Multi-stage optimal design for groundwater remediation: A hybrid bi-level programming approach

This paper presents the development of a hybrid bi-level programming approach for supporting multi-stage groundwater remediation design. To investigate remediation performances, a subsurface model was employed to simulate contaminant transport. A mixed-integer nonlinear optimization model was formulated in order to evaluate different remediation strategies. Multivariate relationships based on a filtered stepwise clustering analysis were developed to facilitate the incorporation of a simulation model within a nonlinear optimization framework. By using the developed statistical relationships, predictions needed for calculating the objective function value can be quickly obtained during the search process. The main advantage of the developed approach is that the remediation strategy can be adjusted from stage to stage, which makes the optimization more realistic. The proposed approach was examined through its application to a real-world aquifer remediation case in western Canada. The optimization results based on this application can help the decision makers to comprehensively evaluate remediation performance.     

Pulsed pumping process optimization using a potential flow model

A computational model is applied to the optimization of pulsed pumping systems for efficient in situ remediation of groundwater contaminants. In the pulsed pumping mode of operation, periodic rather than continuous pumping is used. During the pump-off or trapping phase, natural gradient flow transports contaminated groundwater into a treatment zone surrounding a line of injection and extraction wells that transect the contaminant plume. Prior to breakthrough of the contaminated water from the treatment zone, the wells are activated and the pump-on or treatment phase ensues, wherein extracted water is augmented to stimulate pollutant degradation and recirculated for a sufficient period of time to achieve mandated levels of contaminant removal. An important design consideration in pulsed pumping groundwater remediation systems is the pumping schedule adopted to best minimize operational costs for the well grid while still satisfying treatment requirements. Using an analytic two-dimensional potential flow model, optimal pumping frequencies and pumping event durations have been investigated for a set of model aquifer-well systems with different well spacings and well-line lengths, and varying aquifer physical properties. The results for homogeneous systems with greater than five wells and moderate to high pumping rates are reduced to a single, dimensionless correlation. Results for heterogeneous systems are presented graphically in terms of dimensionless parameters to serve as an efficient tool for initial design and selection of the pumping regimen best suited for pulsed pumping operation for a particular well configuration and extraction rate. In the absence of significant retardation or degradation during the pump-off phase, average pumping rates for pulsed operation were found to be greater than the continuous pumping rate required to prevent contaminant breakthrough.     

Simultaneous optimization of dense non-aqueous phase liquid (DNAPL) source and contaminant plume remediation

A framework is developed for simultaneous, optimal design of groundwater contaminant source removal and plume remediation strategies. The framework allows for varying degrees of effort and cost to be dedicated to source removal versus plume remediation. We have accounted for the presence of physical heterogeneity in the DNAPL source, since source heterogeneity controls mass release into the plume and the efficiency of source removal efforts. We considered high and low estimates of capital and operating costs for chemical flushing removal of the source, since these are expected to vary form site to site. Using the lower chemical flushing cost estimates, it is found that the optimal allocation of funds to source removal or plume remediation is sensitive to the degree of heterogeneity in the source. When the time elapsed between the source release and the implementation of remediation was varied, it was found that, except for the longest elapsed time (50,000 days), a combination of partial source removal and plume remediation was most efficient. When first-order, dissolved contaminant degradation was allowed, source removal was found to be unnecessary for the cases where the degradation rate exceeded intermediate values of the first-order rate constant. Finally, it was found that source removal became more necessary as the degree of aquifer heterogeneity increased.     

