Adsorption Coefficient Research Articles

Prioritization of monitoring compounds from SNTS identified organic micropollutants in contaminated groundwater using a machine learning optimized ToxPi model

Advanced suspect and non-target screening (SNTS) approach can identify a large number of potential hazardous micropollutants in groundwater, underscoring the need for pinpointing priority pollutants among detected chemicals. This present study therefore demonstrates a novel multi-criteria decision making (MCDM) framework utilizing machine learning (ML) algorithms coupled with toxicological prioritization index tool (i.e., ml_ToxPi) to rank 251 chemicals of interest in groundwater for subsequent targeted analysis. The MCDM framework integrated chemical analysis data (i.e., peak area and detection frequency), toxicity profiles (i.e., bioactivity ratio, human exposure metadata, and carcinogenicity metadata), as well as the environmental fate and transport information (i.e., octanol-water partition coefficient (log Kow), water solubility, biodegradation half-life, and soil adsorption coefficient (Koc)) for ranking the identified pollutants, and the random forest machine learning model was useful for systematically determining the weighting factors of each variable according to their variable importance scores (R2 = 0.808 and 0.778 for training and testing datasets, respectively, while RMSE = 0.042 in both cases). A total of 47 unique high priority compounds (i.e., ml_ToxPi score ≥ 0.55) were identified across the investigated sampling regions, which constituted diverse groups of compounds classified according to their chemical uses, such as alkylated polycyclic aromatic hydrocarbons (alkyl-PAHs), organophosphate flame retardants (OPFRs), parent PAHs, personal care products (PCPs), pesticides, pharmaceuticals, phenols, plasticizers, transformation product (TPs), and other industrial use chemicals. By incorporating relevant variables into the proposed ML-optimized ToxPi MCDM framework, the prioritization approach described here may be adopted in future SNTS assessment of environmental and biological media.

Obtaining Highly Efficient Radon Adsorbents by Adjusting the Pore Structure of Bamboo Charcoal with Particle Size Fractionated Activation.

To achieve highly efficient adsorbents for radon (Rn), this study prepared bamboo activated carbon (BAC) using bamboo charcoal as the precursor and KOH and NaOH as activators and employed a method of activation by adjusting the pore structure through particle size fractionation. Under the same activation conditions, KOH was consumed less and showed better Rn adsorption performance than NaOH, and the solid milling method saved more activator dosage compared to the liquid immersion method. After carbonizing the bamboo, the highest Rn adsorption coefficients of the bamboo charcoal activated with particle size fractionation (0.43-0.85, 0.25-0.43, 0.18-0.25, and <0.18 mm) were 8.41 ± 0.05, 10.03 ± 0.24, 9.31 ± 0.01, and 8.15 ± 0.21 L/g, respectively under N2 conditions (at a temperature of 25 °C and humidity of 35%), which were significantly greater than those of bamboo charcoal with overall activation (7.05 ± 0.23 L/g). After optimization, all of the bamboo charcoals with different particle sizes had the highest volume ratio for pores with a diameter of 0.77 nm. BC0.43-0.85K1.25 and BC0.25-0.43K0.75 maintained 95.74 and 92.36%, respectively, of the original adsorption coefficient after 5 cycles of regeneration under nitrogen. As the bamboo charcoal particle size decreased, the optimal mass ratio of alkali/carbon also decreased. This indicates that particle-size-fractionated activation can reduce the raw material and activator waste. The optimized BAC has a significantly higher Rn adsorption coefficient than the currently used coconut shell activated carbon (4.13 ± 0.51 L/g), making it an efficient and economical adsorbent with excellent application value for radon removal.

Activated Carbon and Biochar Derived from Sargassum sp. Applied in Polyurethane-Based Materials Development.

