Publications

2013

• BLUE-based NO2 data assimilation at urban scale
  
  • Tilloy Anne
  • Mallet Vivien
  • Poulet David
  • Pesin Céline
  • Brocheton Fabien
  Journal of Geophysical Research, American Geophysical Union, 2013, 118 (4), pp.2031-2040. We aim at optimally combining air quality computations, from the Gaussian model ADMS Urban, and ground observations at urban scale. An ADMS simulation generated NO2 concentration fields across Clermont-Ferrand (France) down to street level, every 3 h for the full year 2008. A monitoring network composed of nine fixed stations provided hourly observations to be assimilated. Every 3 h, we compute the so-called BLUE (best linear unbiased estimator), which is a concentration field merging ADMS outputs and ground observations. Its error variance is supposed to be minimal under given assumptions regarding the errors on observations and model simulations. A key step lies in the modeling of error covariances between the computed NO2 concentrations across the city. We introduce a parameterized covariance which heavily relies on the road network. The covariance between two locations depends on the distance of each location to the road network and on the distance between the locations along the road network. Efficient parameters for the covariances are primarily chosen according to prior assumptions, χ2 diagnosis and leave-one-out cross-validations. According to the cross-validations, the improvements due to the assimilation seem moderately far from the observation network, but the root mean square error roughly decreases by 30-50% in the main city where the station density is high. The method is computationally tractable for the generation of improved concentration fields over a long period, or for day-to-day forecasts. (10.1002/jgrd.50233)
  DOI : 10.1002/jgrd.50233
• Prévisions d'ensemble à l'échelle saisonnière : mise en place d'une dynamique stochastique
  
  • Saunier-Batté Lauriane
  , 2013. La prévision d'ensemble à l'échelle saisonnière avec des modèles de circulation générale a connu un essor certain au cours des vingt dernières années avec la croissance exponentielle des capacités de calcul, l'amélioration de la résolution des modèles, et l'introduction progressive dans ceux-ci des différentes composantes (océan, atmosphère, surfaces continentales et glace de mer) régissant l'évolution du climat à cette échelle. Malgré ces efforts, prévoir la température et les précipitations de la saison à venir reste délicat, non seulement sur les latitudes tempérées mais aussi sur des régions sujettes à des aléas climatiques forts comme l'Afrique de l'ouest pendant la saison de mousson. L'une des clés d'une bonne prévision est la prise en compte des incertitudes liées à la formulation des modèles (résolution, paramétrisations, approximations et erreurs). Une méthode éprouvée est l'approche multi-modèle consistant à regrouper les membres de plusieurs modèles couplés en un seul ensemble de grande taille. Cette approche a été mise en œuvre notamment dans le cadre du projet européen ENSEMBLES, et nous montrons qu'elle permet généralement d'améliorer les rétro-prévisions saisonnières des précipitations sur plusieurs régions d'Afrique par rapport aux modèles pris individuellement. On se propose dans le cadre de cette thèse d'étudier une autre piste de prise en compte des incertitudes du modèle couplé CNRM-CM5, consistant à ajouter des perturbations stochastiques de la dynamique du modèle d'atmosphère ARPEGE-Climat. Cette méthode, baptisée “dynamique stochastique”, consiste à introduire des perturbations additives de température, humidité spécifique et vorticité corrigeant des estimations d'erreur de tendance initiale du modèle. Dans cette thèse, deux méthodes d'estimation des erreurs de tendance initiale ont été étudiées, basées sur la méthode de nudging (guidage) du modèle vers des données de référence. Elles donnent des résultats contrastés en termes de scores des rétro-prévisions selon les régions étudiées. Si on estime les corrections d'erreur de tendance initiale par une méthode de nudging itéré du modèle couplé vers les réanalyses ERA-Interim, on améliore significativement les scores sur l'hémisphère Nord en hiver en perturbant les prévisions saisonnières en tirant aléatoirement parmi ces corrections. Cette amélioration est accompagnée d'une nette réduction des biais de la hauteur de géopotentiel à 500 hPa. Une rétro-prévision en utilisant des perturbations dites“optimales” correspondant aux corrections d'erreurs de tendance initiale du mois en cours de prévision montre l'existence d'une information à l'échelle mensuelle qui pourrait permettre de considérablement améliorer les prévisions. La dernière partie de cette thèse explore l'idée d'un conditionnement des perturbations en fonction de l'état du modèle en cours de prévision, afin de se rapprocher si possible des améliorations obtenues avec ces perturbations optimales (10.70675/fb454f2dzb714z433fz8903zf890340b213a)
  DOI : 10.70675/fb454f2dzb714z433fz8903zf890340b213a
• Modélisation de la qualité de l'air : nombre de particules
  
