The nitrate reduction reaction (NO3- RR) offers an eco-friendly pathway for sustainable ammonia production, this research presents a novel NO3 -to NH3 conversion mechanisms by elucidating the structure-activity relationship between different [MnO6] octahedral connection modes and catalytic performance. The alpha-MnO2-160 catalyst rich in corner-positioned oxygen vacancies ([Mn3+] - VO- [Mn3+]) demonstrated the best performance, achieving a Faraday efficiency (FE) of 91.48% at -1.0 V vs. RHE and an NH3 production rate of 1540.9 mu mol h- 1 cm- 2 at -1.2 V vs. RHE, while maintaining stability during 15 h of continuous operation. The [Mn3+] - VO[Mn3+] structure, serving as a bimetallic active center, significantly enhances the NO3 -adsorption energy (-2.39 eV) and promotes N - O bond dissociation, while effectively reducing the energy barriers (-3.30 eV, -1.84 eV) of the *NOH -> *N -> *NH pathway and suppressing the conventional *NOH -> *NHOH pathway (-1.25 eV). This corner oxygen vacancy-induced electron rearrangement mechanism achieves precise regulation of the adsorption strength of reaction intermediates, providing a theoretical basis for designing high-performance Mnbased NO3- RR catalysts and demonstrating its potential in efficient catalysis as well as the development of energy and chemical industries.

The slow Fe3+/Fe2+ redox cycle represents a fundamental rate-limiting step in iron-mediated peroxymonosulfate (PMS) activation, due to constrained interfacial electron-transfer kinetics. While transition-metal dichalcogenides such as MoS2 have emerged as promising co-catalysts to overcome these kinetic barriers, the definitive correlation between MoS2 structures and their co-catalytic performance remains unclear. Herein, we systematically investigate the roles of phase composition (1 T/2H ratio) and relative edge exposure in governing the electron transfer and redox dynamics of MoS2-assisted Fe3+/PMS Fenton-like systems. To establish clear structure–activity relationships, five MoS2 samples with tuned structures were synthesized and tested for the degradation of Atrazine (ATZ), as a model contaminant. Electrochemical analyses reveal enhanced interfacial electron-transfer capability for the 1 T-rich MoS2 structures, while Fe2+ evolution measurements support their enhanced Fe3+/Fe2+ redox cycling. Radical-quenching experiments and electron paramagnetic resonance (EPR) spectroscopy confirm the sulfate radical (SO4•‒) as the primary radical. Furthermore, X-ray photoelectron spectroscopy (XPS) and in situ Raman spectroscopy demonstrate that phase composition and relative edge exposure synergistically promote Fe3+/PMS activation through enhanced interfacial electron transfer. These results provide mechanistic insights into the structural determinants of MoS2 co-catalysis and offer a robust framework for designing efficient, iron-based advanced oxidation processes for water treatment.

The two-electron oxygen reduction reaction (2e- ORR) offers a promising route for the on-site electrosynthesis of hydrogen peroxide (H2O2). While oxygen-functionalized carbon-based catalysts exhibit favorable ORR activity, their performance is often limited by the simplistic idealization of individual oxygen functional groups (OFGs). This study introduces a gradient engineering strategy of OFGs to precisely modulate the microenvironment surrounding cobalt phthalocyanine (CoPC) molecular interfaces. Based on the theory of density universal function (DFT), the gradient strategy is transferred to the spatial probability distribution of OFGs, and it is clear that the symmetric distribution of carbonyl group (C--O) can spatially isolate its strong electron-withdrawing effect and optimize the binding energy between the electron-deficient Co center and the OOH* intermediate. Integrated into a proton exchange membrane (PEM) reactor, the resulting catalyst achieved continuous and stable operation at a current density of 50 mA cm- 2 for 24 h, delivering a high H2O2 yield of 9.7 mol gcat low cell voltage of 2.26 V. This work provides new mechanistic insights into OFG gradient engineering as an effective strategy to enhance H2O2 electrosynthesis.

