Articles | Volume 10, issue 10
Atmos. Chem. Phys., 10, 4775–4793, 2010

Special issue: European Integrated Project on Aerosol-Cloud-Climate and Air...

Atmos. Chem. Phys., 10, 4775–4793, 2010

  26 May 2010

26 May 2010

Explaining global surface aerosol number concentrations in terms of primary emissions and particle formation

D. V. Spracklen1, K. S. Carslaw1, J. Merikanto1, G. W. Mann1, C. L. Reddington1, S. Pickering1, J. A. Ogren2, E. Andrews2, U. Baltensperger3, E. Weingartner3, M. Boy4, M. Kulmala4, L. Laakso4, H. Lihavainen5, N. Kivekäs5, M. Komppula5,20, N. Mihalopoulos6, G. Kouvarakis6, S. G. Jennings7, C. O'Dowd7, W. Birmili8, A. Wiedensohler8, R. Weller9, J. Gras10, P. Laj11, K. Sellegri12, B. Bonn13, R. Krejci14, A. Laaksonen5,15, A. Hamed15, A. Minikin16, R. M. Harrison17, R. Talbot18, and J. Sun19 D. V. Spracklen et al.
  • 1Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, LS2 9JT, UK
  • 2NOAA/ESRL Global Monitoring Division, 325 Broadway R/GMD1, Boulder, Co 80305, USA
  • 3Paul Scherrer Institut, Laboratory of Atmospheric Chemistry, 5232 Villigen, Switzerland
  • 4Department of Physics, University of Helsinki, 00014 Helsinki, Finland
  • 5Climate Change, Finnish Meteorological Institute, P.O. Box 503, 00101, Helsinki, Finland
  • 6Department of Chemistry, University of Crete, University campus, P.O. Box 2208, 71003, Voutes, Heraklion, Crete, Greece
  • 7Department of Physics, National University of Ireland, Galway, Ireland
  • 8Leibniz Institute for Tropospheric Research, Permoserstrasse 15, 04318 Leipzig, Germany
  • 9Alfred Wegener Institute, Am Handelshafen 12, 27570 Bremerhaven, Germany
  • 10CSIRO Marine and Atmospheric Research, Ctr Australian Weather and Climate Res, Aspendale, Victoria, Australia
  • 11Laboratoire de Glaciologie et Géophysique de l'Environnement CNRS/Université Grenoble 1, Grenoble, France
  • 12Laboratoire de Météorologie Physique, Université Clermont-Ferrand/ CNRS, Clermont-Ferrand, France
  • 13Institute for Atmospheric and Environmental Sciences, J. W. Goethe University, Frankfurt/Main, Germany
  • 14Department of Applied Environmental Science (ITM), Stockholm University, 106 91 Stockholm, Sweeden
  • 15Department of Physics and Mathematics, University of Eastern Finland, (Kuopio campus), P.O. Box 70211 Kuopio, Finland
  • 16Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut f�r Physik der Atmosphäre, Oberpfaffenhofen, Germany
  • 17National Centre for Atmospheric Science, School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
  • 18Climate Change Research Center, University of New Hampshire, Durham, NH 03824 USA
  • 19Key Laboratory for Atmospheric Chemistry of CMA, Center for Atmosphere Watch and Services, Chinese Academy of Meteorological Sciences, CMA, Beijing 100081, China
  • 20Kuopio Unit, Finnish Meteorological Institute, Kuopio, Finland

Abstract. We synthesised observations of total particle number (CN) concentration from 36 sites around the world. We found that annual mean CN concentrations are typically 300–2000 cm−3 in the marine boundary layer and free troposphere (FT) and 1000–10 000 cm−3 in the continental boundary layer (BL). Many sites exhibit pronounced seasonality with summer time concentrations a factor of 2–10 greater than wintertime concentrations. We used these CN observations to evaluate primary and secondary sources of particle number in a global aerosol microphysics model. We found that emissions of primary particles can reasonably reproduce the spatial pattern of observed CN concentration (R2=0.46) but fail to explain the observed seasonal cycle (R2=0.1). The modeled CN concentration in the FT was biased low (normalised mean bias, NMB=−88%) unless a secondary source of particles was included, for example from binary homogeneous nucleation of sulfuric acid and water (NMB=−25%). Simulated CN concentrations in the continental BL were also biased low (NMB=−74%) unless the number emission of anthropogenic primary particles was increased or a mechanism that results in particle formation in the BL was included. We ran a number of simulations where we included an empirical BL nucleation mechanism either using the activation-type mechanism (nucleation rate, J, proportional to gas-phase sulfuric acid concentration to the power one) or kinetic-type mechanism (J proportional to sulfuric acid to the power two) with a range of nucleation coefficients. We found that the seasonal CN cycle observed at continental BL sites was better simulated by BL particle formation (R2=0.3) than by increasing the number emission from primary anthropogenic sources (R2=0.18). The nucleation constants that resulted in best overall match between model and observed CN concentrations were consistent with values derived in previous studies from detailed case studies at individual sites. In our model, kinetic and activation-type nucleation parameterizations gave similar agreement with observed monthly mean CN concentrations.

Final-revised paper