A multi-objective optimization framework for surfactant-enhanced remediation of DNAPL contaminations

The occurrence of Dense Non-Aqueous Phase Liquid (DNAPL) contaminations in the subsurface is a threat for drinkwater resources in the western world. Surfactant-Enhanced Aquifer Remediation (SEAR) is widely considered as one of the most promising techniques to remediate DNAPL contaminations in-situ, be it with considerable additional costs compared to classical pump-and-treat remediations. A cost-effective design of the remediation set-up is therefore essential. In this work, a pilot SEAR test is executed at a DNAPL contaminated site in Belgium in order to collect data for the calibration of a multi-phase multi-component model. The calibrated model is used to assess a series of scenario-analyses for the full-scale remediation of the site. The remediation variables that were varied were the injection and extraction rate, the injection and extraction duration, and the surfactant injection concentrations. A constrained multi-objective optimization of the model was applied to obtain a Pareto set of optimal remediation strategies with different weights for the two objectives of the remediation: (i) the maximal removal of DNAPL and (ii) a total minimal cost. These Pareto curves can help decision makers to select an optimal remediation strategy in terms of cost and remediation efficiency. The Pareto front shows a considerable trade-off between the total remediation cost and the removed DNAPL mass.     

Dissolved plume attenuation with DNAPL source remediation, aqueous decay and volatilization--analytical solution, model calibration and prediction uncertainty

A vertically-integrated analytical model for dissolved phase transport is described that considers a time-dependent DNAPL source based on the upscaled dissolution kinetics model of Parker and Park with extensions to consider time-dependent source zone biodecay, partial source mass reduction, and remediation-enhanced source dissolution kinetics. The model also considers spatial variability in aqueous plume decay, which is treated as the sum of aqueous biodecay and volatilization due to diffusive transport and barometric pumping through the unsaturated zone. The model is implemented in Excel/VBA coupled with (1) an inverse solution that utilizes prior information on model parameters and their uncertainty to condition the solution, and (2) an error analysis module that computes parameter covariances and total prediction uncertainty due to regression error and parameter uncertainty. A hypothetical case study is presented to evaluate the feasibility of calibrating the model from limited noisy field data. The results indicate that prediction uncertainty increases significantly over time following calibration, primarily due to propagation of parameter uncertainty. However, differences between the predicted performance of source zone partial mass reduction and the known true performance were reasonably small. Furthermore, a clear difference is observed between the predicted performance for the remedial action scenario versus that for a no-action scenario, which is consistent with the true system behavior. The results suggest that the model formulation can be effectively utilized to assess monitored natural attenuation and source remediation options if careful attention is given to model calibration and prediction uncertainty issues.     

Quantification of groundwater contamination in an urban area using integral pumping tests

In this paper, the integral groundwater investigation method is used for the quantification of PCE and TCE mass flow rates at an industrialized urban area in Linz, Austria. In this approach, pumping wells positioned along control planes perpendicular to the groundwater flow direction are operated for a time period on the order of days and sampled for contaminants. The concentration time series of the contaminants measured during operation of the pumping wells are then used to determine contaminant mass flow rates, mean concentrations and the plume shapes and positions at the control planes. The three control planes used in Linz were positioned downstream of a number of potential source zones, which are distributed over the field site. By use of the integral investigation method, it was possible to identify active contaminant sources, quantify the individual source strength in terms of mass flow rates at the control planes and estimate the contaminant plume position relative to the control planes. The source zones emitting the highest PCE and TCE mass flow rates could be determined, representing the areas where additional investigation and remediation activities will be needed. Additionally, large parts of the area investigated could be excluded from further investigation and remediation activities.     

Use of principal component analysis to profile temporal and spatial variations of chlorinated solvent concentration in groundwater

This work aims at evaluating spatial distribution patterns of concentration variations for chlorinated solvents in groundwater, based on principal component analysis and geographic information system (GIS) tools. The study investigates long-time series of chlorinated solvent concentrations in groundwater measured for 18 contaminated industrial sites. The characterization of contaminant plumes and delineation of pollutant sources are essential for choosing appropriate monitoring and remediation strategies, as contaminated groundwaters are characterized by complex patterns of spatial and temporal concentration variability, with wide unpredictable fluctuations over time. The present work describes the results of a new exploratory statistical method called the Variability Index Method (VIM) applied to environmental data to assess the performance of using concentration variations as molecular tracers to reveal aquifer dynamics, industrial impacts, and point sources for contamination plumes. The application of this method provides a useful assessment of controls over contaminant concentration variations as well as support for remediation techniques.     

