Articles | Volume 16, issue 22
https://doi.org/10.5194/gmd-16-6757-2023
https://doi.org/10.5194/gmd-16-6757-2023
Model experiment description paper
 | 
22 Nov 2023
Model experiment description paper |  | 22 Nov 2023

The effect of emission source chemical profiles on simulated PM2.5 components: sensitivity analysis with the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.2

Zhongwei Luo, Yan Han, Kun Hua, Yufen Zhang, Jianhui Wu, Xiaohui Bi, Qili Dai, Baoshuang Liu, Yang Chen, Xin Long, and Yinchang Feng

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Cited articles

Appel, K. W., Pouliot, G. A., Simon, H., Sarwar, G., Pye, H. O. T., Napelenok, S. L., Akhtar, F., and Roselle, S. J.: Evaluation of dust and trace metal estimates from the Community Multiscale Air Quality (CMAQ) model version 5.0, Geosci. Model Dev., 6, 883–899, https://doi.org/10.5194/gmd-6-883-2013, 2013. 
Bi, X., Dai, Q., Wu, J., Zhang, Q., Zhang, W., Luo, R., Cheng, Y., Zhang, J., Wang, L., Yu, Z., Zhang, Y., Tian, Y., and Feng, Y.: Characteristics of the main primary source profiles of particulate matter across China from 1987 to 2017, Atmos. Chem. Phys., 19, 3223–3243, https://doi.org/10.5194/acp-19-3223-2019, 2019a. 
Bi, X., Dai, Q., Wu, J., Zhang, Q., Zhang, W., Luo, R., Cheng, Y., Zhang, J., Wang, L., Yu, Z., Zhang, Y., Tian, Y., and Feng, Y.: Data for: chemical compositions of the main source profiles of ambient particulate matter across China, Mendeley Data [data set], https://doi.org/10.17632/x8dfshjt9j.2, 2019b. 
Cao, J., Qiu, X., Gao, J., Wang, F., Wang, J., Wu, J., and Peng, L.: Significant decrease in SO2 emission and enhanced atmospheric oxidation trigger changes in sulfate formation pathways in China during 2008–2016, J. Clean. Prod., 326, 129396, https://doi.org/10.1016/j.jclepro.2021.129396, 2021. 
Chapel Hill, N.: Operational Guidance for the Community Multiscale Air Quality (CMAQ) Modeling System Version 5.0, https://www.airqualitymodeling.org/index.php/CMAQ_version_5.0_(February_2010_release)_OGD#Aerosol_Module, last access: February 2012. 
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Short summary
This study explores how the variation in the source profiles adopted in chemical transport models (CTMs) impacts the simulated results of chemical components in PM2.5 based on sensitivity analysis. The impact on PM2.5 components cannot be ignored, and its influence can be transmitted and linked between components. The representativeness and timeliness of the source profile should be paid adequate attention in air quality simulation.