A Monitoring Network Design Procedure for Three-Dimensional (3D) Groundwater Contaminant Source Identification

Finding the location and concentration of contaminant sources is an important step in groundwater remediation and management. This discovery typically requires the solution of an inverse problem. This inverse problem can be formulated as an optimization problem where the objective function is the sum of the square of the errors between the observed and predicted values of contaminant concentration at the observation wells. Studies show that the source identification accuracy is dependent on the observation locations (i.e., network geometry) and frequency of sampling; thus, finding a set of optimal monitoring well locations is very important for characterizing the source. The objective of this study is to propose a sensitivity-based method for optimal placement of monitoring wells by incorporating two uncertainties: the source location and hydraulic conductivity. An optimality metric called D-optimality in combination with a distance metric, which tends to make monitoring locations as far apart from each other as possible, is developed for finding optimal monitoring well locations for source identification. To address uncertainty in hydraulic conductivity, an integration method of multiple well designs is proposed based on multiple hydraulic conductivity realizations. Genetic algorithm is used as a search technique for this discrete combinatorial optimization problem. This procedure was applied to a hypothetical problem based on the well-known Borden Site data in Canada. The results show that the criterion-based selection proposed in this paper provides improved source identification performance when compared to uniformly distributed placement of wells.     

Kinetics of soil ozonation: an experimental and numerical investigation

This study investigates the use of ozone for soil remediation. Batch experiments, in which ozone-containing gas was continuously recycled through a soil bed, were conducted to quantify the rate of ozone self-decomposition and the rates of ozone interaction with soil organic and inorganic matter. Column experiments were conducted to measure ozone breakthrough from a soil column. Parameters such as ozone flow rate, soil mass, and ozonation time were varied in these experiments. After ozone concentration had reached steady state, the total organic carbon concentration was measured for all soil samples. The ozonation efficiency, represented by the ratio of soil organic matter consumed to the total ozone input, was quantified for each experiment. Numerical simulations were conducted to simulate experimentally obtained column breakthrough curves. Experimentally obtained kinetic rate constants were used in these simulations, and the results were in good agreement with experimental data. In contrast to previous studies in which soil inorganic matter was completely ignored, our experiments indicate that soil inorganic matter may also promote depletion of ozone, thus reducing the overall ozonation efficiency. Three-dimensional numerical simulations were conducted to predict the efficacy of ozonation for soil remediation in the field. These simulations indicate that such ozonation can be very effective, provided that effective circulation of ozone is achieved through appropriately placed wells.