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Energy-Related CO 2 Emission in China’s Provincial Thermal Electricity Generation: Driving Factors and Possibilities for Abatement

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  • Qingyou Yan

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Yaxian Wang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Tomas Baležentis

    (Lithuanian Institute of Agrarian Economics, Kudirkos Str. 18-2, Vilnius LT-03105, Lithuania)

  • Yikai Sun

    (State Grid Zhejiang Economy Research Institute, Hangzhou 310008, China)

  • Dalia Streimikiene

    (Lithuanian Institute of Agrarian Economics, Kudirkos Str. 18-2, Vilnius LT-03105, Lithuania)

Abstract

China’s electricity sector mainly relies on coal-fired thermal generation, thus resulting that nearly 50% of China’s total CO 2 emissions coming from the electricity sector. This study focuses on the provincial CO 2 emissions from China’s thermal electricity generation. Methodologically, Index Decomposition Analysis (IDA), facilitated by the Shapley Index, is applied to discover the driving factors behind CO 2 emission changes at the provincial level. In addition, the Slack-based Model (SBM) is used to identify which provincial power grids should be allocated with a higher (lower) CO 2 reduction burden. The IDA results indicate that economic activity pushed the CO 2 emissions up in all 30 provincial power grids, excluding Beijing and Shanghai; the carbon factor contributed to a decrease in the CO 2 emissions in all 30 provincial power grids, with the exception of Jilin, Guangdong, and Ningxia; though the effect of energy intensity varied across the 30 provinces, it played a significant role in the mitigation of CO 2 emissions in Beijing, Heilongjiang, Liaoning, Jilin, Shanghai, Anhui, and Sichuan. According to the SBM results, the lowest carbon shadow prices are observed in Yunnan, Shanghai, Inner Mongolia, Jilin, Qinghai, Guizhou, Anhui, and Ningxia. These provincial power grids, thus, should face higher mitigation targets for CO 2 emissions from thermal electricity generation.

Suggested Citation

  • Qingyou Yan & Yaxian Wang & Tomas Baležentis & Yikai Sun & Dalia Streimikiene, 2018. "Energy-Related CO 2 Emission in China’s Provincial Thermal Electricity Generation: Driving Factors and Possibilities for Abatement," Energies, MDPI, vol. 11(5), pages 1-25, April.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:5:p:1096-:d:143853
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    References listed on IDEAS

