Wang Weijun, Tang Qing, Gao Bing
Department of Economics and Management, North China Electric Power University, Baoding, 071003 Hebei China.
Hengshui Power Supply Branch of State Grid Hebei Electric Power Co., Ltd, Hengshui, 053000 Hebei China.
Clean Technol Environ Policy. 2022 Dec 15:1-15. doi: 10.1007/s10098-022-02456-1.
Low-carbon development of China's power sector is the key to achieving carbon peaking and carbon neutrality goals. Based on the logarithmic mean divisor index (LMDI) model, considering the carbon transfer caused by inter-provincial electricity trading, this paper analyzes the influencing factors of CO emissions in the provincial power sector and uses K-means clustering method to divide 30 provinces into four categories to analyze the differences in regional carbon emission characteristics. In addition, by establishing different development scenarios, the carbon emission trends and emission reduction potentials of each cluster under different emission reduction measures from 2020 to 2040 are studied, in order to explore the differentiated emission reduction paths of each cluster. The results show that the contribution of influencing factors shows great differences in different provinces. Trends in CO emissions vary widely across scenarios. In the reference scenario, the CO emissions of each cluster will continue to increase; in the existing policy scenario, the total power industry will peak at 6.1Gt in 2030; in the advance peak scenario that puts more emphasis on the development of advanced technologies and renewable energy under the clean development model, the carbon emission peak will be brought forward to 2025, and the peak will be reduced to 5.2Gt. Finally, differentiated emission reduction paths and measures are proposed for the future low-carbon development of different cluster power industries, providing theoretical reference for the deployment of provincial-level emission reduction work, which is of great significance to the global green and low-carbon transformation.
The online version contains supplementary material available at 10.1007/s10098-022-02456-1.
中国电力部门的低碳发展是实现碳达峰和碳中和目标的关键。基于对数平均除数指数（LMDI）模型，考虑到省际电力交易引起的碳转移，本文分析了省级电力部门碳排放的影响因素，并采用K均值聚类方法将30个省份分为四类，以分析区域碳排放特征的差异。此外，通过建立不同的发展情景，研究了2020年至2040年不同减排措施下各集群的碳排放趋势和减排潜力，以探索各集群的差异化减排路径。结果表明，影响因素的贡献在不同省份表现出很大差异。不同情景下的碳排放趋势差异很大。在基准情景下，各集群的碳排放将继续增加；在现有政策情景下，电力行业总量将在2030年达到61亿吨的峰值；在清洁发展模式下更加强调先进技术和可再生能源发展的提前达峰情景下，碳排放峰值将提前至2025年，峰值降至52亿吨。最后，针对不同集群电力行业未来的低碳发展提出了差异化的减排路径和措施，为省级减排工作的部署提供了理论参考，对全球绿色低碳转型具有重要意义。
在线版本包含可在10.1007/s10098-022-02456-1获取的补充材料。
