Sequential Monte Carlo in Bayesian Assessment of Contaminant Source Localization Based on the Sensors Concentration Meas
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
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´ National Centre for Nuclear Research, Swierk-Otwock, Poland [email protected] 2 Institute of Computer Science, Siedlce University, Siedlce, Poland Poland Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland
Abstract. 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. We have applied the methodology combining Bayesian inference with Sequential Monte Carlo (SMC) to the problem of the atmospheric contaminant source localization. The algorithm input data are the on-line arriving concentrations of given substance registered by the distributed sensor’s network. We have proposed the different version of the Hybrid SMC along with Markov Chain Monte Carlo (MCMC) algorithms and examined its effectiveness to estimate the probabilistic distributions of atmospheric release parameters. The proposed algorithms scan 5-dimensional parameters’ space searching for the contaminant source coordinates, release strength and atmospheric transport dispersion coefficients.
Keywords: Bayesian inference methods · SMC methods
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Stochastic reconstruction
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MCMC
Introduction
Environmental sensors have been deployed in various cities for early detection of contaminant releases into the atmosphere. Accidental atmospheric releases of hazardous material pose great risk to human health and the environment. During the event of an atmospheric release of chemical, radioactive or biological materials, emergency responders need to, as soon as possible, determine the location of source of dispersed substance. Such information help responders to make timecritical decisions regarding precautions for peoples safety, plans for evacuation R. Wyrzykowski et al. (Eds.): PPAM 2013, Part II, LNCS 8385, pp. 407–417, 2014. c Springer-Verlag Berlin Heidelberg 2014 DOI: 10.1007/978-3-642-55195-6 38,
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and management of emergency services. In this context it is valuable to develop the emergency system which based on measurements of the concentration of dangerous substance by the network of sensors can inform about probable location of the release source. Moreover, the contamination source’s location should be found as soon as possible. It is clear that knowing gas source and wind field we can calculate the expected gas concentration for any downwind location. On the other hand, given concentration measurements and knowledge of the wind field and other atmospheric air parameters, finding the location of the source and its parameters is ambiguous. The problem has no unique solution and can be considered only in the probab
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