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Characterization and source apportionment of PM2.5 based on error estimation from EPA PMF 5.0 model at a medium city in China.
Environ Pollut. 2017 Mar; 222:10-22.EP

Abstract

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 μg/m3 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 NH4+ in autumn/winter. Correlation analysis between PM2.5 and SO42-/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.

Authors+Show Affiliations

State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China. Electronic address: envwujh@nankai.edu.cn.State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.Heze Environmental Monitoring Center Station, Heze, 274000, China.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

28088626

Citation

Liu, Baoshuang, et al. "Characterization and Source Apportionment of PM2.5 Based On Error Estimation From EPA PMF 5.0 Model at a Medium City in China." Environmental Pollution (Barking, Essex : 1987), vol. 222, 2017, pp. 10-22.
Liu B, Wu J, Zhang J, et al. Characterization and source apportionment of PM2.5 based on error estimation from EPA PMF 5.0 model at a medium city in China. Environ Pollut. 2017;222:10-22.
Liu, B., Wu, J., Zhang, J., Wang, L., Yang, J., Liang, D., Dai, Q., Bi, X., Feng, Y., Zhang, Y., & Zhang, Q. (2017). Characterization and source apportionment of PM2.5 based on error estimation from EPA PMF 5.0 model at a medium city in China. Environmental Pollution (Barking, Essex : 1987), 222, 10-22. https://doi.org/10.1016/j.envpol.2017.01.005
Liu B, et al. Characterization and Source Apportionment of PM2.5 Based On Error Estimation From EPA PMF 5.0 Model at a Medium City in China. Environ Pollut. 2017;222:10-22. PubMed PMID: 28088626.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Characterization and source apportionment of PM2.5 based on error estimation from EPA PMF 5.0 model at a medium city in China. AU - Liu,Baoshuang, AU - Wu,Jianhui, AU - Zhang,Jiaying, AU - Wang,Lu, AU - Yang,Jiamei, AU - Liang,Danni, AU - Dai,Qili, AU - Bi,Xiaohui, AU - Feng,Yinchang, AU - Zhang,Yufen, AU - Zhang,Qinxun, Y1 - 2017/01/13/ PY - 2016/09/13/received PY - 2017/01/04/revised PY - 2017/01/04/accepted PY - 2017/1/16/pubmed PY - 2017/2/28/medline PY - 2017/1/16/entrez KW - CWT KW - Chemical species KW - Error estimation KW - PMF KW - PSCF KW - Source apportionment SP - 10 EP - 22 JF - Environmental pollution (Barking, Essex : 1987) JO - Environ. Pollut. VL - 222 N2 - 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 μg/m3 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 NH4+ in autumn/winter. Correlation analysis between PM2.5 and SO42-/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. SN - 1873-6424 UR - https://www.unboundmedicine.com/medline/citation/28088626/Characterization_and_source_apportionment_of_PM2_5_based_on_error_estimation_from_EPA_PMF_5_0_model_at_a_medium_city_in_China_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0269-7491(17)30039-8 DB - PRIME DP - Unbound Medicine ER -