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Successful in situ chemical oxidation (ISCO) applications require real-time monitoring to assess the oxidant delivery and treatment effectiveness, and to support rapid and cost-effective decision making. Existing monitoring methods often suffer from poor spatial coverage given a limited number of boreholes in most field conditions. The ionic nature of oxidants (e.g., permanganate) makes time-lapse electrical resistivity tomography (ERT) a potential monitoring tool for ISCO. However, time-lapse ERT is usually limited to qualitative analysis because it cannot distinguish between the electrical responses of the ionic oxidant and the ionic products from contaminant oxidation. This study proposed a real-time quantitative monitoring approach for ISCO by integrating time-lapse ERT and physics-based reactive transport models (RTM). Moving past common practice, where an electrical-conductivity anomaly in an ERT survey would be roughly linked to concentrations of anything ionic, we used PHT3D as our RTM to distinguish the contributions from the ionic oxidant and the ionic products and to quantify the spatio-temporal evolution of all chemical components. The proposed approach was evaluated through laboratory column experiments for trichloroethene (TCE) remediation. This ISCO experiment was monitored by both time-lapse ERT and downstream sampling. We found that changes in inverted bulk electrical conductivity, unsurprisingly, did not correlate well with the observed permanganate concentrations due to the ionic products. By integrating time-lapse ERT and RTM, the distribution of all chemical components was satisfactorily characterized and quantified. Measured concentration data from limited locations and the non-intrusive ERT data were found to be complementary for ISCO monitoring. The inverted bulk conductivity data were effective in capturing the spatial distribution of ionic species, while the concentration data provided information regarding dissolved TCE. Through incorporating multi-source data, the error of quantifying ISCO efficiency was kept at most 5 %, compared to errors that can reach up to 68 % when relying solely on concentration data., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

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 (S N ) and hydraulic conductivity (K). The DCIP-estimated K/S N 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/S N fields, while integrating DCIP data with sparse but accurate borehole data results in a high resolution characterization of the SZA., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Non-aqueous phase liquid (NAPL) leakage poses serious threats to human health and the environment. Understanding NAPL migration and distribution in subsurface systems is crucial for developing effective remediation strategies. Multiphase flow modeling is an important tool to quantitatively describe the NAPL migration process in the subsurface. However, most multiphase flow models are built for temperatures typical of warmer climates and above freezing conditions, only considering two phases (water-NAPL) or three phases (air-water-NAPL). To date, few studies simulate NAPL migration in a four-phase system (ice-air-water-NAPL), which would be more appropriate for cold regions. In this study, we developed a coupled non-isothermal multiphase transport model to quantitatively describe NAPL migration in a four-phase (ice, gas, water, NAPL) system. The ice phase was added in the continuity equations and the constitutive relationship between unfrozen water content and temperature was applied to solve the energy and flow equations. The developed mathematical model was evaluated using a two-dimensional experiment under freeze-thaw cycles (FTCs) with an R 2  = 0.8803 between the simulated and observed NAPL saturation. Next, we evaluated the effect of freezing-induced changes in pressure and density between LNAPL and DNAPL on NAPL distribution under freeze-thaw condition. Simulation results show that ignoring the impact of ice formation and thawing during freeze-thaw cycles for LNAPL and DNAPL transport simulations can result in up to a 48% and 13% difference in model predictions of local NAPL saturations respectively, affecting model predictions of overall NAPL spatial distributions and potentially predicted remediation effectiveness., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

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., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The widespread presence of entrapped dense non-aqueous phase liquid (DNAPL) in the subsurface poses a continuing challenge to groundwater remediation. Cost-effective and high-resolution subsurface characterization is a critical issue for further DNAPL recovery due to the complexity of DNAPL source zone architecture (SZA). Geophysical techniques provide a noninvasive, spatially continuous and cost-effective way for monitoring the DNAPL remediation process. In particular, the spectral induced polarization (SIP) method has shown great potential in environmental problems. In this study, we performed real-time SIP measurements on DNAPL contaminated soil in columns to quantitatively assess the ability of SIP method for monitoring surfactant-enhanced DNAPL remediation process. Chemical data was simultaneously collected during the remediation process to verify the results obtained by SIP method. Taking account into the variations of subsurface environment, we conducted a series of column flushing experiments under different flow rate, surfactant concentrations and fluid salinities. The results highlight that SIP method is able to effectively monitor the DNAPL remediation process, as well as to evaluate the remediation efficiency under different conditions. The variations in the flow rate, the concentration of surfactant and the salinity of pore water not only affect remediation effectiveness, but also have an impact on the SIP signatures. This study shows that SIP performs better for monitoring DNAPL remediation at a relatively low flow rate of ~ 0.4 m/d, low surfactant concentration of 5000 mg/L and high salinity of 1.0 S/m, with an error of saturation estimation (RMSE S ) <0.1., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Laboratory saturated columns packed with granular limestone grains were used to explore the retention and remobilization of functional bacteria FA1 under various physicochemical conditions. The unique surface properties of limestone and FA1 caused some unexpected phenomena. Solution IS, cation type, temperature and surface biological property all affected FA1 retention in the columns. The IS effect was temperature dependent and initial solution pH showed little influence due to the strong buffering ability of limestone. Perturbations of solution IS caused slight release of previously retained bacteria in some columns with NaCl as the background electrolyte, while increase in flow rate caused no release at all. When CaCl 2 was the background, bacterial remobilization only occurred following both cation exchange and IS reduction. DLVO forces incorporating with surface roughness calculation were determined to assist with interpretation of interaction mechanisms. All the experimental evidences suggest the importance of cation bridging, cation exchange, surface roughness, and hydrophobic interaction in controlling bacterium transport in saturated limestone porous media., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Precise delineation of contaminant plume distribution is essential for effective remediation of contaminated sites. Traditional in situ investigation methods like direct-push (DP) sampling are accurate, but are usually intrusive and costly. Electrical resistivity tomography (ERT) method, as a non-invasive geophysical technique to map spatiotemporal changes in resistivity of the subsurface, is becoming increasingly popular in environmental science. However, the resolution of ERT for delineation of contaminant plumes still remains controversial. In this study, ERT and DP technique were both conducted at a real inorganic contaminated site. The reliability of the ERT method was validated by the direct comparisons of their investigation results that the resistivity acquired by ERT method is in accordance with the total dissolved solid concentration in groundwater and the overall variation of the total iron content in soil obtained by DP technique. After testifying the applicability of ERT method for contaminant identification, the extension of contaminant plume at the study site was revealed by supplementary ERT surveys conducted subsequently in the surrounding area of the contaminant source zone.

