Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 25, issue 20
Articles | Volume 25, issue 20
https://doi.org/10.5194/acp-25-13585-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-13585-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 20
Research article
 | 
23 Oct 2025
Research article |  | 23 Oct 2025

Rethinking machine learning weather normalisation: a refined strategy for short-term air pollution policies

Yuqing Dai, Bowen Liu, Chengxu Tong, David C. Carslaw, A. Robert MacKenzie, and Zongbo Shi

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Short summary
Air pollution causes millions of deaths annually, driving policies to improve air quality. However, assessing these policies is challenging because weather changes can hide their true impact. We created a logical evaluation framework and found that a widely applied machine learning approach that adjusts for weather effects could underestimate the effectiveness of short-term policies, like emergency traffic controls. We proposed a refined approach that could largely reduce such underestimation.
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