A Critical Review of Discrete Soil Sample Data Reliability: Part 1—Field Study Results
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Part 1 of this study summarizes data for a field investigation of contaminant concentration variability within individual, discrete soil samples (intra-sample variability) and between closely spaced, “co-located” samples (inter-sample variability). Hundreds of discrete samples were collected from three sites known respectively to be contaminated with arsenic, lead, and polychlorinated biphenyls. Intra-sample variability was assessed by testing soil from ten points within a minimally disturbed sample collected at each of 24 grid points. Inter-sample variability was assessed by testing five co-located samples collected within a 0.5-m diameter of each grid point. Multi Increment soil samples (triplicates) were collected at each study site for comparison. The study data demonstrate that the concentration of a contaminant reported for a given discrete soil sample is largely random within a relatively narrow (max:min <2X) to a very wide (max:min >100X) range of possibilities at any given sample collection point. The magnitude of variability depends in part on the contaminant type and the nature of the release. The study highlights the unavoidable randomness of contaminant concentrations reported in discrete soil samples and the unavoidable error and inefficiency associated with the use of discrete soil sample data for decision making in environmental investigations.