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Driving Factors of CO 2 Emissions in China’s Power Industry: Relative Importance Analysis Based on Spatial Durbin Model

Author

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  • Yuanying Chi

    (School of Economics and Management, Beijing University of Technology, Beijing 100124, China)

  • Wenbing Zhou

    (School of Economics and Management, Beijing University of Technology, Beijing 100124, China)

  • Songlin Tang

    (Economic School, Shandong Technology and Business University, Yantai 264005, China)

  • Yu Hu

    (School of Economics and Management, Beijing University of Technology, Beijing 100124, China)

Abstract

The low-carbon transformation of the power industry is of great significance to realize the carbon peak in advance. However, almost a third of China’s CO 2 emissions came from the power sector in 2019. This paper aimed to identify the key drivers of CO 2 emissions in China’s power industry with the consideration of spatial autocorrelation. The spatial Durbin model and relative importance analysis were combined based on Chinese provincial data from 2003 to 2019. This combination demonstrated that GDP, the power supply structure and energy intensity are the key drivers of CO 2 emissions in China’s power industry. The self-supply ratio of electricity and the spatial spillover effect have a slight effect on increasing CO 2 emissions. The energy demand structure and CO 2 emission intensity of thermal power have a positive effect, although it is the lowest. Second, the positive impact of GDP on CO 2 emissions is decreasing, but that of the power supply structure and energy intensity is increasing. Third, the energy demand of the industrial and residential sectors has a greater impact on CO 2 emissions than that of construction and transportation. For achieving the CO 2 emission peak in advance, governments should give priority to developing renewable power and regional electricity trade rather than upgrading thermal power generation. They should also focus on promoting energy-saving technology, especially tapping the energy-saving potential of the industry and resident sectors.

Suggested Citation

  • Yuanying Chi & Wenbing Zhou & Songlin Tang & Yu Hu, 2022. "Driving Factors of CO 2 Emissions in China’s Power Industry: Relative Importance Analysis Based on Spatial Durbin Model," Energies, MDPI, vol. 15(7), pages 1-15, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2631-:d:786629
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    as
    1. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2019. "Modelling dynamic impacts of urbanization on disaggregated energy consumption in China: A spatial Durbin modelling and decomposition approach," Energy Policy, Elsevier, vol. 133(C).
    2. Xie, Pinjie & Yang, Fan & Mu, Zhuowen & Gao, Shuangshuang, 2020. "Influencing factors of the decoupling relationship between CO2 emission and economic development in China’s power industry," Energy, Elsevier, vol. 209(C).
    3. Li, Jinying & Li, Sisi, 2020. "Energy investment, economic growth and carbon emissions in China—Empirical analysis based on spatial Durbin model," Energy Policy, Elsevier, vol. 140(C).
    4. Jia, Zhijie & Lin, Boqiang, 2021. "The impact of removing cross subsidies in electric power industry in China: Welfare, economy, and CO2 emission," Energy Policy, Elsevier, vol. 148(PB).
    5. Park, Jongmun & Yun, Sun-Jin, 2022. "Social determinants of residential electricity consumption in Korea: Findings from a spatial panel model," Energy, Elsevier, vol. 239(PE).
    6. Tang, Songlin & Zhou, Wenbing & Li, Xinjin & Chen, Yingchao & Zhang, Qian & Zhang, Xiliang, 2021. "Subsidy strategy for distributed photovoltaics: A combined view of cost change and economic development," Energy Economics, Elsevier, vol. 97(C).
    7. Tang, Baojun & Li, Ru & Yu, Biying & An, Runying & Wei, Yi-Ming, 2018. "How to peak carbon emissions in China's power sector: A regional perspective," Energy Policy, Elsevier, vol. 120(C), pages 365-381.
    8. Lin, Boqiang & Bega, François, 2021. "China's Belt & Road Initiative coal power cooperation: Transitioning toward low-carbon development," Energy Policy, Elsevier, vol. 156(C).
    9. Zhao, Pengjun & Zeng, Liangen & Li, Peilin & Lu, Haiyan & Hu, Haoyu & Li, Chengming & Zheng, Mengyuan & Li, Haitao & Yu, Zhao & Yuan, Dandan & Xie, Jinxin & Huang, Qi & Qi, Yuting, 2022. "China's transportation sector carbon dioxide emissions efficiency and its influencing factors based on the EBM DEA model with undesirable outputs and spatial Durbin model," Energy, Elsevier, vol. 238(PC).
    10. Zhao, Jun & Jiang, Qingzhe & Dong, Xiucheng & Dong, Kangyin & Jiang, Hongdian, 2022. "How does industrial structure adjustment reduce CO2 emissions? Spatial and mediation effects analysis for China," Energy Economics, Elsevier, vol. 105(C).
    11. Xu, Jin-Hua & Yi, Bo-Wen & Fan, Ying, 2020. "Economic viability and regulation effects of infrastructure investments for inter-regional electricity transmission and trade in China," Energy Economics, Elsevier, vol. 91(C).
    12. Ninpanit, Panittra & Malik, Arunima & Wakiyama, Takako & Geschke, Arne & Lenzen, Manfred, 2019. "Thailand’s energy-related carbon dioxide emissions from production-based and consumption-based perspectives," Energy Policy, Elsevier, vol. 133(C).
    13. Tang, Liwei & He, Gang, 2021. "How to improve total factor energy efficiency? An empirical analysis of the Yangtze River economic belt of China," Energy, Elsevier, vol. 235(C).
    14. Liu, Xianmei & Peng, Rui & Zhong, Chao & Wang, Mingyue & Guo, Pibin, 2021. "What drives the temporal and spatial differences of CO2 emissions in the transport sector? Empirical evidence from municipalities in China," Energy Policy, Elsevier, vol. 159(C).
    15. Croonenbroeck, Carsten & Palm, Marcel, 2020. "A spatio-temporal Durbin fixed effects IV-Model for ENTSO-E electricity flows analysis," Renewable Energy, Elsevier, vol. 148(C), pages 205-213.
    16. Pellini, Elisabetta, 2021. "Estimating income and price elasticities of residential electricity demand with Autometrics," Energy Economics, Elsevier, vol. 101(C).
    17. Espoir, Delphin Kamanda & Sunge, Regret, 2021. "CO₂ Emissions and Economic Development in Africa: Evidence from A Dynamic Spatial Panel Model," EconStor Preprints 234131, ZBW - Leibniz Information Centre for Economics.
    18. Wu, Haitao & Xu, Lina & Ren, Siyu & Hao, Yu & Yan, Guoyao, 2020. "How do energy consumption and environmental regulation affect carbon emissions in China? New evidence from a dynamic threshold panel model," Resources Policy, Elsevier, vol. 67(C).
    19. Tan, Zhongfu & Li, Li & Wang, Jianjun & Wang, Jianhui, 2011. "Examining the driving forces for improving China’s CO2 emission intensity using the decomposing method," Applied Energy, Elsevier, vol. 88(12), pages 4496-4504.
    20. Wang, Zhaoxia & Zhu, Han & Ding, Yan & Zhu, Tianli & Zhu, Neng & Tian, Zhe, 2018. "Energy efficiency evaluation of key energy consumption sectors in China based on a macro-evaluating system," Energy, Elsevier, vol. 153(C), pages 65-79.
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    2. Liu, Xiaohong & Yang, Jiangjiang & Xu, Chengzhen & Li, Xingchen & Zhu, Qingyuan, 2023. "Environmental regulation efficiency analysis by considering regional heterogeneity," Resources Policy, Elsevier, vol. 83(C).

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