Contaminated Groundwater Sites Research Articles

Insights into In Situ Benthic Caging Tests for Ecotoxicity Assessments Targeting Discharging Groundwater Contaminant Plumes

While in situ toxicity testing with caged organisms has been used to assess surface water and sediment contamination, no successful application to benthic organisms exposed to highly contaminated groundwater plumes discharging to surface waters has been reported. The objective of this study was to demonstrate and evaluate this application using four sets of tests performed at three previously reported contaminated groundwater sites, which include one river site affected by volatile organic contaminant plumes, and two sites, one pond and one small urban stream, impacted by landfill plumes. The study examined multiple cage designs and orientations and two test organisms: an amphipod (Hyalella azteca) and midge larvae (Chironomus riparius; only one study). Cages were deployed for between 5 and 28 days and assessed for organism survival and growth. At all sites and for some deployment conditions, cages exposed to high contaminant concentrations in the plume footprint had greater mortality compared to those exposed to lower or background concentrations. Organism growth was less clear as a metric of toxicity. Vertically oriented cages typically showed high mortality to plume contaminants, but some were also affected by other non-target groundwater conditions (e.g., low dissolved oxygen, other contaminant sources), while horizontally oriented cages were rarely responsive to either groundwater influence. A hybrid cage design showed much promise in its single study. Useful observations on the test organisms and on potentially problematic site conditions were also made. The informed use of in situ toxicity cages could be an additional beneficial tool for groundwater contaminated site assessments.

Interpretable machine learning for predicting the fate and transport of pentachlorophenol in groundwater

Pentachlorophenol (PCP) is a commonly found recalcitrant and toxic groundwater contaminant that resists degradation, bioaccumulates, and has a potential for long-range environmental transport. Taking proper actions to deal with the pollutant accounting for the life cycle consequences requires a better understanding of its behavior in the subsurface. We recognize the huge potential for enhancing decision-making at contaminated groundwater sites with the arrival of machine learning (ML) techniques in environmental applications. We used ML to enhance the understanding of the dynamics of PCP transport properties in the subsurface, and to determine key hydrochemical and hydrogeological drivers affecting its transport and fate. We demonstrate how this complementary knowledge, provided by data-driven methods, may enable a more targeted planning of monitoring and remediation at two highly contaminated Swedish groundwater sites, where the method was validated. We evaluated 6 interpretable ML methods, 3 linear regressors and 3 non-linear (i.e., tree-based) regressors, to predict PCP concentration in the groundwater. The modeling results indicate that simple linear ML models were found to be useful in the prediction of observations for datasets without any missing values, while tree-based regressors were more suitable for datasets containing missing values. Considering that missing values are common in datasets collected during contaminated site investigations, this could be of significant importance for contaminated site planners and managers, ultimately reducing site investigation and monitoring costs. Furthermore, we interpreted the proposed models using the SHAP (SHapley Additive exPlanations) approach to decipher the importance of different drivers in the prediction and simulation of critical hydrogeochemical variables. Among these, sum of chlorophenols is of highest significance in the analyses. Setting that aside from the model, tetra chlorophenols, dissolved organic carbon, and conductivity found to be of highest importance. Accordingly, ML methods could potentially be used to improve the understanding of groundwater contamination transport dynamics, filling gaps in knowledge that remain when using more sophisticated deterministic modeling approaches.

Physics-informed surrogate modeling for supporting climate resilience at groundwater contamination sites

Contamination of soil and groundwater presents a widespread global problem, significantly impacting both human well-being and environmental stability. Conventional models employed for estimating pollutant concentrations under varying climatic conditions demand extensive computational power and high-performance computing resources. In response to this issue, we have devised an innovative method utilizing a physics-informed machine learning technique, known as the U-Net Enhanced Fourier Neural Operator (U-FNO), to generate rapid surrogate models for flow and transport. These models are capable of forecasting groundwater pollution levels under diverse climatic situations and subsurface characteristics without necessitating a supercomputer. In our research, we centered our attention on the Department of Energy’s Savannah River Site (SRS) F-Area and established two time-dependent structures: U-FNOB and U-FNOB-R. Both frameworks incorporate a tailored loss function, including specific physical constraints of groundwater flow and transport such as spatial derivatives, and contaminant boundary conditions. The findings of our study indicate that the U-FNO models can consistently foresee spatialtemporal fluctuations in groundwater flow and pollutant transportation properties, such as contaminant concentration, hydraulic head, and Darcy’s velocity. Our research reveals that the U-FNOB-R architecture is especially adept at predicting the effects of alterations in recharge rates on groundwater contamination sites, delivering superior time-dependent forecasts compared to the U-FNOB structure. Our novel approach holds the potential to revolutionize environmental monitoring and remediation efforts by providing rapid, precise, and cost-efficient estimations of groundwater pollution levels under uncertain climate conditions.

