Globally, the disturbances caused by dam construction to the stability of river ecosystems are intensifying. Previous studies largely focused on a single stressor, a single trophic level, or a single dimension of stability. In contrast, this review adopts a multi-trophic cascade perspective to systematically outline four key mechanisms through which dam construction affects stability: (1) hydrological changes weaken resistance, resilience, and persistence; (2) biogeochemical imbalances increase the risk of regime shifts; (3) the transition from brown food webs to green food webs and the resulting simplification lead to decreased resistance; and (4) diversity compression disrupts resistance and increases variability through increased species synchrony and reduced network modularity. Traditional unidimensional assessments struggle to capture these non-synergistic changes; multidimensional stability frameworks, such as ellipsoids and n-dimensional hypervolumes, provide methods to analyze decoupling and reconstruction. Dam construction often occurs in conjunction with phenomena such as eutrophication, and their coupled effects exhibit heterogeneity across different trophic levels, further complicating stability assessments. Future research should integrate multidisciplinary methods, including eDNA and ecological network analysis, to provide further theoretical support for adaptive river management.

Red mud is a substantial solid waste produced by the alumina industry, with an annual global output of more than 100 million tons, while its comprehensive utilization rate is still less than 15%. The environmental pollution caused by its extensive stockpiling has become a major issue restricting the sustainable development of the industry. This paper summarizes recent research findings on red mud recycling both domestically and internationally, and based on the development status of recycling technology, proposes three collaborative approaches for red mud treatment: source reduction through production process optimization, resource recovery of valuable components, and large-scale utilization for extensive consumption. The analysis suggests that future improvements in recovery efficiency and expansion of recovery scale for red mud will require innovations in production processes to reduce output, enhancing resource utilization efficiency through multi-element collaborative recovery, and relying on large-scale utilization to improve harmless treatment levels. These measures aim to transform red mud from “red solid waste” into a “green resource,” thereby supporting the high-quality development of the aluminum industry.

A series of self-standing tubular membranes were fabricated by incorporating F-doped polyaniline-derived porous carbon (F-PPC) with carbon nanotubes (CNTs) at systematically varied mass ratios (CNT:F-PPC = 1:2, 1:1, 2:1) for electro-Fenton filtration applications. Comprehensive structural and physicochemical characterization indicated that compositional control can effectively regulate the membrane properties. Specifically, increasing the CNT content can modulate the electrocatalytic performance, microstructure, and electron density distribution of the hybrid membranes. Among the configurations, the C1P1 membrane (CNT:F-PPC = 1:1) achieved an optimal balance, featuring a moderate pore size, appropriate hydrophobicity (94.36°), and satisfactory conductivity (33.1 Ω), indicating synergistic effects between defect-mediated catalytic activity and conductive pathways for reactive oxygen species generation. Under electrochemical assistance, the C1P1 membrane exhibited superior antifouling performance and contaminant removal efficiency, achieving complete bovine serum albumin rejection, along with 33.7% degradation of glucose and 38.6% degradation of humic acid. The enhanced performance can be attributed to the balanced degree of graphitization and defect density resulting from fluorine-induced electron redistribution. This redistribution synergistically promotes both the 2e^– oxygen reduction reaction and the Fenton pathway for the efficient production of ·OH. This work establishes fundamental structure–property relationships in multifunctional carbon membranes and provides a sustainable strategy for integrated wastewater treatment through simultaneous filtration and electro-Fenton processes.

