Dense Nonaqueous Phase Liquid Saturation Research Articles

Coupling of radon and microbial analysis for dense non-aqueous-phase liquid tracing and health risk assessment in groundwater under seasonal variations

Dense non-aqueous-phase liquids (DNAPLs) represent one of the most hazardous contaminants of groundwater, posing health risks to humans. Radon is generally used to trace DNAPLs; however, external factors, such as rainfall or stream water, can influence its efficacy. To overcome these limitations, this study pioneered the integration of radon and microbial community structures to explore DNAPL tracing and natural attenuation in the context of seasonal variations for human health risk assessments. The results showed that a radon tracer can estimate DNAPL saturation in the source zone, especially during the dry season when radon deficiency predominates. However, samples exhibited mixing effects during the wet season because of local precipitation. Moreover, bioremediation and low health risks were observed in the plume boundary zone, indicating that microbial dechlorination was a predominant factor determining these risks. The abnormal patterns of radon observed during the wet season can be elucidated by examining microbiological communities. Consequently, a combined approach employing radon and microbial analysis is advocated for the boundary zone, albeit with a less intensive management strategy, compared with that for the source zone. This novel coupling method offers a theoretical and practical foundation for managing DNAPL-contaminated groundwater.

Characterization of DNAPL source zones in clay-sand media via joint inversion of DC resistivity, induced polarization and borehole data

Toxic organic contaminants in groundwater are pervasive at many industrial sites worldwide. These contaminants, such as chlorinated solvents, often appear as dense non-aqueous phase liquids (DNAPLs). To design efficient remediation strategies, detailed characterization of DNAPL Source Zone Architecture (SZA) is required. Since invasive borehole-based investigations suffer from limited spatial coverage, a non-intrusive geophysical method, direct current (DC) resistivity, has been applied to image the DNAPL distribution; however, in clay-sand environments, the ability of DC resistivity for DNAPLs imaging is limited since it cannot separate between DNAPLs and surrounding clay-sand soils. Moreover, the simplified parameterization of conventional inversion approaches cannot preserve physically realistic patterns of SZAs, and tends to smooth out any sharp spatial variations. In this paper, the induced polarization (IP) technique is combined with DC resistivity (DCIP) to provide plausible DNAPL characterization in clay-sand environments. Using petrophysical models, the DCIP data is utilized to provide tomograms of the DNAPL saturation (SN) and hydraulic conductivity (K). The DCIP-estimated K/SN tomograms are then integrated with borehole measurements in a deep learning-based joint inversion framework to accurately parameterize the highly irregular SZA and provide a refined DNAPL image. To evaluate the performance of the proposed approach, we conducted numerical experiments in a heterogeneous clay-sand aquifer with a complex SZA. Results demonstrate the standalone DC resistivity method fails to infer the DNAPL in complex clay-sand environments. In contrast, the combined DCIP technique provides the necessary information to reconstruct the large-scale features of K/SN fields, while integrating DCIP data with sparse but accurate borehole data results in a high resolution characterization of the SZA.

Representative Elementary Volume Estimation and Neural Network-Based Prediction of Change Rates of Dense Non-Aqueous Phase Liquid Saturation and Dense Non-Aqueous Phase Liquid–Water Interfacial Area in Porous Media

Investigation of the change rate for contaminant parameters is important to characterize dense non-aqueous phase liquid (DNAPL) transport and distribution in groundwater systems. In this study, four experiments of perchloroethylene (PCE) migration are conducted in two-dimensional (2D) sandboxes to characterize change rates of PCE saturation (So) and PCE–water interfacial area (AOW) under different conditions of salinity, surface active agent, and heterogeneity. Associated representative elementary volume (REV) of the change rate of So (So rate) and change rate of AOW (AOW rate) is derived over the long-term transport process through light transmission techniques. REV of So rate (SR-REV) and REV of AOW rate (AR-REV) are estimated based on the relative gradient error (εgi). Regression analysis is applied to investigate the regularity, and a model based on a back-propagation (BP) neural network is built to simulate and predict the frequencies of SR-REV and AR-REV. Experimental results indicated the salinity, surface active agent, and heterogeneity are important factors that affect the So rate, AOW rate, SR-REV, and AR-REV of the PCE plume in porous media. The first moment of the PCE plume along the vertical direction is decreased under conditions of high salinity, surface active agent, and heterogeneity, while these factors have different effects on the second moment of the PCE plume. Compared with the salinity and surface active agent, heterogeneity has the greatest effect on the GTP, the distributions of the So rate and AOW rate along the depth, and dM, dI. For SR-REV, the standard deviation is increased by the salinity, surface active agent, and heterogeneity. Simultaneously, the salinity and heterogeneity lead to lower values of the mean value of SR-REV, while the surface active agent increases the mean value of SR-REV. However, the mean and standard deviation of AR-REV have no apparent difference under different experimental conditions. These findings reveal the complexity of PCE transport and scale effect in the groundwater system, which have important significance in improving our understanding of DNAPL transport regularity and promoting associated prediction.

