0.2
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
5.6
0.7
1.3
0.1
0.0
0.0
3.2
0.8
0.0
0.2
0.0
0.4
3.8
0.0
0.1
1.6
0.0
K(4)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
0.0
0.2
0.0
0.0
0.0
2.8
0.5
0.0
0.1
0.2
0.2
2.1
0.0
0.0
0.1
0.1
L(5)
%
463
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
31.9
0.4
1.7
0.0
0.0
0.0
18.1
0.9
0.0
0.0
0.0
0.2
18.7
0.0
0.0
2.5
0.0
M(6)
%
Uncertainty
463
464
1.A.2.b.
1.A.2.b.
1.A.2.b.
1.A.2.c.
1.A.2.c.
1.A.2.c.
1.A.2.c.
1.A.2.c.
1.A.2.d.
1.A.2.d.
1.A.2.d.
1.A.2.d.
1.A.2.e.
1.A.2.e.
1.A.2.e.
1.A.2.e.
1.A.2.f.
1.A.2.f.
1.A.2.f.
1.A.2.f.
1.A.2.f.
1.A.2.g.
1.A.2.g.
1.A.2.g.
1.A.2.g.
1.A.3.a.
1.A.3.b.
1.A.3.b.
1.A.3.b.
1.A.3.b.
1.A.3.b.
1.A.3.c.
1.A.3.c.
1.A.3.d.
1.A.3.d.
Non-Ferrous Metals
Non-Ferrous Metals
Non-Ferrous Metals
Chemicals
Chemicals
Chemicals
Chemicals
Chemicals
Pulp, Paper and Print
Pulp, Paper and Print
Pulp, Paper and Print
Pulp, Paper and Print
Food Processing, Beverages
Food Processing, Beverages
Food Processing, Beverages
Food Processing, Beverages
Non-metallic minerals
Non-metallic minerals
Non-metallic minerals
Non-metallic minerals
Non-metallic minerals
Other Industries
Other Industries
Other Industries
Other Industries
Domestic Aviation
Road Transportation
Road Transportation
Road Transportation
Road Transportation
Road Transportation
Railways
Railways
Domestic Navigation
Domestic Navigation
Source Category
and
and
and
and
Tobacco
Tobacco
Tobacco
Tobacco
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Other fossil fuels
Biomass
Liquid fuels
Solid fuels
Gaseous fuels
Biomass
Liquid fuels
Solid fuels
Gaseous fuels
Biomass
Liquid fuels
Solid fuels
Gaseous fuels
Other fossil fuels
Biomass
Liquid Fuels
Solid Fuels
Gaseous Fuels
Biomass
Jet kerosene
Gasoline
Diesel oil
Liquefied petroleum gases (LPG)
Gaseous fuels
Biomass
Liquid fuels
Solid fuels
Residual fuel oil
Gas/diesel oil
Fuel
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
Gas
Turkish GHG Inventory Report 1990-2021
68.4
0.3
2.1
1.8
8.9
288.2
249.5
11.1
31.7
0.3
0.5
8.7
17.2
76.8
2.6
15.7
30.2
1.5
17.0
3.3
18.8
29.3
305.0
1 067.3
8.8
2.5
11.2
37.5
5.6
24.3
0.0
1.0
9.9
6.1
5.3
0.5
21.2
21.2
21.2
15.8
15.8
15.8
2.0
2.0
18.0
18.0
18.0
2.0
5.0
18.0
14.1
2.0
27.8
25.5
29.2
2.0
2.0
70.7
70.7
70.7
2.0
5.5
10.0
10.0
10.0
10.0
10.0
5.0
5.0
15.0
15.0
%
0.1
0.7
0.4
0.1
9.1
3.4
0.0
0.2
0.0
3.2
0.3
0.4
0.1
14.8
14.8
Gg CO2 eq Gg CO2 eq
2.1
0.6
AD
Unc.
Emissions
in 2021
Emissions
in 1990
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
85.0
250.0
250.0
250.0
250.0
250.0
142.0
150.0
140.0
140.0
102.2
102.2
102.2
101.2
101.2
101.2
100.0
100.0
101.6
101.6
101.6
100.0
100.1
101.6
101.0
100.0
103.8
103.2
104.2
100.0
100.0
122.5
122.5
122.5
100.0
85.2
250.2
250.2
250.2
250.2
250.2
142.1
150.1
140.8
140.8
EF Combined
Unc.
Unc.
%
%
Table A6 Approach 1 Uncertainty assessment (cont’d)
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
H(1)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
I(2)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
J(3)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
1.1
0.4
0.0
0.0
0.0
0.2
0.0
0.0
0.0
K(4)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
L(5)
%
464
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.2
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
M(6)
%
Uncertainty
1.A.3.e.
1.A.4.a.
1.A.4.a.
1.A.4.a.
1.A.4.b.
1.A.4.b.
1.A.4.b.
1.A.4.b.
1.A.4.c.
1.A.4.c.
1.B.2.c.
2.B.2.
3.B.
3.D.
3.F.
4.A.
4.B.
4.C.
4.D.
4.(IV).
5.B.
5.C.
5.D.1
Turkish GHG Inventory Report 1990-2021
Total N2O
Pipeline Transportation
Commercial/institutional
Commercial/institutional
Commercial/institutional
Residential
Residential
Residential
Residential
Agriculture/Forestry/Fisheries
Agriculture/Forestry/Fisheries
Venting and flaring
Nitric acid production
Manure management
Agricultural soils
Field burning of agricultural residues
Forest land
Cropland
Grassland
Wetlands
Indirect N2O Emissions
Biological treatment of solid waste
Incineration and open burning of waste
Wastewater treatment and discharge
Source Category
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Liquid fuels
Solid fuels
Gaseous fuels
Biomass
Liquid fuels
Gaseous fuels
Fuel
CO2 eq
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
N2O
Gas
25 001.0
6.7
11.2
1 441.0
0.9
1 063.6
3 084.3
17 313.5
81.9
50.2
11.8
61.0
0.1
359.7
680.3
40 883.2
2
2
5
26
1
0.2
1.2
15.1
4.9
0.6
69.7
17.2
76.3
139.3
0.2
0.9
023.1
155.3
249.0
37.5
459.5
25.1
10.0
4.4
78.1
10.3
0.6
356.4
Gg CO2 eq
Gg CO2 eq
0.0
Emissions
in 2021
Emissions
in 1990
5.0
7.1
14.1
5.0
7.1
14.1
5.0
300.0
14.1
7.0
7.0
2.0
14.1
18.5
50.0
23.5
23.5
23.5
23.5
166.0
10.0
30.4
30
%
AD
Unc.
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
250.0
100.0
100.0
20.0
50.0
94.6
40.0
0.9
4.5
4.5
4.5
350.0
20.0
100.0
42.4
100.1
100.3
101.0
100.1
100.3
101.0
100.1
316.2
250.4
100.2
100.2
20.1
52.0
96.4
64.0
23.5
23.9
23.9
23.9
387.4
22.4
104.5
51.9
EF Combined
Unc.
Unc.
%
%
Table A6 Approach 1 Uncertainty assessment (cont’d)
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.3
24.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
H(1)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
I(2)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
J(3)
%
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.7
1.9
0.0
0.0
0.2
1.7
19.9
0.1
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.7
K(4)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.0
0.0
0.0
0.7
4.5
0.0
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.7
L(5)
%
465
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.6
3.6
0.0
0.0
0.0
3.4
417.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
M(6)
%
Uncertainty
465
466
472.8
472.8
7 360.6
0.1
329.4
6880.2
6.8
0.0
49.8
65.0
29.2
Gg CO2 eq
Gg CO2 eq
25.0
25.0
25.0
2.0
25.0
5.0
25.0
25.0
%
AD
Unc.
(6) Uncertainty introduced into the trend in total national emissions
(5) Uncertainty in trend in national emissions introduced by activity data uncertainty
5.0
5.0
5.0
5.0
5.0
5.0
5.0
5.0
Overall
Unc.
5.5
8.0
25.5
25.5
25.5
5.4
25.5
7.1
25.5
25.5
EF Combined
Unc.
Unc.
%
%
Overall
Unc.
(4) Uncertainty in trend in national emissions introduced by emission factor / estimation parameter uncertainty
(3) Type B sensitivity
(2) Type A sensitivity
(1) Contribution to Variance by Category in Year t
219 526.2 564 389.7
CO2 eq
Gas
HFC
HFC
HFC
PFC
PFC
SF6
SF6
SF6
Total all gases without LULUCF
Fuel
153 015.2 517 244.0
Total HFCs, PFCs and SF6
Other
Fire protection
Other applications
Aluminium Production
Other
Magnesium Production
Other
Electrical equipment
Total all gases with LULUCF
2.E.5.
2.F.3.
2.F.6.
2.C.3.
2.E.5.
2.C.4.
2.E.5.
2.G.1.
Source Category
Emissions
in 2021
Emissions
in 1990
Table A6 Approach 1 Uncertainty assessment (cont’d)
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
H(1)
%
Trend
Unc.
Trend
Unc.
