Jean-Sébastien Dubé

An Evaluation of Fresh Water Sediments Contamination: The Lachine Canal Sediments Case, Montréal, Canade. Part II: Heavy Metal Particulate Speciation Study

Over the last century, discharge of industrial effluents and municipal wastewater have contaminated the Lachine Canal sediments. This study investigated the associations between heavy metals and natural sediment constituents. X-ray Diffraction, Transmission Electron Microscopy and geochemical analysis revealed that the sediments consisted mainly of silt and clay size fractions composed of: feldspar, illite, kaolinite, chlorite, calcite and dolomite as well as minor amounts of Fe minerals. Organic matter and amorphous metal oxides were also identified. Each of these constituents bound heavy metals at varying degrees as assessed by a sequential chemical extraction (SCE) protocol. The associations with each geochemical phase were (in order of decreasing significance): 1) residual phase, 2) oxide phase, 3) carbonate phase, 4) organic phase and 5) exchangeable phase. According to the cation exchange capacity (CEC), carbonate and oxide content measurements, the heavy metals occupied a minor fraction of the total capacity of the sediments to retain metals by these mechanisms. The SCE results revealed that the partition patterns varied with pH. The phases associated to the carbonate and the exchangeable phases were the most sensitive to a change in pH with the residual phase being almost unchanged. The Zn and Cd were sensitive to release when the conditions drifted to acidic conditions. The partition patterns for various grain size fractions (<53 µm, 53–75 µm, 75–175 µm and <175 µm) revealed that no particular fraction accumulated a certain heavy metal. Finally, from protocols, techniques and results interpretation in this study, various engineering applications such as the technical choice of clean-up scenarios, screening of remediation techniques and the development of remediation quality criteria were proposed within the framework of the management of contaminated sediments.

An Extension of Marston’s Solution for the Stresses in Backfilled Trenches with Inclined Walls

Infrastructure rehabilitation and development are very active fields around the world. Many of these activities involve the installation of conduits buried in trenches. The analysis and design of such conduits often rely on a solution developed by Marston and his coworkers who used the basic arching theory proposed by Janssen. This solution is theoretically only valid for vertical trenches, but it has been used for trenches with different wall inclinations, which sometimes leads to non-conservative stresses. In this paper, a more general solution for the stress state in backfilled trenches is developed based on the approach adopted by Marston and his coworkers. The effects of wall inclination and of a surcharge on top of the backfill are introduced in the analytical solution. Numerical modeling is performed and the results are used to adjust some components of the equations, leading to a more general solution. The good correlation between the vertical stress distributions given by the proposed solution and additional numerical simulations indicates that this new solution is representative of the stress state in backfilled trenches, and can thus be used for the design of infrastructure rehabilitation and development.

Analysis of procedures for sampling contaminated soil using Gy's Sampling theory and practice

Soil sampling is a critical step in environmental site assessment studies. The representativeness of soil samples has a direct influence on financial, liability, environmental and public health issues associated with the outcome of remediation activities. Representativeness must be quantified for assessing and designing soil sampling procedures. Gys Sampling Theory and Practice (STP) was used to analyze the reproducibility of two soil sampling procedures, namely a procedure based on grab sampling (GSP) and an alternative procedure (ASP) developed from STP principles. Sampling reproducibility, a component of sampling representativeness, was determined by theoretical calculations and experimental measurement of relative variances in trace metals concentrations at each stage of both sampling procedures. The ASP significantly increased the reproducibility of soil sampling compared to the GSP. Larger relative variances occurred during field sampling for the ASP and during laboratory sampling for the GSP. They were due to subsample mass reduction without control over particle size. Relative theoretical and experimental variances were in agreement. However, large discrepancies were observed for all sampling stages of both procedures between absolute theoretical and experimental relative variances. In the case of Pb, theoretical calculations were closer to experimental measurements when using a calculated value of the liberation factor (l) based on mineralogical data rather than l=1. It was shown that the b-exponent had a large influence on theoretical variances. Increasing the estimate of b from 0.5 to 1 largely improved the agreement between theory and experiment. Finally, 99% of experimental relative variance was explained by sampling errors compared to analytical errors.

