Author(s)

J. R. Rocco, L. H. Wilson & R. B. Gilbert

Abstract

Successful decision-making for the reuse and redevelopment of a brownfields property must incorporate complex social, economic, and environmental issues to achieve the critical outcomes of brownfields redevelopment - the environmental cleanup and beneficial reuse of the property. The decision making process must be open to and representative of the diverse concerns and issues of the many stakeholders that are impacted or may be impacted by a brownfields property. It must be well defined, agreed to by the stakeholders, and applied in a consistent manner. Further, the decision making process must ensure that information and data are effectively managed, appropriately linked to models and the decision making process, and effectively communicated to diverse audiences. This paper presents a framework for effectively implementing the complex decision-making process necessary to address the reuse of a brownfields property based on clearly defined decision attributes, risk profile values and endpoint utilities. A major component of this framework is the use of a GIS application linked with tabular databases and models for analysis of environmental and other pertinent data, risk assessment, reuse planning, decision analysis for evaluating environmental and reuse alternatives, and visualization of results. These applications not only provide an excellent visualization mechanism, but also when linked with environmental and other information databases, provide an engine for calculating environmental and economic risks, evaluating uncertainty, and evaluating reuse alternatives. Introduction A brownfields property by definition is an abandoned, idled or under-used industrial or commercial property where expansion or reuse is complicated by a real or perceived environmental condition [1]. However, the environmental condition is not the only impediment to the reuse of most brownfields properties, Reuse for many properties considered to be brownfields, possibly the largest

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