Lina Gao1, Peng Yan This email address is being protected from spambots. You need JavaScript enabled to view it.1, Jietai Mao2, Xiaochun Zhang1, Xiaoling Zhang3,6, Yongxue Wu3, Junshan Jing1, Jianming Xu4, Xuejiao Deng5, Wenxue Chi1 

1 Meteorological Observation Center, China Meteorological Administration, Beijing 100081, China
2 School of Physics, Peking University, Beijing 100871, China
3 Beijing Meteorological Service, Beijing 100089, China
4 Yangtze River Delta Center for Environmental Meteorology Prediction and Warning, Shanghai 200030, China
5 Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou 510080, China
6 School of Atmospheric Sciences Chengdu University of Information Technology, Chengdu 610225 China

Received: July 8, 2020
Revised: January 21, 2021
Accepted: February 2, 2021

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

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Gao, L., Yan, P., Mao, J., Zhang, X., Zhang, X., Wu, Y., Jing, J., Xu, J., Deng, X., Chi, W. (2021). Ambient Atmospheric Aerosol Extinction Coefficient Reconstruction from PM2.5 Mass Concentrations and Application to Haze Identification in China. Aerosol Air Qual. Res.


  • An aerosol extinction coefficient reconstruction method is introduced in this study.
  • Linear regression is used to decrease the bias between calculations and observations.
  • The threshold of the extinction ratio are selected to identify the haze and fog weather phenomena.


Based on hourly observations of the fine-particle (PM2.5) mass concentration, relative humidity (RH), and visibility at 9 stations in China from 2014-2015, an aerosol extinction coefficient reconstruction method is introduced in this study. The fine aerosol number concentration distribution of wet aerosol particles under ambient conditions can be obtained from the PM2.5 mass concentration by the κ-Kӧhler theory. Then, the aerosol extinction coefficient can be obtained through the Mie theory. The reconstruction model was set up and relevant parameters were recommended. Sensitive tests with different parameters and combinations indicate that good correlations exist between the extinction coefficient calculated with these different parameters and that calculated with the recommended or “reference” parameters. So, a linear regression is adopted to reduce the bias between the calculations and observations. Based on the extinction closure study, the threshold of the extinction ratio (β/βObs) is determined and in order to identify haze and fog weather phenomena at the stations. The bias of haze hour identified by combinations of different values of parameters against that identified by the “reference” parameters are calculated at 61 stations in China. Results indicate that about 99.8% of all stations have a relative bias smaller than 15%, which suggest that the method is feasible for haze identification.

Keywords: Aerosol extinction reconstruction, Haze and fog, Identification

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