Evaluation of the benefits of improved permeability estimation on high-resolution characterization of DNAPL distribution in aquifers with low-permeability lenses

High-resolution characterization of dense non-aqueous phase liquid (DNAPL) source zone architecture (SZA) is crucial for developing remediation strategies. Inverse modeling approaches are widely used to characterize DNAPL SZA. However, unknown parameters (permeability and DNAPL saturation) are usually assumed as Gaussian distribution in traditional geostatistical inverse methods (e.g., ensemble smoother with multiple data assimilation, ESMDA). This assumption may not be true in channels of fluvial deposits. The presence of clay lenses will bring significant challenges in reconstructing the DNAPL SZA using geostatistical inverse methods based on the Gaussian assumption. Moreover, the DNAPL characterization also suffers from a limited number of borehole data in the field. In this study, we use ESMDA's variant, ensemble smoother with multiple data assimilation-direct sampling (ESMDA-DS), to improve the estimation of non-Gaussian permeability field and evaluate the benefits of improved permeability estimation on the reconstruction of DNAPL source zone. The inversion technique is based on the iterative inversion framework to incorporate the clay content information into the DNAPL characterization. The performance of our proposed framework is examined and discussed through a numerical synthetic case with challenging pool-dominated SZA. To overcome data scarcity, we integrated hydrogeological and geophysical (electrical resistance tomography) datasets. Results show that the permeability is characterized well using ESMDA-DS method compared with ESMDA method. With the improved permeability estimation, the DNAPL source zone can be characterized in higher resolution. Compared with ESMDA method, the root mean square error (RMSE) of permeability is reduced by 38.5% using the ESMDA-DS method. Then the estimation RMSE of DNAPL saturation is reduced by 24.9% by improved permeability estimation. We also demonstrated the significant benefits of improved permeability estimation on DNAPL depletion behavior and plume evolution. Numerical simulations demonstrate with the improved permeability estimation, the DNAPL depletion prediction is highly improved, the prediction RMSE of the DNAPL dissolved plume is reduced by 34.5% after 50 years.

Integrating deep learning-based data assimilation and hydrogeophysical data for improved monitoring of DNAPL source zones during remediation

Data assimilation techniques allow the integration of multi-source data with physical modeling of dense nonaqueous phase liquid (DNAPL) source zones to monitor their evolution in time and thereby improve remediation efforts. The DNAPL source zone is governed by multiphase physics and its architecture is usually highly irregular and nonstationary. Traditional data assimilation methods use stationary models to describe these nonstationary DNAPL saturation fields, leading to significant errors in the estimation of unknown source zone architectures (SZAs). In this study, we propose a geostatistical data assimilation method to improve performance monitoring of DNAPL remediation. We estimate the DNAPL SZA after parameterizing the DNAPL saturation field using a deep learning method instead of a stationary statistical model. First, we train a convolutional variational autoencoder (CVAE) network to capture the physics of DNAPL infiltration and depletion. Then, we incorporate the CVAE network within the Ensemble Kalman filter (EnKF) to resolve the evolving DNAPL SZA by assimilating time-lapse hydrogeophysical measurements (i.e., oscillatory hydraulic tomography, downgradient dissolved DNAPL concentration, and electrical resistivity tomography). To assess the proposed CVAE-EnKF framework's performance, we conducted numerical experiments with evolving DNAPL SZAs in a 2D heterogeneous aquifer. Results show that the proposed framework significantly improved DNAPL saturation estimates throughout the source zone over time, compared to the standard EnKF method. CVAE-EnKF reduced the estimation error of DNAPL mass remediated by 51% from EnKF, along with better predictions of source zone longevity. It also better captured the morphology and center/spread of mass of the evolving remediated portions of the source zone and provided better estimates of pooled-DNAPL mass. Furthermore, the CVAE-EnKF method is more stable and converges faster than EnKF alone. Overall, the proposed data assimilation framework can improve real-time monitoring of DNAPL remediation and risk analysis.

