Pump-and-treat (P&T) vs groundwater circulation wells (GCW): Which approach delivers more sustainable and effective groundwater remediation?

Synergistic approach of GCW-ISTR for enhanced remediation of semi-volatile organic contaminants in groundwater: Modeling and experimental validation

The poor remediation performance of groundwater circulation well (GCW) on semi-volatile organic contaminants (such as aniline) has severely limited its practical application. To address the challenges posed by the low volatility and solubility of these contaminants, an innovative integration of GCW with in-situ thermal remediation (ISTR) was proposed to create a thermal enhanced circulation well (GCW-ISTR) in this study. Laboratory experiments and model simulations were performed to evaluate the heat transfer and enhanced remediation effect by GCW-ISTR. Results demonstrate that the heat transfer process is controlled by the water circulation around GCW-ISTR and is influenced by factors such as aeration flow rate, groundwater velocity and aquifer permeability. Heating area is directly proportional to the seepage velocity of groundwater which can be analyzed by multiplying the water head difference between the upper and lower screens with the aquifer permeability. Therefore, the heat transfer model, based on Darcy's seepage theory and the energy conservation equation, effectively simulates the heat transfer with an error margin of less than 10%. Compared to individual GCW, GCW-ISTR exhibits a 25.8% improvement in aniline remediation efficiency, resulting in a decrease in the average concentration from 97.95 mg/L to 0.168 mg/L within 48 h, effectively mitigating the occurrence of tailing phenomena. This study provides a feasible method of enhancing the remediation of GCW on semi-volatile contaminants and is anticipated to broaden the applicability of GCW in site application.

Spatial variations and vertical migration potentials of petroleum hydrocarbons with varying chain lengths in soils of different depths: Roles of solid and dissolved organic matters and soil texture

Petroleum hydrocarbons (PHs) in contaminated sites may threaten human health and ecological safety, while the environmental behaviors of PHs with varying carbon chains and critical influencing factors need to be elucidated, thus facilitating efficient risk management. This study explored the occurrence characteristics and spatial variations of different PHs at the depths of 0-10 m in an abandoned industrial site, as well as evaluated the effects of solid organic matter (SOM), dissolved organic matter (DOM), and soil texture on the migration potentials of PHs with varying carbon chains. Furthermore, the leaching potentials of different PHs were integrated into their risk assessment. The total concentrations of PHs in contaminated soils ranged from 22.7 to 397 mg/kg in contaminated soils, and the long-chained PHs (C22-C40) represented the major components with an average contribution of 46.9 %, followed by short-chained PHs (C10-C12, 32.0 % average) and medium-chained PHs (C13-C21, 21.1 % average). As soil depth increased, a declining trend was observed in the proportions of long-chain PHs, with an augmentation in the relative abundance of short-chain PHs. The random forest model coupling redundancy analysis showed that SOM was the major contributor to the occurrence and vertical attenuation of PHs with longer carbon chains in underground soils, with clay component exerting a greater additional effect than silt and sand components. While DOM in soils exhibited a relatively high contribution to the retention of PHs with short carbon chains. These results demonstrated the significant influence of SOM and clay on the behavior of long-chained PHs and DOM on that of short-chained ones. Besides direct human exposure, the leaching potentials of PHs, particularly short-chained ones, in soils should be considered for a more comprehensive risk assessment. The findings of this study may assist with the behavior modelling and prediction of different PHs as well as the corresponding risk control.

