Spatio-temporal Features and the Association of Ground-level PM2.5 Concentration and Its Emission in China

被引：0
|
作者：
Feng Z. [1 ,2 ,3 ]
Shi R. [1 ,2 ,3 ,4 ,5 ]
机构：
[1] Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai
[2] School of Geographic Sciences, East China Normal University, Shanghai
[3] Joint Laboratory for Environmental Remote Sensing and Data Assimilation, East China Normal University, Shanghai
[4] Joint Research Institute of Resources and Environment, East China Normal University, Shanghai
[5] Chongming Ecological Research Institute, East China Normal University, Shanghai
来源：
Journal of Geo-Information Science | 2021年 / 23卷 / 07期
关键词：
Air pollution; Association analysis; PM[!sub]2.5[!/sub] concentration; PM[!sub]2.5[!/sub] emission; Space distribution; Standard deviational ellipse; Time series; Trend analysis;
D O I：
10.12082/dqxxkx.2021.200367
中图分类号：
学科分类号：
摘要：
PM2.5 is one of the major air pollutants that threaten human health. A large number of studies have focused on the monitoring of ground-level PM2.5 concentration and its spatio-temporal distribution, but there is currently a lack of research on the correlation between PM2.5 emissions and ground- level PM2.5 concentration. Based on the ground- level PM2.5 concentration grid data and PM2.5 emission grid data from 2000 to 2014 in China, a long-term sequence analysis method was used to analyze and compare the spatio-temporal changes of PM2.5 concentration and PM2.5 emissions from qualitative and quantitative perspectives in this study. Furthermore, combined with standard deviational ellipse analysis and trend analysis, the spatio-temporal variations of groundlevel PM2.5 concentration and PM2.5 emissions and their correlation were analyzed. The results show that the spatial distributions of ground- level PM2.5 concentration and PM2.5 emissions were generally consistent, with dense populated areas concentrated in the east of the Hu Huanyong Line. However, there was still a situation of "low emission and high pollution" in parts of southern and central China. This was due to factors such as atmospheric transmission, topographical cumulative effect, and the conversion of PM2.5 concentration by precursors (SO2, CO, NO2, etc.). Temporally, there was a dynamic time difference between PM2.5 concentration and emissions, and the change of PM2.5 concentration was more obvious. The proportion of land area higher than 35 μg/m3 increased by 14.26% from 2000 to 2007, and decreased by 2.84% from 2007 to 2014. From the standard deviational ellipse analysis, the PM2.5 concentration ellipse and the emission ellipse were consistent with the distribution of population and economy in terms of the coverage area and azimuth, with the former having a larger area and a longer axis close to the east-west direction. There was a difference of about 17° between PM2.5 concentration ellipse and emission ellipse due to natural source pollution in the west and the diffusion of pollutants in the atmosphere. And the center positions of the two ellipses showed a clear trajectory and legacy characteristics over time. In addition, affected by factors such as meteorological parameters and point source emissions, the variations of PM2.5 concentration and the emission were not completely consistent in the east of the Hu Huanyong line. In some areas, the emission trend was decreasing while the concentration trend was increasing. Revealing the complex spatio-temporal correlation between PM2.5 concentration and the emissions in China can help formulate scientific prevention and control measures according to local conditions and effectively improve air quality. © 2021, Science Press. All right reserved.
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页码：1221 / 1230
页数：9
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