Integrating hydraulic tomography, electrical resistivity tomography, and partitioning interwell tracer test datasets to improve identification of pool-dominated DNAPL source zone architecture

High-resolution characterization of complex dense non-aqueous phase liquid (DNAPL) contaminated sites is crucial for developing effective remediation strategies. The DNAPL source zone is usually characterized by hydraulic/partitioning tracer tomography (HPTT). However, the HPTT method may fail to capture the highly saturated pool-dominated DNAPL source zone architecture (SZA), because partitioning tracers tend to bypass the low-permeability zones where the pool DNAPL accumulates, resulting in a low-resolution DNAPL estimation. With a limited number of measurements, the estimation errors may be significant. To overcome these difficulties, time-lapse electrical resistivity tomography (ERT) was integrated with the partitioning interwell tracer test (PITT) and hydraulic tomography (HT) to characterize the pool-dominated DNAPL SZA. Herein, we proposed an iterative joint inversion framework coupling the multiphase flow model with the ERT forward model to estimate the heterogeneous permeability distribution and DNAPL SZA. Under this framework, permeability was estimated using the hydraulic head data from HT in stage 1, and the DNAPL SZA was subsequently estimated by assimilating both the PITT and ERT observations in stage 2. The permeability estimated from stage 1 was used as prior information for stage 2, and the DNAPL saturation estimated from stage 2 was served as prior information for stage 1 in the next loop to form an iterative loop to improve the estimation of both permeability and DNAPL SZA. The iterative joint inversion framework was evaluated in two numerical experiments with different heterogeneous structures by assimilating multi-source datasets, including hydraulic head, partitioning interwell tracer concentration, and electrical resistivity. Results show that with limited measurements of HPTT method, one can roughly capture the DNAPL distribution, missing the fine structure of the DNAPL SZA. In contrast, by incorporating multi-source datasets, the heterogeneous permeability and DNAPL SZA can be reconstructed with a higher resolution. Furthermore, the inversion accuracy of the DNAPL SZA improves progressively as the iteration proceeds, which demonstrates the advantage of utilizing complementary information from permeability and DNAPL distribution through the iteration framework. Comparing with the results without loop iteration, the estimation error is reduced by 17.3% for permeability and 8.6% for DNAPL saturation in Experiment 1; by 14.7% for permeability and 11.2% for DNAPL saturation in Experiment 2 through the iterative framework. To further evaluate our framework, we preformed the prediction of the depletion process of the DNAPL source zone and plume based on the estimated DNAPL SZA. Results show that using the iterative framework, the prediction of the SZA depletion is greatly improved, i.e., the estimation error of the dissolved downstream plume from the DNAPL source zone after 3 years is reduced by 20.9% in Experiment 1, and by 43.2% in Experiment 2, respectively, through the iterative framework. This significant improvement is because the iterative method can better capture the spread of DNAPL pool.

Hydrogeophysical Characterization of Nonstationary DNAPL Source Zones by Integrating a Convolutional Variational Autoencoder and Ensemble Smoother

AbstractDetailed characterization of dense nonaqueous phase liquid (DNAPL) source zone architecture (SZA) is essential for designing efficient remediation strategies. However, it is difficult to characterize a highly irregular and localized SZA, because traditional drilling investigations provide limited information. With limited data, the estimation accuracy of traditional geostatistical methods is strongly affected by the parameterization of the prior description of the SZA. To improve characterization performance, we parameterized the DNAPL saturation field using a physics‐based approach. We trained a convolutional variational autoencoder (CVAE) using data from multiphase modeling that captures the physics of DNAPL infiltration. The trained CVAE network was used in SZA inversion to obtain an improved prior DNAPL saturation field, instead of the typical stationary prior covariances. We then integrated the CVAE network into an iterative ensemble smoother (ES), to formulate a joint inversion framework. To overcome difficulties from limited/sparse data, we incorporated hydrogeological and geophysical datasets in the proposed inversion framework. To evaluate the performance of our method, we conducted numerical experiments in a hypothetical heterogeneous aquifer with an intricate SZA. The results show that the CVAE was an effective and efficient parameterization method which can capture the DNAPL infiltration patterns better than a Gaussian prior. The improved prior, combined with multisource datasets, can result in better resolution, and overall improved SZA characterization. In contrast to the standard ES method, the proposed framework reconstructed the SZA more accurately. We also demonstrated that DNAPL depletion behavior and dissolved concentration profiles can be predicted accurately using the estimated SZA.

