Fate Processes Research Articles

Comparison of novel physics-guided machine learning models with empirical equations for predicting longitudinal dispersion coefficient in diverse natural river systems

Accurate calculation of the longitudinal dispersion coefficient (LDC) is crucial for assessing river fate and transport processes. Traditional methods, including experimental, analytical, and empirical equations, each have their challenges, such as complexity and susceptibility to errors. This study introduces and evaluates advanced physics-guided machine learning (ML) models, including hybrid hydrodynamic-particle simulation (HHPS), physics-enhanced ML (PEML), and physics-regularized regression trees (PRRT). Our dataset includes hydraulic and geometric parameters collected from 50 diverse rivers across the US and the UK, encompassing variables such as river width (W), flow depth (H), average flow velocity (U), flow shear velocity (U*), concentration of the solute (μgL) and LDC (ε). Input parameters were dimensioned using the UU∗ and WHratios, while the dimensionless LDC (εHU∗) served as the model output. By embedding core hydrodynamic principles such as continuity, mass and momentum conservation, and Navier-Stokes equations into the ML algorithms, these models achieved high predictive accuracy. Specifically, the HHPS model reached a coefficient of determination of 0.997, and both PEML and PRRT demonstrated Nash-Sutcliffe efficiencies exceeding 0.950, significantly outperforming traditional empirical equations. Additionally, SHapley Additive exPlanations (SHAP) sensitivity analysis revealed the substantial influence of channel width and flow conditions on LDC predictions. Our study highlights the superior performance of physics-guided ML models in providing accurate and reliable tools for river water quality management, demonstrating their substantial improvements over traditional methods and their potential broader applications in environmental studies.

Systematic Assessment of Mechanisms, Developments, Innovative Solutions, and Future Perspectives of Microplastics and Ecotoxicity – A Review

AbstractAs plastics become more ubiquitous, their impact on the environment and on human health cannot be overlooked. Once generated, micro‐ and nano‐plastics end‐up in the environment, causing widespread health and environmental risks. This is a significant environmental problem given the minuscule sizes of microplastics, and therefore warrants further investigation. This study presents a comprehensive review of the ecotoxicology of microplastics and methods for their degradation and decomposition besides discussing the fate and transport processes, recent progress, emerging strategies, challenges and potential future directions. The authors carefully evaluate the processes through which microplastics cause harm, from molecular interactions in species, to ecological impacts, and end with advances in microplastic biodegradation. Different kinds of microplastics found in the environment include polyethylene, polystyrene, polypropylene, polyvinyl chloride, polycarbonate, polyurethane, polypropylene, and polyethylene terephthalate. Analysis of microbial and enzymatic decomposition provides several swelling mitigation strategies designed to reduce environmental threats. In‐depth investigations of microplastic ecotoxicity and biodegradation are being facilitated by interdisciplinary proposals in the areas of nanotechnology, new analytical methods, and synthetic biology. The extensive study helps understand microplastics comprehensively which in‐turn ensures informed actions to mitigate the challenge of the environmental impact of microplastics for sustainable future.

ScBoolSeq: Linking scRNA-seq statistics and Boolean dynamics.

Boolean networks are largely employed to model the qualitative dynamics of cell fate processes by describing the change of binary activation states of genes and transcription factors with time. Being able to bridge such qualitative states with quantitative measurements of gene expression in cells, as scRNA-seq, is a cornerstone for data-driven model construction and validation. On one hand, scRNA-seq binarisation is a key step for inferring and validating Boolean models. On the other hand, the generation of synthetic scRNA-seq data from baseline Boolean models provides an important asset to benchmark inference methods. However, linking characteristics of scRNA-seq datasets, including dropout events, with Boolean states is a challenging task. We present scBoolSeq, a method for the bidirectional linking of scRNA-seq data and Boolean activation state of genes. Given a reference scRNA-seq dataset, scBoolSeq computes statistical criteria to classify the empirical gene pseudocount distributions as either unimodal, bimodal, or zero-inflated, and fit a probabilistic model of dropouts, with gene-dependent parameters. From these learnt distributions, scBoolSeq can perform both binarisation of scRNA-seq datasets, and generate synthetic scRNA-seq datasets from Boolean traces, as issued from Boolean networks, using biased sampling and dropout simulation. We present a case study demonstrating the application of scBoolSeq's binarisation scheme in data-driven model inference. Furthermore, we compare synthetic scRNA-seq data generated by scBoolSeq with BoolODE's, data for the same Boolean Network model. The comparison shows that our method better reproduces the statistics of real scRNA-seq datasets, such as the mean-variance and mean-dropout relationships while exhibiting clearly defined trajectories in two-dimensional projections of the data.

