Chemical composition and sources of PM1 and PM2.5 in Beijing in autumn

Beijing, the capital of China, suffers from severe atmospheric aerosol pollution; nevertheless, a comprehensive study of the constituents and sources of PM1 is still lacking, and the differences between PM1 and PM2.5 are still unclear. In this study, an intensive observation was conducted to reveal the pollution characteristics of PM1 and PM2.5 in Beijing in autumn. Positive matrix factorization (PMF), backward trajectories and a potential source contribution function (PSCF) model were used to identify the source categories and source areas of PM1 and PM2.5. The results showed that the average concentrations of PM1 and PM2.5 reached 78.20 mu g/m(3) and 95.47 mu g/m(3) during the study period, respectively. PM1 contributed greatly to PM2.5. The PM1/PM2.5 value increased from 73.6% to 90.1% with PM1 concentration growing from <50 mu g/m(3) to >150 mu g/m(3). Higher secondary inorganic aerosol (SIA) proportions (31.3%-70.8%) were found in PM1. The higher fraction of SIA, OC, EC and typical elements in PM1 illustrated that anthropogenic components accumulated more in smaller size particles. Three typical weather patterns causing the heavy pollution in autumn were found as follows: (1) Siberian high and uniform high pressure field, (2) cold front and low-voltage system, and (3) uniform low pressure field. A PMF analysis indicated that secondary aerosols and coal combustion, vehicle, industry, biomass burning, and dust were the important sources of PM, accounting for 53.8%, 8.0%, 13.0%, 13.2% and 12.0% of PM1, respectively, and for 47.5%, 9.9%, 12.4%, 8.4% and 21.8% of PM2.5, respectively. The HYSPLIT and chemical components analysis indicated the potential contribution from biomass burning and fertilization ammonia emissions to PM1 in autumn. The source areas were similar for PM1 and PM1-2.5 under general polluted conditions, but during the heavily polluted periods, the source areas were distributed in farther regions from Beijing for PM1 than for PM1-2.5. (C) 2018 Elsevier B.V. All rights reserved.