What are adjusted benchmarks, how are they derived, and how are they applied?
With discrete sampling, data are compared to the benchmark appropriate for the particular objective (e.g., soil samples are compared to earthworm toxicity reference value). When discrete samples are composited, concentrations of chemicals within individual samples that exceed the benchmark may be masked within the composite. Therefore, the benchmark is adjusted to indicate if chemical concentrations within any of the individual samples are likely to exceed the benchmark. To perform effectively, the adjusted benchmark must balance both the false positive and false negative error rates to fulfill the specific objective. Statisticians have derived different approaches of varying degrees of statistical complexity for adjusting the benchmark (Boswell et al. 1996, Carson 2001, Correll 2001, US EPA 1991, 1992) and for selecting discrete samples for separate analysis when composites exceed adjusted benchmarks (Patil and Taillie 2001). Each approach has assumptions that markedly influence the a
