Chloride (Cl‒) exerts complex and condition-dependent effects in heterogeneous catalytic ozonation (HCO), yet current mechanistic interpretations remain fragmented and often lack direct evidence. This Perspective rethinks Cl‒ effects across ozone availability, interfacial accessibility, and oxidation pathway regulation, while considering complexities under realistic saline conditions. A roadmap integrating comprehensive performance assessment, subprocess-specific validation, and application-oriented evaluation is proposed to enable more reliable interpretation of Cl‒ effects.
At high salinities, scaling of hydrophobic membranes by sparingly soluble salts causes flux decline and eventual membrane failure in membrane distillation (MD) technology. To overcome this, a large body of research has focused on chemically modifying existing hydrophobic membranes. While chemical modification of polyvinylidene-difluoride (PVDF) membranes by fluoroalkyl silanes improves resistance to mineral scaling, it involves multiple steps, harsh chemicals, and offers only marginal improvement. In this study, we present the possibility of engineering anti-scaling surfaces by tailoring the top membrane layer during non-solvent-induced phase separation (NIPS) itself. Contrary to common perception where scaling resistance mandates a rough superhydrophobic surface, our comparative studies reveal that PVDF membranes with a relatively smooth surface and low pore size effectively deter gypsum scale adhesion over other NIPS strategies. The same also outperformed commercial PVDF membranes of different average pore sizes (0.45 µm and 0.2 µm). Overall, while NIPS can be tailored to fabricate PVDF membranes with diverse morphologies, our findings demonstrate that using water as the non-solvent yields a membrane surface on which gypsum scales exhibit weak adhesion, allowing most deposits to be readily washed away.
Previous studies have described the potential emergence of treatment-resistant pathogenic E. coli in municipal sewage. This study sought to characterize a group of chlorine-tolerant Klebsiella pneumoniae species complex (KpSC) isolates based on antimicrobial resistance genes (ARGs), phylogenetic relationships to clinical strains, and other genomic traits associated with pathogenicity. Sewage samples collected from various wastewater treatment plants in Alberta, Canada, were treated with chlorine bleach at doses sufficient to reduce coliform bacteria by 4 log10 (i.e., 99.99% reduction), yielding 21 chlorine-tolerant KpSC isolates. Comparative genomics was used to characterize these chlorine-tolerant KpSC isolates against publicly available genomes from clinical and non-clinical KpSC strains. Chlorine-tolerant KpSC isolates belonged to 15 different sequence types and included Klebsiella pneumoniae, Klebsiella quasipneumoniae, and Klebsiella variicola, which are among the most common and clinically relevant KpSC phylogroups. Phylogenetically, chlorine-tolerant isolates from sewage were genetically diverse, clustering with clinical genomes according to species and sequence type, and reflecting significant strain diversity. Of the 21 chlorine-tolerant sewage isolates, eight resolved into a clade with one or more exclusively clinical genomes. Six isolates differed by < 80 single nucleotide polymorphisms from at least one clinical isolate, implying high genetic similarity to clinical strains. Virulence gene profiles were also remarkably similar, albeit the resistomes of the chlorine-tolerant sewage isolates lacked many relevant ARGs frequently detected in related clinical genomes. Collectively, these data suggest that chlorine-tolerant KpSC sewage isolates may be clinically important.
Solar evaporation technology holds profound significance as a sustainable and innovative solution to global freshwater scarcity, energy sustainability, and environmental remediation. This work presents a high-performance solar evaporator (PDAS) developed by functionalizing delignified almond shells with a photothermal coating. The systematic characterization confirms the successful formation of a cohesive, conductive PPy layer on the porous biomass substrate, which enhances light absorption and improves the photothermal effect. The designed evaporator PDAS achieves a high evaporation rate of 2.49 kg m−2 h−1, the photothermal conversion efficiency of 84.94%, and the water evaporation efficiency of 155%, under one-sun illumination, along with outstanding salt-resistance and long-term stability. When applied to seawater desalination and wastewater treatment, PDAS effectively removes salt ions, heavy metals, organic and pharmaceutical contaminants, producing freshwater that meets WHO drinking standards. The high-output performance of PDAS was revealed with the optimal open-circuit voltage of 288.9 mV and the power density of 16.78 mW/m2, at 3.5 wt% saline solution under one solar irradiation. This work demonstrates a sustainable strategy for transforming abundant biomass wastes into efficient solar evaporators for practical freshwater collection, wastewater treatment, and energy production.
