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This study compares conventional grab sampling to incremental sampling methodology (ISM) to characterize metal contamination at a military small-arms-range. Grab sample results had large variances, positively skewed non-normal distributions, extreme outliers, and poor agreement between duplicate samples even when samples were co-located within tens of centimeters of each other. The extreme outliers strongly influenced the grab sample means for the primary contaminants lead (Pb) and antinomy (Sb). In contrast, median and mean metal concentrations were similar for the ISM samples. ISM significantly reduced measurement uncertainty of estimates of the mean, increasing data quality (e.g., for environmental risk assessments) with fewer samples (e.g., decreasing total project costs). Based on Monte Carlo resampling simulations, grab sampling resulted in highly variable means and upper confidence limits of the mean relative to ISM.

Military ranges are unlike many waste sites because the contaminants, both energetics and metals, are heterogeneously distributed in soil during explosive detonation or ballistic impact and cannot be readily characterized using conventional grab sampling. The Incremental Sampling Methodology (ISM) has been successful for characterization of energetic contamination in soils, but no published ISM processing studies for soils with small arms range metals such as Pb, Cu, Sb, and Zn exists. This study evaluated several ISM sample-processing steps: (1) field splitting to reduce the sample mass shipped to the analytical laboratory, (2) necessity of milling, and (3) processing a larger subsample mass for digestion in lieu of milling. Cone-and-quartering and rotary sectorial splitting techniques yielded poor precision and positively skewed distributions. Hence, an increase in digestion mass from 2 to 10 g was evaluated with milled and unmilled samples. Unmilled samples yielded results with the largest variability regardless of aliquot mass.