Pathway and Policy for China's Provincial Carbon Emission Peak

被引：4
|
作者：
Miao A.-K. [1 ]
Yuan Y. [1 ]
Wu H. [2 ]
Ma X. [1 ]
Shao C.-Y. [1 ]
机构：
[1] College of Energy and Electrical Engineering, Hohai University, Nanjing
[2] Smart Grid Research Institute, Nanjing Institute of Technology, Nanjing
来源：
Huanjing Kexue/Environmental Science | 2023年 / 44卷 / 08期
关键词：
carbon emission peak path; LEAP-Jiangsu model; M-LMDI model; pollutant reduction; synergistic effect of the carbon; Tapio decoupling index;
D O I：
10.13227/j.hjkx.202208273
中图分类号：
学科分类号：
摘要：
An effective way for China to achieve a carbon emission peak by 2030 is to encourage developed regions to take the lead in attaining carbon peaking at the regional level. Considering Jiangsu Province as an example, this study established a provincial low emissions analysis platform (LEAP-Jiangsu) model. It combined the improved multilevel logarithmic mean Divisia index (M-LMDI) model, Tapio decoupling model, and the synergistic effect of pollution and carbon reduction model to explore the key influencing factors of carbon emissions and carbon reduction paths. The improved M-LMDI model was used to analyze the factors influencing historical and future carbon emissions in Jiangsu Province. Based on the analysis results and planning objectives, a LEAP-Jiangsu model involving various development scenarios 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 air pollutant emission reduction. The prediction results demonstrated that the total primary energy demand of Jiangsu Province in 2035 was predicted to be approximately 401. 2-474. 6 Mt, and the final energy demand would be approximately 319. 2-382. 3 Mt. Jiangsu Province was most likely to achieve the goal of carbon peaking in 2025-2030, and the peak carbon emission was approximately 815. 3-845. 7 Mt. The contribution rates of energy conservation and emission reduction measures such as energy intensity reduction, industrial structure optimization, terminal electrification improvement, and energy structure adjustment were 33. 1%, 26. 8%, 21%, and 15. 2%, respectively. © 2023 Science Press. All rights reserved.
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页码：4623 / 4646
页数：23
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