基于地理探测器的中国碳排放时空分布特征及驱动因素研究  

Research on Spatial-Temporal Distribution and the Driving Factors of CO_(2) Emissions in China Based on Geographic Detector

作　　者：田娟娟 张金锁[2,3] TIAN Juanjuan;ZHANG Jinsuo(College of Energy Engineering,Xi’an University of Science and Technology,Xi’an Shaanxi 710054,China;Research Center for Energy Economy and Management,Xi’an University of Science and Technology,Xi’an Shaanxi 710054,China;School of Economics and Management,Yan’an University,Yan’an Shaanxi 716000,China)

机构地区：[1]西安科技大学能源学院,陕西西安710054 [2]西安科技大学能源经济与管理研究中心,陕西西安710054 [3]延安大学经济管理学院,陕西延安716000

出　　处：《生态经济》2022年第7期13-20,27,共9页Ecological Economy

基　　金：国家自然科学基金项目“不确定条件下我国重要能源资源供给安全管理的理论与政策研究”(71273206);国家自然科学基金项目“生态环境约束下我国煤炭跨期最优开采规模及保障机制研究”(71704140);教育部人文社会科学研究青年基金项目“省际视角下中国煤炭产能动态优化机理与政策研究”(20YJC630190)。

摘　　要：基于30个省份的面板数据,分别运用探索性空间数据分析法及地理探测器考察了我国省域碳排放时空分布特征与驱动因素,结果表明:(1)我国碳排放空间分异及空间相关特征显著,初期呈现“西低东高”“北高南低”特征,而后高值区逐渐向东南及西北省份移动。(2)碳排放热点区主要聚集于华北、长三角、河南、山东等地,冷点聚集程度逐年下降。(3)经济发展、环境规制及固定资产投资是碳排放空间分异的主要驱动因子,产业结构的解释力度最小,且多数因子在与其他因子空间叠加后会产生非线性增强作用。(4)经济发展、人口规模、产业结构、能源强度、固定资产投资、外商投资的高值区,碳排放量均处于较高水平。Based on the panel data of 30 provinces in China,we employ exploratory spatial data analysis(ESDA)with geographic detector so as to investigate the spatial-temporal characteristics and driving factors of carbon emissions.The results are as follows:(1)There are significant spatial heterogeneity and spatial dependency characteristics of China’s CO_(2)emissions,which are low in the west and the south,high in the east and the north in the initial stage,then the high value areas gradually move to the southeast and northwest provinces.(2)The carbon emissions hotspots are mainly located in North China,Yangtze River Delta,Henan,Shandong and other regions,while the degree of cold spot aggregation is decreasing year by year.(3)The economic development,environmental regulation and fixed asset investment are major driving factors of spatial heterogeneity characteristic,while the industrial structure has the least influence.Furthermore,most of the factors will produce nonlinear enhancement effect after superposition with other factors subspace.(4)Provinces with higher value of economic development,population size,industrial structure,energy intensity,fixed asset investment and foreign investment have higher carbon emissions.

关 键 词：碳排放 空间相关性 地理探测器 驱动因素 

分 类 号：F062.2[经济管理—政治经济学]