Characterization and source apportionment of PM2.5 based on error estimation from EPA PMF 5.0 model at a medium city in China

Heze city, a medium-size city in Shandong province, Eastern China. Ambient PM2.5 samples were collected in urban area of Heze from August 2015 to April 2016, and chemical species and sources of PM2.5 were investigated in this paper. The results indicated that the average concentration of PM2.5 was 100.9 mu g/m(3) during the sampling period, and the water-soluble ions, carbonaceous species included elemental carbon (EC) and organic carbon (OC), as well as elements contributed 32.7-51.7%, 16.3% and 12.5%, respectively, to PM2.5. Pearson's correlation analysis showed that the existing form of NH4+ was more complex and diverse in spring/summer, and ammonium nitrate, ammonium sulfate and ammonium hydrogen sulfate might be major form of NHS in autumn/winter. Correlation analysis between PM2,5 and so(4)(2-)/NO3-, PM2.5 and OC/EC during different seasons suggested that mobile sources might make an important impact on the increase of PM2.5 concentrations in spring/summer, and stationary sources might play a critical role on the increase of PM2.5 concentrations in autumn/winter. Seven factors were selected in Positive Matrix Factorization (PMF) models analysis based on the Error Estimation (EE) diagnostics during different seasons. Secondary source had the highest contribution to PM2.5 in Heze for the whole year, and followed by coal combustion, vehicle exhaust, soil dust, construction dust, biomass burning and metal manufacturing, and their annual contributions to PM2.5 were 26.5%, 17.2%, 16.5%, 11.5%, 7.7%, 7.0% and 3.8%, respectively. The air masses that were originated from Mongolia reflected the features of large-scale and long-distance air transport; while the air masses that began in Jiangsu, Shandong and Henan showed the features of small-scale and short-distance. Shandong, Henan and Jiangsu were identified as the major potential sources-areas of PM2,5 by using potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models. (C) 2017 Elsevier Ltd. All rights reserved.