GSTDTAP  > 地球科学
DOI10.5194/acp-19-973-2019
Positive matrix factorization of organic aerosol: insights from a chemical transport model
Drosatou, Anthoula D.1,2; Skyllakou, Ksakousti2; Theodoritsi, Georgia N.1,2; Pandis, Spyros N.1,2,3
2019-01-24
发表期刊ATMOSPHERIC CHEMISTRY AND PHYSICS
ISSN1680-7316
EISSN1680-7324
出版年2019
卷号19期号:2页码:973-986
文章类型Article
语种英语
国家Greece; USA
英文摘要

Factor analysis of aerosol mass spectrometer measurements (organic aerosol mass spectra) is often used to determine the sources of organic aerosol (OA). In this study we aim to gain insights regarding the ability of positive matrix factorization (PMF) to identify and quantify the OA sources accurately. We performed PMF and multilinear engine (ME-2) analysis on the predictions of a state-of-the-art chemical transport model (PMCAMx-SR, Particulate Matter Comprehensive Air Quality Model with extensions - source resolved) during a photochemically active period for specific sites in Europe in an effort to interpret the diverse factors usually identified by PMF analysis of field measurements. Our analysis used the predicted concentrations of 27 OA components, assuming that each of them is "chemically different" from the others.


The PMF results based on the chemical transport model predictions are quite consistent (same number of factors and source types) with those of the analysis of AMS measurements. The estimated uncertainty of the contribution of fresh biomass burning is less than 30% and of the other primary sources less than 40 %, when these sources contribute more than 20% to the total OA. The PMF uncertainty increases for smaller source contributions, reaching a factor of 2 or even 3 for sources which contribute less than 10% to the OA.


One of the major questions in PMF analysis of AMS measurements concerns the sources of the two or more oxygenated OA (OOA) factors often reported in field studies. Our analysis suggests that these factors include secondary OA compounds from a variety of anthropogenic and biogenic sources and do not correspond to specific sources. Their characterization in the literature as low- and high-volatility factors is probably misleading, because they have overlapping volatility distributions. However, the average volatility of the one often characterized as a low-volatility factor is indeed lower than that of the other (high-volatility factor). Based on the analysis of the PMCAMx-SR predictions, the first oxygenated OA factor includes mainly highly aged OA transported from outside Europe, but also highly aged secondary OA from precursors emitted in Europe. The second oxygenated OA factor contains fresher secondary organic aerosol from volatile, semivolatile, and intermediate volatility anthropogenic and biogenic organic compounds. The exact contribution of these OA components to each OA factor depends on the site and the prevailing meteorology during the analysis period.


领域地球科学
收录类别SCI-E
WOS记录号WOS:000456710100005
WOS关键词BASIS-SET APPROACH ; SOURCE APPORTIONMENT ; MASS-SPECTROMETER ; MULTILINEAR ENGINE ; HYDROCARBON-LIKE ; VOLATILITY ; SEMIVOLATILE ; COMPONENTS ; MEGACITY ; WINTERTIME
WOS类目Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/23875
专题地球科学
作者单位1.Univ Patras, Dept Chem Engn, Patras, Greece;
2.Fdn Res & Technol Hellas FORTH ICE HT, Inst Chem Engn Sci, Patras, Greece;
3.Carnegie Mellon Univ, Dept Chem Engn, Pittsburgh, PA 15213 USA
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Drosatou, Anthoula D.,Skyllakou, Ksakousti,Theodoritsi, Georgia N.,et al. Positive matrix factorization of organic aerosol: insights from a chemical transport model[J]. ATMOSPHERIC CHEMISTRY AND PHYSICS,2019,19(2):973-986.
APA Drosatou, Anthoula D.,Skyllakou, Ksakousti,Theodoritsi, Georgia N.,&Pandis, Spyros N..(2019).Positive matrix factorization of organic aerosol: insights from a chemical transport model.ATMOSPHERIC CHEMISTRY AND PHYSICS,19(2),973-986.
MLA Drosatou, Anthoula D.,et al."Positive matrix factorization of organic aerosol: insights from a chemical transport model".ATMOSPHERIC CHEMISTRY AND PHYSICS 19.2(2019):973-986.
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