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Updated: Apr 15, 2026

Clean Sampling and Analysis of River and Estuarine Waters for Trace Metal Studies
Published on: July 1, 2016
Representativeness of laboratory sampling procedures for the analysis of trace metals in soil
Jean-Sébastien Dubé1, Jean-Philippe Boudreault, Régis Bost
1Département de génie de la construction, École de technologie supérieure, 1100 Notre-Dame ouest, Montréal, QC, H3C 1K3, Canada, jean-sebastien.dube@etsmtl.ca.
Abstract:
This study was conducted to assess the representativeness of laboratory sampling protocols for purposes of trace metal analysis in soil. Five laboratory protocols were compared, including conventional grab sampling, to assess the influence of sectorial splitting, sieving, and grinding on measured trace metal concentrations and their variability. It was concluded that grinding was the most important factor in controlling the variability of trace metal concentrations. Grinding increased the reproducibility of sample mass reduction by rotary sectorial splitting by up to two orders of magnitude. Combined with rotary sectorial splitting, grinding increased the reproducibility of trace metal concentrations by almost three orders of magnitude compared to grab sampling. Moreover, results showed that if grinding is used as part of a mass reduction protocol by sectorial splitting, the effect of sieving on reproducibility became insignificant. Gy's sampling theory and practice was also used to analyze the aforementioned sampling protocols. While the theoretical relative variances calculated for each sampling protocol qualitatively agreed with the experimental variances, their quantitative agreement was very poor. It was assumed that the parameters used in the calculation of theoretical sampling variances may not correctly estimate the constitutional heterogeneity of soils or soil-like materials. Finally, the results have highlighted the pitfalls of grab sampling, namely, the fact that it does not exert control over incorrect sampling errors and that it is strongly affected by distribution heterogeneity.
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