"双碳"背景下陕西县域碳排放时空异质性及影响因素分析OACHSSCD
Analyses on the Spatial-Temporal Heterogeneity and Influencing Factors of County-level Carbon Emissions in Shaanxi Province under the Background of"Dual Carbon"
在"双碳"背景下,陕西作为中国能源大省,其碳排放的有效控制对国家"双碳"目标至关重要.以陕西省107 个区县为研究对象,运用探索性空间数据分析(ESDA)探讨陕西县域碳排放的空间相关性与空间依赖性等,基于时空地理加权回归模型(GTWR)剖析陕西县域碳排放影响因素的时空异质性.结果显示:从时间序列来看,统计期内陕西省碳排放整体呈现增长趋势;从空间分布来看,全省碳排放呈现陕北、关中、陕南依次递减的分布格局;各区县碳排放存在显著的空间正相关性和空间集聚性,"高-高"集聚主要分布在榆林第二产业发达地区,"低-低"集聚分布在第三产业占比较大的陕南地区;各影响因素存在较强的时空异质性,人均 GDP、人口密度、对外开放程度与财政一般预算支出对陕西县域碳排放呈现显著正向作用,产业结构已初显对碳排放的抑制效应.
Under the background of"dual carbon",as a major energy province in China,Shaanxi's effec-tive control of carbon emissions is crucial to the national"dual carbon"goals.Taking 107 districts and coun-ties in Shaanxi Province as the research objects,exploratory spatial data analysis(ESDA)was used to explore the spatial correlation and spatial dependence of carbon emissions in Shaanxi counties,and the spatio-tempo-ral heterogeneity of the influencing factors of carbon emissions in Shaanxi counties was analyzed based on the spatio-temporal geographic weighted regression model(GTWR).The results show that from a time series per-spective,the carbon emissions in Shaanxi Province had generally an increasing trend during the statistical peri-od;from a spatial distribution standpoint,the carbon emissions across the province exhibited a decreasing pat-tern from the northern part to the central part and then to the southern part.There was a significant spatial posi-tive correlation and spatial clustering of carbon emissions across different districts and counties.The"high-high"clustering was mainly concentrated in the second industry-developed areas of Yulin,while the"low-low"clustering was distributed in the southern Shaanxi region where the proportion of the third industry was relatively large.There was strong spatial and temporal heterogeneity in each influencing factor.GDP per capita,population density,degree of opening to the outside world and general budget expenditure had a significant pos-itive effect on county carbon emissions in Shaanxi,and industrial structure has shown a significant inhibitory effect on carbon emissions.
李俊亭;张子悦;曹金凤
西安石油大学 管道工程学院,陕西 西安 710065西安石油大学 管道工程学院,陕西 西安 710065西安石油大学 管道工程学院,陕西 西安 710065
管理科学
县域碳排放ESDA模型GTWR模型影响因素
county carbon emissionsESDA modelGTWR modelinfluencing factors
《西安石油大学学报(社会科学版)》 2026 (2)
70-79,90,11
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