Spatiotemporal distribution characteristics of PM2.5 concentration in China from 2000 to 2018 and its impact on population

Haoyu Jin; Ruida Zhong; Moyang Liu; Changxin Ye; Xiaohong Chen

doi:10.1016/j.jenvman.2022.116273

Spatiotemporal distribution characteristics of PM2.5 concentration in China from 2000 to 2018 and its impact on population

J Environ Manage. 2022 Dec 1:323:116273. doi: 10.1016/j.jenvman.2022.116273. Epub 2022 Sep 21.

Authors

Haoyu Jin¹, Ruida Zhong¹, Moyang Liu², Changxin Ye¹, Xiaohong Chen³

Affiliations

¹ School of Civil Engineering, Sun Yat-sen University, Guangzhou, 510275, China; Guangdong Engineering Technology Research Center of Water Security Regulation and Control for Southern China, Sun Yat-sen University, Guangzhou, 510275, China; Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong High Education Institute, Sun Yat-sen University, Guangzhou, 510275, China.
² The Fenner School of Environment and Society, The Australian National University (ANU), Canberra, ACT, 0200, Australia.
³ School of Civil Engineering, Sun Yat-sen University, Guangzhou, 510275, China; Guangdong Engineering Technology Research Center of Water Security Regulation and Control for Southern China, Sun Yat-sen University, Guangzhou, 510275, China; Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong High Education Institute, Sun Yat-sen University, Guangzhou, 510275, China. Electronic address: eescxh@mail.sysu.edu.cn.

PMID: 36261986
DOI: 10.1016/j.jenvman.2022.116273

Abstract

PM2.5 is an important indicator reflecting changes in air quality. In recent years, affected by climate change and human activities, the problem of environmental pollution has become more and more prominent. In this study, the PM2.5 data from 2000 to 2018 obtained by satellite remote sensing inversion algorithm were selected to analyze the temporal and spatial distribution of PM2.5 in China. The results show that the areas with higher PM2.5 concentrations were mainly in the North China, the Sichuan Basin, and the Tarim Basin. The areas with a significant increase in PM2.5 were mainly in the Northeast China, while the areas with a significant decrease were mainly in the Sichuan Basin and southeastern Gansu. The change of PM2.5 in southern China was not significantly correlated with the change of population and economy, while PM2.5 in Northeast China increases with the increase of population and economy. In 2000, 2005, 2010, and 2015, the proportion of the population polluted by PM2.5 was 8.65%, 7.2%, 22.99%, and 9.75%, respectively. The year with the highest percentage (37.63%) of population when air quality reached EXCELLENT was 2015. When the PM2.5 spatial cluster number was six, it can better reflect the PM2.5 spatial distribution state. The places with large changes in PM2.5 spatial clustering were mainly in the Northeast China, Sichuan Basin, and Tarim Basin, which were also areas with large changes in PM2.5. This study provides an important reference for atmospheric environmental monitoring and protection.

Keywords: Cluster analysis; GDP; PM2.5; Population; Spatiotemporal change.

MeSH terms

Air Pollutants* / analysis
Air Pollution* / analysis
Environmental Monitoring / methods
Environmental Pollution
Humans
Particulate Matter / analysis

Substances

Particulate Matter
Air Pollutants