  • Deschamps S.
  • Sartelet Karine
  , 2013. Modélisation de la concentration en nombre des particules à l'échelle urbaine avec le logiciel Polyphemus pour la qualité de l'air, et de comparaison des résultats du modèle avec des résultats de campagne de mesures (e.g. megapoli) an d'élucider les principaux facteurs gouvernant le nombre de particules en zone urbaine.
• Sensibilité des concentrations de PM2.5 au changement climatique sur l'Europe
  
  • Lecoeur Eve
  • Seigneur Christian
  , 2013. Les concentrations de particules fines (PM2.5) sont fortement dépendantes à la fois des conditions météorologiques et de nombreux processus chimiques. Le but de cette étude est de présenter un modèle statistique permettant de caractériser ces concentrations à l'échelle européenne à partir des conditions météorologiques. Le modèle de chimie-transport Polyphemus/Polair3D a été utilisé pour simuler les concentrations de PM2.5 sur la période 2000-2008 en Europe. Chaque année de simulation a été évaluée de façon opérationnelle par comparaison avec les observations fournies par les réseaux de surveillance de la qualité de l'air. Par ailleurs, la longue durée de la simulation (9 ans) a permis d'effectuer une évaluation dynamique de la capacité du modèle à reproduire la variabilité des concentrations et de la composition chimique des PM2.5 en fonction de la météorologie (température, précipitations, vent). Les résultats de ces simulations sont utilisés par la suite en tant que pseudo-observations pour implémenter un modèle statistique visant à caractériser les concentrations de particules fines à l'échelle européenne. Ce modèle utilise uniquement les résultats de la simulation, des données climatiques de grande échelle (pression à la surface de la mer) et la température de surface. Après validation de ce modèle pour le climat présent, la méthode sera applicable pour évaluer les concentrations de PM2.5 à partir de projections climatiques
• A multi-media approach to environmental impacts of road traffic in urban areas
  
  • Bonhomme Céline
  • Fallahshorshani Masoud
  • André Michel
  • Seigneur Christian
  , 2013. Road traffic pollutants are a cause of major concern in urban areas. In fact, traffic generated emissions are degrading air quality up to the point where the physical health of the citizens is directly threatened (in particular NOx, Sox, metals, microparticles..). Moreover, they contribute to a local and global deterioration of other environmental media by affecting for example water quality (in particular metals, PAH, aliphatic hydrocarbons). Even if all traffic pollutants are not a matter of concern for both air and water, some of them are in common between these media or linked by their vectors (for example particles). It justifies the need to try to treat jointly air and surface water impacts of road traffic emissions. The present work focuses on the development of a modeling platform linking traffic, emission, atmospheric dispersion and water fate of road pollutants. At the moment, the modeling chain begins with the traffic model output that serves as input for the pollutant emission model. Then the emission is considered as a lineic source and the pollutant dispersion is simulated with a Gaussian dispersion model in the atmosphere. Wet and dry depositions link that to the build-up and to the pollutant transport on urban surfaces during rainy events using an urban hydrological model. The main scientific challenge lies in evaluating the appropriate scales at which the global platform can give reliable results and by adopting different strategies to model each component of the model depending on the chosen spatial and temporal scales. Priority pollutants are sometimes different between the air and water environment, which may cause insufficient data and knowledge of pollutant emissions for water pollutants. Therefore, different emission or traffic components are available on the platform, depending on the scales or the nature of the pollutants that are simulated. Finally, the resolutions of the atmospheric and hydrological models are adapted to the emission knowledge and to the scale of observations. To illustrate the talk, some results from different case studies will be shown (Cours Lafayette, Viry Chatillon and Sucy catchments). At any time, the interest of these results with regard to the urban environment will be discussed. In particular, some scenarios may be tested with the platform: the impact of changes in the composition of the vehicle park or the occurrence of different meteorological conditions or urban design options on air or water quality. In conclusion, this attempt to implement a full modeling chain highlights the lake and the need of appropriate data in this field and opens the perspective of a new coupled traffic-air-water modeling field in urban areas.
• Evaluation of the Weather Research and Forecast/urban model over Greater Paris
  