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
I(2)
%
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
J(3)
%
12.3
35.9
0.0
0.0
0.2
0.1
0.0
0.0
0.0
0.0
K(4)
%
0.0
0.1
1.6
0.0
0.0
0.0
0.0
0.0
L(5)
%
466
0.0
0.0
2.6
0.0
0.0
0.0
0.0
0.0
M(6)
%
Uncertainty
Turkish GHG Inventory Report 1990-2021
Turkish GHG Inventory Report 1990-2021
Public Electricity and Heat Production
Cement Production (Mineral Products)
Lime Production (Mineral Products)
Urea application
Incineration and open burning of waste
Rice cultivation
Managed waste disposal
Unmanaged waste disposal sites
Biological treatment of solid waste
Incineration and open burning of waste
Domestic wastewater
Industrial wastewater
Biological treatment of solid waste
Incineration and open burning of waste
Wastewater treatment and discharge
1.A.1.a.
2.A.1.
2.A.2.
3.H.
5.C.
3.C.
5.A.1.
5.A.2.
5.B.
5.C.
5.D.1
5.D.2
5.B.
5.C.
5.D.1
Gaseous fuels
Solid fuels
Liquid fuels
N2O
N2O
N2O
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CO2
CO2
CO2
CO2
CO2
CO2
CO2
19.49
0.00
0.02
20.97
77.02
0.07
0.33
329.29
33.87
9.35
1.91
1449.63
2683.98
37272.44
45136.77
98081.63
1232.24
19.48
0.00
0.02
24.15
77.04
0.07
0.36
327.05
51.94
104.52
22.36
40.67
38.03
104.52
22.36
48.49
32.38
76.9
34.64
50.24
9.47
50.99
14.14
5.39
1.50
3.50
4.24
Combined
Uncertainty (%)
Approach 1 (±)
1.91
1451.54
2684.52
37270.42
44124.70
102140.92
1190.78
Estimates of 2017
Emissions (Means) with MC
(kt)
Source: Ulusoy, G., 2019. Investigation of Sectoral Uncertainties in Turkish Greenhouse Gas Inventory and Application of Monte Carlo Simulation. TurkStat Expertness Thesis, Ankara.
Public Electricity and Heat Production
1.A.1.a.
Selected Sources
Public Electricity and Heat Production
1.A.1.a.
2017
Emissions
(kt)
Table A7.1 Approach 2 Uncertainty assessment (Monte Carlo Simulation Method) for 2017
467
-24.38, +25.56
-72.73, +100
+50
-32.71, +41.28
-40.16, +40.77
-85.71, +114.29
±22.22
-46.85, +47.31
-34.93, +34.82
-68.95, +70.43
±41.88
-13.54, +14.70
-12.29, +12.90
-4.97, +5.02
-1.46, +1.47
-2.97, +2.91
±2.65
Combined
Uncertainty (%)
Approach 2
Uncertainty
467
468
37 025.7
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CH4
N2O
IPPU Sector
2.A.1. Cement Production (Mineral Products)
2.A.2. Lime Production (Mineral Products)
2.A.3. Glass Production
2.A.4. Other process uses of carbonates
2.B.1. Ammonia Production
2.B.5. Carbide production
2.B.7. Soda ash production
2.B.8. Petrochemical and carbon black production
2.C.1. Iron and Steel Production
2.C.2. Ferroalloys Production
2.C.3. Aluminium Production
2.C.5. Lead Production
2.D.1. Lubricant Use
2.D.2. Paraffin Wax Use
2.C.1. Iron and Steel Production
2.B.2. Nitric acid production
1 823.2
17.1
13.0
193.4
8.1
107.3
169.8
12 536.6
1.2
224.4
6.2
1 038.4
3 356.3
650.0
2 786.7
2018
Emissions
(kt)
1 823.8
17.3
13.0
193.4
8.1
107.4
169.9
12 599.2
1.2
224.4
6.2
1 038.3
3 354.3
650.1
2 789.5
37 027.0
Estimates of 2018
Emissions (Means)
with MC (kt)
20.10
11.18
103.08
55.90
32.02
5.10
25.50
26.93
14.14
5.10
20.62
5.39
30.07
5.39
14.14
5.39
Combined
Uncertainty
(%) Approach
1 (±)
Table A7.2 Approach 2 Uncertainty assessment (Monte Carlo Simulation Method) for 2018
Turkish GHG Inventory Report 1990-2021
468
±20.59
-13.04, +11.59
-98.46, +107.31
-51.96, +59.43
-22.87, +24.60
-5.15, +5.16
-25.15, +25.52
-29.05, +29.32
±14.29
-5.10, +5.15
-20.55, +20.87
-7.46, +7.54
-16.68, +17.81
-9.63, +9.82
-16.87, +17.92
-5.35, +5.37
Combined
Uncertainty (%)
Approach 2
Uncertainty
Uncertainty
The probability density functions resulting from the Monte Carlo assessment are shown below:
Figure A1 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Public Electricity and Heat Production - Liquid fuels in ENERGY sector,
2017
Figure A2 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Public Electricity and Heat Production - Solid fuels in ENERGY sector, 2017
Turkish GHG Inventory Report 1990-2021
469 469
Uncertainty
Figure A3 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Public Electricity and Heat Production- Gaseous fuels in ENERGY sector,
2017
Figure A4 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Cement Production in IPPU sector, 2018
470
Turkish GHG Inventory Report 1990-2021
470
Uncertainty
Figure A5 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Lime Production in IPPU sector, 2018
Figure A6 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Glass Production in IPPU sector, 2018
Turkish GHG Inventory Report 1990-2021
471 471
Uncertainty
Figure A7 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Ceramics in IPPU sector, 2018
Figure A8 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Other Uses of Soda Ash in IPPU sector, 2018
472
Turkish GHG Inventory Report 1990-2021
472
Uncertainty
Figure A9 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Non-Metallurgical Magnesia Production in IPPU sector, 2018
Figure A10 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Ammonia Production in IPPU sector, 2018
Turkish GHG Inventory Report 1990-2021
473 473
Uncertainty
Figure A11 Probability density function resulting from Monte Carlo analysis for N2O
emissions from Nitric Acid Production in IPPU sector, 2018
Figure A12 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Carpide Production in IPPU sector, 2018
474
Turkish GHG Inventory Report 1990-2021
474
Uncertainty
Figure A13 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Soda Ash Production in IPPU sector, 2018
Figure A14 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Petrochemical and Carbon Black Production in IPPU sector, 2018
Turkish GHG Inventory Report 1990-2021
475 475
Uncertainty
Figure A15 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Iron and Steel Production in IPPU sector, 2018
Figure A16 Probability density function resulting from Monte Carlo analysis for CH4
emissions from Iron and Steel Production in IPPU sector, 2018
476
Turkish GHG Inventory Report 1990-2021
476
Uncertainty
Figure A17 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Ferroalloys Production in IPPU sector, 2018
Figure A18 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Aluminum Production in IPPU sector, 2018
Turkish GHG Inventory Report 1990-2021
477 477
Uncertainty
Figure A19 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Lead Production in IPPU sector, 2018
Figure A20 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Lubricant Use in IPPU sector, 2018
478
Turkish GHG Inventory Report 1990-2021
478
Uncertainty
Figure A21 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Paraffin Wax Use in IPPU sector, 2018
Figure A22 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Urea Application in AGRICULTURE sector, 2017
Turkish GHG Inventory Report 1990-2021
479 479
Uncertainty
Figure A23 Probability density function resulting from Monte Carlo analysis for CH4
emissions from Rice Cultivation in AGRICULTURE sector, 2017
Figure A24 Probability density function resulting from Monte Carlo analysis for CH4
emissions from Managed SWDS in WASTE sector, 2017
480
Turkish GHG Inventory Report 1990-2021
480
Uncertainty
Figure A25 Probability density function resulting from Monte Carlo analysis for CH4
emissions from Unmanaged SWDS in WASTE sector, 2017
Figure A26 Probability density function resulting from Monte Carlo analysis for CH4
emissions from Biological Treatment of Solid Waste - Composting in WASTE sector, 2017
Turkish GHG Inventory Report 1990-2021
481 481
Uncertainty
Figure A27 Probability density function resulting from Monte Carlo analysis for N2O
emissions from Biological Treatment of Solid Waste - Composting in WASTE sector, 2017
Figure A28 Probability density function resulting from Monte Carlo analysis for CO2
emissions from Incineration and Open Burning Of Waste in WASTE sector, 2017
482
Turkish GHG Inventory Report 1990-2021
482
Uncertainty
Figure A29 Probability density function resulting from Monte Carlo analysis for CH4
emissions from Incineration and Open Burning Of Waste in WASTE sector, 2017
Figure A30 Probability density function resulting from Monte Carlo analysis for N2O
emissions from Incineration and Open Burning of Waste in WASTE sector, 2017
Turkish GHG Inventory Report 1990-2021
483 483
Uncertainty
Figure A31 Probability density function resulting from Monte Carlo analysis for CH4
emissions from Wastewater Treatment and Discharge- Industrial Wastewater in WASTE
sector, 2017
Figure A32 Probability density function resulting from Monte Carlo analysis for CH4
emissions from Wastewater Treatment and Discharge- Domestic Wastewater in WASTE
sector, 2017
484
Turkish GHG Inventory Report 1990-2021
484
Uncertainty
Figure A33 Probability density function resulting from Monte Carlo analysis for N2O
emissions from Wastewater Treatment and Discharge- Domestic Wastewater in WASTE
sector, 2017
Turkish GHG Inventory Report 1990-2021
485 485
Country Specific Carbon Content Determination and
Emission Factors
Annex 3: Country Specific Carbon Content Determination and
Emission Factors
In Türkiye we do not have ETS registry yet. Therefore, in order to calculate country specific EFs, we
lean on data obtained from a number of coal firing plants, BOTAŞ and some public university
laboratories. Those analyses are the basis of country specific Carbon Contents.
