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长江中游城市群工业碳排放空间关联及其影响因素

Spatial Network Structure of Industrial Carbon Emission of Urban Agglomerations in the Middle Reaches of the Yangtze River and Its Influencing Factors
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摘要 厘清工业碳排放空间网络结构特征及影响因素,能为推进区域工业协同减排提供参考。该文基于2011-2020年长江中游城市群地级市工业碳排放数据,借助社会网络分析法揭示长江中游城市群工业碳排放空间网络结构特征及其影响因素。研究表明:(1)2011-2020年长江中游城市群工业碳排放呈现出复杂的网络结构特征;(2)长沙和武汉等城市在长江中游城市群工业碳排放空间关联网络中居于核心地位,而鹰潭和上饶等城市处于网络的边缘地位;(3)空间地理距离、经济发展水平、城镇化水平、产业结构和对外开放水平等共同驱动着工业碳排放空间关联关系的形成。 Clarifying the spatial network characteristics and influencing factors of industrial carbon emissions can provide reference for promoting regional industrial collaborative emission reduction.Based on the industrial carbon emission data of 29 prefecture-level cities in the middle reaches of the Yangtze River from 2011 to 2020,the methods of social network analysis(SNA)and quadratic assignment procedure(QAP)are used for exploring the spatial correlation and influencing factors of industrial carbon emission of city clusters in the middle reaches of the Yangtze River.The results showed that industrial carbon emissions of city clusters in the middle reaches of the Yangtze River show a complex network structure from 2011 to 2020.Changsha and Wuhan occupy a core position in the spatial correlation network of industrial carbon emissions in the middle reaches of the Yangtze River,while Yingtan and Shangrao occupy a marginal position in the network.Spatial distance relationship,economic development level,urbanization level,industrial structure and opening to the outside world jointly drive the formation of industrial carbon emission spatial correlation.
作者 陆杉 李雯 LU Shan;LI Wen(School of Resources and Environment,Hunan University of Technology and Business,Changsha 410205,China;School of Economics and Trade,Hunan University of Technology and Business,Changsha 410205,China)
出处 《环境科学与技术》 CAS CSCD 北大核心 2023年第8期227-236,共10页 Environmental Science & Technology
基金 国家社会科学基金项目(20BJY123) 湖南省教育厅重点项目(21A0377)
关键词 工业碳排放 城市群 空间关联 社会网络分析 industrial carbon emissions urban agglomerations spatial correlation social network analysis
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