Pan-cancer Analysis Reveals m6A Variation and Cell-specific Regulatory Network in Different Cancer Types.

As the most abundant messenger RNA (mRNA) modification, N6-methyladenosine (m6A) plays a crucial role in RNA fate, impacting cellular and physiological processes in various tumor types. However, our understanding of the role of the m6A methylome in tumor heterogeneity remains limited. Herein, we collected and analyzed m6A methylomes across nine human tissues from 97 m6A sequencing (m6A-seq) and RNA sequencing (RNA-seq) samples. Our findings demonstrate that m6A exhibits different heterogeneity in most tumor tissues compared to normal tissues, which contributes to the diverse clinical outcomes in different cancer types. We also found that the cancer type-specific m6A level regulated the expression of different cancer-related genes in distinct cancer types. Utilizing a novel and reliable method called "m6A-express", we predicted m6A-regulated genes and revealed that cancer type-specific m6A-regulated genes contributed to the prognosis, tumor origin, and infiltration level of immune cells in diverse patient populations. Furthermore, we identified cell-specific m6A regulators that regulate cancer-specific m6A and constructed a regulatory network. Experimental validation was performed, confirming that the cell-specific m6A regulator CAPRIN1 controls the m6A level of TP53. Overall, our work reveals the clinical relevance of m6A in various tumor tissues and explains how such heterogeneity is established. These results further suggest the potential of m6A in cancer precision medicine for patients with different cancer types.

Conceptualizing Controlling Factors for PFAS Salting Out in Groundwater Discharge Zones Along Sandy Beaches.

Understanding fate and transport processes for per- and poly-fluoroalkyl substances (PFAS) is critical for managing impacted sites. "PFAS Salting Out" in groundwater, defined herein, is an understudied process where PFAS in fresh groundwater mixes with saline groundwater near marine shorelines, which increases sorption of PFAS to aquifer solids. While sorption reduces PFAS mass discharge to marine surface water, the fraction that sorbs to beach sediments may be mobilized under future salinity changes. The objective of this study was to conceptually explore the potential for PFAS Salting Out in sandy beach environments and to perform a preliminary broad-scale characterization of sandy shoreline areas in the continental U.S. While no site-specific PFAS data were collected, our conceptual approach involved developing a multivariate regression model that assessed how tidal amplitude and freshwater submarine groundwater discharge affect the mixing of fresh and saline groundwater in sandy coastal aquifers. We then applied this model to 143 U.S. shoreline areas with sandy beaches (21% of total beaches in the USA), indirectly mapping potential salinity increases in shallow freshwater PFAS plumes as low (<10 ppt), medium (10-20 ppt), or high (>20 ppt) along groundwater flow paths before reaching the ocean. Higher potential salinity increases were observed in West Coast bays and the North Atlantic coastline, due to the combination of moderate to large tides and large fresh groundwater discharge rates, while lower increases occurred along the Gulf of Mexico and the southern Florida Atlantic coast. The salinity increases were used to estimate potential perfluorooctane sulfonic acid (PFOS) sorption in groundwater due to salting out processes. Low-category shorelines may see a 1- to 2.5-fold increase in sorption of PFOS, medium-category a 2.0- to 6.4-fold increase, and high-category a 3.8- to 25-fold increase in PFOS sorption. The analysis presented provides a first critical step in developing a large-scale approach to classify the PFAS Salting Out potential along shorelines and the limitations of the approach adopted highlights important areas for further research.