Field evaluation of carbon injection method for in-situ biological denitrification in groundwater using geochemical and metataxonomic analyses

This study focuses on the bioremediation of nitrate-contaminated groundwater, which has become a significant environmental problem due to the increasing usage of fertilizers and sewage disposal. The nitrate reduction efficiencies of biological denitrification by injection of carbon source in a pilot-scale treatment system setup were investigated at a groundwater contamination site. The field test was conducted using acetate as a carbon source for 22 days to assess the nitrate reduction efficiencies of in-situ treatment. Geochemical parameters and microbial community analysis using next-generation sequencing were performed before and after carbon source injection. After 12 h of reaction time, nitrate concentration decreased from 31.6 to 4.2 mg-N/L at PC-2, and then remained stable at 3.9 mg-N/L. The nitrate reduction rate when acetate was injected was 29.0 mg-N/L/day. Aquabacterium commune, pseudomonas brassicacearum, dechloromonas denitrificans, and Massilia FAOS were dominant species after acetate injection. Predictive metabolic pathway analysis indicated that nitrate reduction metabolisms during injection of acetate were denitrification and assimilatory nitrate reduction to ammonium. The evaluated hazard quotient of nitrate-contaminated groundwater significantly decreased after acetate injection (non-carcinogenic risk decreased from 1.176 to 0.134 for children). This research could provide fundamental information for decision-makers in nitrate-contaminated groundwater quality protection and management.

Response of Microbial Community Stability to Chemical Oxidation Remediation Process in a Petroleum Hydrocarbon Contaminated Groundwater Site

The stability of the microbial community is a vital indicator of microbial ecosystems. However, the mechanism of microbial community stability during in situ chemical oxidation in petroleum-hydrocarbon-polluted groundwater is unclear. This study analyzed the biomass, diversity, co-occurrence network feature and negative cohesion of microbial community at different stages to identify the changes in microbial community stability under chemical oxidation. In addition, microbial module compositions and crucial functions were analyzed to further explore the reason for the change in community stability at the module level. Multiple regression analysis was conducted to explore the microbial module explanatory degree to microbial community stability changes. The results indicated that the microbial community stability was destroyed by chemical oxidation. The carbon source effect was the main reason in the early oxidation stage, while the oxidation stress effect was the main reason in the late oxidation stage. Most microbial modules were transformed from K-strategists to r-strategists, and modular keystones were transformed to stress-tolerant species in the oxidation stage. This study suggested that microbial clusters were essential indicators of the microbial community in petroleum hydrocarbon groundwater during the chemical oxidation period.