Microbial adaptation and genetic modifications for enhanced remediation in low-permeability soils

Low-permeability soils, characterized by fine texture and high clay content, pose significant challenges to traditional soil remediation techniques due to limited hydraulic conductivity, restricted nutrient flow, and reduced oxygen availability. These unique properties enable low-permeability soils to function as natural barriers in environmental protection; however, they also trap contaminants, making traditional remediation efforts challenging. This review synthesizes current knowledge on microbial adaptation and genetic engineering approaches that enhance the effectiveness of bioremediation in such environments. Key microbial adaptations, including anaerobic metabolism, extracellular enzyme production, and stress response mechanisms, allow individual microbes to adapt in low-permeability soils. Additionally, community-level strategies like microhabitat creation, biofilm formation, and functional redundancy further support microbial resilience. Advancements in genetic engineering now enable the modification of microbial traits-such as soil adhesion, nutrient utilization, and stress tolerance-to enhance bioremediation efficacy. Synthetic biology techniques further allow for the design of tailored microbial consortia that work cooperatively to degrade contaminants in complex soil matrices. This review highlights the integration of microbial and genetic engineering strategies, offering a comprehensive overview that informs current practices and guides future research in low-permeability soil remediation.

Low-disturbance land remediation using vertical groundwater circulation well technology: The first commercial deployment in an operational chemical plant

Soil and groundwater contamination by organic pollutants from chemical plants presents significant risks to both environmental and human health. We report a significant field trial where a chemical plant in operation showed soil and groundwater pollution, as verified by sampling and laboratory tests. While many remediation methods are effective, they often require the temporary shutdown of plant operations to install necessary equipment. This paper introduces a novel combination of low-disturbance contaminant remediation technologies, including groundwater circulation well (GCW), pump and treat (P&T), and in-situ chemical oxidation (ISCO) technologies, that can be applied on the premises of an active plant without halting production. The groundwater with dissolved contaminants is removed through P&T and GCW, while GCW enhances ISCO that focus on eliminating the remaining hard-to-pump contaminants. Results show: (1) after two years of remediation effort, the contaminant levels in soil and groundwater were significantly reduced; (2) the average concentration reduction rate of four contaminants, including 1,2-dichloroethane, methylbenzene, ethylbenzene, and M&P-xylene, exceeds 98 %; (3) the presented remediation strategy results in the improvement of remediation efficiency. Specifically, the concentration of 1,2-dichloroethane in observation wells dropped from 40,550.7 μg/L to 44.6 μg/L. This study offers a first-of-its-kind commercial deployment of a GCW-based remediation strategy in an active plant setting. Moreover, the combined remediation approach presented here can serve as a model for designing contaminant remediation projects that require minimal operational disruption.

Understanding the dynamics of enhanced light non-aqueous phase liquids (LNAPL) remediation at a polluted site: Insights from hydrogeophysical findings and chemical evidence

This study intricately unfolds a pioneering methodology for remediating contaminants in a persistent light non-aqueous phase liquids (LNAPL)-contaminated site. The remediation strategy seamlessly integrates enhanced desorption and in-situ chemical oxidation (ISCO), orchestrating the injection of PetroCleanze® (a desorbent) and RegenOx® (an oxidizer) through meticulously designed wells. These injections, based on detailed geological and hydrogeological assessments, aim at mobilizing residual contaminants for subsequent extraction. Real-time subsurface dynamics are investigated through geophysical monitoring, employing electrical resistivity tomography (ERT) to trace reagent migration pathways via their effect on bulk electrical conductivity. The integration of groundwater sampling data aims at providing additional insights into the transformations of contaminants in the spatiotemporal context. Vivid two-dimensional time-lapse ERT sections showcase the evolution of resistivity anomalies, providing high-resolution evidence of the heterogeneity, dispersion pathways of desorbent and oxidant, and residual LNAPL mobilization. Hydrochemical analyses complement this, revealing effective mobilization processes with increasing aqueous concentrations of total petroleum hydrocarbons (TPH) over time. Speciation analysis unveils the intricate interplay of desorption and oxidation, portraying the dynamic fractionation of hydrocarbon components. The hydrogeophysical and data-driven framework not only delivers qualitative and quantitative insights into reagent and contaminant distribution but also enhances understanding of spatial and temporal physio-chemical changes during the remediation process. Time-lapse ERT visually narrates the reagent's journey through time, while chemical analyses depict the unfolding processes of desorption and oxidation across space and time. The coupling of hydrogeophysical and chemical findings pictures the transformations of pollutants following the sequence of product injection and the push and pull activities, capturing the removal of mobilized contaminants through hydraulic barrier wells. This enhanced understanding proves instrumental towards optimizing and tailoring remediation efforts, especially in heterogeneous environmental settings. This study establishes a new standard for a sophisticated and innovative contaminant remediation approach, advancing environmental practices through the harmonized analysis of geophysical and chemical data.

