The principal use of this standard is in assessment, compliance and corrective action environmental monitoring programs (for example, for any facility that could potentially contaminate ground water). The significance of the guidance is that it presents a statistical method that allows comparison of ground-water data to regulatory and/or health based limits.
Of course, there is considerable USEPA support for statistical methods applied to detection, assessment and corrective action monitoring programs that can be applied to environmental investigations. For example, the 90 % upper confidence limit (UCL) of the mean is used in SW846 (Chapter 9) for determining if a waste is hazardous. If the UCL is less than the criterion for a particular hazardous waste code, then the waste is not a hazardous waste even if certain individual measurements exceed the criterion. Similarly, in the USEPA Statistical Analysis of Groundwater Monitoring Data at RCRA Facilities Addendum to the Interim Final Guidance (1992)
There are several reasons why statistical methods are essential in assessment and corrective action monitoring programs. First, a single measurement indicates very little about the true concentration in the sampling location of interest, and with only one sample there is no way of knowing if the measured concentration is a typical or an extreme value. The objective is to compare the true concentration (or some interval that contains it) to the relevant criterion or standard. Second, in many cases the constituents of interest are naturally occurring (for example, metals) and the naturally existing concentrations may exceed the relevant criteria. In this case, the relevant comparison is to background (for example, off-site soil or upgradient ground water) and not to a fixed criterion. As such, background data must be statistically characterized to obtain a statistical estimate of an upper bound for the naturally occurring concentrations so that it can be confidently determined if onsite concentrations are above background levels. Third, there is often a need to compare numerous potential constituents of concern to criteria or background, at numerous sampling locations. By chance alone there will be exceedances as the number of comparisons becomes large. The statistical approach to this problem can insure that false positive results are minimized.
Statistical methods for detection monitoring have been well studied in recent years (see Gibbons, 1994a, 1996, USEPA 1992
The guide is summarized in Fig. 1, which provides a f......