山西省县域碳排放时空格局及影响因素分析  

Spatiotemporal Pattern and Influencing Factors of Carbon Emissions at County Level in Shanxi Province

作　　者：赵文婷 罗淑贞 原晓红 张强 杨方社[1] 刘跃廷 谢文豪 ZHAO Wenting;LUO Shuzhen;YUAN Xiaohong;ZHANG Qiang;YANG Fangshe;LIU Yueting;XIE Wenhao(College of Urban and Environmental Science,Northwest University,Xi'an 710127,China)

机构地区：[1]西北大学城市与环境学院,陕西西安710127

出　　处：《环境科学与技术》2022年第8期226-236,共11页Environmental Science & Technology

基　　金：国家重点研发计划项目(SQ2019YFC020023);国家自然科学基金青年科学基金项目(41807342);大气重污染成因与治理攻关项目(DQGG-05-32)。

摘　　要：文章基于2006-2017年山西省118个县域碳排放数据,采用变异系数、空间自相关分析和时空地理加权回归模型(GTWR)对山西省县域碳排放时空格局和影响因素进行分析。结果表明:时间上,2006-2012年山西省县域碳排放量增长迅速,高碳排放区逐渐扩大;2012年之后各区县碳排放量较为稳定,且稳中有降。空间上,山西省县域碳排放呈中间高、东西低的分布格局;县域碳排放存在显著的空间不平等性和集聚性,表现为逐渐下降的特征;在局部范围内具有较高的空间依赖格局,大部分碳排放高(低)的县域相邻,且汾阳市、孝义市、介休市和大同市城区存在“高碳锁定”效应。各影响因素呈现较强的时空异质性,人口规模和产业结构是碳排放的主导因素,对山西省县域均为正向影响,且产业结构的影响逐年上升;城镇化率和经济发展水平对山西省县域碳排放影响较小,且对大部分区县具有负向影响。因此,分析山西省县域碳排放时空格局演变特征和各因素对不同县域碳排放的影响程度,可为实现区域差异化碳减排政策提供指导。Based on the 118 counties’ carbon emission data in Shanxi Province from 2006 to 2017, the temporal and spatial pattern and influencing factors were analyzed using the variation coefficient, spatial autocorrelation analysis and geographically and temporally weighted regression(GTWR) model. The results show that the county carbon emissions in Shanxi Province increased rapidly from 2006 to 2012, and the high carbon emission areas gradually expanded. After 2012, the carbon emissions of all districts and counties were relatively stable and decreased steadily. The county carbon emissions in Shanxi Province are high in the middle and low in the east and west. The distribution characteristic had significant spatial inequality and clustering effect, but this phenomenon showed a gradual decline. It has a high spatial dependence pattern in a local range.Most counties with high(low) carbon emissions are adjacent to each, and there is a“high carbon locking”effect in Fenyang City, Xiaoyi City, Jiexiu City and Datong City. The influencing factors show substantial temporal and spatial heterogeneity.Population size and industrial structure are the leading factors of carbon emission. These two factors positively affect counties in Shanxi Province, and the effect of the industrial structure increases year by year. Urbanization rate and economic development level have little impact on carbon emission and harm in most districts and counties. Therefore, analyzing the evolution characteristics of temporal and spatial patterns of county carbon emission and various factors on different county carbon emissions in Shanxi Province can guide realizing regionally differentiated carbon reduction policies.

关 键 词：山西省县域 碳排放 空间自相关 GTWR模型 

分 类 号：X321[环境科学与工程—环境工程]