Estimating risk assessment exposure point concentrations when the data are not normal or lognormal.

The U.S. Environmental Protection Agency (EPA) recommends the use of the one-sided 95% upper confidence limit of the arithmetic mean based on either a normal or lognormal distribution for the contaminant (or exposure point) concentration term in the Superfund risk assessment process. When the data are not normal or lognormal this recommended approach may overestimate the exposure point concentration (EPC) and may lead to unecessary cleanup at a hazardous waste site. The EPA concentration term only seems to perform like alternative EPC methods when the data are well fit by a lognormal distribution. Several alternative methods for calculating the EPC are investigated and compared using soil data collected from three hazardous waste sites in Montana, Utah, and Colorado. For data sets that are well fit by a lognormal distribution, values for the Chebychev inequality or the EPA concentration term may be appropriate EPCs. For data sets where the soil concentration data are well fit by gamma distributions, Wong's method may be used for calculating EPCs. The studentized bootstrap-t and Hall's bootstrap-t transformation are recommended for EPC calculation when all distribution fits are poor. If a data set is well fit by a distribution, parametric bootstrap may provide a suitable EPC.