Internal corrosion in drinking water distribution systems (DWDSs) drives secondary water quality deterioration, yet scalable approaches for inferring in-service corrosion condition remain limited. In this study, 20 excavated pipe segments from a large metropolitan DWDS were investigated using paired upstream-downstream water quality measurements, inner wall image interpretation, and physicochemical characterization of corrosion scales. A residence-time-normalized variation rate was used to quantify segment-level water quality change. By comparing alternative image-weighting schemes and PCA scoring combinations, a mutually validated corrosion score was derived. The score captured the dominant contrast between Fe-rich corrosion products and Ca-enriched materials and showed strong agreement with the image-based condition index (Spearman's ρ = 0.95, p < 0.001). Among the evaluated models, a multivariable linear regression (MLR) model was selected for its strong predictive performance and interpretability. Incorporating pipe attributes and selected variation metrics, it explained 85.4% of the variance in the corrosion score (R2 = 0.854) and provided clear in-sample discrimination between severe and non-severe segments. Independent validation using 12 additional and non-excavated pipe segments achieved 83.3% classification accuracy. These results demonstrate that pipe corrosion condition can be inferred from routine water quality signals through a mechanistically interpretable and statistically grounded framework, providing new insight into how pipe wall condition shapes downstream water quality responses in drinking water distribution systems.

Periodate (PI)-based oxidation has emerged as a promising alternative to conventional advanced oxidation processes in water treatment. Among various catalytic systems, manganese-periodate (Mn/PI) systems have attracted increasing attention due to their environmental compatibility, cost-effectiveness, and distinctive reactivity. However, existing studies predominantly interpret Mn/PI chemistry from an “activation” perspective, while a unified understanding of its intrinsic redox nature remains lacking. Herein, we propose that Mn/PI systems should be redefined as redox-coupled catalytic networks, in which manganese species and iodine species undergo mutual redox interactions, driving pollutant transformation through multiple intertwined pathways. This review systematically elucidates the fundamental physicochemical properties of PI and traces the evolution of Mn/PI systems, supported by bibliometric analysis to reveal emerging research trends. Manganese-based catalysts are categorized into six classes according to manganese speciation and structural configuration, and their performance in degrading representative emerging contaminants is critically evaluated. Mechanistically, Mn/PI systems are interpreted through four interconnected pathways: reactive manganese species, reactive iodine species, reactive oxygen species, and electron transfer. Special emphasis is placed on the pivotal role of electron transfer and high-valent manganese intermediates in governing selective oxidation and limited mineralization. Furthermore, emerging evidence suggests that such redox-driven pathways may induce transformation-oriented processes, including coupling or oligomerization of electron-rich contaminants, thereby underscoring the need to reassess Mn/PI systems from both pathway complexity and application-scenario perspectives. Beyond pollutant degradation, the transformation, cycling, and environmental fate of iodine species are comprehensively analyzed, highlighting potential risks associated with iodinated by-products and secondary pollution. Finally, key challenges related to mechanistic ambiguity, mineralization efficiency, material durability, and large-scale applicability are identified. Future research directions are proposed to shift the focus from simple contaminant removal toward redox regulation, iodine risk management, and scenario-oriented application. This review aims to establish a conceptual framework for understanding Mn/PI redox coupling and to provide theoretical guidance for the rational design and sustainable implementation of Mn/PI systems.

The increasing detection of trace organic micropollutants (OMPs) in water is intensifying the need for efficient and sustainable treatment. Ultraviolet-based advanced oxidation processes (UV-AOPs) have emerged as an important class of options for OMP control, but diversification of UV sources and wavelengths complicates selection. This review integrates mechanistic insights and performance metrics to guide UV-AOP design and source selection. Krypton-chloride excilamps emitting at 222 nm represent an emerging far-UVC source with growing research interest, but are constrained by low wall-plug efficiency and short lifetimes. Low-pressure mercury lamps remain a robust choice for large-scale applications, whereas ultraviolet light-emitting diodes offer flexible wavelength combinations and modularity but still suffer from limited wall-plug efficiency. Shorter wavelengths enhance direct photolysis and radical formation in peroxide-based systems, while activation of free chlorine is favored at 265-300 nm and chlorine dioxide responds most strongly in the UVA. In real waters, dissolved organic matter, nitrate, halides, and carbonate alkalinity redistribute photons and reshape reactive species pathways, often attenuating gains observed in clean matrices. Faster degradation does not necessarily translate into lower electrical energy per order. No single type of UV source is universally optimal; implementation should be application driven, matching wavelength-oxidant combinations to matrix conditions while balancing performance and energy efficiency across diverse treatment contexts.

