Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 22, issue 10
Articles | Volume 22, issue 10
https://doi.org/10.5194/acp-22-6471-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-6471-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 10
Research article
 | 
19 May 2022
Research article |  | 19 May 2022

The impact of large-scale circulation on daily fine particulate matter (PM2.5) over major populated regions of China in winter

Zixuan Jia, Ruth M. Doherty, Carlos Ordóñez, Chaofan Li, Oliver Wild, Shipra Jain, and Xiao Tang

Supplement

https://doi.org/10.5194/acp-22-6471-2022-supplement

Data sets

ERA5 hourly data on pressure levels from 1979 to present H. Hersbach, B. Bell, P. Berrisford, G. Biavati, A. Horányi, J. Muñoz Sabater, J. Nicolas, C. Peubey, R. Radu, I. Rozum, D. Schepers, A. Simmons, C. Soci, D. Dee, and J.-N. Thépaut https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels

GPCP Version 1.2 One-Degree Daily Precipitation Data Set G. J. Huffman, D. T. Bolvin, and R. F. Adler https://rda.ucar.edu/datasets/ds728.3/

A High-resolution Air Quality Reanalysis Dataset over China (CAQRA)[DS/OL] X. Tang, L. Kong, J. Zhu, Z. Wang, J. Li, H. Wu, Q. Wu, H. Chen, L. Zhu, W. Wang, B. Liu, Q. Wang, D. Chen, Y. Pan, T. Song, F. Li, H. Zheng, G. Jia, M. Lu, L. Wu, and G. R. Carmichael http://cstr.cn/31253.11.sciencedb.00053

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Short summary
This study investigates the modulation of daily PM2.5 over three major populated regions in China by regional meteorology and large-scale circulation during winter. These results demonstrate the benefits of considering the large-scale circulation for air quality studies. The novel circulation indices proposed here can explain a considerable fraction of the day-to-day variability of PM2.5 and can be combined with regional meteorology to improve our capability to predict the variability of PM2.5.
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