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

Pump-and-treat (P&T) is commonly used to remediate contaminated groundwater sites. The scientific community is currently engaged in a debate regarding the long-term effectiveness and sustainability of P&T for groundwater remediation. This work aims to provide a quantitative comparative analysis of the performance of an alternative system to traditional P&T, to support the development of sustainable groundwater remediation plans. Two industrial sites with unique geological frameworks and contamination with dense non-aqueous phase liquid (DNAPL) and arsenic (As) respectively, were selected for the study. At both locations, attempts were made for decades to clean up groundwater contamination by pump-and-treat. In response to persistently high levels of pollutants, groundwater circulation wells (GCWs) were installed to explore the possibility of accelerating the remediation process in unconsolidated and rock deposits. This comparative evaluation focuses on the different mobilization patterns observed, resulting variations in contaminant concentration, mass discharge, and volume of extracted groundwater. To facilitate the fusion of multi-source data, including geological, hydrological, hydraulic, and chemical information, and enable the continuous extraction of time-sensitive information, a geodatabase-supported conceptual site model (CSM) is utilized as a dynamic and interactive interface. This approach is used to assess the performance of GCW and P&T at the investigated sites. At Site 1, the GCW stimulated microbiological reductive dichlorination and mobilized significantly higher 1,2-DCE concentrations than P&T, despite recirculating a smaller volume of groundwater. At Site 2, As removal rate by GCW resulted generally higher than pumping wells. One conventional well mobilized higher masses of As in the early stages of P&T. This reflected the P&T's impact on accessible contaminant pools in early operational periods. P&T withdrew a significantly larger volume of groundwater than the GCW. The outcomes unveil the diverse contaminant removal behavior characterizing two distinct remediation strategies in different geological environments, revealing the dynamics and decontamination mechanisms that feature GCWs and P&T and emphasizing the limitations of traditional groundwater extraction systems in targeting aged pollution sources. GCWs have been shown to reduce remediation time, increase mass removal, and minimize the significant water consumption associated with P&T. These benefits pave the way for more sustainable groundwater remediation approaches in various hydrogeochemical scenarios.

Groundwater Contamination Site Identification Based on Machine Learning: A Case Study of Gas Stations in China

Accurately identifying groundwater contamination sites is vital for groundwater protection and restoration. This study aims to use a machine learning (ML) approach to identify groundwater contamination sites with total petroleum hydrocarbons (TPH) as target contaminants in a case study of gas stations in China. Firstly, six classical ML algorithms, including logistic regression, decision tree, gradient boosting decision tree (GBDT), random forest, multi-layer perceptron, and support vector machine, were applied to develop the identification models of TPH-contaminated groundwater with 40 features and the performances were compared. The comparison results showed that the GBDT model achieves the best prediction performance, with F1 score of 1 and AUC value of 1. Next, Bayesian optimization optimized GBDT (BO-GBDT) was conducted to further decrease the training time from 19,125 s to 513 s while maintaining the same prediction performance (F1 score = 1, AUC = 1). Finally, Shapley additive explanations (SHAP) analysis was performed on the BO-GBDT model. The SHAP results displayed that the critical feature variables in the BO-GBDT model include wind, population, evaporation, total potassium in the soil, precipitation, and leakage accident. This study demonstrated that BO-GBDT is one satisfactory model to identify groundwater TPH-contamination at gas stations. The method proposed in this study has the potential to be applied to other types of groundwater contamination sites.

Toxicity prediction: An application of alternative testing and computational toxicology in contaminated groundwater sites in Taiwan

Groundwater contamination remains a global threat due to its toxic effects to humans and the environment. The remediation of contaminated groundwater sites can be costly, thus, identifying the priority areas of concern is important to reduce money spent on resources. In this study, we aimed to identify and rank the priority groundwater sites in a contaminated petrochemical district by combining alternative, non-animal approaches – chemical analysis, cell-based high throughput screening (HTS), and Toxicological Priority Index (ToxPi) computational toxicology tool. Groundwater samples collected from ten different sites in a contaminated district showed pollutant levels below the detection limit, however, hepatotoxic bioactivity was demonstrated in human hepatoma HepaRG cells. Integrating the pollutants information (i.e., pollutant characteristics and concentration data) with the bioactivity data of the groundwater samples, an evidence-based ranking of the groundwater sites for future remediation was established using ToxPi analysis. The currently presented combinatorial approach of screening groundwater sites for remediation purposes can further be refined by including relevant parameters, which can boost the utility of this approach for groundwater screening and future remediation.