Abstract Microplastics are widespread, yet methods to measure polymer type simultaneously and particles size smaller than 20 µm are limited, hindering toxicity assessment and policy formulations. We introduce a machine learning-assisted spectral flow cytometry approach that identifies six major polymers relevant to the environment and human health within the 5–100 µm range and allows projection in the 1–100 µm range. High-throughput, sensitive detection, straightforward sampling, and strong quality control make this technique suitable for routine monitoring of industrial and natural waters. Clear differences in microplastics levels and polymer composition were found between Lake Geneva, nearby rivers, and surface versus deep waters. With up to 97% of microplastics between 1 and 20 µm, data indicates a substantial underestimation of pollution. Consistent with laser-infrared measurements, concentrations of small-sized microplastics exceed previous reports in lake waters up to 656-fold. Environmental risk assessment of microplastics suggests that risk might be expected at some sampling sites.
Catalytic ozonation is often limited by inefficient ozone utilization at gas–liquid–solid interfaces and sluggish mineralization of refractory oxidation intermediates. Here, we report a facile and potentially scalable molecular foaming strategy to construct macroporous Mn–Ce binary oxides (HP-MnCeO) that integrate interconnected diffusion pathways with coupled Mn2+/Mn3+/Mn4+ and Ce3+/Ce4+ redox cycles. The optimized HP-70MnCeO exhibited enhanced deep oxidation capability, achieving 68% total organic carbon removal during carbamazepine ozonation, while only moderately accelerating parent compound degradation compared with ozonation alone. Compared with mesoporous counterparts, HP-70MnCeO delivered a 1.7-fold higher apparent reaction rate and promoted more efficient transformation of refractory intermediates, despite its lower surface area. It also accelerated ozone decomposition by 6–12 times compared with single-metal oxides, demonstrating improved ozone activation and utilization. Finite element simulations indicate that macropores enhance O3 and pollutant transport, while density functional theory suggests preferential O3 adsorption at Mn–Ce bridge sites. HP-70MnCeO maintained stable activity with negligible Mn leaching (0.01 mg/L) during cycling tests and enabled continuous-flow treatment of real wastewater. This work provides a strategy for designing macroporous multimetal oxide catalysts with enhanced mineralization efficiency for practical ozone-based water purification.
To address the intersecting challenges of solid waste, carbon emissions, and freshwater scarcity, this study presents a scalable methodology to upcycle discarded wooden furniture into high-performance 3D interfacial solar steam generators (ISSGs) via high-temperature gasification. Key findings demonstrate that the resulting biochar (BC-200) features a hierarchical porous structure, an expanded surface area (106.0 m² g-1), and ~90% broadband optical absorption. By integrating this biochar into a 0.5 cm-thick 3D cubic absorber with a balanced capillary wicking system, the device achieved an exceptional evaporation rate of ~1.9 kg m−2 h−1 and 127% solar-to-vapor efficiency under 1-sun irradiation, alongside a robust outdoor water yield of 12.59 kg m−2 day−1. Ultimately, this upcycling approach delivers a threefold climate mitigation impact—avoiding landfill emissions, directly sequestering carbon, and indirectly averting greenhouse gases—offering a practical pathway toward global carbon neutrality and decentralized water purification.
Energy-extracting wastewater reuse and waste-mining metal recovery have garnered significant attention for their contributions to advancing the circular economy. In this study, we design an economically viable zinc-based electrochemical neutralization desalination (ZEND) cell that simultaneously enables desalination of hypersaline industrial streams, energy generation, and hydrogen production from hazardous acidic and alkaline wastewaters without external energy input. When practical parasitic losses are considered, the system achieves an effective energy conversion efficiency of ~59%. This study also employs waste zinc metal as the anode, replacing expensive materials such as platinum and eliminating the need for an external hydrogen supply, which is typically required in conventional electrochemical neutralization cells. Experimental results demonstrate a remarkable peak power density of 37.9 mW∙cm−2 and stable operation at a current density of 70 mA∙cm−2 for over 18 h. The system also exhibits rapid desalination kinetics of 0.47 L·g−1·h−1, confirming its capability as a synergistic pretreatment step to reduce osmotic loads. A prospective screening-level cradle-to-grave life cycle assessment yielded a net GWP of approximately −52.0 kg CO2e m−3 of treated seawater for the current single-cycle case. A degradation-aware scenario sensitivity analysis reduced the modeled net credit to −30.1 and −8.5 kg CO2e m−3 under the base and conservative stress tests, respectively, demonstrating sensitivity to zinc use, component lifetime, output retention, and conditional co-product substitution. By integrating multiple functions with recycled materials, the ZEND cell emerges as a promising transitional technology for industrial wastewater reclamation and resource reuse.
