[Analysis of Influencing Factors of Regional Carbon Emissions in China Based on Emission Reduction Level Indexes].

Q2 Environmental Science
Yu-Cong Jiang, Yan-Ying Li, Shun-Ping Wang, Yu-Xin Yang
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引用次数: 0

Abstract

China has put forward the strategic goal of achieving carbon peak by 2030 and carbon neutrality by 2060, and study of the CO2 emission reduction potential is crucial for China and provincial regions to realize the dual-carbon goal. In this study, 30 provinces (autonomous regions and municipalities directly under the central government) in China are used as the research objects, and a regional carbon emission reduction potential evaluation system is constructed. Based on the BP neural network under the CRITIC coefficient of variation method, the provincial emission reduction index is calculated, combined with the cluster analysis of the differences in regional emission reduction potentials, and the SSA-XGBoost model is set up to investigate the factors influencing regional carbon emissions in China and their degree of influence. The results of the study include the following: ① The regional carbon emission reduction level index has a significant spatial correlation. The average carbon emission reduction value is higher in the southeastern coastal provinces, and the inland provinces with more backward economic development have more low values. ② China's 30 provincial-level regions are divided into four emission reduction potential categories, including Shandong, Guangdong, Hebei, Jiangsu, Zhejiang, Fujian, Henan, Hubei, Hunan, and Sichuan with good and excellent emission reduction potentials, which are the main driving forces for realizing the "double carbon" goal, and 14 provinces with average emission reduction potential. The degree of influence on carbon emissions has the following order: energy structure > digital structure > infrastructure structure > industrial structure > resource structure > population structure > economic structure. Energy structure as an influencing factor has the strongest potential to reduce carbon emissions in the industry category, infrastructure structure has a higher degree of influence in the optimization of the environment category, and population structure is more important than digital structure in the social category. The results show that China's carbon emission reduction level is characterized by uneven development regionally, cleaner energy, and a higher influence of social digitalization. To realize benign and efficient transformation and green development of the provinces and the country, it is suggested that the characteristics of provinces with strong emission reduction capacity should gradually be extended to the average and poorer provinces.

[基于减排水平指标的中国区域碳排放影响因素分析]。
中国提出了到2030年实现碳峰值、到2060年实现碳中和的战略目标,研究二氧化碳减排潜力对中国和各省实现双碳目标至关重要。本研究以中国30个省(区、市)为研究对象,构建区域碳减排潜力评价体系。基于CRITIC变异系数法下的BP神经网络,计算各省减排指数,结合区域减排潜力差异的聚类分析,建立SSA-XGBoost模型,研究中国区域碳排放的影响因素及其影响程度。研究结果表明:①区域碳减排水平指数具有显著的空间相关性。东南沿海省份的平均碳减排值较高,经济发展较为落后的内陆省份碳减排值较低。②将全国30个省级地区划分为4个减排潜力类别,其中减排潜力较好和较优的是山东、广东、河北、江苏、浙江、福建、河南、湖北、湖南、四川,是实现“双碳”目标的主要动力;减排潜力一般的有14个省份。影响碳排放的程度依次为:能源结构>;数字结构>;基础设施结构>;产业结构>;资源结构>;人口结构>;经济结构。能源结构作为影响因素在产业类别中碳减排潜力最强,基础设施结构在环境类别优化中影响程度更高,人口结构在社会类别中比数字结构更重要。结果表明,中国碳减排水平具有区域发展不平衡、能源清洁、社会数字化影响较大的特征。为实现各省和国家的良性高效转型和绿色发展,建议将减排能力强省份的特色逐步向中等偏贫省份推广。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
环境科学
环境科学 Environmental Science-Environmental Science (all)
CiteScore
4.40
自引率
0.00%
发文量
15329
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