Theoretical and Experimental Adsorption of Silica Gel and Activated Carbon onto Chlorinated Organic Compounds in Water: A Case Study on the Remediation Assessment of a Contaminated Groundwater Site

Chlorinated organic compounds (COCs) are a serious threat to human health and the ecological environment due to their toxicity, mutagenicity and carcinogenicity. A number of corresponding treatment techniques have been developed thus far; among these techniques, adsorption is considered an efficient and low-cost method. However, it is very important to find suitable and economical adsorbent types and usage amounts. In this study, the adsorption of trichloroethylene (TCE) and perchloroethylene (PCE) onto two different adsorbents (silica gel and activated carbon) was investigated, and the obtained adsorption constants were then introduced into Langmuir and Freundlich adsorption models. The adsorption isotherm constants of these two models were used to predict the adsorbate removal efficiency and the required adsorbent mass. The results showed that the Langmuir and Freundlich models predicted the removal efficiency and adsorbent quality of the TCE and PCE adsorbed onto silica gel and activated carbon, and the errors were less than 10% compared with the measured values obtained through adsorption experiments. According to the differences in adsorption efficiency and cost between silica gel and activated carbon, it was found that, when the adsorption efficiency of the silica gel for TCE and PCE significantly decreased, adding activated carbon to continue the adsorption effectively reduced the adsorption cost of on-site remediation. This result was demonstrated by taking the Radio Corporation of America (RCA) pollution incident in Taiwan as an example, and it was estimated that 6427 ± 172 tons and 343 ± 21 tons of silica gel and activated carbon, respectively, would be required for the on-site remediation of TCE, and the total cost would be approximately 4,390,000 USD. The remediation of PCE would require 7553 ± 57 tons of silica gel and 350 ± 68 tons of activated carbon, with a total cost of approximately 5,030,000 USD. Therefore, silica gel should be used to reduce the pollutant concentration first, and then activated carbon should be added for continuing adsorption. This method of adding adsorbents is economical and can effectively reduce the adsorption cost.

Early arrival waveform inversion using data uncertainties and matching filters with application to near-surface seismic refraction data

We develop an early arrival waveform inversion (EAWI) technique for high-resolution near-surface velocity estimation by iteratively updating the P-wave velocity model to minimize the difference between the observed and calculated seismic refraction data. Traditional EAWI uses a least-squares penalty function and an acoustic forward-modeling engine. Conventional least-squares error is sensitive to data with low signal-to-noise ratio (S/N) and iterations of EAWI stop at a local-minimum data misfit or at the preassigned maximum number of iterations. These stopping criteria can result in overfitting the data. In addition, fitting the elastic field data with an acoustic modeling engine can introduce artifacts in velocity estimation, especially in land data with significant elastic effects. To overcome these challenges, we develop a robust EAWI (REAWI) method by (1) incorporating the data uncertainties into the penalty function and (2) mitigating the elastic effects using a matching filter workflow. The data uncertainties are estimated from waveform reciprocal errors. When full-waveform reciprocity is not available, trace interpolation is applied. The proposed method prevents closely fitting data with low S/N, avoids overall overfitting by stopping the iterations when a normalized chi-square ([Formula: see text]) waveform misfit of one is achieved, and is less affected by elastic effects. Numerical examples and application to near-surface refraction data at a groundwater contamination site suggest that the final REAWI models are more accurate than the corresponding EAWI models, at the same level of misfit. This is the first known application of a matching filter workflow to real land data. The final REAWI models satisfy an appropriate misfit between the real data and predicted elastic P-wave data, making this approach in this respect equivalent to elastic waveform inversion. We also develop a method to analyze model constraint by examining the energy of the wavefield Fréchet derivative thereby avoiding the influence of the data residuals in traditional Fréchet kernels.

Reactive transport modeling for supporting climate resilience at groundwater contamination sites

Abstract. Climate resilience is an emerging issue at contaminated sites and hazardous waste sites, since projected climate shifts (e.g., increased/decreased precipitation) and extreme events (e.g., flooding, drought) could affect ongoing remediation or closure strategies. In this study, we develop a reactive transport model (Amanzi) for radionuclides (uranium, tritium, and others) and evaluate how different scenarios under climate change will influence the contaminant plume conditions and groundwater well concentrations. We demonstrate our approach using a two-dimensional (2D) reactive transport model for the Savannah River Site F-Area, including mineral reaction and sorption processes. Different recharge scenarios are considered by perturbing the infiltration rate from the base case as well as considering cap-failure and climate projection scenarios. We also evaluate the uranium and nitrate concentration ratios between scenarios and the base case to isolate the sorption effects with changing recharge rates. The modeling results indicate that the competing effects of dilution and remobilization significantly influence pH, thus changing the sorption of uranium. At the maximum concentration on the breakthrough curve, higher aqueous uranium concentration implies that sorption is reduced with lower pH due to remobilization. To better evaluate the climate change impacts in the future, we develop the workflow to include the downscaled CMIP5 (Coupled Model Intercomparison Project) climate projection data in the reactive transport model and evaluate how residual contamination evolves through 2100 under four climate Representative Concentration Pathway (RCP) scenarios. The integration of climate modeling data and hydrogeochemistry models enables us to quantify the climate change impacts, assess which impacts need to be planned for, and therefore assist climate resiliency efforts and help guide site management.

