atmos. chem. phys., 14, 6159–6176

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  • Atmos. Chem. Phys., 14, 61596176, Author(s) 2014. CC Attribution 3.0 License.

    Organic aerosol components derived from 25 AMS data sets acrossEurope using a consistent ME-2 based source apportionmentapproach

    M. Crippa 1,*, F. Canonaco1, V. A. Lanz1, M. ijl 2, J. D. Allan3,17, S. Carbone4, G. Capes3, D. Ceburnis13,M. DallOsto 5, D. A. Day6, P. F. DeCarlo1,** , M. Ehn2, A. Eriksson7, E. Freney8, L. Hildebrandt Ruiz 9,*** , R. Hillamo4,J. L. Jimenez6, H. Junninen2, A. Kiendler-Scharr10, A.-M. Kortelainen 11, M. Kulmala 2, A. Laaksonen11, A.A. Mensah10,**** , C. Mohr1,***** , E. Nemitz12, C. ODowd13, J. Ovadnevaite13, S. N. Pandis14, T. Petj2, L. Poulain15,S. Saarikoski4, K. Sellegri8, E. Swietlicki7, P. Tiitta11, D. R. Worsnop2,4,11,16, U. Baltensperger1, and A. S. H. Prvt1

    1Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 PSI Villigen, Switzerland2Department of Physics, P.O. Box 64, University of Helsinki, 00014 Helsinki, Finland3School of Earth, Atmospheric & Environmental Sciences, The University of Manchester, Manchester, UK4Air Quality Research, Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland5Institute of Environmental Assessment and Water Research (IDAEA), CSIC, 08034 Barcelona, Spain6Cooperative Institute for Research in Environmental Sciences (CIRES), Boulder, CO, USA7Division of Nuclear Physics, University of Lund, 221 00 Lund, Sweden8Laboratoire de Mtorologie Physique, CNRS-Universit Blaise Pascal, UMR6016, 63117, Clermont Ferrand, France9Center for Atmospheric Particle Studies, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA, 15213, USA10Institut fr Energie- und Klimaforschung: Troposphre (IEK 8), Forschungszentrum Jlich GmbH, Jlich, Germany11Department of Environmental Science, Univ. of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland12Centre for Ecology and Hydrology, Bush Estate, Penicuik, Midlothian, EH26 0QB, UK13School of Physics & Centre for Climate & Air Pollution Studies, National University of Ireland Galway, Galway, Ireland14Institute of Chemical Engineering Sciences (ICE-HT), Foundation for Research and Technology Hellas (FORTH), Patras,26504, Greece15Leibniz Institute for Tropospheric Research, Permoserstr. 15, 04318 Leipzig, Germany16Aerodyne Research, Inc. Billerica, MA, USA17National Centre for Atmospheric Science, The University of Manchester, Manchester, UK* now at: European Commission, Joint Research Centre, Institute for Environment and Sustainability, Air and Climate Unit,Via Fermi, 2749, 21027 Ispra, Italy** now at: Department of Civil, Architectural, and Environmental Engineering and Department of Chemistry, DrexelUniversity, Philadelphia, PA, 19104, USA*** now at: The University of Texas at Austin, McKetta Department of Chemical Engineering, Austin, TX, 78712, USA**** now at: ETH Zurich, Institute for Atmospheric and Climate Science, Zurich, Switzerland***** now at: Department of Atmospheric Sciences, University of Washington, Seattle WA 98195, USA

    Correspondence to:A. S. H. Prvt (

    Received: 7 August 2013 Published in Atmos. Chem. Phys. Discuss.: 5 September 2013Revised: 18 April 2014 Accepted: 3 May 2014 Published: 23 June 2014

    Published by Copernicus Publications on behalf of the European Geosciences Union.

  • 6160 M. Crippa et al.: Organic aerosol components derived from 25 AMS datasets

    Abstract. Organic aerosols (OA) represent one of the ma-jor constituents of submicron particulate matter (PM1) andcomprise a huge variety of compounds emitted by differentsources. Three intensive measurement field campaigns to in-vestigate the aerosol chemical composition all over Europewere carried out within the framework of the European In-tegrated Project on Aerosol Cloud Climate and Air Qual-ity Interactions (EUCAARI) and the intensive campaigns ofEuropean Monitoring and Evaluation Programme (EMEP)during 2008 (MayJune and SeptemberOctober) and 2009(FebruaryMarch). In this paper we focus on the identifi-cation of the main organic aerosol sources and we define astandardized methodology to perform source apportionmentusing positive matrix factorization (PMF) with the multilin-ear engine (ME-2) on Aerodyne aerosol mass spectrometer(AMS) data. Our source apportionment procedure is testedand applied on 25 data sets accounting for two urban, sev-eral rural and remote and two high altitude sites; thereforeit is likely suitable for the treatment of AMS-related am-bient data sets. For most of the sites, four organic compo-nents are retrieved, improving significantly previous sourceapportionment results where only a separation in primaryand secondary OA sources was possible. Generally, our solu-tions include two primary OA sources, i.e. hydrocarbon-likeOA (HOA) and biomass burning OA (BBOA) and two sec-ondary OA components, i.e. semi-volatile oxygenated OA(SV-OOA) and low-volatility oxygenated OA (LV-OOA).For specific sites cooking-related (COA) and marine-relatedsources (MSA) are also separated. Finally, our work providesa large overview of organic aerosol sources in Europe and aninteresting set of highly time resolved data for modeling pur-poses.

