Articles | Volume 25, issue 12
https://doi.org/10.5194/acp-25-6197-2025
https://doi.org/10.5194/acp-25-6197-2025
Research article
 | 
25 Jun 2025
Research article |  | 25 Jun 2025

Toward a learnable Artificial Intelligence Model for Aerosol Chemistry and Interactions (AIMACI) based on the Multi-Head Self-Attention algorithm

Zihan Xia, Chun Zhao, Zining Yang, Qiuyan Du, Jiawang Feng, Chen Jin, Jun Shi, and Hong An

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Cited articles

Arfin, T., Pillai, A. M., Mathew, N., Tirpude, A., Bang, R., and Mondal, P.: An overview of atmospheric aerosol and their effects on human health, Environ. Sci. Pollut. Res., 30, 125347–125369, https://doi.org/10.1007/s11356-023-29652-w, 2023.  
Bi, K., Xie, L., Zhang, H., Chen, X., Gu, X., and Tian, Q.: Accurate medium-range global weather forecasting with 3D neural networks, Nature, 619, 533–538, https://doi.org/10.1038/s41586-023-06185-3, 2023. 
Calvert, J. G., Lazrus, A., Kok, G. L., Heikes, B. G., Walega, J. G., Lind, J., and Cantrell, C. A.: Chemical mechanisms of acid generation in the troposphere, Nature, 317, 27–35, https://doi.org/10.1038/317027a0, 1985. 
Carmichael, G. R., Sandu, A., Song, C. H., He, S., Phandis, M. J., Daescu, D., Damian-Iordache, V., and Potra, F. A.: Computational Challenges of Modeling Interactions Between Aerosol and Gas Phase Processes in Large Scale Air Pollution Models, in: Large Scale Computations in Air Pollution Modelling, edited by: Zlatev, Z., Brandt, J., Builtjes, P. J. H., Carmichael, G., Dimov, I., Dongarra, J., van Dop, H., Georgiev, K., Hass, H., and Jose, R. S., Springer Netherlands, Dordrecht, 99–136, https://doi.org/10.1007/978-94-011-4570-1_10, 1999. 
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Short summary
Traditional numerical schemes of aerosol chemistry and interactions (ACI) in atmospheric models are computationally costly and are often simplified or omitted, introducing uncertainties. We use an AI scheme to achieve fast, accurate, and stable end-to-end simulation for full ACI within an atmospheric model, replacing numerical schemes. This innovation is expected to enhance the accuracy and efficiency of ACI simulations in climate models that would otherwise neglect or simplify ACI processes.
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