Polyphemus : une plate-forme multimodèles pour la pollution atmosphérique et l'évaluation des risques

National audienceCet article présente le système de modélisation de la qualité de l'air Polyphemus, ses principales fonctionnalités et quelques applications. Polyphemus est dédié à la modélisation de la dispersion atmosphérique de traceurs passifs ou d'espèces réactives aux échelles locale, régionale et continentale. Polyphemus est développé au CEREA, laboratoire commun entre EDF R&D et lʼÉcole des Ponts et au sein dʼun projet commun avec lʼInstitut national de recherche en informatique et automatique (INRIA), avec le soutien de lʼIRSN et de lʼINERIS. Polyphemus est un système dʼun type nouveau qui se distingue de lʼapproche classique du " modèle tout en un " par sa construction modulaire, notamment fondée sur des bibliothèques et des pilotes manipulant les modèles de dispersion. Accueillant plusieurs modèles, Polyphemus est une plate-forme et non un modèle. Une de ses fonctionnalités notables est sa capacité à effectuer des simulations multimodèles, ce qui permet d'évaluer des incertitudes. Plusieurs méthodes dʼassimilation de données font aussi partie du système afin de pouvoir intégrer des données fournies par des réseaux de mesure

Inverse modeling of NOx emissions at regional scale over northern France: Preliminary investigation of the second-order sensitivity

International audienceThe purpose of this article is to perform the inverse modeling of emissions at regional scale for photochemical applications. The case study is the region of Lille in northern France for simulations in May 1998. The chemistry-transport model, Polair3D, has been validated with 1 year of model-to-observation comparisons over Lille. Polair3D has an adjoint mode, which enables inverse modeling with a variational approach. A sensitivity analysis has been performed so as to select the emission parameters to be modified in order to improve ozone forecasts. It has been shown that inverse modeling of the time distribution of nitrogen oxide emissions leads to satisfactory improvements even after the learning period. A key issue is the robustness of the inverted emissions with respect to uncertain parameters. A brute force second-order sensitivity analysis of the optimized emissions has been performed with respect to other parameters and has proven that the optimized time distribution of NOx emissions is robust

Investigation of some numerical issues in a chemistry-transport model: Gas-phase simulations

International audienceMany numerical strategies have been specifically developed for chemistry-transport models. Since no exact solutions are available for 3-D real problems, there are only few insights to choose between alternative numerical schemes and approximations, or to estimate the performance discrepancy between two approaches. However it is possible to assess the importance of numerical approximations through the comparison of different strategies. We estimated the impact of several numerical schemes for advection, diffusion and stiff chemistry. We also addressed operator splitting with different methods and operator orders. The study is performed with a gas-phase Eulerian model from the modeling platform Polyphemus. It is applied to ozone forecasts mainly over Europe, with focus on a few key species: ozone, nitric oxide, nitrogen dioxide, sulfur dioxide and hydroxy radical. The outcome is a ranking of the most sensitive numerical choices. It stresses the prominent impact of the advection scheme and of the splitting time step

Simulation numérique et assimilation de données variationnelle pour la dispersion atmosphérique de polluants

This work has led to the development of a three-dimensional chemistry-transport model Polair3D which simulates photochemistry. Model-to-data comparison of ozone and nitrogen oxides measurements over Lille in 1998 has proven its reliability at regional scale. 4 D-var data assimilation has been implemented. It relies on the adjoint model of Polair3D obtained through automatic differentiation. An application of inverse modelling of emissions over Lille with real measurements has been performed. It has proven that the inversion of temporal parameters of nitrogen oxides emissions leads to a significant improvement of forecasts. The so-called second-order sensitivity allows to study the sensitivity of the inversion with respect to the data assimilation system itself by computing its conditioning. This is illustrated by two test cases: short-range dispersion of radionuclides and gas-phase atmospheric chemistry characterized by a wide range of timescales.Ce travail a permis de développer un modèle de chimie-transport tridimensionnel Polair3D pour simuler la pollution photochimique. Des comparaisons aux mesures d'ozone et d'oxydes d'azote sur la région de Lille pour l'année 1998 l'ont validé à l'échelle régionale. La méthode d'assimilation de données 4D-var a été implémentée. Elle est basée sur le modèle adjoint de Polair3D qui a été obtenu par différenciation automatique. Une application à la modélisation inverse des émissions sur Lille avec des observations réelles a montré que l'inversion de paramètres temporels d'émissions d'oxydes d'azote permet d'améliorer notablement les prévisions. La sensibilité de "second-ordre" permet d'étudier la sensibilité de l'inversion au système d'assimilation de données lui-même en calculant son conditionnement. Cette problématique est illustrée sur deux applications: la dispersion de radionucléides à petite échelle et la chimie atmosphérique, caractérisée par sa disparité d'échelles temporelles