Olfaction plays an essential role in human survival, evolution, and well-being. Mapping the odorant–olfactory receptor (OR)–olfactory perception network is essential for understanding olfactory mechanisms and identifying odorants, and machine learning approaches can facilitate this process. Odor quality and threshold are important olfactory perception characteristics for various industries. Moreover, ORs are promising biosensor materials for odor measurement. This review focuses on mapping the odorant–OR–olfactory perception network using machine learning methods. We comprehensively summarize and categorize the latest odor-related data sources for molecular properties, ORs, and olfactory perceptions. The current prediction models and general prediction workflows are reviewed. We delve into the application of machine learning in exploring the relationships among odorants, ORs, and olfactory perception. Deep learning methods based on molecular graphs (area under the receiver operating characteristic curve reaching 0.964) outperform classical machine learning approaches in odor quality prediction. Random Forest models (square correlation coefficient reaching 0.798) generally show advantages over other classical models in predicting odor threshold. We highlight the role of ORs in network mapping. Integrating machine learning and molecular docking can accelerate the identification and application of ORs. We also discuss the challenges and propose directions for future research in odor prediction and biosensor development. Sufficient and accurate experimental data are needed to improve odor prediction. The effects of concentration on odor quality need to be elucidated. Prediction models for odorant mixtures need to be developed by considering interactions among odorants. Binding affinity of odorant to OR is a potential input feature for odor prediction.

Current sensory evaluation methods for drinking water are often limited by inter-individual variability and insufficient comparability, making it difficult to comprehensively reflect consumer sensory experience. To address this issue, this study developed and validated a comprehensive flavor evaluation method based on Flavor Rating Assessment (FRA) and the flavor wheel, combined with benchmark referencing and objective weighting. Three objective weighting methods were compared, and the coefficient of variation method (CVM) was identified as the optimal approach for correcting subject-specific scoring weights. After assigning a flavor score of 5 to a benchmark water sample with stable physicochemical parameters, the 95% confidence interval of the recovered blind-test scores was [4.913, 5.507], confirming the feasibility of the framework. Application of this method to ten terminal water treatment approaches showed significant differences in flavor improvement performance. In particular, one multi-stage filtration process reduced “chlorinous” perception from 31% to nearly zero and increased “smooth” perception from 3% to 17%, leading to a marked improvement in drinking water flavor. Overall, the proposed method provides a more reliable framework for drinking water flavor evaluation and offers a basis for linking sensory perception with key water quality parameters and for developing future flavor prediction models.

Municipal wastewater treatment plants (WWTPs) are facing mounting pressure from rising treatment demand and increasingly stringent discharge limits. The magnetite-enhanced activated sludge (MEAS) process offers a promising pathway for in situ WWTP upgrading, yet its key operating parameters and microbial mechanisms remain unclear. This study systematically evaluated MEAS performance under various operating conditions using continuous-flow anaerobic–anoxic–oxic (AAO) reactors. The results identified sludge-to-magnetite ratio (S/M) as a critical parameter: at S/M = 1:1, TN removal efficiencies reached 90.5 % (C/N = 10) and 82.8 % (C/N = 5), 1.8- and 1.7-fold higher than the control; meanwhile, NH4+-N removal remained ∼99 % under all conditions, which was 1.6 times higher than the control. In addition, magnetite addition also demonstrated rapid start-up and strong resilience to shock loads and influent fluctuations. The process was further verified using real wastewater and achieved 72.4 % TN and 98.6 % NH4+-N removal, alongside stable COD (95.2 %) and TP (96.0 %) removal performance, all meeting Class A discharge standards in Jiangsu Province. Metagenomic sequencing revealed that magnetite addition restructured the microbial community by selectively enriching key functional taxa while inhibiting potentially problematic groups. The relative abundance of core nitrogen-transforming phylum Proteobacteria increased by 4–5 % across the three functional units in the AAO reactor; in contrast, filamentous Chloroflexi declined by 3–6 %. These shifts indicate that magnetite fosters a more functionally integrated microbial network linking nitrification, denitrification, and internal carbon cycling, thereby reinforcing both treatment efficiency and process stability. These findings establish both the operational basis and microbial mechanisms of MEAS process, providing a technically feasible strategy for sustainable WWTP upgrading.

