Publications

2021

• Hydraulic traits are coupled with plant anatomical traits under drought–rewatering cycles in Ginkgo biloba L.
  
  • Li Shan
  • Li Xin
  • Wang Jie
  • Chen Zhicheng
  • Lu Sen
  • Wan Xianchong
  • Sun Hongyan
  • Wang Li
  • Delzon Sylvain
  • Cochard Hervé H.
  • Jiang Xiaomei
  • Shu Jianhua
  • Zheng Jingming
  • Yin Yafang
  Tree Physiology, Oxford University Press (OUP), 2021, pp.12 p.. Abstract Investigating the responses of plant anatomical traits of trees to drought–rewatering cycles helps us to understand their responses to climate change; however, such work has not been adequately reported. In this study, Ginkgo biloba L. saplings were subjected to moderate, severe, extreme and lethal drought conditions by withholding water according to the percentage loss of hydraulic conductivity (PLC) and rewatering on a regular basis. Samples of phloem, cambium and xylem were collected to quantify their cellular properties including cambium and phloem cell vitality, xylem growth ring width, pit aspiration rates and pit membrane thickness using light microscopy and transmission microscopy. The results showed that the mortality rate of G. biloba saplings reached 90% at approximately P88 (xylem water potential inducing 88% loss of hydraulic conductivity). The onset of cambium and phloem cell mortality might be in accordance with that of xylem embolism. Close negative correlations between xylem water potential and PLC and between xylem water potential and cambium and phloem mortality suggested that xylem hydraulic traits are coupled with anatomical traits under declining xylem water potential. Cambium and phloem cell vitality as well as xylem growth ring width decreased significantly with increasing drought conditions. However, xylem pit membrane thickness, cambial zone width and cambial cell geometry were not affected by the drought–rewatering cycles. The tracheid radial diameter, intertracheid cell wall thickness and tracheid density decreased significantly during both drought conditions and rewatering conditions. In addition to hydraulic traits, cambium and phloem cell vitality can be used as anatomical traits to evaluate the mortality of G. biloba under drought. Future work is proposed to observe the dynamics of pit aspiration rates under drought–rewatering cycles in situ to deepen our understanding of the essential role of bordered pits in the ‘air-seeding’ mechanism. (10.1093/treephys/tpab174)
  DOI : 10.1093/treephys/tpab174
• Modelling solar radiation for PV optimisation
  
  • Al Asmar Lea
  , 2021. A strong development of the solar energy sector is expected for the coming years inFrance and around the world. An accurate prediction of the amount of solar irradiancereaching the ground is necessary to optimize the performance of photovoltaic (PV) farms and to forecast the production at different time scales. However, the amount of solar irradiance reaching the ground is influenced by different geographical, meteorological and atmospheric parameters, including the characteristics of clouds and aerosols. The objective of this thesis is to improve the modeling of solar irradiation, by focusing on the impact of clouds and aerosols.Improvements have been made to the standalone 1D irradiance model of the CFD software code_saturne. The model now estimates the total solar irradiance and its direct and diffuse components taking into account clouds, aerosols and absorption by minor gases. Simulations are conducted and compared to measurements at the French SIRTA observatory (instrumental site for atmospheric remote sensing research), located in Palaiseau, Ile-de-France.Satisfactory results are obtained during clear-sky days when considering the impact ofaerosols which optical properties are estimated by coupling our model to the Polyphemus platform. Clouds have a strong influence on the amount of solar irradiance reaching the ground, they have large spatio-temporal variations and are difficult to model. The estimation of irradiance during cloudy-sky days is improved by coupling the model to on-site measurements of cloud parameters (cloud optical thickness, cloud fraction) from the SIRTA observatory. A sensitivity analysis on the cloud parameters is performed in order to better understand and quantify the influence of these parameters on the simulated irradiance (globaland direct), and to identify the data sources that minimize the prediction error. Moreover, hourly values of solar fluxes are analyzed to determine and physically understand the causes of the largest errors between model and measurements when measured cloud parameters are used. The second part of the thesis consisted in applying and validating the model on a well-documented case of a radiative fog at the SIRTA (ParisFog campaign), where the fog evolves into a low stratus cloud. Special attention is given to the impact of aerosols concentration and of the presence of black carbon in cloud droplets on the dissipation of the fog as well as the hypothesis used for the cloud fraction. In the third part, further improvements are implemented in the 3D irradiation scheme in order to take into account the aerosols and clouds and for its application to PV farms. This 3D model is applied to a case of interaction with an obstacle, and results are compared to those obtained with the 1D scheme. (10.70675/7e850abaz0de2z4d89zb768zdffefd541d84)
  DOI : 10.70675/7e850abaz0de2z4d89zb768zdffefd541d84
• Modelling solar radiation for photovoltaic (PV) optimisation
  
