dc.contributor.authorQin, Xiaosheng
dc.identifier.citationQin, X. S. (2012). Assessing environmental risks through fuzzy parameterized probabilistic analysis. Stochastic Environmental Research and Risk Assessment, 26(1), 43-58.en_US
dc.description.abstractA fuzzy parameterized probabilistic analysis (FPPA) method was developed in this study to assess risks associated with environmental pollution-control problems. FPPA integrated environmental transport modeling, fuzzy transformation, probabilistic risk assessment, fuzzy risk quantification into a general risk assessment framework, and was capable of handling uncertainties expressed as fuzzy-parameterized stochastic distributions. The proposed method was applied to two environmental pollution problems, with one being about the point-source pollution in a river system with uncertain water quality parameters and the other being concerned with groundwater contaminant plume from waste landfill site with poorly known contaminant physical properties. The study results indicated that the complex uncertain features had significant impacts on modeling and risk-assessment outputs; the degree of impacts of modeling parameters were highly dependent on the level of imprecision of these parameters. The results also implied that FPPA was capable of addressing vagueness or imprecision associated with probabilistic risk evaluation, and help generate risk outputs that could be elucidated under different possibilistic levels. The proposed method could be used by environmental managers to evaluate trade-offs involving risks and costs, as well as identify management solutions that sufficiently hedge against dual uncertainties.en_US
dc.relation.ispartofseriesStochastic environmental research and risk assessmenten_US
dc.rights© 2011 Springer-Verlag.en_US
dc.subjectDRNTU::Engineering::Environmental engineering
dc.titleAssessing environmental risks through fuzzy parameterized probabilistic analysisen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Civil and Environmental Engineeringen_US

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