Carlon Claudio, Pizzol Lisa, Critto Andrea, Marcomini Antonio
Consorzio Venezia Ricerche, Via della Libertà 5-12, I-30175 Marghera, Venice, Italy.
Environ Int. 2008 Apr;34(3):397-411. doi: 10.1016/j.envint.2007.09.009. Epub 2007 Nov 26.
When soil and groundwater contaminations occur over large areas, remediation measures should be spatially prioritized on the basis of the risk posed to human health and in compliance with technological and budget constraints. Within this scope, the application of human health risk assessment algorithms in a spatially resolved environment raises a number of methodological and technical complexities. In this paper, a methodology is proposed and applied in a case study to support the entire formulation process of remediation plans, encompassing hazard assessment, exposure assessment, risk characterisation, uncertainty assessment and allocation of risk reduction measures. In the hazard assessment, it supports the selection of Contaminants of Concern (CoC) with regard to both their average concentrations and peak concentrations, i.e. hot spots. In the exposure assessment, it provides a zoning of the site based on the geostatistical mapping of contaminant. In the risk characterisation, it generates vector maps of Risk Factors on the basis of the risk posed by multiple substances and allows the interrogation of most relevant CoC and exposure pathways for each zone of the site. It also supports the Monte Carlo based probabilistic estimation of the Risk Factors and generates maps of the associated uncertainty. In the risk reduction phase, it supports the formulation of remediation plans based on the stepwise spatial allocation of remediation interventions and the on-time simulation of risk reduction performances. The application of this methodology is fully supported by an easy-to-use and customized Geographical Information System and does not require high expertise for interpretation. The proposed methodology is the core module of a Decision Support System (DSS) that was implemented in the DESYRE software aimed at supporting the risk-based remediation of megasites.
当大面积出现土壤和地下水污染时，应根据对人类健康构成的风险，并在符合技术和预算限制的前提下，对修复措施进行空间优先排序。在此范围内，在空间解析环境中应用人类健康风险评估算法会带来一些方法和技术上的复杂性。本文提出了一种方法，并将其应用于一个案例研究中，以支持修复计划的整个制定过程，包括危害评估、暴露评估、风险表征、不确定性评估以及风险降低措施的分配。在危害评估中，它支持根据关注污染物（CoC）的平均浓度和峰值浓度（即热点）来进行选择。在暴露评估中，它基于污染物的地质统计映射对场地进行分区。在风险表征中，它根据多种物质造成的风险生成风险因素矢量图，并允许查询场地每个区域最相关的CoC和暴露途径。它还支持基于蒙特卡洛法的风险因素概率估计，并生成相关不确定性的地图。在风险降低阶段，它支持基于修复干预措施的逐步空间分配和风险降低性能的实时模拟来制定修复计划。这种方法的应用得到了一个易于使用且可定制的地理信息系统的充分支持，并且不需要很高的专业知识来进行解释。所提出的方法是决策支持系统（DSS）的核心模块，该系统已在DESYRE软件中实现，旨在支持大型场地基于风险的修复。