Towards predicting DNAPL source zone formation to improve plume assessment: Using robust laboratory and numerical experiments to evaluate the relevance of retention curve characteristics

We conducted multiple laboratory trials in a robust and repeatable experimental layout to study dense non-aqueous phase liquid (DNAPL) source zone formation. We extended an image processing and analysis framework to derive DNAPL saturation distributions from reflective optical imaging data, with volume balance deviations < 5.07%. We used a multiphase flow model to simulate source zone formation in a Monte Carlo approach, where the parameter space was defined by the variation of retention curve parameters. Integral and geometric measures were used to characterize the source zones and implemented into a multi-criteria objective function. The latter showed good agreement between observation data and simulation results for effective DNAPL saturation values > 0.04, especially for early stages of DNAPL migration. The common hypothesis that parameters defining the DNAPL-water retention curves are constant over time was not confirmed. Once DNAPL pooling started, the optimal fit in the parameter space was significantly different compared to the earlier DNAPL migration stages. We suspect more complex processes (e.g., capillary hysteresis, adsorption) to become relevant during pool formation. Our results reveal deficits in the grayscale-DNAPL saturation relationship definition and laboratory estimation of DNAPL-water retention curve parameters to overcome current limitations to describe DNAPL source zone formation.

Improved Characterization of DNAPL Source Zones via Sequential Hydrogeophysical Inversion of Hydraulic‐Head, Self‐Potential and Partitioning Tracer Data

AbstractHigh‐resolution characterization of hydraulic properties and dense nonaqueous phase liquid (DNAPL) contaminant source is crucial to develop efficient remediation strategies. However, DNAPL characterization suffers from a limited number of borehole data in the field, resulting in a low‐resolution estimation. Moreover, high‐resolution DNAPL characterization requires a large number of unknowns to be estimated, presenting a computational bottleneck. In this paper, a low‐cost geophysical approach, the self‐potential method, is used as additional information for hydraulic properties characterization. Joint inversion of hydraulic head and self‐potential measurements is proposed to improve hydraulic conductivity estimation, which is then used to characterize the DNAPL saturation distribution by inverting partitioning tracer measurements. The computational barrier is overcome by (a) solving the inversion by the principal component geostatistical approach, in which the covariance matrix is replaced by a low‐rank approximation, thus reducing the number of forward model runs; (b) using temporal moments of concentrations instead of individual concentration data points for faster forward simulations. To assess the ability of the proposed approach, numerical experiments are conducted in a 3‐D aquifer with 104 unknown hydraulic conductivities and DNAPL saturations. Results show that with realistic DNAPL sources and a limited number of hydraulic heads, the traditional hydraulic/partitioning tracer tomography roughly reconstructs subsurface heterogeneity but fails to resolve the DNAPL distribution. By adding self‐potential data, the error is reduced by 24% in hydraulic conductivity estimation and 68% in DNAPL saturation characterization. The proposed sequential inversion framework utilizes the complementary information from multi‐source hydrogeophysical data sets, and can provide high‐resolution characterizations for realistic DNAPL sources.

Remediation of trapped DNAPL enhanced by SDS surfactant and silica nanoparticles in heterogeneous porous media: experimental data and empirical models.

The remediation of nonaqueous phase liquids (NAPLs) enhanced by surfactant and nanoparticles (NP) has been investigated in numerous studies. However, the role of NP-assisted surfactants in the dissolution process is still not well discussed. Besides, there is a lack of empirical dissolution models considering the effects of initial residual saturation Strap, NAPL distribution, and surfactant concentration in NAPL-aqueous phase systems. In this work, micromodel experiments are conducted to quantify mass transfer coefficients for different injected aqueous phases including deionized water, SDS surfactant solutions, and NP-assisted solutions with different levels of concentrations and flow rates. Observations reveal that silica nanoparticles (SNP) can significantly enhance interphase mass transfer, while SDS surfactant reduces the mass transfer coefficient. In addition, Strap and intrinsic interfacial area ai, as an indicator of dense nonaqueous phase liquids (DNAPL) distribution, influence the interphase mass transfer. The ai is also independent of DNAPL saturation SNAPL except for SNAPL < 7% when ganglia breakup occurs. Based on these observations, new empirical dissolution models are proposed in the presence and the absence of SDS surfactant and SNP in which ai, Strap, and surfactant concentrations are introduced as new parameters. The evaluated mass transfer rate coefficients using the proposed models show a significant improvement compared to available empirical models. The finding of this study might be attractive for application in field-scale simulations of surfactant-enhanced aquifer remediation (SEAR) and NP-assisted methods.