A spatio-temporal analysis of environmental fate and transport processes of pesticides and their transformation products in agricultural landscapes dominated by subsurface drainage with SWAT+

Pesticides are detected in surface water and groundwater, endangering the environment. In lowland regions with subsurface drainage systems, drained depressions become hotspots for transport of pesticides and their transformation products (TPs). This study focuses on detailed modelling of the degradation and transport of pesticides with different physico-chemical properties. The objective is to analyse complex hydrological transport processes, to understand the temporal and spatial dynamics of the degradation and transport of pesticides. The ecohydrological model SWAT+ simulates hydrological processes as well as agricultural management and pesticide degradation, and can therefore be used to develop pesticide loss reduction strategies. This study focuses on modelling of three pesticides (pendimethalin, diflufenican, and flufenacet), and two TPs, flufenacet-oxalic acid (FOA) and flufenacet sulfonic acid (FESA). The study area is a 100-hectare farmland in the northern German lowlands of Schleswig-Holstein that is characterized by an spacious drainage network of 6.3 km and managed according to common conventional agricultural practice.SWAT+ modelled streamflow with very good agreement between observed and simulated data during calibration and validation. Regarding pesticides, the model performance for highly mobile substances is better than for non-mobile pesticides. While the transport of the moderately to very mobile substances via tile drains played an important role in both wet and dry conditions, no transport via tile drains was modelled for the highly sorptive and non-mobile pendimethalin.In conclusion, the model can reliably represent the degradation of moderately to very mobile pesticides in small-scale tile drainage-dominated catchments, as well as surface runoff-induced peak loads. However, it has weaknesses in accounting for the subsurface transport of non-mobile substances, which can lead to an underestimation of the subsequent delivery after precipitation events and thus underestimates the total load.

Estimation of virus transport parameters in both unsaturated-saturated zone using numerical simulation and flower pollination algorithm

To develop a virus transport model considering both the unsaturated and saturated zone, it is essential to consider separate parameters for both the zone. This is because the virus fate and transport process depends on the degree of saturation. As such, this paper introduces a parameter estimation model that simultaneously identifies virus transport parameters in an unconfined aquifer for both the unsaturated and saturated zones. The proposed model utilizes a linked simulation-optimization technique to minimize errors between observed and simulated virus concentrations. The simulation model used in this study is termed as “variable detachment model,” this is because the simulation component of this approach incorporates varying adsorption rates, which are influenced by the degree of saturation. This study also highlights the complexities involved in parameter estimation for virus transport models, such as non-uniqueness, instability, and non-identifiability. These challenges arise when multiple parameter combinations can produce similar model predictions, leading to difficulty in determining the actual parameter values. To address these challenges, a meta-heuristic optimization algorithm, Flower Pollination Algorithm (FPA), is used, effectively solving such non-convex problems. The model could estimate all the parameters accurately except the inactivation rates of viruses. Later when the global sensitivity analysis was carried out to understand the relative importance of each parameter, inactivation rates were found to be less influential to the model output. Thus, FPA based parameter estimation model can be used as an alternative for estimating the virus transport parameters in groundwater aquifers.

Modification of Biodegradable Polymer Nanofibers for Cartilage Tissue Engineering Applications: A Review

Tissue engineering is the use of a combination of cells, engineering and materials methods, and suitable biochemical and physiochemical factors to improve or replace biological functions at the injured site. The designing of a biomaterial that can mimic the three-dimensional tissues in vivo is still challenging. Biodegradable polymers are used for the development of tissue engineering constructs in the form of sponges, films, and macroporous scaffolds, which do not influence cell fate processes such as cell differentiation, migration, and proliferation. Biodegradable polymer nanofibers fabricated by electrospinning have gathered great attention in tissue engineering applications. The electrospun materials have a nanofibrous morphology that is closest to the natural extracellular matrix (ECM). The electrospun material is composed of three-dimensional networks of nanosized fibrous materials that mimic an extracellular matrix such as collagen, elastin, and keratin. These polymers fabricated in the form of fibers in nanosize cause a more favorable microenvironment for cells. We prepared the PLGA/PPG (polylactic-co-glycolic acid/polypropylene glycol) nanofibers by electrospinning technique. PLGA (85:15)/PLGA (75:25) nanofibers are hydrophobic, which can be minimized by the addition of PPG to give better hydrophilicity for cell adhesion for tissue engineering constructs. The morphology of the electrospun fibers of the composite of PLGA and PPG was observed using scanning electron microscopy (SEM). The results proved that the small amount of polypropylene glycol polymer to the polylactic-co-glycolic acid (PLGA 85:15) drastically improves the hydrophilicity of the electrospun nanofibers. The addition of a small amount of hydrophilic polymer to the biodegradable hydrophobic polymer increases the hydrophilic property and can be used for nanofiber-based tissue engineering constructs. In addition, the biomimetic approach for tissue engineering scaffolds for cartilage repair has been discussed.