Estimating contaminant mass discharge: a field comparison of the multilevel point measurement and the integral pumping investigation approaches and their uncertainties

In this field study, two approaches to assess contaminant mass discharge were compared: the sampling of multilevel wells (MLS) and the integral groundwater investigation (or integral pumping test, IPT) that makes use of the concentration-time series obtained from pumping wells. The MLS approached used concentrations, hydraulic conductivity and gradient rather than direct chemical flux measurements, while the IPT made use of a simplified analytical inversion. The two approaches were applied at a control plane located approximately 40m downgradient of a gasoline source at Canadian Forces Base Borden, Ontario, Canada. The methods yielded similar estimates of the mass discharging across the control plane. The sources of uncertainties in the mass discharge in each approach were evaluated, including the uncertainties inherent in the underlying assumptions and procedures. The maximum uncertainty of the MLS method was about 67%, and about 28% for the IPT method in this specific field situation. For the MLS method, the largest relative uncertainty (62%) was attributed to the limited sampling density (0.63 points/m(2)), through a novel comparison with a denser sampling grid nearby. A five-fold increase of the sampling grid density would have been required to reduce the overall relative uncertainty for the MLS method to about the same level as that for the IPT method. Uncertainty in the complete coverage of the control plane provided the largest relative uncertainty (37%) in the IPT method. While MLS or IPT methods to assess contaminant mass discharge are attractive assessment tools, the large relative uncertainty in either method found for this reasonable well monitored and simple aquifer suggests that results in more complex plumes in more heterogeneous aquifers should be viewed with caution.     

Application of first-order reliability method to modelling the fate and transport of benzene in groundwater

Parameter uncertainty plays a significant role in decision making regarding groundwater contamination and remediation, especially for non-conservative chemicals. This paper presents a probabilistic screening model to accommodate parameter uncertainty in the aquifer media, and physical–chemical parameters, using the first-order reliability method (FORM). The application of the developed model is illustrated on transport of benzene in groundwater. The results matched those obtained using the Monte Carlo simulation method, with a smaller number of functional evaluations. Parametric studies were conducted to estimate the effect of various parameters on the results.     

Monitoring groundwater contamination and delineating source zones at industrial sites: uncertainty analyses using integral pumping tests

Field-scale characterisations of contaminant plumes in groundwater, as well as source zone delineations, are associated with uncertainties that can be considerable. A major source of uncertainty in environmental datasets is due to variability of sampling results, as a direct consequence of the heterogeneity of environmental matrices. We develop a methodology for quantifying uncertainties in field-scale mass flow and average concentration estimations, using integral pumping tests (IPTs), where the contaminant concentration is measured as a function of time in a pumping well. This procedure increases the sampling volume and reduces the effect of small-scale variability that may bias point-scale measurements. In particular, using IPTs, the interpolation uncertainty of conventional point-scale measurements is transformed to a quantifiable uncertainty related to the (unknown) plume position relative to the pumping well. We show that this plume position uncertainty generally influenced the predicted mass flows and average concentrations (of acenapthene, benzene and CHCs) to a greater extent than a boundary condition uncertainty related to the local water balance, considering 19 control planes at a highly heterogeneous industrial site in southwest Germany. Furthermore, large (order of magnitude) uncertainties only occurred if the conditions were strongly heterogeneous in the nearest vicinity of the well. We also develop a consistent methodology for an assessment of the combined effect of uncertainty in hydraulic conditions and uncertainty in reactive transport parameters for delimiting of both contaminant source zones and zones absent of source, based on (downgradient) IPTs.     