  • Al Asmar Léa
  , 2021. A strong development of the solar energy sector is expected for the coming years in France and around the world. An accurate prediction of the amount of solar irradiance reaching the ground is necessary to optimize the performance of photovoltaic (PV) farms and to forecast the production at different time scales. However, the amount of solar irradiance reaching the ground is influenced by different geographical, meteorological and atmospheric parameters, including the characteristics of clouds and aerosols. The objective of this thesis is to improve the modelling of solar radiation, by focusing on the impact of clouds and aerosols. Improvements have been made to the standalone 1D irradiance model of the CFD software code_saturne. The model now estimates the total solar irradiance and its direct and diffuse components, taking into account clouds, aerosols and absorption by minor gases. Simulations are conducted and compared to measurements at the French SIRTA observatory (instrumen- tal site for atmospheric remote sensing research), located in Palaiseau, Île-de-France. Satis- factory results are obtained during clear-sky days when considering the impact of aerosols, which optical properties are estimated by coupling our model to the Polyphemus platform. Clouds have a strong influence on the amount of solar irradiance reaching the ground, they have large spatio-temporal variations and are difficult to model. The estimation of irradiance during cloudy-sky days is improved by coupling the model to on-site measurements of cloud parameters (cloud optical thickness, cloud fraction) from the SIRTA observatory. A sensitivity analysis on the cloud parameters is performed in order to better understand and quantify the influence of these parameters on the simulated irradiance (global and direct), and to identify the data sources that minimize the prediction error. Moreover, hourly values of solar fluxes are analysed to determine and physically understand the causes of the largest errors between model and measurements when measured cloud parameters are used. The second part of the thesis consisted in applying and validating the model on a well-documented case of a radiative fog at the SIRTA (ParisFog campaign), where the fog evolves into a low stra- tus cloud. Special attention is given to the impact of aerosols concentration and of the presence of black carbon in cloud droplets on the dissipation of the fog as well as the hypothesis used for the cloud fraction. In the third part, further improvements are implemented in the 3D irradiation scheme in or- der to take into account the aerosols and clouds and for its application to PV farms. In a first step, this 3D model is applied to this case of radiative fog, and results are compared to those obtained with the 1D scheme.
• Chemical Characterization of PM2.5 in the East Mediterranean during the hot season
  
  • Fakhri Nansi
  • Fadel Marc
  • Öztürk Fatma
  • Keleş Melek
  • Iakovides Minas
  • Pikridas Michael
  • Abdallah Charbel
  • Karam Cyril
  • Sciare Jean
  • Hayes Patrick
  • Afif Charbel
  , 2021.
• Improvement of solar irradiance modelling during cloudy-sky days using measurements
  
