Effect of installed capacity size on environmental efficiency across 528 thermal power stations in North China

  • Chao Wu
  • Keunyeob OhEmail author
  • Xingle LongEmail author
  • Jing Zhang
Research Article


Thermal power plants are the main source of carbon dioxide emissions in China. Beijing-Tianjin-Hebei and their neighborhood provinces are the most polluted regions in China. Environmental efficiencies of 528 thermal power plants were evaluated through metafrontier epsilon-based measure, which aimed to overcome the invalid inferences of radial or non-radial model. We also analyzed the heterogeneity of environmental efficiency across different regions by considering environmental technology differences. Bootstrap regression was used in order to testify three different hypotheses to address the disadvantages of conventional regression. We found that environmental efficiency in Beijing and Tianjin is higher than the other regions and is becoming divergent. In addition, coal consumption intensity negatively affects environmental efficiency. Large-scale power stations are more environmental efficient than smaller ones. Longer equipment utilization hour can enhance energy performance of power stations, which can decrease carbon emissions and increase environmental efficiency. It is better to promote technology transfer from regions with higher environmental efficiency to regions with lower environmental efficiency. Low-carbon technologies should be promoted to decrease carbon emissions.


: Heterogeneity Divergent Size Coal consumption intensity 


Funding information

We acknowledge the support of the National Natural Science Foundation of China (Nos. 71803068, 71603105, 71911540483), the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2018S1A5A2A03036952), the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2014K2A2A2000766), the Natural Science Foundation of Jiangsu, China (No. SBK2016042936), the Science Foundation of Ministry of Education of China (No. 16YJC790067), and China Postdoctoral Science Foundation (No. 2017M610051, 2018T110054).


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Finance and EconomicsJiangsu UniversityZhenjiangChina
  2. 2.College of Economics and ManagementChungnam National UniversityDaejeonKorea
  3. 3.School of ManagementJiangsu UniversityZhenjiangChina

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