Arsenic (As) is a carcinogenic environmental contaminant whose dissolution and speciation are strongly related to sulfate reactions, including reduction-oxidation, precipitation, complexation, and the microbial activities of sulfate-reducing bacteria. In lowland rice paddy fields, the interaction between As and sulfate are highly variable due to the sharp oxic/anoxic transition in the upper soils and the strongly reducing condition in the lower soils. Both water and sulfate management practices have been demonstrated to reduce As bioavailability. However, interactions between these processes at sub-centimeter scales within paddy soil profiles are poorly understood and could even lead to enhanced As mobilization. To address this knowledge gap, we established mesocosms with mine-impacted soil under continuous or intermittent flooding, with and without sulfate addition. Millimeter-scale in situ profiles of dissolved AsIII, S-II and FeII were obtained using diffusive gradients in thin-films (DGT) and diffusive equilibration in thin-films (DET), and these were complemented by centimeter-scale soil DNA sampling to quantify the abundance of functional microbial groups. Our results show that high sulfate concentrations enhance AsIII in the near-surface 0-2 cm layer of the soil profile (near the soil-water interface) under continuous flooding, while in the anaerobic zone (below 4 cm), sulfate inhibits AsIII mobilization by facilitating the reduction of FeIII and SO42- to FeII and S-II through the enhanced activity of iron- and sulfate-reducing bacteria. The subsequent FeS precipitation adsorbs As, thereby reducing AsIII availability by 40%. Additionally, in this mesocosm experiment, differences in As mobilization between continuous and intermittent flooding were evident only in the near-surface 0-2 cm layer, with similar As profiles observed below 2 cm depth. This study provides insights into As migration and transformation mechanisms across soil depths under varying redox conditions and sulfate levels. Under flooded conditions, high-concentration sulfate increase AsIII mobility in this near-surface 0-2 cm layer, whereas intermittent flooding reduces its mobility. These findings inform remediation strategies for As contamination in high-sulfate soils.

Cadmium (Cd) contamination in soil and its accumulation in rice grains pose serious risks to human health. Biochar can alter soil properties, Cd availability, and rhizosphere enzyme activities, but spatially resolved evidence of these processes remains limited. A 30-day rhizotron experiment was conducted using loofah sponge biochar (LSB) at 0.1

Anomaly detection in water-related time-series data often reveals important environmental problems and serves as a starting point for scientific discoveries. Machine learning has become the mainstream method and a research hotspot for anomaly detection in recent years. This review examines 106 research articles from the Web of Science database published over the past 10 years. Unlike other surveys, this review focuses on anomalies arising from the water-related variables themselves rather than from equipment malfunctions. The work assesses the overall trends in the application and development of machine learning models for water-related anomaly detection. It classifies machine learning-based anomaly-detection models from two dimensions: development stage and anomaly-detection paradigm. Our analysis covers the mechanisms, strengths, limitations, and applications of various machine learning-based anomaly-detection models across different paradigms, highlighting current challenges and prospective research directions in water-related anomaly detection.

The resource utilization of waste had significant economic value and environmental benefits. Among them, constructing a light-driven advanced oxidation system using waste was an effective strategy for treating organic wastewater. This study constructed a lake sediment/g-C3N4 heterojunction - Peroxymonosulfate (PMS) photocatalytic system. The photoelectrochemical experiments and in-situ XPS analysis demonstrated that the heterojunction formed by lake sediments and g-C3N4 facilitated the separation and transfer of photogenerated carriers. The BET results indicate that the specific surface area of this heterojunction material reached 20.1595 m2/g. Furthermore, the joint activation of PMS by transition metals and heterojunctions effectively increased the concentration of reactive substances in the system. Under simulated natural light conditions, this system could degrade 92.17% of tetracycline (TC) within 30 min, and the mineralization rate could reach 71.99%, and the apparent quantum efficiency (AQE) is 0.77%. After five cycles, this system was still able to achieve a degradation rate of 78.828%. The degradation pathway of TC and the stability of its products were analyzed through LC-MS and DFT calculations. The Ecological Structure Activity Relationships (ECOSAR) simulation and plant cultivation experiments had confirmed that this system could effectively reduce the environmental risk of TC. This study focused on specific components in lake sediments and examines their roles during the photocatalytic process. This study employed more intuitive simulation or experimental methods to analyze the transfer pathways of photogenerated electrons, providing valuable insights for the subsequent development of sediment photocatalytic materials.