  • Kim Youngseob
  • Sartelet Karine
  • Raut Jean-Christophe
  • Chazette Patrick
  Boundary-Layer Meteorology, Springer Verlag, 2013, 149 (1), pp.105-132. Meteorological modelling in the planetary boundary layer (PBL) over Greater Paris is performed using the Weather Research and Forecast (WRF) numerical model. The simulated meteorological fields are evaluated by comparison with mean diurnal observational data or mean vertical profiles of temperature, wind speed, humidity and boundary-layer height from 6 to 27 May 2005. Different PBL schemes, which parametrize the atmospheric turbulence in the PBL using different turbulence closure schemes, may be used in the WRF model. The sensitivity of the results to four PBL schemes (two non-local closure schemes and two local closure schemes) is estimated. Uncertainties in the PBL schemes are compared to the influence of the urban canopy model (UCM) and the updated Coordination of Information on the Environment (CORINE) land-use data. Using the UCM and the CORINE land-use data produces more realistic modelled meteorological fields. The wind speed, which is overestimated in the simulations without the UCM, is improved below 1,000 m height. Furthermore, the modelled PBL heights during nighttime are strongly modified, with an increase that may be as high as 200 %. At night, the impact of changing the PBL scheme is lower than the impact of using the UCM and the CORINE land-use data. (10.1007/s10546-013-9838-6)
  DOI : 10.1007/s10546-013-9838-6
• Modeling secondary organic aerosol in an urban area: application to Paris, France
  
  • Couvidat Florian
  • Kim Youngseob
  • Sartelet Karine
  • Seigneur Christian
  • Marchand Nicolas
  • Sciare J.
  Atmospheric Chemistry and Physics, European Geosciences Union, 2013, 13, pp.983-996. A secondary organic aerosol (SOA) model, H2O (Hydrophilic/Hydrophobic Organic), is evaluated over the Paris area. This model treats the formation of SOA with two kinds of surrogate species: hydrophilic species (which condense preferentially on an aqueous phase) and hydrophobic species (which condense only on an organic phase). These surrogates species are formed from the oxidation in the atmosphere of volatile organic compounds (VOC) by radicals (HO and NO3) and ozone. These VOC are either biogenic (isoprene, monoterpenes and sesquiterpenes) or anthropogenic (mainly aromatic compounds). This model includes the formation of aerosols from different precursors (biogenic precursors, aromatics), and semi-volatile organic compounds (SVOC) from traffic. The H2O aerosol model was incorporated into the Polyphemus air quality modeling platform and applied to the Paris area and evaluated by comparison to measurements performed during the Megapoli campaign in July 2009. The comparison to measurements in the suburbs and in the city center of Paris shows that the model gives satisfactory results for both elemental carbon (EC) and organic carbon (OC). However, the model gives a peak of OC concentrations in the morning due to high emissions from traffic, which does not appear in measurements. Uncertainties in the modeled temperature, which can affect the gas-particle partitioning, in the partitioning of primary SVOC or underestimation of primary organic aerosol (POA) evaporation by the model could explain the differences between model and measurements. Moreover, using a theoretical mechanism for the oxidation of primary SVOC and intermediate volatility organic compounds (IVOC), POA concentrations were found to be likely overestimated by models due to the use of simple partitioning constants (which do not take into account the affinity of a compound with the liquid aerosol solution) or due to the assumption that the organic aerosol solution is a one-phase ideal solution. The organic aerosol in the city center of Paris was found to be originating mostly from distant sources with only 30 to 38% due to local sources. (10.5194/acp-13-983-2013)
  DOI : 10.5194/acp-13-983-2013
• Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe, Part II: Evaluation of chemical concentrations and sensitivity simulations
  