In this work, column experiments were conducted to investigate the transport characteristics of graphene oxide (GO) nanoparticles in limestone media under various electrolytes, solution pH, and humic acid (HA) concentration conditions. In the limestone media, GO exhibited relatively low mobility with the mass recovery rate lower than 65.2%, even when solution ionic strength was low. The presence of HA enhanced its mobility. In addition, the presence of S 2- , a divalent anion, also promoted GO transport in limestone media compared to Cl - under similar ionic strength conditions through neutralizing more positive charge and thus diminishing the cation bridging. Solution pH showed slight effect on the transport of GO in limestone with the mass recovery range from 40.3% to 51.7%. Over all, decreases in solution pH, HA concentration and increases in solution ionic strength reduced the mobility of GO in the limestone media under the tested conditions. These results indicated both environmental conditions and media characteristics played important roles in controlling GO fate and transport in porous media. The one-site kinetic deposition model was applied to describe the interactions between the GO and limestone media and model simulations fitted the observed experimental data very well. As limestone is an important component of aquiferous media in subsurface, findings from this study elucidated the key factors and processes controlling the fate of GO particles in limestone media, which can inform the prediction and assessment of the risks of GO in groundwater environment., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Understanding the fate and transport of antibiotics in porous media can help reduce their contamination risks to soil and groundwater systems. In this work, batch and column experiments were conducted to determine the interactions between two representative antibiotics, sulfacetamide (SA) and levofloxacin (LEV), and sand porous media under various solution pH, humic acid (HA) concentration, grain size, and moisture content conditions. Batch sorption experimental results indicated that the sand had relatively strong bonding affinity to LEV, but little sorption of SA under different pH, HA concentration, grain size conditions. Results from the packed sand column experiments showed that SA had extremely high mobility in the porous media for all combinations of pH, HA concentration, grain size, and moisture content. The mass recovery of SA was higher than 98.5% in all the columns with the exception of the one packed with fine sand (97.2%). The retention of LEV in the columns was much higher and the recovery rates ranged from 0% to 71.1%. Decreases in solution pH, HA concentration, grain size, or moisture content reduced the mobility of LEV in the columns under the tested conditions. These results indicated that type of antibiotics and environmental conditions also played an important role in controlling their fate and transport in porous media. Mathematical models were applied to simulate and interpret experimental data, and model simulations described the interactions between the two antibiotics and sand porous media very well. Findings from this study elucidated the key factors and processes controlling the fate of SA and LEV in porous media, which can inform the prediction and assessment of the environmental risks of antibiotics., (Copyright © 2016 Elsevier B.V. All rights reserved.)

The potential for rice husk (RH) and wood chip (WC) biochars to remove levofloxacin (LEV) from aqueous solution was evaluated. The physical and chemical properties of the biochars were characterized using various tools and techniques. Furthermore, batch sorption experiments were conducted to determine the sorption ability of the biochars to LEV. The pseudo-second order kinetic model described the sorption kinetic data better than the pseudo-first order kinetic model and the Elovich equation because the process involved both surface adsorption and pore diffusion. For the isotherms, the Langmuir equation fitted the data better than the Freundlich equation. The maximum Langmuir sorption capacities of the biochars to LEV ranged from 1.49 to 7.72 mg g(-1). Thermodynamic parameters obtained from the experiments showed that the adsorption of LEV onto the WC biochar was spontaneous and exothermic, while its adsorption onto the RH biochar was spontaneous and endothermic under tested conditions. A mixture of 0.025 M phosphate buffer (80%, pH 3.0) and acetonitrile (20%) effectively desorbed the LEV from the biochars with a recovery rate up to 80%. Findings from this work indicate that biochars can be used as an alternative adsorbent to effectively remove emerging contaminants including LEV from aqueous solutions., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Accurately predicting the fate and transport of graphene oxide (GO) in porous media is critical to assess its environmental impact. In this work, sand column experiments were conducted to determine the effect of input concentration and grain size on transport, retention, and size perturbation of GO in saturated porous media. The mobility of GO in the sand columns reduced with decreasing grain size and almost all GO were retained in fine sand columns for all of the tested conditions. This result can be explained with colloid filtration and XDLVO theories. Input concentration also influenced the retention and transport of GO in the sand columns because of the 'blocking' mechanism that reduces the particle retention rate. After passing through the column, average GO sizes increased dramatically. In addition, the sizes of GO retained in the sand also increased with travel distance. These results suggested that transport through the porous media induced GO aggregation. A mathematical model based on the advection-dispersion equation coupled with the second-order kinetics to reflect the blocking effect simulated the experimental data well.