Articles | Volume 16, issue 21
https://doi.org/10.5194/gmd-16-6049-2023
https://doi.org/10.5194/gmd-16-6049-2023
Model description paper
 | 
30 Oct 2023
Model description paper |  | 30 Oct 2023

Rapid Adaptive Optimization Model for Atmospheric Chemistry (ROMAC) v1.0

Jiangyong Li, Chunlin Zhang, Wenlong Zhao, Shijie Han, Yu Wang, Hao Wang, and Boguang Wang

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Cited articles

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Short summary
Photochemical box models, crucial for understanding tropospheric chemistry, face challenges due to slow computational efficiency with large chemical equations. The model introduced in this study, ROMAC, boosts efficiency by up to 96 % using an advanced atmospheric solver and an adaptive optimization algorithm. Moreover, ROMAC exceeds traditional box models in evaluating the impact of physical processes on pollutant concentrations.