Algal blooms in eutrophic lakes are shaped by non-linear responses to both current and antecedent environmental conditions, while their dominant drivers can vary across space and bloom stage. This study developed an explainable machine-learning framework for predicting algal density using high-frequency monitoring data collected from six stations in Lake Taihu, China, during 2021–2024. The lake was divided into eastern and western functional zones, and separate models were developed for stable, outbreak, and decline stages. Two predictor schemes were compared: W1 contained contemporaneous environmental variables, whereas W2 additionally incorporated 3–15 d lagged, moving-average, and cumulative predictors. Across four algorithms and seven data subsets, W2 outperformed W1 in all 28 matched comparisons: mean test-set R² increased by 0.140, while MSE, RMSE, and MAE decreased by 41.2%, 24.0%, and 27.8%, respectively. XGBoost achieved the best overall performance, with a maximum test-set R² of 0.901. An integrated ranking based on model-specific importance, permutation importance, and SHapley Additive exPlanations (SHAP) showed strong context dependence. Solar radiation, total phosphorus (TP), and the 15-d mean N:P ratio dominated the global model; TP and total nitrogen were prominent during eastern functional-zone outbreak and decline stages, whereas antecedent pH, permanganate index, precipitation, turbidity, conductivity, and N:P were more influential in western functional-zone stage-specific models. BIC-supported segmented SHAP analysis with bootstrap confidence intervals identified reproducible model-derived transition ranges, including stage-dependent TP transitions on the eastern functional zone, pH transitions near 7.8 on the western shore, and N:P transitions during bloom decline. These results demonstrate that antecedent environmental information improves prediction and that spatial-stage stratification reveals local response regimes that are obscured in a lake-wide model.

Efficient nitrogen removal from low C/N wastewater remains a major challenge for conventional biological treatment processes. In this study, a modified continuous-flow A/O process with programmable cyclic flow control was established to achieve enhanced nitrogen removal. The system consistently achieved low effluent TIN concentrations of 2.6 ± 0.9 mg-N/L and 6.3 ± 1.1 mg-N/L under influent C/N ratios of 5.5 and 3.1, respectively. Notably, the process promoted in-situ enrichment of anammox bacteria, with their relative abundance reaching 0.8%. Correspondingly, the abundances of key anammox functional genes increased substantially, with hzs and hdh rising from 7.3 and 0.9 TPM to 202.6 and 31.4 TPM, respectively. Mass balance analyses revealed clear functional partitioning of nitrogen transformation pathways. Simultaneous nitrification–denitrification (SND) and partial denitrification–anammox (PDA) predominantly occurred in the oxic and anoxic tanks, respectively, while conventional nitrification–denitrification (CND) acted as a complementary pathway. At the higher C/N of 5.5, SND dominated nitrogen removal, accounting for 67.2% ± 0.9% of the total flux. At the lower C/N of 3.1, PDA played a more prominent role, contributing 39.4% of the overall nitrogen removal. This functional differentiation was supported by microbial community profiling and functional gene analyses. Batch experiments further confirmed the pronounced SND and PDA potentials in the oxic and anoxic tanks, respectively. This study establishes a novel operational strategy that enables in-situ enrichment of anammox bacteria and achieves highly efficient nitrogen removal via PDA, SND, and CND.

Decabromodiphenyl ether (BDE-209), the most widely used polybrominated diphenyl ether (PBDE), remains environmentally persistent and bioaccumulative, yet its comprehensive neurotoxic mechanisms in aquatic ecosystems remain unresolved. Here, we integrated single-cell RNA sequencing (scRNA-seq) with multi-level analysis to investigate the neurotoxicity of BDE-209 in zebrafish brain. Zebrafish exposed to environmentally relevant and high concentrations of BDE-209 for 21 d did not show visible morphological changes but exhibited significant biochemical alterations, including decreased superoxide dismutase, increased lipid peroxidation, and upregulated pro-inflammatory cytokines, indicating sublethal neurotoxicity in the absence of acute lethality and overt morphological alterations. Histological staining revealed neuronal damage and apoptosis, corroborating the biochemically observed oxidative stress and inflammatory responses. The scRNA-seq results further revealed cell-type–specific transcriptional changes in macrophages, natural killer T cells, excitatory neurons, and inhibitory neurons, involving pathways related to oxidation (PPAR signaling pathway), immune activation (Toll-like, NOD-like, RIG-I-like, and C-type lectin receptor pathways), and neurotransmission (endocytosis and efferocytosis pathways). In addition, network analysis identified central genes that mediate these processes. Our results provide the first cellular- and molecular-resolution evidence that BDE-209 induces an oxidation–immune–neurotransmission neurotoxic cascade in zebrafish brain. These findings will advance our mechanistic understanding of the toxicity of PBDEs in aquatic ecosystems and provide new insights into environmental risk assessment and effective management of persistent flame retardants.