Activated carbon (AC) and biochar (BC) are porous materials with large surface areas and widely used in environmental and industrial applications. In this study, different types of AC and BC samples were produced from Sargassum sp. by a chemical activation and pyrolysis process and compared to commercial activated carbon samples. All samples were characterized using various techniques to understand their structure and functionalities. The metal content of the samples was characterized by using an inductively coupled optical emission spectrometer (ICP-OES). A toxicity test was applied to investigate the effect of AC/BC on organisms, where Sinapis alba seed and Escherichia coli bacteria-based toxicity tests were used. The results revealed that the samples did not negatively affect these two organisms. Thus, it is safe to use them in various applications. Therefore, the samples were tested as fillers in polyurethane composites and, thus, polyurethane-AC/BC samples were prepared. The amounts of AC/BC mixed into the polyurethane formulation were 1%, 2%, and 3%. Mechanical and acoustic properties of these composites were analyzed, showing that by adding the AC/BC to the system an increase in the compression strength for all the samples was achieved. A similar effect of the AC/BC was noticed in the acoustic measurements, where adding AC/BC enhanced the sound adsorption coefficient (α) for all composite materials.

How do reactive aluminum and iron phases control soil organic carbon and phosphate adsorption capacity in agricultural topsoils across Japan?

ABSTRACT The growing number of studies suggests that the prediction of soil organic carbon (SOC) storage and persistence can be improved by accounting for variations in soil reactive metal phases. Nevertheless, the dataset on reactive metals is often limited at a national scale. In Japan, the phosphate adsorption coefficient (PAC) has been measured for agricultural soils nationwide. PAC is known to be strongly controlled by reactive metals, and hence, it can be used as a surrogate for reactive metal content. However, the relationships between SOC, reactive metals and PAC across a wide range of agricultural soils remain unclear. We thus examined these relationships using agricultural topsoils taken from 115 sites across Japan, covering two major soil great groups, Andosols and Lowland soils, as well as various land uses and soil temperature regimes (7.2–19.1°C). For the whole dataset, PAC was strongly correlated with oxalate-extractable metals (Alox + 0.5Feox: Metalox, r = 0.83) and moderately with pyrophosphate-extractable metals (Alp + 0.5Fep: Metalp, r = 0.68). These results suggest a stronger contribution of short-range-order (SRO) minerals to PAC as the former parameter reflects the content of both SRO minerals and organically complexed metals, while the latter reflects only that of organo-metal complexes. Moreover, Metalp was the best predictor of SOC contents in both Andosols (r = 0.79) and Lowland soils (r = 0.65). When only soils at near neutral soil pH range were considered, the exchangeable Ca content also co-varied with SOC in Lowland soils (n = 17). Of the two metallic elements, reactive Al phases better explained the variation of SOC and PAC in Andosols, whereas reactive Fe phases also showed similar explanatory power for PAC in Lowland soils. Our analyses also suggested that soil group (esp. erosion intensity) and land use likely impacted the SOC-Metalox relationship in Andosols, whereas environmental factors such as soil temperature and soil redox regime affected those relationships in Lowland soils. Overall, we showed that PAC is a useful surrogate for SRO minerals and organo-metal complexes and, with careful considerations of the environmental and pedogenic factors, it is potentially useful to estimate the amounts of SOC stabilized by reactive metal phases in agricultural soils across Japan.

Biocompatible Hydrogel Coating on Silicone Rubber with Improved Antifouling and Durable Lubricious Properties.

Silicone rubber is widely used in various medical applications. However, silicone rubber is prone to biofouling due to their affinity for lipids and has a high friction coefficient, which can significantly impact their efficacy and performance used as medical devices. Thus, the development of hydrogels with antifouling and lubricious abilities for the modification of silicone rubber is in high demand. We herein prepared a variety of hydrogel coatings mainly based on polyvinylpyrrolidone (PVP) and poly (ethylene glycol) diacrylate (PEGDA). We modified the silicone rubber using the prepared hydrogel coatings and cured it using a heating method. Then, we characterized its surface and evaluated the antifouling property, lubricious property, cytotoxicity, sensitization, and vaginal irritation. The results of water contact angle (WCA), protein adsorption, and friction coefficient indicated the success of the modification of the silicone rubber, leading to a significant decrease in the corresponding test values. Meanwhile, the results of cytotoxicity, sensitization, and vaginal irritation tests showed that the hydrogel coating-modified silicone rubbers have an excellent biocompatibility. This study describes how the silicone rubber could be modified with a biocompatible hydrogel coating. The hydrogel coating-modified silicone rubbers have improved antifouling and durable lubricious properties.

