Air Pollution Modelling

 Lahore, Gujranwala, and Okara are the most polluted city based on PM2.5  Jhang, Multan, and Vehari are the most polluted cities based on AOD  Aerosols, nighttime lights, population, cropland, and fire show same spatial patterns  Pakistan's entire population is exposed to long-term PMx (x = 1, 2.5, & 10)  Pakistan's air quality is mainly affected by local anthropogenic sources Highlights (for review) 2

The qualifying scientific work (research thesis) as a manuscript for the technical sciences degree in the specialty 21.06.01 "Environmental safety." –Kyiv National University of Construction and Architecture of the Ministry of Education and Science of Ukraine. - Kyiv, 2021.

The main content of the dissertation work.

Atmospheric air pollution in urban areas due to the increase in mobile motor vehicle pollution sources running on gasoline and diesel fuel has become significant in recent years.

Recently, in large industrial cities of the world and, in particular, Ukraine, as a result of air pollution, such a negative phenomenon as the formation of photochemical smog has become more frequent. The main factors and mechanisms of smog formation, including over the city of Kyiv, studied to date insufficiently. And although the mechanism of smog formation, which was considered in many foreign authors' works, is identical to the air of large cities, the indicator of urban photochemical pollution is chosen in each case. It depends on many factors, especially weather conditions, types of pollutants, and more.

For Kyiv, such an indicator can be the concentration of formaldehyde as a product of oxidation of hydrocarbons from the emission of exhaust gases from various automobile engines and natural factors (hydrocarbons of plant origin). Given the annual growth of road transport on the roads of major cities of Ukraine, including Kyiv, the correlation between photochemical smog over road overpasses (especially at two or more levels) and at busy intersections and the number of vehicles, is the extremely relevant and timely scientific and practical task of assessing and forecasting the concentration of secondary air pollution by formaldehyde in cities transport.

These existing solutions' capabilities allow obtaining relative estimates of the "contribution" of mobile sources (including vehicles) in total emissions into the atmosphere. Also, with the help of direct measurements to solve the problem of identifying emissions from road overpasses and large intersections, where vehicles move at low speeds and stand in the so-called "traffic jams" and "traffic jams" is impossible.

It is important to make a preliminary forecast of air pollution in these local areas of the city to help management decisions and evaluate traffic flows in city highways' design and rehabilitation, taking into account forecast forecasts. In practical situations, with an existing fixed network of monitoring observations, there is usually a need for operational information for management decision-makers to assess and forecast the formation of smog situations over road junctions and overpasses. The paper substantiates the need to develop a mathematical model to determine the concentration of hydrocarbon emissions from engines running on gasoline and diesel fuel and secondary air pollution due to photochemical transformations, formaldehyde, which is an indicator of photochemical smog over city highways.

The dissertation research addresses environmental risk management in urban areas with secondary pollution of atmospheric air by formaldehyde from vehicles. This study's proposed calculation scenario is where the level of risk is determined depending on the concentration of formaldehyde molecules formed in the air resulting from photochemical transformations under stable weather conditions.

To determine secondary pollution concentration by formaldehyde was developed mathematical model consisting of two interconnected blocks: dynamic and kinetic. The first block of the model was developed is based on a convective jet theory from a warm surface, thus allowing to obtain the parameters of a polluted air dome formed over a motor transport highway. Depending on the road junction area and the site's meteorological conditions, the system of the model's dynamic block's obtained equations makes it possible to get the total amount of hydrocarbon emissions, depending on the number of vehicles on the highway at the same time.

The kinetic block of the model makes it possible to determine the concentration of secondary pollution with formaldehyde in atmospheric air due to photochemical transformations of hydrocarbons included in the emissions of internal combustion engines. The reaction rate of conversion for chemical elements was performed based on Van-Hoff-Arrhenius differential equation.

Based on the calculations, the error between the calculated and measured values of formaldehyde concentrations does not exceed 7.2%. Similarly, calculations were made on 7 overpasses in the city of Minsk (Belarus), and the resulting error does not exceed 8%.

The error in comparing the experimental and calculated values of the rate constant of the conversion of hydrocarbon emissions from vehicles into formaldehyde can be explained by the fact that the main process of smog formation occurs at an altitude of 200 (two hundred) m and more. -1/T when calculating (Darnytsia area PSZ №9) values of lnK (CHCOH/CCH), while monitoring measurements of CHCOH occurring in the surface layer of atmospheric air at a height of about 2 (two) m from the surface. This positive error is variable, tends to increase in the summer months, and is also characteristic of a number of Ukrainian cities.

The mathematical model was developed using a system of regular monitoring observations of atmospheric air pollution in Kyiv. Using the developed model, the Microsoft Excel calculator, and the program codes (scripting languages for scientific-analytical programs such as Python, and MATLAB) allow calculating hydrocarbons' emission into the atmosphere from road transport as well as formaldehyde concentration. It can reduce environmental risk to the health of the population located on motor transport highways and residential areas on the verge of a motor transport junction.

The calculation of carcinogenic and non-carcinogenic risks to public health from air pollution according to the standard method at the main intersections and overpasses of Kyiv showed that the average carcinogenic risk is in the range of IELCR (min: 5,12E-05, max:1,54E-04) and HQ (min:1,72, max:5,17), which according to the existing classification of risk levels is defined as average, which requires dynamic control and in-depth study of the possible consequences of adverse effects on the population. The maximum values of both non-carcinogenic and carcinogenic risk are observed in the summer months near the Central Bus Station, metro stations "Shulyavka", "Lybidska", "Dorogozhychi", at the intersection of Danyla Sherbakivskoho and Stetsenko streets, near Poshtova Square.