Natural gas
In order for carbon content of natural gas to be calculated, densities of gases included in it must be
known to convert volumetric compositions to mass fractions.
Volumetric fractions of gas concentrations were obtained through gas chromatography analysis from
Petroleum Pipeline Corporation (BOTAŞ). Using density of the gases and some stoichiometry carbon
mass amount coming from each gas was calculated and summed up to reach an overall carbon amount.
For gaseous fuels CO measured in the stack gas was used in order to calculate unoxidised carbon’s
mass percentage and then oxidation rate of the related fuel. In order to calculate the oxidation rate of
gaseous fuels (natural gas), CO concentration measured in the stack gas of the related plants were
obtained from the Ministry of Environment, Urbanization and Climate Change.
Turkish Lignite
Ultimate analysis results, which were obtained from coal firing plants, were used to calculate carbon
content of the related coal types. In the analysis results Carbon content together with, Hydrogen,
Sulphur, Oxygen moisture, ash, volatile substances contents are measured. Also net and gross calorific
values are provided in the same reports. Carbon contents and net calorific values (circulated figures in
the below analysis report) are used for calculating carbon content of Turkish lignite.
Oxidation rate of solid fuels was calculated by using the mass percentage of carbon in ash-slag analysis
reports which were obtained from coal firing plants.
Hard coal
Carbon contents and oxidation rates of hard coal is calculated in the same way as in Turkish Lignite.
Country specific carbon content and oxidation rates of hard coal calculated based on power plants coal
analysis are used for all 1.A categories.
486
Turkish GHG Inventory Report 1990-2021
486
Country Specific Carbon Content Determination and
Emission Factors
Coke oven coke
Country specific Carbon content of coke oven coke is calculated based on carbon content and net
calorific values provided by the integrated iron&steel facilities in Türkiye. There are 3 integrated
iron&steel facilities in Türkiye and there are coke production plants in all of them. Carbon contents of
all carbonaceous material used for iron and steel production is measured by all the facilities. Carbon
content of coke oven coke is also measured since it is used as reducing agent in pig iron production.
Annual average carbon content of coke oven coke as kg C/ton of coke and net calorific values are
compiled from integrated facilities. The mass of carbon is divided by net calorific values of coke oven
coke and the result is the carbon content as kg C/GJ of coke. Calculated country specific carbon content
is used for estimation of CO2 emissions from coke combustion of all other sectors using coke as a fuel.
Gas/diesel oil and Residual fuel oil
Carbon content of gas/diesel oil and residual fuel oil is calculated based on fuel analysis made by
Petroleum Research Centre at Middle East Technical University (METU) in Ankara. The Research Center
was founded by METU Petroleum Engineering Department and General Directorate of Petroleum Affairs
(under the Ministry of Energy and Natural Resources). The main objective of the Center is to make
research on the oil and gas exploration and production, refining and transportation and to conduct
projects on topics requested by public and private organizations.
Based on the fuel analysis of Petroleum Research Center, an example for calculation of carbon content
of gas diesel oil and residual fuel oil is given below.
Sample
A
Number of
Sample
B
C, normalized
(%)
C
NCV
kcal/kg
(average)
D
NCV GJ/kg
(average)
E
C mass/kg
fuel
F (C/100)
C content
kg C/GJ
G (F/E)
Diesel
639/06-1106
86.261
10233
0.0428435
0.86261
20.133975
Fuel Oil
255/06-330
86.611
9901
0,0414535
0.86611
20.893530
Source: METU, Petroleum Research Laboratory, 2006.
An example for oxidation rate for gas diesel oil and residual fuel oil;
Oxidation rate of gas/diesel oil and residual fuel oil is calculated based on stack gas analysis of oil fired
power plants. In stack gas analysis, CO percentage in stack gas is measured. Based on the inlet carbon
already provided in fuel analysis report and outlet C derived from stack gas analysis, oxidation rates are
calculated.
Turkish GHG Inventory Report 1990-2021
487 487
Country Specific Carbon Content Determination and
Emission Factors
An example calculation is given below.
Fuel oil density (kg/m3)
0.9757
CO (average v/v %)
3.25
C inlet (m/m) %
86.611
C (outlet v/v %) (*12/28)
1.39
C inlet (v/v) %
88.768
Oxidation rate, %: ((C inlet - C outlet)/C inlet)*100 = 98.43
Petroleum coke
Petroleum coke is used in mostly in cement factories. There are around 54 cement factories in Türkiye.
Availability of fuel analysis report is asked to the factories via official letters. Net calorific values are
available in most of the factories but a few of them has carbon content analysis. Averages of all available
data are used as country specific carbon content of petroleum coke.
488
Turkish GHG Inventory Report 1990-2021
488
Emission Factors
Emissions Factors
Emission Factors used for Energy Sector
NCV of Fuels
2021
Hard coal
26.03
Lignite
8.27
Asphaltite
19.51
Coke
24.94
BFG
729
Coke oven gas
4 181
BOF gas
1 520
Oil
43.96
Coal tar
37.25
Petroleum Coke
32.24
Fuel oil
39.39
Diesel oil
43.33
Gasoline
44.80
LPG
47.31
Refinery gas
48.15
Jet Kerosene
44.59
Kerosene
43.75
Naphtha
45.01
By products
40.19
Basic oil
42.00
White spirit
43.50
Bitumen
40.19
Other petroleum products
40.19
Natural gas
34.54
Wood
12.56
Crop and animal residue
11.19
Biofuels
36.05
Unit
TJ/kton
TJ/kton
TJ/kton
TJ/kton
Kcal/kg
Kcal/kg
Kcal/kg
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/kton
TJ/10^6m3
TJ/kton
TJ/kton
TJ/kton
(TJ/kt) = (1000 TOE)/(kt) * 41.868
(TJ/10^6m3) = (1000 TOE)/(10^6m3) * 41.868
Turkish GHG Inventory Report 1990-2021
489 489
Emission Factors
Years
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
490
Hard
Coal
93.37
101.38
101.35
100.54
99.12
102.17
102.50
103.34
102.81
93.39
95.52
99.28
96.27
100.90
90.34
94.23
88.71
88.52
93.35
96.03
98.56
95.10
96.65
96.18
93.15
92.38
85.32
94.50
93.25
96.89
91.76
93.64
Country Specific CO2 Emission Factor
Lignite
Coke
BFG
COG
114.16
114.01
113.85
113.70
113.54
113.39
113.23
113.08
112.92
112.77
110.05
110.58
111.30
112.00
112.72
113.50
114.18
113.62
112.51
111.39
110.26
109.48
109.29
109.09
107.63
107.63
107.41
107.24
108.88
106.62
104.75
104.08
110.29
110.29
110.29
110.29
110.29
110.29
110.29
110.29
110.29
110.29
110.29
110.29
110.29
110.70
110.62
112.25
110.29
111.97
110.29
111.58
109.79
110.05
111.01
112.45
110.71
110.38
108.37
112.22
108.08
108.48
110.70
108.77
258.85
258.85
258.85
258.85
258.85
258.85
258.85
258.85
255.17
255.17
260.85
261.55
261.55
261.55
261.55
256.64
261.55
264.06
257.53
259.33
257.31
257.81
256.94
252.27
251.92
258.70
265.09
264.12
268.30
285.82
260.32
255.95
40.46
40.46
40.46
40.46
40.46
40.46
40.46
40.46
40.25
40.27
40.27
40.90
40.60
41.51
41.76
43.40
40.88
41.41
40.91
41.85
41.22
39.36
40.05
42.12
42.03
40.78
39.02
37.45
37.35
38.87
39.74
42.30
Turkish GHG Inventory Report 1990-2021
BOF
Gas
176.53
176.53
176.53
176.53
176.53
176.53
176.53
176.53
176.53
176.53
176.53
176.53
176.53
176.53
176.53
176.53
176.53
176.53
176.53
175.60
179.97
174.71
174.81
176.39
173.73
175.09
182.31
190.08
194.38
194.80
196.53
195.64
(t/TJ)
Natural
Gas
55.61
55.61
55.61
55.61
55.61
55.61
55.61
55.61
55.61
55.61
55.61
55.61
55.61
55.65
55.61
55.60
55.61
55.62
55.62
55.68
55.74
56.31
55.66
55.66
55.68
55.75
55.39
55.62
55.27
53.67
55.67
55.43
Emission Factors
Default CO2 Emission Factors
Fuels
1990-2021
Sub bituminous coal
96.1
Coal tar
80.7
Crude oil
73.3
Petroleum Coke
97.4
Fuel Oil
77.0
Diesel Oil
72.3
Gasoline
69.3
LPG
63.1
Refinery gas
57.6
Jet kerosene
71.5
Kerosene
71.9
Naphtha
72.7
By products
73.3
Basic oil
73.3
White spirit
73.3
Bitumen
80.7
Other petroleum products
73.3
Navigation diesel oil
72.3
Navigation fuel
77.0
Wood
111.8
Biofuels and Waste
100.1
CH4 and N2O Emission Factors
Turkish GHG Inventory Report 1990-2021
491 491
Emission Factors
CH4 and N2O Emission Factors (cont’d)
492
Turkish GHG Inventory Report 1990-2021
492
Emission Factors
Emission factors used for IPPU
Category
Cement Production
CKD
EF
Lime Production
EF high calcium lime ((tonnes
CO2/tonne carbonate)
EF dolomitic lime (tonnes
CO2/tonne carbonate)
Soda (tonnes CO2/tonne
Glass
production/Ceramic carbonate)
s/Roof and Tiles/
Dolomit (tonnes CO2/tonne
Soda ash use
carbonate)
EF
1.02
0.52
0.69
Reference
IPCC Default
CS
CS
0.77
Default
0.41
IPCC Vol 2. Table 2.1. https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_2_Ch2_Mineral_Industry.pdf
IPCC Vol 2. Table 2.1. https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_2_Ch2_Mineral_Industry.pdf
IPCC Vol 2. Table 2.1. https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_2_Ch2_Mineral_Industry.pdf
IPCC Vol 2. Table 2.1. https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_2_Ch2_Mineral_Industry.pdf
BOTAŞ
BOTAŞ
BOTAŞ
Default
IPCC VOL 2. Table 3.3. https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_3_Ch3_Chemical_Industry.pdf
IPCC VOL 2. Table 3.3. https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_3_Ch3_Chemical_Industry.pdf
IPCC VOL 2. Table 3.8. https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_3_Ch3_Chemical_Industry.pdf
IPCC VOL 2. Table 3.8. https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_3_Ch3_Chemical_Industry.pdf
IPCC VOL 2. Equation 3.4.