  • Zhang Y.
  • Sartelet Karine
  • Shupeng Zhu
  • W. Wang
  • Wu Lin
  • Zhang Xiaojing
  • Wang K.
  • Pierre Tran
  • Seigneur Christian
  • Wang Z. F.
  Atmospheric Chemistry and Physics, European Geosciences Union, 2013, 13, pp.6845-6875. (10.5194/acp-13-6845-2013)
  DOI : 10.5194/acp-13-6845-2013
• State of the model to simulate the Fukushima Daiichi nuclear power plant accident
  
  • Mathieu A.
  • Korsakissok I.
  • Quélo D.
  • Saunier O.
  • Groell J.
  • Didier D.
  • Corbin D.
  • Denis J.
  • Tombette M.
  • Winiarek V.
  • Bocquet M.
  • Quentric E.
  • Benoit J.-P.
  Pollution Atmosphérique : climat, santé, société, APPA, 2013 (217). On March 11, 2011, the Tohoku earthquake generated a huge tsunami that ravaged the Pacific coast of Japan, leading to the Fukushima Daiichi nuclear power plant (NPP) accident. Three cores out of the six Fukushima Daiichi nuclear reactors melted, resulting in the release of huge amounts of radionuclides into the atmosphere. Two years after the accident, many uncertainties remain, which prevent us from reaching a full understanding of the accident. This article presents the approach carried out during the accident and afterwards, to improve our understanding of the events and environmental consequences. We trace the time evolution of the radioactivity released to the atmosphere, its subsequent dispersion simulated by models, and we compare the results to actual measurements. Four main release periods are highlighted. The first event had limited consequences to the north of the NPP along the coast; the second had no impact on Japanese territory because the plumes traveled toward the Pacific Ocean; the third was responsible for a significant and long-term impact, especially northwest of the NPP; and the last had consequences of lesser impact on the Tokyo area. The source term, i.e. the release rate of each radionuclide, is still highly uncertain. To improve it, a new method based on inverse modeling techniques and involving the use of gamma dose rate measurements has been developed. The method proved to be efficient and reliable when applied to the Fukushima accident. The inverted source term allowed identifying the main contamination events and helped to improve the model-to-data comparisons. An important outcome on this study is that the method proved to be perfectly suited to crisis management. It should contribute to improve the emergency response of the crisis center in case of a nuclear accident.
• Evaluating the capability of regional scale air quality models to capture the vertical distribution of pollutants
  
