Publications

2014

• Prise en compte d'un modèle de sol multi-couches pour la simulation multi-milieux à l'échelle européenne des polluants organiques persistants
  
  • Loizeau Vincent
  , 2014. Les polluants organiques persistants (POPs) sont des substances toxiques ayant la capacité de se bioaccumuler le long de la chaîne alimentaire. Une fois émis dans l'atmosphère, ils sont dispersés par le vent puis se déposent au sol. Du fait de leur persistance, ils peuvent être réémis depuis le sol vers l'atmosphère et parcourir ainsi de longues distances. Ce processus est couramment appelé « effet saut de sauterelle ». On peut donc retrouver les POPs très loin de leurs sources d'émissions. Pour pouvoir prendre des décisions visant à réduire leur impact environnemental, il est nécessaire de comprendre leur comportement dans l'atmosphère mais également dans les autres milieux, tels que le sol, la végétation ou l'eau. De nombreux modèles numériques de complexité variable ont été développés dans le but de prédire le devenir des POPs dans l'environnement. La plupart d'entre eux considèrent le sol comme un compartiment homogène, pouvant ainsi mener à une sous-estimation des réémissions du sol vers l'atmosphère. Or, du fait de la mise en place de réglementations visant à réduire les émissions anthropiques des POPs, la concentration dans l'atmosphère tend à diminuer et le sol, qui semblait jusqu'alors être seulement un réservoir, devient une source potentielle de POPs pour l'atmosphère. Il apparaît donc nécessaire de coupler les modèles de dispersion atmosphérique à un modèle de sol réaliste. Mes recherches ont permis d'étudier l'impact des interactions entre le sol et l'atmosphère sur la concentration dans les différents milieux. Pour cela, nous avons développé un modèle de sol multi-couches permettant de mieux estimer le profil de concentration dans le sol et les échanges entre ces deux milieux. Une analyse de sensibilité a été effectuée afin d'identifier les paramètres clés dans la détermination des réémissions. Puis ce modèle a été couplé à un modèle 3D de chimie-transport atmosphérique. Une étude de cas à l'échelle européenne a alors été réalisée afin d'évaluer ce modèle et d'estimer l'impact des réémissions sur les concentrations de POPs dans l'environnement (10.70675/2b349e6fz4fcaz4f4ez8f97zca3173141374)
  DOI : 10.70675/2b349e6fz4fcaz4f4ez8f97zca3173141374
• Assimilation of lidar signals: application to aerosol forecasting in the western Mediterranean basin
  
  • Wang Yiguo
  • Sartelet Karine
  • Bocquet Marc
  • Chazette Patrick
  • Sicard Michaël
  • d'Amico Giuseppe
  • Léon Jean-François
  • Alados Arboledas Lucas
  • Amodeo Aldo
  • Augustin Patrick
  • Bach J.
  • Belegante Livio
  • Binietoglou Ioannis
  • Bush Xavier
  • Comerón Adolfo
  • Delbarre Hervé
  • García-Vizcaino David
  • Guerrero Rascado Juan Luis
  • Hervo Maxime
  • Iarlori Marco
  • Kokkalis Panos
  • Lange Diego
  • Molero Fransisco
  • Montoux Nadège
  • Muñoz A.
  • Muñoz Constantino
  • Nicolae Doina
  • Papayannis Alexandros
  • Pappalardo Gelsomina
  • Preissler Jana
  • Rizi Vincenzo
  • Rocadenbosch Francesc
  • Sellegri Karine
  • Wagner Frank
  • Dulac François
  Atmospheric Chemistry and Physics, European Geosciences Union, 2014, 14 (22), pp.12031 - 12053. This paper presents a new application of assim-ilating lidar signals to aerosol forecasting. It aims at in-vestigating the impact of a ground-based lidar network on the analysis and short-term forecasts of aerosols through a case study in the Mediterranean basin. To do so, we em-ploy a data assimilation (DA) algorithm based on the opti-mal interpolation method developed in the POLAIR3D chem-istry transport model (CTM) of the POLYPHEMUS air qual-ity modelling platform. We assimilate hourly averaged nor-malised range-corrected lidar signals (PR 2) retrieved from a 72 h period of intensive and continuous measurements performed in July 2012 by ground-based lidar systems of the European Aerosol Research Lidar Network (EAR-LINET) integrated into the Aerosols, Clouds, and Trace Published by Copernicus Publications on behalf of the European Geosciences Union. 12032 Y. Wang et al.: Assimilation of lidar signals gases Research InfraStructure (ACTRIS) network and an ad-ditional system in Corsica deployed in the framework of the pre-ChArMEx (Chemistry-Aerosol Mediterranean Ex-periment)/TRAQA (TRAnsport à longue distance et Qualité de l'Air) campaign. This lidar campaign was dedicated to demonstrating the potential operationality of a research net-work like EARLINET and the potential usefulness of assim-ilation of lidar signals to aerosol forecasts. Particles with an aerodynamic diameter lower than 2.5 µm (PM 2.5) and those with an aerodynamic diameter higher than 2.5 µm but lower than 10 µm (PM 10−2.5) are analysed separately using the li-dar observations at each DA step. First, we study the spatial and temporal influences of the assimilation of lidar signals on aerosol forecasting. We conduct sensitivity studies on al-gorithmic parameters, e.g. the horizontal correlation length (L h) used in the background error covariance matrix (50 km, 100 km or 200 km), the altitudes at which DA is performed (0.75–3.5 km, 1.0–3.5 km or 1.5–3.5 km a.g.l.) and the assim-ilation period length (12 h or 24 h). We find that DA with L h = 100 km and assimilation from 1.0 to 3.5 km a.g.l. dur-ing a 12 h assimilation period length leads to the best scores for PM 10 and PM 2.5 during the forecast period with refer-ence to available measurements from surface networks. Sec-ondly, the aerosol simulation results without and with lidar DA using the optimal parameters (L h = 100 km, an assim-ilation altitude range from 1.0 to 3.5 km a.g.l. and a 12 h DA period) are evaluated using the level 2.0 (cloud-screened and quality-assured) aerosol optical depth (AOD) data from AERONET, and mass concentration measurements (PM 10 or PM 2.5) from the French air quality (BDQA) network and the EMEP-Spain/Portugal network. The results show that the simulation with DA leads to better scores than the one with-out DA for PM 2.5 , PM 10 and AOD. Additionally, the com-parison of model results to evaluation data indicates that the temporal impact of assimilating lidar signals is longer than 36 h after the assimilation period. (10.5194/acp-14-12031-2014)
  DOI : 10.5194/acp-14-12031-2014
• Campagne TEMERAIRE (Test de la Mesure de la Réfractivité Atmosphèrique par Radar à l'Echelle hectométrique) - été 2014
  
