气候变化领域集成服务门户(CCPortal): Positive matrix factorization of organic aerosol: Insights from a chemical transport model

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DOI	10.5194/acp-19-973-2019
	Positive matrix factorization of organic aerosol: Insights from a chemical transport model
	Drosatou A.D.; Skyllakou K.; Theodoritsi G.N.; Pandis S.N.
发表日期	2019
ISSN	16807316
起始页码	973
结束页码	986
卷号	19 期号:2
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. © Author(s) 2019.
语种	英语
scopus关键词	aerosol; biomass burning; concentration (composition); mass spectrometry; modeling; Europe
来源期刊	Atmospheric Chemistry and Physics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/144697
作者单位	Department of Chemical Engineering, University of Patras, Patras, Greece; Institute of Chemical Engineering Sciences, Foundation for Research and Technology Hellas (FORTH/ICE-HT), Patras, Greece; Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, United States
推荐引用方式 GB/T 7714	Drosatou A.D.,Skyllakou K.,Theodoritsi G.N.,et al. Positive matrix factorization of organic aerosol: Insights from a chemical transport model[J],2019,19(2).
APA	Drosatou A.D.,Skyllakou K.,Theodoritsi G.N.,&Pandis S.N..(2019).Positive matrix factorization of organic aerosol: Insights from a chemical transport model.Atmospheric Chemistry and Physics,19(2).
MLA	Drosatou A.D.,et al."Positive matrix factorization of organic aerosol: Insights from a chemical transport model".Atmospheric Chemistry and Physics 19.2(2019).