Quantification of Uncertainties from Image Processing and Analysis in Laboratory-Scale DNAPL Release Studies Evaluated by Reflective Optical Imaging

Subsurface DNAPL (dense non-aqueous phase liquid) contamination from (un-) intentional spilling typically leads to severe environmental hazards. A large number of studies have demonstrated the relevance of DNAPL source zone geometry for the determination of contaminant plume propagation in groundwater. Optical imaging represents a promising non-invasive method for identifying DNAPL saturation without disturbing multiphase flow dynamics. However, workflow and image analysis methodologies have not been sufficiently developed or described for general application to related experimental efforts. For example, the choice of dye(s) used for phase colorization affects image processing and can bias final estimations of DNAPL saturations. In this study, we perform a series of DNAPL migration and entrapment studies in transparent tanks that are filled with three different types of porous media. Different dyes are used and raw images are acquired. Subsequently, these are used to evaluate a suite of image processing and analysis approaches, which are organized into a workflow. Our approach allows for us to identify key image processing and analysis steps that introduce the most error. Applicable dye configurations led to uncertainties of up to 41% depending on the selection of processing steps. Based on these findings, it was possible to delineate a flexible framework for image processing and analysis that has the potential for transfer and application in other tank experiment setups.

Coupled hydrogeophysical inversion of DNAPL source zone architecture and permeability field in a 3D heterogeneous sandbox by assimilation time-lapse cross-borehole electrical resistivity data via ensemble Kalman filtering

Characterization of dense non-aqueous phase liquid (DNAPL) distribution is important to facilitate the decision of remediation strategies. However, it is still a great challenge to characterize DNAPL source zone architecture with high resolution due to subsurface heterogeneity and relatively sparse data from traditional hydrogeological investigations. To overcome difficulties from such sparse data, electrical resistivity tomography (ERT) is introduced to locate DNAPL using time-lapse cross-borehole measurements. Due to the significant impact of geological heterogeneity on DNAPL source zone architecture, a data assimilation framework based on the coupled multiphase fluids-ERT model is developed to jointly invert DNAPL saturation and the permeability field using time-lapse ERT data. To validate the efficiency and performance of this framework, synthetic and laboratory experiments are both performed to monitor DNAPL migration and distribution in 3D heterogeneous sandbox with cross-borehole ERT. Result shows that time-lapse ERT and direct inversion can map the evolution of the DNAPL plume but loses details regarding the plume morphology due to the over-smoothing caused by geophysical inversion using an isotropic and homogeneous roughness-based regularization procedure. By contrast, the coupled inversion is successful to characterize both the permeability field and the evolution of the DNAPL plume with a higher resolution. This is because the coupled inversion is able to directly translate raw geophysical data into hydrologic meaningful information and therefore avoid artifacts caused by direct geophysical inversion.

An empirical model for the evaluation of the dissolution rate from a DNAPL-contaminated area.

This paper investigates dynamic variation in the morphologic distribution of dense non-aqueous phase liquids (DNAPLs), which take into account the coupled mass transfer. Experiments were carried out in a 2D tank representing a reconstructed aquifer model. DNAPL dissolution rates were investigated over a wide range of DNAPL saturations, several source configurations, and different hydraulic conditions. Morphometric indexes are presented that take into consideration further factors affecting the dissolution process. Local information regarding transport parameters related to the characteristics of the medium was obtained through a neural network and an optimization algorithm applied to experimental tracer tests. The history of DNAPL source architecture, in terms of saturation, indentation grade, and orientation, was determined by image analysis. Dissolved concentrations were registered and mass transfer rate coefficients were obtained for a wide range of source-zone configurations. A statistical analysis was performed to develop a constitutive equation that is descriptive of the mass transfer rate as a function of source-zone metric characteristics. A new empirical dissolution model using the proposed morphometric parameters is presented and compared with other models. The mass transfer correlation reported incorporates morphometric parameters and considers the complex and variable architecture of non-miscible contaminants. The proposed correlation can be used for an initial assessment of non-aqueous phase liquid (NAPL) dissolution rates over a wide range of saturation (residual and non-residual) conditions and different aqueous phase velocities within the NAPL source zone.