    as
    1. Shao, Shuai & Liu, Jianghua & Geng, Yong & Miao, Zhuang & Yang, Yingchun, 2016. "Uncovering driving factors of carbon emissions from China’s mining sector," Applied Energy, Elsevier, vol. 166(C), pages 220-238.
    2. Duan, Na & Guo, Jun-Peng & Xie, Bai-Chen, 2016. "Is there a difference between the energy and CO2 emission performance for China’s thermal power industry? A bootstrapped directional distance function approach," Applied Energy, Elsevier, vol. 162(C), pages 1552-1563.
    3. Yu, Shiwei & Wei, Yi-Ming & Wang, Ke, 2014. "Provincial allocation of carbon emission reduction targets in China: An approach based on improved fuzzy cluster and Shapley value decomposition," Energy Policy, Elsevier, vol. 66(C), pages 630-644.
    4. Wang, Miao & Feng, Chao, 2017. "Decomposition of energy-related CO2 emissions in China: An empirical analysis based on provincial panel data of three sectors," Applied Energy, Elsevier, vol. 190(C), pages 772-787.
    5. Ipek Tunç, G. & Türüt-AsIk, Serap & AkbostancI, Elif, 2009. "A decomposition analysis of CO2 emissions from energy use: Turkish case," Energy Policy, Elsevier, vol. 37(11), pages 4689-4699, November.
    6. Bi, Gong-Bing & Song, Wen & Zhou, P. & Liang, Liang, 2014. "Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model," Energy Policy, Elsevier, vol. 66(C), pages 537-546.
    7. Malla, Sunil, 2009. "CO2 emissions from electricity generation in seven Asia-Pacific and North American countries: A decomposition analysis," Energy Policy, Elsevier, vol. 37(1), pages 1-9, January.
    8. Li, DuoQi & Wang, DuanYi, 2016. "Decomposition analysis of energy consumption for an freeway during its operation period: A case study for Guangdong, China," Energy, Elsevier, vol. 97(C), pages 296-305.
    9. Hoekstra, Rutger & van den Bergh, Jeroen C. J. M., 2003. "Comparing structural decomposition analysis and index," Energy Economics, Elsevier, vol. 25(1), pages 39-64, January.
    10. Liu, Zhu & Geng, Yong & Lindner, Soeren & Guan, Dabo, 2012. "Uncovering China’s greenhouse gas emission from regional and sectoral perspectives," Energy, Elsevier, vol. 45(1), pages 1059-1068.
    11. Wei, Chu & Löschel, Andreas & Liu, Bing, 2013. "An empirical analysis of the CO2 shadow price in Chinese thermal power enterprises," Energy Economics, Elsevier, vol. 40(C), pages 22-31.
    12. Yan, Qingyou & Zhang, Qian & Zou, Xin, 2016. "Decomposition analysis of carbon dioxide emissions in China's regional thermal electricity generation, 2000–2020," Energy, Elsevier, vol. 112(C), pages 788-794.
    13. M. Murty & Surender Kumar & Kishore Dhavala, 2007. "Measuring environmental efficiency of industry: a case study of thermal power generation in India," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 38(1), pages 31-50, September.
    14. Su, Bin & Ang, B.W., 2014. "Attribution of changes in the generalized Fisher index with application to embodied emission studies," Energy, Elsevier, vol. 69(C), pages 778-786.
    15. Kaivo-oja, J. & Luukkanen, J. & Panula-Ontto, J. & Vehmas, J. & Chen, Y. & Mikkonen, S. & Auffermann, B., 2014. "Are structural change and modernisation leading to convergence in the CO2 economy? Decomposition analysis of China, EU and USA," Energy, Elsevier, vol. 72(C), pages 115-125.
    16. Li, Tianxiang & Baležentis, Tomas & Makutėnienė, Daiva & Streimikiene, Dalia & Kriščiukaitienė, Irena, 2016. "Energy-related CO2 emission in European Union agriculture: Driving forces and possibilities for reduction," Applied Energy, Elsevier, vol. 180(C), pages 682-694.
    17. Zhang, Ming & Liu, Xiao & Wang, Wenwen & Zhou, Min, 2013. "Decomposition analysis of CO2 emissions from electricity generation in China," Energy Policy, Elsevier, vol. 52(C), pages 159-165.
    18. Ma, Chunbo, 2014. "A multi-fuel, multi-sector and multi-region approach to index decomposition: An application to China's energy consumption 1995–2010," Energy Economics, Elsevier, vol. 42(C), pages 9-16.
    19. Wang, Junfeng & He, Shutong & Qiu, Ye & Liu, Nan & Li, Yongjian & Dong, Zhanfeng, 2018. "Investigating driving forces of aggregate carbon intensity of electricity generation in China," Energy Policy, Elsevier, vol. 113(C), pages 249-257.
    20. Goh, Tian & Ang, B.W. & Su, Bin & Wang, H., 2018. "Drivers of stagnating global carbon intensity of electricity and the way forward," Energy Policy, Elsevier, vol. 113(C), pages 149-156.
    21. Robaina Alves, Margarita & Moutinho, Victor, 2013. "Decomposition analysis and Innovative Accounting Approach for energy-related CO2 (carbon dioxide) emissions intensity over 1996–2009 in Portugal," Energy, Elsevier, vol. 57(C), pages 775-787.
    22. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "Measuring environmental performance under different environmental DEA technologies," Energy Economics, Elsevier, vol. 30(1), pages 1-14, January.