In the work according to the proposed scenario, the concentrations of secondary formaldehyde pollution from road transport near the main overpasses were calculated at the maximum monthly concentrations and the environmental risks to public health for the conditions of Kyiv were calculated. The results of calculations for the most polluted interchanges in Kyiv are visually presented.

An online system (web portal) of environmental analysis, created on the basis and using ArcGIS solutions (Environmental Analysis) for assessing and understanding the potential ecological risk impact on the environment and public health, taking into account the predicted indicators of formaldehyde concentrations from vehicles at the time of designing the development of city infrastructure (automobile highway), allows you to optimize the environmental impact assessment and reduce the time that needed for required to review the project by government agencies and environmental organizations.

The model creates a real-time forecast (synchronization of data on the calculation of formaldehyde concentrations) for each point (highways) of the earth, which allows you to predict future risk trends, allowing you to move from response strategy to warning strategy and make more informed decisions.

The city densification and, consequently, the potential polluting activities have increased significantly in the last decades, compromising the air quality. Thus, it is necessary to know this scenery to model the pollution behavior and its respective pattern in each region of the Federal District. So, the main goal of this study was to analyze the Aerosol product available by National Aeronautics and Space Administration (NASA) at the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (TERRA). With these preexisting data, it was possible to analyze the aerosol (AOD) distribution from 2010 and the optical depth. These data were integrated to the processed values of Total Particles in Suspension (PTS) of the eight air quality monitoring stations variably distributed in the Federal District, with two of them (714 south and HUB) kept and managed by the Interdisciplinary Center of Transport Studies (Centro Interdisciplinar de Estudos em Transportes - Ceftru/UnB), correlating the month of October 2010. The study showed that the region of Brasília downtown and the surroundings of the Fercal region, overall, were the ones that kept most of the Aerosol Optical Depth (AOD) and the highest values of the Angström Exponent (AE), which can be attributed to the types of activities performed in these regions.

Editor: Pavlos Kassomenos To investigate spatial inequality of ambient air pollutants and comparison of their heterogeneity and homogene-ity across Tehran, the following quantitative indicators were utilized: coefficient of divergence (COD), the 90 th percentile of the absolute differences between ambient air pollutant concentrations and coefficient of variation (CV). Real-time hourly concentrations of particulate matter (PM) and gaseous air pollutants (GAPs) of twenty-two air quality monitoring stations (AQMSs) were obtained from Tehran Air Quality Control Company (TAQCC) in 2017. Annual mean concentrations of PM 2.5 , PM 10-2.5 , and PM 10 (PM X) ranged from 21.7 to 40.5, 37.3 to 75.0 and 58.0 to 110.4 μg m −3 , respectively. Annual mean PM 2.5 and PM 10 concentrations were higher than the World Health Organization air quality guideline (WHO AQG) and national standard levels. NO 2 , O 3 , SO 2 and CO annual mean concentrations ranged from 27.0 to 76.8, 15.5 to 25.1, 4.6 to 12.2 ppb, and 1.9 to 3.8 ppm over AQMSs, respectively. Our generated spatial maps exhibited that ambient PM X concentrations increased from the north into south and southwestern areas as the hotspots of ambient PM X in Tehran. O 3 hotspots j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / s c i t o t e n v were observed in the north and southwest , while NO 2 hotspots were in the west and south. COD values of PM X demonstrated more results lower than the 0.2 cut off compared to GAPs; indicating high to moderate spatial ho-mogeneity for PM X and moderate to high spatial heterogeneity for GAPs. Regarding CV approach, the spatial var-iabilities of air pollutants followed in the order of O 3 (87.3%) N SO 2 (65.2%) N CO (61.8%) N PM 10-2.5 (52.5%) N PM 2.5 (48.9%) N NO 2 (48.1%) N PM 10 (42.9%), which were mainly in agreement with COD results, except for NO 2. COD values observed a statistically (P b 0.05) positive correlation with the values of the 90 th percentile across AQMSs. Our study, for the first time, highlights spatial inequality of ambient PM X and GAPs in Tehran in detail to better facilitate establishing new intra-urban control policies.

Air pollution, being especially severe in the fast-growing developing world, continues to post a threat to public health. Yet, few studies are capable of quantifying well how different groups of people in different places experience different levels of air pollution at the global scale. In this paper, we use worldwide Chinese as a lens to quantify the spatiotemporal variations and geographic differences in PM 2.5 exposures using unprecedented mobile phone big data and air pollution records. The results show that Chinese in South and East Asia suffer relatively serious PM 2.5 exposures, where the Chinese in China have the highest PM 2.5 exposures (52.8 mg/m 3 /year), which is fourfold higher than the exposures in the United States (10.7 mg/m 3 /year). Overall, the Chinese in Asian cities (35.5 mg/m 3 /year) experienced the most serious PM 2.5 exposures when compared with the Chinese in the cities of other continents. These results, partly presented as a spatiotemporally explicit map of PM 2.5 exposures for worldwide Chinese, help researchers and governments to consider how to address the effects of air pollution on public health with respect to different population groups and geographic locations.

