Articles | Volume 26, issue 18
https://doi.org/10.5194/acp-26-13341-2026
https://doi.org/10.5194/acp-26-13341-2026
Research article
 | 
22 Sep 2026
Research article |  | 22 Sep 2026

Scenario-driven ozone projections and associated impact on mortality over Africa with an integrated machine learning framework

Huimin Li, Yang Yang, and Hailong Wang

Model code and software

geoschem/geos-chem: GEOS-Chem 13.4.1 (Version 13.4.1) M. Sulprizio https://doi.org/10.5281/zenodo.7254273

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Short summary
The O3 pollution across Africa has been exacerbating, which poses serious threats to public health. In this study, we predict future near-surface O3 concentrations with an integrated machine learning framework. This study reveals that global warming will exacerbate the health risk associated with O3 pollution. The elevated air temperatures act as primary driver of increased mortality ratios, while enhanced O3 concentrations are an additional stressor and adverse side effect of warming climate.
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