https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_3_Ch3_Chemical_Industry.pdf
CS, Petkim
CS
PS, confidential
IPCC VOL 2. Table 4.5 https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_4_Ch4_Metal_Industry.pdf
PS
0.48
Kalker (tonnes CO2/tonne
carbonate)
0.44
Magnesia
Production
Magnesia (tonnes CO2/tonne
carbonate)
0.52
Ammonia
Production
Natural Gas NCV (kcal/sm3)
Natural Gas NCV (GJ/sm3)
Nat Gas. Car. Cont. (kgC/GJ)
Carbon Oxidation Factor
Middle pressure plant (kg
N2O/tonne nitric acid)
8453.7
0.0354
15.2
1
7
Nitric Acid
Production
with abatement technology(kg
N2O/tonne nitric acid)
2.5
Carpide (tonnes CO2/tonne
carbide produced)
1.09
Asetilen (tonnes CO2/tonne
carbide produced)
1.1
Soda Ash
Production
Soda ash (tonnes CO2/tonne
of Trona)
0.097
Petrochemicals
Iron and Steel
Production
Ferro chrome
production
Fuel gas
EAF
Integrated Plants
Aluminium
production
Net prebaked anode
consumption (ton/ ton
alüminyum)
Carbon content wt %
Carpide Production
Lead
production
Lubricant and
paraffin wax
use
0.67227
0.0712
1.3
0.412
98.83
0.2
Carbon content
20
Oxidation rate
0.2
PS
IPCC VOL 2. Table 4.21 https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_4_Ch4_Metal_Industry.pdf
IPCC VOL 2. Table 5.2 https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_5_Ch5_Non_Energy_Products.pdf
IPCC VOL 2. Equation 5.4 https://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volum
e3/V3_5_Ch5_Non_Energy_Products.pdf
Turkish GHG Inventory Report 1990-2021
493 493
Emission Factors
Emission factors/parameters used in the agriculture sector
3.A Enteric Fermentation
EF
(kg CH4/head/yr)
Method
Note
3.A.1 Cattle
Dairy Cattle
83.7
T2
Latest Inventory year figure
Non-Dairy Cattle
47.4
T2
Latest Inventory year figure
Domestic
5.0
T1
Table 10.10
Merino
6.5
T1
Table 10.10, value is derived as follows:
(developing EF + developed EF)/2
3.A.3 Swine
1.0
T1
Table 10.10
Buffalo
55.0
T1
Table 10.10
Camels
46.0
T1
Table 10.10
Goats
5.0
T1
Table 10.10
Horses
18.0
T1
Table 10.10
Mules and Asses
10.0
T1
Table 10.10
Poultry
NA
3.A.2 Sheep
3.A.4 Other livestock
All table references given above refer to the 2006 IPCC Guidelines Volume 4 except for EFs given for cattle.
3.B(a)
Manure Management
CH4 Emissions
EF
(kg CH4/head/yr)
Method
Note
3.A.1 Cattle
Dairy Cattle
a
T1
Table 5.17
Non-Dairy Cattle
a
T1
Table 5.17
Domestic
b
T1
Table 5.18
Merino
b
T1
Table 5.18
3.A.3 Swine
a
T1
Table 5.17
Buffalo
b
T1
Table 5.18
Camels
b
T1
Table 5.18
Goats
b
T1
Table 5.18
Horses
b
T1
Table 5.18
Mules and Asses
b
T1
Table 5.18
Poultry
b
T1
Table 5.18
3.A.2 Sheep
3.A.4 Other livestock
a
b
494
Given on Table 5.17 of this Inventory Report.
Given on Table 5.18 of this Inventory Report.
Turkish GHG Inventory Report 1990-2021
494
Emission Factors
Emission factors/parameters used in the agriculture sector (continued)
3.B(b)
Manure Management
Direct N2O Emissions
EF3
(kg N2O-N / kg N
excreted)
Method
Note
Liquid system
0.005
T1
Table 10.21
Solid storage
0.005
T1
Table 10.21
Dry lot
0.02
T1
Table 10.21
Pasture, range and paddock
-
T1
Reported under 3.D agricultural soils category
Burned for fuel or as waste
-
T1
Reported under the energy sector
Other (Poultry manure)
0.001
T1
Table 10.21
All table references given above refer to the 2006 IPCC Guidelines Volume 4.
3.B(b)
Manure Management
Indirect N2O Emissions
Value
Method
Note
All related manure
management systems
0.01
T1
Table 11.3, EF4
[kg N2O-N / (kg NH3-N + NOx-N volatilised)]
FracGASMS
***
T1
***Default values given on Table 10.22
FracLEACHMS
4.5%
T1
Mid-value between 3% and 6% given for drier
climates on page 10.56
All value, table and page references given above refer to the 2006 IPCC Guidelines Volume 4.
3.C Rice Cultivation
Value
EFc
1.30
SFw
Unit
Method
Note
T1
Baseline emission factor for all types of water
regimes, Table 5.11
1.00
T1
Scaling factor for continuously flooded water
regime, Table 5.12
SFw
0.60
T1
Scaling factor for intermittently flooded (single
aeration) water regime, Table 5.12
SFw
0.52
T1
Scaling factor for intermittently flooded
(multiple aeration) water regime, Table 5.12
SFp
1.00
T1
Scaling factor for non-flooded pre-season less
than 180 days, Table 5.13
SFp
0.68
T1
Scaling factor for non-flooded pre-season more
than 180 days, Table 5.13
SFp
1.90
T1
Scaling factor for flooded pre-season over 30
days, Table 5.13
kg CH4
/ha/ day
All table references given above refer to the 2006 IPCC Guidelines Volume 4.
Turkish GHG Inventory Report 1990-2021
495 495
Emission Factors
Emission factors/parameters used in the agriculture sector (continued)
3.D.a Agricultural Soils
Direct N2O Emissions
EF
3.D.a.1
Inorganic N fertilizers
0.01
3.D.a.2
Organic N fertilizers
0.01
3.D.a.3
Urine and dung deposited by
grazing animals
3.D.a.4
Unit
kg N2O‒N /
(kg N)
kg N2O‒N /
(kg N)
Note
**
kg N2O‒N /
(kg N)
**0.02 for cattle, buffalo, pigs, poultry
and 0.01 for sheep and other animals
Crop residues
0.01
kg N2O‒N /
(kg N)
0.003 is taken for flooded rice &
0.01 for crop residues except flooded rice
3.D.a.5
Loss/Gain of soil organic matter
0.01
kg N2O‒N /
(kg N)
Note that this particular source category is
currently reported as not occurring (NO).
