Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 26, issue 9
Articles | Volume 26, issue 9
https://doi.org/10.5194/acp-26-6117-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-6117-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 9
Research article
 | 
08 May 2026
Research article |  | 08 May 2026

Multi-machine-learning approaches to modeling small-scale source attribution of ozone formation

Zheng Xiao, Yifeng Lu, and Guangli Xiu

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Short summary
This study innovates air pollution tracking in industry by combining AI with traditional methods. By analyzing 3 years of data from a chemical park in Shanghai, we identified sources of ozone pollution and seasonal variations, revealing chemical solvents and fuel vapor as key factors. Our approach identifies sources of pollution faster and more accurately, helping to make better air quality decisions in rapidly developing areas.
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