Modelling organic aerosol over Europe in summer conditions with the VBS-GECKO parameterization: sensitivity to secondary organic compound properties and IVOC emissions

Abstract. The VBS-GECKO parameterization for secondary organic aerosol (SOA) formation was integrated in the chemistry-transport model CHIMERE. Concentrations of organic aerosol (OA) and SOA were simulated over Europe for the July–August 2013 period. Simulated concentrations with the VBS-GECKO were compared to results obtained with the former H2O parameterization implemented in CHIMERE and to observations from EMEP, ACTRIS and other observations available in the EBAS database. The model configuration using the VBS-GECKO parameterization slightly improves the performances compared to the model configuration using the former H2O parameterisation. The VBS-GECKO model configuration performs well for stations showing a large SOA concentration from biogenic sources, especially in northern Europe but underestimate OA concentrations over stations close to urban areas. Simulated OA was found to be mainly secondary (~ 85 %) and from terpene oxidation. Simulations show negligible contribution of the oxidation of mono-aromatic compounds to SOA production. Tests performed to examine the sensitivity of simulated OA concentrations to hydro-solubility, volatility, ageing rates and NOx regime have shown that the VBS-GECKO parameterization provides consistent results, with a weak sensitivity to changes in the parameters provided by the gas phase mechanism included in CHIMERE (e.g. HOx or NOx concentrations). Different emission scenarios (from heavy diesel to light gasoline fleet) were tested to examine the contribution of S/IVOC oxidation to SOA production. At the continental scale, these simulations show a weak sensitivity of OA concentrations to the vehicle fleet. At the local scale, accounting for IVOC emission was found to lead to a substantial increase of OA concentrations in the plume from urban areas, especially if diesel fleet case is assumed. This additional OA source remains too small to explain the gap between simulated and measured values at stations where anthropogenic sources are dominant.