A hybrid method for inverse characterization of subsurface contaminant flux

The methods presented in this work provide a potential tool for characterizing contaminant source zones in terms of mass flux. The problem was conceptualized by considering contaminant transport through a vertical “flux plane” located between a source zone and a downgradient region where contaminant concentrations were measured. The goal was to develop a robust method capable of providing a statement of the magnitude and uncertainty associated with estimated contaminant mass flux values.In order to estimate the magnitude and transverse spatial distribution of mass flux through a plane, the problem was considered in an optimization framework. Two numerical optimization techniques were applied, simulated annealing (SA) and minimum relative entropy (MRE). The capabilities of the flux plane model and the numerical solution techniques were evaluated using data from a numerically generated test problem and a nonreactive tracer experiment performed in a three-dimensional aquifer model. Results demonstrate that SA is more robust and converges more quickly than MRE. However, SA is not capable of providing an estimate of the uncertainty associated with the simulated flux values. In contrast, MRE is not as robust as SA, but once in the neighborhood of the optimal solution, it is quite effective as a tool for inferring mass flux probability density functions, expected flux values, and confidence limits.A hybrid (SA-MRE) solution technique was developed in order to take advantage of the robust solution capabilities of SA and the uncertainty estimation capabilities of MRE. The coupled technique provided probability density functions and confidence intervals that would not have been available from an independent SA algorithm and they were obtained more efficiently than if provided by an independent MRE algorithm.     

Analysis of groundwater contamination using concentration–time series recorded during an integral pumping test: Bias introduced by strong concentration gradients within the plume

When only few monitoring wells are available to assess the extent and level of groundwater contamination, inversion of concentration breakthrough curves acquired during an integral pumping test can be used as an alternative quantification method. The idea is to use concentration–time series recorded during integral pumping tests through an inversion technique to estimate contaminant mass fluxes crossing a control plane. In this paper, we examine how a longitudinal concentration gradient along a contaminant plume length scale affects the estimated inversed-concentration distribution and its associated mass flux. The analytically inversed-concentration distribution at the imaginary control plane (ICP) is compared to a numerically generated concentration distribution, treating the latter one as a “real contaminant plume” characterized by the presence of a longitudinal concentration gradient. It is found that the analytically inversed-concentration can lead to overestimation or underestimation of concentration distribution values depending on the transport time period and dispersivity values. At lower dispersivity values, with shorter transport time periods, the analytically inversed-concentration distribution overestimates the “real” concentration distribution.A better fit of the estimated concentration distribution to the “real” one is observed when the transport time period increases, i.e. when the advective front has already crossed the ICP. However, for higher dispersivity values, underestimation of the real concentration distribution is observed. Deviation of the inversed-concentration distribution from the “real” one is assessed for a site-specific concentration gradient term. A concentration gradient adjusted contaminant mass flux is thus formulated to evaluate groundwater contamination levels at a given time period through an ICP. This concentration gradient ratio can indicate whether the ICP is well positioned to evaluate accurately contaminant mass fluxes which are representative of groundwater contamination levels.     

Analysis of groundwater contamination using concentration-time series recorded during an integral pumping test: bias introduced by strong concentration gradients within the plume

When only few monitoring wells are available to assess the extent and level of groundwater contamination, inversion of concentration breakthrough curves acquired during an integral pumping test can be used as an alternative quantification method. The idea is to use concentration-time series recorded during integral pumping tests through an inversion technique to estimate contaminant mass fluxes crossing a control plane. In this paper, we examine how a longitudinal concentration gradient along a contaminant plume length scale affects the estimated inversed-concentration distribution and its associated mass flux. The analytically inversed-concentration distribution at the imaginary control plane (ICP) is compared to a numerically generated concentration distribution, treating the latter one as a "real contaminant plume" characterized by the presence of a longitudinal concentration gradient. It is found that the analytically inversed-concentration can lead to overestimation or underestimation of concentration distribution values depending on the transport time period and dispersivity values. At lower dispersivity values, with shorter transport time periods, the analytically inversed-concentration distribution overestimates the "real" concentration distribution. A better fit of the estimated concentration distribution to the "real" one is observed when the transport time period increases, i.e. when the advective front has already crossed the ICP. However, for higher dispersivity values, underestimation of the real concentration distribution is observed. Deviation of the inversed-concentration distribution from the "real" one is assessed for a site-specific concentration gradient term. A concentration gradient adjusted contaminant mass flux is thus formulated to evaluate groundwater contamination levels at a given time period through an ICP. This concentration gradient ratio can indicate whether the ICP is well positioned to evaluate accurately contaminant mass fluxes which are representative of groundwater contamination levels.     