Toxicity Prediction: An Application of Alternative Testing and Computational Toxicology in Contaminated Groundwater Sites in Taiwan

Toxicity Prediction: An Application of Alternative Testing and Computational Toxicology in Contaminated Groundwater Sites in Taiwan

Spatial–temporal assessment of hydrocarbon biodegradation mechanisms at a contaminated groundwater site in Serbia

ABSTRACT The characterization and cleanup of groundwater contamination in hazardous-waste sites are of significant engineering and scientific importance. This study analyzes biodegradation fingerprints in groundwater, 25 years after the accidental leakage of kerosene (jet fuel) at the site in central Serbia. The long-term existence of hydrocarbon contamination and the presence of indigenous microbiological populations capable of biodegradation have been confirmed by the results of GCxGC-MS chromatography and microbiological characterization. Total petroleum hydrocarbons (TPH), geochemical indicators, and other parameters were spatially analyzed to provide insight into biodegradation occurrence. The lowest concentrations of electron acceptors (O2, NO3 -, and SO4 2-) and the highest concentrations of microbial metabolic products (Mn and Fe) overlap in the piezometers closest to the source of contamination, due to the occurrence of different biodegradation mechanisms. Based on the analysis of redox-sensitive compounds, the mixed oxic-anoxic processes in groundwater also correspond to the aforementioned zone, as confirmed by the redox potential (Eh) measurements. The results of cross-study analysis reveal further reduction of hydrocarbon contamination, the occurrence of less anoxic redox processes, and the increase of oxic conditions in groundwater. Overall, the results provide clear evidence of the biodegradation effects in groundwater and insight into their evolution under natural attenuation processes.

Beneficial effects of dynamic groundwater flow and redox conditions on Natural Attenuation of mono-, poly-, and NSO-heterocyclic hydrocarbons

Natural Attenuation (NA) processes have been demonstrated to reduce pollutant loads at different contaminated groundwater sites world-wide and are increasingly considered in contaminated site management concepts. However, data are mainly available for steady state groundwater flow and stable redox conditions as well as pollutants listed in standard regulatory schemes. In this study, the influence of transient groundwater flow and redox conditions on NA was examined at a former gas works site near the river Rhine in Germany. The investigated 78 pollutants included 40 mono- and polyaromatic hydrocarbons (MAHs, PAHs) and 38 NSO-heterocyclic aromatic hydrocarbons (NSO-HET). In the highly polluted areas, the MAHs benzene, indene and indane, the PAHs naphthalene, acenaphthene, 1- and 2-methylnaphthalene and the NSO-HET 2-methylquinoline, carbazole, benzothiophene, dibenzofuran and benzofuran were predominant. Pollutant concentrations decreased with increasing distance from the sources of contamination. At the plume fringes, the MAHs benzene and indane, the PAH acenaphthene, the NSO-HET carbazole, 5-methylbenzothiophene, 2- and 3-methylbenzofuran and 2-methyldibenzofuran were predominant, indicating low retention and slow intrinsic biodegradation of these compounds. The influence of surface water on groundwater level, pollutant concentrations, and redox conditions in the monitoring wells was observed with a permanently installed groundwater sensor. The temporary availability of oxygen was observed at the plume fringes, resulting in aerobic and ferric iron reducing biodegradation processes. Field and laboratory data were used to set-up a groundwater flow and reactive transport model used for quantification of the field mass transfer rates. In conclusion, the study demonstrates that NA is effective under transient flow and redox conditions. A conceptual model and reactive transport simulation can facilitate the interpretation of pronounced fluctuations of pollutant concentration in monitoring wells. Based on the analysis of 78 pollutants, indane, indene and several NSO-HET like carbazole, benzothiophene and 2-methyldibenzofuran are recommended for monitoring at tar oil polluted sites, besides EPA-PAHs and BTEX.

