Cr(VI) remediation performance of zero valent iron (ZVI) and activated carbon (AC) mixtures is investigated via Spectral Induced Polarization (SIP) and transport modeling in two parallel laboratory columns. The strong correlation (R² = 0.75-0.96) between chargeability and Cr (VI) removal capacity provides a real-time proxy for tracking reactive surface area dynamics and contaminant degradation progress. Acid-washed ZVI demonstrates enhanced reactivity, with prolonged remediation efficiency. Reactive transport modeling calibrated by chargeability improves accuracy of contaminant breakthrough curves, revealing distinct removal capacities and material utilization efficiencies in different zones of the two laboratory columns. In the acid-washed column, the lower section of the column shows higher Cr(VI) removal (3.92 mg/g) and lower active surface area depletion rate (0.012 g/mg) than the upper section, highlighting the early confrontation of the Cr(VI) plume with ZVI-AC mixtures in the lower section. SIP reveals the spatial heterogeneity for Cr(VI) removal capacity of ZVI-AC, facilitating the zoned optimization of PRB design to extend the barrier's service life.

In-situ microemulsion flushing has been considered a development potential technology for remediating aquifers contaminated by dense non-aqueous phase liquids (DNAPLs) via increasing the apparent solubility and reducing the interfacial tension. Normally, monitoring wells are established in the remediation area for tracking the spread of injectant and the removal of DNAPLs. On this basis, alternating time domain induced polarization (TDIP) measurements and injection/pumping operations were conducted at a CHCl3-contaminated weathered andesite site. Full-decay TDIP data were inverted and correlated with groundwater sampling to reflect contaminant solubilization and reagent distribution. Interpretation results demonstrated that TDIP provided spatially continuous electrical imaging in the entire remediation volume, capturing the footprints of CHCl3-contaminated groundwater and the remediation reagent. The injected reagent exhibited strong conductivity and polarization contrasts with contaminated groundwater, confirming its spread across most of the weathered andesite layer. Thresholds of m = 50 mV/V delineated CHCl3 contamination zones exceeding the regulatory limit of 300 µg/L. Reagent spreading along profiles revealed preferential flow paths within highly permeable fracture zones. Chargeability reduction is correlated with DNAPL desorption, showing over 90

Environmental contamination from unregulated landfills poses significant challenges, requiring accurate subsurface characterization. Non-invasive geophysical techniques like electrical resistivity tomography (ERT) and time domain induced polarization (TDIP) provide valuable insights but their interpretation often remains subjective. This study addresses the need for more objective and efficient approaches to identify and delineate contaminated zones within landfills. By integrating ERT and TDIP surveys with K-means clustering, we successfully partitioned the subsurface into five distinct, quantitatively characterizable clusters based on resistivity and phase parameters. This achieved an overall clustering matching rate of 87.1 %, while the chromium-containing sludge zones showed an accuracy of 84.1 %, a recall of 84.6 %, a precision of 88.0 %, and an F1 score of 86.3 % when validated against borehole data. Our results demonstrate that machine learning-enhanced geophysics can autonomously distinguish between domestic waste and chromium-containing sludge without prior labels, establishing clearer contaminant boundaries and reducing interpretation bias compared to traditional methods. This approach not only improves the reliability of contamination mapping but also offers a robust framework for data fusion in complex environmental settings. The methodology presents a powerful tool for landfill characterization and remediation guidance, with potential applications extending to various contaminated site investigations and environmental management strategies.