Persistence of human respiratory viral RNA in wastewater-settled solids.

Wastewater-based epidemiology has emerged as a valuable tool for monitoring respiratory viral diseases within communities by analyzing concentrations of viral nucleic-acids in wastewater. However, little is known about the fate of respiratory virus nucleic-acids in wastewater. Two important fate processes that may modulate their concentrations in wastewater as they move from household drains to the point of collection include sorption or partitioning to wastewater solids and degradation. This study investigated the decay kinetics of genomic nucleic-acids of seven human respiratory viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), respiratory syncytial virus (RSV), human coronavirus (HCoV)-OC43, HCoV-229E, HCoV-NL63, human rhinovirus (HRV), and influenza A virus (IAV), as well as pepper mild mottle virus (PMMoV) in wastewater solids. Viruses (except for PMMoV) were spiked into wastewater solids and their concentrations were followed for 50 days at three different temperatures (4°C, 22°C, and 37°C). Viral genomic RNA decayed following first-order kinetics with decay rate constants k from 0 to 0.219 per day. Decay rate constants k were not different from 0 for all targets in solids incubated at 4°C; k values were largest at 37°C and at this temperature, k values were similar across nucleic-acid targets. Regardless of temperature, there was limited viral RNA decay, with an estimated 0% to 20% reduction, over the typical residence times of sewage in the piped systems between input and collection point (<1 day). The k values reported herein can be used directly in fate and transport models to inform the interpretation of measurements made during wastewater surveillance.IMPORTANCEUnderstanding whether or not the RNA targets quantified for wastewater-based epidemiology (WBE) efforts decay during transport between drains and the point of sample collection is critical for data interpretation. Here we show limited decay of viral RNA targets typically measured for respiratory disease WBE.

The HIF-1α/PLOD2 axis integrates extracellular matrix organization and cell metabolism leading to aberrant musculoskeletal repair

While hypoxic signaling has been shown to play a role in many cellular processes, its role in metabolism-linked extracellular matrix (ECM) organization and downstream processes of cell fate after musculoskeletal injury remains to be determined. Heterotopic ossification (HO) is a debilitating condition where abnormal bone formation occurs within extra-skeletal tissues. Hypoxia and hypoxia-inducible factor 1α (HIF-1α) activation have been shown to promote HO. However, the underlying molecular mechanisms by which the HIF-1α pathway in mesenchymal progenitor cells (MPCs) contributes to pathologic bone formation remain to be elucidated. Here, we used a proven mouse injury-induced HO model to investigate the role of HIF-1α on aberrant cell fate. Using single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics analyses of the HO site, we found that collagen ECM organization is the most highly up-regulated biological process in MPCs. Zeugopod mesenchymal cell-specific deletion of Hif1α (Hoxa11-CreERT2; Hif1afl/fl) significantly mitigated HO in vivo. ScRNA-seq analysis of these Hoxa11-CreERT2; Hif1afl/fl mice identified the PLOD2/LOX pathway for collagen cross-linking as downstream of the HIF-1α regulation of HO. Importantly, our scRNA-seq data and mechanistic studies further uncovered that glucose metabolism in MPCs is most highly impacted by HIF-1α deletion. From a translational aspect, a pan-LOX inhibitor significantly decreased HO. A newly screened compound revealed that the inhibition of PLOD2 activity in MPCs significantly decreased osteogenic differentiation and glycolytic metabolism. This suggests that the HIF-1α/PLOD2/LOX axis linked to metabolism regulates HO-forming MPC fate. These results suggest that the HIF-1α/PLOD2/LOX pathway represents a promising strategy to mitigate HO formation.

Predicting environmental concentrations of nanomaterials for exposure assessment - a review