3.D.a.6
Cultivation of organic soils
8
kg N2O‒N /
ha
EF2 CG, Temp for temperate organic crop
and grassland soils
-
All EF values given above refer to Table 11.1 of the 2006 IPCC Guidelines Volume 4. The method used for 3.D.a is T1.
3.D.b Agricultural Soils
Indirect N2O Emissions
Value
EF4
0.01
kg N2O-N / (kg NH3-N + NOx-N
volatilised)
EF5
0.0075
kg N2O-N /
(kg N leaching/runoff)
Leaching/runoff
FracGASF
0.10
kg NH3-N + NOx-N /
(kg N applied)
Volatilisation from synthetic
fertiliser
FracGASM
0.20
kg NH3-N + NOx-N /
(kg N applied or deporsited)
Volatilisation from all organic N
fertilisers applied, and dung and
urine deposited by grazing animals
FracLEACH-(H)
0.015
kg N / (kg N additions or
deposition by grazing animals)
Country-specific value*
Unit
Note
N volatilisation and re-deposition
All values given above refer to Table 11.3 of the 2006 IPCC Guidelines Volume 4 except for the FracLEACH-(H) value. The T1 method
was applied for 3.D.b.
* Calculations on the country-specific FracLEACH-(H) value of 0.015:
Equation 11.10 is given below;
N2O(L)−N = (FSN + FON + FPRP + FCR + FSOM) • FracLEACH −(H) • EF5
Where F=(Fsn+Fon+Fprp+Fcr+Fsom),
N2O(L)-N = F * FracLEACH-(H) * EF5
and
N2O(L) = N2O-N * (44/12)
Applying this equation for two different factors of FracLEACH-(H) would result in
for 95% of the total area according to the map given as
N2O(L)-N = F * 0.95 * FracLEACH-(H) * EF5 (where FracLEACH-(H) is 0.00)
and
for 5% of the total area according to the map given as
N2O(L)-N = F * 0.05 * FracLEACH-(H) * EF5 (where FracLEACH-(H) is 0.30)
Please note that FracLEACH-(H) (for 95% of the land area) equals 0.00 and
FracLEACH-(H) (for 5% of the land area) equals 0.30.
Finding a new weighted average rate for FracLEACH-(H) is as straightforward as follows:
F * FracLEACH-(H)new * EF5 = {[F *0.95] * FracLEACH-(H) * EF5} + {[F * 0.05] * FracLEACH-(H)* EF5}
F * FracLEACH-(H)new * EF5 = {[F *0.95] * 0.00 * EF5} + {[F * 0.05] * 0.30 * EF5}
F * FracLEACH-(H)new * EF5 = { 0.00 } + { [F * 0.05] * 0.30 * EF5}
F * FracLEACH-(H)new * EF5 = { F * 0.015 * EF5 }
FracLEACH-(H)new = 0.015
496
Turkish GHG Inventory Report 1990-2021
496
Emission Factors
Emission factors/parameters used in the agriculture sector (continued)
Gef
(g /kg)
3.F Field Burning of
agricultural residues CH4
N2O
Cf
CH4 and
N2O
Method
3.F.1.1 Wheat
2.7
0.07
0.9
T1
3.F.1.2 Barley
2.7
0.07
0.9
T1
3.F.1.3 Maize
2.7
0.07
0.8
T1
3.F.1.4 Rice
2.7
0.07
0.8
T1
Note
Cf value for wheat is used
All values given above refer to Table 2.5 for Gef and Table 2.6 for Cf of the 2006 IPCC Guidelines Volume 4.
EF
3.H Urea Application
(tonne of C/
tonne of urea)
Urea fertilisation
0.20
Method
T1
Note
Information given on page 11.32 of the
2006 IPCC Guidelines Volume 4.
Turkish GHG Inventory Report 1990-2021
497 497
Emission Factors
Emission factors/parameters used in the waste sector
Category
EF
AD Source
TurkStat's surveys and
database
Methane recovery facilities
5.A Solid waste disposal
Default values in IPCC 2006, Vol 5,
Chp 3
5.B Biological treatment of solid waste
5.B.1 Composting
5.B.1.a Municipal Solid Waste
CH4: 4, N2O: 0.24 (IPCC 2006, Vol 5,
Chp 4, Table 4.1
TurkStat's surveys and
database
Composting plants
5.C Incineration and open burning of waste CO2: OF= 0.58 for MSW (IPCC 2006,
5.C.2 Open Burning of Waste
Vol 5, Chp 5, Table 5.2)
5.C.2.1 Biogenic
CH4 & N2O: Defaults (IPCC 2006, Vol
5.C.2.1.a Municipal Solid Waste
5, Chp 5, Section 5.4.2 & Table 5.6)
TurkStat's surveys and
database
5.D Wastewater treatment and discharge
5.D.1 Domestic Wastewater
Default values (IPCC 2006, Vol 5,
Chp 6, Table 6.3 & 6.11)
CS BOD values for TOW calculation
(as provided below)
5.D.2 Industrial Wastewater
Default values (IPCC 2006, Vol 5,
Chp 6, Table 6.8 & 6.9)
Country-specific BOD values
BOD (g/person/day)
TurkStat's surveys and
database
Methane recovery facilities
FAOSTAT
TurkStat's surveys and
database
I
Country-specific per capita BOD for wastewater collected by
sewers
Correction factor for additional industrial BOD
discharged into sewers
53
1
BOD (g/person/day)
BOD (g/person/day)
Country-specific per capita BOD for receiving bodies
Country-specific per capita BOD for sludge
removed
25
28
Country specific values for degrees of treatment utilization (T) by income groups
Treatment or discharge system or pathway
Rural
Urban
To
To
To
To
To
To
To
To
sea, river and lake
aerobic plant, not well managed
septic systems
sea, river and lake
aerobic plant, well managed
aerobic plant, not well managed
anaerobic digester for sludge
septic systems
Total
498
T (%)
0.43
0.44
10.72
15.43
44.01
1.82
20.83
6.31
100
Turkish GHG Inventory Report 1990-2021
498
National Energy Balance Sheets, 2021
Annex 4: National Energy Balance Sheets, 2021
Distribution of Energy Supply
Domestic Production (+)
Hard Coal
Lignite
Asphaltite
736
16.428
696
Import (+)
22.915
Export (-)
183
6
Coke
Derivative
Gases
BFG
COG
BOF Gas
Coal Tar
Oil
Oil Products
Petroleum
Coke
Fuel Oil
19.000
1.584
1.572
8.022
11
1.247
3.614
755
6
11
113
32.989
3.380
Bunkers (-)
-24
251
11
23.444
16.672
707
744
0
0
0
-4
-22
0
93
0
0
0
-16.534
-11.775
-562
2.667
-11.740
-11.468
-562
Main activity producer plants
-10.412
-11.370
-562
Autoproducers
-1.327
-98
-332
-293
Stock Change (+/-)
Primary Energy Supply
Statistical Difference (+/-)-Transformation Sector
4
Electricity and Heat Production
Heat Production
-4.259
Coke ovens
2.667
Blast Furnaces
-362
144
-10
-211
0
-95
36.241
7.742
1.563
-173
0
6
0
642
713
-154
114
-36.241
36.491
1.348
467
106
325
36
-714
-429
-198
-87
-714
-429
-198
-87
-144
-64
-26
-54
794
794
-285
1.519
1.313
-988
-714
-245
-29
-77
-36
-36
39.731
-315
-2.919
19
0
44.233
2.912
-5
36
13
0
43.591
2.198
149
36
13
0
2.647
2.198
27
130
21
33
18
2
0
12
2
-15
Total final energy consumption
6.909
4.897
145
3.410
467
106
325
36
Sectors Total
6.913
4.919
145
3.317
467
106
325
4.878
2.544
24
3.317
467
106
325
0
0
327
429
327
412
Food(10)
-30
-77
-35.926
-204
Manufacture of Food, beverage, tobacco products 10,11,12)
-207
206
Own use and loses
Industry Consumption
169
-107
114
Petroleum Refineries
Mining and Quarrying (07,08,09)
287
13
1.348
1
Beverages(11)
1.327
-1.016
7
3
0
0
Tobacco (12)
17
33
4
4
291
560
0
12
8
Textile13)
152
525
Clothing (14)
138
35
Sugar(10.81)
Manufacture of textile and leather (13,14,15)
Leather and related (15)
0
1
11
8
1
0
0
Manufacture of wood products (16)
10
0
10
Manufacture of paper (17,18)
32
138
5
Manufacture of chemicals and petro chemicals (20,21,22)
342
144
0
18
2
Chemicals(20)
339
97
0
13
1
Fertilizer (20)
0
Pharmaceutical (21)
3
0
2
Rubberi plastics (22)
0
47
3
2.849
1.252
36
163
2.813
1.089
1.026
18
Manufacture of non-metalic minerals (23)
Cement (23)
Basic Metal Industry (24,25)
0
1
2
2
2.308
1
0
2.173
9
1