  • Al Asmar Léa
  • Musson Genon Luc
  • Dupont Eric
  • Dupont Jean Charles
  • Sartelet Karine
  Solar Energy, Elsevier, 2021. Clouds have a strong influence on the amount of solar irradiance reaching the ground. However, they have large spatio-temporal variations and are difficult to model. The 1D irradiance model of code_saturne is used to estimate the global and direct solar irradiances at the ground, taking into account the impact of atmospheric gas, clouds and aerosols. Simulations are conducted and compared to measurements at the French SIRTA observatory (instrumental site for atmospheric remote sensing research), located in Palaiseau, Ile-de-France in August 2009 and in the year 2014. Although irradiance is very well modelled during clear-sky days, it is over-estimated during cloud-sky days. The estimation of irradiance during cloudy-sky days is improved by coupling the model to on-site measurements of cloud parameters from the SIRTA. RMSEs around 59 W m−2 and 50 W m−2 and MBEs around +17 W m−2 and -18 W m−2 are obtained, respectively, for global and direct irradiances during cloudy-sky days using pyranometer measurements for cloud fraction and microwave radiometric measurements for liquid water path. A sensitivity analysis on the cloud parameters that may lead to the best improvement of simulated irradiance is performed. The cloud optical depth is the most important one, followed by the cloud fraction. The different instruments used for the determination of these parameters are examined. Moreover, hourly values of solar fluxes are analysed to determine and physically understand persistent errors between model and measurements when measured cloud parameters are used. (10.1016/j.solener.2021.10.084)
  DOI : 10.1016/j.solener.2021.10.084
• PIRATE (Port Inventories ReAl TimE): Overview of an upcoming French-Korean project
  
  • Riffault Véronique
  • d'Anna B.
  • Roustan Yelva
  • Escat Emmanuel
  • Cortinovis Jérôme
  • Armengaud Alexandre
  • Lim Hyoji
  • Lee Yongchan
  • Lee Heekwan
  , 2021.
• A comparison of combined data assimilation and machine learning methods for offline and online model error correction
  
  • Farchi Alban
  • Bocquet Marc
  • Laloyaux Patrick
  • Bonavita Massimo
  • Malartic Quentin
  Journal of computational science, Elsevier, 2021, 55, pp.101468. Recent studies have shown that it is possible to combine machine learning methods with data assimilation to reconstruct a dynamical system using only sparse and noisy observations of that system. The same approach can be used to correct the error of a knowledge-based model. The resulting surrogate model is hybrid, with a statistical part supplementing a physical part. In practice, the correction can be added as an integrated term (i.e. in the model resolvent) or directly inside the tendencies of the physical model. The resolvent correction is easy to implement. The tendency correction is more technical, in particular it requires the adjoint of the physical model, but also more flexible. We use the two-scale Lorenz model to compare the two methods. The accuracy in long-range forecast experiments is somewhat similar between the surrogate models using the resolvent correction and the tendency correction. By contrast, the surrogate models using the tendency correction significantly outperform the surrogate models using the resolvent correction in data assimilation experiments. Finally, we show that the tendency correction opens the possibility to make online model error correction, i.e. improving the model progressively as new observations become available. The resulting algorithm can be seen as a new formulation of weak-constraint 4D-Var. We compare online and offline learning using the same framework with the two-scale Lorenz system, and show that with online learning, it is possible to extract all the information from sparse and noisy observations. (10.1016/j.jocs.2021.101468)
  DOI : 10.1016/j.jocs.2021.101468
• Quantification of uncertainties in the assessment of an atmospheric release source applied to the autumn 2017 106Ru event
  
  • Dumont Le Brazidec Joffrey
  • Bocquet Marc
  • Saunier Olivier
  • Roustan Yelva
  Atmospheric Chemistry and Physics, European Geosciences Union, 2021, 21, pp.13247-13267. Using a Bayesian framework to solve the inverse modelling problem of release source assessment has proven to be of signi_cant interest in recent years. Through Markov chain Monte Carlo (MCMC) algorithms, distributions of the variables describing the release such as the location, the duration, and the magnitude as well as the errors can be sampled in order to get a complete characterisation of the source. In this study, several approaches are described and applied to improve the rightness of these distributions, and therefore to get a better apprehension of the uncertainties. First, we propose a method based on ensemble forecasting, where physical parameters of both the meteorological _elds and the transport model are perturbed to create an enhanced ensemble. Members of the ensemble are then represented by weights and sampled at once with the other variables describing the source to take in account modelling errors. Secondly, we discuss how the choice of the likelihood can alter a radiological or nuclear source assessment, and propose several suited distributions. Finally, two designs depending on the measurements set of the observation error covariance matrix are proposed. These methods are applied on the case of the detection of Ruthenium 106 of unknown origin in Europe in autumn 2017. We present a posteriori distributions meant to identify the origin of the release, to assess the source term, to quantify the uncertainties associated to the observations and the modelling, as well as densities of the weights of the perturbed ensemble. (10.5194/acp-21-13247-2021)
  DOI : 10.5194/acp-21-13247-2021
• Cross-analysis for the assessment of urban environmental quality: An interdisciplinary and participative approach
  
