Allocating remedial costs at a superfund site using risk magnitude, geographic information systems, and Monte Carlo analysis

• Published in: Environmental forensics 2020-04, Vol.21 (2), p.223-235
• Main Authors: McGuire, Travis M., Newell, Charles J., Osorio, Ximena, Walker, Kenneth L., Keat, Andrew J.
• Format: Article
• Language: English
• Subjects: Components; Cost allocation; Cost analysis; Costs; Digital media; Environmental cleanup; Geographic information systems; Geographical information systems; Groundwater; Hazardous waste sites; Hazardous wastes; Information systems; Landfills; Litigation; Monte Carlo; Monte Carlo simulation; Pollution abatement; Pollution control; Remediation; Remote sensing; Risk; risk magnitude; Statistical methods; Superfund; Waste disposal; Waste management; Waste streams
• ISSN: 1527-5922; 1527-5930
• DOI: 10.1080/15275922.2020.1728435

A method for allocating remediation costs among a number of potentially responsible parties (PRPs) was developed as part of a highly technical, complex Superfund litigation case involving a former hazardous waste disposal site located in the southern United States. The method was devised in response to questions from the U.S. district court regarding the volume and composition of wastes disposed, the "remedy drivers" (defined by the court as wastes or chemicals that most influenced the selection of the remedy), and the relationship between these factors and the various PRPs. A key element of the method was calculation of the Risk Magnitude, which was defined as the logarithm of the maximum concentration of a chemical in groundwater divided by its cleanup standard. Risk magnitude was linked to site remediation costs based on an analysis of remediation difficulty, data from remediation performance studies, and other sources. Key components of the allocation method included: (i) identifying remedy driver chemicals (RDCs) based on risk magnitude; (ii) quantifying the spatially adjusted cumulative risk magnitude associated with each RDC using a Geographic Information System (GIS); (iii) adjusting the risk magnitude to account for remediation difficulty of each RDC; (iv) correlating RDCs with the volume of different waste streams disposed by each PRP at the site; (v) developing an estimate for the waste volume for each PRP using multiple lines of evidence inside a Monte Carlo analysis; and (vi) apportioning final cleanup costs between PRPs based on their attributable volume and cumulative Risk Magnitude. The basic methodology was applied by the district court to develop a scientifically sound opinion that allocated site remediation costs between the PRPs-a decision that was upheld by the U.S. court of appeals. Though developed for a particular site, the method is adaptable, and its fundamental components could be applied to other sites where allocating remedial costs of complex chemical mixtures in environmental media is the objective.