    1 Introduction

    Atmospheric aerosols negatively affect human health (Popeand Dockery, 2006), reduce visibility, and interact with cli-mate and ecosystems (IPCC, 2007). Among particulate pol-lutants, great interest is dedicated to organic aerosols (OA)since they can represent from 20 to 90 % of the total sub-micron mass (Zhang et al., 2007; Jimenez et al., 2009). Or-ganic aerosols are ubiquitous and are directly emitted by vari-ous sources, including traffic, combustion activities, biogenicemissions, and can also be produced via secondary formationpathways in the atmosphere (Hallquist et al., 2009). Con-straining OA emission sources and understanding their evo-lution and fate in the atmosphere is therefore fundamental todefine mitigation strategies for air quality.

    Our work is part of the European Integrated Project onAerosol Cloud Climate and Air Quality Interactions (EU-CAARI), which aims to understand the interactions betweenair pollution and climate. An introduction about project ob-jectives and an overview on the goals reached within the EU-

    CAARI project are provided by several papers (Kulmala etal., 2009, 2011; Knote et al., 2011; Fountoukis et al., 2011;Murphy et al., 2012). The coordinated EUCAARI campaignsof 2008 and 2009 provide significantly more aerosol massspectrometer (AMS) data sets to analyze in comparison toprevious efforts (Aas et al., 2012). For the investigationof the aerosol chemical composition and organic aerosol(OA) sources dedicated studies were performed. Nemitz etal. (2014) discuss the organic and inorganic components ofatmospheric aerosols, using AMS measurements performedduring three intensive field campaigns in 2008 and 2009. Ma-jor contribution to the submicron particulate matter (PM1)mass is provided by the organic compounds, which con-tribute from 20 to 63 % to the total mass depending on thesite. Our work deals with the identification and quantifica-tion of organic aerosol sources in Europe using high timeresolution data from aerosol mass spectrometer. Here we fo-cus on the investigation of OA sources applying the positivematrix factorization algorithm (PMF) running on the gener-alized multi-linear engine (ME-2) (Paatero, 1999; Canonacoet al., 2013) to the organic AMS mass spectra from all overEurope.

    Currently, only a few studies concerning a broad spatialoverview of OA sources are available in the literature. Zhanget al. (2007) investigated organic aerosol sources in urbanand anthropogenically influenced remote sites in the North-ern Hemisphere, focusing on the discrimination between thetraffic-related and secondary oxygenated OA components.Jimenez et al. (2009) presented an overview of PM1 chemicalcomposition all over the world (including 8 European mea-surement sites) focusing on the identification of OA sourcesusing AMS data. Ng et al. (2010) provided an overview ofOA sources in the Northern Hemisphere, including a broaderspatial domain than Europe and a wide range of locationsaffected by different aerosol sources. Moreover, their ma-jor focus was the investigation of the secondary oxygenatedcomponents and their aging. Lanz et al. (2010) providedan overview of the aerosol chemical composition and OAsources in central Europe focusing on Switzerland, Germany,Austria, France, and Liechtenstein. In all of these studies,the major fraction of PM1 was often represented by organ-ics which consisted, for most of the locations, of oxygenatedOA; however the contribution of primary sources (like trafficand biomass burning) was not always identified especially inrural and remote places. Our work includes 17 measurementsites all over Europe, comprising 25 unit mass resolutionAMS data sets, and represents therefore an unprecedentedoverview of OA sources in Europe. Moreover, the applicationof advanced source apportionment methods allow us to over-come limitations of commonly used source apportionmenttechniques for AMS data, such as the purely unconstrainedpositive matrix factorization (Canonaco et al., 2013). Thepositive matrix factorization (PMF) model does not alwayssucceed since the co-variance of the sources might be largedue to the meteorology and the relative source contributions

    Atmos. Chem. Phys., 14, 61596176, 2014

  • M. Crippa et al.: Organic aerosol components derived from 25 AMS datasets 6161

    which vary too little. This can often be the case at rural andremote sites but it was also shown for an urban backgroundsite in Zurich, for which Lanz et al. (2008) pioneered the useof ME-2 for AMS data. Here, for all measurement sites weare able to clearly separate primary and secondary OA com-ponents, including hydr