Critical situations that cannot be solved by conventional approaches (traditional air quality monitoring networks), have the possibility of being managed quickly by a wide network of portable systems with sensors. The purpose of this research was to calibrate and validate low-cost sensors. Pilot indoor and outdoor areas, in the central area of Brasilia (Brazil's capital city) were chosen for corporative performance evaluation of the sensors. The CO at 99.999% volumetric injection method has been used in a gas test box, among two MiCS-5521 (CO/VOC) sensors, one being new and the other one with a short useful life. The number of injections adopted to each volume (from 1 ml to 6 ml) was 10, rising each sensor's confidence interval mean. A increase of the injected volume (ml) of CO resulted in significant decrease in a resistance (Ohms), as shown by a good inverse relationship on the interaction of these two variables (r = 0.88), with good measurement accuracy, when compared to the manufacturer's reference datasheet. Finally, a geospatial management system was built for the pollution data measured by the low-cost sensors.

مدل سازی بوسیله نرم افزار یک روش سریع و دقیق برای پیش بینی میزان گسترش دامنه رهایش مواد و شبیه سازی پیامدهای آن می باشد. از آنجا که مدل های ریاضی موجود برای مدل سازی پیامد شامل محاسباتی پیچیده و بسیار زمانبر هستند، بکارگیری نرم افزارهای شبیه سازی در این مرحله اهمیت خاصی پیدا میکند و به دلیل اینکه ارزیابی پیامد خطراتی همچون رها شدن مواد شیمیایی پر خطر در محیط، یکی از ضروری ترین و اصلی ترین مراحل برای افزایش سطح ایمنی در واحدهای موجود یا در حال طراحی می باشد اهمیت استفاده از نرم افزاری با قابلیت های بیشتر دو چندان میشود. Aloha یکی از نرم افزارهای رایگان در زمینه انتشار آلاینده در هوا می باشد. این نرم افزار توسط سازمان حفاظت از محیط زیست آمریکا برای مدل سازی حوادث ناشی از رهایی مواد سمی، منفجره و یا آتش و انفجار در پیامد آنها عرضه شده است. این نرم افزار دارای بانک اطلاعاتی بسیار غنی (اطلاعات بیش از ۱۰۰۰ ماده شیمیایی) و محیطی ساده برای جلوگیری از اشتباهات کاربر است. در این خودآموز با ذکر سناریوی احتمالی نشت آلاینده و مدلسازی آن اقدام به آموزش بخشی از این نرم افزار قدرتمند خواهد شد.

The dispersion of heavier-than-air aerosol clouds is of great relevance to the analysis and assessment of hazards in the chemical and petrochemical industries. There are many simple mathematical models for heavy gas dispersion but, in most cases, two-phase dynamics are either ignored or treated in a very simple way, without any convincing scientific justification. In fact almost all of those models which do treat two-phase phenomena rely on the "homogeneous equilibrium" assumption, whether they be for jet dispersion, for gravity dominated dispersion, or for any other aspect of a two-phase release. Here we test the homogeneous equilibrium model against a more sophisticated aerosol approach, in the context of two-phase ammonia clouds released in dry and moist air. It is shown that the simpler model does indeed provide a good description for some envisaged release situations, and guidance is given on where the homogeneous equilibrium model is not likely to be adequate. The homogeneous equilibrium model seems to be adequate for evaluating the dispersion of heavier-than-air clouds containing droplets smaller than 100 ~m.

Accurate prediction of mercury content emitted from fossil-fueled power stations is of the utmost importance for environmental pollution assessment and hazard mitigation. In this paper, mercury content in the output gas of power stations' boilers was predicted using an adaptive neuro-fuzzy inference system (ANFIS) method integrated with particle swarm optimization (PSO). The input parameters of the model included coal characteristics and the operational parameters of the boilers. The dataset was collected from 82 sample points in power plants and employed to educate and examine the proposed model. To evaluate the performance of the proposed hybrid model of the ANFIS-PSO, the statistical meter of MARE% was implemented, which resulted in 0.003266 and 0.013272 for training and testing, respectively. Furthermore, relative errors between the acquired data and predicted values were between −0.25% and 0.1%, which confirm the accuracy of the model to deal non-linearity and represent the dependency of flue gas mercury content into the specifications of coal and the boiler type. machine learning and soft computing expertise, S.S., M.H., A.B., A.M., J.B., and A.R.V.-K.; mathematics expertise, M.H., A.B., and J.B.; management, database, writing, administration, Mathematics 2019, 7, 965 11 of 16 and methodology, M.H., A.B.; visualization, M.H. and A.B.; supervision, resources, software, expertise, revision, funding, and verification of the results, J.B. and A.R.V.-K.

The present study deals with the air pollution caused by Industry and transportation in
urban areas of Pakistan. Rawalpindi and Islamabad, the twin cities of Pakistan were considered for
this purpose. The concentrations of major air pollutants were taken from different location according
their standard time period using Air Quality Monitoring Station. Five major air pollutants were
considered i.e., NO2, SO2, CO, O3and PM2.5. The average mean values for all pollutants were taken
on monthly and four monthly bases. The concentrations of NO2and PM2.5 were exceeding the
permissible limits as define by Environmental Protection Agency of Pakistan. Other pollutants
concentrations were within the standard limits. Geographic Information System was used as a tool
for the representation and analysis of Environmental Impacts of air pollution. Passquill and Smith
dispersion model was used to calculate the buffer zones. Some mitigation measures were also
recommended to assess the environmental and health Impacts because of PM2.5 and NO2.
Keywords; Air Quality Monitoring Network; Multi-pollutant; Industrial area; Road transp