Estimating the mean and standard deviation of environmental data with below detection limit observations: Considering highly skewed data and model misspecification.

In environmental studies, concentration measurements frequently fall below detection limits of measuring instruments, resulting in left-censored data. Some studies employ parametric methods such as the maximum likelihood estimator (MLE), robust regression on order statistic (rROS), and gamma regression on order statistic (GROS), while others suggest a non-parametric approach, the Kaplan-Meier method (KM). Using examples of real data from a soil characterization study in Montreal, we highlight the need for additional investigations that aim at unifying the existing literature. A number of studies have examined this issue; however, those considering data skewness and model misspecification are rare. These aspects are investigated in this paper through simulations. Among other findings, results show that for low skewed data, the performance of different statistical methods is comparable, regardless of the censoring percentage and sample size. For highly skewed data, the performance of the MLE method under lognormal and Weibull distributions is questionable; particularly, when the sample size is small or censoring percentage is high. In such conditions, MLE under gamma distribution, rROS, GROS, and KM are less sensitive to skewness. Related to model misspecification, MLE based on lognormal and Weibull distributions provides poor estimates when the true distribution of data is misspecified. However, the methods of rROS, GROS, and MLE under gamma distribution are generally robust to model misspecifications regardless of skewness, sample size, and censoring percentage. Since the characteristics of environmental data (e.g., type of distribution and skewness) are unknown a priori, we suggest using MLE based on gamma distribution, rROS and GROS.

Stress distribution in a cohesionless backfill poured in a silo

The field of infrastructure rehabilitation and development requires a better understanding of soil-structure in teractions. The interaction behaviour between soil and structures has mostly been investigated through theoretical and/or numerical analysis. This paper presents a series of experiments performed on an intermediate-scale physical model made of an instrumented silo. In contrast to most reported laboratory tests, both the horizontal and vertical stresses were monitored during backfilling operations realised by wild pouring. Drop tests were performed to investigate the density variation with respect to the drop (or falling) height of the soil, which were introduced in the pressure interpretation. The results showed that horizontal stress in the direction parallel to the pouring plane is larger than that perpendicular to the pouring plane. Apparently, the vertical stress is well-described using the arching solution by considering the backfill in an active state, whereas the horizontal stress perpendicular to the pouring plane is better described with the arching solution by considering the backfill in an at-rest state. An estimate of the earth pressure coefficients based on the measured vertical and horizontal stresses indicates, however, that the backfill was closer to an at-rest state in the direction perpendicular to the pouring plane, whereas in the direction parallel to the pouring plane, it was in a state between at-rest and passive. These results indicate that it is important to measure both the horizontal and vertical stresses to obtain a whole picture of the state of the backfill. The results showed also that the horizontal stresses can be larger than those calculated by the overburden solution, probably due to dynamic loading by drop mass during the filling operation and stress lock.

Estimation of total and effective stresses in trenches with inclined walls

Abstract Load estimation is a critical issue in infrastructure design. This task is usually realized using the Marston solution, which is developed for vertical trenches, without consideration of the water condition. In many cases, trenches need to be excavated with inclined walls. Also, rain, snow or other water sources may flow in the trenches where conduits are buried. Once submerged by water, the state of the backfill in such trenches may change significantly in terms of total and effective stresses. This aspect has been addressed by the authors and collaborators for vertical backfilled openings. Furthermore, solutions have been proposed for estimating the stresses in backfill within inclined wall trenches under fully drained conditions (zero pore water pressure). However, there is no analytical solution available for evaluating the total and effective stresses in backfill within inclined wall trenches. In this paper, an analytical solution is presented to evaluate total and effective vertical stresses in partly or totally submerged backfilled trenches with inclined walls. Then, numerical modeling is performed and compared to the analytical solution. Results show that the proposed solution predicts the vertical stresses at the bottom of trenches quite well. With certain precautions, it could be used to estimate the backfill loads on buried conduits in inclined wall trenches.