Assessment of flushing methods for the removal of heavy chlorinated compounds DNAPL in an alluvial aquifer

Immiscible mobilization and foam flushing were assessed as low surfactant consuming technologies, for the enhanced recovery of dense non-aqueous phase liquid (DNAPL) residual at a site contaminated by heavy chlorinated compounds. Preliminary experiments in well-controlled conditions demonstrated the phenomena involved in these remediation technologies and their limitations. Furthermore, we characterized the technologies according to by their surfactant consumption (per kg of DNAPL recovered) and the final DNAPL saturation reached. Surfactant foam flushing (SFF) produced lower DNAPL saturation than immiscible mobilization, thanks to its higher viscosity. However, its efficiency is strongly correlated to the pressure gradient (▽P) used during injection, and that is limited by risks of soil fracturing. The two technologies were tested in field cells (10m×10m×10m) delimited by cement/bentonite walls anchored in the clayey substratum. The deepest soil layer was the most contaminated. It was composed of silt-sandy soil and had an average hydraulic conductivity of 10−4ms−1. Field results show that we should now model flushing fluid propagation to design efficient set-ups for recovering the displaced DNAPL.

Estimation of representative elementary volume for DNAPL saturation and DNAPL-water interfacial areas in 2D heterogeneous porous media

Representative elementary volume (REV) is important to determine properties of porous media and those involved in migration of contaminants especially dense nonaqueous phase liquids (DNAPLs) in subsurface environment. In this study, an experiment of long-term migration of the commonly used DNAPL, perchloroethylene (PCE), is performed in a two dimensional (2D) sandbox where several system variables including porosity, PCE saturation (Soil) and PCE-water interfacial area (AOW) are accurately quantified by light transmission techniques over the entire PCE migration process. Moreover, the REVs for these system variables are estimated by a criterion of relative gradient error (εgi) and results indicate that the frequency of minimum porosity-REV size closely follows a Gaussian distribution in the range of 2.0mm and 8.0mm. As experiment proceeds in PCE infiltration process, the frequency and cumulative frequency of both minimum Soil-REV and minimum AOW-REV sizes change their shapes from the irregular and random to the regular and smooth. When experiment comes into redistribution process, the cumulative frequency of minimum Soil-REV size reveals a linear positive correlation, while frequency of minimum AOW-REV size tends to a Gaussian distribution in the range of 2.0mm–7.0mm and appears a peak value in 13.0mm–14.0mm. Undoubtedly, this study will facilitate the quantification of REVs for materials and fluid properties in a rapid, handy and economical manner, which helps enhance our understanding of porous media and DNAPL properties at micro scale, as well as the accuracy of DNAPL contamination modeling at field-scale.

QUANTIFICATION OF DENSE NONAQUEOUS PHASE LIQUID SATURATION IN DOUBLE-POROSITY SOIL MEDIA USING A LIGHT TRANSMISSION VISUALIZATION TECHNIQUE

In this research, the light transmission visualization (LTV) technique was used to measure the dense nonaqueous phase liquid (DNAPL) saturation distribution in a two-dimensional (2-D) flow chamber packed with double-porosity soil medium. This, to the best of our knowledge, is a new application of LTV in measuring DNAPL saturation as well as monitoring its migration in double-porosity soil media. The double-porosity structure was created using layers of fine silica sand and solidified kaolin clay spheres. Tetrachloroethylene (PCE) was used to simulate DNAPL and was dyed with Oil-Red-O for better visualization. Known amounts of PCE were injected into the flow chamber before being correlated to amounts calculated using image analysis based on the LTV method. A strong correlation having an R2 value of 0.994 was found between the injected PCE volumes and calculated PCE volumes obtained from the LTV method. For comparative purposes, the same experiment was carried out by filling the flow chamber with local silica sand as a single-porosity medium to investigate the influence of soil structure on DNAPL migration. Results, again, showed a strong correlation, with an R2 value of 0.996, between the amounts of PCE injected into the flow chamber and the calculated amounts of PCE. A significant difference in the migration of PCE in the two experiments was observed as the rate of PCE migration in the double-porosity medium was much faster compared to the migration rate in the single-porosity medium. This finding is most likely due to the occurrence of interaggregate pores in the double-porosity soil. This research proves that the noninvasive and nonintrusive LTV technique can be used to quantify DNAPL saturation in double-porosity soil structure in 2-D, two-phase systems.

