International audienceThe Chernobyl nuclear accident, and more recently the Fukushima accident, highlighted that the largest source of error on consequences assessment is the source term, including the time evolution of the release rate and its distribution between radioisotopes. Inverse modeling methods, which combine environmental measurements and atmospheric dispersion models, have proven efficient in assessing source term due to an accidental situation (Gudiksen, 1989; Krysta and Bocquet, 2007; Stohl et al., 2012a; Winiarek et al., 2012). Most existing approaches are designed to use air sampling measurements (Winiarek et al., 2012) and some of them also use deposition measurements (Stohl et al., 2012a; Winiarek et al., 2014). Some studies have been performed to use dose rate measurements (Duranova et al., 1999; Astrup et al., 2004; Drews et al., 2004; Tsiouri et al., 2012) but none of the developed methods were carried out to assess the complex source term of a real accident situation like the Fukushima accident. However, dose rate measurements are generated by the most widespread measurement system, and in the event of a nuclear accident, these data constitute the main source of measurements of the plume and radioactive fallout during releases. This paper proposes a method to use dose rate measurements as part of an inverse modeling approach to assess source terms. The method is proven efficient and reliable when applied to the accident at the Fukushima Daiichi Nuclear Power Plant (FD-NPP). The emissions for the eight main isotopes 133Xe, 134Cs, 136Cs, 137Cs, 137mBa, 131I, 132I and 132Te have been assessed. Accordingly, 105.9 PBq of 131I, 35.8 PBq of 132I, 15.5 PBq of 137Cs and 12 134 PBq of noble gases were released. The events at FD-NPP (such as venting, explosions, etc.) known to have caused atmospheric releases are well identified in the retrieved source term. The estimated source term is validated by comparing simulations of atmospheric dispersion and deposition with environmental observations. In total, it was found that for 80% of the measurements, simulated and observed dose rates agreed within a factor of 2. Changes in dose rates over time have been overall properly reconstructed, especially in the most contaminated areas to the northwest and south of the FD-NPP. A comparison with observed atmospheric activity concentration and surface deposition shows that the emissions of caesiums and 131I are realistic but that 132I and 132Te are probably underestimated and noble gases are likely overestimated. Finally, an important outcome of this study is that the method proved to be perfectly suited to emergency management and could contribute to improve emergency response in the event of a nuclear accident

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.

Abstract. We briefly present in this short paper a new SIze REsolved Aerosol Model (SIREAM) which simulates the evolution of atmospheric aerosol by solving the General Dynamic Equation (GDE). SIREAM segregates the aerosol size distribution into sections and solves the GDE by splitting coagulation and condensation/evaporationnucleation. A quasi-stationary sectional approach is used to describe the size distribution change due to condensation/evaporation, and a hybrid equilibrium/dynamical masstransfer method has been developed to lower the computational burden. SIREAM uses the same physical parameterizations as those used in the Modal Aerosol Model, MAM . It is hosted in the modeling system POLYPHEMUS Mallet et al., 2007, but can be linked to any other three-dimensional Chemistry-Transport Model.

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