Monitoring removal performance of permeable reactive barriers (PRBs) for groundwater nitrate remediation and distinguishing remediation mechanism contributions remains a key challenge. Based on flow-through column experiments, this study integrated spectral induced polarization (SIP) monitoring with reactive transport modeling to investigate the dynamics of removal by zero-valent iron (ZVI) and activated carbon (AC) mixtures. SIP parameters link material changes to removal performance. The strong correlation between normalized chargeability and cumulative removal capacity of constrained reactive transport model errors, with average relative errors of 12.5% and 21% for predicted breakthrough concentrations. The presence of Ca2+ and in solution promoted the corrosion of ZVI and the total -N removal capacity increased from 6.61 to 9.05 mg/g. The remediation enhancement is concentrated primarily in the proximal sections near the contaminant injection point. The reaction term exhibits a substantially increase compared to the adsorption term. Conversely, remediation performance declines in distal sections. This finding highlights the important contribution of regulatory ions to the reaction term and emphasizes the necessity of rational proportioning of remediation materials in different PRB sections for enhanced material utilization efficiency. Transport models calibrated via SIP robustly quantify spatial heterogeneity in adsorption and reaction processes, exhibiting significant potential to guide the design of PRBs.

Metallic infrastructure, such as steel sheet situated within landfills, poses significant challenges to accurate tracking of leachate using induced polarization (IP) methods. The application of IP method is efficient to delineate leakage; however, the presence of metallic structures can cause an interference on the survey and generate high-chargeability anomalies as observed in field survey. To comprehensively validate the interference caused by steel sheets, both numerical and empirical field tests were conducted. As expected, both results demonstrate that interference diminishes as the distance between survey line and metallic structure increases. Additionally, at consistent intervals, the chargeability values inverted using integral chargeability (IC) exhibit a monotonic increase with depth. Moreover, the interference induced by metallic structures is also affected by the controlling factors (i.e. depth, width and thickness) of the structure alongside the intrinsic resistivity and chargeability. Strategic utilization of the size, chargeability and spatial positioning of metallic structures relative to survey lines can significantly enhance background polarization. This approach offers a promising framework for improving the spatial resolution of subsurface targets exhibiting low polarization effects. The optimization of survey line placement, which must consider the dimensions and electrical properties of metallic structures such as steel sheets, is essential for accurately characterizing landfill leachate using the IP method.

Abstract Time domain induced polarization (TDIP) has emerged as a highly effective tool for delineating contaminated sites. While numerous studies have focused on conceptual and mechanistic modelling, inversion methods, and coupled simulations to enhance accuracy, the acquisition of high-quality TDIP data has received insufficient attention. This research analyses the limitations of TDIP data quality in contaminated site surveys. Data acquisition layouts were evaluated from seven distinct sites, with a particular focus on the controlling factors that influence data quality. This study addresses the selection of reliable TDIP acquisition layouts and the assessment of information content regarding data quality. The results demonstrate significant differences in the raw data obtained through different acquisition layouts, with the inversion results derived from these datasets exhibiting varying degrees of discrepancy. The data quality associated with dual cables utilizing non-polarizable electrodes layout (Dual-CL-NP) is markedly superior, thereby ensuring the reliability of the results. Furthermore, apparent resistivity and measured voltage are identified as key factors controlling data quality. Finally, preliminary threshold values for selecting the acquisition layouts are established. Specifically, the Dual-CL-NP should be utilized when the average apparent resistivity of the TDIP profile is less than 7.9 Ωm. This threshold will be refined by adding more suitable field examples. Consequently, a preliminary guideline for TDIP data acquisition is proposed to address limitations associated with TDIP data quality and facilitates its advancement.

ABSTRACT As geomembranes emerged as a prevalent solution to mitigate reservoir seepage, maintaining the structural integrity of geomembrane antiseepage systems (GAS) is essential for reservoir safety. Conventional geophysical methods often struggle to detect anomalies in GAS deposits beneath deep water layers due to limited resolution and insufficient penetration depth. This study presented the suspended resistivity profiling (SRP) method, which enabled rapid, high-resolution underwater surveying unaffected by water depth using small electrode spacing near targets. With the measurement cable suspended 1–2 m above the target, a 1-m-thick cover layer was accurately detected in synthetic and field experiments using a nonconventional array with a 2-m electrode spacing. Field investigations revealed that the thickness of the cover layer varies between 0.7 and 1.6 m. An integrity index, computed from these thickness variations, indicated that a significant portion of the reservoir basin lay within the normal range. However, notable disparities across the reservoir revealed sedimentation risks in the northeast and erosion risks in the west. The potential discrepancies associated with SRP were evaluated by examining the influence of electrode positioning on geometric factors; results showed relative errors of less than 2%, which underscored the reliability of the SRP method. Furthermore, a summary from various publications highlighted the capability of the SRP approach for high-resolution underwater imaging at a survey speed of 4 km/h. These findings provided a robust framework for decision makers to develop more cost-effective strategies for assessing and restoring the integrity of GAS.