A variety of treatment technologies effectively remove drinking water contaminants but often strip essential minerals. To mitigate potential mineral deficiencies associated with the prolonged consumption of overly purified water, minerals supplementation via natural ores has emerged as a promising strategy. In this study, four natural ores-Muyu stone(MYS), Tourmaline, pumice stone and Maifan stone(MFS)-were evaluated for their performance to release macronutrients and micronutrients. After 24 h, the concentration of dissolved Mg from MYS reached 2.27 mg/L, which was 11 times higher than that from MFS and significantly greater than the other ores (all <0.2 mg/L). MYS also released 3 times more K than MFS and over threefold more Ca than pumice stone. MYS demonstrated the broadest elemental release, whereas others were selective for few elements. Dissolution kinetics and mechanisms were described using the unreacted shrinking-core model, allowing comparison between experimental and predicted results. In tap water, MYS not only enhanced the concentrations of beneficial minerals like Mg, but also reduced disinfection by-products, particularly in trihalomethanes and haloacetonitriles. This work provides new insights into the dissolution dynamics and key parameters governing mineral release from natural ores in water, supporting their potential application in drinking water remineralization.

Carbamazepine (CBZ), a persistent pharmaceutical pollutant resistant to conventional water treatment, poses ecological risks in aquatic environments. Ultraviolet (UV)-based advanced oxidation processes (AOPs) can effectively degrade micropollutants to ensure water quality safety. This study employed sodium dichloroisocyanurate (DCCNa) as a disinfectant oxidant in a UV/DCCNa process. Adding bromide (Br-) to form UV/ DCCNa/Br- significantly enhanced CBZ degradation, increasing the pseudo-first-order rate constant (kobs) by 56.5 % (0.0479 min- 1 vs. 0.0306 min- 1). Reactive chlorine species (RCS) and hydroxyl radicals (& sdot;OH) dominated in UV/DCCNa, while UV/DCCNa/Br- additionally generated reactive bromine species (RBS), boosting efficiency. Both processes were highly pH-dependent. Photosensitizers (Cl-, HCO3- and HA) in water bodies can influence CBZ photodegradation in UV/DCCNa process. The transformation pathways of CBZ were elucidated by combining liquid chromatography-mass spectrometry (LC-MS) analysis with density functional theory (DFT) calculations. The results demonstrated that CBZ degradation predominantly occurred through oxidative cleavage at multiple reactive sites, including C8, C7, C2 and C13 positions in the molecular structure. Notably, while Brsignificantly enhanced CBZ degradation efficiency, it concurrently increased the formation of brominated transformation products with higher ecological risks, representing a double-edged sword effect ecological risk.

Naphthenic acids (NAs) are persistent, toxic, hydrocarbon-derived compounds formed during bitumen extraction and commonly found in oil sands process water (OSPW). Solar-activated calcium peroxide (CaO2) shows potential for OSPW remediation, yet the photochemical mechanisms controlling hydrolysate and reactive species (HRS) formation remain unclear. Combined kinetic modeling with probe-based experiments was used to quantify steady-state HRS concentrations ([HRS](SS)) of hydrogen peroxide (H2O2, (0.4 -2.5) & times; 10(-3) M (mol L-1)), hydroxyl radicals ((OH)-O-center dot, (0 -1.5) & times; 10(-15) M), singlet oxygen (O-1(2), (9.6 -6.8) & times; 10(-13) M), carbonate radicals (CO3 center dot-, (1.7 -2.6) & times; 10(-13) M), triplet-excited dissolved organic matter ((DOM)-D-3*, (1.6 -2.0) & times; 10(-13) M), and superoxide (O-2(center dot-), (0.06 -1.3)& times; 10(-10) M) under varying CaO2 doses (0-0.3 g L-1). Corresponding apparent quantum yields ([Phi(a)(HRS)](SS), mol Eins(-1)) across CaO2 doses of 0-0.3 g L-1 were similar to 0.99 (H2O2)-H-(), 0 -0.29 ((OH)-O-center dot), 0.093 -0.075 (O-1(2)), (1.30 -0.28) & times; 10(-4) (CO3 center dot-), 0.047 -0.090 ((DOM)-D-3*), and 0.23 -0.036 (O-2(center dot-)), respectively. The [Phi(a)(HRS)](SS) for (OH)-O-center dot and O-1(2) decreased with increasing CaO2 dose due to light-shielding effects, whereas (DOM)-D-3* and O-2(center dot-) formation rates increased at higher doses. The optimized solar/CaO2 (0.1 g L-1) achieved 68.9% removal of classical NAs (mainly center dot OH-mediated), 65.8% hydrocarbon abatement, and a 20% reduction in acute toxicity. It also improved biodegradability, increasing the BOD5/COD ratio from < 0.03-0.14, indicating partial transformation of recalcitrant organic matter into biodegradable intermediates. Synchronous fluorescence spectroscopy suggested the breakdown of multi-fused NAs into less toxic, mono-cyclic, and other more bioavailable intermediates. Additionally, total UV-vis absorbance and fluorescence intensity proved to be reliable surrogate parameters for tracking hydrocarbon removal kinetics in OSPW. These findings advance the mechanistic understanding of CaO2 photochemistry in OSPW and support a sustainable strategy for pit lake remediation.