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مدل سازی بوسیله نرم افزار یک روش سریع و دقیق برای پیش بینی میزان گسترش دامنه رهایش مواد و شبیه سازی پیامدهای آن می باشد. از آنجا که مدل های ریاضی موجود برای مدل سازی پیامد شامل محاسباتی پیچیده و بسیار زمانبر هستند، بکارگیری نرم افزارهای شبیه سازی در این مرحله اهمیت خاصی پیدا میکند و به دلیل اینکه ارزیابی پیامد خطراتی همچون رها شدن مواد شیمیایی پر خطر در محیط، یکی از ضروری ترین و اصلی ترین مراحل برای افزایش سطح ایمنی در واحدهای موجود یا در حال طراحی می باشد اهمیت استفاده از نرم افزاری با قابلیت های بیشتر دو چندان میشود. Aloha یکی از نرم افزارهای رایگان در زمینه انتشار آلاینده در هوا می باشد. این نرم افزار توسط  سازمان حفاظت از محیط زیست آمریکا برای مدل سازی حوادث ناشی از رهایی مواد سمی، منفجره و یا آتش و انفجار در پیامد آنها عرضه شده است. این نرم افزار دارای بانک اطلاعاتی بسیار غنی (اطلاعات بیش از ۱۰۰۰ ماده شیمیایی) و محیطی ساده برای جلوگیری از اشتباهات کاربر است. در این خودآموز با ذکر سناریوی احتمالی نشت آلاینده و مدلسازی آن اقدام به آموزش بخشی از این نرم افزار قدرتمند خواهد شد.

In this study the effect of acid rain on the geo technical properties of the soil was investigated. acidic environment was created to prepare the samples infiltrated with different pH level of acid rains. industrial advance in agriculture, chemical industries has led to release of pollutants in to the environment contaminating the soil. The soil is being contaminated by anthropogenic source such as leakage from waste contaminates facilities, accidental spills and industrial operations. This paper reports the effect sulphuric acid, oxalic acid and nitric acid on the
compaction characteristics of the soil at varying percentages. The acid contamination of soil adversely effects the geotechnical properties of soil. the geotechnical properties of the soil get altered when an acid compaction gets mixed with soil. Atterberg’s limits, compaction
characteristics and unconfined compressive strength test have been carried out. Result are indicative that the compaction characteristics and unconfined compressive strength are altered due to acid contamination.

Lead pollution in Arctic ice reflects mid-latitude emissions from ancient
lead-silver mining and smelting. The few reported measurements
have been extrapolated to infer the performance of ancient
economies, including comparisons of economic productivity and
growth during the Roman Republican and Imperial periods. These
studies were based on sparse sampling and inaccurate dating,
limiting understanding of trends and specific linkages. Here we
show, using a precisely dated record of estimated lead emissions
between 1100 B.C.E. and 800 C.E. derived from sub-annually resolved
measurements in Greenland ice and detailed atmospheric
transport modeling, that annual European lead emissions closely
varied with historical events including imperial expansion, wars,
and major plagues. Emissions rose coeval with Phoenician expansion,
accelerated during expanded Carthaginian and Roman
mining primarily in the Iberian Peninsula, and reached a maximum
under the Roman Empire. Emissions fluctuated synchronously with
wars and political instability particularly during the Roman Republic,
and plunged coincident with two major plagues in the 2nd
and 3rd centuries, remaining low for >500 years. Bullion in silver
coinage declined in parallel, reflecting the importance of leadsilver
mining in ancient economies. Our results indicate sustained
economic growth during the first two centuries of the Roman
Empire, terminated by the 2nd-century Antonine plague.

A method for air pollution evaluation and control, based on one of
the most popular neural networks – the backpropagation algorithm, is proposed.
After the backpropagation training, the neural network, based on weather
forecasting data, determines the future concentration of critical air pollution
indicators. Depending on these concentrations, relevant episode warnings and
actions are activated. A case study is carried out to illustrate and validate
the method proposed, based on Istanbul air pollution data. Sulphur dioxide
and inhalable particulate matter are selected as air pollution indicators
(neural network outputs). Relevant episode measures are proposed. Among ten
backpropagation algorithms, the BFGS algorithm (Quasi-Newton algorithms) is
adopted since it showed the lowest training error. A comparison of NN-AirPol
method against regression and perceptron models showed significantly better
performance.

Users must concentrate their Sewage/Wastewater treatment process to ensure that it complies with regulatory guidelines. The main purpose of Sewage treatment process is to remove the various constituents of the polluting load: solids, organic carbon, nutrients, inorganic salts, metals, pathogens etc. Effective wastewater collection and treatment are of great importance from the standpoint of both; environmental and public health. Sewage/Wastewater treatment operations are done by various methods in order to reduce its water and organic content, and the ultimate goal of wastewater management is the protection of the environment in a manner commensurate with public health and socio-economic concerns. In this article, Sewage/Wastewater treatment techniques, factors affecting selection and design Sewage/Wastewater systems are discussed briefly.

Air pollution is a major problem in Bangladesh. Cement industries are one of the most top contributors to GDP. They produce a lot of pollution in the environment. Local manufacturers do not maintain the requirement of the Department of Environment (DOE). This paper aims to study the pollution sources, emission inventory, emission monitoring, air pollution modeling, and pollution control equipment in the cement industry. Sample air pollution modeling is shown in AERMOD software. Finally, some recommendation was done in the paper.

