Ambient Atmospheric Aerosol Extinction Coefficient Reconstruction From Pm2.5 Mass Concentrations And Application To Haze Identification In China

This study developed a method of reconstructing the aerosol extinction coefficient based on hourly observations of the fine-particle (PM2.5) mass concentration, relative humidity (RH), and visibility at 9 stations in China between 2014 and 2015. First, we applied kappa-Kohler theory to evaluate the number concentration distribution of the fine particles under ambient conditions from the PM2.5 mass and then used Mie theory to calculate the aerosol extinction coefficient. Second, we established the reconstruction model and identified reference values for the relevant parameters. After sensitivity tests confirmed good agreement between the extinction coefficients obtained through combinations of various values and those resulting from the reference values, linear regression was employed to reduce the discrepancy between the reconstructed and the observed coefficients. A closure study enabled us to determine the threshold of the extinction ratio (beta/beta(Obs)) and identify haze and fog weather phenomena at the stations. Finally, we assessed the bias in the predicted number of hours with haze for 61 stations in China by comparing the estimates derived from different values for the model's parameters with those derived from the reference values and found a relative bias of less than 15% for approximately 99.8% of the stations, indicating the feasibility of our approach for detecting haze.