Atmospheric Chemistry and Physics (Jan 2012)

Distributions and regional budgets of aerosols and their precursors simulated with the EMAC chemistry-climate model

  • A. Pozzer,
  • A. de Meij,
  • K. J. Pringle,
  • H. Tost,
  • U. M. Doering,
  • J. van Aardenne,
  • J. Lelieveld

DOI
https://doi.org/10.5194/acp-12-961-2012
Journal volume & issue
Vol. 12, no. 2
pp. 961 – 987

Abstract

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The new global anthropogenic emission inventory (EDGAR-CIRCE) of gas and aerosol pollutants has been incorporated in the chemistry general circulation model EMAC (ECHAM5/MESSy Atmospheric Chemistry). A relatively high horizontal resolution simulation is performed for the years 2005–2008 to evaluate the capability of the model and the emissions to reproduce observed aerosol concentrations and aerosol optical depth (AOD) values. Model output is compared with observations from different measurement networks (CASTNET, EMEP and EANET) and AODs from remote sensing instruments (MODIS and MISR). A good spatial agreement of the distribution of sulfate and ammonium aerosol is found when compared to observations, while calculated nitrate aerosol concentrations show some discrepancies. The simulated temporal development of the inorganic aerosols is in line with measurements of sulfate and nitrate aerosol, while for ammonium aerosol some deviations from observations occur over the USA, due to the wrong temporal distribution of ammonia gas emissions. The calculated AODs agree well with the satellite observations in most regions, while negative biases are found for the equatorial area and in the dust outflow regions (i.e. Central Atlantic and Northern Indian Ocean), due to an underestimation of biomass burning and aeolian dust emissions, respectively. Aerosols and precursors budgets for five different regions (North America, Europe, East Asia, Central Africa and South America) are calculated. Over East-Asia most of the emitted aerosols (precursors) are also deposited within the region, while in North America and Europe transport plays a larger role. Further, it is shown that a simulation with monthly varying anthropogenic emissions typically improves the temporal correlation by 5–10% compared to one with constant annual emissions.