This paper describes the application of the air pollution model (TAPM-CTM) for photochemical airshed modelling in the Ho Chi Minh region. The model was developed by the Commonwealth Scientific and Research Organisation (CSIRO), Australia, and incorporates both a prognostic meteorological component and photochemical component. Based on the emission inventory developed by Vietnam National University, simulation of meteorological and chemical transport dispersion processes for air quality in Ho Chi Minh City (HCMC) is performed using TAPM-CTM. The model performance is evaluated using publicly available measured meteorological data at Ho Chi Minh City airport and air quality data as measured by the Hydro-meteorological Center of Southern Region and our research team at the Ho Chi Minh City University of Science. The model is then applied to simulate a 1-month period in the dry season to determine the extent of the photochemical pollution in Ho Chi Minh City and the surrounding areas. The results show that under the north easterly prevailing wind in this period, the high pollution is more likely to be experienced in the south west of Ho Chi Minh in the Long An, Tien Giang, Ben Tre and Vinh Long provinces. It is recommended that monitoring stations should be set up in these provinces to monitor the peak ozone events that are formed due to transport of precursors from Ho Chi Minh City. The results show that TAPM-CTM performed well as applied to the Ho Chi Minh City airshed region and is a promising tool to study scenario emission for air quality management in this city and the surrounding areas.

This paper presents a summary of the work
done within the European Union’s Seventh Framework Programme project ECLIPSE (Evaluating the Climate and Air
Quality Impacts of Short-Lived Pollutants). ECLIPSE had a
unique systematic concept for designing a realistic and effective
mitigation scenario for short-lived climate pollutants
(SLCPs; methane, aerosols and ozone, and their precursor
species) and quantifying its climate and air quality impacts,
and this paper presents the results in the context of this overarching strategy. The first step in ECLIPSE was to create a
new emission inventory based on current legislation (CLE)
for the recent past and until 2050. Substantial progress compared to previous work was made by including previously
unaccounted types of sources such as flaring of gas associated
with oil production, and wick lamps. These emission
data were used for present-day reference simulations with
four advanced Earth system models (ESMs) and six chemistry
transport models (CTMs). The model simulations were
compared with a variety of ground-based and satellite observational data sets from Asia, Europe and the Arctic. It was
found that the models still underestimate the measured seasonality of aerosols in the Arctic but to a lesser extent than
in previous studies. Problems likely related to the emissions
were identified for northern Russia and India, in particular.
To estimate the climate impacts of SLCPs, ECLIPSE followed
two paths of research: the first path calculated radiative
forcing (RF) values for a large matrix of SLCP species emissions,
for different seasons and regions independently. Based
on these RF calculations, the Global Temperature change Potential metric for a time horizon of 20 years (GTP20/ was
calculated for each SLCP emission type. This climate metric
was then used in an integrated assessment model to identify
all emission mitigation measures with a beneficial air
quality and short-term (20-year) climate impact. These measures together defined a SLCP mitigation (MIT) scenario.
Compared to CLE, the MIT scenario would reduce global
methane (CH4/ and black carbon (BC) emissions by about
50 and 80 %, respectively. For CH4, measures on shale gas
production, waste management and coal mines were most
important. For non-CH4 SLCPs, elimination of high-emitting
vehicles and wick lamps, as well as reducing emissions from
gas flaring, coal and biomass stoves, agricultural waste, solvents
and diesel engines were most important. These measures
lead to large reductions in calculated surface concentrations
of ozone and particulate matter. We estimate that
in the EU, the loss of statistical life expectancy due to air
pollution was 7.5 months in 2010, which will be reduced to
5.2 months by 2030 in the CLE scenario. The MIT scenario
would reduce this value by another 0.9 to 4.3 months. Substantially larger reductions due to the mitigation are found for China (1.8 months) and India (11–12 months). The climate
metrics cannot fully quantify the climate response. Therefore,
a second research path was taken. Transient climate
ensemble simulations with the four ESMs were run for the
CLE and MIT scenarios, to determine the climate impacts
of the mitigation. In these simulations, the CLE scenario resulted in a surface temperature increase of 0.7+-0.14K between the years 2006 and 2050. For the decade 2041–2050,
the warming was reduced by 0.22+-0.07K in the MIT scenario,
and this result was in almost exact agreement with the
response calculated based on the emission metrics (reduced
warming of 0.22+-0.09 K). The metrics calculations suggest
that non-CH4 SLCPs contribute 22% to this response and
CH4 78 %. This could not be fully confirmed by the transient
simulations, which attributed about 90% of the temperature
response to CH4 reductions. Attribution of the observed
temperature response to non-CH4 SLCP emission reductions
and BC specifically is hampered in the transient simulations
by small forcing and co-emitted species of the emission basket
chosen. Nevertheless, an important conclusion is that our
mitigation basket as a whole would lead to clear benefits for
both air quality and climate. The climate response from BC
reductions in our study is smaller than reported previously,
possibly because our study is one of the first to use fully
coupled climate models, where unforced variability and sea
ice responses cause relatively strong temperature fluctuations
that may counteract (and, thus, mask) the impacts of small
emission reductions. The temperature responses to the mitigation were generally stronger over the continents than over the oceans, and with a warming reduction of 0.44K (0.39–
0.49)K the largest over the Arctic. Our calculations suggest
particularly beneficial climate responses in southern Europe,
where surface warming was reduced by about 0.3K and precipitation rates were increased by about 15 (6–21)mmyr􀀀1
(more than 4% of total precipitation) from spring to autumn.
Thus, the mitigation could help to alleviate expected future
drought and water shortages in the Mediterranean area. We
also report other important results of the ECLIPSE project.

