Remediation Design Research Articles

Efficient simultaneous removal of phosphate and microcystin-LR in water using a novel g-C3N4/calcite composite under dark-visible light cycles

Harmful algal blooms (HABs) associated with the abundant presence of phosphorus and microcystin in natural waters have raised a growing global concern. In this study, an adsorption-photocatalysis strategy was developed using a novel g-C3N4/calcite composite for efficient simultaneous removal of phosphate and microcystin-LR in water under dark-visible light cycles for the first time. The appropriate introduction of calcite into g-C3N4 (i.e., g-C3N4/calcite-1) was efficient in both phosphate adsorption (>78.5 %) and microcystin-LR degradation (>84.3 %) under a dark-visible light cycle of 3:3h at an optimal dosage of 100 mg/L in waters (pH 5–9 and temperature 10–40 °C). The simultaneous removal mechanisms proposed that g-C3N4/calcite-1 adsorbed phosphate via adsorption and precipitation with surface Ca2+, and degraded microcystin-LR via oxidation by photogenerated reactive species (mainly h+ and •OH). The material characterizations and density functional theory (DFT) calculations revealed that the combination of g-C3N4 and calcite could not only change the electric field distributions of calcite and optimize the charge transfer during adsorption to improve its adsorption capacity towards phosphate, but also narrow the band gaps of g-C3N4, promote the electron-hole separation and lower the first-step reaction barrier in oxygen reduction pathway during photocatalysis to enhance its visible-light photocatalytic activity towards microcystin-LR. Collectively, these findings are believed to offer valuable insights on the green material design for water environmental remediation and the underlying mechanism elucidation for simultaneous removal of phosphorus and microcystin in water to achieve effective comprehensive management of HABs.

Evaluation of intensive remediation using simulation-optimization modeling based on long-term monitoring at a DNAPL contaminated site

Simulation-optimization modeling is extensively used to identify optimal remediation designs. However, verifying these optimal solutions often remains unclear. In this study, we determine optimal groundwater remediation strategies using simulation-optimization modeling and assess the effectiveness of previous remediation efforts by validating optimized results through 14 years of long-term monitoring of trichloroethylene (TCE) contamination. The study site is the Road Administrative Office (RAO) in Wonju, Korea, where significant TCE contamination has occurred, and long-term in-situ remediation and monitoring have been conducted. We employ MODFLOW for simulating groundwater flow and MT3D for modeling dissolved TCE concentration distribution. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied to derive optimal groundwater remediation designs. Initial simulation results effectively predicted long-term TCE contamination trends and the impact of short-term in-situ remediation. Our evaluation involved comparing these optimal designs with field test outcomes, leading to the integration of continuous intensive pump-and-treat with in-situ remediation strategies. By comparing various modeling scenarios against long-term TCE contamination trends, we confirmed the effectiveness of previous remediation efforts and demonstrated that the optimal remediation design substantially minimized TCE concentrations at the main source zone. This study highlights successful strategies in historical contamination and remediation trend assessments, proposing an optimal design for pump-and-treat with reduced pumping stress to manage remaining TCE contamination at the site effectively.

Machine Learning toward Realizing End-to-End Biochar Design for Environmental Remediation

Machine Learning toward Realizing End-to-End Biochar Design for Environmental Remediation

Metal oxide-combined sol-gel synthesized ceria nanoparticles: An operative photocatalyst for visible-light-driven mineralization of ciprofloxacin antibiotic in water

The superb spreading of antibiotic waste represents a vital issue related to water and soil contamination that distress the environment and humankind. Accordingly, various research projects for the eco-friendly degradation of such contaminants. Here, we envisioned the coupling of narrow bandgap (Eg) metal oxide with copolymeric-assisted sol-gel-prepared ceria nanoparticles (CeO2) for photoelimination of ciprofloxacin (CiP) as a model for antibiotic waste in water. The few tens nanometer-sized cubic CeO2 was receptive to the irradiated visible light by a combination of a few nanometer-sized AgVO3, Bi2O3, and CoTiO3 at 10.0 wt% by simple precipitation of their salt precursors. The designed nanostructures exposed mesoporous surfaces similar to the pristine CeO2 with a specific surface area range of 165–169 m2 g−1. The 1.25 mg mL−1 dose CoTiO3-composited CeO2 displayed the best-performed photomineralization of CiP (98 ± 1.2 %) within only 2 h of light illumination compared to added oxides with an outstanding reaction rate of 0.0297 min−1. In addition, the CoTiO3/CeO2 displayed a bearable recyclability of five times with 93 % of its mineralization efficiency. The boosted photoactivity of CoTiO3/CeO2 is referred to the momentous light captivation and a band alignment with Eg minimization to 2.48 eV. Also, the constructed heterojunction among n-type CoTiO3 and n-type CeO2 has improved the photoexcited charge separation and migration as resolved by high photocurrent and photoluminescence suppression. Such a comparative study proposes an efficient photocatalyst design for clean and sustainable antibiotic waste remediation.

