江苏省县域碳排放时空演化及影响因素分析  

The Spatiotemporal Pattern Evolution and Influencing Factors of Carbon Emissions at the County Level in Jiangsu Province

作　　者：李建豹 揣小伟[2] 周艳 LI Jianbao;CHUAI Xiaowei;ZHOU Yan(School of Public Administration,Nanjing University of Finance&Economics,Nanjing Jiangsu 210023,China;College of Geography and Oceanography Sciences,Nanjing University,Nanjing Jiangsu 210023,China;Faculty of Geography,Yunnan Normal University,Kunming Yunnan 650050,China)

机构地区：[1]南京财经大学公共管理学院,江苏南京210023 [2]南京大学地理与海洋科学学院,江苏南京210023 [3]云南师范大学地理学部,云南昆明650050

出　　处：《生态经济》2023年第7期36-44,共9页Ecological Economy

基　　金：国家自然科学基金项目“多尺度视角下长三角地区城镇化碳排放效应及调控策略研究”(41901245);江苏高校哲学社会科学研究一般项目“多尺度视角下城镇化对碳排放影响机理及调控策略研究——以江苏省为例”(2019SJA0254);教育部人文社会科学青年基金“土地市场对城市建设用地扩张影响的尺度效应及调控机制研究——以成渝城市群为例”(20YJCZH250)。

摘　　要：掌握县域碳排放时空演化规律及影响因素,对制定符合区域特点的低碳调控政策,推进低碳发展与可持续发展具有重要意义。在ESTDA框架下,研究2000—2017年江苏省县域碳排放时空演化特征,并构建HSAR模型,分析其影响因素。结果表明:(1)碳排放的绝对差异和相对差异总体上均呈增加趋势,空间集聚性呈波动变化,各县域碳排放呈增加趋势。(2)碳排放空间差异明显,较高值区主要分布在苏南地区。LISA时空跃迁分析表明,碳排放的时空结构存在较强的空间锁定效应和“俱乐部趋同”现象。(3)人均GDP、年末总人口和碳排放强度对碳排放具有显著的正向作用,土地城镇化对碳排放具有显著的负向作用。Mastering the spatiotemporal evolution laws and influencing factors of carbon emissions at the county level is of great significance for formulating low-carbon control policies that conform to regional characteristics and promoting low-carbon and sustainable development.Under the framework of ESTDA,this study investigated the spatiotemporal evolution characteristics of carbon emissions at the county level in Jiangsu Province from 2000 to 2017,and the hierarchical spatial autoregressive model was constructed to analyze its influencing factors.The results are shown as follows:(1)Both the absolute difference and the relative difference of carbon emissions showed an increasing trend.The spatial agglomeration of carbon emissions showed a fluctuating trend.Carbon emissions in each county were increasing.(2)There was obvious spatial disparity in carbon emissions,and the areas with higher carbon emissions were mainly distributed in southern Jiangsu.The LISA spatiotemporal transition analysis shows that the spatiotemporal structure of carbon emissions had a strong spatial locking effect and the phenomenon of“club convergence”.(3)GDP per capita,total population at the end of the year,and carbon intensity have a significant positive effect on carbon emissions,and land urbanization has a significant negative effect on carbon emissions.

关 键 词：县域 碳排放 时空演化 影响因素 ESTDA 

分 类 号：F124.5[经济管理—世界经济] X321[环境科学与工程—环境工程]