An analytical technique to solve the Eulerian advection-diffusion equation for nonstationary conditions and passive contaminant within the Planetary Boundary Layer is analysed in this paper. The approach produces comparable results when considering the most important quantity in air-pollution application, that is the ground level concentration distribution. This is a promising result as this computer-based technique may be used for quantitative and qualitative estimations of contaminant distribution.

Various forms of geoengineering have been proposed to counter anthropogenic climate change. Methods which aim to modify the Earth's energy balance by reducing insolation are often subsumed under the term solar radiation management (SRM). Here, we present results of a standard SRM modelling experiment in which the incoming solar ir-radiance is reduced to offset the global mean warming induced by a quadrupling of atmospheric carbon dioxide. For the first time in an atmosphere–ocean coupled climate model, we include atmospheric composition feedbacks for this experiment. While the SRM scheme considered here could offset greenhouse gas induced global mean surface warming, it leads to important changes in atmospheric composition. We find large stratospheric ozone increases that induce significant reductions in surface UV-B irradiance, which would have implications for vitamin D production. In addition, the higher stratospheric ozone levels lead to decreased ozone photolysis in the troposphere. In combination with lower atmospheric specific humidity under SRM, this results in overall surface ozone concentration increases in the idealized G1 experiment. Both UV-B and surface ozone changes are important for human health. We therefore highlight that both stratospheric and tropospheric ozone changes must be considered in the assessment of any SRM scheme, due to their important roles in regulating UV exposure and air quality.

Air quality indices are used for local and regional air quality management in many metro cities of the world. In the present study, air quality indices have been calculated using the US Environmental Protection Agency procedure to assess the status of ambient air quality near busy traffic intersections in Bangalore, India. The measured 24 h average criteria pollutants such as sulfur dioxide, oxides of nitrogen, respirable suspended particulate matter and suspended particulate matter for the period from 1997 to 2005 at three air quality monitoring stations are used for the development of AQIs. The result indicated that the air pollution at all the three air quality monitoring stations can be characterized as 'good' and 'moderate' for SO 2 and NO x concentrations for all days from 1997 to 2004. Analysis of air quality indices values for both forms of suspended matter concentrations during 1999–2005 indicates 91% and 94% of the times days are in category 'good' and 'moderate'. The yearly average air quality indices values of respirable suspended particulate matter and suspended particulate matter concentrations indicated decreasing trend and are coming under the category of 'good' and 'moderate' form the category of 'poor' and 'very poor'.

ÖZET Toplamda %70'i denizler ve okyanuslardan oluşan dünyamızda denizyolu taşımacılığının ciddi bir kirletici kaynak grubu olduğu tahmin edilmektedir. Hava kirliliği yaklaşımında yenicil ve bütüncül metotların başında kimyasal modeller gelmektedir. Bu çalışmanın amacı, dünya genelinde son senelerde yapılmış deniz taşımacılığı dolayısı ile oluşan kirleticilerin modelleme çalışmalarının derlenmesi, karşılaştırılması ve yorumlanmasıdır. Çalışma kapsamında kullanılan sekiz adet makale vardır ve bu makaleler iki tanesi Türkiye olmak üzere Dünya'nın farklı yerlerinden, farklı dönemlerde ve kısmen farklı modelleme yöntemleri kullanılarak hazırlanmıştır.
ABSTRACT It is estimated that maritime transport is a serious source of pollutants in our world, which is composed of 70% seas and oceans. In the air pollution approach, chemical models are at the beginning of innovative and holistic methods. The aim of this study is to compile, compare and interpret the modeling studies of the pollutants formed due to the maritime transportation in recent years in the world. It has been prepared for different purposes, at different periods and for different modeling methods here. There are eight different articles under this study and all of them are different places of the World. Also two of them are about Turkey.

Air pollution can be defined as the presence in the atmosphere of one or more contaminants in such quality and for such duration as is injurious, or tends to be injurious, to human health or welfare, animal or plant life. It is the contamination of air by the discharge of harmful substances. Industrialization have led to air getting more and more polluted over the years. Industries, vehicles, increase in the population, and urbanization are some of the major factors responsible for air pollution. The following industries are among those that emit a great deal of pollutants into the air: thermal power plants, cement, steel, refineries, petro chemicals, and mines.
Air pollution can cause health problems and it can also damage the environment and property. It has caused thinning of the protective ozone layer of the atmosphere, which is leading to climate change.

Data sets from street canyons in Stockholm, Berlin and London are used to investigate the performance of the Gaussian model ADMS-Roads 1 and the Lagrangian model LASAT 2 and the impact of different meteorological input, flow schemes and NO-NO 2 conversion schemes. ADMS-Roads tends to under-predict NO x concentrations. Nevertheless, the more complex Lagrangian model is not always in better agreement with the observations. LASAT with a simpler flow scheme leads to higher concentrations of NO x than the more complex DMK scheme in Stockholm and Berlin. Model runs based on time-series of stability classes render in several cases better results than those with constant neutral conditions. Two NO-NO 2 conversion schemes are used. The scheme after Romberg performs better for LASAT in most of the cases while the Derwent approach is more successful for ADMS-Roads. Although point to point correlations between model results and measurements are generally weak, both dispersion models are quite successful in predicting average values, maximum values as well as the occurrence of exceedances of threshold limits within the street canyons.

