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In 2011 the IRSN conducted several assessments of atmospheric radioactive releases due to the Fukushima Daiichi NPP accident (March 11, 2011) and of their impact on Japan's terrestrial environment. They were based on the IRSN's emergency management tools and on the abundant information and technical data gradually published in Japan. According to these assessments, the main release phase lasted from March 12 to 25, 2011 and impacted Japanese land in two events, the first on 15 and 16 March, in which the main radioactive deposits were formed, and the second from March 20 to 23, which was less significant. The highest amounts of radioactive deposits were found in an area extending upwards of several tens of kilometers northwest of the plant. Lower amounts were discontinuously scattered in an area extending up to over 250 km away. Initially composed mainly of short-lived radionuclides, the deposits' activity sharply decreased in the subsequent weeks. Since the summer of 2011, cesium-134 and cesium-137 have become the residual deposits' main components. According to IRSN estimates, in the absence of protection, the doses due to exposure to the radioactive plume during the atmospheric release phase may have been potentially higher for people who remained in coastal areas up to several tens of kilometers north and south of the damaged plant. Thereafter, people living up to 50 km northwest of the plant, outside the 20-km emergency evacuation zone, were potentially most vulnerable to residual radioactive deposits over time. [ABSTRACT FROM AUTHOR]

This paper presents experiments of PM10 data assimilation with the optimal interpolation method. The observations are provided by BDQA (Base de Données sur la Qualité de l'Air), whose monitoring network covers France. Two other databases (EMEP and AirBase) are used to evaluate the improvements in the analyzed state over January 2001 and for several outputs (PM10, PM2.5 and chemical composition). The method is then applied in operational-forecast conditions. It is found that the assimilation of PM10 observations significantly improves the one-day forecast of total mass (PM10 and PM2.5), whereas the improvement is non significant for the two-day forecast. The errors on aerosol chemical composition are sometimes amplified by the assimilation procedure, which shows the need for chemical data. Since the observations cover a limited part of the domain (France versus Europe) and since the method used for assimilation is sequential, we focus on the horizontal and temporal impacts of the assimilation and we study how several parameters of the assimilation system modify these impacts. The strategy followed in this paper, with the optimal interpolation, could be useful for operational forecasts. Meanwhile, considering the weak temporal impact of the approach (about one day), the method has to be improved or other methods have to be considered. [ABSTRACT FROM AUTHOR]

This paper aims at presenting a model-to-data comparison of the Aerosol Optical Thickness (AOT) and of a few sparse data for Single Scattering Albedo (SSA) over Europe for one year. The main contribution of this paper is the sensitivity study to a large number of parameters, including physical and numerical parameters of the aerosol model itself. The optical parameters are computed from a sizeresolved aerosol model embedded in the POLYPHEMUS system. The methodology is first described, showing that several hypothesis can be made for micro-physical aerosol properties. The simulation is made over one year (2001); statistics and monthly time series for the simulation and AERONET data are used to evaluate the ability of the model to reproduce AOT and vertically averaged SSA fields and their variability. The relation with the uncertainties of measurements is discussed. Then a sensitivity study with respect to the mixing state of the particle, the way to take into account water uptake, numerical parameters and physical parameterizations of the model is carried out. The results indicate that the mixing state of particles has an influence on optical parameters, as well as the computation of the wet diameter. But some physical and numerical parameters associated with the aerosol model itself have even more influence under certain conditions, through the uncertainties on the aerosol chemical composition, and their size distribution. [ABSTRACT FROM AUTHOR]

This paper presents experiments of PM10 data assimilation with the optimal interpolation method. The observations are provided by BDQA (Base de Données sur la Qualité de l'Air), whose monitoring network covers France. Two other databases (EMEP and AirBase) are used to evaluate the improvements in the analyzed state over one month (January, 2001) and for several outputs (PM10, PM2.5 and chemical composition). Then, the method is applied in operational conditions. The results show that the assimilation of PM10 observations significantly improves the one-day forecast for total mass (PM10 and PM2.5). The errors on aerosol chemical composition are not reduced and are sometimes amplified by the assimilation procedure, which shows the need for chemical data. As the observations cover a limited part of the domain (France versus Europe) and as the method used for assimilation is sequential, we focus on the horizontal and temporal impacts of assimilation in the last part of this paper. To conclude, we discuss the perspectives, especially the use of a variational method for assimilation or the investigation of the sensitivity to a few choices (e.g., the error statistics, etc.). [ABSTRACT FROM AUTHOR]

Polyphemus is an air quality modeling platform which aims at covering the scope and the abilities of modern air quality systems. It deals with applications from local scale to continental scale, using two Gaussian models and two Eulerian models. It manages passive tracers, radioactive decay, photochemistry and aerosol dynamics. The structure of the system includes four independent levels with data management, physical parameterizations, numerical solvers and high-level methods such as data assimilation. This enables sensitivity and uncertainty analysis, primarily through multimodel approaches. On top of the models, drivers implement advanced methods such as model coupling or data assimilation. [ABSTRACT FROM AUTHOR]

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/evaporation-nucleation. A quasi-stationary sectional approach is used to describe the size distribution change due to condensation/ evaporation, and a hybrid equilibrium/dynamical mass-transfer method has been developed to lower the computational burden. SIREAM uses the same physical parameterizations as those used in the Modal Aerosol Model, MAM Sartelet et al. (2006). It is hosted in the modeling system POLYPHEMUS Mallet et al., 2007, but can be linked to any other three-dimensional Chemistry-Transport Model. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a multi-pollutant sensitivity study of an air quality model over Europe with a focus on aerosols. Following the evaluation presented in the companion paper, the aim here is to study the sensitivity of the model to input data, mathematical parameterizations and numerical approximations. To that end, 30 configurations are derived from a reference configuration of the model by changing one input data set, one parameterization or one numerical approximation at a time. Each of these configurations is compared to the same reference simulation over two time periods of the year 2001, one in summer and one in winter. The sensitivity of the model to the different configurations is evaluated through a statistical comparison between the simulation results and through comparisons to available measurements. The species studied are ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), ammonia (NH3), coarse and fine aerosol particles (PM c and PM2.5), sulfate, nitrate, ammonium, chloride and sodium. For all species, the modeled concentrations are very sensitive to the parameterization used for vertical turbulent diffusion and to the number of vertical levels. For the other configurations considered in this work, the sensitivity of the modeled concentration to configuration choice varies with the species and the period of the year. O3 is impacted by options related to boundary conditions. PM c is sensitive to sea-salt related options, to options influencing deposition and to options related to mass transfer between gas and particulate phases. PM2.5 is sensitive to a larger number of options than PM c : sea-salt, boundary conditions, heterogeneous reactions, aqueous chemistry and gas/particle mass transfer. NO2 is strongly influenced by heterogeneous reactions. Nitrate shows the highest variability of all species studied. As with NO2, nitrate is strongly sensitive to heterogeneous reactions but also to mass transfer, thermodynamic related options, aqueous chemistry and computation of the wet particle diameter. While SO2 is mostly sensitive to aqueous chemistry, sulfate is also sensitive to boundary conditions and, to a lesser extent, to heterogeneous reactions. As with nitrate, ammonium is largely impacted by the different configuration choices, although the sensitivity is slightly lower than for nitrate. NH3 is sensitive to aqueous chemistry, mass transfer and heterogeneous reactions. Chloride and sodium are impacted by sea-salt related options, by options influencing deposition and by options concerning the aqueous-phase module. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]