Brewer's Spent Grain-Cellulose-Coated Copper Electrode-Based Extended Gate Field-Effect Transistor for Nonenzymatic Glucose Detection toward Diagnosis of Diabetes Mellitus.

The demand for environmentally friendly, reliable, and cost-effective electrodes for glucose sensor technology has become a major research area in the paradigm shift toward green electronics. In this regard, cellulose has emerged as a promising flexible biopolymer solution with unique properties such as biocompatibility, biodegradability, nontoxicity, renewability, and sustainability. Because of their large surface area and porous structure, fibrous cellulose substrates quickly adsorb and disperse analytes at detection sites. This work focuses on utilizing glyoxal-treated cellulose (derived from brewer's spent grain (BSG)) for the fabrication of extended gate field-effect transistor (EGFET)-based glucose sensors. This investigation extends to the utilization of BSG-cellulose for glucose detection in biomimicking electrolytes (phosphate buffer saline) to facilitate glucose detection in human blood samples. The fabricated electrode demonstrates a linear range of glucose detection from 1 to 13.5 mM with a Langmuir adsorption coefficient (K) of 0.102. Also, its selectivity toward glucose over interfering molecules such as sucrose, fructose, ascorbic acid, and uric acid under physiological conditions has been demonstrated. This cellulose-based EGFET electrode exhibits a sensitivity of 6.5 μA mM-1 cm-2 with a limit of detection (LOD) of 0.135 mM. Computational studies by density functional theory calculations confirmed the higher binding affinity of glucose molecules with glyoxal-modified cellulose (-0.95 eV) than with pristine cellulose (-0.46 eV). Here, the novelty lies in the fabrication of electrodes with biodegradable catalysts and their integration into the EGFET configuration.

Kinetics and sorption behavior of glyphosate and tricyclazole for their efficient retention in biomixtures

The present investigation aims to study adsorption-desorption behavior of glyphosate and tricyclazole in rice straw-compost biomixtures. To enhance pesticide adsorption and performance of the bio-purification system, rice straw-compost (BM) biomixture was mixed with wheat straw biochar (WBC, 1% and 5%), and adsorption of both pesticides in control (BM) and WBCBM(1%) and WBCBM(5%) biomixtures was compared. The kinetics study suggested that the pseudo-second-order model best explained the time-dependent adsorption of both pesticides and intraparticle adsorption was not the rate-determining step. Tricyclazole was more sorbed than glyphosate in all biomixtures which can be attributed to its lower water solubility. The WBC increased the sorption of both pesticides, but the effect varied with the nature of pesticides and biochar content. The adsorption coefficient values in BM, WBCBM(1%), and WBCBM(5%) biomixtures were 26.74, 38.16, and 51.97 (glyphosate) and 38.07, 59.94, and 84.54 (tricyclazole), respectively. The adsorption data was subjected to the Freundlich, the Langmuir, and the Temkin isotherms, and among them, the Freundlich isotherm best explained pesticide adsorption behavior. Desorption results suggested that the adsorption of glyphosate was more irreversible than tricyclazole and depended upon initial pesticide concentration. This study suggested that biochar mixed rice straw-compost biomixtures can be exploited in bio-purification systems for glyphosate and tricyclazole.

