A New Traceability Method for Sudden Water Pollution Accidents

Hai Dong Yang; Dong Guo Shao; Bi Yu Liu

doi:10.4028/www.scientific.net/AMR.807-809.1570

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Oxalic Acid Enhances Remediation of Cr Contaminated Soil in Leersia Hexandra Swartz
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Influence of Alkalinity on Partial Nitrification Treating Domestic Sewage and the Microbial Community in MBR
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Remediation of Perchloroethylene Contaminated Groundwater by Zero-Valent Iron Integrated with Anaerobic Microbial Community
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Low-Temperature Catalytic Clearing of Gases of Thermal Power Station from Harmful Impurity in the Presence of the Cobalt Complexes Fixed on a Polymeric Matrix
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Characteristics of Suspended Sediment and Resuspension Process in Wendeng Coastal Area, Shandong Peninsula
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 807-809A New Traceability Method for Sudden Water...

A New Traceability Method for Sudden Water Pollution Accidents

Abstract:

Pollution point source identification for the non-shore emission which is the main form of sudden water pollution incident is considered in this paper. Firstly, the source traceability of sudden water pollution accidents is taken as the Bayesian estimation problem; secondly, the posterior probability distribution of the source's parameters are deduced; thirdly, the marginal posterior probability density is obtained by using a new traceability method; finally, this proposed method is compared with Bayesian-MCMC by numerical experiments. The conclusions are as following: the new traceability method can reduce the iterations, improve the recognition accuracy, and reduce the overall average error obviously and it is more stable and robust than Bayesian-MCMC and can identify sudden water pollution accidents source effectively. Therefore, it provides a new idea and method to solve the difficulty of traceability problems in sudden water pollution accidents.

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Periodical:

Advanced Materials Research (Volumes 807-809)

Pages:

1570-1574

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.807-809.1570

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Online since:

September 2013

Authors:

Hai Dong Yang, Dong Guo Shao, Bi Yu Liu

Keywords:

Bayesian, Differential Evolution, Monte Carlo, Sudden Water Pollution, Traceability

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