Adaptive machine learning surrogate based multiobjective optimization for scavenging residual saltwater behind subsurface dams

High-fidelity physically based groundwater flow and solute transport models have been limited for seawater intrusion remediation design because of computationally intensive evolutionary algorithms. Data-driven machine learning approaches are promising to substitute expensive-cost groundwater numerical models within optimization due to computing efficiency. However, machine learning surrogates may accumulate error of forecasting and thereby result in infeasible optimal solutions. To achieve desired fidelity level, this study proposes a novel adaptive machine learning surrogate based multiobjective optimization method for coastal aquifer desalination. An adaptive modeling algorithm is newly introduced to iteratively retrain poorly-performed machine learning models and enhance predicting accuracy. The method is demonstrated to seek optimal extraction and injection strategies for scavenging residual saltwater trapped in an upstream aquifer behind a subsurface dam. Two conflicting objectives of minimizing the total extraction-injection rate and maximizing saltwater removal effectiveness are considered. Three machine learning models including artificial neural network (ANN), Gaussian process (GP) and response surface regression model (RSR) are developed to replace a high-fidelity seawater intrusion model for predicting chloride concentration and salinity mass. Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed to derive Pareto fronts. Pareto optimal solutions obtained from machine learning models are compared against those from the seawater intrusion model. Results indicate that the developed machine learning models do not only have strong predicting capability, but also maintain good quality of Pareto optimal solutions, while achieving substantial computational saving up to 95%. Especially, the adaptively retrained RSR model inhibits error accumulation of forecasting and accelerates correct convergence to the true Pareto front. The proposed method is found superior performance in accurate convergence, widely-spread diversity as well as high computing efficiency than conventional methods.

Porous β-cyclodextrin polymers for rapid and efficient removal of organic micropollutants from water: The role of sulfonation and porosity on adsorption performance

Removal of organic micropollutants (OMPs) from water, especially hydrophilic and ionized ones, is challenging for water remediation. Herein, porous β-cyclodextrin polymers (PCPs) with tailored functionalization were prepared based on molecular expansion strategy and sulfonation. Partially benzylated β-cyclodextrin was knotted by external crosslinker to form PCP1, and knotting PCP1 by expansion molecule generated PCP2. PCP1 and PCP2 were sulfonated to achieve PCP1–SO3H and PCP2–SO3H. Based on systematical adsorption evaluation toward multiple categories of OMPs, it was found that the introduced strong polar –SO3H group could bring strong hydrogen bonding and electrostatic interactions. PCP2 showed the highest surface (998.97 m2/g) displayed more excellent adsorption performance toward neutral and anionic OMPs, and the adsorption mechanism for this property of PCP2 was dominated by hydrophobic interactions. In addition, the PCP1–SO3H with the lowest surface area (39.75 m2/g) rather than PCP2–SO3H with higher surface (519.28 m2/g) exhibited more superior adsorption towards hydrophilic and cationic OMPs, benefiting by hydrogen bonding and electrostatic interactions as well as appropriate porosity. These results not only confirmed the performance enhancement of PCPs through the integration of novel preparation strategy, but also provided fundamental guidance for PCPs design for water remediation.

Synergistic Engineering of Energy Band Alignment and Interfacial Electric Field Distribution over Bi-bismuth-Based Hetero-nanofibers for Boosting Visible-Light-Driven Photocatalytic Ammonia Synthesis and Antibiotic Removal.