In supervised data assimilation machine learning emulation, the training data contain targets produced by an existing data assimilation scheme, such as analysis increments. By contrast, data assimilation networks were recently proposed to learn the analysis operator while they are embedded in the forecast–analysis cycle: their only targets are the true trajectory and the observations thereof. They are therefore trained to produce a stable and accurate sequential estimator, rather than to reproduce the output of a prescribed data assimilation algorithm. Conceptually more fundamental, yet computationally more challenging, such learned data assimilation scheme was shown to achieve accuracy comparable to that of the ensemble Kalman filter when applied to low-order chaotic dynamics. Strikingly, the same accuracy can be reached with a single state forecast instead of an ensemble, hence bypassing the need to explicitly represent forecast uncertainty. In this study, we extend the investigation of such learned analysis operators beyond the preliminary experiments reported so far. First, we analyse the emergence of local patterns encoded in the operator, which accounts for the remarkable scalability of the approach to high-dimensional state spaces. Second, we assess the performance of the learned operators in stronger nonlinear regimes of the chaotic dynamics. We show that they can match the efficiency of the iterative ensemble Kalman filter, the baseline in this context, while avoiding the need for nonlinear iterative optimisation. Throughout the paper, we seek underlying reasons for the efficiency of the approach, drawing on insights from both machine learning and nonlinear data assimilation.
Arizona and other inland arid regions face mounting water-supply constraints as climate change, groundwater depletion, population growth, and Colorado River uncertainty reduce the reliability of traditional supplies. This paper compares two contrasting water-augmentation pathways for Arizona that span opposite ends of the infrastructure spectrum: Sea of Cortez desalination with long-distance conveyance, a mature centralized technology, and atmospheric water harvesting (AWH), an emerging distributed approach that captures water vapor from air near the point-of-use. Arizona provides a demanding test case because its inland location, distance from the coast, and limited brine-disposal options challenge both strategies. Sea of Cortez desalination is a long-term augmentation option requiring major infrastructure, binational governance, permitting, financing, and decades of implementation. In contrast, AWH is deployable for targeted applications but remains constrained by early readiness levels, high energy demand, limited production capacity, and uncertain life-cycle costs. Under screening assumptions, Sea of Cortez desalination and conveyance require 5.56 kWh/m³ with a lower-bound levelized cost of water of $2.0–$4.4/m³, whereas sorption-based AWH requires 116–1200 kWh/m³ but no conveyance or complex management costs. These contrasting pathways illustrate technology-readiness, economic, environmental, and governance trade-offs while broadening the concept of water importation to include the atmosphere as a natural conveyance pathway for harvesting water vapor near demand.
Chlorpyrifos pollution in aquatic streams has become a serious environmental concern due to its high toxicity and adverse effects on ecosystems and human health. In this study, continuous fixed-bed column adsorption of chlorpyrifos was studied using activated carbon synthesised from Magnolia champaca leaf biomass (MCAC). Experiments were conducted at pH 2 by varying the flow rate (Q), bed height (Z), and influent chlorpyrifos concentration (C0). Breakthrough curve analysis showed that C0 = 25 mg/L, Z = 1 cm, and Q = 6 mL/min yielded optimal adsorption performance, achieving an adsorption capacity (qe) of 105.81 mg/g. Among the conventional models, the Thomas, Adams-Bohart, and Yoon-Nelson models showed excellent agreement with high R2 > 0.99. Furthermore, several machine learning (ML) models, including SVR, XGB, RF, GB, CB, LGBM, and ANN, were used to predict Ct/C0 behaviour. Among these, the SVR model demonstrated superior predictive capability, with a test R2 value of 0.9968 and low RMSE and MAE values of 0.0182 and 0.0122, respectively. Feature importance analysis and SHAP-based interpretation identified contact time as the most influential parameter governing breakthrough behaviour. Overall, this study demonstrates a robust approach for optimising adsorption-based wastewater treatment using fixed-bed modelling and interpretable ML.
