This paper presents three approaches to find optimized grids for atmospheric dispersion measurements and calculations in emergency planning. This can be useful for deriving optimal positions for mobile monitoring stations, or help to reduce discretization errors and improve recommendations. Indeed, threshold-based recommendations or conclusions may differ strongly on the shape and size of the grid on which atmospheric dispersion measurements or calculations of pollutants are based. Therefore, relatively sparse grids that retain as much information as possible, are required. The grid optimization procedure proposed here is first demonstrated with a simple Gaussian plume model as adopted in atmospheric dispersion calculations, which provides ...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
This paper investigates the solution of a 3D atmospheric dispersion problem using a time-dependent a...
This article addresses the challenge of searching for the optimal location for a newly designed poll...
In the event of the release of a radiological pollutant into the atmosphere, a fast and accurate est...
Air quality is far from being a new concern but remains an issue demanding increasing attention. The...
In case of a nuclear accident, decision makers rely on high-resolution and accurate information abou...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
This paper presents the SILAM dispersion modelling system that has been developed for solving variou...
This paper presents the SILAM dispersion modelling system that has been developed for solving variou...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
Steady-state Gaussian binomial equations are widely used for predicting the dispersion and ground-le...
Steady-state Gaussian binomial equations are widely used for predicting the dispersion and ground-le...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
This paper investigates the solution of a 3D atmospheric dispersion problem using a time-dependent a...
This article addresses the challenge of searching for the optimal location for a newly designed poll...
In the event of the release of a radiological pollutant into the atmosphere, a fast and accurate est...
Air quality is far from being a new concern but remains an issue demanding increasing attention. The...
In case of a nuclear accident, decision makers rely on high-resolution and accurate information abou...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
This paper presents the SILAM dispersion modelling system that has been developed for solving variou...
This paper presents the SILAM dispersion modelling system that has been developed for solving variou...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
Steady-state Gaussian binomial equations are widely used for predicting the dispersion and ground-le...
Steady-state Gaussian binomial equations are widely used for predicting the dispersion and ground-le...
International audienceAbstract. Numerical atmospheric dispersion models (ADMs) are used for predicti...
This paper investigates the solution of a 3D atmospheric dispersion problem using a time-dependent a...
This article addresses the challenge of searching for the optimal location for a newly designed poll...