Assimilation de données pour la qualification d'un rejet radioactif

Rapport de contrat IRSNNo abstrac

Impact of mass consistency errors for atmospheric dispersion

International audienceAtmospheric dispersion models are usually off-line coupled to mesoscale meteorological models. This may generate the loss of mass consistency, defined as the conservation of uniform mixing ratio. We investigate in this short paper the impact of the resulting mass consistency errors. Three methods based on the renormalization of density, on fluxes computed with mass mixing ratio and on the adjustment of the vertical velocity, respectively, are aimed at reducing the mass consistency errors. They are benchmarked and applied to two test cases: air quality modeling over Europe for summer 2001 (typical of reactive dispersion) and simulation of the Chernobyl accident (typical of passive dispersion). Our tests indicate the differences between the passive and the reactive cases. The investigation of the spatial patterns (especially of the vertical distribution) discriminates the method based on the adjustment of the vertical velocity. Indeed, this method suffers from the enhancement of the numerical diffusion (illustrated in the passive case) and from the modification of the escape flux (for ozone)

Data assimilation and inverse modeling of atmospheric chemistry

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Data assimilation for short range atmospheric dispersion of radionuclides : a case study of second-order sensitivity

International audienceThis article presents the application of variational data assimilation to a simple Gaussian plume model for radionuclides. Adjoint modeling is applied to the model in order to minimize discrepancies between contamination observations and model outputs. The interest of such an approach is to get a better estimation of some parameters such as emissions or dispersion parameters. A second-order analysis is also performed to assess the sensitivity of the optimized parameters to some poorly known parameters. Sensitivity with respect to network design is also done

Source Reconstruction for Accidental Releases of Radio-elements

International audienceNo abstrac

Cloud diagnosis impact on deposition modelling applied to the Fukushima accident

International audienceIn case of a nuclear accident, they are two phases concerning the dispersion of radioactive materials: 1. Forecast: Anticipating the consequences of an atmospheric release of radioactive material. 2. Aftermath: Understand the soil contamination and the possible harm suffered by the populations during the event. Wet deposition modeling is important to achieve these goals. The cloud diagnosis is a key issue for wet deposition modelling since it allows distinguishing between two processes: in-cloud scavenging: the collection of radioactive particles into the cloud below-cloud scavenging: the removal of radioactive material due to the falling drops. Which cloud diagnosis to use for the atmospheric transport models ? Cloud diagnosis choice have a major impact to the volume of the atmosphere considered as-. Then, the repartition between in-cloud and below-cloud may be strongly impacted by the cloud diagnosis. Cloud water mixing ratio (Q C) is the most interesting variable, which describes only the cloud water. Q c provides satisfactory results and is not sensitive to the threshold. We therefore recommend to use Q c to distinguish in-cloud and below-cloud scavenging in the atmospheric transport modelling. Comparison of observed and diagnosed cloud maps, the 16 th March 00:00 EGU 2017 8845 At the Fukushima airport, a deposit as large as 36 kBq.m-2 of Cs-137 was measured. Both dry and wet deposition were probably involved since a raining event occurred on the 15th of March when the plume was passing nearby