Unraveling the competitive transport of metformin and erythromycin in saturated sandy soil: Experimental investigation, modeling insights and implications on SDGs

The presence of metformin (MTN) and erythromycin (ETM) in groundwater is a growing global concern due to their persistence and toxicity. This study addresses a critical gap in understanding the fate and transport of these pharmaceutical and personal care products in saturated sandy soil columns at environmentally relevant concentrations, an underexplored area. The results show that MTN, due to its high mobility, appeared earlier in the soil column with a recovery rate exceeding 90 % and an adsorption coefficient (Kd) of 1.063 Lkg−1. In contrast, ETM, with a higher Kd value of 5.426 Lkg−1, exhibited delayed breakthrough and recovery of less than 15 %, indicating stronger adsorption potential. Desorption studies indicated a greater risk of MTN leaching into groundwater, while ETM remained strongly adsorbed to soil particles. Despite the limited organic matter content in sandy soil, a significant amount of ETM was adsorbed, suggesting sands' high adsorption capacity and potential for natural remediation. This research fills a knowledge gap regarding the adsorption capacity of sandy soils at environmentally relevant concentrations, providing essential insights for environmental risk assessments and groundwater contamination mitigation strategies, directly supporting Sustainable Development Goals 3 (Health and Well-being), 6 (Clean Water and Sanitation), and 14 (Life Below Water).

A FAIR comparison of activated carbon, biochar, cyclodextrins, polymers, resins, and metal organic frameworks for the adsorption of per- and polyfluorinated substances

Per- and polyfluorinated substances (PFAS) have complex sorption behaviors, complicating removal from water and selection of suitable adsorbents. We evaluated adsorption of 44 PFAS across four adsorbent groups: activated carbon and biochar (AC and BC), cyclodextrin-based adsorbents (cyclodextrins), polymer-based adsorbents and resins, and inorganic adsorbents and metal organic frameworks (MOFs). We analyzed over 500 adsorption coefficients (Kd) from literature, calculated at aqueous equilibrium concentration of 1 ± 0.3 µg/L under comparable experimental conditions. On average, Kd of AC and BC exceeded 107 L/kg for PFAS with C-F bonds > 7, unlike other adsorbents with Kd < 107. This trend holds for C-F bonds ≥ 4. Cyclodextrins, polymer-based adsorbents and resins outperform AC and BC for C-F bonds < 4. For AC and BC, Kd follows the order PFOS>PFOA>PFBS>PFBA, with adsorption increasing with increasing point of zero charge of the adsorbent. For AC and BC, as well as cyclodextrins, Kd values were related to PFAS hydrophobicity and steric properties. Additionally, adsorption was influenced by head group type, non-fluorinated carbon atoms, and the presence of oxygen and/or chlorine in the PFAS. No clear relationship was found for the other adsorbents. Adsorption prediction using a Random Forest Regressor and literature data was feasible for AC and BC, but not for other adsorbents. Cyclodextrins outperform AC and BC for removing PFAS across varying mobilities from water, whereas AC and BC are superior for low mobility PFAS. To support further data use all data and code used are freely available, following FAIR data principles.

Migration of naphthalene in a biochar-amended bioretention facility based on HYDRUS-1D analysis

Biochar has been proved as a promising and efficient filler in bioretention facilities for enhancing the stormwater pollutants removal. However, the migration behaviors of stormwater pollutants in biochar filled bioretention facilities is unclear. In this study, as one of the most typical stormwater pollutants, naphthalene was selected as an example and a HYDRUS-1D model was first used to understand the migration behavior of naphthalene in a bioretention facility. In comparison with the conventional bioretention soil media (sandy loam), the amended biochar filled bioretention cell showed that the naphthalene removal rate was enhanced by up to 10.1%. Meanwhile, the experimental data was well-fitted by the “two-site sorption model” in HYDRUS-1D model. Another, the effect of rainfall intensity on the naphthalene migration in both bioretention columns was further investigated. The HYDRUS-1D model fitting indicated that the increase in rainfall intensity promoted naphthalene migration by increasing hydraulic conductivity and water flux. In addition, static batch experiments revealed that the biochar filled fillers achieved about 50% higher adsorption capacity than sandy loam. The sensitivity analysis from the HYDRUS-1D model data verified adsorption coefficient Kd and longitudinal dispersivity λ are the main factors affecting naphthalene migration. Finally, the model simulation displays that the proportion of naphthalene retained by the fillers was highest during high rainfall intensities, indicating that the fillers remain the most important fate for naphthalene. This study presents research on the behavior and mechanisms of stormwater pollutant transport through improved bioretention facilities.

