Environmental Review: A Comprehensive Review of Existing Classification Systems of Brownfield Sites

Abstract

The state of brownfield remediation and rehabilitation approaches continues to advance significantly, particularly with respect to the types of brownfield technologies available for assessing and treating contaminants. However, largely absent is a structured means for integrating the objectives of multiple stakeholders (e.g., municipality, developer, regulator, community) comprehensively by using a classification method that can differentiate among the brownfields based on an overall suite of relevant characteristics—such as community issues, site characteristics, development potential, and financial viability—and analyze them categorically. Existing brownfield scoring schemes, ranking methods, and identification approaches that were developed in the past by various organizations can be used as classification mechanisms, but many of these systems are designed for a specific group of stakeholders or jurisdictions and cannot be used to evaluate situations outside their intended original use. Nevertheless, they provide useful starting points to consider what the desirable elements are within a comprehensive classification system. This article reviews 12 contemporary brownfield classification systems and analyzes their strengths and weaknesses. It concludes that the lack of a multidisciplinary approach in the development of the existing classification systems limits their use on a broader scale. Lastly, the article establishes the need for a broader multidisciplinary classification system that can serve as a basic framework for systematic decision making regarding brownfields.

Acknowledgments

The authors sincerely acknowledge the helpful and practical advice of Peter Beukema and Patrick Shriner from AMEC Earth & Environmental, Marcia Wallace from the Province of Ontario, and Mark Brickell from Niagara Economic Development Corporation; and the support from the Ontario Centers of Excellence. The authors also thank Nik Schruder and Philip Byer, University of Toronto, for their input.