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Risk Management of BTEX Contamination in Ground Water—An Integrated Fuzzy Approach

Authors

  • X. S. Qin,

    1. Faculty of Engineering, University of Regina, Regina, Saskatchewan, Canada S4S 0A2.
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  • G. H. Huang,

    Corresponding author
    1. Faculty of Engineering, University of Regina, Regina, Saskatchewan, Canada S4S 0A2.
    2. Chinese Research Academy of Environmental Science, North China Electric Power University, Beijing, China 100012-102206.
      Center for Studies in Energy and Environment, University of Regina, Regina, Saskatchewan, Canada S4S 0A2; (306) 585-4095; fax: (306) 585-4855; huangg@uregina.ca
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  • Y. P. Li

    1. College of Urban and Environmental Sciences, Peking University, Beijing, China 100871.
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Center for Studies in Energy and Environment, University of Regina, Regina, Saskatchewan, Canada S4S 0A2; (306) 585-4095; fax: (306) 585-4855; huangg@uregina.ca

Abstract

An integrated fuzzy simulation-assessment method (FSAM) was developed for assessing environmental risks from petroleum hydrocarbon contamination in ground water. In the FSAM, techniques of fuzzy simulation and fuzzy risk assessment were coupled into a general framework to reflect a variety of system uncertainties. A petroleum-contaminated site located in western Canada was selected as a study case for demonstrating applicability of the proposed method. The risk assessment results demonstrated that system uncertainties would significantly impact expressions of risk-level outputs. A relatively deterministic expression of the risks would have clearer representations of the study problem but may miss valuable uncertain information; conversely, an assessment under vaguer system conditions would help reveal potential consequences of adverse effects but would suffer from a higher degree of fuzziness in presenting the modeling outputs. Based on the risk assessment results, a decision analysis procedure was used to calculate a general risk index (GRI) to help identify proper responsive actions. The proposed method was useful for evaluating risks within a system containing multiple factors with complicated uncertainties and interactions and providing support for identifying proper site management strategies.

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