A novel cold-adapted bacterium, Acinetobacter bohemicus strain FX-Q2, was isolated from activated sludge and demonstrated efficient simultaneous aerobic removal of nitrogen and phosphorus. The strain could completely remove NH₄⁺-N and PO₄^3–-P from real wastewater within 36 h at 10  °C. Under optimized cultivation conditions (sodium acetate as the carbon source, C/N 10, P/N 0.2, pH 7.5, and 150 r/min) at 10 °C, strain FX-Q2 achieved the highest removal efficiencies for NH₄⁺-N (99.89%), NO₂^–-N (99.84%), NO₃^–-N (94.94%), and PO₄^3–-P (100%) within 48 h. Functional gene annotation revealed that the strain possessed genes associated with three nitrogen metabolic pathways: heterotrophic ammonia assimilation (HAA), assimilatory nitrate reduction (ANRA), and dissimilatory nitrate reduction to ammonium (DNRA), suggesting strain FX-Q2 could assimilate nitrogen via multiple mechanisms. This prediction was substantiated by nitrogen balance analysis, which identified heterotrophic assimilation as the dominant nitrogen removal route, whereas nitrification contributed only marginally. The presence of nitrification activity was further confirmed using enzyme assays. Genomic analysis and enzymatic assays indicated that aerobic phosphorus removal was primarily mediated by ppk1 and ppx-gppA. Phosphorus distribution experiments showed that 50.89%–58.62% of phosphorus was incorporated into the cell membrane, while phosphorus associated with extracellular polymeric substances (EPS) served as a dynamic phosphorus reservoir. Collectively, Acinetobacter bohemicus strain FX-Q2 exhibits the potential for sustainable nutrient removal and recovery in cold-climate bioprocesses.

The application of anaerobic ammonium oxidation (anammox) is often constrained by the limited availability of nitrite (NO₂^–-N). Microbial electrochemical technology offers a promising strategy to circumvent this limitation. Therefore, we constructed microbial electrolysis cells (MECs) incorporating marine-anammox electroactive biofilm and conducted batch experiments to investigate the effects of operational parameters and quorum sensing (QS) signal molecules on their performance. Under NO₂^–-N-deficient conditions, the anodic biofilm utilized the graphite felt electrode as an extracellular electron acceptor to drive anammox process, achieving ammonia (NH₃-N) removal while generating a sustained electrical current. Notably, no nitrate was produced, and NO was not a key intermediate in electrode-dependent anammox. NH₃-N removal followed first-order kinetics, with a substantially lower rate constant for the electrode as electron acceptor than for NO₂^–-N. Higher initial NH₃-N concentrations (25–100 mg/L) and temperatures (10–35 °C) significantly enhanced nitrogen removal and current generation. NO₂^–-N below 5 mg/L had a negligible impact, whereas higher levels (5–75 mg/L) slightly improved nitrogen removal but markedly suppressed current generation. Dissolved oxygen below 1.0 mg/L exerted minimal influence. Externally-added C₆-HSL, C₁₂-HSL, and 3-oxo-C₆-HSL (5–80 µmol/L) promoted both nitrogen removal and current generation. Conversely, 3-oxo-C₁₂-HSL (5–80 µmol/L) and acylase I (10–80 mg/L) inhibited these processes. The promoting or inhibitory effects exhibited concentration- and time-dependence, with lower concentrations requiring longer exposure to achieve stable effects. These findings demonstrate the potential of marine anammox-based MECs for treating NO₂^–-N-deficient mariculture wastewater and highlight the role of QS in regulating their performance.

