Abstract
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.
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Data availability
The data were digitized by the authors from 2014 Power Industry Statistics. The dataset is not free and not available online.
Notes
Meta-frontier DEA analysis (O'Donnell et al., 2008) is another method that differs from the combined use of DEA analysis and regression analysis to identify the sources of technical inefficiency. For example, Eguchi et al. (2021) applied meta-frontier DEA analysis to three years of input-output data for a number of Chinese power plants (567 plants in 2009, 569 plants in 2010, and 507 plants in 2011) and decomposed the sources of technical inefficiency into regional inefficiency and scale inefficiency. However, meta-frontier DEA analysis is not suitable for identifying multiple determinants, as in this study, as it may lose the robustness of the DEA results due to a decrease in sample size (Eguchi et al. 2021). The combined approach of DEA analysis and regression analysis allows us to test the statistical significance of the analysis results.
Although the produced heat from CHP power plants should be converted to its electricity equivalent, heat supply data for each CHP plant were unavailable. To overcome this problem, Zhou et al. (2012) suggests that CHP and thermal power plants should be evaluated at separate production frontiers.
The TE scores of Hunan and Sichuan provinces in the CHP model, as well as Jiangxi province in the thermal model, should be interpreted with caution due to the small dataset.
In Lam and Shiu (2004), UTILIZATION, an independent variable similar to HOUR in this study, was used in the regression model. UTILIZATION is defined as the ratio of the average annual utilization hours of the thermal power plants in each province to the total hours in a year.
In Lam and Shiu (2001), CAPACITY, an independent variable similar to LOAD in this study, was used in the regression model. CAPACITY is defined as the average load of thermal power plants in each province divided by the average installed capacity in each province.
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Acknowledgements
We are grateful to the editor and anonymous referees for their helpful comments and suggestions. We accept full responsibility for any errors in the manuscript.
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This research was supported by JSPS KAKENHI Grant Number JP20H00081.
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Tomoaki Nakaishi: conceptualization; formal analysis; investigation; methodology; project administration; software; validation; visualization; writing—original draft; writing—review & editing. Shigemi Kagawa: conceptualization; funding acquisition; formal analysis; investigation; methodology; software; validation; writing—original draft; writing—review & editing. Hirotaka Takayabu: conceptualization; formal analysis; investigation; methodology; software; validation; writing—original draft; writing—review & editing. Chen Lin: data curation; resources; validation; writing—review & editing.
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Nakaishi, T., Kagawa, S., Takayabu, H. et al. Determinants of technical inefficiency in China’s coal-fired power plants and policy recommendations for CO2 mitigation. Environ Sci Pollut Res 28, 52064–52081 (2021). https://doi.org/10.1007/s11356-021-14394-4
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DOI: https://doi.org/10.1007/s11356-021-14394-4