Articles | Volume 25, issue 2
https://doi.org/10.5194/acp-25-905-2025
https://doi.org/10.5194/acp-25-905-2025
Research article
 | 
23 Jan 2025
Research article |  | 23 Jan 2025

Understanding summertime peroxyacetyl nitrate (PAN) formation and its relation to aerosol pollution: insights from high-resolution measurements and modeling

Baoye Hu, Naihua Chen, Rui Li, Mingqiang Huang, Jinsheng Chen, Youwei Hong, Lingling Xu, Xiaolong Fan, Mengren Li, Lei Tong, Qiuping Zheng, and Yuxiang Yang

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Subject: Gases | Research Activity: Field Measurements | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
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Cited articles

Behera, S. N., Sharma, M., Aneja, V. P., and Balasubramanian, R.: Ammonia in the atmosphere: a review on emission sources, atmospheric chemistry and deposition on terrestrial bodies, Environ. Sci. Pollut. R., 20, 8092–8131, https://doi.org/10.1007/s11356-013-2051-9, 2013. 
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Hong, Z., Li, M., Wang, H., Xu, L., Hong, Y., Chen, J., Chen, J., Zhang, H., Zhang, Y., Wu, X., Hu, B., and Li, M.: Characteristics of atmospheric volatile organic compounds (VOCs) at a mountainous forest site and two urban sites in the southeast of China, Sci. Total Environ., 657, 1491–1500, https://doi.org/10.1016/j.scitotenv.2018.12.132, 2019. 
Hu, B., Liu, T., Hong, Y., Xu, L., Li, M., Wu, X., Wang, H., Chen, J., and Chen, J.: Characteristics of peroxyacetyl nitrate (PAN) in a coastal city of southeastern China: Photochemical mechanism and pollution process, Sci. Total Environ., 719, 137493, https://doi.org/10.1016/j.scitotenv.2020.137493, 2020. 
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Box modeling with the Master Chemical Mechanism (MCM) was used to explore summertime peroxyacetyl nitrate (PAN) formation and its link to aerosol pollution under high-ozone conditions. The MCM model is effective in the study of PAN photochemical formation and performed better during the clean period than the haze period. Machine learning analysis identified ammonia, nitrate, and fine particulate matter as the top three factors contributing to simulation bias.
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