Refining hydrogel-based sorbent design for efficient toxic metal removal using machine learning-Bayesian optimization

Hydrogel-based sorbents show promise in the removal of toxic metals from water. However, optimizing their performance through conventional trial-and-error methods is both costly and challenging due to the inherent high-dimensional parameter space associated with complex condition combinations. In this study, machine learning (ML) was employed to uncover the relationship between the fabrication condition of hydrogel sorbent and their efficiency in removing toxic metals. The developed XGBoost models demonstrated exceptional accuracy in predicting hydrogel adsorption coefficients (Kd) based on synthesis materials and fabrication conditions. Key factors such as reaction temperature (50–70 °C), time (5–72 h), initiator ((NH4)2S2O8: 2.3–10.3 mol%), and crosslinker (Methylene-Bis-Acrylamide: 1.5–4.3 mol%) significantly influenced Kd. Subsequently, ten hydrogels were fabricated utilizing these optimized feature combinations based on Bayesian optimization, exhibiting superior toxic metal adsorption capabilities that surpassed existing limits (logKd (Cu): increased from 2.70 to 3.06; logKd (Pb): increased from 2.76 to 3.37). Within these determined combinations, the error range (0.025–0.172) between model predictions and experimental validations for logKd (Pb) indicated negligible disparity. Our research outcomes not only offer valuable insights but also provide practical guidance, highlighting the potential for custom-tailored hydrogel designs to combat specific contaminants, courtesy of ML-based Bayesian optimization.

Module-based machine learning models using sigma profiles of organic linkers to predict gaseous adsorption in metal-organic frameworks

BackgroundMetal-organic frameworks (MOFs) have drawn considerable attention for their potential in adsorption applications, such as gas separation and storage. Machine learning (ML) augmented high-throughput screening approaches have emerged as an effective strategy to expedite the materials search. Traditionally, ML models developed to predict the adsorption properties of MOFs rely on various geometrical and chemical descriptors. While these descriptors are effective, they tend to be specific to each MOF's unique structure, completely omitting the modular nature of MOFs. MethodsA new approach is proposed in this study: a modular descriptor based on the sigma profile of MOF organic linkers. These sigma profiles effectively represent the chemical environment of organic linkers. With these profiles as input features, we train extreme gradient boosting (XGBoost) models to predict the Henry's coefficient (KH) of adsorption for hydrocarbons and acid gases in MOFs. FindingsThe results show that sigma profiles enhance the prediction accuracy and emerge as the most important features for hydrocarbon gases. This study highlights the potential of sigma profiles in developing accurate ML models for identifying optimal MOF adsorbents. Such an approach could also facilitate an inverse design of MOFs with targeted properties.