While the impact of future climate change on physical water availability has been extensively studied, the interplay with water quality and the associated impact on water scarcity-particularly the ensuing competition among sectors (domestic, irrigation, livestock, manufacturing, and energy) for clean water-is less well understood. Here we employed a globally applicable modelling framework to assess future cross-sectoral clean water gaps arising from competition for limited clean water resources, explicitly accounting for sector-specific water quantity and quality requirements under global change. Our results show that deteriorating water quality and insufficient water quantity will severely exacerbate future water gaps, exposing nearly 67% of the world's population to severe clean water gaps by 2100. As a result, cross-sectoral competition for clean water will greatly intensify, with disproportional impacts on the manufacturing and thermoelectric sectors, each facing a 20% increase in water gaps relative to their demands, primarily related to rising water temperatures. Overall, our findings underscore the need for integrated water management strategies that address both water quantity and quality to mitigate growing competition for clean water.
Membrane distillation is hindered by a persistent trade-off between vapor permeability and long-term wetting resistance, rooted in the tight coupling of surface skin consolidation with bulk demixing during conventional phase inversion. This work demonstrates that controlled deposition of low-inertia microdroplets onto the polymer dope surface prior to immersion establishes localized surface-tension gradients that drive Marangoni convection, effectively decoupling skin formation from bulk demixing through a kinetically programmable pathway. In LiCl-doped membranes, this intervention optimizes additive leaching and anti-scaling resilience, with the optimized membrane achieving 17.86 kg m−2 h−1 flux and 99.97% salt rejection. Remarkably, the same intervention applied to a pristine, additive-free system generates a fully interconnected, macrovoid-free architecture delivering 19.93 kg m−2 h−1 and 99.62% salt rejection, a ~ 1410% (1.32 kg m−2 h−1 to 19.93 kg m−2 h−1) flux enhancement over the control. These results establish droplet-mediated interfacial transport as a self-sufficient design principle, shifting fabrication from chemical modification to kinetically controlled decoupling of skin from bulk demixing.
Produced water (PW) from oil and gas operations contains complex salts, metals, hydrocarbons, and radionuclides that pose challenges for treatment and reuse. This study evaluated water quality and treatment performance of three pilot-scale multistage membrane treatment trains employing different nanofiltration and reverse osmosis configurations in the Permian Basin. Approximately 470 analytes were measured, of which 105 were detected in feeds, 70 in permeates, and 43 in post-treated desalinated PW. Despite variable feed salinity of 26.1–116 g/L, the systems removed ~99% salts, 56.3-99.4% (average 91.6%) total organic carbon, and 95–>99.9% radionuclides. Membrane rejection was strongest for multivalent ions and transition metals, while monovalent halides and low-molecular-weight neutral oxygenates compounds showed more variable removal. Post-treatment further reduced residual salinity, organics, ammonia, boron, and radiological risk in permeates to meet the current water quality criteria for fit-for-purpose applications. Membrane rejection mechanisms for inorganic and organic constituents in hypersaline PW were investigated and a tiered monitoring framework using surrogate parameters and indicator compounds was developed to support process control, treatment evaluation, and risk assessment. Overall, this study addresses key knowledge gaps in field-scale evaluation of membrane-based PW treatment and provides science-based evidence to support treatment design, monitoring strategies, and fit-for-purpose reuse.
The flow arriving at a wastewater treatment plant mixes municipal sewage, rainfall, soil moisture and groundwater, yet is routinely interpreted as if its composition were fixed. Despite the uncertainty this introduces to any case where the signal is used, from combined sewer overflow management to wastewater-based epidemiology, source-resolved composition is relatively underexplored. Here we introduce WWCompose, an empirical-conceptual model that recovers the dynamic contributions of rainfall, soil moisture and groundwater to daily influent, and apply it to approximately 2900 treatment plants across England using open national data. Predicted flows match observations out of sample (median held-out Kling–Gupta efficiency 0.64; 60% of plants above 0.6), with fitted parameters organising around hydrogeology, permeability and urbanisation. Non-municipal water is widespread: municipal flow averages 61% nationally, and at individual works may vary from 100% in dry weather to <5% during the wet conditions that often dominate periods of interest.
