Journal of contaminant hydrology最新文献

This study applied electrokinetic (EK) in situ soil remediation for perfluorooctanoic acid (PFOA) removal from kaolinite soil. The kaolinite soil was spiked with 10 mg/kg PFOA for the EK treatment using Sodium Cholate bio-surfactant coupled with Activated Carbon (AC) or iron-coated Activated Carbon (FeAC) permeable reactive barrier (PRB). The study also evaluated the impact of AC and FeAC PRBs' position on the EK process performance. In the EK with the PRB in the middle section, PFOA removal from kaolinite was 52.35 % in the AC-EK tests and 59.55 % in the FeAC-EK. Experimental results showed the accumulation of PFOA near the cathode region in FeAC PRB tests, hypothesising that Fe from the PRB formed a complex with PFOA ions and transported it to the cathode region. Spent PRBs were regenerated with methanol for PFOA extraction and reuse in the EK experiments. Although FeAC PRB achieved better PFOA removal than AC PRB, the EK tests with regenerated AC-EK and FeAC-EK PRBs achieved 40.37 % and 20.62 % PFOA removal. For EK with FeAC PRB near the anode, PFOA removal was 21.96 %. Overall, using PRB in conjunction with the EK process can further enhance the removal efficiency. This concept could be applied to enhance the removal of various PFAS compounds from contaminated soils by combining a suitable PRB with the EK process. It also emphasizes the feasibility of in-situ soil remediation technologies for forever chemical treatment.

Mine waste rock poses significant environmental challenges. Evaluating management and reclamation options is particularly complex because of the wide particle size distribution, the non-uniform distribution of acid-generating and buffering minerals, and the variable contribution of the different particle size fractions to acid mine drainage (AMD) generation. Reactive transport simulations can be useful to complement and overcome the limitations of laboratory and field experiments. However, predicting field-scale and long-term geochemical behavior of waste rock requires a better understanding of numerical parameters scale-up. In this study, three waste rocks, with different mineral composition and particle size distribution, were separated into different fractions and tested in the laboratory. Kinetic tests were used to calibrate numerical models and adjust minerals' effective kinetic rate constants to match measured pH and metal concentrations. Calibrated reactive transport simulations were able to reproduce accurately the effect of particle size on pH and sulfate and calcium production rates. Experimental and numerical results confirmed that waste rock oxidation and neutralization rates tended to decrease with increasing particle sizes. Several models were tested and the weighted geometric mean of the effective kinetic rate constants as a function of the proportion of each fraction provided the most accurate estimation of the whole specimen kinetic rate constants. A novel approach to predict waste rock geochemical behavior from a single laboratory test also showed promising results. Overall, these results should contribute to improving the extrapolation of laboratory kinetic test results to field predictions.

The contaminant mass discharge is a relevant metric to evaluate the risk that a groundwater plume poses to water resources. However, this assessment is often vitiated by a high uncertainty inherent to the assessment method and often limited number of measurement points to carry out the assessment. Direct-Push techniques in combination with profiling tools and dedicated sampling can be an interesting alternative to increase the measurement point density and hence reduce the mass discharge uncertainty. The main objective of our study was to assess if DP logging and sampling could be employed to get a reasonable estimate of contaminant mass discharge in a large sulfonamide contaminant plume (> 1500 m wide), compared to a more traditional approach based on monitoring wells. To do so, an Hydraulic Profiling Tool (HPT) logging with a dedicated site calibration was used to estimate the hydraulic conductivity field. The sulfonamide concentrations were inferred from the compound fluorescence properties measured by laboratory spectrofluorometry (λ_Ex / λ_Em = 255/340 nm) and a dedicated log-log linear regression model. Our results show that HPT-derived hydraulic conductivity values are in good agreement with the monitoring well results, and within the order of magnitude reported in similar studies or indirect geophysical techniques. Fluorescence appears as a powerful proxy for the sulfonamide concentration levels. Ultimately, the contaminant mass discharge estimate from HPT and fluorescence techniques lies within a factor 2 from the estimate by monitoring wells, with 549 [274–668] and 776 [695–879] kg/yr respectively. Overall, this study highlights that DP logging tools combined with indirect methods (correlation with fluorescence) could provide a relevant contaminant mass discharge estimate for some optically active substances, given that a proper calibration phase is carried out.