Glass (23)
Ceramics (23)
0
2
2
2
49
39
2.258
2.135
9
3.284
466
106
323
36
13
27
0
466
106
323
36
13
15
0
7
0
Iron and steel (24)
992
3.279
Non-ferrous metals (24)
33
5
0
18
5
Manufacture of machine, electrical and electronical products (26,27,28)
0
2
4
0
0
1
5
0
2
0
Fabricated metal products 25)
Manufacture of transportation Equipment(29,30)
Motorized land vehicles 29)
0
1
Other transportation vehicles (30)
2
Furniture and other production(31)
0
9
Construction(41,42,43)
1
14
24
Otherr industry
TRANSPORT
0
0
0
0
88
0
0
0
0
0
0
0
29.940
Rail
105
Domestic Navigation
368
Domestic Aviation
954
0
19
19
Pipelines
28.513
Road
Other Sectors
Residential
Commercial and Public services
2.035
2.374
121
1.963
1.638
121
72
736
0
0
0
0
0
0
0
0
102
437
458
102
3.193
Agriculture and farming
Non Energy Use
4.087
0
0
0
0
0
0
0
0
0
0
6.918
0
0
1.962
Petrochemicals Feedstock
Turkish GHG Inventory Report 1990-2021
499 499
National Energy Balance Sheets, 2021
Gas
Gasoline
Diesel Oil
Distribution of Energy Supply
LPG
Refinery Gas
Jet Kerosene
Kerosene
Naphta
By Products
Base oil
White Spirit
Bitumen
Others
Domestic Production (+)
Import (+)
11.328
5
3.507
222
184
145
343
35
3
72
Export (-)
2.627
1.791
245
51
159
852
228
1
732
80
Bunkers (-)
313
Stock Change (+/-)
221
0
21
-8
41
0
-25
27
19
17
18
35
8.609
-1.785
3.283
-8
-2.568
0
1
-680
134
51
-711
27
0
0
5
0
0
0
77
0
0
0
0
0
17.282
4.842
1.146
8
3.521
2
2.038
1.307
140
2
1.958
2.730
17.946
4.935
1.146
1.332
3.521
2
2.038
1.307
140
2
1.958
2.730
-487
-93
Total final energy consumption
25.891
3.057
4.428
0
954
2
2.039
626
273
53
1.246
2.757
Sectors Total
25.891
3.057
4.423
0
954
2
1.962
626
273
53
1.246
2.757
311
1
110
0
0
0
0
0
0
0
0
0
109
0
0
Manufacture of Food, beverage, tobacco products 10,11,12)7
0
2
Food(10)
7
0
1
Beverages(11)
1
0
1
Tobacco (12)
0
Sugar(10.81)
0
0
954
0
0
0
0
0
0
0
2
0
0
0
0
0
0
1.962
626
273
53
1.246
2.757
Primary Energy Supply
Statistical Difference (+/-)-Transformation Sector
Electricity and Heat Production4
2.780
-178
-178
Main activity producer plants
Autoproducers
Heat Production
Coke ovens
Blast Furnaces
Petroleum Refineries
Own use and loses
Industry Consumption
Mining and Quarrying (07,08,09)
Manufacture of textile and leather (13,14,15)
-1.324
3
0
1
Textile13)
2
0
1
Clothing (14)
1
0
0
Leather and related (15)
0
0
Manufacture of wood products (16)
9
Manufacture of paper (17,18)
2
0
0
Manufacture of chemicals and petro chemicals (20,21,22)
6
0
9
Chemicals(20)
4
0
8
Fertilizer (20)
1
Pharmaceutical (21)
0
0
0
Rubberi plastics (22)
2
0
1
120
0
6
0
0
1
0
Manufacture of non-metalic minerals (23)
Glass (23)
Ceramics (23)
Cement (23)
Basic Metal Industry (24,25)
0
10
0
109
0
5
25
0
2
15
0
0
Non-ferrous metals (24)
7
0
0
Fabricated metal products 25)
3
0
2
Manufacture of machine, electrical and electronical products2 (26,27,28)0
2
Manufacture of transportation Equipment(29,30)
Iron and steel (24)
0
4
0
0
Motorized land vehicles 29)
2
0
0
Other transportation vehicles (30)
2
0
0
Furniture and other production(31)
9
0
0
Construction(41,42,43)
14
Otherr industry
88
TRANSPORT
22.388
Rail
105
Domestic Navigation
348
3.056
3.523
954
Domestic Aviation
Pipelines
Road
Other Sectors
21.934
3.056
3.193
0
790
0
0
435
Residential
Agriculture and farming
Non Energy Use
Petrochemicals Feedstock
2
356
Commercial and Public services
500
3.523
3.193
0
0
0
0
0
0
1.962
Turkish GHG Inventory Report 1990-2021
500
National Energy Balance Sheets, 2021
Distribution of Energy Supply
Domestic Production (+)
Nat. Gas
Biofuels and Waste
Wood
Crop and animal
residue
Biofuels
Hydro
Wind
342
4.099
1.191
2.678
229
4.810
2.704
Electricty
Other Heat
Jeothermal
Solar
Total
11.234
2.059
46.720
Import (+)
48.431
201
124.296
Export (-)
316
360
9.012
3.380
Bunkers (-)
774
Stock Change (+/-)
807
49.231
4.099
1.191
2.678
229
4.810
2.704
-159
0
11.234
2.059
159.432
0
0
0
0
0
0
0
0
0
0
0
715
-19.526
-1.264
0
-1.264
0
-4.810 -2.704
24.607
3.977
-9.280
-1.199
-35.573
-17.394
-1.262
-1.262
-4.810 -2.704
28.786
2.065
-9.280
-1.199
-30.566
Main activity producer plants
-14.408
-1.243
-1.243
-4.806 -2.694
26.197
1.495
-9.280
-913
-28.204
Autoproducers
-2.986
-19
-19
-286
-2.362
-1.525
-1
-1
Primary Energy Supply
Statistical Difference (+/-)-Transformation Sector
4
Electricity and Heat Production
Heat Production
-3
-10
2.589
570
2.265
-66
-684
Coke ovens
1.519
Blast Furnaces
Petroleum Refineries
-558
-208
Own use and loses
-49
-3.971
-353
2.686
-8.462
Total final energy consumption
29.705
2.835
1.191
1.415
229
0
0
24.447
3.977
1.954
860
123.859
Sectors Total
29.705
2.835
1.191
1.415
229
0
0
24.447
3.977
1.954
860
123.144
10.824
1.077
0
1.077
0
0
0
11.481
3.914
0
301
41.488
208
41
543
Industry Consumption
164
Mining and Quarrying (07,08,09)
Manufacture of Food, beverage, tobacco products 10,11,12)
Food(10)
1.267
83
83
860
550
3.567
1.187
83
83
724
550
3.295
Beverages(11)
42
48
Tobacco (12)
8
22
29
Sugar(10.81)
31
0
0
67
152
1.366
5
5
1.692
118
4.042
1.128
5
5
1.403
118
3.340
228
0
0
248
Manufacture of textile and leather (13,14,15)
Textile13)
Clothing (14)
Leather and related (15)
10
61
Manufacture of wood products (16)
91
651
40
367
367
233
51
95
776
1.004
230
7
7
365
228
2.695
3
3
1.399
357
4.959
Chemicals(20)
1.619
2
2
628
338
3.036
Fertilizer (20)
Manufacture of paper (17,18)
Manufacture of chemicals and petro chemicals (20,21,22)
842
62
Pharmaceutical (21)
60
60
Rubberi plastics (22)
174
1
1
649
19
893
2.056
606
606
1.284
64
10.420
Manufacture of non-metalic minerals (23)
Glass (23)
Ceramics (23)
Cement (23)
Basic Metal Industry (24,25)
Iron and steel (24)
905
125
794
181
976
1.007
218
1.473
255
606
606
885
64
7.972
2.060
2
2
3.107
341
10.342
1.604
1
1
2.466
285
9.121
437
55
835
Non-ferrous metals (24)
298
Fabricated metal products 25)
157
1
1
204
2
2
242
6
393
272
0
0
264
9
551
246
0
0
216
9
474
25
0
0
48
77
Furniture and other production(31)
39
2
2
64
115
Construction(41,42,43)
325
381
0
Otherr industry
152
1.383
2.106
135
0
Manufacture of machine, electrical and electronical products (26,27,28)
138
Manufacture of transportation Equipment(29,30)
Motorized land vehicles 29)
Other transportation vehicles (30)
TRANSPORT
259
229
0
0
229
0
0
386
722
0
301
4.053
0
30.562
108
Rail
213
368
Domestic Navigation
954
Domestic Aviation
Pipelines
192
Road
66
229
17.823
1.528
1.191
337
13.760
1.528
1.191
337
Other Sectors
Residential
Commercial and Public services
Agriculture and farming
Non Energy Use
27
229
0
28.809
0
0
12.832
6.408
125
1.149
0
0
0
63
5.275
3.938
799
219
0
0
0
0
63
0
1.954
559
43.377
853
559
26.134
475
12.149
627
5.093
0
0
7.717
1.962
Petrochemicals Feedstock
Energy balance sheets for 1972-2021 are available on the MENR website (https://www.eigm.gov.tr/trTR/Denge-Tablolari/Denge-Tablolari).