The efficient management of food waste (FW) has emerged as a pivotal bottleneck impeding the sustainable development of the urban circular economy. This work employs a thermally activated persulfate (PDS) system to investigate abiotic carbon source production pathways of FW, aiming to achieve efficient resource utilization through biorefinery. The physicochemical properties, structure-activity relationship, and carbon source products analysis of FW during the conversion process revealed that the introduction of PDS significantly enhanced the hydrolysis and the dissolution of organic matter. Under the optimal conditions of PDS dosage of 0.2 mmol/g VS, 70 °C, and 1 h, the system achieved the highest carbon source production efficiency, with SCOD and TOC reaching 13726.0 ± 325.6 mg/L and 3862.0 ± 95.2 mg/L, respectively, representing increases of 35.2% and 26.6% relative to the control. The resulting FW-derived carbon source exhibited significantly elevated concentrations of volatile fatty acids, reducing sugars, and soluble sugars, indicating that complex particulate organic matter was effectively transformed into highly bioavailable low-molecular-weight compounds. EPR analysis elucidated that the ∙OH and ∙SO4- were the key reactive species driving the cleavage, depolymerization, and solubilization of macromolecular organic matter. Simultaneously, dissolved organic matter evolved from protein-like and microbially derived components toward humic-like substances, revealing the synergistic parallel characteristic of carbon source production and humification. In the batch nitrate utilization tests, the FW-derived carbon source achieved a denitrification rate of 70.56 mg/(g MLVSS·d), indicating its feasibility as an alternative external carbon source. As a technology for rapid carbon source production of FW, this approach is anticipated to enhance the utilization efficiency of low-grade resources, while facilitating waste resource utilization and offering feasible and important support for circular economy and sustainable urban development.

Mixed chlorine/chloramines are prevalent in water treatment and distribution systems but frequently disregarded. This study systematically investigated chlorine speciation and consumption, micropollutant degradation, and DBP formation where free chlorine (FC) was mixed with monochloramine (NH2Cl). Chlorine decay and degradation of 12 recalcitrant micropollutants (including 5 probe compounds with known and selective reactivities toward specific reactive species and 2 odorants) were markedly accelerated in mixed chlorine/ chloramines systems compared to systems with FC or NH2Cl alone. The maximal rates were achieved at the [FC]/ [NH2Cl] molar ratio of approximately 1.0, primarily driven by hydroxyl radical (HO center dot) formation. Concentrations of total DBPs formed in humic acid (HA) solutions gradually increased with increasing [FC]/[NH2Cl], accompanied by a sharp rise in calculated cyto- and genotoxicity associated with the quantified trihalomethanes (THMs) and haloacetonitriles (HANs), with CTI and GTI increasing by approximately 190% and 66%, respectively, primarily ascribed to HANs near [FC]/[NH2Cl] of 1.0. These trends can be well explained by the profile of reactive species. The formation of HO center dot and reactive nitrogen species (RNS) peaked at [FC]/[NH2Cl] of 0.8-1.0, whereas the dominant species shifted from HO center dot and RNS toward ClO center dot and Cl2 center dot- by excessive FC with increasing [FC]/[NH2Cl]. The presence of common anions selectively inhibited reactive species generation and DBP formation. Sampling from a full-scale DWTP switching disinfectant from NH2Cl to FC confirmed enhanced micropollutant degradation by HO center dot formed due to mixed chlorine/chloramines in the field. These findings build fundamentals and facilitate developing strategies for mixed chlorine/chloramines scenarios such as booster chlorination and disinfectant switching.

