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<p>The power sector is a major contributor to global energy use and greenhouse gas emissions. In 2020, China’s power sector accounted for over 40% of national carbon emissions, underscoring the importance of its decarbonization for achieving global climate targets. Effective emission-reduction policies require detailed and reliable carbon data. Given China’s “top-down” target-setting system, accurate regional data are essential for designing differentiated local policies and evaluating their effectiveness. In this study, we systematically estimate CO<sub>2</sub> emissions from the power sector in 352 Chinese cities from 2000 to 2019, providing broader spatial and temporal coverage than existing datasets. Using a particle swarm optimization–back propagation algorithm, we established relationships among provincial and prefectural power generation, socioeconomic indicators, and operating revenue for the electricity and heat production and supply sectors. City-level power generation was derived based on provincial training results, combined with the 2021 electricity CO<sub>2</sub> emissions factor published by the Ministry of Ecology and Environment and the National Bureau of Statistics, providing a valuable foundation for regional low-carbon research and policymaking.</p>

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China’s City-level CO2 emissions from power sector between 2000 and 2019

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月1日

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  • Boyang Chen,
  • Ming Gao,
  • Yu Liu,
  • Jiafu An,
  • Zhengxian Zhang

摘要

The power sector is a major contributor to global energy use and greenhouse gas emissions. In 2020, China’s power sector accounted for over 40% of national carbon emissions, underscoring the importance of its decarbonization for achieving global climate targets. Effective emission-reduction policies require detailed and reliable carbon data. Given China’s “top-down” target-setting system, accurate regional data are essential for designing differentiated local policies and evaluating their effectiveness. In this study, we systematically estimate CO2 emissions from the power sector in 352 Chinese cities from 2000 to 2019, providing broader spatial and temporal coverage than existing datasets. Using a particle swarm optimization–back propagation algorithm, we established relationships among provincial and prefectural power generation, socioeconomic indicators, and operating revenue for the electricity and heat production and supply sectors. City-level power generation was derived based on provincial training results, combined with the 2021 electricity CO2 emissions factor published by the Ministry of Ecology and Environment and the National Bureau of Statistics, providing a valuable foundation for regional low-carbon research and policymaking.