There have been major advances in the science to predict the likely environmental concentrations of nanomaterials, which is a key component of exposure and subsequent risk assessment. Considerable progress has been since the first Material Flow Analyses (MFAs) in 2008, which were based on very limited information, to more refined current tools that take into account engineered nanoparticle (ENP) size distribution, form, dynamic release, and better-informed release factors. These MFAs provide input for all environmental fate models (EFMs), that generate estimates of particle flows and concentrations in various environmental compartments. While MFA models provide valuable information on the magnitude of ENP release, they do not account for fate processes, such as homo- and heteroaggregation, transformations, dissolution, or corona formation. EFMs account for these processes in differing degrees. EFMs can be divided into multimedia compartment models (e.g., atmosphere, waterbodies and their sediments, soils in various landuses), of which there are currently a handful with varying degrees of complexity and process representation, and spatially-resolved watershed models which focus on the water and sediment compartments. Multimedia models have particular applications for considering predicted environmental concentrations (PECs) in particular regions, or for developing generic “fate factors” (i.e., overall persistence in a given compartment) for life-cycle assessment. Watershed models can track transport and eventual fate of emissions into a flowing river, from multiple sources along the waterway course, providing spatially and temporally resolved PECs. Both types of EFMs can be run with either continuous sources of emissions and environmental conditions, or with dynamic emissions (e.g., temporally varying for example as a new nanomaterial is introduced to the market, or with seasonal applications), to better understand the situations that may lead to peak PECs that are more likely to result in exceedance of a toxicological threshold. In addition, bioaccumulation models have been developed to predict the internal concentrations that may accumulate in exposed organisms, based on the PECs from EFMs. The main challenge for MFA and EFMs is a full validation against observed data. To date there have been no field studies that can provide the kind of dataset(s) needed for a true validation of the PECs. While EFMs have been evaluated against a few observations in a small number of locations, with results that indicate they are in the right order of magnitude, there is a great need for field data. Another major challenge is the input data for the MFAs, which depend on market data to estimate the production of ENPs. The current information has major gaps and large uncertainties. There is also a lack of robust analytical techniques for quantifying ENP properties in complex matrices; machine learning may be able to fill this gap. Nevertheless, there has been major progress in the tools for generating PECs. With the emergence of nano- and microplastics as a leading environmental concern, some EFMs have been adapted to these materials. However, caution is needed, since most nano- and microplastics are not engineered, therefore their characteristics are difficult to generalize, and there are new fate and transport processes to consider.

Influence of organic matters on the adsorption-desorption of 1,2-dichloroethane on soil in water and model saturated aquifer.

1,2-Dichloroethane (1,2-DCA) is a typical organic chlorinated compound largely utilized in chemical manufacturing and industrial production and also a common pollutant in organically contaminated sites. The adsorption of 1,2-DCA on soil grains significantly influences its environmental fate and removal process. This study investigated the influence of fulvic acid (FA) and humic acid (HA) on the adsorption-desorption of 1,2-DCA in solid-liquid interfaces in water or constructed porous media. Experimental findings demonstrated the influence of organic matter on the adsorption of 1,2-DCA at the solid-water interface. 1,2-DCA adsorption increased in the FA or HA-treated soils when organic matter was present on the solid surfaces. The 1,2-DCA adsorption in the mixture of FA and HA was slightly lower than that in single organic acids, depending on the binding of FA and HA to the soil grains/colloids. Basic conditions reduced the adsorption of 1,2-DCA on soils, whereas acidic conditions enhanced adsorption due to the increased interactions via adsorption sites and hydrogen bonds. Conversely, the presence of organic matter in solutions (liquid phase in constructed porous media) will reduce the adsorption of 1,2-DCA on solid surfaces and increase the transport in the model aquifer. The combination of FA, HA, and rhamnolipids is helpful for the removal of 1,2-DCA from solid surfaces. Additionally, because of the enhanced desorption, the risk of 1,2-DCA contamination in groundwater can be increased when the organic matter or surfactant is present in the liquid phase if the eluent is not collected. This study helps to better understand the cooperative interaction of soil organic matter and chlorinated hydrocarbons at solid-water interfaces and the environmental fate and potential removal strategies of chlorinated hydrocarbons in contaminated sites.

Engineering considerations in the design of tissue specific bioink for 3D bioprinting applications.

Over eight million surgical procedures are conducted annually in the United Stats to address organ failure or tissue losses. In response to this pressing need, recent medical advancements have significantly improved patient outcomes, primarily through innovative reconstructive surgeries utilizing tissue grafting techniques. Despite tremendous efforts, repairing damaged tissues remains a major clinical challenge for bioengineers and clinicians. 3D bioprinting is an additive manufacturing technique that holds significant promise for creating intricately detailed constructs of tissues, thereby bridging the gap between engineered and actual tissue constructs. In contrast to non-biological printing, 3D bioprinting introduces added intricacies, including considerations for material selection, cell types, growth, and differentiation factors. However, technical challenges arise, particularly concerning the delicate nature of living cells in bioink for tissue construction and limited knowledge about the cell fate processes in such a complex biomechanical environment. A bioink must have appropriate viscoelastic and rheological properties to mimic the native tissue microenvironment and attain desired biomechanical properties. Hence, the properties of bioink play a vital role in the success of 3D bioprinted substitutes. This review comprehensively delves into the scientific aspects of tissue-centric or tissue-specific bioinks and sheds light on the current challenges of the translation of bioinks and bioprinting.