Large-scale open-pit combined underground mining activities (OUM) not only reshape the original topography, geomorphology, and hydrogeochemical environment of the mining area, but also alter the regional water cycle conditions. However, due to the complexity arising from the coexistence of two coal mining technologies (open-pit and underground mining), the hydrological environmental effects remain unclear. Here, we selected the Pingshuo Mining Area in China, one of the most modernized open-pit combined underground mining regions, as the focus of our research. We comprehensively employed mathematical statistics, Piper diagram, Gibbs model, ion combination ratio, principal component analysis and other methods to compare the hydrochemistry and isotope data of different water bodies before (2006) and after (2021) large-scale mining. The changing patterns of hydrochemical characteristics of different water bodies and their main controlling factors in mining area driven by OUM were analyzed and identified, revealing the water circulation mechanism under the background of long-term coal mining. The results showed that: (1) The chemical composition of water has changed greatly due to large-scale coal mining. The hydrochemical types of Quaternary and Permian-Carboniferous aquifers shifted from predominantly HCO₃-Ca·Mg before intensive mining to primarily HCO₃·SO₄-Ca·Mg, HCO₃-Na, HCO₃·SO₄-Na·Mg, and HCO₃·SO₄-Ca·Mg, HCO₃-Ca·Na, HCO₃·SO₄-Mg·Ca post-mining. Variations in the hydrochemical types of surface water were found to be complex and diverse. (2) Coal mining activities promote the dissolution of silicate rock and sodium-bearing evaporites, enhancing the strength and scale of positive alternating adsorption of cations. The oxidation of pyrite, dissolution of silicate weathering, and the leaching of coal gangue were identified as the main reasons for the significant increase of SO₄²⁻, while decarbonation in confined aquifers led to a decrease in HCO₃⁻. (3) Results from the principal component analysis and stable isotopes demonstrated the hydraulic connection among surface water, Quaternary aquifers, and Permian-Carboniferous aquifers induced by long-term OUM. The research findings provide a reference basis for the coordinated development of coal and water in the Pingshuo Mining Area and other open-pit combined underground mining areas.

Scarcity of stream salinity data poses a challenge to understanding salinity dynamics and its implications for water supply management in water-scarce salt-prone regions around the world. This paper introduces a framework for generating continuous daily stream salinity estimates using instance-based transfer learning (TL) and assessing the reliability of the synthetic salinity data through uncertainty quantification via prediction intervals (PIs). The framework was developed using two temporally distinct specific conductance (SC) datasets from the Upper Red River Basin (URRB) located in southwestern Oklahoma and Texas Panhandle, United States. The instance-based TL approach was implemented by calibrating Feedforward Neural Networks (FFNNs) on a source SC dataset of around 1200 instantaneous grab samples collected by United States Geological Survey (USGS) from 1959 to 1993. The trained FFNNs were subsequently tested on a target dataset (1998-present) of 220 instantaneous grab samples collected by the Oklahoma Water Resources Board (OWRB). The framework's generalizability was assessed in the data-rich Bird Creek watershed in Oklahoma by manipulating continuous SC data to simulate data-scarce conditions for training the models and using the complete Bird Creek dataset for model evaluation. The Lower Upper Bound Estimation (LUBE) method was used with FFNNs to estimate PIs for uncertainty quantification. Autoregressive SC prediction methods via FFNN were found to be reliable with Nash Sutcliffe Efficiency (NSE) values of 0.65 and 0.45 on in-sample and out-of-sample test data, respectively. The same modeling scenario resulted in an NSE of 0.54 for the Bird Creek data using a similar missing data ratio, whereas a higher ratio of observed data increased the accuracy (NSE = 0.84). The relatively narrow estimated PIs for the North Fork Red River in the URRB indicated satisfactory stream salinity predictions, showing an average width equivalent to 25 % of the observed range and a confidence level of 70 %.

The residual air saturation plays a crucial role in modeling hydrological processes of groundwater and the migration and distribution of contaminants in subsurface environments. However, the influence of factors such as media properties, displacement history, and hydrodynamic conditions on the residual air saturation is not consistent across different displacement scenarios. We conducted consecutive drainage-imbibition cycles in sand-packed columns under hydraulic conditions resembling natural subsurface environments, to investigate the impact of wetting flow rate, initial fluid state, and number of imbibition rounds (NIR) on residual air saturation. The results indicate that residual air saturation changes throughout the imbibition process, with variations separated into three distinct stages, namely, unstable residual air saturation (S_gr-u), momentary residual air saturation (S_gr-m), and stable residual air saturation (S_gr). The results also suggest that the transition from S_gr-u to S_gr is driven by changes in hydraulic pressure and gradient; the calculated values followed the following trend: S_gr > S_gr-u > S_gr-m. An increase in capillary number, which ranged from 1.46 × 10⁻⁷ to 3.07 × 10⁻⁶, increased S_gr-u and S_gr-m in some columns. The increase in S_gr ranged from 0.034 to 0.117 across all the experimental columns; this consistent increase can be explained by water film expansion at the primary wetting front along with a strengthening of the hydraulic gradient during water injection. Both the pre-covered water film on the sand grain surface and a pore-to-throat aspect ratio of up to 4.42 were identified as important factors for the increased residual air saturation observed during the imbibition process. Initial air saturation (S_ai) positively influenced all three types of residual air saturation, while initial capillary pressure (P_ci) exhibited a more pronounced inhibitory effect on residual air saturation, as it can partly characterized the initial connectivity of the air phase generated under different drying flow rates. Under identical wetting flow rate conditions, S_gr was higher during the second imbibition than during the first imbibition due to variations in initial fluid state, involving both fluid distribution and the concentration of dissolved air in the pore water. In contrast, NIR did not have an obvious effect on the three types of residual air saturation. This work aims to provide empirical evidences and offer further insights into the capture of non-wetting phases in groundwater environments, as well as to put forward some potential suggestion for future investigations on the retention and migration of contaminants that involves multiphase interface interactions in subsurface environments.

