Understanding of aquaporins (AQPs) facilitating the transport of water and many other small solutes including metalloids like silicon (Si) and arsenic (As) is important to develop stress tolerant cultivars. In the present study, 40 AQPs were identified in the genome of pigeonpea (Cajanus cajan), a pulse crop widely grown in semi-arid region and areas known to affected with heavy metals like As. Conserved domains, variation at NPA motifs, aromatic/arginine (ar/R) selectivity filters, and pore morphology defined here will be crucial in predicting solute specificity of pigeonpea AQPs. The study identified CcNIP2-1 as an AQP predicted to transporter Si (beneficial element) as well as As (hazardous element). Further Si quantification in different tissues showed about 1.66% Si in leaves which confirmed the predictions. Furthermore, scanning electron microscopy showed a higher level of Si accumulation in trichomes on the leaf surface. A significant alleviation in level of As, Sb and Ge stress was also observed when these heavy metals were supplemented with Si. Estimation of relative water content, H₂O₂, lipid peroxidation, proline, total chlorophyll content and other physiological parameters suggested Si derived stress tolerance. Extensive transcriptome profiling under different developmental stages from germination to senescence was performed to understand the tissue-specific regulation of different AQPs. For instance, high expression of TIP3s was observed only in reproductive tissues. Co-expression network developed using transcriptome data from 30 different conditions and tissues, showed interdependency of AQPs. Expression profiling of pigeonpea performed using real time PCR showed differential expression of AQPs after Si supplementation. The information generated about the phylogeny, distribution, molecular evolution, solute specificity, and gene expression dynamics in article will be helpful to better understand the AQP transport system in pigeonpea and other legumes.

The concentration of persistent organic pollutants (POPs) makes remarkable difference to environmental fate. In the field of passive sampling, the partition coefficients between polystyrene-divinylbenzene resin (XAD) and air (i.e., KXAD₋A) are indispensable to obtain POPs concentration, and the KXAD₋A is generally thought to be governed by temperature and molecular structure of POPs. However, experimental determination of KXAD₋A is unrealistic for countless and novel chemicals. Herein, the Abraham solute descriptors of poly parameter linear free energy relationship (pp-LFER) and temperature were utilized to develop models, namely pp-LFER-T, for predicting KXAD₋A values. Two linear (MLR and LASSO) and four nonlinear (ANN, SVM, kNN and RF) machine learning algorithms were employed to develop models based on a data set of 307 sample points. For the aforementioned six models, R²ₐdⱼ and Q²ₑₓₜ were both beyond 0.90, indicating distinguished goodness-of-fit and robust generalization ability. By comparing the established models, the best model was observed as the RF model with R²ₐdⱼ = 0.991, Q²ₑₓₜ = 0.935, RMSEₜᵣₐ = 0.271 and RMSEₑₓₜ = 0.868. The mechanism interpretation revealed that the temperature, size of molecules and dipole-type interactions were the predominant factors affecting KXAD₋A values. Concurrently, the developed models with the broad applicability domain provide available tools to fill the experimental data gap for untested chemicals. In addition, the developed models were helpful to preliminarily evaluate the environmental ecological risk and understand the adsorption behavior of POPs between XAD membrane and air.

Distribution in ice is regarded as one of important transport modes for pollutants in seasonal freeze-up waters in cold regions. However, the distribution characteristics and mechanisms of fluorinated antibiotics as emerging contaminants during the water freezing process remain unclear. Here, florfenicol and norfloxacin were selected as model fluorinated antibiotics to investigate their ice-water distribution. Effects of antibiotic molecular structure on the distribution were explored through comparative studies with their non-fluorinated structural analogs. Results showed that phase changes during the ice growth process redistributed the antibiotics, with antibiotic concentrations in water 3.0–6.4 times higher than those in ice. The solute-rich boundary layer with a concentration gradient was presented at the ice-water interface and controlled by constitutional supercooling during the freezing process. The ice-water distribution coefficient (KIW) values of antibiotics increased by 34.8%–38.0% with a doubling of the cooling area. The solute distribution coefficient (Kbₛ) values of antibiotics at −20 °C were 65.6%–70.3% higher than at −10 °C. The KIW and Kbₛ values of all antibiotics were negatively correlated with their water solubilities. The fluorine substituents influenced the binding energies between antibiotics and ice, resulting in a 1.1-fold increase in the binding energy of norfloxacin on the ice surface relative to its structural analog pipemidic acid. The results provide a new insight into the transport behaviors of fluorinated pharmaceuticals in ice-water systems.