Concentration division for adsorption coefficient prediction using machine learning with Abraham descriptors: Data-splitting approach comparison and critical factors identification

Machine learning (ML) including Abraham descriptors from polyparameter linear free energy relationships (pp-LFERs) has been a popular method for the adsorption coefficient (Kd) prediction. However, Abraham descriptors from pp-LFERs are concentration-dependent and the significance of these descriptors can change over different adsorbate concentrations. Ignoring concentration effects on the adsorption process and Kd prediction will hinder the understanding of interactions among solutes, solvents and adsorbents at different equilibrium concentration (Ce) ranges. Therefore, our study first systematically investigated the concentration effects on micropollutant adsorption to carbon-based adsorbents using ML with Abraham descriptors. Concentration-selection approach, as a new data-splitting approach, divided the whole dataset according to the different Ce ranges. This concentration-selection approach performed better than the data-splitting approach used in previous studies. After the ML models were built in different Ce subsets, Shapley values were calculated to quantify input descriptor contributions. The results indicated specific surface area (BET) was the only critical factor when Ce was in the highest range. The importance of Abraham descriptors increased gradually when Ce decreased. Total pore volume (Vt) was a far less important feature than BET for Kd prediction. Critical factors identified at different Ce ranges for Kd prediction provide a guidance for novel carbon-based adsorbent design.

Enhancing herbicide adsorption in low-fertility soil using sugarcane biochar: Insights from Imazapic dynamics

Biochar amendment has emerged as a potential solution for preventing, remediating, and mitigating agricultural compound pollution. This groundbreaking technique not only improves crucial soil properties like porosity, water retention capacity, cation exchange capacity, and pH, but also intricately impacts the interaction and retention mechanisms of polluting molecules. In this study, we investigate the dynamic of the herbicide Imazapic when subjected to applying pyrolyzed biochars, specifically at temperatures of 300 and 500 °C, within the context of a low-fertility soil characterized as dystrophic Yellow Ultisol (YUd) in a sugarcane cultivation area in Igarassu-PE, Brazil. The biochars were produced from sugarcane bagasse by pyrolysis process in a muffle furnace. In laboratory conditions, with saturated soil columns under steady-state, analyses of the mechanisms involved in interaction and transport and determining hydrodispersive parameters for Imazapic were performed by the two-site nonequilibrium transport model using the CXTFIT 2.0 program. Samples of YUd soil amended with biochar pyrolyzed at 300 °C presented a negligible interaction with Imazapic. However, adding biochar pyrolyzed at 500 °C (BC500) to the soil samples enhanced the adsorption coefficient and improved the interaction with Imazapic. This research points out that biochar produced from agricultural waste biomass, such as sugarcane bagasse specifically pyrolyzed at 500 °C, offers a potential means to adsorb herbicides, reducing their leaching to deeper layers of the amended soils and the risk of groundwater contamination and potential environmental negative impacts.

New silica-based adsorbents for water purification: Removal of short- and long-chain perfluoroalkyl sulfonic acids (PFSA) at sub-nanomolar concentrations

Perfluoroalkyl acids (PFAAs) are widespread in the aquatic environment and also measurable in ground and drinking water. Because of the insufficient PFAA elimination in conventional water treatment processes, e. g. active carbon based methods, consumers in areas with contaminated water supplies are exposed to an elevated health hazard. For this purpose, the applicability of five differentially fluorinated silica-based adsorbents (HSU00107954-958) to remove the potentially human toxic perfluoroalkyl sulfonic acids(PFSAs) perfluorooctane sulfonic acid (PFOS), perfluorohexane sulfonic acid (PFHxS), and perfluorobutane sulfonic acid (PFBS) from water was investigated with regard to removal efficiencies (REs) and equilibrium loadings. During the adsorbent screening at nanomolar concentrations (20.0–33.4 nmol L−1) maximum REs of 46.9% for PFBS (HSU00107954), 79.4% for PFHxS (HSU00107954), and between 86.5 to 96.7% for PFOS (HSU00107956, and HSU00107954, respectively) have been achieved. Even at picomolar concentrations (< 400 pmol L−1) HSU00107954 was still able to eliminate PFBS and PFHxS with an efficiency of 46.3–51.2% and 79.1–88.2%, respectively. Analyses of the equilibrium loadings of the functionalized adsorbents in the concentration range 40.1 pmol to 3.34 nmol L−1 resulted in appropriate linearized Freundlich isotherms for all investigated PFSA. Compared to literature-based Freundlich adsorption coefficients (KF) for granular activated carbon (GAC), the determined KF values (nmol(1−n) Ln m−2) of the most efficient adsorbents HSU00107956 and HSU00107954 for each PFSA were significantly 8–10 and 50–60 times higher, respectively. These proven increased adsorption capacities relative to activated carbon possibly indicate specific PFSA selectivities of the functionalized macroporous silica adsorbents.