INSIDE-T: A Groundwater Contamination Transport Model for Sustainability Assessment in Remediation Practice

Current sustainability assessment (SA) tools to help deal with contaminated groundwater sites are inherently subjective and hardly applied. One reason may be lack of proper tools for addressing contaminant spread which are basically objective. To fill this gap, there is a need for contaminant transport models that provide site managers with needed room for applying their judgments and considerations about the efficiency of each remediation method based on their experiences in similar cases. INSIDE-T uses trend analysis and inverse modeling to estimate transport parameters. It then simulates contaminant transport both with and without the inclusion of remedial actions in a transparent way. The sustainability of each remedy measure can then be quantified based on the underlying SA tool (INSIDE). INSIDE-T was applied to a site in south Sweden, contaminated with pentachlorophenol. Simulation scenarios were developed to enable comparison between various remediation strategies and combinations of these. The application indicated that natural attenuation was not a viable option within the timeframe of interest. Although pump-and-treat combined with a permeable reactive barrier was found to be just as effective as bioremediation after five years, it received a much lower sustainability score overall. INSIDE-T outcomes enable site managers to test and evaluate different scenarios, a necessity in participatory decision-making practices such as remediation projects.

Assessing data-scarce contaminated groundwater sites surrounding petrochemical industries

A common problem when studying groundwater contamination in low-income countries is that data required for a detailed risk assessment are limited. This study presents a method for assessment of the potential impact of groundwater contamination by total petroleum hydrocarbons (TPH) in a data-scarce region. Groundwater modeling, using the MODFLOW, was used to simulate regional-scale flow pattern. Then, a semi-analytical contamination transport model was calibrated by minimization of the absolute errors between measured and modeled concentrations. The method was applied to a case study in Kazakhstan to assess the potential spreading of a TPH plume, based on historical observations. The limited data included general information about the local geology, observations of GW level in the area, and concentrations during 5 years of TPH in monitoring wells surrounding the source of the pollution. The results show that the plume could spread up to 2–6 km from the source, depending on estimate of the initial concentrations, until the concentration reaches permissible levels. Sensitivity analysis identified parameters of longitudinal and transverse dynamic dispersivity together with the plume of TPH spreading, as the priority subjects for future investigations. The proposed approach can be used as a tool for governmental and municipal decision-makers to better plan the usage of affected groundwater sites in data-scarce regions. It can also help to decrease the negative impact of contaminated GW on human health and to better manage the industrial pollution.

Combining continuous monitoring and High-Precision altitude measurements in forensic groundwater surveys: a case study of chlorinated solvent pollution in an urban context

This paper describes a forensic investigation of groundwater in an urban context in Italy. The present case study was conducted to detect the hydraulic flow path between a sportfishing pond and a nearby industrial plant’s contaminated groundwater site. The investigation was performed to evaluate the potential for diffusion of contaminants through groundwater flow into a fishing pond located downstream from a chemical factory. High-precision altitude measurements of monitoring stations combined with continuous water level monitoring were crucial to understand the groundwater flow dynamics and define the hydrogeological conceptual model. The study verified that the fishing pond, dug in low-permeability volcanic rock, was not hydraulically connected to the groundwater flow. The presence of contaminants in the pond may be related to the periodic topping-up activity performed using water from an existing well. The identified groundwater flow paths were consistent with the possible contaminant migration from the chemical factory to the water well near the fishing pond.

