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
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