Source apportionment of airborne particulate matter using inorganic and organic species as tracers

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• 作者：Yungang Wang^a ; Philip K. Hopke^b ; ^{hopkepk@clarkson.edu} ; Xiaoyan Xia^b ; Oliver V. Rattigan^c ; David C. Chalupa^d ; ^e ; Mark J. Utell^d ; ^e
• 关键词：Source apportionment ; Positive matrix factorization (PMF) ; Particulate matter (PM) ; Molecular markers (MM) ; Aethalometer Delta-C
• 刊名：Atmospheric Environment
• 出版年：2012
• 期刊代码：11_13522310
• 类别：env
• 出版时间：August, 2012
• 卷：55
• 期：Complete
• 页码：525-532
• 文件大小：1496 K

摘要

Source apportionment is typically performed on chemical composition data derived from particulate matter (PM) samples. However, many common sources no longer emit significant amounts of characteristic trace elements requiring the use of more comprehensive chemical characterization in order to fully resolve the PM sources. Positive matrix factorization (EPA PMF, version 4.1) was used to analyze 24-hr integrated molecular marker (MM), secondary inorganic ions, trace elements, carbonaceous species and light absorption data to investigate sources of PM_2.5 in Rochester, New York between October 2009 and October 2010 to explore the role of specific MMs. An eight-factor solution was found for which the factors were identified as isoprene secondary organic aerosol (SOA), airborne soil, other SOA, diesel emissions, secondary sulfate, wood combustion, gasoline vehicle, and secondary nitrate contributing 6.9%, 12.8%, 3.7%, 7.8%, 45.5%, 9.1%, 7.9%, and 6.3%to the average PM_2.5 concentration, respectively Concentrations of pentacosane, hexacosane, heptacosane, and octacosane in the gasoline vehicles factor were larger compared to diesel emissions. Aethalometer Delta-C was strongly associated with wood combustion. The compounds, n-heptacosanoic acid and n-octacosanoic acid, occasionally used in the past as tracers for road dust, were found to largely associate with SOA in this study. In comparison with a standard PMF analyses without MM, inclusion of them was necessary to resolve SOA and wood combustion factors in urban areas.