  • Haouès-Jouve Sinda
  • Lemonsu Aude
  • Gauvreau Benoit
  • Amossé Alexandre
  • Can Arnaud
  • Carissimo Bertrand
  • Gaudio Noémie
  • Lopez Claudia Ximena
  • Hidalgo Julia
  • Chouillou Delphine
  • Richard Isabelle
  • Luc Adolphe
  • Berry-Chikhaoui Isabelle
  • Bouyer Julien
  • Challéat Samuel
  • de Munck Cécile
  • Dorier Elisabeth
  • Guillaume Gwenaël
  • Sophie Hooneart
  • Le Bras Julien
  • Legain Dominique
  • Lévy Jean-Pierre
  • Masson Valéry
  • Marry Solène
  • Nguyen-Luong Danny
  • Rojas Arias Juan Carlos
  • Gao Zhenlan
  Environment and Planning B: Urban Analytics and City Science, SAGE Publications, 2021, 49 (3), pp.1024-1047. The goal of this research is to assess environmental quality at the neighbourhood level through a multi-dimensional and multi-sensory approach that combines social and physical methodologies. For this purpose, an interdisciplinary protocol has been designed to simultaneously collect physical parameter measurements (related to microclimate and acoustics) and survey data on perceptions (involving residents and non-residents). The cross-referenced analysis of data collected at six contrasting places in a district in Toulouse (France) enabled us (i) to better understand and prioritise the factors that influence residents' assessment of the quality of their living environment and (ii) to understand to what extent the differentiation of the places by the inhabitants converges with the differentiation of these places based on acoustic and micrometeorological measurements. The statistical analysis based on individuals showed the importance of noise and air quality that rank just after the aesthetic dimension for all respondents. Nevertheless, the quality of maintenance and the feeling of security that the place inspires seem to be as crucial as these environmental criteria for the inhabitants. The analysis focused on the sites highlighted the consistency between the typology of places based on perceptions and that based on acoustic measurements, which confirms the high inhabitants' sensitivity to this environmental component. (10.1177/23998083211037350)
  DOI : 10.1177/23998083211037350
• PM2.5 sources in the Eastern Mediterranean capital Beirut: chemical characterization and contribution to ambient concentrations.
  
  • Fakhri Nansi
  • Fadel Marc
  • Öztürk Fatma
  • Keleş Melek
  • Iakovides Minas
  • Pikridas Michael
  • Abdallah Charbel
  • Karam Cyril
  • Sciare Jean
  • Hayes Patrick
  • Afif Charbel
  , 2021.
• Using machine learning to correct model error in data assimilation and forecast applications
  
  • Farchi Alban
  • Laloyaux Patrick
  • Bonavita Massimo
  • Bocquet Marc
  Quarterly Journal of the Royal Meteorological Society, Wiley, 2021, 147 (739). The idea of using machine learning (ML) methods to reconstruct the dynamics of a system is the topic of recent studies in the geosciences, in which the key output is a surrogate model meant to emulate the dynamical model. In order to treat sparse and noisy observations in a rigorous way, ML can be combined with data assimilation (DA). This yields a class of iterative methods in which, at each iteration, a DA step assimilates the observations and alternates with a ML step to learn the underlying dynamics of the DA analysis. In this article, we propose to use this method to correct the error of an existing, knowledge‐based model. In practice, the resulting surrogate model is a hybrid model between the original (knowledge‐based) model and the ML model. We demonstrate the feasibility of the method numerically using a two‐layer, two‐dimensional, quasi‐geostrophic channel model. Model error is introduced by the means of perturbed parameters. The DA step is performed using the strong‐constraint 4D‐Var algorithm, while the ML step is performed using deep learning tools. The ML models are able to learn a substantial part of the model error and the resulting hybrid surrogate models produce better short‐ to mid‐range forecasts. Furthermore, using the hybrid surrogate models for DA yields a significantly better analysis than using the original model. (10.1002/qj.4116)
  DOI : 10.1002/qj.4116
• Modélisation de la qualité de l'air dans les rues de Paris
  
