Yelva Roustan

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

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.

Hints to discriminate the choice of wet deposition models applied to an accidental radioactive release

In nuclear emergency management, wet deposition modelling is of crucial importance for correctly evaluating soil contamination after an atmospheric release. Wet deposition is generally divided into two main processes: in-cloud scavenging (rainout) and below-cloud scavenging (washout). The large number of schemes proposed in the literature for both processes reflects the uncertainties in our current understanding of these phenomena. There is presently no scientific consensus to discriminate between the two processes. In order to improve our understanding of the magnitude of modelling uncertainties, a comprehensive sensitivity analysis was performed by focusing on representation of wet deposition fluxes. A large number of model configurations involving different deposition schemes and modelling options were evaluated by comparison with available observations of soil contamination. The objective is to establish a priority rank order of wet deposition schemes for soil contamination modelling.

Using the Wasserstein distance to compare fields of pollutants: application to the radionuclide atmospheric dispersion of the Fukushima-Daiichi accident

The verification of simulations against data and the comparison of model simulation of pollutant fields rely on the critical choice of statistical indicators. Most of the scores are based on point-wise, that is, local, value comparison. Such indicators are impacted by the so-called double penalty effect. Typically, a misplaced blob of pollutants will doubly penalise such a score because it is predicted where it should not be and is not predicted where it should be. The effect is acute in plume simulations where the concentrations gradient can be sharp. A non-local metric that would match concentration fields by displacement would avoid such double penalty. Here, we experiment on such a metric known as the Wasserstein distance, which tells how penalising moving the pollutants is. We give a mathematical introduction to this distance and discuss how it should be adapted to handle fields of pollutants. We develop and optimise an open Python code to compute this distance. The metric is applied to the dispersion of cesium-137 of the Fukushima-Daiichi nuclear power plant accident. We discuss of its application in model-to-model comparison but also in the verification of model simulation against a map of observed deposited cesium-137 over Japan. As hoped for, the Wasserstein distance is less penalising, and yet retains some of the key discriminating properties of the root mean square error indicator.

Modelling the Fate of Chemicals in the Atmosphere

Atmosphere is an important component of the whole ecosystem because it directly interacts with all the other media, i.e. soil, surface waters, vegetation and biota. This chapter describes the processes that should be considered in models simulating the fate of chemicals in the atmosphere. The first section describes model approaches able to simulate the long-range transport of chemicals in the atmosphere. The second section describes the partition of chemicals between gaseous and particulate phases in the atmosphere. Two approaches, respectively, based on liquid vapour pressure and octanol-air partition coefficient are presented. The third section describes chemical reactions occurring in the atmosphere, driven by photolysis and reactions with photooxidants like the hydroxyl radical OH. The forth section describes dry deposition of both gaseous and particulate chemicals on the earth surface. Dry deposition is driven by aerodynamic, quasi-laminar sublayer and canopy resistances. The calculation of these latter is presented here in detail. The fifth section describes wet deposition of both gaseous and particulate chemicals on the earth surface, driven by rainout (in-cloud) and washout (below-cloud) scavenging.

Sensitivity Analysis of Ambient Particulate Matter to Industrial Emissions Using a Plume-in-Grid Approach: Application in the Greater Paris Region

The Polyphemus Plume-in-Grid (PinG) model, which is based on a 3D Eulerian model and an imbedded puff model, was developed to represent the dispersion and transformation of air pollutants in industrial plumes. It was later improved to take into account particulate matter (PM) formation and transport in order to evaluate secondary PM formation in refinery plumes. The performance of the PinG model, applied to a refinery in the Greater Paris region, was previously evaluated at the regional scale for July 2009, showing satisfactory results for O3 and PM. The PinG model is applied here to the same refinery for a different period, April 2013, when local measurements were available. The refinery is located close to a large NH3 source, which is also treated here using the puff model in order to evaluate the interactions of the plumes of these two industrial sites. Modeled PM is compared here to local measurements in terms of mass concentrations and chemical composition. The measurement sites are located around the refinery and are impacted by the plumes of the two industrial sites. The results show good agreement between measured and modeled PM chemical composition. The sensitivity of the local concentrations to the refinery emissions is evaluated. It is mostly due to primary and secondary inorganic aerosols, emitted and formed in the plumes, and to secondary organic aerosols (SOA) formed from the refinery VOC fugitive emissions.