Optimal Resource Allocation for the Cleanup of Petroleum Contaminated Sites

by Owete S. Owete, P.E., Ph.D.,
Amy B. Chan Hilton, Ph.D.,



Document Type: Proceeding Paper

Part of: World Environmental and Water Resources Congress 2007: Restoring Our Natural Habitat

Abstract: Site rehabilitation is conducted in many states using a risk-based corrective action process wherein alternative remedial actions are evaluated and implemented, depending on the level of contamination, current and future site use, and other site conditions. There are sequences of activities that must be completed at each site to reach closure, and all the sites undergoing cleanup compete for the limited cleanup program fund. Most states set forth guidelines for conducting site assessments at petroleum contaminated sites, risk assessments, and remedial actions, as well as specific target cleanup levels. However, the funds required for the remediation of petroleum-contaminated sites typically exceed the available budget for a given year. Thus, only a limited number of sites can be brought to closure at a given time. In this work, a resource allocation optimization model is developed to improve the distribution of funds for addressing petroleum-contaminated sites. A set of administrative and technical constraints are formulated in this model. The goal is to determine the optimal combination of sites to be funded for a specified time horizon that satisfies a given budget. The goal of this resource allocation tool is to help answer the following questions. How may the model help decide which sites to initiate cleanup activities, when there are simple and complex sites, and when many states have established administrative procedures and priority ranking for selecting sites? How does the model accommodate the number of sites awaiting cleanup, which are in the thousands? Does the model reduce cleanup costs and how does it meet cleanup objectives?

Subject Headings: Site investigation | Remediation | Pollution | Resource management | Optimization models | Risk management | Petroleum

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