Climate-driven deterioration of future ozone pollution in Asia predicted by machine learning with multi-source data

Li, Huimin; Yang, Yang; Jin, Jianbing; Wang, Hailong; Li, Ke; Wang, Pinya; Liao, Hong

doi:https://doi.org/10.5194/acp-23-1131-2023

Articles | Volume 23, issue 2

https://doi.org/10.5194/acp-23-1131-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-23-1131-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 2

Research article

|

23 Jan 2023

Research article |

| 23 Jan 2023

Climate-driven deterioration of future ozone pollution in Asia predicted by machine learning with multi-source data

Huimin Li, Yang Yang, Jianbing Jin, Hailong Wang, Ke Li, Pinya Wang, and Hong Liao

Supplement

https://doi.org/10.5194/acp-23-1131-2023-supplement

Data sets

LandScan Global 2010 E. Bright, P. Coleman, A. Rose, and M. Urban https://doi.org/10.48690/1524206

Model code and software

geoschem/geos-chem: GEOS-Chem 12.9.3 (12.9.3) The International GEOS-Chem User Community https://doi.org/10.5281/zenodo.3974569

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Short summary

Future climate change will aggravate ozone pollution in Asia, especially in high-forcing scenarios. Ozone pollution in China will expand from North China to South China and extend into the cold season in a warmer future. The emphasis of this work is to quantify the impacts of future climate change on O₃ pollution in Asia, which is of great significance for future O₃ pollution mitigation strategies.