  • Hallali Ruben
  • Dalaudier Francis
  • Parent Du Châtelet Jacques
  • Wilson Richard
  • Delanoë Julien
  • Dupont E.
  • Musson-Genon L.
  • Legain Dominique
  • Le Gac Christophe
  • Pauwels Nicolas
  • Vinson Jean-Paul
  • Brett Williams
  • Bertrand Fabrice
  • Caudoux Christophe
  • Coulomb Romain
  • Tzanos Diane
  • Suquia David
  • Moulin Emmanuel
  • Faucheux A.
  • Lefranc Y.
  • Zhangi F.
  • Thibord T.
  , 2014.
• Screening sensitivity analysis of a radionuclides atmospheric dispersion model applied to the Fukushima disaster
  
  • Girard Sylvain
  • Korsakissok Irène
  • Mallet Vivien
  Atmospheric Environment, Elsevier, 2014, 95, pp.490-500. Numerical models used to forecast the atmospheric dispersion of radionuclides following nuclear accidents are subject to substantial uncertainties. Input data, such as meteorological forecasts or source term estimations, as well as poorly known model parameters contribute for a large part to this uncertainty. A sensitivity analysis with the method of Morris was carried out in the case of the Fukushima disaster as a first step towards the uncertainty analysis of the Polyphemus/Polair3D model. The main difficulties stemmed from the high dimension of the model's input and output. Simple perturbations whose magnitudes were devised from a thorough literature review were applied to 19 uncertain inputs. Several outputs related to atmospheric activity and ground deposition were aggregated, revealing different inputs rankings. Other inputs based on gamma dose rates measurements were used to question the possibility of calibrating the inputs uncertainties. Some inputs, such as the cloud layer thickness, were found to have little influence on most considered outputs and could therefore be safely discarded from further studies. On the contrary, wind perturbations and emission factors for iodine and caesium are predominant. The performance indicators derived from dose rates observations displayed strong sensitivities. This emphasises the share of the overall uncertainty due to input uncertainties and asserts the relevance of the simple perturbation scheme that was employed in this work. (10.1016/j.atmosenv.2014.07.010)
  DOI : 10.1016/j.atmosenv.2014.07.010
• Advanced Data Assimilation for Geosciences
  
  • Blayo Eric
  • Bocquet Marc
  • Cosme Emmanuel
  • Cugliandolo Leticia F
  , 2014, pp.608. Data assimilation aims at determining as accurately as possible the state of a dynamical system by combining heterogeneous sources of information in an optimal way. Generally speaking, the mathematical methods of data assimilation describe algorithms for forming optimal combinations of observations of a system, a numerical model that describes its evolution, and appropriate prior information. Data assimilation has a long history of application to high-dimensional geophysical systems dating back to the 1960s, with application to the estimation of initial conditions for weather forecasts. It has become a major component of numerical forecasting systems in geophysics, and an intensive field of research, with numerous additional applications in oceanography, atmospheric chemistry, and extensions to other geophysical sciences. The physical complexity and the high dimensionality of geophysical systems have led the community of geophysics to make significant contributions to the fundamental theory of data assimilation.This book gathers notes from lectures and seminars given by internationally recognized scientists during a three-week school held in the Les Houches School of physics in 2012, on theoretical and applied data assimilation. It is composed of (i) a series of main lectures, presenting the fundamentals of the most commonly used methods, and the information theory background required to understand and evaluate the role of observations; (ii) a series of specialized lectures, addressing various aspects of data assimilation in detail, from the most recent developments of the theory to the specificities of various thematic applications.
• Modeling SOA formation from the oxidation anthropogenic precursors in an outdoor chamber
  