Pre-chlorination is an economical strategy for algae control, yet extracellular polymeric substances (EPS) can compromise its reliability. This study elucidated how EPS molecular structure governs algal responses to free chlorine (FC) and monochloramine (MC) during stepwise EPS removal. Loosely bound EPS (LB-EPS) was a soluble, protein-rich, nitrogen-containing fraction, whereas tightly bound EPS (TB-EPS) formed a more structured polysaccharide and humic-like matrix. Reaction kinetics showed higher reactivity with FC than with MC; TB-EPS consumed FC faster than LB-EPS (3.20 × 10-2 v.s. 2.14 × 10-2 mg-1·L·min-1), while MC reactions were slower (5.81 × 10-3 for LB EPS and 6.24 × 10-3 mg-1·L·min-1 for TB-EPS). Chlor(am)ination reshaped EPS protein secondary structure, with FC producing larger decreases in the α-helix/(β-sheet + random coil) ratio (39.5% for LB-EPS and 28.6% for TB-EPS), indicating weakened protein-mediated cohesion and enhanced EPS detachment. In algae assays, EPS removal accelerated intracellular oxidative stress and photosystem II (PSII) impairment before membrane permeabilization. Superoxide (O2•-) increased under FC by 59.4% without LB-EPS and 201.8% without B-EPS, and under MC by 110.3% and 500%, respectively, accompanied by stronger antioxidant enzyme responses under MC. These results highlight B-EPS as a key regulator of oxidant demand and stress buffering, guiding pre-chlorination designs for non-lytic inactivation.

Leachate from different municipal solid waste (MSW) facilities serves as a significant reservoir and a dissemination hub for pathogenic microorganisms, which can pose significant health risks to on-site sanitation workers. In this study, a quantitative microbial risk assessment (QMRA) framework based on Monte Carlo simulation was used to evaluate and compare the health risks for sanitation workers exposed to various pathogens in leachate. To this end, digital PCR (dPCR) was employed to measure pathogen concentrations in leachate from 33 MSW facilities across China. Results showed that the estimated median annual infection risks were highest for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), exceeding risks from other pathogens by 0-6 orders of magnitude. The fresh leachate from waste storage rooms, waste transfer stations, and incineration plants consistently showed higher annual infection and illness risks than landfill leachate. The probability of ungloved hand-to-mouth contact pathway was higher than that of the splashing and gloved hand-to-mouth contact pathways. Latex glove usage reduced the median annual infection risks of pathogens by 0%-90.3%. The sensitivity analysis revealed that the hourly frequency of hand-to-mouth contact and the volume of ingested leachate were the most influential parameters for the hand-to-mouth and splashing exposure pathways, respectively. Overall, the QMRA model of leachate for multi-scenario, multi-pathogen, and multi-pathway risks can aid waste management authorities in adopting effective risk mitigation strategies for sanitation workers.

Per- and polyfluoroalkyl substances (PFAS), including perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), are persistent, bioaccumulative and difficult to remove from wastewater using conventional treatment processes. Developing effective adsorbents that perform under complex wastewater conditions while supporting sustainable waste valorization is therefore critical. In this study, FeCl3-activated biochar was synthesized from municipal anaerobic digester sludge and evaluated for PFOS and PFOA removal from real municipal wastewater pre-UV secondary effluent. By converting sludge generated at the same wastewater treatment plant into an adsorbent for treating its effluent, this work demonstrates a closed-loop strategy for simultaneous PFAS mitigation and resource recovery. FeCl3-A-BC exhibited adsorption capacities of 54.9 mg/g for PFOS and 12.5 mg/g for PFOA, with high removal efficiency under real wastewater conditions. This performance was associated with its high surface area, hierarchical porosity, and Fe-/O-containing surface sites, while kinetic and isotherm modeling suggested surface-mediated monolayer adsorption. The material demonstrated good PFOA reusability over repeated regeneration cycles, while maintaining low leaching (<5.3%). The treatment reduced COD and TOC by up to 62% and 53%, respectively, demonstrating concurrent improvement in effluent quality and highlighting the potential of FeCl3-A-BC as an effective adsorbent within circular economy frameworks.