Quantitative assessment of electrical resistivity tomography for monitoring DNAPLs migration – Comparison with high-resolution light transmission visualization in laboratory sandbox

Real-time monitoring of dense non-aqueous phase liquids (DNAPLs) migration and distribution is essential for the decision of an effective remediation strategy. Light transmission visualization (LTV) has shown its accuracy and efficiency for measuring DNAPLs saturation and water content in the laboratory, but it cannot be implemented in three dimensional sandbox or field-scale sites. Recently developed electrical resistivity tomography (ERT) has been applied in monitoring the migration and distribution of DNAPLs in bench- and field-scale studies. However, the evaluation of the ability of ERT for monitoring DNAPLs migration by a direct comparison of ERT with high-resolution techniques such as LTV within an experimental system is still lacking. Two sandbox experiments with different permeability conditions are conducted to quantitatively assess the capability of ERT for monitoring the DNAPLs migration. During the injections, LTV method is used to visualize the DNAPLs migration and provide high-resolution saturation data while ERT method is applied to capture the change of resistivity. The results from the comparison between LTV and ERT methods show that ERT is successful in detecting the accumulation and flow bypassing phenomenon around the low-permeability lenses, as well as the penetration through the high-permeability lenses. There is a fair correlation between the resistivity and saturation with overall correlation coefficients above 0.6, except at last stage. However, using classical regularization techniques (based on smoothness), the area of DNAPLs plume determined by ERT is commonly overestimated. Compared to the plume around the low-permeability lenses, the plume around the high-permeability lenses estimated by ERT is more extensive due to larger resistivity contrasts. In addition, ERT measurements indicate that the resistivity increase caused by the low-saturation DNAPLs is not apparent enough, which is likely to be covered up under the changing hydrogeochemical environments in field investigations.

Influence of flow velocity and spatial heterogeneity on DNAPL migration in porous media: insights from laboratory experiments and numerical modelling

Understanding the migration of dense non-aqueous phase liquids (DNAPLs) in complex subsurface systems is important for evaluating contamination source zones and designing remediation schemes after spill events. Six sandbox experiments were performed to explore the individual effect of flow velocity, and the combined effect of flow velocity and layered lenses on a DNAPL (PCE) migration in porous media. DNAPL saturation was measured using a light transmission system, and saturation distribution was quantified by spatial moments. The experimental results show that large flow velocity significantly promotes lateral and vertical migration of the low-viscosity DNAPL, while when layered lenses exist, the infiltration rate decreases and horizontal spread increases. Migration processes were numerically simulated, and the modelling results tested against experimental results. Furthermore, migration of DNAPLs with different viscosities was simulated to explore the combined effects of flow velocity and geological heterogeneity. Simulation results show that enhanced heterogeneity makes low-viscosity DNAPLs migrate along preferential pathways, resulting in irregular DNAPL morphology. Layered lenses combined with heterogeneity complicate the effect of flow velocity on the migration of low-viscosity DNAPLs by changing percolation paths. Results also demonstrate that flow velocity exhibits relatively little influence on the migration of medium/high-viscosity DNAPLs, which is predominantly controlled by viscosity and heterogeneity. Enhanced heterogeneity has a larger effect on migration behavior. Findings indicate that the migration paths and position of the source zone could change significantly, due to the combined effect of groundwater flow velocity and geological heterogeneity; thus, comprehensive hydrogeological investigation is needed to characterize the source zone.