Sol-Gel Synthesis of TiO2 with Pectin and Their Efficiency in Solar Cells Sensitized by Quantum Dots.

In this study, titanium oxide TiO2 nanoparticles were produced using the sol-gel approach of green synthesis with pectin as the reducing agent. The synthetized TiO2 nanoparticles with pectin were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), visible light absorption (UV-Vis) and the BET method. The structure and morphology of the TiO2 powder were described with SEM, revealing uniform monodisperse grains with a distribution of 80% regarding sizes < 250 nm; the resulting crystal phase of synthetized TiO2 was identified as an anatase and rutile phase with a crystallinity size estimated between 27 and 40 nm. Also, the surface area was determined by nitrogen adsorption-desorption using the Brown-Emmet-Teller method, with a surface area calculated as 19.56 m2/g, typical of an IV type isotherm, indicating mesoporous NPs. UV-Vis spectra showed that sol-gel synthesis reduced the band gap from the 3.2 eV common value to 2.22 eV after estimating the optical band gap energy using the adsorption coefficient; this translates to a possible extended photo response to the visible region, improving photoactivity. In addition, the power conversion of the photoelectrode was compared based on similar assembly techniques of TiO2 electrode deposition. Quantum dot crystals were deposited ionically on the electrode surface, as two different paste formulations based on a pectin emulsifier were studied for layer deposition. The results confirm that the TiO2 paste with TiO2-synthesized powder maintained good connections between the nanocrystalline mesoporous grains and the deposited layers, with an efficiency of 1.23% with the transparent paste and 2.27% with the opaque paste. These results suggest that pectin could be used as a low-cost, functional sol-gel catalysis agent for the synthesis of controlled NPs of metal oxide. It demonstrates interesting optical properties, such as an increase in photo response, suggesting further applications to photocatalysts and biomedical features.

Implementation of temporal moments to elucidate the reactive transport of metformin and erythromycin in the saturated porous media.

This study investigates the fate and transport dynamics of metformin (MTN) and erythromycin (ETM), both classified as pharmaceutical and personal care products (PPCPs), in a saturated sandy soil column using temporal moment analysis (TMA). The key flow and transport parameters, including Darcy velocity, longitudinal dispersivity, adsorption, and degradation coefficients, were analyzed. The results reveal that MTN, a highly mobile contaminant, is eliminatedfrom the column in approximately 40days, while ETM shows significant adsorption due to its hydrophobic and adsorptive nature. Darcy velocity significantly affects PPCP transport; a one-order magnitude change alters contaminant mass recovery at the column outlet by 88% for MTN and 39-fold for ETM. Longitudinal dispersivity has minimal impacton the transport of PPCPs. However adsorption primarily governs the fateofPPCPs with high adsorption coefficients (Kd), and degradation rates control the fateoflow-sorbing PPCPs. A one-order magnitude change in Kd results in a 55% change in the zeroth temporal moment (ZTM) of MTN and a 30-fold change in the case of ETM. Additionally, a one-order magnitude change in the degradation coefficient leads to a 60% variation in MTN's ZTM and a 5% variation in ETM's ZTM. Thus, TMA is a valuable tool for understanding PPCP dynamics in subsurface environments, providing critical insights for managing their increasing concentrations.