  • Solazzo E.
  • Bianconi R.
  • Pirovano G.
  • Moran M. D.
  • Vautard R.
  • Hogrefe C.
  • Matthias V.
  • Grossi P.
  • Appel K. W.
  • Bessagnet B.
  • Brandt J.
  • Chemel C.
  • Christensen J. H.
  • Forkel R.
  • Francis X. V.
  • Hansen A.
  • Mckeen S.
  • Nopmongcol U.
  • Prank M.
  • Sartelet Karine
  • Segers A.
  • Silver J. D.
  • Yarwood G.
  • Werhahn J.
  • Zhang J.
  Geoscientific Model Development, European Geosciences Union, 2013, 6 (3), pp.791-818. This study is conducted in the framework of the Air Quality Modelling Evaluation International Initiative (AQMEII) and aims at the operational evaluation of an ensemble of 12 regional-scale chemical transport models used to predict air quality over the North American (NA) and European (EU) continents for 2006. The modelled concentrations of ozone and CO, along with the meteorological fields of wind speed (WS) and direction (WD), temperature (T), and relative humidity (RH), are compared against high-quality in-flight measurements collected by instrumented commercial aircraft as part of the Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by Airbus In-service airCraft (MOZAIC) programme. The evaluation is carried out for five model domains positioned around four major airports in NA (Portland, Philadelphia, Atlanta, and Dallas) and one in Europe (Frankfurt), from the surface to 8.5 km. We compare mean vertical profiles of modelled and measured variables for all airports to compute error and variability statistics, perform analysis of altitudinal error correlation, and examine the seasonal error distribution for ozone, including an estimation of the bias introduced by the lateral boundary conditions (BCs). The results indicate that model performance is highly dependent on the variable, location, season, and height (e.g. surface, planetary boundary layer (PBL) or free troposphere) being analysed. While model performance for T is satisfactory at all sites (correlation coefficient in excess of 0.90 and fractional bias a parts per thousand currency sign 0.01 K), WS is not replicated as well within the PBL (exhibiting a positive bias in the first 100 m and also underestimating observed variability), while above 1000 m, the model performance improves (correlation coefficient often above 0.9). The WD at NA airports is found to be biased in the PBL, primarily due to an overestimation of westerly winds. RH is modelled well within the PBL, but in the free troposphere large discrepancies among models are observed, especially in EU. CO mixing ratios show the largest range of modelled-to-observed standard deviations of all the examined species at all heights and for all airports. Correlation coefficients for CO are typically below 0.6 for all sites and heights, and large errors are present at all heights, particularly in the first 250 m. Model performance for ozone in the PBL is generally good, with both bias and error within 20%. Profiles of ozone mixing ratios depend strongly on surface processes, revealed by the sharp gradient in the first 2 km (10 to 20 ppb km(-1)). Modelled ozone in winter is biased low at all locations in the NA, primarily due to an underestimation of ozone from the BCs. Most of the model error in the PBL is due to surface processes (emissions, transport, photochemistry), while errors originating aloft appear to have relatively limited impact on model performance at the surface. Suggestions for future work include interpretation of the model-to-model variability and common sources of model bias, and linking CO and ozone bias to the bias in the meteorological fields. Based on the results from this study, we suggest possible in-depth, process-oriented and diagnostic investigations to be carried out next. (10.5194/gmd-6-791-2013)
  DOI : 10.5194/gmd-6-791-2013
• Fundamental principles of data assimilation underlying the Verdandi library: applications to biophysical model personalization within euHeart
  
  • Chapelle Dominique
  • Fragu Marc
  • Mallet Vivien
  • Moireau Philippe
  Medical and Biological Engineering and Computing, Springer Verlag, 2013, 51, pp.1221-1233. We present the fundamental principles of data assimilation underlying the Verdandi library, and how they are articulated with the modular architecture of the library. This translates -- in particular -- into the definition of standardized interfaces through which the data assimilation library interoperates with the model simulation software and the so-called observation manager. We also survey various examples of data assimilation applied to the personalization of biophysical models, in particular for cardiac modeling applications within the euHeart European project. This illustrates the power of data assimilation concepts in such novel applications, with tremendous potential in clinical diagnosis assistance. (10.1007/s11517-012-0969-6)
  DOI : 10.1007/s11517-012-0969-6
• Numerical simulations of the microscale heterogeneities of turbulence observed on a complex site
  