River ecosystems are under increasing stress in the background of global change and ever-growing anthropogenic impacts in Central Asia. However, available water quality data in this region are insufficient for a reliable assessment of the current status, which come as no surprise that the limited knowledge of regulating processes for further prediction of solute variations hinders the development of sustainable management strategies. Here, we analyzed a dataset of various water quality variables from two sampling campaigns in 2019 in the catchments of two major rivers in Central Asia—the Amu Darya and Syr Darya Rivers. Our results suggested high spatial heterogeneity of salinity and major ion components along the longitudinal directions in both river catchments, pointing to an increasing influence of human activities toward downstream areas. We linked the modeling outputs from the global nutrient model (IMAGE-GNM) to riverine nutrients to elucidate the effect of different natural and anthropogenic sources in dictating the longitudinal variations of the riverine nutrient concentrations (N and P). Diffuse nutrient loadings dominated the export flux into the rivers, whereas leaching and surface runoff constituted the major fractions for N and P, respectively. Discharge of agricultural irrigation water into the rivers was the major cause of the increases in nutrients and salinity. Given that the conditions in Central Asia are highly susceptible to climate change, our findings call for more efforts to establish holistic management of water quality.

The m-aminophenol (m-AP) is a widely used industrial chemical, which enters water, soils, and sediments with waste emissions. A common soil metal oxide, birnessite (δ-MnO2), was found to mediate the transformation of m-AP with fast rates under acidic conditions. Because of the highly complexity of the m-AP transformation, mechanism-based models were taken to fit the transformation kinetic process of m-AP. The results indicated that the transformation of m-AP with δ-MnO2 could be described by precursor complex formation rate-limiting model. The oxidative transformation of m-AP on the surface of δ-MnO2 was highly dependent on reactant concentrations, pH, temperature, and other co-solutes. The UV-VIS absorbance and mass spectra analysis indicated that the pathway leading to m-AP transformation may be the polymerization through the coupling reaction. The m-AP radicals were likely to be coupled by the covalent bonding between unsubstituted C2, C4 or C6 atoms in the m-AP aromatic rings to form oligomers as revealed by the results of activation energy and mass spectra. Furthermore, the toxicity assessment of the transformation productions indicated that the toxicity of m-AP to the E. coli K-12 could be reduced by MnO2 mediated transformation. The results are helpful for understanding the environmental behavior and potential risk of m-AP in natural environment.

Measurement of solute-transport parameters through soils for a wide range of solute- and soil-types is time-consuming, laborious, expensive and practically impossible. So, indirect methods for estimating the transport parameters by pedo-transfer functions are now advancing. This study developed and evaluated an Artificial Neural Network (ANN) model for estimating the transport velocity (V), dispersion coefficient (D) and retardation factor (R) of NaAsO₂, Pb(NO₃)₂, Cd(NO₃)₂, C₉H₉N₃O₂ and CaCl₂ from the basic soil properties. Breakthrough data of the solutes were measured in 14 agricultural soils of Bangladesh by time-domain reflectometry (TDR) in repacked soil columns under unsaturated steady-state water-flow conditions. The transport parameters of the chemicals were determined by analyzing the solute breakthrough data. Bulk density (γ), organic carbon (OC), clay (C) content, pH, median grain diameter (D₅₀) and uniformity coefficient (Cᵤ) of the soils were determined. An ANN model for V, D and R was developed by using data of eight soils, validated/tested with the data of five soils and verified with the data of one soil. Clay content and bulk density of the soils were the most sensitive input variables to the ANN model followed by other soil properties (OC, C, pH, D₅₀ and Cᵤ). The model reliably predicted V, D and R with relative root-mean-square error (RRMSE) of 0.028–0.363, mean error (ME) of – 0.00004 to 0.0005, bias error (BOE%) of 0–0.003 and modeling efficiency (EF) of >0.99. Thus, the ANN model can significantly enhance prediction of pollution transport through soils in terms of cost and effort.

