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Among the G20 countries, China is the only country to experience an increase in electricity generation from coal-fired thermal power plants from 2019 to 2020. This study aims to develop an analytical framework combining metafrontier data envelopment analysis with the logarithmic mean Divisia index for a detailed decomposition analysis of 'mass-based' energy-related CO2 reduction potential through efficiency improvements in coal-fired thermal power plants in China. The results show that inefficiency in power generation can be largely attributed to differences in the location of power plants and the production scale. Moreover, the impact of regional heterogeneity on the changes in power generation efficiency is more notable for the small–medium power plants in the northeast region than the large power plants in the western region in China. However, when focusing on the mass-based CO2 reduction potential associated with the regional heterogeneity, its positive effects in the western region for the large power plants are 6.2 times larger than that in the northeast region for the small–medium power plants. These results imply that an analysis that focuses only on the efficiency score would ignore the production scale of coal-fired thermal power plants and thus would fail to properly evaluate the environmental impacts associated with efficiency changes. [ABSTRACT FROM AUTHOR]

China is the world's largest CO 2 emitting country, and coal-fired thermal power generation accounted for over 50% of the total electricity generation in China in 2015. This study reports the changes in the power generation efficiency of coal-fired thermal power plants in China from 2009 to 2011 and elucidates how the differences in the production scale of the power plants and regional heterogeneity affect the power generation efficiency. We propose a metafrontier data envelopment analysis (DEA) decomposition framework to investigate the sources of inefficiency in power generation. The results suggest that, on average, the power generation efficiency of large-scale power plants is 13% higher than that of small-scale power plants. Although operational inefficiency is the main source of inefficiency in eastern and central China, the technology gap - the differences in the quality of coal consumed for electricity production and in the equipment of the power plants among regions - is the main source of inefficiency in western China. This study uses the results of the framework to discuss the scrapping policies for coal-fired thermal power plants in China. For large-scale power plants in western China, the components of inefficiency vary and, thus, policymakers should consider scrapping thermal power plants based not only on the level of inefficiency but also on their components. • We propose a multi-hierarchy metafrontier DEA decomposition framework. • Change in power generation efficiency during the study period is not significant. • Power generation efficiency is strongly affected by regional heterogeneity. • The components of inefficiency vary significantly in western China. [ABSTRACT FROM AUTHOR]