Synergistic engineering of energy band alignment and interfacial electric field distribution is essential for photocatalyst design but is still challenging because of the limitation on refined regulation in the nanoscale. This study addresses the issue by employing surface modification and thermal-induced phase transformation in Bi2MoO6/BixOyIz hetero-nanofiber frameworks. The energy band alignment switches from a type-II interface to a Z-scheme contact with stronger redox potentials and inhibited electron traps, and the optimized built-in electric field distribution could be reached based on experimental and theoretical investigations. The engineered hetero-nanofibers exhibit outstanding visible-light-driven photocatalytic nitrogen reduction activity (605 μmol/g/h) and tetracycline hydrochloride removal rate (81.5% within 30 min), ranking them among the top-performing bismuth series materials. Furthermore, the photocatalysts show promise in activating advanced oxidants for efficient organic pollutant degradation. Moreover, the Bi2MoO6/Bi5O7I hetero-nanofibers possess good recycling stability owing to their three-dimensional network structure. This research offers valuable insights into heterojunction design for environmental remediation and industrial applications.

Feature Extraction and Classification of Power Quality Disturbances Using Optimized Tunable-Q Wavelet Transform and Incremental Support Vector Machine

The widespread integration of renewable energy sources (RESs) into power systems using power electronics-based interface devices has led to a substantial rise in power quality (PQ) issues. There is an immediate requirement for effective monitoring, detection, and classification of power quality disturbances (PQDs) that is needed to take remedial measures and design planning of the system architecture. This study presents a hybrid approach with an objective for the feature extraction and classification of PQDs. The proposed hybrid approach is comprised of an optimized tunable-Q wavelet transform (OTQWT) for the feature extraction and incremental support vector machine (ISVM). A four-stage approach is suggested for the PQ detection and classification in this study. In the first stage, the various data are retrieved both in the form of synthetic data by mathematical formulations and real-time data with prototype design setup. In the second stage, regardless of the specified wavelet function, the PQD signals are decomposed into low-pass and high-pass sub-bands using the tunable-Q wavelet transform (TQWT). However, the utilization of default decomposition parameters to address nonstationary PQ signals may lead to information loss and reduced performance of the system. To avoid this limitation, an OTQWT as an enhanced technique to TQWT based on an Adaptive Particle Swarm Optimization (APSO) is suggested. A modified objective function based on the mean square error (MSE) is used to improve the decomposition process. In the third stage, an efficient classifier is suggested based on the ISVM. Lastly, to test and evaluate the performance of the proposed approach, twelve types of PQDs including noise and multiple occurrences are considered. The comparative analysis with other popular methods reflects the better performance of the proposed approach and justifies its use for PQ detection and classification purposes in real-time​ conditions.

Comparative life-cycle sustainability assessment of centralized and decentralized remediation strategies at the city level

Remediation of contaminated soil at industrial sites has become a challenge and an opportunity for sustainable urban land use, considering the substantial secondary impacts resulting from remediation activities. The design of soil remediation strategies for multi-site remediation from a regional perspective is of great significance for cities with a large number of brownfields. Centralized and decentralized facilities have been studied in different environmental fields, yet limited research has focused on centralized soil remediation, specifically the treatment of contaminated soil from different sites through the construction of shared soil treatment facilities. This study proposes a framework for comparing centralized and decentralized strategies for contaminated soil remediation based on the integration of life-cycle sustainability assessment and multi-objective optimization. With Zhuzhou, an industrial city in China, serving as an example, results show that after optimization, the centralized scenario can reduce total environmental impacts by 25 %–41 %. In addition, the centralized scenario can reduce economic costs by 27 %–39 %, saving up to 176 million USD. The advantages of the centralized soil remediation strategy include: (1) increased use of soil washing, (2) reduced use of off-site disposal, and (3) reduced construction and efficient utilization of soil treatment facilities. In conclusion, the centralized strategy is relatively suitable for cities or areas with a large number of medium or small-sized contaminated sites. The built framework can quantitatively evaluate multiple sites soil remediation at both the city and individual site level, allowing for a straightforward and objective comparison with the optimal remediation design.

Automating SQL Injection and Cross-Site Scripting Vulnerability Remediation in Code

Internet-based distributed systems dominate contemporary software applications. To enable these applications to operate securely, software developers must mitigate the threats posed by malicious actors. For instance, the developers must identify vulnerabilities in the software and eliminate them. However, to do so manually is a costly and time-consuming process. To reduce these costs, we designed and implemented Code Auto-Remediation for Enhanced Security (CARES), a web application that automatically identifies and remediates the two most common types of vulnerabilities in Java-based web applications: SQL injection (SQLi) and Cross-Site Scripting (XSS). As is shown by a case study presented in this paper, CARES mitigates these vulnerabilities by refactoring the Java code using the Intercepting Filter design pattern. The flexible, microservice-based CARES design can be readily extended to support other injection vulnerabilities, remediation design patterns, and programming languages.

