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Statistical Approach to Meeting Soil Cleanup Goals

机译:实现土壤清理目标的统计方法

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摘要

The establishment of health-protective soil remediation levels often relies on the results of a risk assessment, which provides a way to equate a permissible risk to a target soil contaminant concentration. Inherent in such risk assessments is the assumption that the target concentrations are representative averages. Unfortunately, soil cleanup levels thus calculated are typically misapplied on a point by point basis rather than on an average. This is not cost-effective because it results in post-remedy conditions that overshootthe target risk goals. Because environmental contamination is characterized by a distribution of concentrations, some exceedances of target averages, average risk, or average concentration can be allowed in the post-remediation distribution. This work presents a mathematical model for calculating this allowable higher than average concentration, termed the confidence response goal (CRG), which places a limit on concentrations requiring remediation while ensuring thattarget average concentrations are satisfied overall. The CRG is site-specific becauses it depends on the contaminant concentration distribution. The strength of the approach lies in its ability to handle typical data uncertainties quantitatively because it relies on the upper confidence limit as a measure of the mean concentration (in a manner similar to its use in risk assessment), hence the term "confidence" in the CRG. The advantages of the approach are significant. An example is given of a Superfund site where excavation volumes were reduced by 66% and $40 million was saved, about half of which could be attributed to the CRG approach.
机译:建立保护性土壤的补救措施水平通常取决于风险评估的结果,该评估提供了一种将允许的风险等同于目标土壤污染物浓度的方法。此类风险评估的固有假设是目标浓度为代表性平均值。不幸的是,这样计算出的土壤净化水平通常是逐点而不是平均地错误应用。这不具有成本效益,因为它会导致补救后状况超出目标风险目标。由于环境污染的特征在于浓度分布,因此在修复后的分布中可以允许超过目标平均值,平均风险或平均浓度。这项工作提出了一个数学模型,用于计算该允许的高于平均浓度的水平,称为置信响应目标(CRG),该模型对需要补救的浓度设置了限制,同时确保总体上满足目标平均浓度。 CRG是特定于站点的,因为它取决于污染物的浓度分布。该方法的优势在于其能够定量处理典型数据不确定性的能力,因为该方法依赖于置信度上限作为平均浓度的度量​​(以类似于风险评估中使用的方式),因此,术语“置信度” CRG。该方法的优点很明显。以一个超级基金站点为例,该站点的开挖量减少了66%,节省了4000万美元,其中大约一半可归功于CRG方法。

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