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Discussion papers
https://doi.org/10.5194/acp-2019-468
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2019-468
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 19 Jun 2019

Research article | 19 Jun 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

Sources of organic aerosols in Europe: A modelling study using CAMx with modified volatility basis set scheme

Jianhui Jiang1, Sebnem Aksoyoglu1, Imad El-Haddad1, Giancarlo Ciarelli2, Hugo A. C. Denier van der Gon3, Francesco Canonaco1, Stefania Gilardoni4, Marco Paglione4,a, María Cruz Minguillón5, Olivier Favez6, Yunjiang Zhang6,7, Nicolas Marchand8, Liqing Hao9, Annele Virtanen9, Kalliopi Florou10, Colin O’Dowd11, Jurgita Ovadnevaite11, Urs Baltensperger1, and André S. H. Prévôt1 Jianhui Jiang et al.
  • 1Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland
  • 2Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, USA
  • 3TNO, Department of Climate, Air and Sustainability, Utrecht, the Netherlands
  • 4Italian National Research Council – Institute of Atmospheric Sciences and Climate, Bologna, Italy
  • 5Institute of Environmental Assessment and Water Research (IDAEA), CSIC, 08034 Barcelona, Spain
  • 6Institut National de l'Environnement Industriel et des Risques (INERIS), Verneuil-en-Halatte, France
  • 7Laboratoire des Sciences du Climat et de l’Environnement (LSCE), Gif-sur-Yvette, France
  • 8Aix-Marseille Univ, CNRS, LCE, Marseille, France
  • 9Department of Applied Physics, University of Eastern Finland, P.O. Box 1627, FI-70211 Kuopio, Finland
  • 10Department of Chemical Engineering, University of Patras, 26500 Patras, Greece
  • 11School of Physics, Ryan Institute’s Centre for Climate and Air Pollution Studies, and Marine Renewable Energy Ireland, National University of Ireland Galway, University Road, Galway, H91 CF50, Ireland
  • anow at: Institute of Chemical Engineering Sciences, Foundation for Research and Technology Hellas (FORTH/ICE-HT), Patras, Greece

Abstract. Source apportionment of organic aerosols (OA) is of great importance to better understand the health impact and climate effects of particulate matter air pollution. Air quality models act as potential tools to identify OA components and sources at high spatial and temporal resolution, however, they generally underestimate OA concentrations, and comparisons of their outputs with an extended set of measurements are still rare due to the lack of long-term experimental data. In this study, we addressed such challenges at the European level. Using the regional air quality model Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and contained more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a whole-year period (2011). We modelled separately the primary and secondary OA contributions from old and new diesel and gasoline vehicles, biomass burning (mostly residential wood burning and agricultural waste burning excluding wildfires), other anthropogenic sources (mainly shipping, industry and energy production) and biogenic sources. An important feature of this study is that we evaluated the model results with measurements over a longer period than in the previous studies which strengthens our confidence in our modelled source apportionment results. Comparison against positive matrix factorization (PMF) analyses of aerosol mass spectrometric measurements at nine European sites suggested that the modified VBS scheme improved the model performance for total OA as well as the OA components, including hydrocarbon-like (HOA), biomass burning (BBOA) and oxygenated components (OOA). By using the modified VBS scheme, the mean bias of OOA was reduced from −1.3 μg m−3 to −0.4 μg m−3 corresponding to a reduction of mean fractional bias from −45 % to −20 %. The winter OOA simulation, which was largely underestimated in previous studies, was improved by 29 %–42 % among the evaluated sites compared to the default parameterization. Wood burning was the dominant OA source in winter (61 %) while biogenic emissions contributed ~55 % to OA during summer in Europe on average. In both seasons, the other anthropogenic sources comprised the second largest component (9 % in winter and 19 % in summer as domain average), while the average contributions of diesel and gasoline vehicles were rather small (~5 %) except for the metropolitan areas where the highest contribution reached 31 %. The results indicate the need to improve the emission inventory to include currently missing and highly uncertain local emissions, as well as further improvement of VBS parameterization for winter biomass burning. Although this study focused on Europe, it can be applied in any other part of the globe. This study highlights the ability of long-term measurements and source apportionment modelling to validate and improve emission inventories, and identify sources not yet properly included in existing inventories.

Jianhui Jiang et al.
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Short summary
We use an air quality model with modified organic aerosol (OA) module based on chamber experiments to identify the OA sources and their contributions in Europe. Comparisons with long-term measurements at nine sites in 2011 show an improvement in OA simulation. Our results suggest that the biomass burning and biogenic emissions are the dominant sources in winter and summer, respectively. Contributions of diesel and gasoline vehicles are relatively small compared to a previous study in the US.
We use an air quality model with modified organic aerosol (OA) module based on chamber...
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