The importance of building-level plumbing systems in ensuring safe and reliable drinking water for end-users is increasingly recognized. However, biofilms forming on pipe walls present persistent public health risks. In particular, the dynamics of chlorine-resistant bacterial and fungal communities within these biofilms remain poorly analyzed and quantified under real-world conditions. Leveraging a large-scale building renovation campaign in a megacity in eastern China, we sampled biofilms from 24 residential buildings and assessed microbial resistance to chlorine disinfectants based on 16S rRNA and ITS amplicon sequencing. Elevated chlorine stress selected for chlorine-resistant taxa, while ammonia from monochloramine decay supported nitrifiers, deteriorating water quality. Although the number of bacterial-fungal links declined with rising chlorine (0 -0.96 mg-Cl2/L), proportions of positive associations remained stable (∼70%). Pipe materials and water supply regimes also shaped microbial communities, with polyethylene-lined steel (S-PE) pipes and dual-tank systems enriching genera such as Mycobacterium, which include potentially opportunistic species. Notably, S-PE pipes supported the highest microbial colonization reaching up to 289 CFU/cm2 (approximately an order of magnitude higher than SS). These findings underscore the need for sustained disinfectant management and informed material selection to mitigate biofilm-associated risks in aging urban drinking water infrastructure.

Energy conservation and carbon reduction in pumping systems at urban water supply plants are pivotal for achieving carbon peak and carbon neutrality goals.Over 90%of the electricity consumption in such plants is attributed to pump operation.However,current research faces three interconnected problems.First,static models based on theoretical characteristics fail to represent actual dynamic operating conditions accurately,leading to biased optimization baselines.Second,the coupling between intelligent algorithms and increasingly complex pump-optimization problems remains insufficient,often resulting in suboptimal solutions.Third,the evaluation system is fragmented,and assessment results are not effectively fed back into the optimization process to enable iterative improvement.These disconnections among the Model-Algorithm-Assessment components represent a core scientific challenge that hinders precise and effective decarbonization of water-supply systems.This review systematically examines recent advances in the application of intelligent algorithms to pump energy optimization.It first outlines the key elements of pump energy modeling,including operating-point derivation via curve fitting,objective function formulation,and constraint setting,which together provide a foundation for subsequent algorithmic optimization.It then categorizes and analyzes the application scenarios and technical features of traditional heuristics,data-driven methods,and hybrid algorithms.Literature analysis reveals that traditional heuristics remain the most widely applied algorithms but are prone to premature convergence under dynamic conditions,limiting their practical effectiveness.In contrast,emerging hybrid algorithms that integrate mechanistic models with data-driven techniques have demonstrated additional energy-saving potential:specifically,they can reduce energy consumption by 5%to 10%compared to traditional algorithms.A life-cycle perspective indicates that operational-phase carbon emissions account for 70%to 85%of the total footprint,while the manufacturing and disposal stages contribute 15%to 30%.This finding suggests that life-cycle assessment(LCA)could complement existing evaluation systems and underscores the need for a holistic assessment beyond mere operational energy use.Operational-phase metrics are also detailed,as they are essential for quantifying optimization effects and providing feedback to algorithms.The results indicate that the iterative synergy between intelligent algorithms and assessment systems is central to enhancing performance.To address the identified gaps,we propose a Model-Algorithm-Assessment tripartite framework that focuses on three interrelated aspects:(1)a sufficiently accurate and generalizable mathematical model;(2)intelligent algorithms that overcome algorithm-problem mismatch and achieve efficient optimization under complex,time-varying conditions;and(3)a life-cycle assessment system that provides comprehensive validation and broader evaluation dimensions for optimization strategies.This framework promotes the implementation of intelligent energy-saving and carbon-reduction technologies in urban water-supply plants.