  • Couvidat Florian
  • Vivanco Marta G.
  • Seigneur Christian
  • Bessagnet Bertrand
  , 2014, pp.164. Secondary organic aerosols (SOA) constitute a significant fraction of the atmospheric particulate matter. These particles are formed as a consequence of the oxidation reaction of certain organic gases that leads to the formation of low-volatility compounds. Much research has been done during the last years to take into account the influence of conditions (like low-NOx or high NOx conditions, dry or humid conditions) in SOA mechanisms. In this study we present a comparison between box model results of a SOA model to measurements done in the outdoor chambers EUPHORE (Ceam, Valencia, Spain; Vivanco et al., 2013). The experiments were focused on a mixture of four anthropogenic VOCs (toluene, 1,3,5 trimethylbenzene, o-xylene and octane) over different sets of conditions (dry or humid conditions, different NOx concentrations and with or without SO2). Some measurements (like measured concentrations of some compounds, SMPS data) were used to constrain the box model and represent properly the gas-phase chemistry, which can impact strongly SOA formation.
• Large-eddy simulation of wind flows and comparisons with very-near field campaign data
  
  • Lacome Jean-Marc
  • Leroy Guillaume
  • Truchot Benjamin
  • Joubert A.
  • Wei Xiao
  • Dupont Eric
  • Gilbert Eric
  • Carissimo Bertrand
  , 2014, pp.615-620. Pollutant dispersion in stable atmospheric conditions is still a phenomenon that is highly difficult to model or to reproduce in an experimental wind tunnel. However, such conditions are of major interest in the field of risk assessment because they are generally conservative and the low level of turbulence induces the most important distance for toxic impact. Using LES approach appears relevant and promising to overcome difficulties related to stable conditions modelling. The objective of this paper is to present the preliminary results obtained in terms of wind flow modelling with the open source CFD code FDS, from NIST, which is based on Large Eddy Simulation approach. It is essential to determine the best parameterization of this type of code for atmospheric gas dispersion modelling. Starting from atmospheric flow conditions that were observed during INERIS experimental campaign of ammonia release, the process related to satisfy this requirement will be presented.
• Analysis and comparison of two models response to an emissions abatement scenario
  
  • Roustan Yelva
  • Coll Isabelle
  • Yan Nicolas
  • Elessa Etuman Arthur
  , 2014.
• Identification of sensitive parameters in the modeling of SVOC reemission processes from soil to atmosphere
  
  • Loizeau Vincent
  • Ciffroy Philippe
  • Roustan Yelva
  • Musson-Genon Luc
  Science of the Total Environment, Elsevier, 2014, 493 (1), pp.419-431. Semi-volatile organic compounds (SVOCs) are subject to Long-Range Atmospheric Transport because of transport–deposition–reemission successive processes. Several experimental data available in the literature suggest that soil is a non-negligible contributor of SVOCs to atmosphere. Then coupling soil and atmosphere in integrated coupled models and simulating reemission processes can be essential for estimating atmospheric concentration of several pollutants. However, the sources of uncertainty and variability are multiple (soil properties, meteorological conditions, chemical-specific parameters) and can significantly influence the determination of reemissions. In order to identify the key parameters in reemission modeling and their effect on global modeling uncertainty, we conducted a sensitivity analysis targeted on the ‘reemission’ output variable. Different parameters were tested, including soil properties, partition coefficients and meteorological conditions. We performed EFAST sensitivity analysis for four chemicals (benzo-a-pyrene, hexachlorobenzene, PCB-28 and lindane) and different spatial scenari (regional and continental scales). Partition coefficients between air, solid and water phases are influent, depending on the precision of data and global behavior of the chemical. Reemissions showed a lower variability to soil parameters (soil organic matter and water contents at field capacity and wilting point). A mapping of these parameters at a regional scale is sufficient to correctly estimate reemissions when compared to other sources of uncertainty. (10.1016/j.scitotenv.2014.05.136)
  DOI : 10.1016/j.scitotenv.2014.05.136
• The Secondary Organic Aerosol Processor (SOAP) model : Model development and applications
  
  • Couvidat Florian
  • Kim Y.
  • Sartelet Karine
  • Vivanco Marta G.
  • Bessagnet Bertrand
  , 2014. The Secondary Organic Aerosol Processor (SOAP) model and several applications of the model are presented. This model is designed to be modular with different user options depending on the computing time and the complexity required by the user. This model is based on the molecular surrogate approach, in which each surrogate compound is associated with a molecular structure to estimate some properties and parameters (hygroscopicity, absorption on the aqueous phase of particles, activity coefficients, phase separation). The user can choose between an equilibrium and a dynamic representation of the organic aerosol.
• Local ensemble transform Kalman filter, a fast non-stationary control law for adaptive optics on ELTs: theoretical aspects and first simulation results
  
