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Determinants of technical inefficiency in China’s coal-fired power plants and policy recommendations for CO2 mitigation

pmid: 34002311
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.
- Kyushu University Japan
- Kindai University Japan
- Renmin University of China China (People's Republic of)
- Renmin University of China China (People's Republic of)
- Kyushu University Japan
Air Pollutants, China, Carbon Dioxide, Coal, Policy, Air Pollution, Power Plants
Air Pollutants, China, Carbon Dioxide, Coal, Policy, Air Pollution, Power Plants
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).23 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
