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  Fine particulate matter (PM2.5) trends from land surface changes and air pollution policies in China during 1980–2020

Yousefi, R., Shaheen, A., Wang, F., Ge, Q., Wu, R., Lelieveld, J., et al. (2023). Fine particulate matter (PM2.5) trends from land surface changes and air pollution policies in China during 1980–2020. Journal of Environmental Management, 326B: 116847. doi:10.1016/j.jenvman.2022.116847.

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Yousefi, Robabeh, Author
Shaheen, Abdallah, Author
Wang, Fang, Author
Ge, Quansheng, Author
Wu, Renguang, Author
Lelieveld, Jos1, Author           
Wang, Jun, Author
Su, Xiaokang, Author
Affiliations:
1Atmospheric Chemistry, Max Planck Institute for Chemistry, Max Planck Society, ou_1826285              

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 Abstract: High levels of fine particulate matter (PM2.5) pose a severe air pollution challenge in China. Both land use changes and anthropogenic emissions can affect PM2.5 concentrations. Only a few studies have addressed the long-term impact of land surface changes on PM2.5 in China. We conducted a comprehensive analysis of PM2.5 trends over China using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) during 1980–2020. The monthly mean PM2.5 concentrations of MERRA-2 were evaluated across mainland China against independent surface measurements from 2013 to 2020, showing a good agreement. For the trend analysis, China was subdivided into six regions based on land use and ambient aerosols types. Our results indicate an overall significant PM2.5 increase over China during 1980–2020 with major changes in-between. Notwithstanding continued urbanization and associated anthropogenic activities, the PM2.5 reversed to a downward trend around 2007 over most regions except for the part of China that is most affected by desert dust. Statistical analysis suggests that PM2.5 trends during 1980–2010 were associated with urban expansion and deforestation over eastern and southern China. The trend reversal around 2007 is mainly attributed to Chinese air pollution control measures. A multiple linear regression analysis reveals that PM2.5 variability is linked to soil moisture and vegetation. Our results suggest that land use and land cover changes as well as pollution controls strongly influenced PM2.5 trends and that drought conditions affect PM2.5 particularly over desert and forest regions of China. This work contributes to a better understanding of the changes in PM2.5 over China.

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 Dates: 2023-01-15
 Publication Status: Published online
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 Identifiers: DOI: 10.1016/j.jenvman.2022.116847
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Title: Journal of Environmental Management
Source Genre: Journal
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Pages: - Volume / Issue: 326B Sequence Number: 116847 Start / End Page: - Identifier: -