The catalytic performance of nano-${\mathrm{FeS}}_2$ in the sonoelectrochemical activation of peroxymonosulfate (PMS) and ozone to remove aspirin (ASP) was studied for the first time. The crystal structure and Fe bonds in the catalyst were confirmed through XRD and FTIR analysis. Within 30 min, ASP (TOC) was removed by 99.2 % (81.6 %) and 98.6 % (77.4 %) in nano-${\mathrm{FeS}}_2$/PMS and nano-${\mathrm{FeS}}_2$/$O_3$ sonoelectrochemical systems, respectively. Water anions, especially${\mathrm{HCO}}_3^{-}$ (almost 50 %), had an inhibitory effect on ASP removal. The probes confirmed that ${\mathrm{SO}}_4^{•-}$and ${\mathrm{HO}}^{•}$ were the key to ASP degradation in nano-${\mathrm{FeS}}_2$/PMS and nano-${\mathrm{FeS}}_2$/$O_3$ systems, respectively. The effective activation of oxidants due to the ideal distribution of ${\mathrm{Fe}}^{2+}$ by catalyst was the main mechanism of ASP removal, in which electric current (EC) and ultrasound (US) played a crucial role through the recycling of Fe ions, dissolution and cleaning of the catalyst. LC-MS analysis identified thirteen byproducts in the ASP degradation pathways. The energy consumption of the proposed sonoelectrochemical systems was lower than previous similar systems. This study presented economic and sustainable hybrid systems for pharmaceutical wastewater remediation.

In order to assess sites for a deep geological repository for storing high-level nuclear waste safely in Germany, various numerical models and tools will be in use. For their interaction within one workflow, their reproducibility, and reliability version-controlled open-source solutions and careful documentation of model setups, results and verifications are of special value. However, spatially fully resolved models including all relevant physical and chemical processes are neither computationally feasible for large domains nor is the data typically available to parameterize such models. Thus, simplified models are crucial for the pre-assessment of possible sites to narrow down the list of suitable candidates for which detailed site investigations and fully resolved models will be done at a later stage. Still, the accuracy of these simplified models is of importance as the pre-assessment of suitable sites will be based on them. In this study, we compare the modelling capabilities of TransPyREnd, a one-dimensional transport code based on finite differences, specifically developed for the fast estimation of radionuclide transport by the German federal company for radioactive waste disposal (BGE), with OpenGeoSys, which is a modelling platform based on finite elements in up to three spatial dimensions. Both codes are used in the site selection procedure for the German nuclear waste repository. The comparison of the model results of TransPyREnd and OpenGeoSys is augmented by comparisons with an analytical solution for a homogeneous material. For the purpose of numerical benchmarking, we consider a geological profile located in southern Germany as an example where the hypothetical repository is located in a clay-stone formation. TransPyREnd and OpenGeoSys yield overall similar results. However, both codes use different discretizations which impact is the highest for strongly sorbing compounds, while the difference gets negligible for less sorbing and more diffusive compounds as higher diffusion tends to blur the initial conditions. Overall, the OpenGeoSys model is more exact whereas the TransPyREnd model has considerable faster run times. We found in our example, that significant substance amounts are only leaving the host rock formation, if apparent diffusion is high, for which case both codes give similar results, while relative differences are considerable for strongly sorbing compounds. However, in the latter case no significant substance amount of radionuclides leaves the host-rock formation, thus deeming the differences in the model results minor for the overall safety assessments of sites.

In recent years, everyone has recognized microplastics as an emerging contaminant in aquatic ecosystems. Polypropylene is one of the dominant pollutants. The purpose of this study was to examine the effects of exposing zebrafish (Danio rerio) to water with various concentrations of polypropylene microplastics (11.86 ± 44.62 μm), including control (0 mg/L), group 1 (1 mg/L), group 2 (10 mg/L), and group 3 (100 mg/L) for up to 28 days (chronic exposure). The bioaccumulation of microplastics in the tract was noted after 28 days. From the experimental groups, blood and detoxifying organs of the liver and brain were collected. Using liver tissues evaluated the toxic effects by crucial biomarkers such as reactive oxygen species, anti-oxidant parameters, oxidative effects in protein & lipids, total protein content and free amino acid level. The study revealed that the bioaccumulation of microplastics in the organisms is a reflection of the oxidative stress and liver tissue damage experienced by the group exposed to microplastics. Also, apoptosis of blood cells was observed in the treated group as well as increased the neurotransmitter enzyme acetylcholine esterase activity based on exposure concentration-dependent manner. The overall results indicated bioaccumulation of microplastics in the gut, which led to increased ROS levels. This consequently affected antioxidant biomarkers, ultimately causing oxidation of biomolecules and liver tissue injury, as evidenced by histological analysis. This study concludes that chronic ingestion of microplastics causes considerable effects on population fitness in the aquatic environment, as well as other ecological complications, and is also critical to understand the magnitude of these contaminants' influence on ichthyofauna.