Development of a fuzzy-stochastic nonlinear model to incorporate aleatoric and epistemic uncertainty

Site uncertainties significantly influence groundwater flow and contaminant transport predictions. Aleatoric and epistemic uncertainty are both identified in site characterization and represented using proper uncertainty theories. When one theory best represents one parameter whereas a different theory may be more suitable for another parameter, the hybrid propagation of aleatoric (random) and epistemic (nonrandom) uncertainties will occur. The computational challenges of joint propagation of aleatoric and epistemic uncertainty through groundwater flow and contaminant transport models are significant. A fuzzy-stochastic nonlinear model was developed in this paper to incorporate these two types of uncertain site information and reduce the computational cost. The results show that (1) the computational cost using the nonlinear model is reduced compared with that of using the sparse grid algorithm and Monte Carlo methods; (2) the uncertainty of hydraulic conductivity (K) significantly influences the water head and solute distribution at the observation wells compared to other uncertain parameters, such as the storage coefficient and the distribution coefficient (K_d); and (3) the combination of multiple uncertain parameters substantially affects the simulation results. Neglecting site uncertainties may lead to unrealistic predictions.     

Modelling of an enhanced PAH attenuation experiment and associated biogeochemical changes at a former gasworks site in southern Germany

Former manufactured gas plant sites often form a widespread contaminant source in the subsurface, leading to large plumes that contain a wide variety of tar-oil related compounds. Although most of these compounds eventually degrade naturally, the relevant processes tend to be slow and inefficient, often leaving active remediation as the only viable option to eliminate the risks of toxic substances to reach potential receptors such as surface waters or drinking water wells. In this study we use a reactive transport model to analyse the fate of a contaminant plume containing acenaphthene, methylbenzofurans and dimethylbenzofurans (i) prior to the installation of an active remediation scheme and (ii) for an enhanced remediation experiment during which O(2) and H(2)O(2) were added to the contaminated groundwater through a recirculation well. The numerical model developed for this study considers the primary contaminant degradation reactions (i.e., microbially mediated redox reactions) as well as secondary and competing mineral precipitation/dissolution reactions that affect the site's hydrochemistry and/or contaminant fate. The model was calibrated using a variety of constraints to test the uncertainty on model predictions resulting from the undocumented presence of reductants such as pyrite. The results highlight the important role of reactive transport modelling for the development of a comprehensive process understanding.     

Estimating contaminant-flushing rates for heterogeneous aquifers

Groundwater remediation evaluations typically include cleanup time projections. Current batch flushing-rate equations and analytical models often used to estimate groundwater cleanup rates typically underestimate cleanup times, with a major factor the flawed assumption of aquifer homogeneity. Numerical modelling of groundwater flow and contaminant transport is a time-intensive and costly alternative. An analytical modelling approach has been developed to quickly and cost effectively approximate realistic contaminant cleanup rates, factoring aquifer heterogeneity into the process. The mathematical relationships predict residual dissolved concentrations and average pumped concentrations over time, and also the time required to meet a concentration standard.     

空气喷射处理饱和土壤和地下水中有机污染物

空气喷射 (airsparging)被认为是修复由可挥发性有机物污染的饱和土壤和地下水的一种有效新技术。介绍了空气喷射技术的现场应用与研究现状 ,讨论了空气喷射技术的原理和各种影响因素 ,说明了其对于饱和土壤中有氧生物降解的促进作用 ,分析了空气喷射技术的应用前景。     

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.     

A robust approach for iterative contaminant source location and release history recovery

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.     

A robust approach for iterative contaminant source location and release history recovery

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.     