On the use of the substitution method in left-censored environmental data

ABSTRACT In risk assessment and environmental monitoring studies, concentration measurements frequently fall below detection limits (DL) of measuring instruments, resulting in left-censored data. The principal approaches for handling censored data include the substitution-based method, maximum likelihood estimation, robust regression on order statistics, and Kaplan-Meier. In practice, censored data are substituted with an arbitrary value prior to use of traditional statistical methods. Although some studies have evaluated the substitution performance in estimating population characteristics, they have focused mainly on normally and lognormally distributed data that contain a single DL. We employ Monte Carlo simulations to assess the impact of substitution when estimating population parameters based on censored data containing multiple DLs. We also consider different distributional assumptions including lognormal, Weibull, and gamma. We show that the reliability of the estimates after substitution is highly sensitive to distributional characteristics such as mean, standard deviation, skewness, and also data characteristics such as censoring percentage. The results highlight that although the performance of the substitution-based method improves as the censoring percentage decreases, its performance still depends on the populations distributional characteristics. Practical implications that follow from our findings indicate that caution must be taken in using the substitution method when analyzing censored environmental data.

Representativeness of laboratory sampling procedures for the analysis of trace metals in soil

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.

Toward improved analysis of concentration data: Embracing nondetects

Various statistical tests on concentration data serve to support decision-making regarding characterization and monitoring of contaminated media, assessing exposure to a chemical, and quantifying the associated risks. However, the routine statistical protocols cannot be directly applied because of challenges arising from nondetects or left-censored observations, which are concentration measurements below the detection limit of measuring instruments. Despite the existence of techniques based on survival analysis that can adjust for nondetects, these are seldom taken into account properly. A comprehensive review of the literature showed that managing policies regarding analysis of censored data do not always agree and that guidance from regulatory agencies may be outdated. Therefore, researchers and practitioners commonly resort to the most convenient way of tackling the censored data problem by substituting nondetects with arbitrary constants prior to data analysis, although this is generally regarded as a bias-prone approach. Hoping to improve the interpretation of concentration data, the present article aims to familiarize researchers in different disciplines with the significance of left-censored observations and provides theoretical and computational recommendations (under both frequentist and Bayesian frameworks) for adequate analysis of censored data. In particular, the present article synthesizes key findings from previous research with respect to 3 noteworthy aspects of inferential statistics: estimation of descriptive statistics, hypothesis testing, and regression analysis. Environ Toxicol Chem 2018;37:643-656.

Application of mixed effects models for characterizing contaminated sites

In a typical data collection process for the purpose of characterizing contaminated sites, boreholes are usually drilled in different locations based on a sampling plan; and consequently, multiple samples are collected from each borehole. As a result, it is quite plausible that a certain degree of dependency or similarity exists among observations nested within a borehole. However, when classical regression models are employed, such dependencies are often ignored, resulting in biased estimates. In site characterization studies, further complication arises due to the presence of left-censored observations, those falling below the detection limit of measuring instruments. To overcome the above issues, this paper employs a mixed effects model that allows accounting for the within-borehole data dependency while accommodating left-censored concentrations. The benefits of the adopted methodology are explored by analyzing concentration data obtained from characterization study of a brownfield site located in Montreal, Canada. This paper illustrates that the estimated within-borehole correlation can be used to determine the optimal number of boreholes as well as the sample size to be collected from each borehole. Such correlation is underestimated when censored values are not accommodated in the model but substituted with a constant prior to data analysis. In addition, the adopted methodology provides an accurate insight into the vertical extent of contamination that can result in different compliance decisions when compared with classical approach.