Cadmium-contaminated wastewater from rapidly expanding industrial activities has become a pressing environmental challenge. Here, we developed a one-step mechanochemical modification strategy to enhance Cd(Ⅱ) removal by reconstructing endogenous Si–O and –OH networks in rice straw-derived biochar. By coupling alkaline treatment activation with mechanical ball milling, inherent silicates in the straw were effectively activated to form SiVO–Si and Si–O–C anchoring sites, while mechanical shear fractured polysaccharide chains and promoted the enrichment of surface –OH groups. The optimized adsorbent (Al-bmST1) exhibited a bifunctional adsorption interface with improved coordination affinity toward Cd(Ⅱ), achieving a removal efficiency of 88.01% and the adsorption capacity reached 27.1 mg/g. This performance was significantly superior to that of both the two-step modified biochar (Al-bmST2) and the biochar prepared solely via mechanical milling (bmST). In situ Fourier-transform infrared (FTIR) analysis and density functional theory (DFT) calculations confirmed that Cd(Ⅱ) formed stable ≡Si–O–Cd⁺ complexes, while surface –OH groups further strengthened adsorption stability. Life cycle assessment (LCA) further showed that the one-step mechanical chemical treatment reduced carbon emissions by 56.72% relative to the conventional straw pyrolysis process, without generating significant harmful gas emissions. These findings provide a low-carbon and efficient route for converting agricultural waste into functional adsorbents for heavy metal wastewater treatment.

Machine learning (ML) has been increasingly used to model the adsorption of organic pollutants (OPs) onto microplastics (MPs). However, existing studies have not adequately captured key influencing factors or implemented proper data leakage management (DLM) during model development. To bridge these gaps, ML models were developed using comprehensive features including microplastic properties, pollutant properties, and adsorption conditions, and three DLM strategies, namely data point-, isotherm-, and study-based, were evaluated on datasets. Furthermore, feature-similarity analysis provided mechanistic support for isotherm-based data partitioning, extending model selection beyond predictive performance alone. The resulting models achieved robust predictive performance and revealed the mechanistic relevance of comprehensive factors integration, with equilibrium concentration and hydrogen bonding emerging as dominant drivers. Overall, by addressing the critical but previously overlooked issue of data leakage and underscoring the need for holistic feature integration, this study establishes a new methodological baseline that resolves key limitations in current MP–OP adsorption modeling and guides future research.

Introducing exogenous electron shuttles (ESs) that could synergistically enhance the removal efficiency of both ammonium nitrogen (NH₄⁺-N) and total nitrogen (TN) in Feammox systems. In this study, stable operation of a Feammox reactor was accomplished through acclimation of Feammox sludge. The removal rates of NH₄⁺-N and TN reached approximately 75% and 50%, respectively. The coupled Feammox and nitrate-dependent ferrous iron oxidation (NDFO) processes constituted the primary nitrogen removal pathways. Compared to the blank control group and the commonly used anthraquinone-2,6-disulfonic acid (AQDS), the addition of activated carbon (AC) significantly enhanced NH₄⁺-N and TN removal efficiencies by 30.61% and 18.21%, and 9.01% and 10.34%, respectively. Mechanistic studies indicated the formation of FeOOH in the presence of FeCl₃. The abundant quinone (C=O) and phenolic hydroxyl (–OH) functional groups on the AC surface effectively promoted the recycling of Fe(II)/Fe(III), thereby enhancing electron transfer efficiency in the Feammox system. Additionally, AC stimulated the secretion of microbial extracellular polymeric substances (EPS), further accelerating electron transfer between Fe and NH₄⁺-N. Notably, compared to soluble ESs like AQDS that are prone to loss via water flow, AC as a solid-phase ES exhibits superior stability and persistence, demonstrating enhanced nitrogen removal performance. This study developed a green, cost effective and efficient biological nitrogen removal technology, providing significant theoretical support and technical reserves for the practical engineering application of Feammox.

Phytoplankton regime shifts in shallow lakes have severe effects on ecosystem stability and water quality. However, precise regulation is a formidable task because regime shifts exhibit uncertainties and stochasticity arising from permanent environmental fluctuations. The key challenge lies in capturing their complex non-equilibrium dynamics. Therefore, we developed a potential and flux landscape framework to quantify phytoplankton dynamics. Phytoplankton dynamics showed four distinct temporal patterns in long-term chlorophyll-a records from 80 shallow lakes worldwide: abrupt changes (18.75%), monotonic decline (28.75%), increasing then decreasing trend (17.50%), monotonic increase (35.0%). Phytoplankton bistability was confirmed across all patterns through potential landscape analysis, despite their diverse temporal patterns. Total nitrogen (TN) to total phosphorus (TP) ratios emerged as the dominant driver that induced regime shifts by modulating the potential barrier height. Temperature was identified as the key perturbation because even a slight variation (1%) markedly altered critical transition probability, while larger fluctuation intensities triggered regime shifts within the bistable region. Furthermore, a regulation threshold at TN:TP ≈ 23 was identified by quantifying the driving forces of phytoplankton dynamics through mean flux and entropy production. This threshold reflects thermodynamic reorganization and is detected well before the tipping point where the current state disappears, enabling timely intervention and thereby avoiding delayed responses caused by hysteresis effects. These findings elucidate the regulatory pathways of phytoplankton regime shifts and provide mechanistic insights for managing eutrophication in shallow lakes.