  • Lugon Cornejo von Marttens Lya
  , 2021. Afin de modéliser les concentrations de polluants liés à la qualité de l’air dans les rues de Paris, le modèle de réseau de rues MUNICH (Model of Urban Network of Intersecting Canyons and Highways) est amélioré. Une approche non stationnaire est développée pour représenter la formation des composés secondaires, tels que NO2. Pour modéliser la dynamique des aérosols, MUNICH est couplé au module chimique SSH-aérosol. Les concentrations en gaz et particules dans les rues de Paris sont simulées avec MUNICH, couplé au modèle de chimie-transport Polair3D pour intégrer les concentrations de fond dans les rues. Pour les composés gazeux, le couplage entre MUNICH et Polair3D peut être unidirectionnel (les concentrations de fond influencent celles des rues) ou bidirectionnel (il y a un feedback entre la rue et les concentrations de fond). Les concentrations de NO2 et NOx se comparent bien aux observations, quelque soit l'approche utilisée pour le couplage. Le couplage bidirectionnel influence plus les rues avec un rapport hauteur/largeur intermédiaire et avec des émissions de trafic élevées, atteignant 60% sur les concentrations de NO2 selon la rue. Pour les particules, les concentrations de PM2.5, PM10 et les compositions chimiques simulées sont proches des observations. Les particules secondaires ont un impact important sur les concentrations de PM2.5, atteignant 27% selon la rue et le moment de la journée. La chimie gazeuse a une forte influence sur les espèces gazeuses réactives, augmentant de 37% la concentration moyenne du NO2. L'influence sur les condensables est plus faible, mais atteint 20% selon la rue. L'hypothèse d'équilibre thermodynamique dans le calcul de la condensation/évaporation surestime les concentrations en organiques d'environ 5% en moyenne, jusqu'à 31% à midi selon la rue. Les émissions trafic de NH3 augmentent les concentrations en inorganiques de 3% en moyenne, atteignant 26% selon la rue. Pour expliquer la sous-estimation par le modèle des fortes concentrations de carbone suie (BC) observées dans les rues, l'influence des émissions hors échappement et du couplage bidirectionnel est investiguée. Une nouvelle approche pour calculer la remise en suspension des particules est présentée, modélisant la masse déposée et respectant le bilan de masse à la surface des rues. Les simulations montrent que la remise en suspension des particules a un faible impact sur les concentrations de BC. Les concentrations de BC dans les rues influencent les concentrations urbaines de fond : l’influence du couplage bidirectionnel atteint 50% selon la rue. Les émissions d'usure des pneus contribuent aux émissions de BC de façon comparable aux émissions à l'échappement. Des nouveaux facteurs d'émission sont proposés cohérents avec certaines études de la littérature et la comparaison modèle/mesures effectuée. MUNICH est finalement utilisé sur Paris pour estimer l'impact du renouvellement du parc automobile sur dix ans et de la mobilité urbaine sur l'exposition de la population à de multiples composés. Le renouvellement du parc de véhicules diminue fortement l'exposition de la population aux NO2, BC, PM10, PM2.5 et aux particules organiques. Cette diminution est plus importante que celle estimée en utilisant un CTM à l'échelle régionale. L'exposition de la population aux PM2.5 diminue de façon similaire si les véhicules diesel, essence ou électriques récents sont favorisés. Mais favoriser les véhicules électriques induit la plus forte diminution de l'exposition au NO2. Le télétravail est moins efficace que le renouvellement des véhicules, mais il peut être utilisé pour intensifier la diminution de l'exposition aux concentrations de particules. Cependant, des réductions plus ambitieuses des émissions sont nécessaires pour respecter les directives de qualité de l'air sur Paris (10.70675/d9d7ec7bz2d39z46eaz92d3zbfb3a18fb06d)
  DOI : 10.70675/d9d7ec7bz2d39z46eaz92d3zbfb3a18fb06d
• Application of universal multifractal framework in estimating a new scale invariant power law relation between kinetic energy and intensity of rainfall
  