Exploring the molecular mechanisms of macrophages in islet transplantation using single-cell analysis.

Islet transplantation is a promising treatment for type 1 diabetes that aims to restore insulin production and improve glucose control, but long-term graft survival remains a challenge due to immune rejection. ScRNA-seq data from syngeneic and allogeneic islet transplantation grafts were obtained from GSE198865. Seurat was used for filtering and clustering, and UMAP was used for dimension reduction. Differentially expressed genes were analyzed between syngeneic and allogeneic islet transplantation grafts. Gene set variation analysis (GSVA) was performed on the HALLMARK gene sets from MSigDB. Monocle 2 was used to reconstruct differentiation trajectories, and cytokine signature enrichment analysis was used to compare cytokine responses between syngeneic and allogeneic grafts. Three distinct macrophage clusters (Mø-C1, Mø-C2, and Mø-C3) were identified, revealing complex interactions and regulatory mechanisms within macrophage populations. The significant activation of macrophages in allogeneic transplants was marked by the upregulation of allograft rejection-related genes and pathways involved in inflammatory and interferon responses. GSVA revealed eight pathways significantly upregulated in the Mø-C2 cluster. Trajectory analysis revealed that Mø-C3 serves as a common progenitor, branching into Mø-C1 and Mø-C2. Cytokine signature enrichment analysis revealed significant differences in cytokine responses, highlighting the distinct immunological environments created by syngeneic and allogeneic grafts. This study significantly advances the understanding of macrophage roles within the context of islet transplantation by revealing the interactions between immune pathways and cellular fate processes. The findings highlight potential therapeutic targets for enhancing graft survival and function, emphasizing the importance of understanding the immunological aspects of transplant acceptance and longevity.

An enantioselective study of the behavior of the herbicide ethofumesate in agricultural soils: Impact of the addition of organoclays and biochar

Chiral pesticides that are still commercialized and incorporated into the environment as racemic mixtures of enantiomers require evaluation of the enantioselectivity of their biological activity and environmental fate processes for a better prediction of their field efficacy and environmental risks. In this work, we successfully separated the enantiomers of the chiral herbicide ethofumesate (ETFM), determined their absolute configuration, and characterized their herbicidal activity as well as their adsorption, degradation, enantiomerization, and leaching in Mediterranean agricultural soils. While the herbicidal activity of R-ethofumesate to the sensitive species Portulaca grandiflora was greater than that of S-ethofumesate, the adsorption, degradation, and leaching of the herbicide showed negligible enantioselectivity and enantiomer interconversion did not occur in soils. The adsorption of both enantiomers showed a positive correlation with the soil organic carbon content (r = 0.856, P = 0.015), and their degradation in soils occurred slowly (DT50 > 60 days) and at similar rates independent of their application as individual enantiomers or as a racemic mixture of enantiomers. The addition of three highly adsorptive materials to a scarcely adsorptive soil increased the adsorption of the enantiomers of ETFM and delayed their degradation without affecting the non-enantioselective character of the processes. As a result of their high adsorption capacity, the materials were highly effective in reducing the leaching of both enantiomers of ETFM through soil columns. The results of this work indicate that the application of single-enantiomer ETFM formulations, based on a higher herbicidal activity or a lower toxicity to non-target organisms of the formulated enantiomer, would reduce considerable exposure risks associated with incorporating into the environment the less favorable enantiomer, as this would show long persistence and high leaching potential in soils similar to its optical isomer.

