四川省最终能源消费产生的CO2排放影响因素及贡献分析

Q1 Social Sciences
Wei Liu , Zhijie Jia , Meng Du , Zhanfeng Dong , Jieyu Pan , Qinrui Li , Linyan Pan , Chris Umole
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引用次数: 3

摘要

在二氧化碳排放调峰和碳中和的背景下,对省级二氧化碳排放的研究较少。中国四川省不仅拥有优越的清洁能源资源禀赋,而且具有巨大的二氧化碳减排潜力。因此,采用对数平均分度指数(LMDI)模型分析不同影响因素对四川省最终能源消费CO2排放的影响程度,从而根据影响因素从不同路径制定相应的减排对策。以2010 - 2019年四川省最终能源消费数据为基础,采用间接排放计算方法计算CO2排放量。采用kaya -对数平均分裂指数(LMDI)分解模型,将四川省最终能源消费CO2排放的影响因素分解为人口规模、经济发展程度、产业结构、能源消费强度和能源消费结构。同时,采用灰色关联分析方法,确定了四川省最终能源消费产生的CO2排放量与影响因素之间的相关性。结果表明:人口规模、经济发展和能源消费结构对四川省最终能源消费CO2排放有正贡献,其中经济发展对最终能源消费CO2排放贡献显著,贡献率为519.11%;四川省产业结构和能源消费强度对CO2排放的贡献均为负,且贡献均显著,其中能源消费结构的贡献率为325.96%。从产业结构看,第二产业贡献显著,并将保持抑制作用;从能源消费结构的角度看,工业部门的贡献显著。本文的研究结果有利于四川省碳减排政策的实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Influencing factors and contribution analysis of CO2 emissions originating from final energy consumption in Sichuan Province, China

Within the context of CO2 emission peaking and carbon neutrality, the study of CO2 emissions at the provincial level is few. Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO2 emissions. Therefore, using logarithmic mean Divisia index (LMDI) model to analysis the influence degree of different influencing factors on CO2 emissions from final energy consumption in Sichuan Province, so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors. Based on the data of final energy consumption in Sichuan Province from 2010 to 2019, we calculated CO2 emission by the indirect emission calculation method. The influencing factors of CO2 emissions originating from final energy consumption in Sichuan Province were decomposed into population size, economic development, industrial structure, energy consumption intensity, and energy consumption structure by the Kaya–logarithmic mean Divisia index (LMDI) decomposition model. At the same time, grey correlation analysis was used to identify the correlation between CO2 emissions originating from final energy consumption and the influencing factors in Sichuan Province. The results showed that population size, economic development and energy consumption structure have positive contributions to CO2 emissions from final energy consumption in Sichuan Province, and economic development has a significant contribution to CO2 emissions from final energy consumption, with a contribution rate of 519.11%. The industrial structure and energy consumption intensity have negative contributions to CO2 emissions in Sichuan Province, and both of them have significant contributions, among which the contribution rate of energy consumption structure was 325.96%. From the perspective of industrial structure, secondary industry makes significant contributions and will maintain a restraining effect; from the perspective of energy consumption structure, industry sector has a significant contribution. The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.

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来源期刊
Regional Sustainability
Regional Sustainability Social Sciences-Urban Studies
CiteScore
3.70
自引率
0.00%
发文量
20
审稿时长
21 weeks
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