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

Related authors

Review of source analyses of ambient volatile organic compounds considering reactive losses: methods of reducing loss effects, impacts of losses, and sources
Baoshuang Liu, Yao Gu, Yutong Wu, Qili Dai, Shaojie Song, Yinchang Feng, and Philip K. Hopke
Atmos. Chem. Phys., 24, 12861–12879, https://doi.org/10.5194/acp-24-12861-2024,https://doi.org/10.5194/acp-24-12861-2024, 2024
Short summary
Divergent changes in aerosol optical hygroscopicity and new particle formation induced by heatwaves
Yuhang Hao, Peizhao Li, Yafeng Gou, Zhenshuai Wang, Mi Tian, Yang Chen, Ye Kuang, Hanbing Xu, Fenglian Wan, Yuqian Luo, Wei Huang, and Jing Chen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3242,https://doi.org/10.5194/egusphere-2024-3242, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Direct calibration using atmospheric particles and performance evaluation of PSM 2.0 for sub-10 nm particle measurements
Yiliang Liu, Arttu Yli-Kujala, Fabian Schmidt-Ott, Sebastian Holm, Lauri Ahonen, Tommy Chan, Joonas Enroth, Joonas Vanhanen, Runlong Cai, Tuukka Petäjä, Markku Kulmala, Yang Chen, and Juha Kangasluoma
EGUsphere, https://doi.org/10.5194/egusphere-2024-2603,https://doi.org/10.5194/egusphere-2024-2603, 2024
Short summary
Technical note: Influence of different averaging metrics and temporal resolutions on the aerosol pH calculated by thermodynamic modeling
Haoqi Wang, Xiao Tian, Wanting Zhao, Jiacheng Li, Haoyu Yu, Yinchang Feng, and Shaojie Song
Atmos. Chem. Phys., 24, 6583–6592, https://doi.org/10.5194/acp-24-6583-2024,https://doi.org/10.5194/acp-24-6583-2024, 2024
Short summary
Evolution of nucleophilic high molecular-weight organic compounds in ambient aerosols: a case study
Chen He, Hanxiong Che, Zier Bao, Yiliang Liu, Qing Li, Miao Hu, Jiawei Zhou, Shumin Zhang, Xiaojiang Yao, Quan Shi, Chunmao Chen, Yan Han, Lingshuo Meng, Xin Long, Fumo Yang, and Yang Chen
Atmos. Chem. Phys., 24, 1627–1639, https://doi.org/10.5194/acp-24-1627-2024,https://doi.org/10.5194/acp-24-1627-2024, 2024
Short summary

Related subject area

Atmospheric sciences
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024,https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024,https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024,https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024,https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024,https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary

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. 
Download
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.