Articles | Volume 19, issue 9
https://doi.org/10.5194/acp-19-5791-2019
https://doi.org/10.5194/acp-19-5791-2019
Research article
 | 
03 May 2019
Research article |  | 03 May 2019

Local and regional contributions to fine particulate matter in the 18 cities of Sichuan Basin, southwestern China

Xue Qiao, Hao Guo, Ya Tang, Pengfei Wang, Wenye Deng, Xing Zhao, Jianlin Hu, Qi Ying, and Hongliang Zhang

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Cited articles

Arya, S. P.: Air pollution meteorology and dispersion, Oxford University Press, New York, United States, 1999. 
Begum, B. A., Kim, E., Jeong, C.-H., Lee, D. W., and Hopke, P. K.: Evaluation of the potential source contribution function using the 2002 Quebec forest fire episode, Atmos. Environ., 39, 3719–3724, 2005. 
Bei, N. F., Zhao, L. N., Xiao, B., Meng, N., and Feng, T.: Impacts of local circulations on the wintertime air pollution in the Guanzhong Basin, China, Sci. Total Environ., 592, 373–390, 2017. 
Bei, N. F., Zhao, L. N., Wu, J. R.,Li, X., Feng, T., and Li, G. H.: Impacts of sea-land and mountain-valley circulations on the air pollution in Beijing-Tianjin-Hebei (BTH): A case study, Environ. Pollut., 234, 429–438, 2018. 
Bove, M., Brotto, P., Cassola, F., Cuccia, E., Massabò, D., Mazzino, A., Piazzalunga, A., and Prati, P.: An integrated PM2.5 source apportionment study: positive matrix factorisation vs. the chemical transport model CAMx, Atmos. Environ., 94, 274–286, 2014. 
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Short summary
A source-oriented version of the CMAQ model was used to quantify contributions from nine regions to PM2.5 and its components in the 18 cities within Sichuan Basin. Nonlocal emissions contribute 39–66 % and 25–52 % to the citywide average PM2.5 concentrations of 45–126 and 14–31 µg m3 in the winter and summer, respectively. This study demonstrates the importance of joint emission control efforts among cities within the SCB and neighboring regions to the east.
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