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.

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Technical Note: The air quality modeling system Polyphemus

A review of tephra transport and dispersal models: Evolution, current status, and future perspectives

. The 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 133 Xe, 134 Cs, 136 Cs, 137 Cs, 137m Ba, 131 I, 132 I and 132 Te have been assessed. Accordingly, 105.9 PBq of 131 I, 35.8 PBq of 132 I, 15.5 PBq of 137 Cs 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 131 I are realistic but that 132 I and 132 Te 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.

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An inverse modeling method to assess the source term of the Fukushima Nuclear Power Plant accident using gamma dose rate observations

This paper estimates the uncertainty in the outputs of a chemistry-transport model due to physical parameterizations and numerical approximations. An ensemble of 20 simulations is generated from a reference simulation in which one key parameterization (chemical mechanism, dry deposition parameterization, turbulent closure, etc.) or one numerical approximation (grid size, splitting method, etc.) is changed at a time. Intercomparisons of the simulations and comparisons with observations allow us to assess the impact of each parameterization and numerical approximation and the robustness of the model. An ensemble of 16 simulations is also generated with multiple changes in the reference simulation in order to estimate the overall uncertainty. The case study is a four-month simulation of ozone concentrations over Europe in 2001 performed using the modeling system Polyphemus. It is shown that there is a high uncertainty due to the physical parameterizations (notably the turbulence closure and the chemical mechanism). The low robustness suggests that ensemble approaches are necessary in most applications.

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Uncertainty in a chemistry-transport model due to physical parameterizations and numerical approximations: An ensemble approach applied to ozone modeling

MICS-Asia II: The model intercomparison study for Asia Phase II methodology and overview of findings

This paper describes a three-dimensional chemistry transport model, POLAIR, with a special focus on numerical aspects. POLAIR is a fully modular eulerian model. Several different chemical mechanisms are available, which can deal with photochemistry (Racm, Radm, etc.), continental impact (e.g. passive transport), mercury, aerosols, etc. POLAIR is designed to enable simulations from regional scales to continental scales. A few simulations at those scales have been conducted to assess and improve the code. Beyond forward simulations, inverse modelling and data assimilation can be performed, thanks to the tangent linear and adjoint versions of POLAIR, which are available through automatic differentiation.

Stephanie Lacour

Papers

Development and validation of a fully modular platform for numerical modelling of air pollution: POLAIR