Influence of temporally variable groundwater flow conditions on point measurements and contaminant mass flux estimations

Monitoring of contaminant concentrations, e.g., for the estimation of mass discharge or contaminant degradation rates, often is based on point measurements at observation wells. In addition to the problem, that point measurements may not be spatially representative, a further complication may arise due to the temporal dynamics of groundwater flow, which may cause a concentration measurement to be not temporally representative. This paper presents results from a numerical modeling study focusing on temporal variations of the groundwater flow direction. “Measurements” are obtained from point information representing observation wells installed along control planes using different well frequencies and configurations. Results of the scenario simulations show that temporally variable flow conditions can lead to significant temporal fluctuations of the concentration and thus are a substantial source of uncertainty for point measurements. Temporal variation of point concentration measurements may be as high as the average concentration determined, especially near the plume fringe, even when assuming a homogeneous distribution of the hydraulic conductivity. If a heterogeneous hydraulic conductivity field is present, the concentration variability due to a fluctuating groundwater flow direction varies significantly within the control plane and between the different realizations. Determination of contaminant mass fluxes is also influenced by the temporal variability of the concentration measurement, especially for large spacings of the observation wells. Passive dosimeter sampling is found to be appropriate for evaluating the stationarity of contaminant plumes as well as for estimating average concentrations over time when the plume has fully developed. Representative sampling has to be performed over several periods of groundwater flow fluctuation. For the determination of mass fluxes at heterogeneous sites, however, local fluxes, which may vary considerably along a control plane, have to be accounted for. Here, dosimeter sampling in combination with time integrated local water flux measurements can improve mass flux estimates under dynamic flow conditions.     

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.     

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.     

Design and Verification of a Programmable Gas Dispensing System for Exposing Plants to Dynamic Concentrations of Air Pollutants

Abstract

Landfills represent a source of distributed emissions source over an irregular and heterogeneous surface. In the method termed “Other Test Method-10” (OTM-10), the U.S. Environmental Protection Agency (EPA) has proposed a method to quantify emissions from such sources by the use of vertical radial plume mapping (VRPM) techniques combined with measurement of wind speed to determine the average emission flux per unit area per time from nonpoint sources. In such application, the VRPM is used as a tool to estimate the mass of the gas of interest crossing a vertical plane. This estimation is done by fitting the field-measured concentration spatial data to a Gaussian or some other distribution to define a plume crossing the vertical plane. When this technique is applied to landfill surfaces, the VRPM plane may be within the emitting source area itself. The objective of this study was to investigate uncertainties associated with using OTM-10 for landfills. The spatial variability of emission in the emitting domain can lead to uncertainties of –34 to 190% in the measured flux value when idealistic scenarios were simulated. The level of uncertainty might be higher when the number and locations of emitting sources are not known (typical field conditions). The level of uncertainty can be reduced by improving the layout of the VRPM plane in the field in accordance with an initial survey of the emission patterns. The change in wind direction during an OTM-10 testing setup can introduce an uncertainty of 20% of the measured flux value. This study also provides estimates of the area contributing to flux (ACF) to be used in conjunction with OTM-10 procedures. The estimate of ACF is a function of the atmospheric stability class and has an uncertainty of 10–30%.     