Sorption studies of organic pollutants by microplastics (MPs) in single-solute systems are well established in the literature. However, actual aquatic environments always contain a mixture of contaminants. Prediction of the fate and biological effects of MPs-mediated chemical exposure requires a better understanding of sorption-desorption processes of multiple organic contaminants by MPs. In this study, the altered sorption and desorption behaviors of individual organic UV filters (BP-3 and 4-MBC) in the presence of cosolutes (BP-3, 4-MBC, EHMC and OC) on two types of MPs (LDPE and PS) were examined. In most cases, co-occurrence of other organic UV filters appeared to have an antagonistic effect on the sorption of primary solute, which was consistent with trends found in previous studies. Nevertheless, the sorption uptake of 4-MBC as primary solute on PS was enhanced in the presence of cosolute(s), arising presumably from solute multilayer formation caused by laterally attractive π-π interactions between adsorbed cosolute(s) and 4-MBC molecules. Such formation of multilayer sorption in multi-solute systems depends on the solute hydrophobicity and concentration as well as inherent sorptivity of MPs. Our further desorption experiments revealed that the bioaccessibility of primary solute was significantly elevated with cosolutes, even though competitive sorption was observed under the same experimental conditions. These findings supplement the current knowledge on sorption mechanisms and interactions of multiple organic contaminants on MPs, which are critical for a comprehensive environmental risk assessment of both MPs and hazardous anthropogenic contaminants in natural environments.

Recent classification of metformin as an emerging contaminant warrants assessment of its fate and behaviour in the natural environment especially with land-based application of potentially contaminated wastewaters and biosolids. The present study provided further insight into the sorption mechanisms of metformin and its transformation product guanylurea in soil and upon biosolid fortification. Decreased metformin sorption (12.4%) as measured by the effective distribution coefficient (Kdᵉᶠᶠ) was observed with biosolids amendment while significant increase (2500%) in guanylurea sorption was calculated. Analysis of co-solute effects confirmed their contrasting sorption mechanisms with the absence of competitive effects in unamended soil. Results of the column tests were in good agreement with the batch sorption studies as the fitted values of retardation factors decreased and increased for metformin and guanylurea, respectively, upon addition of biosolids. The shapes of the breakthrough curves suggest slower desorption rates for both compounds in unamended soil resulting to non-equilibrium conditions and back-end tailings. However, in biosolid-amended soil columns, these tailings were less pronounced resembling equilibrium transport. Results also demonstrated enhanced mobility of both compounds upon biosolids fortification. The non-equilibrium chemical transport model fitted the measured data well (0.975 > r² > 0.988) especially for unamended soils which suggests the existence of non-equilibrium conditions and rate-limited sorption sites.

Application of empirical models to adsorption of contaminants on natural heterogeneous sorbents is often challenging due to the uncertainty associated with fitting experimental data and determining adjustable parameters. Sediment samples from contaminated and uncontaminated portions of a study site in Maine, USA were collected and investigated for adsorption of arsenate [As(V)]. Two kinetic models were used to describe the results of single solute batch adsorption experiments. Piecewise linear regression of data linearized to fit pseudo-first order kinetic model resulted in two distinct rates and a cutoff time point of 14–19 h delineating the biphasic behavior of solute adsorption. During the initial rapid adsorption stage, an average of 60–80% of the total adsorption took place. Pseudo-second order kinetic models provided the best fit to the experimental data (R2 > 0.99) and were capable of describing the adsorption over the entire range of experiments. Both Langmuir and Freundlich isotherms provided reasonable fits to the adsorption data at equilibrium. Langmuir-derived maximum adsorption capacity (St) of the studied sediments ranged between 29 and 97 mg/kg increasing from contaminated to uncontaminated sites. Solid phase As content of the sediments ranged from 3.8 to 10 mg/kg and the As/Fe ratios were highest in the amorphous phase. High-pH desorption experiments resulted in a greater percentage of solid phase As released into solution from experimentally-loaded sediments than from the unaltered samples suggesting that As(V) adsorption takes place on different reversible and irreversible surface sites.

Insufficient understanding of the hydrogeochemistry of aquifers makes it necessary to conduct a preliminary water quality assessment in the southern region of Ordos Basin, an arid area in the world. In this paper, the major ions of groundwater have been studied aiming at evaluating the hydrogeochemical processes that probably affect the groundwater quality using 150 samples collected in 2015. The two prevalent hydrochemical facies, HCO3Mg·Na·Ca and HCO3Mg·Ca·Na type water, have been identified based on the hydrochemical analysis from Piper trilinear diagram. Compositional relations have been used to assess the origin of solutes and confirm the predominant hydrogeochemical processes responsible for the various ions in the groundwater. The results show that the ions are derived from leaching effect, evaporation and condensation, cation exchange, mixing effect and human activities. Finally groundwater quality was assessed with single factor and set pair methods, the results indicate that groundwater quality in the study region is generally poor in terms of standard of national groundwater quality. The results obtained in this study will be useful to understand the groundwater quality status for effective management and utilization of the groundwater resource.