Assessing the Contribution of Carbon Emissions Trading in China to Carbon Intensity Reduction

This paper assesses the impacts of emissions trading between Jiangxi Province and the Rest of China on the carbon prices, total cost of carbon reduction and GDP loss using a two-region provincial Computable General Equilibrium model developed for China. The results reveal that without emissions trading, the carbon prices in 2020 would be 46.8 US$in Jiangxi Province and 23.2 US$ in the rest of China, leading to GDP loss of 1.07% and 0.79% respectively. However, if emissions trading is allowed between provinces, Jiangxi Province needs to import CO2 emissions allowance from the rest of China. In 2013, the trading amount is 14.30 million ton or 7.84% of total CO2 emissions of Jiangxi Province. In 2020, the trading amount triples as compared to 2013, to a level of 44.85 million ton, accounting for 19.37% of Jiangxi’s total emissions. The results also reveal that the total costs of Jiangxi Province and the whole China would fall due to emissions trading, which is consistent with the theoretical implications. It is found that in the case of emissions trading, the GDP loss in 2020 would be lower for Jiangxi Province, at 0.36% instead of 1.07%.Key words: Domestic carbon emissions trading; 2-regional CGE model; Chin

Future energy consumption and emissions in East-, Central- and West-China: Insights from soft-linking two global models

AbstractChina's role in the global economy and energy markets is expanding, however many uncertainties with regards to the country's future energy consumption and emissions remain. Large regional disparities between China's provinces exist. Scenario analysis for different sub-regions of China will be useful for an improved understanding of China's potential future development and associated global impacts. This study soft-links a global dynamic CGE model and a global technology-rich energy system model. Both models are expanded to include East-, Central-, and West-China. This study shows that soft-linking affects the China-specific reference scenario results in the CGE model considerably. Energy consumption and emissions are decreasing in China until 2050 while regional differences within China remain high

Air quality co-benefits from climate mitigation for human health in South Korea

Climate change mitigation efforts to reduce greenhouse gas (GHG) emissions have associated costs, but there are also potential benefits from improved air quality, such as public health improvements and the associated cost savings. A multidisciplinary modeling approach can better assess the co-benefits from climate mitigation for human health and provide a justifiable basis for establishment of adequate climate change mitigation policies and public health actions. An integrated research framework was adopted by combining a computable general equilibrium model, an air quality model, and a health impact assessment model, to explore the long-term economic impacts of climate change mitigation in South Korea through 2050. Mitigation costs were further compared with health-related economic benefits under different socioeconomic and climate change mitigation scenarios. Achieving ambitious targets (i.e., stabilization of the radiative forcing level at 3.4 W/m2) would cost 1.3-8.5 billion USD in 2050, depending on varying carbon prices from different integrated assessment models. By contrast, achieving these same targets would reduce costs by 23 billion USD from the valuation of avoided premature mortality, 0.14 billion USD from health expenditures, and 0.38 billion USD from reduced lost work hours, demonstrating that health benefits alone noticeably offset the costs of cutting GHG emissions in South Korea

Guidelines for Modeling and Reporting Health Effects of Climate Change Mitigation Actions.

BACKGROUND: Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers. OBJECTIVE: The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions. METHODS: An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies. RESULTS: The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting. DISCUSSION: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice. https://doi.org/10.1289/EHP6745