Spatio-temporal differentiation characteristics and the influencing factors of PM2.5 emissions from coal consumption in Central Plains Urban Agglomeration

被引:1
|
作者
Yang F. [1 ,2 ]
Yu J. [1 ,2 ]
Zhang C. [1 ,2 ]
Li L. [1 ,2 ]
Lei Y. [1 ,2 ]
Wu S. [1 ,2 ]
Wang Y. [1 ,2 ]
Zhang X. [1 ,2 ]
机构
[1] School of Economics and Management, China University of Geosciences, Beijing
[2] Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources of the People's Republic of China, Beijing
关键词
Influencing factors; PM2.5; emissions; Spatial autocorrelation; Spatial Durbin model; Spatio-temporal differentiation;
D O I
10.1016/j.scitotenv.2024.173778
中图分类号
学科分类号
摘要
Central Plains urban agglomeration (CPUA) had developed rapidly, but its air pollution was also serious. Despite advances in study on China's PM2.5 emissions from coal consumption (CC), the differentiation characteristics and the affecting variables of PM2.5 in CPUA required further investigation. This paper computed the PM2.5 emissions of each city from 2000 to 2020 using CC data from CPUA, evaluated its spatio-temporal fluctuation characteristics using the spatial autocorrelation and analyzed its influencing factors by combining various indicators through the spatial Durbin model (SDM). The results verified that: (1) There was a trend of rapid increase of PM2.5 emissions from CC; (2) The Moran's I of the PM2.5 emissions from CC showed a significant agglomeration effect; (3) PM2.5 emissions from CC had a strong spillover effect. The recommendations were in this following: (1) The urban pollution regulation and the pace of industrial green transformation should be Strengthened; (2) Close linkages between cities should be established and attention should be paid to pollution management; (3) The spillover of PM2.5 emissions from CC should be lessened and development of environmental governance technology should be enhanced. © 2024
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