  • Gray Morgan
  • Petit Cyril
  • Rodionov Sergey
  • Bocquet Marc
  • Bertino Laurent
  • Ferrari Marc
  • Fusco Thierry
  Optics Express, Optical Society of America - OSA Publishing, 2014, 22 (17), pp.20894-20913. We propose a new algorithm for an adaptive optics system control law, based on the Linear Quadratic Gaussian approach and a Kalman Filter adaptation with localizations. It allows to handle non-stationary behaviors, to obtain performance close to the optimality defined with the residual phase variance minimization criterion, and to reduce the computational burden with an intrinsically parallel implementation on the Extremely Large Telescopes (ELTs). (10.1364/OE.22.020894)
  DOI : 10.1364/OE.22.020894
• La prévision numérique du temps
  
  • Bocquet Marc
  , 2014, pp.48-51. De tout temps au cœur des préoccupations des hommes, la prévision météorologique est depuis 150 ans un défi scientifique majeur à l’impact économique et social considérable. Avec le développement des capacités de calcul ces cinquante dernières années, la prévision est également devenue un défi numérique majeur.
• Modélisation de l’impact du trafic routier sur la pollution de l’air et des eaux de ruissellement
  
  • Fallah Shorshani Masoud
  , 2014. Les émissions du trafic routier sont une des sources majeures de pollution dans les villes. La modélisation de la pollution de l'air et des eaux de ruissellement due aux émissions du trafic routier est essentielle pour comprendre les processus qui mènent à cette pollution et fournir les éléments d'information nécessaires au développement de politiques publiques efficaces pour la réduction des niveaux de pollution. L'objectif de cette thèse est d'évaluer la faisabilité et la pertinence de chaînes de modèles pour simuler l'impact du trafic routier sur la pollution de l'air et des eaux de ruissellement. La première partie a consisté à réaliser un état de l'art des outils de modélisation des différents phénomènes (trafic, émissions, pollution atmosphérique, qualité des eaux de ruissellement), mettant en exergue les enjeux liés à l'intégration des différents modèles pour constituer une chaîne cohérente en termes de polluants et d'échelles spatio-temporelles. Deux exemples de chaînes de modélisation ont été proposés, l'une statique avec des pas de temps horaires, la seconde envisageant une approche dynamique du trafic et des pollutions associées. Dans la deuxième partie de la thèse, des outils automatisés d'interfaçage ont été développés pour construire des chaînes de modèles. Ces chaînes de modèles ont ensuite été testées avec différents cas d'étude : (1) Couplage trafic / émissions avec une simulation d'une voie urbaine utilisant un modèle dynamique de trafic en lien avec des modèles d'émissions instantané et moyenné, (2) couplage émissions / pollution atmosphérique en bordure d'une autoroute, (3) couplages trafic / émissions / pollution atmosphérique en bordure d'une autoroute urbaine, (4) couplage émissions / pollution atmosphérique pour un quartier suburbain, (5) couplage dépôts atmosphériques / qualité des eaux de ruissellement pour un bassin versant suburbain, et finalement (6) une chaîne de modélisation complète avec couplages trafic / émissions /qualité de l'air et des eaux de ruissellement pour un bassin versant suburbain. Ces travaux ont permis à travers ces différents cas d'étude d'identifier les enjeux associés à l'intégration de modèles pour le calcul de la pollution de l'air et des eaux de ruissellement due au trafic routier en zone urbaine. Par ailleurs, ils fournissent une base solide pour le développement futur de modèles numériques intégrés de la pollution urbaine (10.70675/702d72c2zfcc2z422dzbba6zd4abd53feec5)
  DOI : 10.70675/702d72c2zfcc2z422dzbba6zd4abd53feec5
• Ensemble forecasting with machine learning algorithms for ozone, nitrogen dioxide and PM10 on the Prev'Air platform
  
  • Debry Edouard
  • Mallet Vivien
  Atmospheric Environment, Elsevier, 2014, 91, pp.71-84. This paper presents the application of an ensemble forecasting approach to the Prev'Air operational platform. This platform aims at forecasting maps, on a daily basis, for ozone, nitrogen dioxide and particulate matter. It relies on several air quality models which differ by their physical parameterizations, their input data and numerical strategies, so that one model may perform better with respect to observations for a given pollutant, at a given time and location. We apply sequential aggregation methods to this ensemble of models, which has already proved good potential in previous research papers. Compared to these studies, the novelties of this paper are the variety of models, the real operational context, which requires robustness assessment, and the application to several pollutants. In this paper, we first introduce the ensemble forecasting methods and the operational platform Prev'Air along with its models. Then, the sequential aggregation performance and robustness are assessed using two different data sets. The results with the discounted ridge regression method show that the errors of the forecasts are respectively reduced by at least 29%, 35% and 19% for hourly, daily and peak O3 concentrations, by 19%, 26% and 20% for hourly, daily and peak NO2 concentrations, and finally by 17%, 19% and 11% for hourly, daily and peak PM10 concentrations. At last, we give a first insight of the ensemble ability to forecast threshold exceedances. (10.1016/j.atmosenv.2014.03.049)
  DOI : 10.1016/j.atmosenv.2014.03.049
• An iterative ensemble Kalman smoother
  
