Evaluating the EPICC-Model for regional air quality simulation: a comparative study with CAMx and CMAQ

Lou, Mengjie; Wu, Qizhong; Wang, Wending; Chen, Huansheng; Cao, Kai; Fan, Xiaohan; Liang, Dingyue; Yu, Fenfen; Zhang, Jiating; Wang, Wei; Wang, Zifa

doi:10.5194/gmd-19-9651-2026

Articles | Volume 19, issue 19

https://doi.org/10.5194/gmd-19-9651-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-9651-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 19

Model description paper

|

12 Oct 2026

Model description paper |

| 12 Oct 2026

Evaluating the EPICC-Model for regional air quality simulation: a comparative study with CAMx and CMAQ

Mengjie Lou, Qizhong Wu, Wending Wang, Huansheng Chen, Kai Cao, Xiaohan Fan, Dingyue Liang, Fenfen Yu, Jiating Zhang, Wei Wang, and Zifa Wang

Supplement

https://doi.org/10.5194/gmd-19-9651-2026-supplement

Data sets

The dataset of the manuscript "Evaluating the EPICC-Model for Regional Air Quality Simulation: A Comparative Study with CAMx and CMAQ" M. Lou and Q. Wu https://doi.org/10.5281/zenodo.20843312

NCEP FNL Operational Model Global Tropospheric Analyses National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce https://doi.org/10.5065/D6M043C6

Model code and software

MEGANv3.21.tar.gz emission calculator code (Version 3.21) A. Guenther https://doi.org/10.5281/zenodo.10526206

CMAQ (Version 5.3.3) US EPA Office of Research and Development https://doi.org/10.5281/zenodo.5213949

Emission and atmospheric Processes Integrated and Coupled Community Model (EPICC-Model) (Version 1.6.0) EPICC-Model Working Group https://doi.org/10.5281/zenodo.20303367

Short summary

This study compares the model performance of the Emission and atmospheric Processes Integrated and Coupled Community Model with the two air quality models in China. The EPICC-Model excels in simulating summer ozone peaks, accurately captures pollution characteristics in highly polluted areas, and better reproduces persistent compound pollution processes. The study reveals common issues among the models and directions for improvement, providing a basis for optimizing global air quality models.