Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 26, issue 20
Articles | Volume 26, issue 20
https://doi.org/10.5194/acp-26-15003-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-15003-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 20
Research article
 | 
26 Oct 2026
Research article |  | 26 Oct 2026

Classification and quantification of low-visibility events using deep learning over eastern China

Yuting Liang, Shitong Zhao, Dantong Liu, Changhao Wu, Li Yi, Xingcan Jia, Honghui Xu, and Jiankan Wang

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Short summary
We identified and quantified low-visibility events over land and sea in eastern China using satellite, weather and pollution data. Our model distinguishes polluted fog from clean fog. Model tests show that a 20% cut in fine particle pollution reduces winter polluted fog area by 43%, but population exposure by only 15%, as the most polluted areas are also densely populated. These findings guide air-quality policies to improve visibility, protect health and support transport safety.
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