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

污染土壤的构成和分布异质性及其对采样不确定度的影响

• 批准号: RGPIN-2019-06227
• 负责人: Dubé, JeanSébastien
• 金额: $ 1.89万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=738784
• 关键词: Constitutional; distributional; heterogeneity; contaminated; soil

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.

在环境场地评价（ESA）中，绝大多数关于污染土壤取样的准则都要求样品具有代表性。然而，它从来没有给出一个适当的描述或定量定义，因为一般缺乏知识的抽样理论（ToS）。在我们之前的发现资助中，我们测量了几种采样技术的代表性。我们开发的抽样策略的基础上的ToS原则，提高抽样代表性的几个数量级。我们将ToS提供的采样方差模型（MoSV）扩展到含有污染物涂层颗粒的土壤，从而使污染土壤的实验室采样方案的定量设计成为可能，迄今为止，这只能定性地进行。 2019-2023年拟议的研究计划通过关注以下问题来开展这项工作。首先，液相污染物（如石油烃，卤化溶剂）污染的土壤的异质性是没有明确表示我们的扩展MoSV。第二，实地采样仍然是一个难以解决的问题，而这是采样过程中至关重要的第一步。第三，土壤湿度在很多颗粒物中明显影响颗粒分布，但在采样方案设计中仍然不能明确考虑。我们将首先概括我们的MoSV进行的液相污染物的异质性，并验证它与模型土壤上进行采样实验。我们还将通过在实验室中用模型土再现纵向桩形成过程，在现场取样阶段研究纵向桩形成过程中发生的离析机制。我们将特别研究隔离对异质性、取样重复性和方案设计的影响。将使用µ CT扫描成像观察分离，并使用离散元素建模（DEM）进行研究。分离程度（DS）将使用图像分析或从DEM与可用的指数（如莱西或配位数指数）进行量化。土壤水分对隔离和采样不确定性的影响将被描述和建模。将对模型土壤桩进行采样，并将采样变异性与DS相关联。这项研究计划的独创性在于开发一个广义的MoSV的固相和液相污染物污染的土壤。它还将提供大量颗粒物中分离动力学的新知识。通过使用尖端技术，即µ CT扫描图像和DEM。它将改进我们以前的ToS框架，用于设计ESA领域的采样过程和分析采样方法的代表性。这将提高欧空局和补救的代表性和成本效益，在每年500亿美元的国际市场上，这些成果对该行业也具有重要意义。