Data Representativeness for Risk Assessment

Abstract

Soil data collected to support a baseline human health or ecological risk assessment should be representative of the exposures likely to be encountered at the site. Representative data are produced when sampling plans consider the receptors, exposure areas, exposure media, exposure pathways, and habitat at the site. The number of soil samples required in each exposure area depends on the expected variability in sample concentrations and on providing adequate areal and depth coverage. Sampling designs that are probability based, such as simple random or grid sampling, provide the best data for risk assessment because they are unbiased, provide a reliable estimate of variability, and allow statistical inferences to be made from the data set of collected samples. The use of composite samples can reduce the total number of analyses needed to estimate the mean concentration. However, the main drawback to composites is that information about the variability in sample concentrations is lost, thus limiting their usefulness for estimating the 95% upper confidence limit (UCL) on the mean concentration, which is often the exposure point concentration used in risk assessment.