  • Zaïdi Hanane
  • Dupont Eric
  • Milliez Maya
  • Carissimo Bertrand
  • Musson-Genon Luc
  Boundary-Layer Meteorology, Springer Verlag, 2013, 147, pp.237-259. (10.1007/s10546-012-9783-9)
  DOI : 10.1007/s10546-012-9783-9
• Modeling coagulation of externally mixed particles: sectional approach for both size and chemical composition
  
  • Dergaoui Hilel
  • Debry Edouard
  • Sartelet Karine
  • Seigneur Christian
  Journal of Aerosol Science, Elsevier, 2013, 58, pp.17-32. Three-dimensional chemical transport models of air quality often assume particles to be internally mixed, that is, particles of a given size are associated to a unique chemical composition. However, measurements show that this assumption is not valid, especially close to sources. We present here the dynamic equation for Brownian coagulation of externally mixed particles (i.e., particles of a given size may have different chemical compositions). Both size distribution and mass fraction of particle chemical components are discretized. Either one or several families of particle chemical components may be discretized to reduce computational cost. The model is validated by comparison to results obtained for internally mixed particles and the effect of mixing is investigated for aerosol mixtures of two, three and four components. Mixing increases with the number of components, because the probability for a particle to coagulate with a particle of different composition increases. (10.1016/j.jaerosci.2012.11.007)
  DOI : 10.1016/j.jaerosci.2012.11.007
• Composition and source apportionment of organic aerosol in Beirut, Lebanon, during winter 2012
  
  • Waked A.
  • Afif Charbel
  • Brioude Jérôme
  • Formenti P.
  • Chevaillier S.
  • El Haddad I.
  • Doussin J. F.
  • Borbon Agnès
  • Seigneur C.
  Aerosol Science and Technology, Taylor & Francis, 2013, 47 (11), pp.1258-1266. Fine organic aerosols were collected at a semi-urban site in Beirut, Lebanon, from 28 January to 12 February 2012 as part of the Emission and Chemistry of Organic Carbon in East Mediterranean-Beirut (ECOCEM-Beirut). A total of 20 quartz filter samples were collected on a 12 h basis using a high-volume sampler and were analyzed using a GC/MS technique. Levoglucosan was the major most abundant single component with an average value of 306 ng.m -3, followed by saturated and unsaturated carboxylic acids and sugars with average values of 234 and 118 ng.m-3, respectively. Reported values for other carboxylic acids, polycyclic aromatic hydrocarbons, and biogenic secondary organic aerosols (BSOA) were 87, 33 and 21 ng.m-3, respectively. Compared to a similar field campaign conducted in summer 2011, levoglucosan concentrations were lower in summer by a factor of 6, due to the use of wood burning for residential heating in winter. Concentrations of saturated and unsaturated carboxylic acids, other carboxylic acids, and BSOA were higher in summer by a factor of 3, 2, and 7, respectively. Higher concentrations observed for BSOA and other dicarboxylic acids during summer are due to higher biogenic emissions and greater photochemical activity in summer. Copyright © American Association for Aerosol Research. (10.1080/02786826.2013.831975)
  DOI : 10.1080/02786826.2013.831975
• Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe, Part I: Model description, evaluation of meteorological predictions, and aerosol-meteorology interactions
  
  • Zhang Y.
  • Sartelet Karine
  • Wu Lin
  • Seigneur Christian
  Atmospheric Chemistry and Physics, European Geosciences Union, 2013, 13, pp.6807-6843. (10.5194/acp-13-6807-2013)
  DOI : 10.5194/acp-13-6807-2013
• Assimilation of ground versus lidar observations for PM10 forecasting
  