Soil and groundwater contamination has been widely concerned because of its impact on industrial, agricultural production, and even human health. Accurate delineation of contaminant distribution is the basis for successful remediation strategies. Traditional drilling based methods are costly and less efficient. Geophysical methods, particularly electrical resistivity (ERT) and induced polarization (IP), are sensitive to soil and groundwater contamination and have been proven very effective. However, there were still some pressing issues to be resolved, such as IP mechanism of contaminant, data acquisition, inversion strategies and monitoring system. In this study, we proposed the conceptual model of IP response for LNAPLs in-situ remediation process based on laboratory columns and sandboxes IP measurements, and quantified the effect of contaminant removal on IP parameters. In addition, the IP data acquisition method were improved for contaminated site surveys, doubling the detection depth and significantly increasing the IP data quality. Moreover, we propose a refined structure-constrained method that updates the smooth weights of all eight elements surrounding a boundary element using three different magnitudes. Combined with the joint interpretation of multisource data, detection accuracy was improved and the number of boreholes was reduced. We have applied ERT and IP techniques to more than 30 contaminated sites and proved their effectiveness.

Time domain induced polarization (TDIP) has emerged as potential and effective geophysical method for delineating contaminated sites owing to its cost effectiveness and information continuity, in addition to the advantage of providing more parameter information to reduce uncertainty. However, the information content of different TDIP datasets (partial integral and full decay) is unclear and thus, the chargeability parameter cannot be used consistently. These issues limit the reliability of TDIP method and the ability to establish a database for contaminants and hydrogeology surveys. In this study, synthetic experiments were carried out to evaluate the TDIP results using both partial integral and full decay data. Furthermore, field TDIP data was also applied to demonstrate its reliability in locating solid waste deposit. The full decay method provides accurate parameter values and distribution, whereas the chargeability values obtained from the partial integral method are inconsistent and can merely be employed to delineate target areas based on relative differences. In addition, the distribution of parameter shows that the partial integral inversion is more suitable for delineating smooth structures such as contamination plume, whereas the full decay inversion is effective for highly heterogeneous media like geological layers. Data quality analysis proves that poor TDIP data is mostly at large depths over 1/8 of the maximum electrode spacing, resulting in the removal of approximate 80 % full decay data. Consequently, identifying deep information may pose significant challenges. Finally, a preliminary TDIP survey database for solid waste deposits is proposed based on the existing publications.

Precise delineation of the spatial distribution of Dense Non-Aqueous Phase Liquids (DNAPLs) is critical for effective remediation. This feasibility study presents a cross-borehole full-decay time domain induced polarization (TDIP) survey, which incorporates petrophysical models that correlate electrical properties with water saturation. Synthetic DNAPL-contaminated zones can be delineated directly between the boreholes. From these simulations, complex resistivity and DNAPL saturation were retrieved, resulting in a high structural similarity index (SSIM) of over 0.9 when compared to preset scenarios. To further enhance the estimation of DNAPL saturation at the decimeter-level resolution, numerical results indicate that an increased ratio of borehole depth to the inter-borehole distance is especially helpful for rectifying potential biases inherent in the full-decay TDIP survey. The present work serves as a preliminary study toward field applications of cross-borehole full-decay TDIP, aiming at high-resolution DNAPL characterization and guiding optimal remediation strategies.

