Spatio-temporal Variation and Multi-dimensional Detection of Driving Mechanism of PM2.5 Concentration in the Chengdu-Chongqing Urban Agglomeration from 2000 to 2021

被引：0
|
作者：
Xu Y. [1 ]
Guo Z.-D. [1 ]
Zheng Z.-W. [1 ]
Dai Q.-Y. [1 ]
Zhao C. [1 ]
Huang W.-T. [1 ]
机构：
[1] College of Geomatics and Geoinfoimation, Guilin University of Technology, Guilin
来源：
Huanjing Kexue/Environmental Science | 2023年 / 44卷 / 07期
关键词：
anthropogenic factor; Chengdu-Chongqing urban agglomeration; climate factor; driving mechanism; Geo-detector; PM[!sub]2.5[!/sub]concentration; topographic factor;
D O I：
10.13227/j.hjkx.202207276
中图分类号：
学科分类号：
摘要：
tudies on the spatio-temporal variation and driving mechanism of PM2.5concentration in the Chengdu-Chongqing urban agglomeration are of great significance for regional atmospheric environment protection and national economic sustainable development. Based on PM2.5remote sensing data, DEM data, in situ meteorological data, MODIS NDVI data, population density data, nighttime lighting data, road network data, and land use type data, a series of mathematical methods such as Theil-Sen Medium analysis and Mann-Kendall significance test, combined with the Geo-detector model were used to analyze the spatio-temporal variation and multi-dimensional detection of the driving mechanism of PM2.5concentration in the Chengdu-Chongqing urban agglomeration. The results showed that the overall PM2.5concentration showed a fluctuating downward trend in the Chengdu-Chongqing urban agglomeration from 2000 to 2021, and the PM2.5pollution was the most prominent in winter. PM2.5concentration exhibited obvious spatial heterogeneity with "high in the middle and low in the surrounding areas."The high-PM2.5concentration areas were mainly concentrated in Zigong, Neijiang, Ziyang, and Guang'an, and the areas with a PM2.5concentration decrease were mainly concentrated in the west of Chongqing. Influencing detection results showed that the spatial heterogeneity of PM2.5concentration in the Chengdu-Chongqing urban agglomeration was influenced by the combined effects of climate factors, topographic factors, vegetation cover, and anthropogenic factors. Furthermore, elevation, slope, and road network density were regarded as the dominant factors influencing the spatial heterogeneity of PM2.5concentration in the study area. Topographic factors and climate factors showed the highest and lowest contribution rate to the spatial heterogeneity of PM2.5concentration, respectively. The contribution rate of topographic factors and anthropogenic factors had gradually increased, and the contribution rate of climate factors and vegetation cover had gradually decreased in the study area from 2000 to 2021. Interaction detection results showed that the spatial heterogeneity of PM2.5concentration in the Chengdu-Chongqing urban agglomeration was mostly affected by the interaction effects of elevation and road network density, slope, precipitation, sunshine duration, and land use type. The interaction detection results exhibited obvious regional differences on the city level. For instance, the spatial heterogeneity of PM2.5concentration in Chengdu, Deyang, and Leshan was mostly affected by the interaction between different influencing types, and the spatial heterogeneity of PM2.5concentration in Dazhou, Meishan, Ya'an, Ziyang, Neijiang, and Zigong was mostly affected by the interaction within a single influencing type. © 2023 Science Press. All rights reserved.
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页码：3724 / 3737
页数：13
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