  • Wang Yiguo
  • Sartelet Karine
  • Bocquet Marc
  • Chazette Patrick
  Atmospheric Chemistry and Physics, European Geosciences Union, 2013, 13 (1), pp.269-283. This article investigates the potential impact of future ground-based lidar networks on analysis and short-term forecasts of particulate matter with a diameter smaller than 10 μm (PM10). To do so, an Observing System Simulation Experiment (OSSE) is built for PM10 data assimilation (DA) using optimal interpolation (OI) over Europe for one month from 15 July to 15 August 2001. First, using a lidar network with 12 stations and representing the "true" atmosphere by a simulation called "nature run", we estimate the efficiency of assimilating the lidar network measurements in improving PM10 concentration for analysis and forecast. It is compared to the efficiency of assimilating concentration measurements from the AirBase ground network, which includes about 500 stations in western Europe. It is found that assimilating the lidar observations decreases by about 54% the root mean square error (RMSE) of PM10 concentrations after 12 h of assimilation and during the first forecast day, against 59% for the assimilation of AirBase measurements. However, the assimilation of lidar observations leads to similar scores as AirBase's during the second forecast day. The RMSE of the second forecast day is improved on average over the summer month by 57% by the lidar DA, against 56% by the AirBase DA. Moreover, the spatial and temporal influence of the assimilation of lidar observations is larger and longer. The results show a potentially powerful impact of the future lidar networks. Secondly, since a lidar is a costly instrument, a sensitivity study on the number and location of required lidars is performed to help define an optimal lidar network for PM10 forecasts. With 12 lidar stations, an efficient network in improving PM10 forecast over Europe is obtained by regularly spacing the lidars. Data assimilation with a lidar network of 26 or 76 stations is compared to DA with the previously-used lidar network. During the first forecast day, the assimilation of 76 lidar stations' measurements leads to a better score (the RMSE decreased by about 65%) than AirBase's (the RMSE decreased by about 59%). (10.5194/acp-13-269-2013)
  DOI : 10.5194/acp-13-269-2013
• Dynamic evaluation of a multi-year model simulation of particulate matter concentrations over Europe
  
  • Lecoeur Eve
  • Seigneur Christian
  Atmospheric Chemistry and Physics, European Geosciences Union, 2013, 13, pp.4319-4337. (10.5194/acp-13-4319-2013)
  DOI : 10.5194/acp-13-4319-2013
• Evaluation of roadway Gaussian plume models with large-scale measurement campaigns
  
  • Briant Régis
  • Seigneur Christian
  • Gadrat M.
  • Bugajny C.
  Geoscientific Model Development, European Geosciences Union, 2013, 6, pp.445-456. Gaussian models are commonly used to simulate atmospheric pollutant dispersion near sources because they provide an efficient compromise between reasonable accuracy and manageable computational time. The Gaussian dispersion formula provides an exact solution to the atmospheric diffusion equation for the dispersion of a pollutant emitted from a point source. However, the Gaussian dispersion formula for a line source, which is convenient to model emissions from on-road traffic, is exact only when the wind is perpendicular to the line source. A novel approach that reduces the error in the line source formula when the wind direction is not perpendicular to the road was recently developed. This model is used to simulate NOx concentrations in a large case study (1371 road sections representing about 831 km). NO2, NO and O3 concentrations are then computed using the photostationary-state approximation. NO2 concentrations are compared with measurements made at 242 locations in the domain area. Model performance is satisfactory with mean normalised errors of 22% (winter month) to 31% (summer month). Results obtained here are also compared with those obtained with a previous formulation and with a standard model used for regulatory applications, ADMS-Urban. Discrepancies among the results obtained with those models are discussed. (10.5194/gmd-6-445-2013)
  DOI : 10.5194/gmd-6-445-2013
• Modeling air pollution in Lebanon: evaluation at a suburban site in Beirut in summer
  
