Social Cost of Carbon

In this paper, a generic multi-tiered reverse logistic model for waste management is proposed in the presence of stochastic waste generation ratio. Various aspects of a comprehensive waste management network such as recycling and remanufacturing are considered. The carbon footprint's social cost and Green House Gas (GHG) emission are also incorporated in the model. In addition, several separation ratios for each facility are taken into account and unnecessary decision variables are avoided accordingly. The proposed model is applied in a real case study, and several sensitivity analyses are performed which allow the extraction of the managerial insights for optimizing the operational and tactical performance of waste management.

In order for the world to stay within the safety threshold of a 2C increase in average temperature agreed by virtually all governments, the transport sector needs to be decarbonized. The two main obstacles that have prevented this from happening have been the absence of a global legally binding deal and the high relative cost of clean vehicle/energy technologies. The Paris Agreement, which commits countries to reductions of GHG emis- sions, has virtually solved the first problem and paved the way for countries to implement environmental taxes and subsidies in order to change the relative costs of clean alternatives, which would solve the second problem. These policy actions combined with investment in clean infrastructure and regulation can decarbonize the transport sector.

Coal and Health in the Hunter: Lessons from one valley for the world, provides an insight
into the evidence of the harm – local, national, and global – from coal production in the Hunter Valley in New South Wales, Australia.

The report reveals there is serious adverse impacts to physical and psychological health associated with coal mining, transportation and production, and estimates there is millions of dollars in health damages associated with air pollution from coal sources in the Hunter and billions of dollars per annum associated with the social costs of carbon from Hunter Valley coal.

To download the full Report, Recommendations for Action, Summary for Policymakers, Case Studies, Infographics and Videos – see http://caha.org.au/projects/hunter-coal/ and www.coalandhealth.org

Future population growth is uncertain and matters for climate policy: higher growth entails more emissions and means more people will be vulnerable to climate-related impacts. We show that how future population is valued importantly determines mitigation decisions. Using the Dynamic Integrated Climate-Economy model, we explore two approaches to valuing population: a discounted version of total utilitarianism (TU), which considers total wellbeing and is standard in social cost of carbon dioxide (SCC) models, and of average utilitarianism (AU), which ignores population size and sums only each time period’s discounted average wellbeing. Under both approaches, as population increases the SCC increases, but optimal peak temperature decreases. The effect is larger under TU, because it responds to the fact that a larger population means climate change hurts more people: for example, in 2025, assuming the United Nations (UN)-high rather than UN-low population scenario entails an increase in the SCC of 85% under TU vs. 5% under AU. The difference in the SCC between the two population scenarios under TU is comparable to commonly debated decisions regarding time discounting. Additionally, we estimate the avoided mitigation costs implied by plausible reductions in population growth, finding that large near-term savings ($billions annually) occur under TU; savings under AU emerge in the more distant future. These savings are larger than spending shortfalls for human development policies that may lower fertility. Finally, we show that whether lowering population growth entails overall improvements in wellbeing—rather than merely cost savings—again depends on the ethical approach to valuing population.

The main purpose of this study is to explore the carbon reduction environmental benefits that can be achieved if carbon benchmarking is applied when semiconductor manufacturers in Taiwan work to improve the technical efficiency of their carbon reduction efforts. The evaluation method used is as follows. First, a technical efficiency measurement method that is capable of considering both desirable outputs and undesirable outputs is used to measure the technical efficiency of the carbon reduction efforts and identify the benchmark firms with the best technical efficiency. Next, an attempt is made to estimate the greenhouse gas reduction that is realized by the sample if their carbon reduction efforts are accompanied by the implementation of a benchmarking system. Finally, the monetary value of the greenhouse gas reduction is estimated so as to develop a better understanding of the carbon reduction benefits for the adoption of the process outlined above. The empirical results show that using carbon benchmarking to raise the technical efficiency of carbon reduction management would, on average, boost the annual sales revenue of each decision-making unit by about US$486.6 million, while also bringing up the average annual CO2 reduction benefits per decision-making unit by US$11.11 million per year

Over the past few decades, we have improved our understanding of the health impacts of climate change.1 Although many public health researchers have contributed to this knowledge, relatively few are aware of how their work may relate to the social cost of carbon. The social cost of carbon is a core economic concept in climate policy and one that can—and should—benefit directly from research produced by the public health community. The concept’s importance was recently highlighted by this past year’s Nobel Prize in Economic Sciences, which was awarded to William Nordhaus in part for his pioneering work developing models to estimate the social cost of carbon. Below we describe this concept, explain how it is calculated, and provide some brief guidance on how health research can improve its estimation.