Li Jianbing, Huang Gordon H, Zeng Guangming, Maqsood Imran, Huang Yuefei
Environmental Engineering Program, University of Northern British Columbia, Prince George, British Columbia, Canada V2N 4Z9.
J Environ Manage. 2007 Jan;82(2):173-88. doi: 10.1016/j.jenvman.2005.12.018. Epub 2006 Mar 30.
An integrated fuzzy-stochastic risk assessment (IFSRA) approach was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with site conditions, environmental guidelines, and health impact criteria. The contaminant concentrations in groundwater predicted from a numerical model were associated with probabilistic uncertainties due to the randomness in modeling input parameters, while the consequences of contaminant concentrations violating relevant environmental quality guidelines and health evaluation criteria were linked with fuzzy uncertainties. The contaminant of interest in this study was xylene. The environmental quality guideline was divided into three different strictness categories: "loose", "medium" and "strict". The environmental-guideline-based risk (ER) and health risk (HR) due to xylene ingestion were systematically examined to obtain the general risk levels through a fuzzy rule base. The ER and HR risk levels were divided into five categories of "low", "low-to-medium", "medium", "medium-to-high" and "high", respectively. The general risk levels included six categories ranging from "low" to "very high". The fuzzy membership functions of the related fuzzy events and the fuzzy rule base were established based on a questionnaire survey. Thus the IFSRA integrated fuzzy logic, expert involvement, and stochastic simulation within a general framework. The robustness of the modeling processes was enhanced through the effective reflection of the two types of uncertainties as compared with the conventional risk assessment approaches. The developed IFSRA was applied to a petroleum-contaminated groundwater system in western Canada. Three scenarios with different environmental quality guidelines were analyzed, and reasonable results were obtained. The risk assessment approach developed in this study offers a unique tool for systematically quantifying various uncertainties in contaminated site management, and it also provides more realistic support for remediation-related decisions.
本研究开发了一种综合模糊 - 随机风险评估（IFSRA）方法，以系统地量化与场地条件、环境准则和健康影响标准相关的概率性和模糊性不确定性。数值模型预测的地下水中污染物浓度由于建模输入参数的随机性而具有概率性不确定性，而污染物浓度违反相关环境质量准则和健康评估标准的后果则与模糊性不确定性相关。本研究关注的污染物是二甲苯。环境质量准则分为三种不同的严格程度类别：“宽松”、“中等”和“严格”。通过模糊规则库系统地研究了因摄入二甲苯而产生的基于环境准则的风险（ER）和健康风险（HR），以获得总体风险水平。ER和HR风险水平分别分为“低”、“低到中等”、“中等”、“中等至高”和“高”五类。总体风险水平包括从“低”到“非常高”的六个类别。基于问卷调查建立了相关模糊事件的模糊隶属函数和模糊规则库。因此，IFSRA在一个通用框架内集成了模糊逻辑、专家参与和随机模拟。与传统风险评估方法相比，通过有效反映两种类型的不确定性，增强了建模过程的稳健性。所开发的IFSRA应用于加拿大西部一个受石油污染的地下水系统。分析了三种具有不同环境质量准则的情景，并获得了合理的结果。本研究开发的风险评估方法为系统量化污染场地管理中的各种不确定性提供了一个独特的工具，也为与修复相关的决策提供了更现实的支持。
