Constitutional and distributional heterogeneity of contaminated soil and its influence on sampling uncertainty

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In environmental site assessment (ESA), sample representativeness is required by a vast majority of guidelines on contaminated soil sampling. However, it is never given a proper description or quantitative definition because of a general lack of knowledge of the Theory of Sampling (ToS). During our previous Discovery Grant, we measured the representativeness of several sampling techniques. We developed sampling strategies based on ToS principles, which improve sampling representativeness by several orders of magnitude. We extended the model of sampling variance (MoSV) provided by ToS to soil containing contaminant-coated particles, thereby enabling the quantitative design of laboratory sampling protocols for contaminated soil, something which could only be performed qualitatively thus far. The proposed research program for 2019-2023 pursues this work by focusing on the following issues. First, the heterogeneity of soil contaminated by liquid-phase contaminants (e.g. petroleum hydrocarbons, halogenated solvents) is not explicitly represented by our extended MoSV. Second, field sampling remains a difficult problem to solve, while being the crucial first step in the sampling process. Third, soil moisture clearly affects particle distribution in a lot of particulate matter, but it still cannot be explicitly considered in sampling protocol design. We will first generalize our MoSV to the heterogeneity carried by liquid-phase contaminants and validating it with sampling experiments performed on model soils. We will also study the segregation mechanisms occurring in longitudinal pile formation at the field sampling stage by reproducing it with model soils in the laboratory. We will notably study the effects of segregation on heterogeneity, sampling reproducibility and protocol design. Segregation will be observed using µCT-scan imaging and also studied using Discrete Element Modeling (DEM). The degree of segregation (DS) will be quantified using image analysis or from DEM with available indices (e.g. Lacey's or coordination number index). The influence of soil moisture on segregation and sampling uncertainty will be characterized and modeled. Piles of model soils will be sampled and sampling variability will be correlated to DS. The originality of this research program lies in the development of a generalized MoSV for soil contaminated by solid-phase and liquid-phase contaminants. It will also provide new knowledge on the dynamics of segregation in lots of particulate matter. by using cutting-edge technology, namely µCT-scan imagery and DEM. It will improve our previous ToS framework for designing sampling processes and analysing the representativeness of sampling methods in the field of ESA. This will increase the representativeness and cost effectiveness of ESA and remediation In an international market of US$50 billions annually, these outcomes will also be significant for the industry.