  • Jose Jerry
  • Gires Auguste
  • Schertzer Daniel
  • Roustan Yelva
  • Ruas Anne
  • Tchiguirinskaia Ioulia
  , 2021. Application of universal multifractal framework in estimating a new scale invariant power law relation between kinetic energy and intensity of rainfall
• Automatic generation from MCM of reduced mechanisms to study the formation and evolution of SOA in 3D air quality models
  
  • Wang Zhizhao
  • Couvidat Florian
  • Sartelet Karine
  , 2021, pp.EGU21-1390. As secondary organic aerosols (SOA) largely contribute to the mass of particles and may strongly affect health, it is essential to represent them as accurately as possible in air quality models (AQM). Their formation and aging involve multi-generation oxidations of numerous volatile organic compounds (VOC) combined with gas-particle partitioning processes. Tracking the non-linear relationship between VOC emissions and aerosol formation demands comprehensive chemical mechanisms, which take into account the whole complexity of the SOA precursor oxidation to simulate aerosols under various conditions. However, the use of explicit gas-phase chemical mechanism (e.g., MCM, GECKO-A) or molecular structure-limited parameterization (e.g., VBS, SOM, FGOM) could be problematical in large-scale SOA modeling, as the former is overwhelmingly computational expensive while the latter loses tracks of VOC oxidation products after few generations and specific properties relying on aerosol formation. Consequently, we have developed semi-explicit SOA chemical mechanisms designed to model the SOA formation and evolution in 3D AQM. These mechanisms are reduced based on simulations of the near-explicit master chemical mechanism (MCM) performed under various conditions representative of ambient conditions and different lumping strategies. The new mechanisms integrate the crucial SOA species/reactions with different mechanism complexities. The mechanisms, therefore, preserve the complexity of the oxidation chemistry (dependence on NOx of the SOA formation, the influence of radical concentrations, humidity, photolysis, etc..) as well as the molecular composition of the organic aerosol. The mechanisms are implemented in a novel 0D aerosol model SSH-aerosol, which can use the molecular structure of lumped compounds to estimate the influence of non-ideality on SOA formation. The current application has been conducted on the MCM degradation scheme of beta-caryophyllene (C<sub>15</sub>H<sub>24</sub>), the most representative sesquiterpene. A reduction of the average 90% CPU time and up to 92% number of S/IVOCs species has been achieved compared to the original MCM mechanism. (10.5194/egusphere-egu21-1390)
  DOI : 10.5194/egusphere-egu21-1390
• Finite volume arbitrary Lagrangian-Eulerian schemes using dual meshes for ocean wave applications
  
  • Ferrand Martin
  • Harris Jeffrey C.
  Computers and Fluids, Elsevier, 2021, 219, pp.104860. • Finite volume three-dimensional Navier-Stokes modeling of water wave propagation • Steep wave generation and propagation with Arbitrary Lagrangian-Eulerian scheme • Use of Compatible Discrete Operators shows improved accuracy and stability Finite volume Arbitrary Lagrangian-Eulerian schemes using dual meshes for ocean wave applications. For reasons of efficiency and accuracy, water wave propagation is often simulated with potential or inviscid models rather than Navier-Stokes solvers, but for wave-induced flows, such as wave-structure interaction, viscous effects are important under certain conditions. Alternatively, general purpose Navier-Stokes (CFD) models can have limitations when applied to such free-surface problems when dealing with large amplitude waves, run-up, or propagation over long distances. Here we present an Arbitrary Lagrangian-Eulerian (ALE) algorithm with special care to the time-stepping and boundary conditions used for the free-surfaces, integrated into Code_Saturne, and we test its capabilities for modeling a variety of water wave generation and propagation benchmarks, and finally consider interaction with a vertical cylinder. Two variants of the mesh displacement computation are proposed and tested against the discrete Geometric Conservation Law (GCL). The more robust variant, for highly curved or sawtoothed free-surfaces, uses a Compatible Discrete Operator scheme on the dual mesh for solving the mesh displacement, which makes the algorithm valid for any polyhedral mesh. Results for standard wave propagation benchmarks for both variants show that, when care is taken to avoid grids with excessive numerical dissipation, this approach is effective at reproducing wave profiles as well as forces on bodies. (10.1016/j.compfluid.2021.104860)
  DOI : 10.1016/j.compfluid.2021.104860
• Inférence bayésienne et quantification d'incertitudes pour l'estimation de sources de rejets de radionucléides
  