Hue-changed sequences of multicolor optical sensors are diverse, whereas hue-quantified sequences of existing quantitative parameters are fixed. Monotonic calibration is unavailable when the two sequences are inconsistent. To overcome this challenge, a hue descriptor named Huev was designed. Its quantification sequence is tunable via a parameter named HT. Furthermore, a method of calculating the optimal HT for each sensor, a Huev-based analytical workflow (including chemical imaging), and a user-friendly analytical platform were developed. We demonstrated that Huev has broader applicability than some existing parameters, calibrated a sensor that cannot be calibrated by existing parameters, transformed qualitative test strips into quantitative tools, and developed a pH imaging method with a broader detection range (0.1-12) than conventional methods. Our work makes it possible to develop a hue-changed phenomenon into a universal optical sensing technique. It promises broad applications in many fields based on analytical chemistry such as point-of-care testing (POCT) and chemical imaging.

Nitrate contamination has prompted global concern due to its far-reaching effects on human health and the ecosystem. As an emerging technology, electrochemical nitrate reduction reaction (eNO(3)RR) provides a promising approach for converting nitrate to valuable ammonia (NH3) or harmless nitrogen gas (N-2). However, the conversion efficiency of eNO(3)RR is still constrained by the mismatch between catalysts and the reaction microenvironment at lower nitrate concentrations (<0.1 mol/L). In this review, we have systematically discussed the feasibility of electrochemical methods in treating low-concentration nitrate by summarizing recent advances and their reaction mechanisms. Meanwhile, the selection between NH3 and N-2 pathways was evaluated based on the nitrate concentration range and safety considerations associated with each scenario. Finally, the dominant factors for applying eNO(3)RR to real-world scenarios were also thoroughly discussed. We hope this review can provide comprehensive insights into the design of optimal catalysts and systems for treating low-concentration nitrates in practical scenarios, thereby promoting the environmental sustainability of electrocatalytic technologies. (c) 2026 Published by Elsevier B.V. on behalf of Chinese Chemical Society and Institute of Materia Medica, Chinese Academy of Medical Sciences.

Rising sea levels and climate change are intensifying soil flooding and altering redox dynamics, profoundly influencing chromium (Cr) behavior in contaminated industrial soils. Here, we combined in situ techniques, including high-resolution diffusive gradients in thin-films (HR-DGT) and planar optodes (PO), with ex situ incubation to investigate the transformation and availability of Cr in different industrial soils under both shortterm and long-term flooding. Results showed that soil physicochemical properties strongly governed the formation of oxic-anoxic microzone (<3 mm) and associated redox-driven Cr availability. In acidic soils characterized by low soil organic matter (SOM) and amorphous Fe oxides (Ox-Fe), limited Cr (VI) reduction resulted in relatively high labile Cr(VI) concentrations even under prolonged flooding (e.g., Guangzhou site). Conversely, high SOM and Ox-Fe in alkaline soils promoted significant Cr(VI) reduction and stabilization (e.g., Shijiazhuang and Shanghai sites). However, an increased potential for Cr(III) reoxidation was observed at the oxic-anoxic microzones in Mn-rich alkaline soils. In addition to higher 16S rDNA copy numbers, correlation analyses suggested that microbial communities may play microenvironment-specific roles. Genera such as Sphingomonas and Lysobacter were associated with Cr(VI) reduction under anoxic conditions, whereas Mn-oxidizing bacteria (e.g., Ramlibacter) were linked to indirect Cr(III) reoxidation at oxic-anoxic interfaces. This study provides a mechanistic framework for predicting Cr behavior in flood-prone industrial soils and highlights the need for site-specific management strategies under changing climate conditions.

The rapid expansion of machine learning applications in heavy metal risk research has generated a large but fragmented body of literature, necessitating a systematic summary of various methodologies. This survey examines 182 research articles from Web of Science, Scopus, and IEEE Xplore over the past 10 years, providing a comprehensive analysis of the application of prevalent machine learning algorithms across research areas related to heavy metal risks, covering more than 30 algorithms and 9 research areas. The results show that regional risk assessment, risk source analysis, risk driver analysis, and research on the pathogenicity of HMs are the four most frequently applied areas of machine learning, accounting for 80.06% of all applications. Classical machine learning, especially a series of tree-based algorithms, dominates across all applications, accounting for 69.93% and 42.74%, respectively. In addition, some auxiliary algorithms, particularly those for feature analysis, are often used in conjunction with machine learning, primarily to interpret model predictions and analyze risk sources or drivers. Three principal methodological challenges emerge from our review: (1) poor model generalizability across different environmental conditions; (2) insufficient reliability of predictions; and (3) difficulty in obtaining high-quality training data. Some current literature is also constrained by small sample sizes, regional bias, limited field validation, and insufficient integration of multi-omics data with machine learning pipelines. To address these gaps, we advocate for the routine adoption of explainable AI techniques with rigorous stability checks, the development of publicly available, field-validated benchmark datasets, and greater integration of mechanistic knowledge with data-driven models.