This study aims to investigate the spatial variation in the source of air pollution, identify the percentage contribution of each pollutant and apportion the mass contribution of each source category using chemometric techniques. Hierarchical agglomerative cluster analysis (HACA) successfully grouped the five air monitoring sites into three groups (cluster 1, 2 and 3). Principal component analysis (PCA) was used to spot out the sources of air pollution which are attributed to anthropogenic activities. Multiple linear regression (MLR) was used to develop an equation model that explains the contribution of pollutants in each cluster. However, it was observed that particulate matter (PM10) and Ozone (O3) are the most significant pollutants influencing the value of air pollutant index (API). Meanwhile, the source apportionment indicates that cluster 1 is influenced by gas and non-gas pollutants to a degree of 84%, weather condition 15% and 1% by gas and secondary pollutants. Cluster 2 i...

Air pollution over China has attracted wide interest from public and academic community. PM 2.5 is the primary air pollutant across China. Quantifying interactions between meteorological conditions and PM 2.5 concentrations are essential to understand the variability of PM 2.5 and seek methods to control PM 2.5. Since 2013, the measurement of PM 2.5 has been widely made at 1436 stations across the country and more than 300 papers focusing on PM 2.5-meteorology interactions have been published. This article is a comprehensive review on the meteorological impact on PM 2.5 concentrations. We start with an introduction of general meteorological conditions and PM 2.5 concentrations across China, and then seasonal and spatial variations of meteorological influences on PM 2.5 concentrations. Next, major methods used to quantify meteorological influences on PM 2.5 concentrations are checked and compared. We find that causality analysis methods are more suitable for extracting the influence of individual meteorological factors whilst statistical models are good at quantifying the overall effect of multiple meteorological factors on PM 2.5 concentrations. Chemical Transport Models (CTMs) have the potential to provide dynamic estimation of PM 2.5 concentrations by considering anthropogenic emissions and the transport and evolution of pollutants. We then comprehensively examine the mechanisms how major meteorological factors may impact the PM 2.5 concentrations, including the dispersion, growth, chemical production, photolysis, and deposition of PM 2.5. The feedback effects of PM 2.5 concentrations on meteorological factors are also carefully examined. Based on this review, suggestions on future research and major meteorological approaches for mitigating PM 2.5 pollution are made finally.

h during all the months from January to December. Emission factors were found to be maximum during early morning and late night when vehicular density was minimum and found to be minimum during maximum traffic hours. RSPM and SPM concentrations were varying from 150–350 and 250–450 µg/m 3 , respectively, in all the seasons, which was exceeding the National ambient air quality standard (NAAQS) of 100 and 300 µg/m 3 , respectively. However, SO2 and NOx concentrations were ranging from 5–17 and 15–35 µg/m 3 , respectively, found to be within the NAAQS of 80 µg/m 3. ISCST3 model predictions were found to be good agreement with observed NOx and SO2 concentrations and model was underpredicting RSPM and SPM concentrations. CALINE4 model was overpredicting NOx concentration and underpredicting SPM concentrations. However, CALINE4 model predictions were found to be satisfactory with observed SPM concentrations.

Ambient Air Quality (AAQ) has been monitored over a period of 8 months from November, 2016 to June, 2017, considering winter, summer and monsoon seasons at three identified locations along the highway passing through industrial area of Mysuru city, India. The number of 2W vehicles were found to be maximum (13620 nos./d) followed by 4W (4654 nos./d), HDV (2410 nos./d) and LDV (2024 nos./d). During weekdays the peak traffic volumes were observed at 08:00–10:00 hours and 17:00–20:00 hours. All the monitored pollutant concentrations were found to be well within National Ambient Air Quality Standard (NAAQS) in all the seasons, except during winter season PM 10 and PM 2.5 at receptor R1 were found to be exceeding the NAAQS. The comparison between observed values with Industrial source complex short term model 3 (ISCST3) and California line source model 4 (CALINE4) predictions showed ISCST3 model prediction found to be good agreement with observed NOx and SO 2 concentration, however, CALINE4 model prediction was good agreement with observed PM 10 concentration. It was also observed that, NOx and PM 10 was contributing ~86% and ~68% from line sources and ~14% and ~32% from point sources, respectively, however, SO 2 was contributing ~67% from point sources and ~33% from line sources. The statistical analysis of ISCST3 model was found to be within the acceptable values, indicating a good agreement with the observed pollutant concentrations.

This paper presents Multi Objective Trajectory Optimization (MOTO) algorithms that were developed for integration in state-of-the-art Air Traffic Management (ATM) and Air Traffic Flow Management (ATFM) systems. The MOTO algorithms are conceived for the automation-assisted replanning of 4-Dimensional Trajectories (4DT) when unforeseen perturbations arise at strategic and tactical online operational timeframes. The MOTO algorithms take into account updated weather and neighbouring traffic data, as well as the related forecasts from selected sources. Multiple user-defined operational, economic and environmental objectives can be integrated as necessary. Two different MOTO algorithms are developed for future implementation in ATM systems: an en-route variant and a Terminal Manoeuvring Area (TMA) variant. In particular, the automated optimal 4DT replanning algorithm for en-route airspace operations is restricted to constant flight level to avoid violating the current vertical airspace structure. As such, the complexity of the generated trajectories reduces to 2 dimensions plus time (2D+T), which are optimally represented in the present 2D ATM display formats. Departing traffic operations will also significantly benefit from MOTO-4D by enabling steep/continuous climb operations with optimal throttle, reducing perceived noise and gaseous emissions.