Time domain induced polarization (TDIP) has emerged as a highly effective tool for characterizing soil and groundwater contamination. Numerous studies have focused on the objective of enhancing accuracy of TDIP results. However, the acquisition of high quality TDIP data has received less attention than it deserved. In this study, three data acquisition methods were evaluated across seven distinct sites, with a particular focus on the controlling factors that influence data quality. This study addresses the questions about how to select a reliable TDIP acquisition method. The results demonstrate that there are significant differences in the raw data obtained through different acquisition methods, with the inverted results derived from these datasets exhibiting varying discrepancy. The data quality associated with the dual cables utilizing non-polarizable electrodes layout (Dual-CL-NP) is markedly superior, thereby ensuring the reliability of the results. Furthermore, apparent resistivity and measured voltage are identified as the key factors on data quality. The threshold values for selecting the acquisition method are determined. The Dual-CL-NP method should be utilized when the averaged apparent resistivity is less than 7.9 Ω·m. Consequently, a guideline for TDIP data acquisition is proposed, which addresses the limitations associated with TDIP data quality and facilitates its advancement.

Solid waste deposits are one of the leading environmental crises in soil and groundwater protection, and their negative impacts will last for decades. In recent years, geophysical methods have been recognized as effective techniques for providing imaging of environmental investigations. A time domain induced polarization (TDIP) survey was undertaken to map solid waste deposits and discriminate contaminant types, supplemented by borehole logs and soil sample analyses. The whole dataset was inverted using a laterally constrained inversion scheme for reconstructing the electrical parameters of soils in terms of electrical resistivity and phase. The results reveal resistivity <2 Omega m or phase >10 mrad zones that show a good agreement with the extent of chromiumcontaining sludge or municipal solid waste. The thickness and location of waste types from surface measurements are further validated and quantified by borehole information. Four zones of solid waste deposits are discriminated with a total volume of 42,355 m(3). TDIP responses also expose a quasi-linear relationship with concentrations of total chromium and total organic carbon. In conclusion, the non-invasive TDIP survey provides quantitative information for future land planning and remediation actions in the area.

Background:Ultrasound based radiomics prediction model can improve the differentiation ability of benign and malignant thyroid nodules to avoid overtreatment. This study evaluates the role of predictive models based on intranodular and perinodular ultrasound radiomics in distinguishing between benign and malignant thyroid nodules. Methods:A total of 1,076 thyroid nodules were enrolled from three hospitals between 2016 and 2022, forming the training, validation and test cohorts. The clinical signature (Clinic_Sig) was developed based on clinical information and conventional morphological features of ultrasound. Expanding 1 pixel, 3 pixels, 5 pixels, 7 pixels, and 9 pixels outward from the thyroid nodule, six radiomics models were constructed using intranodular (intra) and combined radiomics (intranodular and perinodular: +p1,+p3,+p5,+p7,+p9) features. The model with the best area under the curve (AUC) was defined as radiomics signature (Rad_Sig). The combined model was constructed from Clinic_Sig and Rad_Sig. AUC and calibration curves were used to evaluate the predictive performance of the model. Decision curve analysis (DCA) was used to evaluate the clinical net benefit of the model. Results:The intra+p1 radiomics model exhibited the highest efficacy (AUC =0.863) in the test cohort, which was combined with Clinic_Sig to construct the combined model. Compared with Clinic_Sig and Rad_Sig, the combined model showed the higher predictive performance, with AUCs of 0.942 (training), 0.894 (validation), and 0.933 (test). The calibration curve showed that the predicted probabilities of the combined model were in good agreement with the actual probabilities, and DCA indicated that it provided more net benefit than the treat-none or treat-all scheme. Conclusions:The combined model based on clinical signatures, intranodular and perinodular ultrasound radiomics has the potential to effectively predict benign or malignant thyroid nodules.