Molecular structure strongly affects the formation and persistence of persistent free radicals (PFRs) during the photochemical transformation of quinone aromatic compounds, yet the underlying mechanisms remain unclear. In this study, the formation and evolution of PFRs in five quinones aromatic compounds under the irradiation and subsequent dark conditions were investigated using electron paramagnetic resonance (EPR) spectroscopy. Results showed that upon irradiation, all tested quinones rapidly generated PFRs, though the kinetic profiles varied among compounds. After 2 h of irradiation, the relative generation of PFRs followed the order: 2-chloro-p-benzoquinone > 1,4-naphthoquinone > anthraquinone > 2-methyl-p-benzoquinone > 1,4-benzoquinone. However, the light-induced radicals generated from model quinones exhibit low stability, dissipate gradually, and eventually revert to their initial levels. The PFRs decayed rapidly following two-stage kinetics, with the 1/e lifetimes ordered as: 1,4-benzoquinone > 2-methyl-p-benzoquinone > anthraquinone > 1,4-naphthoquinone > 2-chloro-p-benzoquinone. Fourier transform infrared (FTIR) and X-ray photoelectron spectroscopy (XPS) confirmed that PFRs formation involved quinone groups (C=O) conversion to C–O and electron rearrangement within the aromatic rings. Spin-trapping and H₂O₂ measurements further revealed that the involvement of ROS generation and consumption in PFRs evolution. These findings provide insights into the photo-transformation processes of aromatic compounds in environmental matrices and a scientific basis for evaluating their reactivity and ecological risks.

The biological treatment of sulfate-rich organic wastewaters is challenged by the generation of toxic hydrogen sulfide (H₂S), due to its inhibition to key microbial communities of sustaining system stability. Unlike existing reviews focusing on individual H₂S removal technologies, this work presents a holistic control framework that strategically integrates H₂S generation, in-process mitigation, and final control, with a unique emphasis on the synergy of sulfate reduction and system resilience. First, we systematically dissect the multi-level inhibitory mechanisms of H₂S on anaerobic consortia, including the disruption of disulfide bonds, metalloenzymes, and quorum sensing signal molecules. Crucially, we prioritize process management strategies, such as microaeration, gas stripping, and chemical precipitation, balancing H₂S removal and enhanced sulfate-reducing activity under electron-donor-limited conditions. We further comprehensively introduce a paradigm shift from reactive control to predictive one by detailing the integration of online monitoring, machine learning, and digital twins for dynamic process optimization. By identifying critical future directions, including the development of robust liquid phase sensors and hybrid strategies that couple H₂S control with resource recovery, this review provides actionable insights for designing resilient anaerobic systems toward sustainable wastewater treatment.

