Sequential Monte Carlo in Bayesian Assessment of Contaminant Source Localization Based on the Sensors Concentration Measurements

Accidental atmospheric releases of hazardous material pose great risks to human health and the environment. In this context it is valuable to develop the emergency action support system, which can quickly identify probable location and characteristics of the release source based on the measurement of dangerous substance concentration by the sensors network. In this context Bayesian approach occurs as a powerful tool being able to combine observed data along with prior knowledge to gain a current understanding of unknown model parameters.