<p>China’s electric power sector plays a pivotal role in the country’s transition to carbon neutrality. Accurate projections of electricity carbon emission factors with high temporal and spatial resolution are critical for assessing the decarbonization process of not only the power sector but also other sectors such as transportation, building, and industrial manufacturing. Existing datasets primarily focus on historical averages and lack high-resolution forecasts for future emissions. This study presents a comprehensive dataset of projected hourly electricity carbon emission factors for China from 2025 to 2060, offering a temporal resolution of one hour and covering 31 provinces. The dataset, consisting of annual 8760 hourly carbon emission factors for five power system development scenarios, is generated using a simulation method that combines power system planning and operational models. These models account for the future development of the power system, including generation-grid-load-storage co-optimization, and carbon emission flow calculations to derive high-resolution factors. The methodology’s accuracy is validated by comparing simulated emission factors with official data, yielding Mean Absolute Percentage Errors (MAPEs) below 2.525%.</p>

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High temporal and spatial resolution projected electricity carbon emission factors of China from 2025–2060

  • Yaowang Li,
  • Shixu Zhang,
  • Weiran Li,
  • Yuliang Liu,
  • Yuting Qin,
  • Hongyi Wei,
  • Chongqing Kang,
  • Ning Zhang,
  • Ershun Du

摘要

China’s electric power sector plays a pivotal role in the country’s transition to carbon neutrality. Accurate projections of electricity carbon emission factors with high temporal and spatial resolution are critical for assessing the decarbonization process of not only the power sector but also other sectors such as transportation, building, and industrial manufacturing. Existing datasets primarily focus on historical averages and lack high-resolution forecasts for future emissions. This study presents a comprehensive dataset of projected hourly electricity carbon emission factors for China from 2025 to 2060, offering a temporal resolution of one hour and covering 31 provinces. The dataset, consisting of annual 8760 hourly carbon emission factors for five power system development scenarios, is generated using a simulation method that combines power system planning and operational models. These models account for the future development of the power system, including generation-grid-load-storage co-optimization, and carbon emission flow calculations to derive high-resolution factors. The methodology’s accuracy is validated by comparing simulated emission factors with official data, yielding Mean Absolute Percentage Errors (MAPEs) below 2.525%.