Turkish GHG Inventory Report 1990-2021
501 501
Completeness
Annex 5: Completeness
Table A8.1 Completeness, Sources and sinks not estimated ("NE")
GHG
502
Sector
Source/sink category
CH4
Energy
CO2
Agriculture
1.B Fugitive Emissions from Fuels/1.B.1 Solid Fuels/1.B.1.b Solid
Fuel Transformation
CO2
Agriculture
CO2
Energy
CO2
Energy
CO2
Energy
CO2
Energy
CO2
Energy
CO2
Energy
CO2
Energy
N2O
Agriculture
N2O
Energy
N2O
Energy
N2O
Industrial Processes and
Product Use
N2O
LULUCF
no gas
LULUCF
3.G Liming/3.G.1 Limestone CaCO3
3.G Liming/3.G.2 Dolomite CaMg(CO3)2
1.B Fugitive Emissions from Fuels/1.B.1 Solid Fuels/1.B.1.a Coal
Mining and Handling/1.B.1.a.1 Underground Mines/1.B.1.a.1.i
Mining Activities
1.B Fugitive Emissions from Fuels/1.B.1 Solid Fuels/1.B.1.a Coal
Mining and Handling/1.B.1.a.1 Underground Mines/1.B.1.a.1.ii
Post-Mining Activities
1.B Fugitive Emissions from Fuels/1.B.1 Solid Fuels/1.B.1.a Coal
Mining and Handling/1.B.1.a.1 Underground Mines/1.B.1.a.1.iii
Abandoned Underground Mines
1.B Fugitive Emissions from Fuels/1.B.1 Solid Fuels/1.B.1.a Coal
Mining and Handling/1.B.1.a.2 Surface Mines/1.B.1.a.2.i Mining
Activities
1.B Fugitive Emissions from Fuels/1.B.1 Solid Fuels/1.B.1.a Coal
Mining and Handling/1.B.1.a.2 Surface Mines/1.B.1.a.2.ii PostMining Activities
1.B Fugitive Emissions from Fuels/1.B.1 Solid Fuels/1.B.1.b Solid
Fuel Transformation
1.C CO2 Transport and Storage/Injection and Storage/Injection
3.1 Livestock/3.B Manure Management/3.B.2 N2O and NMVOC
Emissions/3.B.2.5 Indirect N2O Emissions
1.B Fugitive Emissions from Fuels/1.B.1 Solid Fuels/1.B.1.a Coal
Mining and Handling
1.B Fugitive Emissions from Fuels/1.B.1 Solid Fuels/1.B.1.b Solid
Fuel Transformation
2.G Other Product Manufacture and Use/2.G.3 N2O from Product
Uses/2.G.3.a Medical Applications
4.F Other Land/4(III) Direct N2O Emissions from N
Mineralization/Immobilization
4.F Other Land
4.D Wetlands/4.D.2 Land Converted to Wetlands/Carbon stock
change/4.D.2.2 Land Converted to Flooded Land/4.D.2.2.2
Cropland converted to flooded land/Carbon stock change in living
biomass
Turkish GHG Inventory Report 1990-2021
502
Completeness
Table A8.2 Completeness, Sources and sinks reported elsewhere ("IE")
GHG
Source/sink category
Explanation
CH4
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i Cars
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i
Cars/Biomass
Included under "1.A.3.e Other
Transportation"
CH4
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i Cars
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i
Cars/Diesel Oil
Included under "1.A.3.e Other
Transportation"
CH4
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i Cars
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i
Cars/Gasoline
Included under "1.A.3.e Other
Transportation"
CH4
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i Cars
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i
Cars/Liquefied Petroleum Gases (LPG)
Included under "1.A.3.e Other
Transportation"
CH4
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks/Gasoline
Included under "1.A.3.e Other
Transportation"
CH4
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks/Biomass
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks
Included under "1.A.3.e Other
Transportation"
CH4
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks/Diesel Oil
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks
Included under "1.A.3.e Other
Transportation"
CH4
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iii Heavy
duty trucks and buses
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iii Heavy
duty trucks and buses/Biomass
Included under "1.A.3.e Other
Transportation"
CH4
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iii Heavy
duty trucks and buses/Diesel Oil
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iii Heavy
duty trucks and buses
Included under "1.A.3.e Other
Transportation"
Turkish GHG Inventory Report 1990-2021
503 503
Completeness
Table A8.2 Completeness, Sources and sinks reported elsewhere ("IE")(Cont’d)
GHG
Source/sink category
Explanation
CH4
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles/Gasoline
Included under "1.A.3.e Other
Transportation"
CH4
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles/Biomass
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles
Included under "1.A.3.e Other
Transportation"
CH4
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles/Diesel Oil
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles
Included under "1.A.3.e Other
Transportation"
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
504
1.AA Fuel Combustion - Sectoral approach/1.A.4 Other
Sectors/1.A.4.c Agriculture/Forestry/Fishing/1.A.4.c.iii
Fishing
1.AA Fuel Combustion - Sectoral approach/1.A.4 Other
Sectors/1.A.4.c Agriculture/Forestry/Fishing/1.A.4.c.iii
Fishing/Gas/Diesel Oil
4.B Cropland/4.B.1 Cropland Remaining Cropland/4(V)
Biomass Burning/Wildfires
4.B Cropland/4.B.2 Land Converted to Cropland/4(V)
Biomass Burning/Wildfires
4.E Settlements/4.E.1 Settlements Remaining
Settlements
4.F Other Land/4.F.2 Land Converted to Other Land
Included under 1.A.4.c.i
Report in "agriculture sector"
Report in "agriculture sector"
included in "agriculture sector"
included in "agriculture sector"
5.C Incineration and Open Burning of Waste/5.C.1 Waste Emissions from 5.C.1.1.b Clinical Waste are
Incineration/5.C.1.1 Biogenic/5.C.1.1.b Other (please
included in 1.A.1.a
specify)/Clinical Waste
5.C Incineration and Open Burning of Waste/5.C.1 Waste Emissions from 5.C.1.1.b Industrial Solid
Wastes are included in 1.A.1.a, 1.A.2.c and
Incineration/5.C.1.1 Biogenic/5.C.1.1.b Other (please
1.A.2.g
specify)/Industrial Solid Wastes
5.C Incineration and Open Burning of Waste/5.C.1 Waste Emissions from 5.C.1.2.b Clinical Waste are
Incineration/5.C.1.2 Non-biogenic/5.C.1.2.b Other
included in 1.A.1.a
(please specify)/Clinical Waste
5.C Incineration and Open Burning of Waste/5.C.1 Waste Emissions from 5.C.1.2.b Industrial Solid
Wastes are included in 1.A.1.a, 1.A.2.c and
Incineration/5.C.1.2 Non-biogenic/5.C.1.2.b Other
1.A.2.g
(please specify)/Industrial Solid Wastes
CO2
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i Cars
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i
Cars/Biomass
Included under "1.A.3.e Other
Transportation"
CO2
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i Cars
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i
Cars/Diesel Oil
Included under "1.A.3.e Other
Transportation"
Turkish GHG Inventory Report 1990-2021
504
Completeness
Table A8.2 Completeness, Sources and sinks reported elsewhere ("IE")(Cont’d)
GHG
Source/sink category
Explanation
CO2
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i Cars
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i
Cars/Gasoline
Included under "1.A.3.e Other
Transportation"
CO2
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i Cars
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i
Cars/Liquefied Petroleum Gases (LPG)
Included under "1.A.3.e Other
Transportation"
CO2
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks/Gasoline
Included under "1.A.3.e Other
Transportation"
CO2
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks/Biomass
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks
Included under "1.A.3.e Other
Transportation"
CO2
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks/Diesel Oil
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks
Included under "1.A.3.e Other
Transportation"
CO2
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iii Heavy
duty trucks and buses/Biomass
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iii Heavy
duty trucks and buses
Included under "1.A.3.e Other
Transportation"
CO2
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iii Heavy
duty trucks and buses/Diesel Oil
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iii Heavy
duty trucks and buses
Included under "1.A.3.e Other
Transportation"
CO2
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles/Gasoline
Included under "1.A.3.e Other
Transportation"
CO2
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles/Biomass
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles
Included under "1.A.3.e Other
Transportation"
Turkish GHG Inventory Report 1990-2021
505 505
Completeness
Table A8.2 Completeness, Sources and sinks reported elsewhere ("IE")(Cont’d)
GHG
Source/sink category
Explanation
CO2
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles/Diesel Oil
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles
Included under "1.A.3.e Other
Transportation"
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
CO2
HFC-134a
506
1.AA Fuel Combustion - Sectoral approach/1.A.4 Other
Sectors/1.A.4.c Agriculture/Forestry/Fishing/1.A.4.c.iii
Fishing
Included under 1.A.4.c.i
1.AA Fuel Combustion - Sectoral approach/1.A.4 Other
Sectors/1.A.4.c Agriculture/Forestry/Fishing/1.A.4.c.iii
Fishing/Gas/Diesel Oil
1.AD Feedstocks, reductants and other non-energy use of Included under 2D
fuels/Liquid Fuels/Lubricants
2.B Chemical Industry/2.B.8 Petrochemical and Carbon
Included in 2.B.8.g
Black Production/2.B.8.b Ethylene
2.B Chemical Industry/2.B.8 Petrochemical and Carbon
Black Production/2.B.8.c Ethylene Dichloride and Vinyl
Chloride Monomer
2.B Chemical Industry/2.B.8 Petrochemical and Carbon
Black Production/2.B.8.e Acrylonitrile
2.C Metal Industry/2.C.1 Iron and Steel
Production/2.C.1.b Pig Iron
4.B Cropland/4.B.1 Cropland Remaining Cropland/4(V)
Biomass Burning/Wildfires
4.B Cropland/4.B.2 Land Converted to Cropland/4(V)
Biomass Burning/Wildfires
Included in 2.B.8.g
Included in 2.B.8.g
CO2 emissions from pig iron production is
included in emissions from steel production
Report in "agriculture sector"
Report in "agriculture sector"
5.C Incineration and Open Burning of Waste/5.C.1 Waste Emissions from 5.C.1.1.b Clinical Waste are
Incineration/5.C.1.1 Biogenic/5.C.1.1.b Other (please
included in 1.A.1.a
specify)/Clinical Waste
5.C Incineration and Open Burning of Waste/5.C.1 Waste Emissions from 5.C.1.1.b Industrial Solid
Wastes are included in 1.A.1.a, 1.A.2.c and
Incineration/5.C.1.1 Biogenic/5.C.1.1.b Other (please
1.A.2.g
specify)/Industrial Solid Wastes
5.C Incineration and Open Burning of Waste/5.C.1 Waste Emissions from 5.C.1.2.b Clinical Waste are
Incineration/5.C.1.2 Non-biogenic/5.C.1.2.b Other
included in 1.A.1.a
(please specify)/Clinical Waste
5.C Incineration and Open Burning of Waste/5.C.1 Waste Emissions from 5.C.1.2.b Industrial Solid
Wastes are included in 1.A.1.a, 1.A.2.c and
Incineration/5.C.1.2 Non-biogenic/5.C.1.2.b Other
1.A.2.g
(please specify)/Industrial Solid Wastes
All emissions caused by HFC-134a is given in
2.F Product Uses as Substitutes for ODS/2.F.6 Other
this section due to lack of disaggregated data.
