• Energy Research

Abstract This study proposes a novel analysis framework to investigate the CO2 and SO2 emission efficiency, emission reduction potential, and marginal abatement cost (MAC) of 316 coal-fired power plants in China. The comprehensive analysis framework is based on the combined approach of utilizing the directional output distance function (DODF) and parametric linear programming (PLP). The average emission efficiencies of CO2 and SO2 were 0.48 and 0.61, respectively, which indicates that China’s coal-fired power plants have a large potential to reduce CO2 and SO2 emissions, on average by 52% and 39%, respectively. In 2010, the average CO2 and SO2 emissions reduction potential for the 316 investigated power plants were 1,517 kt and 3,773 t, respectively. The average MAC prices for CO2 and SO2 were estimated to be 598 yuan/tonne and 22,401 yuan/tonne, respectively, indicating that the reduction of such emissions is very expensive. Furthermore, I formulated an optimization problem for maximizing CO2 and SO2 emission reductions under the governmental budget constraint. Solving this optimization problem yielded the total cost for the maximum reductions of CO2 and SO2 emissions, the maximum possible reductions for CO2 and SO2 emissions for each allocated budget scale, and the optimal budget allocation for each power plant at a given budget scale. I finally suggest effective mitigation strategies for CO2 and SO2 emissions generated from China’s coal-fired power plants.

Abstract This study conducts an environmental efficiency analysis of 104 coal-fired power plants in China by simultaneously considering multiple undesirable outputs (CO2, SO2, NOx, and PM2.5 emissions) generated during the production process and the heterogeneity caused by differences between the five major power generation companies (Datang, Guodian, Huadian, Huaneng, and Power Investment). In the empirical study, slacks-based data envelopment analysis (DEA) was employed to investigate the “total” and individual CO2, SO2, NOx, and PM2.5 “specific” environmental inefficiency scores for each power plant. These scores allow us to identify which undesirable outputs are the main sources of total environmental inefficiency for each company and power plant. The results show that inefficient PM2.5 and SO2 emissions are the main sources of environmental inefficiency for many plants. Furthermore, a meta-frontier DEA decomposition framework is adopted to identify whether the source of total environmental inefficiency for each power plant is due to technological gaps between the five major power generation companies or managerial gaps within the same power generation company. The results imply that, in most cases, managerial gaps within the same power generation company account for a larger proportion of total environmental inefficiency for each power plant. These findings are used to provide comprehensive policy suggestions for government and corporate managers to improve the environmental efficiency of power plants.

This study applies data envelopment analysis (DEA) to estimate the technical efficiency (TE) and CO2 emission reduction potential of 1270 coal-fired power plants in 28 Chinese provinces and municipalities. The large dataset used in the study includes 727 combined heat and power (CHP) plants and 543 thermal power plants. Results show an average TE score of 0.57 for the CHP power plants and 0.58 for the thermal power plants, suggesting a significant potential to reduce coal consumption in both types of coal-fired plants. Total CO2 emission reduction potential was estimated to be 953 Mt-CO2, or 19% of the total CO2 emissions of China's electricity and heat producing sectors, indicating that China's coal-fired power plants have a significant potential to mitigate CO2 emissions through technological improvement. In the second stage of the study, a Tobit regression analysis was conducted to identify the determinants of TE. Factors such as the plant's annual operation rate and capacity utilization rate were found to be significant influences. Based on our results, we propose that the Chinese government create a power distribution structure that generates electricity using technologically efficient equipment in areas rich in coal resources and distributes the generated electricity to other areas of the country.