Viral diseases pose significant threats to global public health and ecological security, necessitating advanced strategies for environmental virus monitoring. Electrochemical detection methods have emerged as a transformative tool in this regard, offering rapid, cost-effective, and field-deployable solutions for monitoring viral pathogens in environmental matrices such as air and water systems. Unlike traditional analytical approaches, electrochemical platforms enable real-time detection of trace viral loads in complex environmental samples, providing critical early warning capabilities for outbreak prevention. This review focuses on the fundamental principles of electrochemical virus detection, emphasizing its application in environmental monitoring. Key biomarkers and biomolecular recognition elements are systematically discussed, with specific examples of their utility in detecting airborne viral aerosols and waterborne pathogens. Electrochemical detection technology, with its unique advantages, has shown great application potential in the field of virus detection and has opened up a new way for the assessment and management of environmental viruses. With the continuous innovation, electrochemical detection of viruses is expected to play a more important role in the field of environmental monitoring and make greater contributions to the protection of human health and ecological environment safety.

BACKGROUND AND AIMS:Phosphorus (P) amendments are increasingly recognized as a critical strategy to mitigate cadmium (Cd) contamination in paddy soils. However, how varying Cd contamination intensity shapes rhizosphere geochemistry and determines the dominant pathway of P-mediated Cd mitigation remains unclear. This study aimed to elucidate the distinct mechanisms by which exogenous P modulates Cd bioavailability under different Cd stress levels. METHODS:We integrated a rhizo-bag pot system with diffusive gradients in thin-films (DGT) and time-resolved porewater monitoring. This approach allowed us to resolve high-resolution spatiotemporal patterns of Cd, P, Fe, and pH dynamics in both rhizosphere (RH) and non-rhizosphere (NRH) zones throughout the rice cultivation period. RESULTS:Under low Cd concentration level, P acted as a nutrient, stimulating biomass growth (2.2- to 3.1-fold). The resulting biomass increase generated an apparent biomass-dilution effect on a concentration basis, with enhanced iron plaque potentially serving as a Cd sink. Under high Cd concentration level, P raised rhizosphere pH (from 7.08 to 7.45-7.69) and likely promoted Cd/Fe phosphate precipitation, reducing labile Cd and Cd accumulation in rice. Correlation analyses supported the dilution effect under low Cd and precipitation-driven immobilization under high Cd. CONCLUSIONS:The mechanism of P-mediated Cd remediation shifts from biological dilution to chemical immobilization with increasing Cd stress. P-based management should be tailored to pollution severity: growth promotion in low-risk soils and chemical stabilization in heavily polluted fields.

Heavy metals in aquatic systems often exist as stable complexes, making their removal challenging through conventional treatment strategies. In this study, an nZVI/MXene nanocomposite was synthesized by anchoring nZVI on Ti3C2Tx MXene nanosheets for Cu(II)-EDTA decomplexation and Cu immobilization. Compared with pristine MXene and bare nZVI, the composite showed higher removal efficiency for EDTA-chelated Cu2+ and maintained effective performance over pH of 3–9. The removal equilibrium was reached within 30 min, with a Langmuir maximum Cu removal capacity of 0.667 mmol/g. The enhanced performance was attributed to the functional integration of nZVI and MXene. nZVI optimized the surface charge properties of the composite and provided reactive Fe sites for Fe-mediated decomplexation and Cu reduction, while MXene promoted nZVI dispersion, improved the accessibility of Fe-related reactive sites, and might also participate in interfacial Cu immobilization. Electrochemical analyses suggested that reduced Cu species might further regulate interfacial electron-transfer behavior. In addition, nZVI/MXene showed applicability toward different Cu(II)-organic complexes and maintained Cu removal performance in fixed-bed column experiments. The spent material could be converted by calcination into a catalyst for PMS activation and tetracycline degradation, suggesting a possible route for secondary utilization. Overall, this work provided a feasible strategy for treating metal-organic complex wastewater through coupled decomplexation and metal immobilization, while offering insights into the design of multifunctional MXene-based composites.

