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Characteristics of the chemical composition and source apportionment of PM2.5 for a one-year period in Wuhan,China
Authors:Zhang  Xiaoyu  Ji  Guixiang  Peng  Xiaowu  Kong  Lingya  Zhao  Xin  Ying  Rongrong  Yin  Wenjun  Xu  Tian  Cheng  Juan  Wang  Lin
Institution:1.Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing, 210042, China
;2.State Environmental Protection Key Laboratory of Eniromental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou, 510655, China
;3.School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
;
Abstract:

In this study, 123 PM2.5 filter samples were collected in Wuhan, Hubei province from December 2014 to November 2015. Water- soluble inorganic ions (WSIIs), elemental carbon (EC), organic carbon (OC) and inorganic elements were measured. Source apportionment and back trajectory was investigated by the positive matrix factorization (PMF) model and the hybrid single particle lagrangian integrated trajectory (HYSPLIT) model, respectively. The annual PM2.5 concentration was 80.5?±?38.2 μg/m3, with higher PM2.5 in winter and lower in summer. WSIIs, OC, EC, as well as elements contributed 46.8%, 14.8%, 6.7% and 8% to PM2.5 mass concentration, respectively. SO42?, NO3? and NH4+ were the dominant components, accounting for 40.2% of PM2.5 concentrations. S, K, Cl, Ba, Fe, Ca and I were the main inorganic elements, and accounted for 65.2% of the elemental composition. The ratio of NO3?/SO42? was 0.86?±?0.72, indicating that stationary sources play dominant role on PM2.5 concentration. The ratio of OC/EC was 2.9?±?1.4, suggesting the existence of secondary organic carbon (SOC). Five sources were identified using PMF model, which included secondary inorganic aerosols (SIA), coal combustion, industry, vehicle emission, fugitive dust. SIA, coal combustion, as well as industry were the dominant contributors to PM2.5 pollution, accounting for 34.7%, 20.5%, 19.6%, respectively.

Keywords:
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