Articles | Volume 25, issue 3
https://doi.org/10.5194/acp-25-1749-2025
https://doi.org/10.5194/acp-25-1749-2025
Research article
 | 
07 Feb 2025
Research article |  | 07 Feb 2025

Insights into ozone pollution control in urban areas by decoupling meteorological factors based on machine learning

Yuqing Qiu, Xin Li, Wenxuan Chai, Yi Liu, Mengdi Song, Xudong Tian, Qiaoli Zou, Wenjun Lou, Wangyao Zhang, Juan Li, and Yuanhang Zhang

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Cited articles

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Short summary
The chemical reactions of ozone (O3) formation are related to meteorology and local emissions. Here, a random forest approach was used to eliminate the effects of meteorological factors (dispersion or transport) on O3 and its precursors. Variations in the sensitivity of O3 formation and the apportionment of emission sources were revealed after meteorological normalization. Our results suggest that meteorological variations should be considered when diagnosing O3 formation.
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