Sulfur autotrophic denitrification (SADN) requires no external organic carbon and has low operating costs. However, its slower denitrification kinetics than heterotrophic denitrification remains a key bottleneck limiting its application for nitrogen removal from low carbon-to-nitrogen (C/N) wastewater. Herein, elemental sulfur (S⁰) and nanoscale zero-valent iron (nZVI) were integrated into uniform millimeter-scale composite pellets (nZVI/S⁰) to enhance SADN. The nZVI/S⁰-amended group not only attained an average total nitrogen (TN) removal efficiency of 96.0% but also exhibited rapid TN removal at an average rate of 3.80 mg N/(L·h), far exceeding the rates observed in the groups supplemented with S⁰ (1.17 mg N/(L·h)) or nZVI (0.08 mg N/(L·h)). In the nZVI/S⁰ system, both nZVI and S⁰ could serve as electron donors, contributing to the enhanced denitrification performance. Specifically, nZVI in nZVI/S⁰ markedly increased the relative abundance of the core sulfur autotrophic denitrifier Thiobacillus and the relative abundances of denitrification genes, sulfur oxidation genes, and electron transfer-related genes. Additionally, it promoted the expression of genes related to denitrification and sulfur oxidation, enhanced the activities of key denitrifying enzymes (including nitrate reductase Nar and nitrite reductase Nir), and elevated the electron transfer activity in the system. Meanwhile, integration within the sulfur matrix significantly reduced the microbial toxicity of nZVI, retarded its rapid passivation, and suppressed the ammonium-forming side reaction caused by direct nitrate reduction by nZVI. This study provides a new approach for improving SADN and achieving efficient nitrogen removal from low C/N wastewater.

Pharmaceutical pollutants are increasingly detected in wastewater, raising substantial concerns for the environment and human health. To tackle this challenge, we developed a layered double hydroxide (LDH)-modified BiVO₄ photoanode (ZnFe-LDH/BVO) for enhanced photoelectrochemical (PEC) degradation of tetracycline (TC-HCl). The ZnFe-LDH/BVO system demonstrated superior PEC performance, achieving a 0.066 min⁻¹ degradation rate, a photocurrent of 3.2 mA, and a 98% removal efficiency for 10 mg/L TC, surpassing bare BiVO₄, which achieved only 0.007 min⁻¹ and 1.6 mA. The ZnFe-LDH/BVO heterostructure effectively suppressed charge recombination, enabling a 9.5-fold increase in degradation rate compared to unmodified BiVO₄. The developed PEC system exhibited high efficacy in treating synthetic reverse osmosis concentrate (ROC) wastewater, where naturally occurring chloride ions were activated to generate reactive chlorine species, •Cl and •ClO, which facilitated efficient TC degradation. To further exploit the process, the system was also assessed for evolution of hydrogen, a useful carbon-free energy carrier, yielding H₂ production of 50 μmol/cm² in synthetic ROC after 2 h, compared to 4 μmol/cm² for unmodified BiVO₄. However, the presence of chloride ions also increased the potential for disinfection byproduct (DBP) formation, which was systematically evaluated under varying TC concentrations. Additionally, natural organic matter (NOM) in ROC solutions slightly inhibited PEC performance by quenching reactive species and adsorbing onto the photoanode, impeding TC-HCl oxidation. This study highlights the ZnFe-LDH/BVO PEC system as a promising technology for pharmaceutical degradation in wastewater, combining effective pollutant removal with potential energy recovery. Its robust performance underscores its practicality for sustainable wastewater treatment.

Antimicrobial resistance (AMR) imposes a substantial burden on global public health. Given the critical importance of last-resort antibiotics (LRAs) in clinical practice, comprehensive surveillance of LRA-related resistance is of paramount public health significance. As an emerging tool, wastewater surveillance (WS) has the potential to effectively complement existing clinical surveillance systems for LRA resistance at the population level. However, the extremely low abundance of LRA-resistant bacteria in wastewater hinders sensitive detection by conventional culture-based or molecular methods. In this study, using Escherichia coli (E. coli) as the target organism, we monitored resistance levels to three typical LRAs (tigecycline (TIG), meropenem (MEM), and colistin (CT)) in wastewater samples collected from wastewater treatment plants and manholes in Beijing, China. Our results demonstrated that the simultaneous species-resistance selection strategy significantly improved the detection of LRA-resistant E. coli, and the resistance rates in wastewater showed a certain correlation with clinical resistance rates. Further analysis revealed that the typical LRA-resistant isolates exhibited pronounced multidrug resistance (MDR) characteristics, with high resistance rates to clinical first-line antibiotics. Moreover, we identified dual LRA-resistant E. coli and a high-risk IncHI1 plasmid co-harboring blaNDM-5, mcr-1.1, and more than 12 antibiotic resistance genes, warranting further investigation. This study validates the feasibility of monitoring the prevalence of LRA resistance through WS and provides methodological support and key monitoring targets for future efforts.