  • Dumont Le Brazidec Joffrey
  , 2021. En cas de rejet de polluants radioactifs dans l’atmosphère, une des missions des autorités est d’évaluer les conséquences de ce rejet afin de mettre en œuvre, si nécessaire, des mesures de protection des populations. Il peut s’agir d’évacuation ou de mise à l’abri à très court terme et de restrictions de consommation ou de commercialisation des denrées alimentaires contaminées à plus long terme. Pour cela, des modèles numériques sont utilisés pour simuler la dispersion des radionucléides dans l’atmosphère.La précision des résultats obtenus à partir de ces modèles dépend fortement de la connaissance du terme source, c’est-à-dire de la localisation, de la durée, de l’ampleur du rejet ainsi que de sa distribution entre radionucléides. Or, la connaissance du terme source est généralement soumise à d’importantes incertitudes. En plus du terme source, d’autres incertitudes proviennent du modèle de transport, des champs météorologiques, des données de mesure et de la représentativité du modèle par rapport aux mesures.Dans cette thèse, nous avons développé et appliqué des méthodes de modélisation inverse permettant d’améliorer l’évaluation du terme source et de quantifier les incertitudes.Parmi les méthodes de modélisation inverse, les approches déterministes variationnelles sont efficaces pour fournir une estimation rapide du terme source, mais la quantification des incertitudes associée à cette estimation est généralement difficile.Nous proposons donc d'aborder le problème dans le cadre probabiliste de l'inférence bayésienne qui s’inscrit dans un formalisme permettant d’obtenir une évaluation plus complète des incertitudes.Plusieurs méthodes d’échantillonnage de Monte Carlo à chaîne de Markov (MCMC) sont mises en œuvre afin de reconstruire les variables décrivant la source : l’algorithme de Metropolis Hastings (MH), l’algorithme du Parallel tempering et enfin le Reversible-Jump MCMC.Ces algorithmes sont tout d’abord appliqués et validés sur l’évènement de détection de ruthénium 106 survenu en Europe à l’automne 2017. Les densités de probabilité des variables de la source sont reconstruites afin d’identifier l’origine géographique des détections ainsi que les quantités de ruthénium 106 rejetées dans l’atmosphère.Puis, dans un second temps, plusieurs méthodes sont développées afin d’incorporer et de quantifier différentes sources d’erreurs au sein du problème bayésien et ainsi permettre une meilleure reconstruction de la distribution du rejet.Le second cas d’étude est dédié à l’accident de Fukushima qui a conduit à des rejets longs associés à une cinétique variable dans le temps. La reconstruction de ces rejets aux caractéristiques plus complexes a nécessité le développement d’un nouvel algorithme MCMC, le Reversible-Jump MCMC, qui a été adapté à partir des méthodes d’échantillonnage précédentes.Appliqué au cas de Fukushima, le Reversible-Jump MCMC montre sa capacité à échantillonner plus finement et plus efficacement la distribution du terme source et des incertitudes. (10.70675/f4b6449dz245bz47a3zac56zea8b30eaea48)
  DOI : 10.70675/f4b6449dz245bz47a3zac56zea8b30eaea48
• Combining homogeneous and heterogeneous chemistry to model inorganic compound concentrations in indoor environments: the H²I model (v1.0)
  