Near surface soil vapor clusters for monitoring emissions of volatile organic compounds from soils

The overall objective of this research was to develop and test a method of determining emission rates of volatile organic compounds (VOCs) and other gases from soil surfaces. Soil vapor clusters (SVCs) were designed as a low dead volume, robust sampling system to obtain vertically resolved profiles of soil gas contaminant concentrations in the near surface zone. The concentration profiles, when combined with a mathematical model of porous media mass transport, were used to calculate the contaminant flux from the soil surface. Initial experiments were conducted using a mesoscale soil remediation system under a range of experimental conditions. Helium was used as a tracer and trichloroethene was used as a model VOC. Flux estimations using the SVCs were within 25% of independent surface flux estimates and were comparable to measurements made using a surface isolation flux chamber (SIFC). In addition, method detection limits for the SVC were an order of magnitude lower than detection limits with the SIFC. Field trials, conducted with the SVCs at a bioventing site, indicated that the SVC method could be easily used in the field to estimate fugitive VOC emission rates. Major advantages of the SVC method were its low detection limits, lack of required auxiliary equipment, and ability to obtain real-time estimates of fugitive VOC emission rates.     

Near Surface Soil Vapor Clusters for Monitoring Emissions of Volatile Organic Compounds from Soils

ABSTRACT

The overall objective of this research was to develop and test a method of determining emission rates of volatile organic compounds (VOCs) and other gases from soil surfaces. Soil vapor clusters (SVCs) were designed as a low dead volume, robust sampling system to obtain vertically resolved profiles of soil gas contaminant concentrations in the near surface zone. The concentration profiles, when combined with a mathematical model of porous media mass transport, were used to calculate the contaminant flux from the soil surface. Initial experiments were conducted using a mesoscale soil remediation system under a range of experimental conditions. Helium was used as a tracer and trichloroethene was used as a model VOC. Flux estimations using the SVCs were within 25% of independent surface flux estimates and were comparable to measurements made using a surface isolation flux chamber (SIFC). In addition, method detection limits for the SVC were an order of magnitude lower than detection limits with the SIFC. Field trials, conducted with the SVCs at a bioventing site, indicated that the SVC method could be easily used in the field to estimate fugitive VOC emission rates. Major advantages of the SVC method were its low detection limits, lack of required auxiliary equipment, and ability to obtain realtime estimates of fugitive VOC emission rates.     

An inverse Gaussian plume approach for estimating atmospheric pollutant emissions from multiple point sources

A method is developed for estimating the emission rates of contaminants into the atmosphere from multiple point sources using measurements of particulate material deposited at ground level. The approach is based on a Gaussian plume type solution for the advection–diffusion equation with ground-level deposition and given emission sources. This solution to the forward problem is incorporated into an inverse algorithm for estimating the emission rates by means of a linear least squares approach. The results are validated using measured deposition and meteorological data from a large lead–zinc smelting operation in Trail, British Columbia. The algorithm is demonstrated to be robust and capable of generating reasonably accurate estimates of total contaminant emissions over the relatively short distances of interest in this study.     

Flux-based assessment at a manufacturing site contaminated with trichloroethylene

Groundwater and contaminant fluxes were measured, using the passive flux meter (PFM) technique, in wells along a longitudinal transect passing approximately through the centerline of a trichloroethylene (TCE) plume at a former manufacturing plant located in the Midwestern US. Two distinct zones of hydraulic conductivity were identified from the measured groundwater fluxes; a 6-m-thick upper zone ( approximately 7 m to 13 m below the ground surface or bgs) with a geometric mean Darcy flux (q(0)) of 2 cm/day, and a lower zone ( approximately 13 m to 16.5m bgs) with a q(0) approximately 15 cm/day; this important hydrogeologic feature significantly impacts any remediation technology used at the site. The flux-averaged TCE concentrations estimated from the PFM results compared well with existing groundwater monitoring data. It was estimated that at least 800 kg of TCE was present in the source zone. The TCE mass discharge across the source control plane (85 m x 38 m) was used to estimate the "source strength" ( approximately 365 g/day), while mass discharges across multiple down-gradient control planes were used to estimate the plume-averaged, TCE degradation rate constant (0.52 year(-1)). This is close to the rate estimated using the conventional centerline approach (0.78 year(-1)). The mass discharge approach provides a more robust and representative estimate than the centerline approach since the latter uses only data from wells along the plume centerline while the former uses all wells in the plume.     