Selected pesticidal POPs and metabolites in the soil of five Vietnamese cities: Sources, fate, and health risk implications

Large quantities of organochlorine pesticides (OCPs) have been used in tropical regions. The fate processes and risks of these legacy contaminants in the tropics are poorly understood. Herein, we investigated the occurrence of three classes of widely used OCPs and their metabolites in surface and core soil from five cities across Vietnam with a prevalent tropical monsoon climate and a long history of OCP application. We aimed to elucidate migration potentials, degradation conditions, and transformation pathways and assess current health risks of these contaminants. Generally, the concentrations of OCPs and metabolites in the soil core were slightly lower than those in surface soil except for hexachlorocyclohexane (HCH) isomers. 2,2-bis(4-chlorophenyl)-1,1,1-trichloroethane (p,p’-DDT), 2,2-bis(4-chlorophenyl)-1,1-dichloroethylene (p,p’-DDE), the sum of dicofol and 4,4′-dichlorobenzophenone (p,p’-DBP), and 2,2-bis(4-chlorophenyl)-1,1-dichloroethane (p,p’-DDD) were the most abundant compounds in both surface and core soils. A uniform distribution of HCHs (the sum of α-, β-, γ-, and δ-HCH) at trace levels was found in almost all soils, serving as evidence of the lack of recent use of HCH pesticides. Higher concentrations of DDTs (the sum of DDT, DDD, and DDE) were observed in north-central Vietnamese soil, whereas appreciable concentrations of ENDs (the sum of α- and β-endosulfan and endosulfan sulfate) were only found in southern Vietnamese soils. Empirical diagnostic ratios indicated residuals of DDTs were mainly from technical DDT rather than dicofol, whereas aged HCHs could be explained by the mixture of lindane and technical HCH. Both historical applications and recent input explain DDTs and ENDs in Vietnamese soil. Total organic carbon performs well in preventing vertical migration of more hydrophobic DDTs and ENDs. The dominant transformation pathway of DDT in surface soil followed p,p’-DDE→2,2-bis(4-chlorophenyl)-1-chloroethylene or p,p’-DDMU→1,1-bis(4-chlorophenyl)ethylene or p,p’-DDNU→p,p’-DBP, whereas the amount of p,p’-DDMU converted from p,p’-DDD and p,p’-DDE is similar in soil core. Non-cancer risks of OCPs and metabolites in all soils and cancer risks of those chemicals in core soils were below the safety threshold, whereas a small proportion of surface soil exhibited potential cancer risk after considering the exposure pathway of vegetable intake. This study implied that organic matter in non-rainforest tropical deep soils still could hinder the leaching of hydrophobic organic contaminants as in subtropical and temperate soils. When lands with a history of OCP application are used for agricultural purposes, dietary-related risks need to be carefully assessed.

An integrated approach to testing and assessment (IATA) to support grouping and read-across of nanomaterials in aquatic systems

Even small changes in physicochemical properties of nanoforms (NFs), can drive differences in their environmental fate and hazard. The large number of new materials being developed means it will not be feasible to test and characterise the fate, behaviour and (eco)toxicity of each individual NF. This is further amplified by transformations of NFs over their lifecycle, changing the processes governing their risk. A common complexity arises from dissolution, where the combined toxicity of the exposure arises from both the solutes and any remaining particles contribution to the overall toxicity of the exposure. For efficient and effective risk assessment, it is the most relevant form of the NF for a given exposure that should be targeted for testing and assessment. In aquatic systems, functional fate processes (including dissolution, dispersion stability and chemical and biological transformations) determine the NF’s exposure relevant form. Whilst transformations in the environment alter the initial properties of an NF, different NFs may follow a shared functional fate pathway and ultimately present a similar fate and hazard profile in the environment. Therefore, these processes may be used to scientifically justify grouping NFs and read-across for specific endpoints from data rich NF(s) to verified members of the group that have not been tested yet. Integrated Approaches to Testing and Assessment (IATA) have been used in other regulatory contexts to support the collection and integration of relevant existing information as well as the targeted generation of new data to support grouping and read-across. Here, a new IATA is presented consisting of decision nodes focused on dissolution, dispersion stability, chemical transformations and the relative contribution to toxicity of the particle and dissolved component of the overall exposure. The IATA focuses on the fate of NFs in aquatic systems outside of the body, but it can be considered a template for future assessment of in vivo kinetics, which will require further development. Guidance on tiered testing approaches and thresholds for grouping within each decision node are critically discussed. Worked examples for ecotoxicity of metal oxide NFs in aqueous systems (in microbial communities isolated from soils and for lettuce plants in hydroponic systems) demonstrate successful identification of the exposure relevant form of the NF in these case studies and allows for different grouping of NFs through application of the IATA.

