a b s t r a c tThis study aims to compare the relative impact of biogenic emissions on ozone (O 3 ) and particulate matter (PM) concentrations between North America (NA) and Europe. The simulations are conducted with the Polyphemus air quality modeling system over July and August 2006. Prior to the sensitivity study on the impact of biogenic emissions on air quality, the modeling results are compared to observational data, as well as to the concentrations obtained by other modeling teams of the Air Quality Model Evaluation International Initiative (AQMEII) study.Over Europe, three distinct emission inventories are used. Model performance is satisfactory for O 3 , PM 10 and PM 2.5 with all inventories with respect to the criteria described in the literature. Furthermore, the rmse and errors are lower than the average rmse and errors of the AQMEII simulations. Over North America, the model performance satisfies the criteria described in the literature for O 3 , PM 10 and PM 2.5 . Polyphemus results are within the range of the AQMEII model results. Although the rmse and errors are higher than the average of the AQMEII simulations for O 3 , they are lower for PM 10 and PM 2.5 .The impact of biogenic and anthropogenic emissions on O 3 and PM concentrations is studied by removing alternatively biogenic and anthropogenic emissions in distinct simulations. Because biogenic species interact strongly with NO x , the impact of biogenic emissions on O 3 concentrations varies with variations of the Volatile Organic Compound (VOC)/NO x ratio. This impact is larger over NA than Europe. O 3 decreases by 10e11% on average over Europe and 20% over NA. Locally, the relative impact is also higher in NA (60% maximum) than in Europe (35% maximum). O 3 decreases near large urban centers where biogenic emissions are large (e.g. Los Angeles, Chicago, Houston in NA, Milan in Europe).Most of secondary organic aerosols (SOA) formed at the continental scale over Europe and NA are biogenic aerosols. Eliminating biogenic emissions reduces SOA by 72e88% over Europe and by 90% over NA. However, biogenic SOA are not only impacted by biogenic but also by anthropogenic emissions: eliminating all anthropogenic emissions affects oxidant levels and the absorbing carbon mass, reducing the formation of SOA by 15e16% over Europe and by about 10% over NA; Furthermore, locally, the reduction may be as large as 50%, especially over large urban centers in Europe and NA.

This paper aims at presenting a validation of multi-pollutants over Europe with a focus on aerosols. Chemistry-Transport Models are now used for forecast and emission reduction studies not only for gas-phase species but also for aerosols. Comprehensive model-to-data comparisons are therefore required. We present in this paper a preliminary validation study of the POLYPHEMUS system applied over Europe for 2001. The aerosol model is the SIze REsolved Aerosol Model (SIREAM). It is a sectional model that describes the temporal evolution of the size/composition distribution of atmospheric particles containing a mix of black carbon, mineral dust, inorganic species, and primary and secondary organics. In addition to a brief model description, we present an overview of the model validation. A comprehensive set of model-to-data statistics is computed with observational data extracted from three European databases (the EMEP, AirBase and BDQA databases). Model performance criteria are verified for ozone and particulate matter (PM) and its inorganic components. Comparisons of correlations and root mean square errors with those generated by other models run over Europe for 2001 indicate a good performance of the POLYPHEMUS system. Modifications of the system configuration and parameterizations may have a significant impact on error statistics, which may question the robustness of such models. Because large differences exist between databases, the robustness of model-to-data error statistics is also investigated.

International audienceInverse modelling techniques can be used to estimate the amount of radionuclides and the temporal profile of the source term released in the atmosphere during the accident of the Fukushima Daiichi nuclear power plant in March 2011. In Winiarek et al. (2012b), the lower bounds of the caesium-137 and iodine-131 source terms were estimated with such techniques, using activity concentration measurements. The importance of an objective assessment of prior errors (the observation errors and the background errors) was emphasised for a reliable inversion. In such critical context where the meteorological conditions can make the source term partly unobservable and where only a few observations are available, such prior estimation techniques are mandatory, the retrieved source term being very sensitive to this estimation. We propose to extend the use of these techniques to the estimation of prior errors when assimilating observations from several data sets. The aim is to compute an estimate of the caesium-137 source term jointly using all available data about this radionuclide, such as activity concentrations in the air, but also daily fallout measurements and total cumulated fallout measurements. It is crucial to properly and simultaneously estimate the background errors and the prior errors relative to each data set. A proper estimation of prior errors is also a necessary condition to reliably estimate the a posteriori uncertainty of the estimated source term. Using such techniques, we retrieve a total released quantity of caesium-137 in the interval 11.6 − 19.3 PBq with an estimated standard deviation range of 15 − 20% depending on the method and the data sets. The "blind" time intervals of the source term have also been strongly mitigated compared to the first estimations with only activity concentration data