| Abstract: | Better site characterization is critical for cheaper, faster, and more effective cleanup. This fact is especially true as cleanup decisions increasingly include site redevelopment and reuse considerations. However, established attitudes about what constitutes “data quality” create many barriers to exciting new tools capable of achieving better characterization, slowing their dissemination into the mainstream. Traditional approaches to environmental “data quality” rest on simplifying assumptions that are rarely acknowledged by the environmental community. Data quality assessments focus on the quality of the analysis, while seldom asking what impact matrix heterogeneity has had on analytical results. Assessments of data quality typically assume that chemical contaminants are distributed nearly homogeneously throughout environmental matrices and that contaminant‐matrix interactions are well behaved during analysis. Yet, these assumptions seldom hold true for real‐world matrices and contaminants at scales relevant to accurate risk assessment and efficient remedial design. For the site cleanup industry to continue technical advancement, over‐simplified paradigms must give way to next‐generation models that are built on current scientific understanding. If reuse programs such as Brownfields are to thrive, the scientific defensibility of individual projects must be maintained at the same time as characterization and cleanup costs are lowered. The U.S. Environmental Protection Agency (EPA) offers the Triad Approach as an alternative paradigm to foster highly defensible, yet extremely cost‐effective reuse decisions. © 2003 Wiley Periodicals, Inc. |
