Articles | Volume 19, issue 4
https://doi.org/10.5194/gmd-19-1703-2026
https://doi.org/10.5194/gmd-19-1703-2026
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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Cited articles

Abuouelezz, W., Ali, N., Aung, Z., Altunaiji, A., Shah, S. B., and Gliddon, D.: Exploring PM2.5 and PM10 ML forecasting models: a comparative study in the UAE, Scientific Reports, 15, 9797, https://doi.org/10.1038/s41598-025-94013-1, 2025. a
Al-Kindi, S. G., Brook, R. D., Biswal, S., and Rajagopalan, S.: Environmental determinants of cardiovascular disease: lessons learned from air pollution, Nature Reviews Cardiology, 17, 656–672, 2020. a
Bell, M. L., McDermott, A., Zeger, S. L., Samet, J. M., and Dominici, F.: Ozone and short-term mortality in 95 US urban communities, 1987–2000, Jama, 292, 2372–2378, 2004. a
Bi, K., Xie, L., Zhang, H., Chen, X., Gu, X., and Tian, Q.: Pangu-weather: A 3d high-resolution model for fast and accurate global weather forecast, arXiv [preprint], https://doi.org/10.48550/arXiv.2211.02556, 2022. a
Bond, T. C., Bhardwaj, E., Dong, R., Jogani, R., Jung, S., Roden, C., Streets, D. G., and Trautmann, N. M.: Historical emissions of black and organic carbon aerosol from energy-related combustion, 1850–2000, Global Biogeochemical Cycles, 21, https://doi.org/10.1029/2006GB002840, 2007. a
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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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