Stochastic evaluation of mass discharge from pointlike concentration measurements

The contaminant mass discharge crossing a control plane is an important metric in the assessment of natural attenuation at contaminated sites. For risk-assessment purposes, the mass discharge must be estimated together with a level of uncertainty. We present a conditional Monte Carlo approach that allows estimating the statistical distribution of mass discharge. The approach is based on conditioning multiple realizations of the hydraulic conductivity field on all data available. We jointly determine a first-order decay coefficient in each realization, leading to conditional statistical distributions of all estimated parameters and the total mass discharge. The resulting statistical distribution of contaminant mass discharges can be used in the assessment of risks at the contaminated site. The method is applied to data of hypothetical test cases, which gives the opportunity to compare estimation results to the true field. As concentration data, we account for pointlike measurements obtained in multi-level sampling wells. The obtained empirical distribution of mass discharge crossing the multi-level sampling fence could be well fitted by a log-normal distribution.     

A coupled simulation-optimization approach for groundwater remediation design under uncertainty: An application to a petroleum-contaminated site

This study provides a coupled simulation–optimization approach for optimal design of petroleum-contaminated groundwater remediation under uncertainty. Compared to the previous approaches, it has the advantages of: (1) addressing the stochasticity of the modeling parameters in simulating the flow and transport of NAPLs in groundwater, (2) providing a direct and response-rapid bridge between remediation strategies (pumping rates) and remediation performance (contaminant concentrations) through the created proxy models, (3) alleviating the computational cost in searching for optimal solutions, and (4) giving confidence levels for the obtained optimal remediation strategies. The approach is applied to a practical site in Canada for demonstrating its performance. The results show that mitigating the effects of uncertainty on optimal remediation strategies (through enhancing the confidence level) would lead to the rise of remediation cost due to the increase in the total pumping rate.     

Assessing the natural attenuation of organic contaminants in aquifers using plume-scale electron and carbon balances: model development with analysis of uncertainty and parameter sensitivity

A quantitative methodology is described for the field-scale performance assessment of natural attenuation using plume-scale electron and carbon balances. This provides a practical framework for the calculation of global mass balances for contaminant plumes, using mass inputs from the plume source, background groundwater and plume residuals in a simplified box model. Biodegradation processes and reactions included in the analysis are identified from electron acceptors, electron donors and degradation products present in these inputs. Parameter values used in the model are obtained from data acquired during typical site investigation and groundwater monitoring studies for natural attenuation schemes. The approach is evaluated for a UK Permo-Triassic Sandstone aquifer contaminated with a plume of phenolic compounds. Uncertainty in the model predictions and sensitivity to parameter values was assessed by probabilistic modelling using Monte Carlo methods. Sensitivity analyses were compared for different input parameter probability distributions and a base case using fixed parameter values, using an identical conceptual model and data set. Results show that consumption of oxidants by biodegradation is approximately balanced by the production of CH4 and total dissolved inorganic carbon (TDIC) which is conserved in the plume. Under this condition, either the plume electron or carbon balance can be used to determine contaminant mass loss, which is equivalent to only 4% of the estimated source term. This corresponds to a first order, plume-averaged, half-life of > 800 years. The electron balance is particularly sensitive to uncertainty in the source term and dispersive inputs. Reliable historical information on contaminant spillages and detailed site investigation are necessary to accurately characterise the source term. The dispersive influx is sensitive to variability in the plume mixing zone width. Consumption of aqueous oxidants greatly exceeds that of mineral oxidants in the plume, but electron acceptor supply is insufficient to meet the electron donor demand and the plume will grow. The aquifer potential for degradation of these contaminants is limited by high contaminant concentrations and the supply of bioavailable electron acceptors. Natural attenuation will increase only after increased transport and dilution.     

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.     

A model for contaminant mass flux in capped sediment under consolidation

The paper presents a model for contaminant transport and flux through a consolidating subaqueous sediment and overlying cap. The formulation is based on the effect of consolidation and excess pore pressure dissipation on transient, nonlinear advective component of transport through sediment and the cap. The consolidation is induced by the buoyant weight of the cap when it is placed on the contaminated sediments. One equation is presented for advective-diffusive transport through the sediment that is dependent upon soil/contaminant properties and transient advective velocity, which is calculated from a second equation based on the Terzaghi consolidation theory. A third equation is provided to describe the transport of contaminants in the cap. The parameters, including advective velocity, and boundary conditions used for contaminant transport through the cap are derived from the solution of the first two equations. The finite difference method is used to solve the system of equations for consolidation and contaminant transport. A hypothetical case is analyzed to demonstrate the formulation, and the results show that advection due to consolidation can accelerate breakthrough of contaminant through the cap by orders of magnitude. The derivation and results show that consolidation should be included for cap design, and that reactive caps are essential for delaying and reducing dissolved contaminant flux.     