Selenium (Se) application can reduce toxic element accumulation in rice, yet the mechanistic basis linking Se to rhizosphere oxygenation and Fe barrier formation remains unresolved. In a 103 day greenhouse pot experiment, sodium selenite was applied to multicontaminated paddy soil either as a soil amendment (1 mg kg-1) or foliar spray (40 mg L-1), with an untreated control. Soil Se application reduced grain concentrations of cadmium by 54%, arsenic by 34%, lead by 41%, chromium by 21%, nickel by 42%, and cobalt by 39%; foliar application achieved reductions of 12%-41%. To resolve the underlying mechanisms, we integrated planar optode and DGT-LA-ICP-MS imaging with physiological and molecular analyses. Selenium stimulated auxin accumulation by 2.74-fold and upregulated auxin biosynthesis and signaling genes (OsYUCCA1, OsTAA1, OsARF19), expanding constitutive aerenchyma from 34% to 65% of cortical area and sustaining radial oxygen loss. The resulting increase in rhizosphere oxygenation decreased labile Fe and Mn fluxes by 54%-89%, consistent with Fe/Mn oxide precipitation, and increased root surface Fe plaque by 5.64-fold, collectively restricting toxic element mobility through adsorption and coprecipitation. These findings establish an auxin-mediated aerenchyma-radial oxygen loss-iron barrier cascade as the mechanistic basis for Se-induced restriction of toxic element uptake by rice.

Iron-modified biochar (BCFe) shows promise for remediating Cr(VI)-contaminated industrial soils, but its long-term effectiveness under environmental stressors like acid rain require investigation. This study integrated column leaching, ex situ soil sampling, and in situ high-resolution (HR) imaging to assess acid rain effects (pH 4.0 vs. 5.6) on chromium (Cr) mobility, distribution, and speciation in BCFe-remediated Cr-contaminated industrial soils. BCFe exhibited high Cr(VI) adsorption capacity (184 mg g-1) and significantly reduced Cr(VI) availability and leaching, promoting the transformation of Cr into more stable geochemical fractions. However, acid rain leaching increased Cr(VI) release compared to normal rainfall leaching. While ex situ analysis indicated Cr migration primarily affected the upper 0-8 cm, in situ HR imaging precisely resolved a distinct 3-5 cm transition zone exhibiting significant microscale heterogeneity. In situ evidence confirmed Cr(VI) reduction via simultaneous Cr(III) increase. Crucially, a strong negative correlation between labile Fe and Cr(VI) occurred only within BCFe treatments in this zone, verifying the key role of Fe(II) in Cr(VI) reduction. By integrating multi-scale (ex situ/in situ) techniques, this study revealed both the potential of BCFe for Cr remediation and the critical compromising effect of acid rain, highlighting the need to consider environmental factors for long-term efficacy.

Arsenic (As) contamination in agroecosystems poses significant risks to food security and human health. The mechanisms of As speciation change in soil within wetland rhizospheres are understood, but their location-precise importance within heterogeneous root-associated microbiomes is uncertain. While microbial processes are often considered dominant drivers of As redox transformations, the role of abiotic factors such as reactive oxygen species (ROS) remains underexplored due to limited in situ evidence. Here, we combined multiple high-resolution in situ techniques to map microscale distributions of As(III)/As(V) and key environmental parameters in rice rhizospheres across three paddy soils. A novel ratiometric fluorescent approach was developed for in situ visualization of ROS. Strong spatial correspondence was observed between ROS hotspots and decreased As(III) (R2 = 0.797), exceeding that for O2 (R2 = 0.348). Integration of imaging with functional gene analysis (aioA, arsC), sterilization and ROS-quenching experiments, and structural equation modeling indicates that ROS-driven processes play a crucial role under the studied conditions. However, as gene abundance reflects microbial potential rather than activity, microbial contributions cannot be excluded. These findings highlight ROS as a key regulator of As speciation and provide new insights into coupled abiotic-biotic processes in rhizosphere environments.

