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International audience; Volcanic SO2 degassing is a crucial indicator of the sub-surface volcanic activity, which is widelyused today for volcano monitoring and hazard assessment purposes. Volcanic SO2 is also importantregarding atmospherical studies. More easily detectable from space, SO2 can be used as a proxy ofthe presence of ash to anticipate air traffic issues caused by explosive eruptions. Moreover, volcanicSO2 strongly impacts air quality but also climate following its conversion to radiatively-activesulphate aerosols. However, the accurate assessment of these various impacts is currently hamperedby the poor knowledge of volcanic SO2 emissions, which can substantially vary with time, in termsof flux and altitude.To fulfil this need, we propose a strategy relying on satellite observations, which consequently allowsfor monitoring the eruptive activity of any remote volcano. The method consists in assimilatingsnapshots of the SO2 load, provided every ~12 hours by IASI, in an inversion scheme that involvesthe use of a chemistry-transport model to describe the dispersion of SO2 released in the atmosphere.Applied on Eyjafjallajökull (Iceland) and Etna (Italy) eruption case-studies, this procedure allows forretrospectively reconstructing both the flux and altitude of the SO2 emissions with an hourlyresolution. We show the improvement gained in the simulations and forecasts of the location andmass load of volcanic SO2 clouds using such a detailed reconstruction of emissions.For calibration-validation purpose, we compared our satellite-derived time-series of the SO2 fluxwith ground-based observations available on Etna. This comparison indicates a good agreementduring ash-poor phases of the eruption. However, large discrepancies are observed during the ashrichparoxysmal phase as a result of enhanced plume opacity affecting ground-based ultravioletspectroscopic retrievals. Therefore, the SO2 emission rate derived from the ground is underestimatedby almost one order of magnitude. This result calls for the necessity to revisit currently availableinventories of the global budget of sulfur released by volcanoes, because they heavily rely on groundbasedobservations. It also shows that volcano observatories cannot rely solely on ground-basedspectroscopical observations for the monitoring of ash-rich explosive eruptions.Moreover, we will discuss the assimilation procedure of recently-developed IASI products whichdeliver snapshots of the volcanic SO2 cloud altitude. Such improvement renders the inversionprocedure, used for the reconstruction of the altitude of emissions, independent of the wind shearprerequisite.Eventually, building on our accurate source of precursory SO2 gas emissions, we can explore theformation and lifecycle of sulphate aerosols in volcanic plumes. Remote sensing of troposphericsulphate aerosols from moderate eruptions is not straightforward. However, we will show how acombination of chemistry-transport modelling and space-borne CALIOP lidar observations allowsfor tracking these aerosols despite their small concentration. The latest promising developments fromhigh-resolution infrared sounders will bring further constraints on sulphate aerosol load andcharacteristics in dispersed volcanic clouds.

Uncontrolled releases of pollutant in the atmosphere may be the consequence of various situations : accidents, for instance leaks or explosions in an industrial plant, or terrorist attacks such as biological bombs, especially in urban areas. In the event of such situations, authorities' objectives are various : predict the contaminated zones to apply first countermeasures such as evacuation of concerned population ; determine the source location ; assess the long-term polluted areas, for instance by deposition of persistent pollutants in the soil. To achieve these objectives, numerical models can be used to model the atmospheric dispersion of pollutants. We will first present the different processes that govern the transport of pollutants in the atmosphere, then the different numerical models that are commonly used in this context. The choice between these models mainly depends of the scale and the details one seeks to take into account.We will then present the general framework of inverse modeling for the estimation of source. Inverse modeling techniques make an objective balance between prior information and new information contained in the observation and the model. We will show the strong dependency of the source term estimation and its uncertainty towards the assumptions made on the statistics of the prior errors in the system. We propose several methods to estimate rigorously these statistics. We will apply these methods on different cases, using either synthetic or real data : first, a semi-automatic algorithm is proposed for the operational monitoring of nuclear facilities. The second and third studies concern the source term estimation of the accidental releases from the Fukushima Daiichi nuclear power plant. Concerning the localization of an unknown source of pollutant, two strategies can be considered. On one hand parametric methods use a limited number of parameters to characterize the source term to be reconstructed. To do so, strong assumptions are made on the nature of the source. The inverse problem is hence to estimate these parameters. On the other hand non-parametric methods attempt to reconstruct a full emission field. Several parametric and non-parametric methods are proposed and evaluated on real situations at a urban scale, with a CFD model taking into account buildings influence on the air flow. In these experiments, some proposed methods are able to localize the source with a mean error of some meters, depending on the simulated situations and the inverse modeling methods, 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