Trends in 1,4‐Dioxane Analyses: Implications for Identification and Characterization of Contaminated Groundwater Sites

Abstract1,4‐Dioxane is a contaminant of emerging concern, and there is significant uncertainty about how its environmental occurrence in groundwater is being assessed given the various analytical methods available. This study compiled public sampling records from 2000 to 2019 that included >106,000 analyses of 1,4‐dioxane from 822 different U.S. sites. The 1,4‐dioxane detection frequency in the entire dataset (including all methods) was 45%, and the median detected concentration was 10 μg/L, highlighting the dilute nature of 1,4‐dioxane in environmental media and the importance of selecting methods with adequate sensitivity. The annual distribution of samples analyzed by each method type confirmed a shift towards methods designed for semi‐volatile compounds (Method 8270 and Method 8270 SIM) that exhibited consistently lower reporting limits (median reporting limit for each year typically ≤1 μg/L). In contrast, the method designed for volatile compounds (Method 8260) exhibited less sensitivity for 1,4‐dioxane (median reporting limit per year between 40 and 100 μg/L) and its use declined significantly over time with increasing use of the moderately sensitive Method 8260 SIM in later years. This shift contributed to an increase in the 1,4‐dioxane detection frequency over time, with a strong correlation between the annual detection frequency and the median reporting limit. Sites where 1,4‐dioxane was analyzed but not detected overwhelmingly used less‐sensitive methods that may not have been adequate for the expected concentration levels. Given the sub‐μg/L groundwater criteria issued for 1,4‐dioxane by some regulatory agencies, more sensitive and accurate methods will be increasingly needed to assess compliance.

Pioneering groundwater contamination investigation, research, and in situ treatment.

The 1972 paper by Professor Jack McKee of the California Institute of Technology, consulting engineer Finley Laverty and Raymond Hertzel of the California Regional Water Quality Control Board-Los Angeles (McKee et al., 1972) was an early, important contribution to the understanding of groundwater contamination with organic liquids and to the integrated use of field, laboratory, and modeling studies to develop remediation approaches. The work presented in the paper was ahead of the curve and helped provide the foundation for the intense research, development, and education in investigation and remediation of groundwater contamination problems that began around 1980 and lasted for two decades. Reading the paper in the current context of more than 40years of research and field experience provides perspective on how little was known in 1972 about groundwater contamination and how to address it, and how well-formulated and forward-looking was the work of McKee et al. PRACTITIONER POINTS: McKee et al. (1972) was an early, important contribution to the understanding of groundwater contamination with organic liquids and to the integrated use of field, laboratory and modeling studies to develop remediation approaches. McKee et al. present the results of site investigation and remediation planning studies for a large-scale groundwater contamination site in the Los Angeles-Glendale, California area. Four specific remediation goals were established, and a comprehensive program of site investigation, research, and modeling was developed to support the achievement of the remediation goals. The comprehensive site investigation and remedial planning involving field, laboratory, and modeling studies described by McKee et al. was a forerunner of what came into standard contaminated site remediation practice in the 1980s and 1990s.

Improving Long-term Monitoring of Contaminated Groundwater at Sites where Attenuation-based Remedies are Deployed.

This study presents an effective approach to tackle the challenge of long-term monitoring of contaminated groundwater sites where remediation leaves residual contamination in the subsurface. Traditional long-term monitoring of contaminated groundwater sites focuses on measuring contaminant concentrations and is applicable to sites where contaminant mass is removed or degraded to a level below the regulatory standard. The traditional approach is less effective at sites where risk from metals or radionuclides continues to exist in the subsurface after remedial goals are achieved. We propose a long-term monitoring strategy for this type of waste site that focuses on measuring the hydrological and geochemical parameters that control attenuation or remobilization of contaminants while de-emphasizing contaminant-concentration measurements. We demonstrate how this approach would be more effective than traditional long-term monitoring, using a site in South Carolina, USA, where groundwater is contaminated by several radionuclides. A comprehensive enhanced attenuation remedy has been implemented at the site to minimize discharge of contamination to surface water. The immobilization of contaminants occurs in three locations by manipulation of hydrological and geochemical parameters, as well as by natural attenuation processes. Deployment of our proposed long-term monitoring strategy will combine subsurface and surface measurements using spectroscopic tools, geophysical tools, and sensors to monitor the parameters controlling contaminant attenuation. The advantage of this approach is that it will detect the potential for contaminant remobilization from engineered and natural attenuation zones, allowing potential adverse changes to be mitigated before contaminant attenuation is reversed.