Emission estimates are made by tier 1 and
Applications/2.F.6.a Emissive/HFC-134a
default emission factor.
Turkish GHG Inventory Report 1990-2021
506
Completeness
Table A8.2 Completeness, Sources and sinks reported elsewhere ("IE")(Cont’d)
GHG
Source/sink category
Explanation
N2O
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i Cars
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i
Cars/Biomass
Included under "1.A.3.e Other
Transportation"
N2O
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i Cars
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i
Cars/Diesel Oil
Included under "1.A.3.e Other
Transportation"
N2O
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i Cars
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.i
Cars/Liquefied Petroleum Gases (LPG)
Included under "1.A.3.e Other
Transportation"
N2O
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks/Gasoline
Included under "1.A.3.e Other
Transportation"
N2O
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks/Biomass
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.ii Light
duty trucks
Included under "1.A.3.e Other
Transportation"
N2O
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iii Heavy
duty trucks and buses
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iii Heavy
duty trucks and buses/Biomass
Included under "1.A.3.e Other
Transportation"
N2O
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles/Gasoline
Included under "1.A.3.e Other
Transportation"
N2O
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles/Biomass
1.AA Fuel Combustion - Sectoral approach/1.A.3
Transport/1.A.3.b Road Transportation/1.A.3.b.iv
Motorcycles
Included under "1.A.3.e Other
Transportation"
N2O
1.AA Fuel Combustion - Sectoral approach/1.A.4 Other
Sectors/1.A.4.c Agriculture/Forestry/Fishing/1.A.4.c.iii
Fishing
1.AA Fuel Combustion - Sectoral approach/1.A.4 Other
Sectors/1.A.4.c Agriculture/Forestry/Fishing/1.A.4.c.iii
Fishing/Gas/Diesel Oil
Included under 1.A.4.c.i
Turkish GHG Inventory Report 1990-2021
507 507
Completeness
Table A8.2 Completeness, Sources and sinks reported elsewhere ("IE")(Cont’d)
GHG
N2O
N2O
N2O
N2O
N2O
N2O
N2O
4.A Forest Land/4.A.2 Land Converted to Forest
Land/4(I) Direct N2O Emissions from N Inputs to
Managed Soils/Organic N Fertilizers
4.B Cropland/4.B.1 Cropland Remaining Cropland/4(V)
Biomass Burning/Wildfires
4.B Cropland/4.B.2 Land Converted to Cropland/4(V)
Biomass Burning/Wildfires
Explanation
No data available
Direct N2O Emissions from N Inputs to
Managed Soils in Forest Land is included in
the Agriculture Sector
No data available
Direct N2O Emissions from N Inputs to
Managed Soils in Forest Land is included in
the Agriculture Sector
Direct N2O Emissions from N Inputs to
Managed Soils in Forest Land is included in
the Agriculture Sector
Report in "agriculture sector"
Report in "agriculture sector"
N2O
4.E Settlements/4.E.1 Settlements Remaining
Settlements/4(I) Direct N2O Emissions from N Inputs to
Managed Soils/Inorganic N Fertilizers
i.e. included in "agriculture sector"
N2O
4.E Settlements/4.E.1 Settlements Remaining
Settlements/4(I) Direct N2O Emissions from N Inputs to
Managed Soils/Organic N Fertilizers
i.e. included in "agriculture sector"
N2O
4.E Settlements/4.E.2 Land Converted to
Settlements/4(I) Direct N2O Emissions from N Inputs to
Managed Soils/Inorganic N Fertilizers
i.e. included in "agriculture sector"
N2O
N2O
N2O
N2O
N2O
N2O
N2O
SF6
SF6
508
Source/sink category
4(IV) Indirect N2O Emissions from Managed
Soils/Atmospheric Deposition
4.A Forest Land/4.A.1 Forest Land Remaining Forest
Land/4(I) Direct N2O Emissions from N Inputs to
Managed Soils/Inorganic N Fertilizers
4.A Forest Land/4.A.1 Forest Land Remaining Forest
Land/4(I) Direct N2O Emissions from N Inputs to
Managed Soils/Organic N Fertilizers
4.A Forest Land/4.A.2 Land Converted to Forest
Land/4(I) Direct N2O Emissions from N Inputs to
Managed Soils/Inorganic N Fertilizers
4.E Settlements/4.E.2 Land Converted to
Settlements/4(I) Direct N2O Emissions from N Inputs to
Managed Soils/Organic N Fertilizers
4.F Other Land/4.F.2 Land Converted to Other Land
i.e. included in "agriculture sector"
included in "agriculture sector"
5.C Incineration and Open Burning of Waste/5.C.1 Waste Emissions from 5.C.1.1.b Clinical Waste are
Incineration/5.C.1.1 Biogenic/5.C.1.1.b Other (please
included in 1.A.1.a
specify)/Clinical Waste
5.C Incineration and Open Burning of Waste/5.C.1 Waste Emissions from 5.C.1.1.b Industrial Solid
Wastes are included in 1.A.1.a, 1.A.2.c and
Incineration/5.C.1.1 Biogenic/5.C.1.1.b Other (please
1.A.2.g
specify)/Industrial Solid Wastes
5.C Incineration and Open Burning of Waste/5.C.1 Waste Emissions from 5.C.1.2.b Clinical Waste are
Incineration/5.C.1.2 Non-biogenic/5.C.1.2.b Other
included in 1.A.1.a
(please specify)/Clinical Waste
5.C Incineration and Open Burning of Waste/5.C.1 Waste Emissions from 5.C.1.2.b Industrial Solid
Wastes are included in 1.A.1.a, 1.A.2.c and
Incineration/5.C.1.2 Non-biogenic/5.C.1.2.b Other
1.A.2.g
(please specify)/Industrial Solid Wastes
5.D Wastewater Treatment and Discharge/5.D.2
Industrial Wastewater
2.G Other Product Manufacture and Use/2.G.1 Electrical
Equipment/SF6
2.G Other Product Manufacture and Use/2.G.1 Electrical
Equipment/SF6
Emissions from 5.D.2 are included in 5.D.1
Due to lack of data, NE is entered
Turkish GHG Inventory Report 1990-2021
508
References
References
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Forestry Service, Petawawa National Forestry Institute, Chalk River, Ontario. Information Report PI-X23.
Alemdağ, I.S., 1984. Total Tree and Merchantable Stem Biomass Equations For Ontario Hardwoods
Agriculture Canada, Ministry of State for Forestry, Petawawa National Forestry Institute, Chalk River
ON. Information Report PI-X-046.
Asan, Ü., 1999. Climate Change, Carbon Sinks and the Forests of Turkey. Proceedings of the
International Conference on Tropical Forests and Climate Change: Status, Issues and Challenges
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