Analytical solutions for flow fields near continuous wall reactive barriers

Permeable reactive barriers (PRBs) are widely applied for in-situ remediation of contaminant plumes transported by groundwater. Besides the goal of a sufficient contaminant remediation inside the reactive cell (residence time) the width of plume intercepted by a PRB is of critical concern. A 2-dimensional analytical approach is applied to determine the flow fields towards rectangular PRBs of the continuous wall (CW) configuration with and without impermeable side walls (but yet no funnel). The approach is based on the conformal mapping technique and assumes a homogeneous aquifer with a uniform ambient flow field. The hydraulic conductivity of the reactive material is furthermore assumed to exceed the conductivity of the aquifer by at least one order of magnitude as to neglect the hydraulic gradient across the reactor. The flow fields are analyzed regarding the widths and shapes of the respective capture zones as functions of the dimensions (aspect ratio) of the reactive cell and the ambient groundwater flow direction. Presented are an improved characterization of the advantages of impermeable side walls, a convenient approach to improved hydraulic design (including basic cost-optimization) and new concepts for monitoring CW PRBs. Water level data from a CW PRB at the Seneca Army Depot site, NY, are used for field demonstration.     

Porous organoclay composite for the sorption of polycyclic aromatic hydrocarbons and pentachlorophenol from groundwater

Complex mixtures of hazardous chemicals such as polycyclic aromatic hydrocarbons (PAHs) in contaminated soil and groundwater can have severe and long-lasting effects on health. The evidence that these contaminants can cause adverse health effects in animals and humans is rapidly expanding. The frequent and wide-spread occurrence of PAHs in groundwater makes appropriate intervention strategies for their remediation highly desirable. The core objective of this research was to assess the ability of a clay-based composite to sorb and remove toxic contaminants from groundwater at a wood-preserving chemical waste site. Treatment efficiencies were evaluated using either effluent from an oil-water separator (OWS) or a bioreactor (B2). The effluent water from these units was passed through fixed bed columns containing either an organoclay composite or granular activated carbon. The sorbent columns were placed in-line using existing sampling ports at the effluent of the OWS or B2. Individual one-liter samples of treated and untreated effluent were collected in Kimax bottles over the course of 78 h (total of 50 samples). Subsequently each sample was extracted by solid phase extraction methodology, and pentachlorophenol (PCP) and PAH concentrations were quantitated via GC/MS. Columns containing porous organoclay composite, i.e. sand-immobilized cetylpyridinium-exchanged low-pH montmorillonite clay (CP/LPHM), were shown to reduce the contaminant load from the OWS effluent stream by 97%. The concentrations of benzo[a]pyrene (BaP) and PCP were considerably reduced (i.e. >99%). An effluent stream from the bioreactor was also filtered through columns packed with composite or an equivalent amount of GAC. Although the composite reduced the majority of contaminants (including BaP and PCP), it was less effective in diminishing the levels of lower ring versus higher ring PAHs. Conversely, GAC was more effective in removing the lower ring PAHs, except for naphthalene and PCP. The effectiveness of sorption of PCP from the OWS effluent by the composite was confirmed using a PCP-sensitive adult hydra bioassay previously described in our laboratory. The findings of this initial study have delineated differences between CP/LPHM and GAC for groundwater remediation, and suggest that GAC (instead of sand) as the solid support for organoclay may be more effective for the treatment of contaminated groundwater under field conditions than GAC or CP/LPHM alone. Further work is ongoing to confirm this conclusion.     

Approximate evaluation of contaminant transport through vertical barriers

Containment of groundwater contamination using physical barriers can be an important element of a subsurface remediation program. This work presents simple analytical tools for predicting the performance of barriers in terms of the steady-state contaminant flux across the barrier, the duration of the transient period following barrier installation, and the time-dependent contaminant concentration distribution within the barrier. The analytical expressions are developed from approximate boundary layer (BL) solutions to the advective–dispersive equation subject to conservative fixed concentration boundary conditions. Critical ranges of important dimensionless quantities are identified for use in barrier performance assessment, for both steady-state and transient conditions. Comparative calculations made with the BL equations and more exact semi-analytical solutions are used to characterize the accuracy and applicability of the BL approach.