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« Previous AbstractYeast mating pheromone alpha factor inhibits adenylate cyclase    Next AbstractSource apportionment of urban air pollutants using constrained receptor models with a priori profile information »

Environ Pollut


Title:Source and risk apportionment of selected VOCs and PM(2).(5) species using partially constrained receptor models with multiple time resolution data
Author(s):Liao HT; Chou CC; Chow JC; Watson JG; Hopke PK; Wu CF;
Address:"Institute of Occupational Medicine and Industrial Hygiene, National Taiwan University, Taipei, Taiwan. Research Center for Environmental Changes, Academia Sinica, Taipei, Taiwan. Division of Atmospheric Sciences, Desert Research Institute, Reno, NV, USA. Center for Air Resources Engineering and Science and Department of Chemical and Biomolecular Engineering, Clarkson University, Potsdam, NY, USA. Institute of Occupational Medicine and Industrial Hygiene, National Taiwan University, Taipei, Taiwan; Department of Public Health, National Taiwan University, Taipei, Taiwan; Institute of Environmental Health, National Taiwan University, Taipei, Taiwan. Electronic address: changfu@ntu.edu.tw"
Journal Title:Environ Pollut
Year:2015
Volume:20150606
Issue:
Page Number:121 - 130
DOI: 10.1016/j.envpol.2015.05.035
ISSN/ISBN:1873-6424 (Electronic) 0269-7491 (Linking)
Abstract:"This study was conducted to identify and quantify the sources of selected volatile organic compounds (VOCs) and fine particulate matter (PM2.5) by using a partially constrained source apportionment model suitable for multiple time resolution data. Hourly VOC, 12-h and 24-h PM2.5 speciation data were collected during three seasons in 2013. Eight factors were retrieved from the Positive Matrix Factorization solutions and adding source profile constraints enhanced the interpretability of source profiles. Results showed that the evaporative emission factor was the largest contributor (25%) to VOC mass concentration, while the largest contributor to PM2.5 mass concentration was soil dust/regional transport related factor (26%). In terms of risk prioritization, traffic/industry related factor was the major cause for benzene, ethylbenzene, Cr, and polycyclic aromatic hydrocarbons (29-69%) while petrochemical related factor contributed most to the Ni risk (36%). This indicated that a larger contributor to mass concentration may not correspond to a higher risk"
Keywords:"Air Pollutants/*chemistry Air Pollution/*analysis Dust/analysis Environmental Monitoring Models, Theoretical Particulate Matter/*analysis Seasons Volatile Organic Compounds/*chemistry Constrained receptor model Multiple time resolution Positive matrix fac;"
Notes:"MedlineLiao, Ho-Tang Chou, Charles C-K Chow, Judith C Watson, John G Hopke, Philip K Wu, Chang-Fu eng Research Support, Non-U.S. Gov't England 2015/06/10 Environ Pollut. 2015 Oct; 205:121-30. doi: 10.1016/j.envpol.2015.05.035. Epub 2015 Jun 6"

 
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