Articles | Volume 14, issue 12
Atmos. Chem. Phys., 14, 6159–6176, 2014
Atmos. Chem. Phys., 14, 6159–6176, 2014

Research article 23 Jun 2014

Research article | 23 Jun 2014

Organic aerosol components derived from 25 AMS data sets across Europe using a consistent ME-2 based source apportionment approach

M. Crippa1,*, F. Canonaco1, V. A. Lanz1, M. Äijälä2, J. D. Allan3,17, S. Carbone4, G. Capes3, D. Ceburnis13, M. Dall'Osto5, D. A. Day6, P. F. DeCarlo1,**, M. Ehn2, A. Eriksson7, E. Freney8, L. Hildebrandt Ruiz9,***, R. Hillamo4, J. L. Jimenez6, H. Junninen2, A. Kiendler-Scharr10, A.-M. Kortelainen11, M. Kulmala2, A. Laaksonen11, A. A. Mensah10,****, C. Mohr1,*****, E. Nemitz12, C. O'Dowd13, J. Ovadnevaite13, S. N. Pandis14, T. Petäjä2, L. Poulain15, S. Saarikoski4, K. Sellegri8, E. Swietlicki7, P. Tiitta11, D. R. Worsnop2,4,11,16, U. Baltensperger1, and A. S. H. Prévôt1 M. Crippa et al.
  • 1Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 PSI Villigen, Switzerland
  • 2Department of Physics, P.O. Box 64, University of Helsinki, 00014 Helsinki, Finland
  • 3School of Earth, Atmospheric {&} Environmental Sciences, The University of Manchester, Manchester, UK
  • 4Air Quality Research, Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
  • 5Institute of Environmental Assessment and Water Research (IDAEA), CSIC, 08034 Barcelona, Spain
  • 6Cooperative Institute for Research in Environmental Sciences (CIRES), Boulder, CO, USA
  • 7Division of Nuclear Physics, University of Lund, 221 00 Lund, Sweden
  • 8Laboratoire de Météorologie Physique, CNRS-Université Blaise Pascal, UMR6016, 63117, Clermont Ferrand, France
  • 9Center for Atmospheric Particle Studies, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA, 15213, USA
  • 10Institut für Energie- und Klimaforschung: Troposphäre (IEK 8), Forschungszentrum Jülich GmbH, Jülich, Germany
  • 11Department of Environmental Science, Univ. of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland
  • 12Centre for Ecology and Hydrology, Bush Estate, Penicuik, Midlothian, EH26 0QB, UK
  • 13School of Physics {&} Centre for Climate & Air Pollution Studies, National University of Ireland Galway, Galway, Ireland
  • 14Institute of Chemical Engineering Sciences (ICE-HT), Foundation for Research and Technology Hellas (FORTH), Patras, 26504, Greece
  • 15Leibniz Institute for Tropospheric Research, Permoserstr. 15, 04318 Leipzig, Germany
  • 16Aerodyne Research, Inc. Billerica, MA, USA
  • 17National 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, Drexel University, 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

Abstract. Organic aerosols (OA) represent one of the major constituents of submicron particulate matter (PM1) and comprise a huge variety of compounds emitted by different sources. Three intensive measurement field campaigns to investigate the aerosol chemical composition all over Europe were carried out within the framework of the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI) and the intensive campaigns of European Monitoring and Evaluation Programme (EMEP) during 2008 (May–June and September–October) and 2009 (February–March). In this paper we focus on the identification of the main organic aerosol sources and we define a standardized methodology to perform source apportionment using positive matrix factorization (PMF) with the multilinear engine (ME-2) on Aerodyne aerosol mass spectrometer (AMS) data. Our source apportionment procedure is tested and applied on 25 data sets accounting for two urban, several rural and remote and two high altitude sites; therefore it is likely suitable for the treatment of AMS-related ambient data sets. For most of the sites, four organic components are retrieved, improving significantly previous source apportionment results where only a separation in primary and secondary OA sources was possible. Generally, our solutions include two primary OA sources, i.e. hydrocarbon-like OA (HOA) and biomass burning OA (BBOA) and two secondary 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-related sources (MSA) are also separated. Finally, our work provides a large overview of organic aerosol sources in Europe and an interesting set of highly time resolved data for modeling purposes.

Final-revised paper