  • Bocquet Marc
  • Sakov Pavel
  Quarterly Journal of the Royal Meteorological Society, Wiley, 2014, 140 (682), pp.1521-1535. The iterative ensemble Kalman filter (IEnKF) was recently proposed in order to improve the performance of ensemble Kalman filtering with strongly nonlinear geophysical models. The IEnKF can be used as a lag-one smoother and extended to a fixed-lag smoother: the iterative ensemble Kalman smoother (IEnKS). The IEnKS is an ensemble variational method. It does not require the use of the tangent linear of the evolution and observation models, nor the adjoint of these models: the required sensitivities (gradient and Hessian) are obtained from the ensemble. Looking for optimal performance, out of the many possible extensions we consider a quasi-static algorithm. The IEnKS is explored for the Lorenz '95 model and for a two-dimensional turbulence model. As the logical extension of the IEnKF, the IEnKS significantly outperforms standard Kalman filters and smoothers in strongly nonlinear regimes. In mildly nonlinear regimes (typically synoptic-scale meteorology), its filtering performance is marginally but clearly better than the standard ensemble Kalman filter and it keeps improving as the length of the temporal data assimilation window is increased. For long windows, its smoothing performance outranks the standard smoothers very significantly, a result that is believed to stem from the variational but flow-dependent nature of the algorithm. For very long windows, the use of a multiple data assimilation variant of the scheme, where observations are assimilated several times, is advocated. This paves the way for finer reanalysis, freed from the static prior assumption of 4D-Var but also partially freed from the Gaussian assumptions that usually impede standard ensemble Kalman filtering and smoothing. (10.1002/qj.2236)
  DOI : 10.1002/qj.2236
• An Overview of Non-Volatile Flip-Flops Based on Emerging Memory Technologies
  
  • Portal Jean-Michel
  • Bocquet Marc
  • Moreau Mathieu
  • Aziza Hassen
  • Deleruyelle Damien
  • Zhang Yue
  • Kang Wang
  • Klein Jacques-Olivier
  • Zhang Youguang
  • Chappert Claude
  • Zhao Weisheng
  Journal of Electronic Science and Technology, 2014, 12 (2), pp.173 - 181. (10.3969/j.issn.1674-862X.2014.02.007)
  DOI : 10.3969/j.issn.1674-862X.2014.02.007
• Characterization of organic tracer compounds in PM2.5 at a semi-urban site in Beirut, Lebanon
  
  • Waked Antoine
  • Afif Charbel
  • Formenti Paola
  • Chevaillier Servanne
  • El-Haddad Imad
  • Doussin Jean-François
  • Borbon Agnès
  • Seigneur Christian
  Atmospheric Research, Elsevier, 2014, 143, pp.85-94. A measurement campaign was conducted at a semi-urban site located in the suburbs of the city of Beirut (Lebanon) during summertime (2–18 July 2011). The molecular composition of organic PM2.5 was investigated following a chemical derivatization gas chromatography/mass spectrometry technique. Accordingly, several classes of compounds represented by 18 individual organic tracers were determined. These tracers include levoglucosan, a tracer for biomass combustion, dicarboxylic acids, and several tracers for the photo-oxidation of isoprene, α-pinene and β-caryophyllene. The sum of the mean concentrations of the isoprene oxidation products was 4 ng/m3, that of α-pinene was 124 ng/m3 and that of β-caryophyllene was 11 ng/m3. For other tracers of organic aerosols, the highest concentrations were obtained for carboxylic acids with an average value of 939 ng/m3. An average value of 49 ng/m3 was obtained for levoglucosan. Organic and elemental carbon concentrations were measured by a thermo-optical analyzer. Average values were 5.6 and 1.8 μg/m3, respectively. A reconstruction of organic PM2.5 composition suggests that cooking, fossil-fuel combustion, biomass burning, sesquiterpenes, monoterpenes, and isoprene contribute on average about 27 ± 13, 16 ± 7, 5 ± 3, 26 ± 5, 26 ± 13 and < 1 ± 0.3% of PM2.5 organic carbon, respectively. (10.1016/j.atmosres.2014.02.006)
  DOI : 10.1016/j.atmosres.2014.02.006
• Descente en échelle de la ressource en énergie éolienne de la mésoéchelle à l'échelle locale par imbrication et assimilation de données à l'aide d'un modèle de CFD
  