Comparing single and multiple objective constrained optimization algorithms for tuning a groundwater remediation system

Groundwater flow and particle tracking models are critical tools to simulate the natural system, contaminant fate and transport, and effects of remediation. Constrained optimization uses models to systematically explore the interplay between remedial design and contaminant fate, considering uncertainty. Sequential Linear Programming (SLP) provides a design alternative addressing a single goal (e.g. maximum hydraulic containment, maximum mass removal). Multi-objective algorithms like Nondominated Sorting Genetic Algorithm (NSGA-II) explore the tradeoffs among such objectives and more (e.g. cost, public-supply well contamination). We explore both approaches at a contaminated site in Long Island, New York USA. We compare the algorithms and ramifications on results. NSGA-II explores, at additional computational cost, explicit tradeoffs among multiple objectives, providing additional insights relative to SLP. The NGSA-II algorithm allows for graphical consideration of three objectives. SLP decision variables often settle at predetermined bounds. Bounds assignment thus differs from parameter estimation; bounds must be acceptable rather than safeguards.

Emerging trends in membrane-based wastewater treatment: electrospun nanofibers and reticular porous adsorbents as key components

Exploring material trends with reticular porous materials (MOFs, COFs) and electrospun nanofibers in hybrid membrane design for wastewater remediation.

Beyond Categories: A Flow-Oriented Approach to Social Justice on Online Labour Platforms

Online labour platforms (OLP) are transforming long-established employment relations, raising questions for researchers and policymakers alike as to the social justice implications of this increasingly pervasive, algorithmic, and platform-mediated form of work. In investigating this issue, this paper makes a case for complementing current category-based approaches to social justice, prevalent in literature and policy on OLPs, with a flow-oriented approach that recognises the diversity of gig-work trajectories when it comes to the situated enactment of social (in)justice. Inspired by the recent work of Tim Ingold and building upon seminal work on social justice by Rawls and Sen, we develop a synthetic framework for revealing the social justice implications of OLPs, in terms of the enactment of opportunities and/or barriers, from three perspectives: access to resources, capabilities to function, and correspondences with flows. The latter perspective temporally reinterprets the former two and offers a processual flow-oriented approach to social justice. We further substantiate and showcase the value-added of our approach through an empirical investigation of different gig-working stories on the Amazon MTurk platform and discuss how our flow-oriented approach leads to revealing social justice implications not foregrounded through other approaches. Finally, we derive remedial design and policy principles that can serve to reshape dialogue about social justice on OLPs, both theoretically and practically, in a manner that is more relevant and responsive to the fluid and evolving realities faced by gig-workers.

Back Analysis and Potential Remedial Approach for Failure Slope at Bukit Nanas, Kuala Lumpur

This study aims to validate the design parameters and stability of the slopes failure and propose acceptable remedial work by assessing the slope stability in Bukit Nanas, center of Kuala Lumpur. The slopes’ height is around 40 and 60 m with the gradient around 30°-45°. Totally 7 boreholes be carried out and the pertinent engineering properties were analyzed from laboratory testing and back analysis (in situ test). An established computer program SLOPE/W was used to carry out for slope stability analysis. The analysis method adopted was Morgenstern-Price’s Method. Based on the result of the field investigation and numerical analysis, the model of lowest factor of safety (FOS) that evaluated from the existing slope in critical section were selected and recommended for remedial work. Two option of remedial slope design had been proposed. The first option is soil nailing with grid beam and proposed drain while the second option is hybrid anchor with grid beam and proposed drain. Both options are used to improve the slope stability, but first option had been chosen as higher FOS and more efficient option. This remedial approach based on the main cause of slope failure in Malaysia can applied as reference in future slope remedial design.

Effect of local openings on bearing behavior and failure mechanism of shield tunnel segments

Local failures (loss of concrete or reinforcement) can severely compromise the bearing capacity of shield segments, damaging the tunnel structures. To investigate the effects of local openings on the bearing behavior and failure mechanism, four full-scale bending tests were conducted on specimens with different opening positions and diameters; monitoring of load, displacement, and concrete strain was performed during loading. The test results reveal that both the opening position and diameter significantly influence the bearing characteristics of the segment. The failure process includes four sequential stages distinguished by three critical loads, namely the cracking, failure, and ultimate loads. Subsequently, the numerical model of the local failure segment was established using the elastoplastic damage constitutive relation of the concrete and verified by inversing the full-scale test results. Based on the numerical model, parametric analyses were performed to comprehensively investigate the influences of the opening position, concrete loss, and reinforcement loss on the bending capacity. Furthermore, an analytical model was proposed, indicating that the opening position is the primary factor decreasing the bearing capacity, followed by the opening diameter and reinforcement loss. The results of this study can provide a theoretical basis for the safety assessment and remedial design of subway shield tunnels under extreme breakthrough conditions.

