除数指数
解耦(概率)
碳纤维
能量强度
温室气体
能源消耗
发射强度
自然资源经济学
环境科学
经济
化学
工程类
数学
算法
复合数
离子
生态学
有机化学
控制工程
电气工程
生物
作者
Ankang Miao,Yue Yuan,Han Wu,Xin Ma,Chenyu Shao,Sheng Xiang
出处
期刊:Energy
[Elsevier BV]
日期:2024-04-24
卷期号:298: 131417-131417
被引量:8
标识
DOI:10.1016/j.energy.2024.131417
摘要
This study establishes the LEAP-Jiangsu model and uses the improved multilevel logarithmic mean Divisia index, Tapio decoupling, and synergistic effect models to explore the carbon reduction paths. The improved multilevel logarithmic mean Divisia index model analyzed the influencing factors of the historical and future carbon emissions. A provincial LEAP model was established to predict the time and value of carbon emission peaks. The Tapio decoupling and synergistic effect models were used to clarify the relationship between carbon emissions and economic development, the synergistic effect of carbon and pollutant reduction, and the terminal sector's carbon reduction potential. The results show that Jiangsu Province will most likely achieve carbon peaking in 2025∼2030, and the peak carbon emission is about 792∼853.9Mt. Terminal energy intensity, power production structure, and terminal energy consumption structure are the main influencing factors of carbon reduction, with a cumulative contribution rate of about 74.4%∼83.5%. The power production structure is critical in promoting the decoupling of economic development and carbon emissions. The contribution rates of energy intensity reduction, industrial structure optimization, improving terminal electrification level, and energy structure adjustment are 30.3%, 26.2%, 20.9%, and 17%, respectively. Coordinating carbon reduction measures will have better synergistic carbon and pollutant reduction effects.
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