  • Waked Antoine
  • Seigneur Christian
  • Couvidat Florian
  • Kim Youngseob
  • Sartelet Karine
  • C. Afif
  • Borbon Agnès
  • P. Formenti
  • S. Sauvage
  Atmospheric Chemistry and Physics, European Geosciences Union, 2013, 13, pp.5873-5886. (10.5194/acp-13-5873-2013)
  DOI : 10.5194/acp-13-5873-2013
• Multi-scale modeling of roadway air quality impacts: development and evaluation of a plume-in-grid model
  
  • Briant Régis
  • Seigneur Christian
  Atmospheric Environment, Elsevier, 2013, 68, pp.162-173. Eulerian three-dimensional (3D) grid-based models are widely used in air quality modeling. In such models, emissions are instantaneously diluted within the grid cells and, therefore, the near-source impacts of large point and line sources cannot be properly resolved. Plume-in-Grid models (PinG) use a subgrid-scale treatment to better represent local source contributions in an Eulerian grid-based simulation. PinG models already exist for point sources. However, modeling emissions from roadway traffic with point sources implies a very large computational burden. We present here a new PinG model that uses a Gaussian line source model, better suited than point sources to model roadway traffic emissions, embedded within an Eulerian model. The model is evaluated with a large dataset of nitrogen dioxide (NO2) concentrations over a 800 km road network. The PinG model leads to greater NO2 concentrations and shows better performance than the Eulerian model. (10.1016/j.atmosenv.2012.11.058)
  DOI : 10.1016/j.atmosenv.2012.11.058
• Investigating the impact of aqueous-phase chemistry and wet deposition on organic aerosol formation using a molecular surrogate modeling approach
  
  • Couvidat Florian
  • Sartelet Karine
  • Seigneur Christian
  Environmental Science and Technology, American Chemical Society, 2013, 47, pp.914-922. A molecular surrogate representation of secondary organic aerosol (SOA) formation is used to investigate the effect of aqueous-phase (in clouds and particles) chemical processing and wet deposition on SOA atmospheric concentrations. To that end, the hydrophilic/hydrophobic organic (H2O) model was augmented to account for several gas/aqueous-phase equilibria and aqueous-phase processes, including the formation of oxalic, glyoxilic and pyruvic acids, the oxidation of methyl vinyl ketone (MVK) and methacrolein (MACR), the formation of tetrols and organosulfates from epoxydiols (IEPOX), and further oxidation of water-soluble SOA (aging). Among those processes, SOA chemical aging and IEPOX reactions led to the most significant increases (up to 1 μg m-3 in some areas) in SOA concentrations in a one-month summer simulation over Europe. However, large uncertainties remain in the gas/aqueous-phase partitioning of oxalic acid, MVK, and MACR. Below-cloud scavenging of SOA precursor gases and of gas-phase SVOC was found to affect SOA concentrations by up to 20%, which suggests that it should be taken into account in air quality models. (10.1021/es3034318)
  DOI : 10.1021/es3034318
• A new algorithm to solve condensation/evaporation for ultra fine, fine, and coarse particles
  
  • Devilliers Marion
  • Debry Edouard
  • Sartelet Karine
  • Seigneur Christian
  Journal of Aerosol Science, Elsevier, 2013, 55, pp.116-136. A new algorithm for condensation/evaporation has been developed that is accurate for both mass and number concentrations over the full size range of ultra fine, fine, and coarse particles. This new algorithm is compared to several standard sectional and modal algorithms for two case studies. In this algorithm, we use the Euler scheme for the number concentration of ultra fine particles and the Euler scheme for the mass concentration of fine and coarse particles. The results of this study provide useful information to select algorithms in order to correctly simulate aerosol dynamics in air quality models over a wide range of particle sizes. (10.1016/j.jaerosci.2012.08.005)
  DOI : 10.1016/j.jaerosci.2012.08.005
• Modélisation numérique de la dispersion atmosphérique accidentelle des radionucléides : l'état de l'art de la recherche
  
  • Bocquet Marc
  Revue du Centre de Défense NBC, Ministère de la Défense, 2013 (3), pp.47-49. No abstract.