Diagnostic identification of the impact of meteorological conditions on PM2.5 concentrations in Beijing

Using daily PM2.5 concentration data from Beijing, surface observations and upper-air sounding data from regional weather stations in Beijing and North China from 2007 to 2008, 5-min AWS (automatic weather station) observations and hourly AMS (aerosol mass spectrum) data from July 2008, we analysed sensitive meteorological parameters and conditions that affect the concentration of PM23. We also diagnosed and identified the impact of meteorological conditions on air quality (AQ). The results show that the condensation function fc is a sensitive and significant parameter for PM2.5 concentration, favourable for generation of secondary aerosol particles. Statistical analysis of a large sample of PM2.5 and meteorological observation data indicates that adaptive weight parameter beta is of great value in diagnosing changes in PM2.5 concentrations. When Beijing and North China experience dry, cold winters with a low fc, the parameter beta will be large, creating conditions that are conducive to suspended fine particles. In moist, hot summers, the high temperature and humidity increase the fc, but beta plays a much weaker role than in winter. beta and fc influence and restrict each other, and their impacts on the changes in PM2.5 concentrations are consistent with the observed seasonal changes in meteorological elements and PM2.5 concentrations. In addition, a good correlation exists between the 24-h forecast of the I index and the PM2.5 observations in Beijing, which will prove useful in diagnosing, identifying and predicting the influence of meteorological conditions on AQ based on PM2.5 concentrations. (C) 2013 Elsevier Ltd. All rights reserved.