Research on the emission reduction effects of carbon trading mechanism on power industry: plant-level evidence from China

• Published in: International journal of climate change strategies and management Vol. 15; no. 2; pp. 212 - 231
• Main Authors: Han, Yonghui, Tan, Shuting, Zhu, Chaowei, Liu, Yang
• Format: Journal Article
• Language: English
• Published: Bingley Emerald Publishing Limited 11.04.2023; Emerald Group Publishing Limited; Emerald Publishing
• Subjects: Anthropogenic factors; Carbon; Carbon dioxide; Carbon dioxide emissions; Carbon trading mechanism; Clean energy; Clean technology; Climate change; Climate policy; Coal; Coal-fired power plants; Collective action; Compliance; Coronaviruses; Costs; COVID-19; Data; Decision making; Design; Developing countries; Economic development; Effectiveness; Electric industries; Electricity; Emission analysis; Emission reduction; Emission standards; Emissions; Emissions control; Emissions trading; Energy; Environmental policy; Environmental regulations; Fossil fueled power plants; Gas-fired power plants; Genetic transformation; Green development; Green economy; Green finance; Greenhouse gases; High resolution; Human influences; Impact analysis; Industrial plant emissions; Investors; LDCs; Methods; Particulate matter; Particulate matter emissions; Policy making; Pollution; Power plants; Resolution; Satellite data; Satellites; Spatiotemporal data; Sustainable energy; China; Emission reduction; Green finance; Carbon trading mechanism; Sustainable energy
• ISSN: 1756-8692; 1756-8692; 1756-8706
• DOI: 10.1108/IJCCSM-06-2022-0074

Purpose Carbon trading mechanism has been adopted to foster the green transformation of the economy on a global scale, but its effectiveness for the power industry remains controversial. Given that energy-related greenhouse gas emissions account for most of all anthropogenic emissions, this paper aims to evaluate the effectiveness of this trading mechanism at the plant level to support relevant decision-making and mechanism design. Design/methodology/approach This paper constructs a novel spatiotemporal data set by matching satellite-based high-resolution (1 × 1 km) CO2 and PM2.5 emission data with accurate geolocation of power plants. It then applies a difference-in-differences model to analyse the impact of carbon trading mechanism on emission reduction for the power industry in China from 2007 to 2016. Findings Results suggest that the carbon trading mechanism induces 2.7% of CO2 emission reduction and 6.7% of PM2.5 emission reduction in power plants in pilot areas on average. However, the reduction effect is significant only in coal-fired power plants but not in gas-fired power plants. Besides, the reduction effect is significant for power plants operated with different technologies and is more pronounced for those with outdated production technology, indicating the strong potential for green development of backward power plants. The reduction effect is also more intense for power plants without affiliation relationships than those affiliated with particular manufacturers. Originality/value This paper identifies the causal relationship between the carbon trading mechanism and emission reduction in the power industry by providing an innovative methodology for identifying plant-level emissions based on high-resolution satellite data, which has been practically absent in previous studies. It serves as a reference for stakeholders involved in detailed policy formulation and execution, including policymakers, power plant managers and green investors.