Biogenic sulfur is a promising electron donor for carbon-limited wastewater treatment, yet its practical application is hindered by the structural variability of its native organic coating. In this study, four post-treatment methods—EDTA, heating, enzymatic, and acid treatments—were applied to modify the coating. Moderate thinning via EDTA or heating treatment substantially enhanced denitrification kinetics, increasing nitrate removal rates by 1.9- to 2.4-fold and shortening the lag phase by over 60%. Mechanistically, this improvement results from a thinner organic coating that lowers the barrier to microbial access, and increased polysulfane content and crystallographic disorder, which together enhance intrinsic sulfur reactivity. In contrast, enzymatic treatment left the coating thick and continuous, while acid treatment resulted in a thin but disrupted surface with oxidation and preferential exposure of low‑reactivity crystal planes; both severely impaired performance. This study provides a mechanistic understanding of how the organic coating governs the bioavailability of bio-S0 and offers a promising post-treatment strategy to enhance its application in nitrogen removal technologies.
Abstract Composite fouling remains a major operational challenge for reclaimed water distribution systems. Conventional hydraulic flushing (HF) often fails over the long term not simply because of the amount of fouling accumulated, but because the deposits develop strong internal cohesion and tight interfacial adhesion that resist shear removal. Here, we present a non-chemical strategy that couples electromagnetic field (MF) with hydraulic flushing (HF) to regulate fouling detachability, defined here as the ease with which deposits are removed by shear, rather than merely attempting to reduce fouling mass. The approach was evaluated in a pilot-scale distribution system operated for 600 h under realistic reclaimed water conditions. The combination of electromagnetic field and hydraulic flushing (MF-HF) treatment substantially reduced total fouling accumulation (64.8–80.8%) and restored system flow rates (70.4–81.3%) relative to the control, outperforming electromagnetic field or hydraulic flushing applied individually. Multiscale analyses revealed that electromagnetic field conditioning altered the physicochemical state of composite fouling, including weakened mineral structures, reduced extracellular polymeric substances, and disruption of organic binding matrices. These changes collectively lowered fouling adhesion and rendered deposits more responsive to shear-induced removal during subsequent flushing, as independently supported by nanoscale adhesion measurements and flushing effluent characterization. The MF-HF strategy converted composite fouling from an adhesion-dominated state to a shear-responsive state, demonstrating that fouling detachability is a regulatable property rather than a passive consequence of fouling accumulation. This change led to markedly improved cleaning efficiency under identical hydraulic conditions and provides mechanistic support for low-energy, chemical-free fouling control in reclaimed water distribution systems.
Machine learning studies in water treatment often report high retrospective accuracy but rarely show whether models can support operational decisions. We analyse 423 full-text studies and a bounded six-plant wastewater-treatment scenario. Plant deployment (2.8%), real-time testing (5.2%), future-facing validation (18.2%) and uncertainty reporting (8.5%) remain uncommon. We propose an operation-aware evidence standard linking sensing context, validation timing, uncertainty and control role to deployment claims.
Abstract This work examines bioinspired 3D printed architectures for enhanced fog harvesting and atmospheric water recovery. It analyzes the mechanisms governing droplet nucleation, growth, transport, and drainage on bioinspired 3D printed micro geometries through various additive manufacturing routes. A normalized performance comparison is presented for various engineered architectures to evaluate water collection enhancement. Numerical modeling approaches, current challenges, and future directions for robust, high-performance water-harvesting systems are also highlighted.
Process-Heat-Supplied (PHS) technology has been proven effective in accommodating low-grade non-concentrating solar thermal energy and reduces the necessary supply temperature for traditional Air-Carried Evaporating Separation (ACES) cycles, enabling complete separation of brine at temperatures around 50 °C. Nevertheless, the thermodynamic mechanism underlying the ACES cycle coupled with PHS remains unelucidated, particularly the fundamental relationships between Gibbs free energy and entropy. Accordingly, this investigation conducts experiments on internal temperature variations of the redesigned system and performs simulation analysis of PHS-coupled evaporating separation process based on thermodynamic second-law. The results demonstrate that PHS effect essentially transforms binary Gibbs free energy model (air and droplets) of traditional processes into a tripartite model (PHS source, air, and droplets). The abundant free energy supplied by PHS source compensates for the inherent irreversible evaporation losses. This novel thermodynamic mechanism not only reduces the necessary temperature but also effectively enhances the exergy efficiency (ηex = 58.85%). Meanwhile, advantages of PHS have been demonstrated to extend beyond the brine. In feasibility milk drying experiment, this system continued to achieve separation whilst maintaining considerable evaporation efficiency. Furthermore, the solar-driven double-stage PHS-ACES system developed through this mechanism enables the cascaded utilization of energy and overcomes thermodynamic limitation of traditional evaporation (me-solar = 2.04 kg/(m2 h), GOR = 139.7%).