Design optimization of groundwater circulation well based on numerical simulation and machine learning

The optimal design of groundwater circulation wells (GCWs) is challenging. The key to purifying groundwater using this technique is its proficiency and productivity. However, traditional numerical simulation methods are limited by long modeling times, random optimization schemes, and optimization results that are not comprehensive. To address these issues, this study introduced an innovative approach for the optimal design of a GCW using machine learning methods. The FloPy package was used to create and implement the MODFLOW and MODPATH models. Subsequently, the formulated models were employed to calculate the characteristic indicators of the effectiveness of the GCW operation, including the radius of influence (R) and the ratio of particle recovery (Pr). A detailed collection of 3000 datasets, including measures of operational efficiency and key elements in machine learning, was meticulously compiled into documents through model execution. The optimization models were trained and evaluated using multiple linear regression (MLR), artificial neural networks (ANN), and support vector machines (SVM). The models produced by the three approaches exhibited notable correlations between anticipated outcomes and datasets. For the optimal design of circulating well parameters, machine learning methods not only improve the optimization speed, but also expand the scope of parameter optimization. Consequently, these models were applied to optimize the configuration of the GCW at a site in Xi'an. The optimal scheme for R (Q = 293.17 m3/d, a = 6.09 m, L = 7.28 m) and optimal scheme for Pr (Q = 300 m3/d, a = 3.64 m, L = 1 m) were obtained. The combination of numerical simulations and machine learning is an effective tool for optimizing and predicting the GCW remediation effect.

Enhancing predictions of remedial reagent transport via a vertical groundwater circulation well with high-resolution aquifer characterization

The vertical groundwater circulation well (GCW) is a commonly used technique in contaminated sites to remove secondary contaminants from low permeable zones. Early GCW studies often used simple subsurface hydraulic properties, such as anisotropic homogeneous aquifers or low conductivity lens/blocks, to mimic the complex subsurface heterogeneity. Although studies based on simplified representations of aquifer heterogeneity provide straightforward flow and transport information for engineering design of a GCW, they may over- or under-estimate contaminant fate and transport in the field. The objective of this study is to identify key heterogeneity factors that control the capture zone extension and to examine the extent to which the accuracy of estimated heterogeneity spatial distributions influences the prediction of remedial reagent transport. To achieve these objectives, we utilized Monte Carlo simulation to investigate the extension of the circulation zone in heterogeneous aquifers and to identify the key factors that contribute most to the variability of the circulation zone. Three commonly used geostatistical approaches (equivalent homogeneous, kriging, and highly parameterized methods) were employed to estimate the spatial distributions of key factors. The reliabilities of these estimated fields were evaluated through their remedial reagent transport predictability. The key factor analysis revealed that the mean porosity value, the variance of lnK, and the correlation length of lnK profoundly influence the lateral expansion of the capture zone. Neglecting the aquifer hydraulic conductivity heterogeneity underestimates the extension of the circulation zone and the spread of remedial reagent. Additionally, utilizing a highly parameterized approach to estimate the high-resolution K field can accurately reproduce the key remedial reagent distributions. The concentration arrival time and peak concentration are significantly improved compared to those predictions based on the equivalent homogeneous and kriged K fields.