A direct passive method for measuring water and contaminant fluxes in porous media

This paper introduces a new direct method for measuring water and contaminant fluxes in porous media. The method uses a passive flux meter (PFM), which is essentially a self-contained permeable unit properly sized to fit tightly in a screened well or boring. The meter is designed to accommodate a mixed medium of hydrophobic and/or hydrophilic permeable sorbents, which retain dissolved organic/inorganic contaminants present in the groundwater flowing passively through the meter. The contaminant mass intercepted and retained on the sorbent is used to quantify cumulative contaminant mass flux. The sorptive matrix is also impregnated with known amounts of one or more water soluble 'resident tracers'. These tracers are displaced from the sorbent at rates proportional to the groundwater flux; hence, in the current meter design, the resident tracers are used to quantify cumulative groundwater flux. Theory is presented and quantitative tools are developed to interpret the water flux from tracers possessing linear and nonlinear elution profiles. The same theory is extended to derive functional relationships useful for quantifying cumulative contaminant mass flux. To validate theory and demonstrate the passive flux meter, results of multiple box-aquifer experiments are presented and discussed. From these experiments, it is seen that accurate water flux measurements are obtained when the tracer used in calculations resides in the meter at levels representing 20 to 70 percent of the initial condition. 2,4-Dimethyl-3-pentanol (DMP) is used as a surrogate groundwater contaminant in the box aquifer experiments. Cumulative DMP fluxes are measured within 5% of known fluxes. The accuracy of these estimates generally increases with the total volume of water intercepted.     

A comparison of numerical solutions of partial differential equations with probabilistic and possibilistic parameters for the quantification of uncertainty in subsurface solute transport

Traditionally, uncertainty in parameters are represented as probabilistic distributions and incorporated into groundwater flow and contaminant transport models. With the advent of newer uncertainty theories, it is now understood that stochastic methods cannot properly represent non random uncertainties. In the groundwater flow and contaminant transport equations, uncertainty in some parameters may be random, whereas those of others may be non random. The objective of this paper is to develop a fuzzy-stochastic partial differential equation (FSPDE) model to simulate conditions where both random and non random uncertainties are involved in groundwater flow and solute transport. Three potential solution techniques namely, (a) transforming a probability distribution to a possibility distribution (Method I) then a FSPDE becomes a fuzzy partial differential equation (FPDE), (b) transforming a possibility distribution to a probability distribution (Method II) and then a FSPDE becomes a stochastic partial differential equation (SPDE), and (c) the combination of Monte Carlo methods and FPDE solution techniques (Method III) are proposed and compared. The effects of these three methods on the predictive results are investigated by using two case studies. The results show that the predictions obtained from Method II is a specific case of that got from Method I. When an exact probabilistic result is needed, Method II is suggested. As the loss or gain of information during a probability–possibility (or vice versa) transformation cannot be quantified, their influences on the predictive results is not known. Thus, Method III should probably be preferred for risk assessments.     

DNAPL source depletion: linking architecture and flux response

The relationship between dense non-aqueous phase liquid (DNAPL) mass reduction and contaminant mass flux was investigated experimentally in four model source zones. The flow cell design for the experiments featured a segmented extraction well that allowed for analysis of spatially resolved flux information. This flux information was coupled with image analysis of the NAPL spatial distribution to investigate the relationship between flux and the up-gradient NAPL architecture. Results indicate that in the systems studied, the relationship between DNAPL mass reduction and contaminant mass flux was primarily controlled by the NAPL architecture. A specific definition of NAPL architecture was employed where the source zone is resolved into a collection of streamtubes with spatial variability in NAPL saturation along each streamtube integrated and transformed into an effective NAPL content for each streamtube. The distribution of NAPL contents among the streamtubes (NAPL architecture) controlled dissolution dynamics. Two simplified models, a streamtube model and an effective Damkohler number model, were investigated for their ability to simulate dissolution dynamics.