  • Duraisamy Jothiprakasam Venkatesh
  , 2014. Le développement de la production d'énergie éolienne nécessite des méthodes précises et bien établies pour l'évaluation de la ressource éolienne, étape essentielle dans la phase avant-projet d'une future ferme. Au cours de ces deux dernières décennies, les modèles d'écoulements linéaires ont été largement utilisés dans l'industrie éolienne pour l'évaluation de la ressource et pour la définition de la disposition des turbines. Cependant, les incertitudes des modèles linéaires dans la prévision de la vitesse du vent sur terrain complexe sont bien connues. Elles conduisent à l'utilisation de modèles CFD, capables de modéliser les écoulements complexes de manière précise autour de caractéristiques géographiques spécifiques. Les modèles méso-échelle peuvent prédire le régime de vent à des résolutions de plusieurs kilomètres mais ne sont pas bien adaptés pour résoudre les échelles spatiales inférieures à quelques centaines de mètres. Les modèles de CFD peuvent capter les détails des écoulements atmosphériques à plus petite échelle, mais nécessitent de documenter précisément les conditions aux limites. Ainsi, le couplage entre un modèle méso-échelle et un modèle CFD doit permettre d'améliorer la modélisation fine de l'écoulement pour les applications dans le domaine de l'énergie éolienne en comparaison avec les approches opérationnelles actuelles. Une campagne de mesure d'un an a été réalisée sur un terrain complexe dans le sud de la France durant la période 2007-2008. Elle a permis de fournir une base de données bien documentée à la fois pour les paramètres d'entrée et les données de validation. La nouvelle méthodologie proposée vise notamment à répondre à deux problématiques: le couplage entre le modèle méso-échelle et le modèle CFD en prenant en compte une forte variation spatiale de la topographie sur les bords du domaine de simulation, et les erreurs de prédiction du modèle méso-échelle. Le travail réalisé ici a consisté à optimiser le calcul du vent sur chaque face d'entrée du modèle CFD à partir des valeurs issues des verticales du modèle de méso-échelle, puis à mettre en œuvre une assimilation de données basée sur la relaxation newtonienne (nudging). La chaîne de modèles considérée ici est composée du modèle de prévision de Météo-France ALADIN et du code de CFD open-source Code_Saturne. Le potentiel éolien est ensuite calculé en utilisant une méthode de clustering, permettant de regrouper les conditions météorologiques similaires et ainsi réduire le nombre de simulations CFD nécessaires pour reproduire un an (ou plus) d'écoulement atmosphérique sur le site considéré. La procédure d'assimilation est réalisée avec des mesures issues d'anémomètre à coupelles ou soniques. Une analyse détaillée des simulations avec imbrication et avec ou sans assimilation de données est d'abord présentée pour les deux directions de vent dominantes, avec en particulier une étude de sensibilité aux paramètres intervenant dans l'imbrication et dans l'assimilation. La dernière partie du travail est consacrée au calcul du potentiel éolien en utilisant une méthode de clustering. La vitesse annuelle moyenne du vent est calculée avec et sans assimilation, puis est comparée avec les mesures non assimilées et les résultats du modèle WAsP. L'amélioration apportée par l'assimilation de données sur la distribution des écarts avec les mesures est ainsi quantifiée pour différentes configurations (10.70675/ea5718e8zdf6dz401aza65ez854007bf50a4)
  DOI : 10.70675/ea5718e8zdf6dz401aza65ez854007bf50a4
• Evaluation of forest fire models on a large observation database
  
  • Filippi Jean-Baptiste
  • Mallet Vivien
  • Nader Bahaa
  Natural Hazards and Earth System Sciences, Copernicus Publ. / European Geosciences Union, 2014, 14, pp.3077 - 3091. This paper presents the evaluation of several fire propagation models using a large set of observed fires. The observation base is composed of 80 Mediterranean fire cases of different sizes, which come with the limited information available in an operational context (burned surface and ap-proximative ignition point). Simulations for all cases are car-ried out with four different front velocity models. The results are compared with several error scoring methods applied to each of the 320 simulations. All tasks are performed in a fully automated manner, with simulations run as first guesses with no tuning for any of the models or cases. This approach leads to a wide range of simulation performance, including some of the bad simulation results to be expected in an operational context. Disregarding the quality of the input data, it is found that the models can be ranked based on their performance and that the most complex models outperform the more em-pirical ones. Data and source codes used for this paper are freely available to the community. (10.5194/nhess-14-3077-2014)
  DOI : 10.5194/nhess-14-3077-2014
• On the Influence of a Simple Microphysics Parametrization on Radiation Fog Modelling: A Case Study During ParisFog
  
  • Zhang Xiaojing
  • Musson-Genon Luc
  • Dupont Eric
  • Milliez Maya
  • Carissimo Bertrand
  Boundary-Layer Meteorology, Springer Verlag, 2014, 151 (2), pp.293-315. A detailed numerical simulation of a radiation fog event with a single column model is presented, which takes into account recent developments in microphysical parametrizations. One-dimensional simulations are performed using the computational fluid dynamics model Code_Saturne and the results are compared to a very detailed in situ dataset collected during the ParisFog campaign, which took place near Paris, France, during the winter 2006–2007. Special attention is given to the detailed and complete diurnal simulations and to the role of microphysics in the fog life cycle. The comparison between the simulated and the observed visibility, in the single-column model case study, shows that the evolution of radiation fog is correctly simulated. Sensitivity simulations show that fog development and dissipation are sensitive to the droplet-size distribution through sedimentation/deposition processes but the aerosol number concentration in the coarse mode has a low impact on the time of fog formation. (10.1007/s10546-013-9894-y)
  DOI : 10.1007/s10546-013-9894-y
• Evaluation of different SOA schemes using experiments in two outdoor chambers
  