Groundwater chlorinated solvent plumes remediation from the past to the future: a scientometric and visualization analysis

Contamination of groundwater with chlorinated hydrocarbons has serious adverse effects on human health. As research efforts in this area have expanded, a large body of literature has accumulated. However, traditional review writing suffers from limitations regarding efficiency, quantity, and timeliness, making it difficult to achieve a comprehensive and up-to-date understanding of developments in the field. There is a critical need for new tools to address emerging research challenges. This study evaluated 1619 publications related to this field using VOSviewer and CiteSpace visual tools. An extensive quantitative analysis and global overview of current research hotspots, as well as potential future research directions, were performed by reviewing publications from 2000 to 2022. Over the last 22 years, the USA has produced the most articles, making it the central country in the international collaboration network, with active cooperation with the other 7 most productive countries. Additionally, institutions have played a positive role in promoting the publication of science and technology research. In analyzing the distribution of institutions, it was found that the University of Waterloo conducted the majority of research in this field. This paper also identified the most productive journals, Environmental Science & Technology and Applied and Environmental Microbiology, which published 11,988 and 3253 scientific articles over the past 22 years, respectively. The main technologies are bioremediation and chemical reduction, which have garnered growing attention in academic publishing. Our findings offer a useful resource and a worldwide perspective for scientists engaged in this field, highlighting both the challenges and the possibilities associated with addressing groundwater chlorinated solvent plumes remediation.

Effect of pumping-induced soil settlement on the migration and transformation of aniline

This study selected a contamination site associated with pesticide production to investigate the impact of soil settlement induced by pumping on the migration and transformation of the principal pollutant, aniline. The TMVOC model was enhanced by incorporating the settlement effect and validated through a soil-column experiment, which examined aniline distribution, phase transformation, and remediation efficiency under soil settlement. The results indicate that the optimized TMVOC model can accurately simulate the impact of pumping-induced soil settlement on aniline removal. The longitudinal migration of aniline was reduced, with the area of high concentrations drawing nearer to the surface. Furthermore, soil settlement negatively affected the removal of aniline in the Non-Aqueous Phase Liquid (NAPL) phase, resulting in a 10.59 % decline in the removal rate. In contrast, soil settlement positively influenced aniline removal in the gas and aqueous phases, increasing the removal rate by 12.55 % and 5.04 %, respectively, with the gas phase showing the most significant increase. Soil porosity decreased due to soil settlement, leading to a change in the proportion of each phase, with NAPL increasing after remediation. Additionally, soil settlement exhibited hysteresis, as evidenced by a noticeable decrease in the removal rate in the 10th month of the remediation process, and the final mass removal rate was reduced by 5.93 %.

A construction strategy of Kriging surrogate model based on Rosenblatt transformation of associated random variables and its application in groundwater remediation

When using simulation-optimization models for optimizing the design of groundwater pumping-treatment plans for pollution, building a surrogate model for the numerical simulation model has become an effective means of overcoming the computational load of such models. However, previous studies often treated pumping time as a single optimization variable, leading to unnecessary excessive pumping. This paper considers the location, pumping rate, start time, and end time of each candidate pumping well as optimization variables, and proposes a Rosenblatt-transform-based optimal Latin hypercube sampling method for the associated random variables to ensure that the start time is less than or equal to the end time. This method is coupled with an adaptive sampling method based on batch local optimal solutions to construct a dynamic adaptive Kriging surrogate model for the numerical model, ensuring that the true value of the optimal remediation scheme is not lost. The results show that, at the final stage of remediation, the pollutant concentration in the 4 scenarios achieves comprehensive compliance. However, when considering the minimization of remediation costs as the evaluation criterion, the remediation scheme in scenario 1 (the pumping start and end times are independent optimization variables for all candidate pumping wells) is optimal. In the optimization design of groundwater pumping-treatment plans, the pumping wells should be arranged in the midstream and downstream regions of the contaminant plume and parallel to the regional flow direction. This paper provides a method reference for the construction and adaptive updating of surrogate models involving associated random variables, as well as guidance for the dynamic optimization of groundwater pumping and treatment at contaminated sites.