Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 25, issue 12
Articles | Volume 25, issue 12
https://doi.org/10.5194/acp-25-6197-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-6197-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 25, issue 12
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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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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