  • Vivanco Marta G.
  • Couvidat Florian
  • Santiago Manuel
  • Seigneur Christian
  • Jang Myoseon
  • Barron Henderson
  • Bessagnet Bertrand
  , 2014, 16, pp.EGU2014-13215. Secondary organic aerosols (SOA) constitute a significant fraction of the atmospheric particulate matter. These particles are formed as a consequence of the oxidation reaction of certain organic gases that leads to the formation of low-volatility compounds. Much research has been done during the last years regarding SOA modelling. Since the initial one-step oxidation reaction included in most regional models more complex schemes taking into account the NOx regime have been proposed. In these schemes the intermediate specie formed from the oxidation of SOA precursors can continue reacting through different pathways depending on the atmospheric chemical conditions. Basically based on chamber experiments, the second-step reaction pathways involve radicals such as HO2, CH3COO or CH3O2 in low NOx conditions. In this study we present an intercomparison of different SOA mechanism (Couvidat et al. 2012, Kim et al. 2011, 1-step scheme currently included in the CHIMERE model) for anthropogenic SOA precursors, and their sensibility to different chemical mechanisms. A comparison of model results against two sets of experiments, performed in two outdoor chambers, EUPHORE (Ceam, Valencia, Spain; Vivanco et al., 2013), and UF (University of Florida, USA) is also included. Experiments in UF were performed for individual VOCs (toluene and 1,3,5 trimethylbenzene), whereas experiments in EUPHORE were focused on a mixture of four anthropogenic VOCs (toluene, 1,3,5 trimethylbenzene, o-xylene and octane). Regarding the gas phase, a comparison of radical concentration for different chemical mechanisms has been done. Modeled radical concentration was evaluated for one experiment measuring OH and HO2 concentration.
• A modelling perspective of the summer 2013 CHARMEX chemistry intensive campaign : origin of photo-oxidant and aerosol formation
  
  • Beekmann Matthias
  • Cholakian Arineh
  • Siour Guillaume
  • Laurent Benoît
  • Borbon Agnès
  • Colette Augustin
  • Durand Pierre
  • Formetti Paula
  • Freney Evelyn
  • Gros Valérie
  • Jambert Corinne
  • Marchand Nicolas
  • Sartelet Karine
  • Sauvage Stéphane
  • Sciare Jean
  • Sellegri Karine
  • Armengaud Alexandre
  • Kermen Pierre
  • Hamonou Eric
  • Dulac François
  , 2014, 16, pp.EGU2014-10753. During summer 2013, a three week intensive campaign took place over the western Mediterranean basin in order to investigate photo-oxidant and aerosol sources over the region. Within the frame of the MISTRAL/CHARMEX program, this campaign included an extensive experimental set-up based on ground based, balloon borne and ship and aircraft measurements. In this paper, a modelling perspective of the campaign is given, based on simulations with the regional CHIMERE chemistry-transport model in a configuration shaped for the Mediterranean region. Major sources of photooxidants (in particular ozone), and aerosol are addressed: long range transport from continental Europe, pollution build-up from shipping emissions, specifically organic aerosol formation from biogenic and anthropogenic VOC emissions, dust emissions. The simulations are evaluated with measurements at places and during periods when these particular sources were predominant. This will give a first overview of driving forces of the pollutant variability over the domain during the campaign. In addition, we will address, how well model forecasts (CHIMERE run by INERIS, Polyphemus run by CEREA) used for campaign planning agree with measurements.
• Nonpoint source pollution of urban stormwater runoff: a methodology for source analysis
  
  • Petrucci Guido
  • Gromaire Marie-Christine
  • Fallah Shorshani Masoud
  • Chebbo Ghassan
  Environmental Science and Pollution Research, Springer Verlag, 2014, pp.18. The characterization and control of runoff pollution from nonpoint sources in urban areas are a major issue for the protection of aquatic environments. We propose a methodology to quantify the sources of pollutants in an urban catchment and to analyze the associated uncertainties. After describing the methodology, we illustrate it through an application to the sources of Cu, Pb, Zn, and polycyclic aromatic hydrocarbons (PAH) from a residential catchment (228 ha) in the Paris region. In this application, we suggest several procedures that can be applied for the analysis of other pollutants in different catchments, including an estimation of the total extent of roof accessories (gutters and downspouts, watertight joints and valleys) in a catchment. These accessories result as the major source of Pb and as an important source of Zn in the example catchment, while activity-related sources (traffic, heating) are dominant for Cu (brake pad wear) and PAH (tire wear, atmospheric deposition). (10.1007/s11356-014-2845-4)
  DOI : 10.1007/s11356-014-2845-4
• Modelling and assimilation of lidar signals over Greater Paris during the MEGAPOLI summer campaign
  
