Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 4
Articles | Volume 19, issue 4
https://doi.org/10.5194/gmd-19-1703-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-1703-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 4
Model description paper
 | 
27 Feb 2026
Model description paper |  | 27 Feb 2026

A Transformer-based agent model of GEOS-Chem v14.2.2 for informative prediction of PM2.5 and O3 levels to future emission scenarios: TGEOS v1.0

Dehao Li, Jianbing Jin, Guoqiang Wang, Mijie Pang, Weihong Zhang, and Hong Liao

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Short summary
To support air quality decision-making in future emission scenarios, this study presents an agent model for a classic chemical transport model based on a transformer deep-learning framework. Addressing the long runtimes and input/output limitations of previous approaches, our agent model accurately reproduces simulations of fine particulate matter and ozone, enabling rapid air quality assessment.
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