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., Le 11 mars 2011, le tremblement de terre du Tohoku a déclenché un tsunami qui a dévasté la côte Pacifique du Japon et engendré l'accident nucléaire de la centrale de Fukushima Daiichi. Trois des cœurs des six réacteurs ont fusionné, entraînant d'importants rejets radioactifs. Deux ans après l'accident de Fukushima, de nombreuses incertitudes demeurent et limitent encore la connaissance de l'événement. L'article présente d'abord l'approche menée dès le début de l'accident pour comprendre son déroulement. Le transport des rejets atmosphériques est simulé et les résultats sont comparés aux observations. Quatre phases principales de rejet ont été identifiées. Deux d'entre elles n'ont pas eu de conséquences importantes sur le sol japonais puisque le panache radioactif est parti vers l'océan. Une troisième phase de rejet a causé la contamination principale au nord-ouest de l'installation nucléaire. La dernière phase de rejet a contribué à la contamination des sols au sud de l'installation et, plus particulièrement, de la région de Tokyo. De nombreuses incertitudes caractérisent encore le terme source de l'accident. Une nouvelle méthode basée sur la modélisation inverse et l'utilisation des mesures de débit de dose a été développée. Les résultats très prometteurs montrent comment la démarche mise en œuvre permet d'améliorer l'estimation du terme source. L'approche développée est parfaitement adaptée à une utilisation opérationnelle et devrait contribuer à améliorer la réponse de l'Institut de Radioprotection et de Sûreté Nucléaire en cas d'accident nucléaire.

International audience; A major difficulty when inverting the source term of an atmospheric tracer dispersion problem is the estimation of the prior errors: those of the atmospheric transport model, those ascribed to the representativity of the measurements, those that are instrumental, and those attached to the prior knowledge on the variables one seeks to retrieve. In the case of an accidental release of pollutant, the reconstructed source is sensitive to these assumptions. This sensitivity makes the quality of the retrieval dependent on the methods used to model and estimate the prior errors of the inverse modeling scheme. We propose to use an estimation method for the errors' amplitude based on the maximum likelihood principle. Under semi-Gaussian assumptions, it takes into account, without approximation, the positivity assumption on the source. We apply the method to the estimation of the Fukushima Daiichi source term using activity concentrations in the air. The results are compared to an L-curve estimation technique and to Desroziers's scheme. The total reconstructed activities significantly depend on the chosen method. Because of the poor observability of the Fukushima Daiichi emissions, these methods provide lower bounds for cesium-137 and iodine-131 reconstructed activities. These lower bound estimates, 1.2 × 1016 Bq for cesium-137, with an estimated standard deviation range of 15%-20%, and 1.9 − 3.8 × 1017 Bq for iodine-131, with an estimated standard deviation range of 5%-10%, are of the same order of magnitude as those provided by the Japanese Nuclear and Industrial Safety Agency and about 5 to 10 times less than the Chernobyl atmospheric releases.

International audience; Following the eruption of the Icelandic volcano Eyjafjallajökull on the 14 April 2010, ground-based N2-Raman lidar (GBL) measurements were used to trace the temporal evolution of the ash plume from 16 to 20 April 2010 above the southwestern suburb of Paris. The nighttime overpass of the Cloud-Aerosol LIdar with Orthogonal Polarization onboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation satellite (CALIPSO/CALIOP) on 17 April 2010 was an opportunity to complement GBL observations. The plume shape retrieved from GBL has been used to assess the size range of the particles size. The lidar-derived aerosol mass concentrations (PM) have been compared with model-derived PM concentrations held in the Eulerian model Polair3D transport model, driven by a source term inferred from the SEVIRI sensor onboard Meteosat satellite. The consistency between model and ground-based wind lidar and CALIOP observations has been checked. The spatial and temporal structures of the ash plume as estimated by each instrument and by the Polair3D simulations are in agreement. The ash plume was associated with a mean aerosol optical thickness of 0.1{plus minus}0.06 and 0.055{plus minus}0.053 for GBL (355 nm) and CALIOP (532 nm), respectively. Such values correspond to ash mass concentrations of ~400{plus minus}160 and ~720{plus minus}670 µg m-3, respectively, within the ash plume, which was lower than 0.5 km in width. The relative uncertainty is ~75% and mainly due to the assessment of the specific cross-section assuming an aerosol density of 2.6 g cm-3. The simulated ash plume is smoother leading to integrated mass of the same order of magnitude (between 50 and 250 mg m-2)

This animation shows the dispersion of the caesium-137 radioactive plume from the Fukushima-Daichii power plant over Japan, the Pacific Ocean and the West coast of North America. It depicts the activity concentration of this radionuclide at ground level. The unit is Becquerel per cubic meter. It has been simulated using the 3D numerical model Polyphemus/Polair3D which accounts for several processes such as advection by the wind, turbulent diffusion, as well as dry and wet deposition. The meteorological fields that drive this transport model simulation are from the ECMWF at a resolution of 0.25°x0.25°. The source term for the emission of caesium-137 at the power plant which is used in this simulation has been estimated by inverse modelling in Winiarek et al. 2014, as a result of a collaboration between École des Ponts ParisTech and the Institute for Nuclear Radioprotection and Safety (see references below). One must be cautious in interpreting the values since this type of simulation remains impacted by high uncertainty in the source term, in the modelling of the physical process and to a lower degree by the meteorological fields.