Analyzing carbon emissions and influencing factors in Chengdu-Chongqing urban agglomeration counties  

作　　者：Zhang Heng Lu Wenfu Peng Lindan Zhang 

机构地区：[1]Key Laboratory of the Evaluation and Monitoring of Southwest Land Resources(Ministry of Education),Sichuan Normal University,Chengdu 610068,China [2]The Institute of Geography and Resources Science,Sichuan Normal University,Chengdu 610068,China

出　　处：《Journal of Environmental Sciences》2025年第5期640-651,共12页环境科学学报(英文版)

基　　金：supported by the Humanities and Social Sciences Project of the Ministry of Education of the Peoples Republic(No.21YJCZH099);the National Natural Science Foundation of China(Nos.41401089 and 41741014);the Science and Technology Project of Sichuan Province(No.2023NSFSC1979).

摘　　要：Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Sichuan Province and Chongqing Municipality for the years 2000 to 2019 to estimate their statistical carbon emissions.We then employed nighttime light data to downscale and infer the spatial distribution of carbon emissions at the county level within the Chengdu-Chongqing urban agglomeration.Furthermore,we analyzed the spatial pattern of carbon emissions at the county level using the coefficient of variation and spatial autocorrelation,and we used the Geographically and Temporally Weighted Regression(GTWR)model to analyze the influencing factors of carbon emissions at this scale.The results of this study are as follows:(1)from 2000 to 2019,the overall carbon emissions in the Chengdu-Chongqing urban agglomeration showed an increasing trend followed by a decrease,with an average annual growth rate of 4.24%.However,in recent years,it has stabilized,and 2012 was the peak year for carbon emissions in the Chengdu-Chongqing urban agglomeration;(2)carbon emissions exhibited significant spatial clustering,with high-high clustering observed in the core urban areas of Chengdu and Chongqing and low-low clustering in the southern counties of the Chengdu-Chongqing urban agglomeration;(3)factors such as GDP,population(Pop),urbanization rate(Ur),and industrialization structure(Ic)all showed a significant influence on carbon emissions;(4)the spatial heterogeneity of each influencing factor was evident.

关 键 词：Carbon emissions Chengdu-Chongqing urban AGGLOMERATION Spatial autocorrelation Geographically and temporally weighted regression 

分 类 号：F42[经济管理—产业经济]