Commercial pH test strips suffer from low sensitivity in the extremely acidic range (pH 0.5-1.5) and are typically single-use due to indicator leaching, causing environmental concern. To address these issues, we developed a reusable pH test strip based on the strong adsorption between Congo red and a nylon film. It was prepared by a simple soaking-ultrasonic washing process (optimal washing times is 15) and can be reused at least 100 times. After a single calibration, it maintains a deviation within ±0.1 from the pH meter following 11 days of storage in water and within ±0.15 after 30 days, demonstrating excellent stability. The response shows low temperature sensitivity in the range of 10.2-39.1 °C and no response to common ions (Na+, K+, Ca+, Mg2+, Cu2+, Fe3+, Zn2+, Pb2+, and Hg2+). Using a smartphone, the Total Huev parameter, and IQA software, the strip enables accurate pH determination of HCl solutions and simulated gastric fluids. Thus, it serves as a low-cost alternative to pH meters for preparing acidic solutions (pH 0.5-1.5) and for preliminary screening of the Zollinger-Ellison syndrome, reducing damage to pH electrodes from highly acidic media. Furthermore, the strip identifies four concentrated acid reagents (H2SO4, CH3COOH, HNO3, and HCl) via kinetic response, naked-eye color comparison, or principal component analysis. Future work includes extending this reusable platform to broader pH ranges to mitigate environmental pollution from disposable test strips. The exceptional leaching resistance of the Congo red-nylon film makes it promising for pH imaging.

The diffusive gradients in thin films (DGT) technique has been used for monitoring various organic pollutants in surface water in recent years. This article applies a novel DGT passive sampler to the Nanjing section of the Yangtze River and urban rivers to measure the in-situ concentrations of polycyclic aromatic hydrocarbons (PAHs), analyze their seasonal changes and determine their fate. PAH concentrations had marked seasonality. The concentration of individual PAH was 1.3-18 ng/L in summer and 4.2-161 ng/L in winter. Source inputs, flow differences and degradation/losses caused the seasonal differences. Inputs from Nanjing and tributary rivers were minor compared to the cumulative loads of PAHs in the main Yangtze river upstream of the city. Petrochemical enterprises along the Yangtze River, ship transportation, and upstream pollution were the main sources of pollution in this area. Source analysis indicated a mixed source with coal and biomass combustion inputs increasing significantly in winter. Risk assessment indicated that although the Yangtze River protection policy has reduced pollution in recent years, water quality still exceeded PAH ecological thresholds in the river and the chemical industry cluster areas during winter. Further measures are needed to reduce pollution and its associated risks from a catchment perspective.

The traditional analysis methods for fluoride ions, including potentiometric titration and chromatography, suffer from issues such as complex analysis processes, high costs, and long duration. Here, a typical nanocomposite, consisting of an iron metal-organic framework (MIL-100(Fe)) with surface defects and graphitic carbon nitride (g-C3N4), has been successfully developed through regulation by 3-aminophenylboric acid, specifically for the fabrication of fluoride ion sensors. The electrochemical behavior of fluoride ions was investigated using the modified electrode via differential pulse voltammetry. The test results demonstrated a significant linear correlation between the intensity of response current and the concentration of fluoride ions, with an R2 value greater than 0.9926, across two concentration ranges: 0.8-8.0 and 8.0-80 μM. The limit of detection and sensitivity for fluoride ions were calculated to be 0.20 μM and 17.007 μA μM-1 cm-2, respectively. Mechanism analysis reveals that the primary reason for the enhancement of the properties of the modified materials lies in the exposure of additional metal active sites due to the defect structure, as well as the synergistic effect of boric acid functional groups. The interference of several common anions, including Br-, I-, Cl-, NO3-, CO32-, SO42-, H2PO4- and CH3COO-, was found to be almost negligible. Additionally, the working electrode has also been preliminarily evaluated in tap water and lake water samples and obtained recoveries in the range of 92-108%.

The pH of environmental systems plays a crucial role in determining pollutant behavior, necessitating the development of effective tools for real-time monitoring. This study introduces a novel series of lipophilic HPTS derivatives, developed through a two-step synthesis route, designed as pH-sensitive dyes, characterized by high fluorescence intensity, photostability, dual excitation/single emission, and significant Stokes shifts. We engineered self-ratiometric pH-sensing planar optode foils and investigated the impact of carbon chain length on foil durability. These foils demonstrate reliable quantitative pH detection across a range of 6.5-9.5 using commercial imaging systems and maintain exceptional photostability with minimal ionic interference. Notably, foils constructed with HPTS(DPA)3 derivatives, where the substituent carbon chain length is longer than six carbons show no significant leakage under varying pH conditions. The practical application of the foil was validated by mapping the two-dimensional pH distribution in the soil rhizosphere around rice roots at a resolution of 17 megapixels, demonstrating the potential for environmental monitoring applications.