Megacities in India (population more than 10 million) have taken actions to control air-pollution emissions. However, the second-level cities (population between one and 10 million) have not drawn an action plan, and people face serious air pollution in these cities. For one such city, Lucknow, a geographic information system (GIS)-based methodology for emission inventory of on-road vehicles has been developed. The pollutants include: sulfur dioxide (SO 2); oxides of nitrogen (NO x); carbon monoxide (CO); particulate matter (PM); 1,3 butadiene; formaldehyde; acetaldehyde; total aldehydes; and total polycyclic aromatic hydrocarbons (PAHs). Video recording was done at nine road intersections of varying land-use patterns to assess traffic count and vehicle kilometer travel. Parking lot surveys were carried out for assessing engine type, vehicle age, etc. and to arrive at a suitable net emission factor for each vehicle category. The 2-wheelers (2-Ws) and 4-wheelers (4-Ws) dominate the total traffic with an 83% share and are main sources of NO x (46%) and CO (77%). The heavy duty vehicles (HDVs: buses and trucks), although they account for only 2% of the vehicle fleet, emit disproportionately high emissions (23% of SO 2 , 36% of NO x , and 28% of PM). Spatial cell (2 × 2 km)-wise emission inventory of pollutants indicates that the city center has the highest pollutant emissions resulting from a large number of vehicles, mostly 2-Ws, 3-Ws, and passenger cars. The inventory information can be used for short-term and long-term planning to reduce emissions.

This research was funded by, and implemented within, a UK national research organisation, while the author was the KE and Impact Evaluation Manager responsible for assessing impact on a £15m UK government-funded research programme.

This work was also submitted as the authors MBA dissertation which was accepted and awarded in 2009.

ABSTRACT: A methodology and methods ‘toolbox’ is proposed for conducting impact research and assessment from within research programmes. The emphasis is upon how to clarify and assess the wider impacts from the early stages onwards.

The approach explicitly acknowledges, and attempts to address, the known issues and challenges of impact assessment while drawing upon the resources and opportunities available to research managers and researchers within such programmes.

The study has two triangulating foundations. Firstly, it examines the academic literature to help identify and design the pilot methodology and methods. Secondly it trials these in a real programme to both test and improve them.

The study was conducted over one year within one leading UK research organisation, where two research programmes (and around 60 research projects of £15m total value) were being assessed for their impacts. The study draws upon actual impact management experience and reflection, prospective (ex ante) and retrospective (ex post) assessments, participatory contributions from leading researchers undergoing assessment, and consultation with external users. The findings of this study outline the pilot and its first iteration. Recommendations are made for improvement to the methodology and methods.

A subsequent follow-on bid to UK government incorporating the impacts identified from implementing this methodology, successfully led to a further £15m of government funding.

It is expected the pilot methodology and methods will be applicable to other organisations, conducting and funding such research programmes, required to research and assess the wider research impacts.

Although primary focus of implemetation trials was upon research in physical sciences, technology, high-tech engineering, computing/IT, and environment, the wider literature study, the methodology design and justification, the methods proposed and used, and the resulting general recommendations and lessons are expected to apply more broadly to many other research areas, where the impact is to be found more widely in the society, economy, government or public sector or within organizations, policies, professions or the public.

Interest in this work is expected from research programme managers, impact managers and assessors, management consultants advising in this area, and government funding managers, all seeking to embed a developing approach to understand, capture, and enhance wider impact.

An air inlet can protrude from the aircraft surface or be submerged into the aircraft body. A submerged inlet
has in general lower aerodynamic drag than an inlet that protrudes from the surface of an aircraft and is
therefore the most preferred design option to the flight industry. An air inlet should ideally not decrease the
total pressure of the air which enters and at the same time only give rise to a minimum amount of additional
aerodynamic drag. Although angle variation in the air inlet have several affects other than inlet efficiency also
the air breathing system of the airplanes. As the varying ramp angle in the airplane, air jet etc, may create the
problems on the working of the air inlet. So this review on efficiency of inlet with varying ramp angle is very
much needful for the system as well as for the designers, and also it would be very helpful for the future
perspective for researches.
Keywords: Ramp Angle, Air Intake, Pressure Distortion.

Highway traffic-induced air pollution is a major concern for health and ecosystem. The SAQIAM was developed to facilitate visualization and interpretation of geographic distribution of air pollution impacts due to highway broadening in East Sikkim. An analytic hierarchy process-based Spatial Air Quality Index (SAQI) was constructed for this purpose. The individual air pollutant maps of CO, NO 2 , SO 2 and suspended particulate matter were prepared using IITLS dispersal model. Model validation and spatial crossvalidation criteria suggested that SAQIAM is a reliable spatial model. Statistical analysis of SAQI showed that it is a reliable index. SAQI maps under various time horizons showed that the pre-project and project-implementation scenarios will have mostly good air quality while post-project implementation scenario will have poor air quality close to the highway. Spatially explicit sensitivity analysis indicates that SAQIAM is robust. SAQIAM has the potential to serve as decision support tool for geovisualization of transport-related project impacts on air quality. Moreover, it can facilitate environmental managers to prioritize mitigation measures by capturing the perception of stakeholders using SAQI.