  • Fiorentino Eve-Agnès
  • Wortham Henri
  • Sartelet Karine
  Geoscientific Model Development, European Geosciences Union, 2021, 14 (5), pp.2747 - 2780. Homogeneous reactivity has been extensively studied in recent years through outdoor air-quality simulations. However, indoor atmospheres are known to be largely influenced by another type of chemistry, which is their reactivity with surfaces. Despite progress in the understanding of heterogeneous reactions, such reactions remain barely integrated into numerical models. In this paper, a room-scale, indoor air-quality (IAQ) model is developed to represent both heterogeneous and homogeneous chemistry. Thanks to the introduction of sorbed species, deposition and surface reactivity are treated as two separate processes, and desorption reactions are incorporated. The simulated concentrations of inorganic species are compared with experimental measurements acquired in a real room, thus allowing calibration of the model's undetermined parameters. For the duration of the experiments, the influence of the simulation's initial conditions is strong. The model succeeds in simulating the four inorganic species concentrations that were measured, namely NO, NO2, HONO and O3. Each parameter is then varied to estimate its sensitivity and to identify the most prevailing processes. The air-mixing velocity and the building filtration factor are uncertain parameters that appear to have a strong influence on deposition and on the control of transport from outdoors, respectively. As expected, NO2 surface hydrolysis plays a key role in the production of secondary species. The secondary production of NO by the reaction of sorbed HONO with sorbed HNO3 stands as an essential component to integrate into IAQ models. (10.5194/gmd-14-2747-2021)
  DOI : 10.5194/gmd-14-2747-2021
• Sensitivity study to select the wet deposition scheme in an operational atmospheric transport model
  
  • Querel Arnaud
  • Quelo Denis
  • Roustan Yelva
  • Mathieu Anne
  Journal of Environmental Radioactivity, Elsevier, 2021, 237, pp.106712. The response to a nuclear crisis is supported by the ability of operational atmospheric transport models to simulate the soil contamination caused by deposition processes. The Fukushima accident was characterised by wet deposits, which were difficult to simulate accurately based on observations. This may have been due to the scheme used in the models to represent the wet deposition flux. Is this scheme actually important? Can feedback from the Fukushima accident be used to make optimal decisions? A sensitivity study was used to investigate these questions based on seven wet deposition schemes integrated into operational and recognised atmospheric transport models and considering various sets of parameters, particularly those with an influence on wet deposition. The deposition maps produced from the multiple simulations are compared – with each other and with the deposits observed from the Fukushima accident – on the basis of criteria representing soil contamination crisis management needs. This study confirms the importance of the wet deposition scheme, particularly in some configurations, and quantifies the impact of this decision in a crisis management context. None of the schemes used in the study clearly appear as the best possible option to satisfy all of the criteria. Among them we identified similarities and discrepancies in average behaviour. Ultimately, the scheme used when modelling wet deposition in an operational atmospheric transport model must be carefully selected. In addition, uncertainty is too widespread with the Fukushima accident for this case to be used as a benchmark when selecting a wet deposition scheme. This study also highlights that crisis managers must not exclusively trust one single model for responses. At the current time, it is preferable to implement and use several wet deposition schemes as part of modelling tools of emergency responses. (10.1016/j.jenvrad.2021.106712)
  DOI : 10.1016/j.jenvrad.2021.106712
• Improvement in Modeling of OH and HO2 Radical Concentrations during Toluene and Xylene Oxidation with RACM2 Using MCM/GECKO-A
  
  • Lannuque Victor
  • D’anna Barbara
  • Couvidat Florian
  • Valorso Richard
  • Sartelet Karine
  Atmosphere, MDPI, 2021, 12 (6), pp.732. Due to their major role in atmospheric chemistry and secondary pollutant formation such as ozone or secondary organic aerosols, an accurate representation of OH and HO2 (HOX) radicals in air quality models is essential. Air quality models use simplified mechanisms to represent atmospheric chemistry and interactions between HOX and organic compounds. In this work, HOX concentrations during the oxidation of toluene and xylene within the Regional Atmospheric Chemistry Mechanism (RACM2) are improved using a deterministic-near-explicit mechanism based on the Master Chemical Mechanism (MCM) and the generator of explicit chemistry and kinetics of organics in the atmosphere (GECKO-A). Flow tube toluene oxidation experiments are first simulated with RACM2 and MCM/GECKO-A. RACM2, which is a simplified mechanism, is then modified to better reproduce the HOX concentration evolution simulated by MCM/GECKO-A. In total, 12 reactions of the oxidation mechanism of toluene and xylene are updated, making OH simulated by RACM2 up to 70% more comparable to the comprehensive MCM/GECKO-A model for chamber oxidation simulations. (10.3390/atmos12060732)
  DOI : 10.3390/atmos12060732