    23. Ang, B.W. & Su, Bin, 2016. "Carbon emission intensity in electricity production: A global analysis," Energy Policy, Elsevier, vol. 94(C), pages 56-63.
    24. Papagiannaki, Katerina & Diakoulaki, Danae, 2009. "Decomposition analysis of CO2 emissions from passenger cars: The cases of Greece and Denmark," Energy Policy, Elsevier, vol. 37(8), pages 3259-3267, August.
    25. Zhang, Yue-Jun & Wang, Ao-Dong & Da, Ya-Bin, 2014. "Regional allocation of carbon emission quotas in China: Evidence from the Shapley value method," Energy Policy, Elsevier, vol. 74(C), pages 454-464.
    26. Zhang, Ning & Zhou, P. & Choi, Yongrok, 2013. "Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: A meta-frontier non-radial directional distance functionanalysis," Energy Policy, Elsevier, vol. 56(C), pages 653-662.
    27. Zhifu Mi & Jing Meng & Dabo Guan & Yuli Shan & Malin Song & Yi-Ming Wei & Zhu Liu & Klaus Hubacek, 2017. "Chinese CO2 emission flows have reversed since the global financial crisis," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
    28. Andreoni, V. & Galmarini, S., 2012. "Decoupling economic growth from carbon dioxide emissions: A decomposition analysis of Italian energy consumption," Energy, Elsevier, vol. 44(1), pages 682-691.
    29. Albrecht, Johan & Francois, Delphine & Schoors, Koen, 2002. "A Shapley decomposition of carbon emissions without residuals," Energy Policy, Elsevier, vol. 30(9), pages 727-736, July.
    30. Ang, B. W. & Liu, F. L. & Chew, E. P., 2003. "Perfect decomposition techniques in energy and environmental analysis," Energy Policy, Elsevier, vol. 31(14), pages 1561-1566, November.
    31. Ke Wang & Jieming Zhang & Yi-Ming Wei, 2017. "Operational and environmental performance in China¡¯s thermal power industry: Taking an effectiveness measure as complement to an efficiency measure," CEEP-BIT Working Papers 100, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    32. Yongxiu He & Weijun Tao & Songlei Zhang & Weihong Yang & Furong Li, 2009. "Decomposition analysis of China's electricity intensity with LMDI method," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 32(1/2), pages 34-48.
    33. Zhang, Wei & Li, Ke & Zhou, Dequn & Zhang, Wenrui & Gao, Hui, 2016. "Decomposition of intensity of energy-related CO2 emission in Chinese provinces using the LMDI method," Energy Policy, Elsevier, vol. 92(C), pages 369-381.
    34. Xu, Shi-Chun & He, Zheng-Xia & Long, Ru-Yin, 2014. "Factors that influence carbon emissions due to energy consumption in China: Decomposition analysis using LMDI," Applied Energy, Elsevier, vol. 127(C), pages 182-193.
    35. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    36. Zhang, Ning & Choi, Yongrok, 2013. "Total-factor carbon emission performance of fossil fuel power plants in China: A metafrontier non-radial Malmquist index analysis," Energy Economics, Elsevier, vol. 40(C), pages 549-559.
    37. Du, Limin & Mao, Jie, 2015. "Estimating the environmental efficiency and marginal CO2 abatement cost of coal-fired power plants in China," Energy Policy, Elsevier, vol. 85(C), pages 347-356.
    38. Cai, Wenjia & Wang, Can & Chen, Jining, 2010. "Revisiting CO2 mitigation potential and costs in China's electricity sector," Energy Policy, Elsevier, vol. 38(8), pages 4209-4213, August.
    39. Wang, Qiang & Jiang, Xue-ting & Li, Rongrong, 2017. "Comparative decoupling analysis of energy-related carbon emission from electric output of electricity sector in Shandong Province, China," Energy, Elsevier, vol. 127(C), pages 78-88.
    40. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    41. Cao, Yijia & Wang, Xifan & Li, Yong & Tan, Yi & Xing, Jianbo & Fan, Ruixiang, 2016. "A comprehensive study on low-carbon impact of distributed generations on regional power grids: A case of Jiangxi provincial power grid in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 766-778.
    42. Goh, Tian & Ang, B.W., 2018. "Quantifying CO2 emission reductions from renewables and nuclear energy – Some paradoxes," Energy Policy, Elsevier, vol. 113(C), pages 651-662.
    43. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    44. Wei, Chu & Ni, Jinlan & Du, Limin, 2012. "Regional allocation of carbon dioxide abatement in China," China Economic Review, Elsevier, vol. 23(3), pages 552-565.
    45. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    46. Liu, Zhu & Liang, Sai & Geng, Yong & Xue, Bing & Xi, Fengming & Pan, Ying & Zhang, Tianzhu & Fujita, Tsuyoshi, 2012. "Features, trajectories and driving forces for energy-related GHG emissions from Chinese mega cites: The case of Beijing, Tianjin, Shanghai and Chongqing," Energy, Elsevier, vol. 37(1), pages 245-254.
    47. Yu, Yanni & Qian, Tao & Du, Limin, 2017. "Carbon productivity growth, technological innovation, and technology gap change of coal-fired power plants in China," Energy Policy, Elsevier, vol. 109(C), pages 479-487.
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