Knowledge Gaps, Remediation and Curricula Design in Childhood Blindness: The Case for Nursing and Midwifery Professional Training in Ghana

The paper on knowledge gaps, remediation and curricula design in childhood blindness: the case for nursing and midwifery professional training in Ghana provides a comprehensive analysis of the global evidence and findings related to childhood blindness. The authors effectively contextualize the topic within the specific context of Ghana, highlighting the need for nursing and midwifery professionals to receive adequate training to address knowledge deficits and provide appropriate care for blind children. The paper is well-researched and informative and presents a compelling argument for improving professional training in the field of nursing and midwifery.

Solubilization mechanism and mass-transfer model of anionic-nonionic gemini surfactants for chlorinated hydrocarbons

Accurate prediction and modeling of the quantitative recovery of chlorinated hydrocarbons in an aquifer by anionic-nonionic gemini surfactants requires estimates of their mass-transfer models and capture mechanisms. In this work, a series of synthesized anionic-nonionic gemini surfactants (GEOnS-m) with different molecular structures were used to solubilize different chlorinated hydrocarbons that contaminate the aquifer. GEOnS-m aggregate showed vesicle, rodlike micelle, and spherical micelle as the ethylene oxide content (EO) number increases. Non-polar chlorinated hydrocarbons (PCE, CT) mainly solubilized in the hydrophobic interior of micelles, and polar chlorinated hydrocarbons (TCE, MCB) mainly solubilized in the “palisade layer” of micelles. Solubilization processes were followed employing first-order and second-order kinetics. The solubilization rate increases with the decrease of EO number of GEOnS-m molecules. In essence, lower interfacial tension reduces the mass-transfer resistance of chlorinated hydrocarbons at the two-phase interface. The diameter of vesicles and spherical micelles increases, and rodlike micelles evenly changed to vesicles as chlorinated hydrocarbons transfer into micelles. The solubilization process of GEOnS-m for chlorinated hydrocarbons conforms to a novel “oil diffusion & micelle reformation model” that represents the coupling to two pre-existing models. And the solubilization mass-transfer mathematical model demonstrated the solubilization mass-transfer coefficient is affected by the combination of surfactant and solubilized organic properties. This study advances the application of solubilization for chlorinated hydrocarbons using anionic-nonionic gemini surfactants in surfactant-enhanced aquifer remediation (SEAR) design.

Catalytic dechlorination of 1,2-DCA in nano Cu0-borohydride system: effects of Cu0/Cun+ ratio, surface poisoning, and regeneration of Cu0 sites

Aqueous-phase catalyzed reduction of organic contaminants via zerovalent copper nanoparticles (nCu0), coupled with borohydride (hydrogen donor), has shown promising results. So far, the research on nCu0 as a remedial treatment has focused mainly on contaminant removal efficiencies and degradation mechanisms. Our study has examined the effects of Cu0/Cun+ ratio, surface poisoning (presence of chloride, sulfides, humic acid (HA)), and regeneration of Cu0 sites on catalytic dechlorination of aqueous-phase 1,2-dichloroethane (1,2-DCA) via nCu0-borohydride. Scanning electron microscopy confirmed the nano size and quasi-spherical shape of nCu0 particles. X-ray diffraction confirmed the presence of Cu0 and Cu2O and x-ray photoelectron spectroscopy also provided the Cu0/Cun+ ratios. Reactivity experiments showed that nCu0 was incapable of utilizing H2 from borohydride left over during nCu0 synthesis and, hence, additional borohydride was essential for 1,2-DCA dechlorination. Washing the nCu0 particles improved their Cu0/Cun+ ratio (1.27) and 92% 1,2-DCA was removed in 7 h with kobs = 0.345 h−1 as compared to only 44% by unwashed nCu0 (0.158 h−1) with Cu0/Cun+ ratio of 0.59, in the presence of borohydride. The presence of chloride (1000–2000 mg L−1), sulfides (0.4–4 mg L−1), and HA (10–30 mg L−1) suppressed 1,2-DCA dechlorination; which was improved by additional borohydride probably via regeneration of Cu0 sites. Coating the particles decreased their catalytic dechlorination efficiency. 85–90% of the removed 1,2-DCA was recovered as chloride. Chloroethane and ethane were main dechlorination products indicating hydrogenolysis as the major pathway. Our results imply that synthesis parameters and groundwater solutes control nCu0 catalytic activity by altering its physico-chemical properties. Thus, these factors should be considered to develop an efficient remedial design for practical applications of nCu0-borohydride.

