Analysis of Spatiotemporal Variation and Influencing Factors of PM2.5 in China Based on Multisource Data

被引:5
作者
Kan, Xi [1 ]
Liu, Xu [2 ]
Zhou, Zhou [2 ]
Zhang, Yonghong [1 ,2 ]
Zhu, Linglong [1 ]
Sian, Kenny Thiam Choy Lim Kam [3 ]
Liu, Qi [2 ]
机构
[1] Wuxi Univ, Sch Internet Things Engn, Wuxi 214105, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Sch Automat, Nanjing 210044, Peoples R China
[3] Wuxi Univ, Sch Atmospher Sci & Remote Sensing, Wuxi 214105, Peoples R China
关键词
PM2.5; correlation analysis; spatiotemporal characteristics; China; PARTICULATE MATTER;
D O I
10.3390/su151914656
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The urbanization process over the past decades has resulted in increasing attention being paid to atmospheric pollution by researchers, especially changes in PM2.5 concentration. This study attempted to explore the spatiotemporal changes in PM2.5 concentration in China from 2000 to 2021, as well as their interaction patterns and intensities with temperature, precipitation, vegetation coverage, and land use types. This was carried out by analyzing monthly average PM2.5 concentration data and various meteorological and geographical factors. Suggestions have also been made to reduce PM2.5 concentration and improve air quality. The results show that in the past 22 years, the overall concentration of PM2.5 in China has shown a downward trend, with an average annual rate of 1.42 mu g/m3 from 2013 to 2021, accompanied by a clear spatial pattern and significant seasonal changes. The high pollution areas are mainly concentrated in the Tarim Basin, Sichuan Basin, North China Plain, and the Middle and Lower Yangtze Valley Plain, where the PM2.5 concentration in autumn and winter is significantly higher than that in spring and summer. In addition, based on the national spatial scale, PM2.5 concentration is negatively correlated with precipitation and vegetation coverage, while it is significantly positively correlated with arable land and impervious surfaces. Strengthening the control of farmland pollution, accelerating urban greening construction, further expanding the scale of forests and grasslands, and enriching vegetation types will help reduce PM2.5 concentration and improve air quality.
引用
收藏
页数:24
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