  • Wang Yiguo
  • Sartelet Karine
  • Bocquet Marc
  • Chazette Patrick
  Atmospheric Chemistry and Physics, European Geosciences Union, 2014, 14 (7), pp.3511-3532. In this study, we investigate the ability of the chemistry transport model (CTM) Polair3D of the air quality modelling platform Polyphemus to simulate lidar backscattered profiles from model aerosol concentration outputs. This investigation is an important preprocessing stage of data assimilation (validation of the observation operator). To do so, simulated lidar signals are compared to hourly lidar observations performed during the MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) summer experiment in July 2009, when a ground-based mobile lidar was deployed around Paris on-board a van. The comparison is performed for six different measurement days, 1, 4, 16, 21, 26 and 29 July 2009, corresponding to different levels of pollution and different atmospheric conditions. Overall, Polyphemus well reproduces the vertical distribution of lidar signals and their temporal variability, especially for 1, 16, 26 and 29 July 2009. Discrepancies on 4 and 21 July 2009 are due to high-altitude aerosol layers, which are not well modelled. In the second part of this study, two new algorithms for assimilating lidar observations based on the optimal interpolation method are presented. One algorithm analyses PM10 (particulate matter with diameter less than 10 μm) concentrations. Another analyses PM2.5 (particulate matter with diameter less than 2.5 μm) and PM2.5-10 (particulate matter with a diameter higher than 2.5 μm and lower than 10 μm) concentrations separately. The aerosol simulations without and with lidar data assimilation (DA) are evaluated using the Airparif (a regional operational network in charge of air quality survey around the Paris area) database to demonstrate the feasibility and usefulness of assimilating lidar profiles for aerosol forecasts. The evaluation shows that lidar DA is more efficient at correcting PM10 than PM2.5, probably because PM2.5 is better modelled than PM10. Furthermore, the algorithm which analyses both PM2.5and PM2.5-10 provides the best scores for PM10. The averaged root-mean-square error (RMSE) of PM10 is 11.63 μg m−3 with DA (PM2.5 and PM2.5-10), compared to 13.69 μg m−3 with DA (PM10) and 17.74 μg m−3 without DA on 1 July 2009. The averaged RMSE of PM10 is 4.73 μg m−3 with DA (PM2.5 and PM2.5-10), against 6.08 μg m−3 with DA (PM10) and 6.67 μg m−3 without DA on 26 July 2009. (10.5194/acp-14-3511-2014)
  DOI : 10.5194/acp-14-3511-2014
• Dispersion atmosphérique et modélisation inverse pour la reconstruction de sources accidentelles de polluants
  
  • Winiarek Victor
  , 2014. Les circonstances pouvant conduire à un rejet incontrôlé de polluants dans l'atmosphère sont variées : il peut s'agir de situations accidentelles, par exemples des fuites ou explosions sur un site industriel, ou encore de menaces terroristes : bombe sale, bombe biologique, notamment en milieu urbain. Face à de telles situations, les objectifs des autorités sont multiples : prévoir les zones impactées à court terme, notamment pour évacuer les populations concernées ; localiser la source pour pouvoir intervenir directement sur celle-ci ; enfin déterminer les zones polluées à plus long terme, par exemple par le dépôt de polluants persistants, et soumises à restriction de résidence ou d'utilisation agricole. Pour atteindre ces objectifs, des modèles numériques peuvent être utilisés pour modéliser la dispersion atmosphérique des polluants. Après avoir rappelé les processus physiques qui régissent le transport de polluants dans l'atmosphère, nous présenterons les différents modèles à disposition. Le choix de l'un ou l'autre de ces modèles dépend de l'échelle d'étude et du niveau de détails (topographiques notamment) désiré. Nous présentons ensuite le cadre général (bayésien) de la modélisation inverse pour l'estimation de sources. Le principe est l'équilibre entre des informations a priori et des nouvelles informations apportées par des observations et le modèle numérique. Nous mettons en évidence la forte dépendance de l'estimation du terme source et de son incertitude aux hypothèses réalisées sur les statistiques des erreurs a priori. Pour cette raison nous proposons plusieurs méthodes pour estimer rigoureusement ces statistiques. Ces méthodes sont appliquées sur des exemples concrets : tout d'abord un algorithme semi-automatique est proposé pour la surveillance opérationnelle d'un parc de centrales nucléaires. Un second cas d'étude est la reconstruction des termes sources de césium-137 et d'iode-131 consécutifs à l'accident de la centrale nucléaire de Fukushima Daiichi. En ce qui concerne la localisation d'une source inconnue, deux stratégies sont envisageables : les méthodes dites paramétriques et les méthodes non-paramétriques. Les méthodes paramétriques s'appuient sur le caractère particulier des situations accidentelles dans lesquelles les émissions de polluants sont généralement d'étendue limitée. La source à reconstruire est alors paramétrisée et le problème inverse consiste à estimer ces paramètres, en nombre réduit. Dans les méthodes non-paramétriques, aucune hypothèse sur la nature de la source (ponctuelle, localisée, ...) n'est réalisée et le système cherche à reconstruire un champs d'émission complet (en 4 dimensions). Plusieurs méthodes sont proposées et testées sur des situations réelles à l'échelle urbaine avec prise en compte des bâtiments, pour lesquelles les méthodes que nous proposons parviennent à localiser la source à quelques mètres près, suivant les situations modélisées et les méthodes inverses utilisées