Experimental upscaling analyses for a surfactant-enhanced in-situ chemical oxidation (S-ISCO) remediation design

Surfactant-enhanced in-situ chemical oxidation (S-ISCO) is an emerging innovative remediation technology for the treatment of dense non-aqueous phase liquids (DNAPLs). S-ISCO combines the solubilization of contaminants by means of surfactants with the chemical oxidation by an oxidizing agent, thus, potentially increasing the efficiency of the state-of-the-art ISCO technique. Scientific investigations are needed to enable the technology transfer for potential field applications based on the development of a remediation design under well-defined boundary conditions.For this purpose, experimental upscaling analyses were performed using the special infrastructure of the research facility for subsurface remediation (VEGAS). Batch tests showed that oxidation of the selected surfactant E-Mulse 3® (EM3) by activated persulfate (Na-PS) reduced the solubilization of the model contaminants 1,4-DCB, naphthalene, and PCE. As a consequence, the processes of contaminant solubilization and degradation were temporally and spatially separated in the developed remediation design.A proof of concept was provided by performing an S-ISCO medium-scale experiment (100 cm length, 70 cm height, 12.5 cm width), with 1,2-DCB as model DNAPL contaminant to be treated. A groundwater circulation well (GCW) was used to inject a 60 g/L Na-PS solution and to effectively mix the reagents. Sampling of the experiment's outflow and the soil material after treatment showed that neither rebound effects nor residual mass loadings on the soil material could be detected after termination of the S-ISCO treatment.To further evaluate the S-ISCO remediation design under field-like conditions, a large-scale S-ISCO experiment was conducted (6 m length, 3 m height, 1 m width), allowing for an extensive sampling campaign to monitor relevant processes. An efficient contaminant removal from the former source zone could be reached by surfactant solubilization, decreasing contaminant levels from initially over 2000 mg/L 1,2-DCB to final concentrations below 5 mg/L 1,2-DCB. The heterogeneously distributed contaminant degradation, implemented by a three-filter GCW, was attributed to density-induced migration processes that impeded an optimal reaction zone. A density-dependent numerical transport could qualitatively match the observations. By comparing different simulation scenarios, an adapted operation of the GCW was established that provides for a more efficient distribution of the density-influenced oxidant injection.

Gowanus Canal Superfund Site. V: Evaluation of ISS Cylinder Sample Crusts Formed During EPA 1315M Testing

The main purpose of treatability testing is to tailor a proposed remedial approach and related testing to site-specific conditions to ensure the maximum possible applicability of the bench-scale results at the full scale, and thus the success of the approach. One such adaption involves the use of modified (“M”) EPA 1315 tests to assess the leaching of volatile organic compounds (VOCs) under simulated brackish-water conditions to provide insights into the mass transfer rates that result from the in situ stabilization/solidification (ISS) of sediments at coastal sites heavily impacted by nonaqueous-phase liquids (NAPLs). As shown in this study, the use of saltwater (SW) baths during EPA 1315M testing can result in the formation of surface crusts on ISS samples and mass-transfer reductions in naphthalene, this effect being very pronounced in Gowanus Canal sediments. At the same time, the pH of the SW bath can drop from greater than 11 for a corresponding deionized water (DIW) bath to approximately 8, thus enabling biological activity. The newly formed ISS sample crusts (primarily aragonite and brucite) were similar in many respects to crusts that form on concrete under marine exposure conditions, based on mineralogical and x-ray-based analyses. However, surprisingly, while some SW baths were shown to be biologically active based on gene-probing analyses, petroleum hydrocarbon degraders, when present, did not necessarily reduce the observed leaching rates. The authors concluded that, while the surface crusts do appear to be associated with mass-transfer reductions, to varying degrees, remedial design should conservatively proceed on the basis of EPA 1315M tests utilizing DIW baths only, and any crusts potentially occurring under field conditions constitute an inherent benefit.