Adsorption–desorption and leaching behavior of benzovindiflupyr in different soil types

Benzovindiflupyr is a succinate dehydrogenase inhibitor fungicide that targets mitochondrial function for disease control. In this study, we investigated the adsorption–desorption and leaching behavior of benzovindiflupyr in eight soil types using the batch equilibrium method and the soil column leaching method. A Freundlich model (r2 > 0.9959) was used to better characterize the adsorption-desorption process in eight soil types, with adsorption coefficients (KF-ads) ranging from 2.303 to 17.886. KF-ads was significantly and positively correlated (p < 0.05) with the organic carbon content. High temperatures and increased initial pH of aqueous solutions led to a decrease in benzovindiflupyr adsorption in the soil. The adsorption was also influenced by factors such as ionic strength, humic acid, surfactant type, microplastic type, and particle size and concentration. Moreover, benzovindiflupyr exhibited low leachability in all four soils selected, but different leaching solutions affected the risk of benzovindiflupyr migration to groundwater. Overall, this study provides insights into the adsorption characteristics of benzovindiflupyr in different soils and provides key information for environmental risk assessment.

Comment on “Adsorption of uranium (VI) complexes with polymer-based spherical activated carbon”, published by Y.-A. Boussouga et al. [Water Research 249 (2024) 120825]

Calculation of thermodynamic parameters of adsorption such as Gibbs free energy ΔG°ads from experimentally determined adsorption data can be helpful for elucidation of sorption mechanisms. This approach includes the transformation of adsorption coefficients Kd or KL into dimensionless standard adsorption constants Kads [-]. The present comment reveals recently published misleading approaches and offers thermodynamically sound alternatives.

HTO and selenate diffusion through compacted Na-, Na–Ca-, and Ca-montmorillonite

Radionuclide transport in smectite clay barrier systems used for nuclear waste disposal is controlled by diffusion, with adsorption significantly retarding transport rates. While a relatively minor component of spent nuclear fuel, 79Se is a major driver of the safety case for spent fuel disposal due to its long half-life (3.3 × 105 yr) and its low adsorption to clay (KD < 10 L/kg), thus a thorough understanding of Se diffusion through clay is critical for understanding the long-term safety of spent fuel disposal systems. Through-diffusion experiments with tritiated water (HTO, conservative tracer) and Se(VI) were conducted with a well-characterized, purified montmorillonite source clay (SWy-2) under a constant ionic strength (0.1 M) and three different electrolyte compositions: Na+, Ca2+, and a Na + -Ca2+ mixture at pH 6.5 in order to probe the effects of electrolyte composition and interlayer cation composition on clay microstructure, Se(VI) aqueous speciation, and ultimately diffusion. The results were modeled using a reactive transport modeling approach to determine values of porosity (ε), De (effective diffusion coefficient), and KD (distribution coefficient for adsorption). HTO diffusive flux was higher in Ca-montmorillonite (De = 1.68 × 10−10 m2 s−1) compared to Na-montmorillonite (De = 7.83 × 10−11 m2 s−1). This increase in flux is likely due to a greater degree of clay layer stacking in the presence of Ca2+ compared to Na+, which leads to larger inter-particle pores. Overall, the Se(VI) flux was much lower than the HTO flux due to anion exclusion, with Se(VI) flux following the order Ca (De = 1.03 × 10−11 m2 s−1) > Na–Ca (De = 2.12 × 10−12 m2 s−1) > Na (De = 1.28 × 10−12 m2 s−1). These differences in Se(VI) flux are due to a combination of factors, including (1) larger accessible porosity in Ca-montmorillonite due to clay layer stacking and smaller electrostatic effects compared to Na-montmorillonite, (2) larger accessible porosity for neutral-charge CaSeO4 species which makes up 32% of aqueous Se(VI) in the pure Ca system, and (3) possibly higher Se(VI) adsorption for Ca-montmorillonite. Through a combination of experimental and modeling work, this study highlights the compounding effects that electrolyte and counterion compositions can have on radionuclide transport through clay. Diffusion models that neglect these effects are not transferable from laboratory experimental conditions to in situ repository conditions.