Comparison of transit time models for exploring seasonal variation of preferential flow in a Moso bamboo watershed

Understanding seasonal variations of the hydrological fluxes and preferential flow is crucial in exploring contaminant fate and transport processes in a watershed of interest. Here, performance of different StorAge Selection (SAS)-based rainfall-runoff models was compared for a Moso bamboo watershed under the East Asian monsoon climate. Most of these models are composed of a two-parallel-reservoir flow module and a companioned SAS module. The results show that the temporal variation in streamflow is well captured by a two-parallel-reservoir flow module. The tracer simulations from different models show that two-uniform-reservoir (SSU) model with no SAS function has the lowest NSE value (0.17), the model including an SAS in one of the two reservoir outflows (SSD(U) and SSD(L)) improves performance (NSE greater than 0.5). The performance in simulating streamflow δ18O is further improved when SAS functions are applied for outflows from both reservoirs (SSD (U, L), NSE = 0.76). Additional inclusion an SAS function for ET fluxes in the model (SSD (U, ET, L)) results in a minor improvement from SSD (U, L). The results of SSD (U, ET, L) have achieved the best transport performance (NSE = 0.77), with implication for preferential flow in the watershed. The preferential flow for deep drainage and lower reservoir outflow shows seasonal variation, with more young water in the East Asian summer monsoon period than that in the East Asian winter monsoon period. The upper reservoir storage and deep drainage rates are the main factors determining the temporal variation of preferential flow for deep drainage and lower reservoir outflow, respectively.

Linear Free Energy Relationship for Predicting the Rate Constants of Munition Compound Reduction by the Fe(II)-Hematite and Fe(II)-Goethite Redox Couples.

Abiotic reduction by iron minerals is arguably the most important fate process for munition compounds (MCs) in subsurface environments. No model currently exists that can predict the abiotic reduction rates of structurally diverse MCs by iron (oxyhydr)oxides. We performed batch experiments to measure the rate constants for the reduction of three classes of MCs (poly-nitroaromatics, nitramines, and azoles) by hematite or goethite in the presence of aqueous Fe2+. The surface area-normalized reduction rate constant (kSA) depended on the aqueous-phase one-electron reduction potential (EH1) of the MC and the thermodynamic state (i.e., pe and pH) of the iron oxide-Feaq2+ system. A linear free energy relationship (LFER), similar to that reported previously for nitrobenzene, successfully captures all MC reduction rate constants that span 6 orders of magnitude: . The finding that the rate constants of all the different classes of MCs can be described by a single LFER suggests that these structurally diverse nitro compounds are reduced by iron oxide-Feaq2+ couples through a common mechanism up to the rate-limiting step. Multiple mechanistic implications of the results are discussed. This study expands the applicability of the LFER model for predicting the reduction rates of legacy and emerging MCs and potentially other nitro compounds.

Fate of herbicides in cropped lysimeters: 1. Influence of different processes and model structure on vadose zone flow

AbstractUnderstanding transport and fate processes in the subsurface is of fundamental importance to identify the leaching potentials of herbicides or other compounds to groundwater resources. HYDRUS‐1D was used to simulate water flow and solute transport in arable land lysimeters. Simulations were compared to observed drainage rates and stable water isotopes (δ18O) in the drainage. Four different model setups were investigated and statistically evaluated for their model performance to identify dominant processes for water flow characterization in the vadose zone under similar cultivation management and climatic conditions. The studied lysimeters contain soil cores dominated by sandy gravel (Ly1) and clayey sandy silt (Ly2), both cropped with maize located in Wielenbach, Germany. First, a single‐porosity setup was chosen. For Ly1, modeling results were satisfactory, but for Ly2, the damping observed in the isotope signature of the drainage could not be fully covered. By considering immobile water with a dual‐porosity setup for Ly2, model performance improved. This could be due to a higher fraction of fine pores in Ly2 available for water storage, leading to mixing processes of isotopically enriched summer precipitation and lighter winter water. Accounting for isotopic evaporation fractionation processes in both model setups did not lead to improved model performance. Consequentially, the difference in soil hydraulic properties between the two lysimeters seems to impact water flow processes. Knowledge of such differences is crucial to prevent contamination and mitigate potential risks to soil and groundwater.