Architecture, persistence and dissolution of a 20 to 45 year old trichloroethene DNAPL source zone

A detailed field-scale investigation of processes controlling the architecture, persistence and dissolution of a 20 to 45year old trichloroethene (TCE) dense non-aqueous phase liquid (DNAPL) source zone located within a heterogeneous sand/gravel aquifer at a UK industrial site is presented. The source zone was partially enclosed by a 3-sided cell that allowed detailed longitudinal/fence transect monitoring along/across a controlled streamtube of flow induced by an extraction well positioned at the cell closed end. Integrated analysis of high-resolution DNAPL saturation (Sn) (from cores), dissolved-phase plume concentration (from multilevel samplers), tracer test and permeability datasets was undertaken. DNAPL architecture was determined from soil concentration data using partitioning calculations. DNAPL threshold soil concentrations and low Sn values calculated were sensitive to sorption assumptions. An outcome of this was the uncertainty in demarcation of secondary source zone diffused and sorbed mass that is distinct from trace amounts of low Sn DNAPL mass. The majority of source mass occurred within discrete lenses or pools of DNAPL associated with low permeability geological units. High residual saturation (Sn>10–20%) and pools (Sn>20%) together accounted for almost 40% of the DNAPL mass, but only 3% of the sampled source volume. High-saturation DNAPL lenses/pools were supported by lower permeability layers, but with DNAPL still primarily present within slightly more permeable overlying units. These lenses/pools exhibited approximately linearly declining Sn profiles with increasing elevation ascribed to preferential dissolution of the uppermost DNAPL. Bi-component partitioning calculations on soil samples confirmed that the dechlorination product cDCE (cis-dichloroethene) was accumulating in the TCE DNAPL. Estimated cDCE mole fractions in the DNAPL increased towards the DNAPL interface with the uppermost mole fraction of 0.04 comparable to literature laboratory data. DNAPL dissolution yielded heterogeneous dissolved-phase plumes of TCE and its dechlorination products that exhibited orders of magnitude local concentration variation. TCE solubility concentrations were relatively localised, but coincident with high saturation DNAPL lens source areas. Biotic dechlorination in the source zone area, however, caused cDCE to be the dominant dissolved-phase plume. The conservative tracer test usefully confirmed the continuity of a permeable gravel unit at depth through the source zone. Although this unit offered significant opportunity for DNAPL bypassing and decreased timeframes for dechlorination, it still transmitted a significant proportion of the contaminant flux. This was attributed to dissolution of DNAPL–mudstone aquitard associated sources at the base of the continuous gravel as well as contaminated groundwater from surrounding less permeable sand and gravel horizons draining into this permeable conduit. The cell extraction well provided an integrated metric of source zone dissolution yielding a mean concentration of around 45% TCE solubility (taking into account dechlorination) that was equivalent to a DNAPL mass removal rate of 0.4tonnes per annum over a 16m2 cell cross sectional area of flow. This is a significant flux considering the source age and observed occurrence of much of the source mass within discrete lenses/pools. We advocate the need for further detailed field-scale studies on old DNAPL source zones that better resolve persistent pool/lens features and are of prolonged duration to assess the ageing of source zones. Such studies would further underpin the application of more surgical remediation technologies.

Steady State DNAPL Dissolution in Three-Dimensional Fractured Sandstone Network Experiments

The distribution of residual dense nonaqueous phase liquid (DNAPL) in the subsurface plays a critical role in the DNAPL dissolution kinetics. However, measuring residual DNAPL at the field scale in fractured bedrock settings is generally impractical. This research uses a three-dimensional (3D), bench-scale, fractured-rock network comprised of low-porosity sandstone to evaluate the dissolution kinetics of tetrachloroethylene (PCE) DNAPL at residual saturation during ambient groundwater conditions. To our knowledge, this work presents the first experiments to investigate DNAPL dissolution in 3D bench-scale fractured systems. DNAPL dissolution in the relatively uniform fracture network was evaluated and described using an effective parameter, the bulk mass transfer coefficient (KL). Results from dissolution experiments revealed a positive, statistically significant correlation between KL and DNAPL-water interfacial area, and between KL and DNAPL saturation, analogous to porous media experiments. While aperture size and uniformity influenced DNAPL trapping and interfacial area in the fracture network experiments, DNAPL-altered aperture size did not have a statistically significant influence on dissolution rates. The mass transfer behavior for our 3D fracture network was more similar to one-dimensional (1D) porous media experiments than to two-dimensional (2D) and 3D porous media experiments, which primarily used nonaqueous phase liquid (NAPL) pools. This result is likely due to a combination of the coexistence of the nonwetting NAPL phase and the flowing-aqueous phase in the larger fractures or at fracture intersections, as well as better mixing due to dynamic flow pathways in the network. Finally, residual NAPL saturations could not be replicated in the networks, possibly due to the unpredictable flow-switching behavior of multiphase fluids in fractured rock.