Pulp and paper mill activated sludge (PPMAS) contains microbial biomass, lignocellulosic residues, and nutrients that make it a promising feedstock for the production of biodegradable polyhydroxyalkanoates (PHAs). However, alkaline pre-treatment required to solubilize sludge solids and increase substrate accessibility can also generate pre-treatment-derived inhibitory compounds that impair microbial carbon conversion. In this study, the formation of inhibitory compounds during alkaline pre-treatment of PPMAS was investigated, and a sequential detoxification strategy was developed to improve hydrolysate fermentability for PHA production by Cupriavidus necator NCIMB 11599. Simultaneous addition of calcium hydroxide with sodium hydroxide or ammonium hydroxide before sterilization showed limited sludge solubilization, with suspended solids decreasing from 15.0 to 11.9 g/L. In contrast, a sequential strategy consisting of NaOH pre-treatment (0.133 g/g suspended solids) followed by post-sterilization Ca(OH)₂ conditioning reduced suspended solids from 15.0 to 8.89 g/L. GC-MS and LC-MS/MS analyses showed that NaOH-treated hydrolysates contained several lignin- and pre-treatment-derived compounds, including vanillic acid, vanillin, syringaldehyde, benzene ethanamine, and fatty-acid derivatives, whereas concentrations of several detected compounds were lower following Ca(OH)₂ conditioning. Fermentation of the sequentially treated hydrolysate supplemented with glucose and minerals resulted in a biomass increase of 10.44 g/L, PHA content of 35.5 wt %, and PHA concentration of 6.86 g/L (0.095 g/L/h PHA productivity), representing a 2.4-fold increase in PHA content compared with NaOH pre-treatment alone. These findings demonstrate that maximizing sludge solubilization alone does not necessarily maximize subsequent biological resource recovery. Instead, hydrolysate quality should be considered together with organic-matter solubilization when designing pre-treatment strategies for sludge valorization.

Per- and polyfluoroalkyl substances (PFAS) are highly persistent in the environment, posing a significant challenge to their effective decomposition. Current degradation techniques relying on hydrated electrons (eaq-) typically necessitate anaerobic and alkaline conditions, which are too stringent for practical applications. Herein, we demonstrate for the first time that perfluorooctanoic acid (PFOA) can be spontaneously degraded during freezing under an oxygen-containing atmosphere. The degradation efficiency reaches 85.6% within 12 h at -20°C, without any foreign additives. The corresponding defluorination efficiency is approximately 9.9 times higher than that in unfrozen water. Mechanistic analyses reveal that the photodegradation of PFOA in frozen solutions is primarily driven by the generation of eaq-. Confocal Raman spectroscopy further confirmed that PFOA is concentrated and confined within the micron-scale unfrozen liquid layer (ULL, 2.57-8.33 μm) during freezing, triggering the freeze-concentration and freeze-confinement effects. These combined effects further lead to enrichment of PFOA and eaq- in the ULL, thereby enhancing the reactivity between them and thus accelerating the photodegradation process of PFOA. The general applicability of this mechanism was further verified for other PFAS. These findings demonstrate a novel strategy for the effective degradation of PFAS, unveiling an undiscovered transformation path of PFAS in natural environments.

Trifluoroacetic acid (TFA) is the most abundant per- and polyfluoroalkyl substance (PFAS) in aquatic environments, posing increasing threats to water quality and potential human exposure. However, its global risk profile and underlying drivers remain poorly understood. Herein, we integrate a CatBoost-based geospatial classifier achieving cross-validated F1 score of 0.70 and test-set sensitivity of 0.77 with an extended environmental multi-regional input-output (EE-MRIO) model to map global TFA exceedance risk in aquatic environments and trace its supply-chain drivers. We identify prominent TFA hotspots in the Yangtze River Delta, the Beijing-Tianjin-Hebei region, Western Europe, and previously unrecognized areas including the Arabian Gulf coast, with a screening-level estimate of ∼64.4 million people potentially affected by elevated source-water risk. EE-MRIO analysis further uncovers a marked mismatch between production and consumption responsibilities, indicating that part of the TFA-related water risk associated with textiles and chemicals is displaced through trade to satisfy final demand in North America and Europe, and parts of Asia. This redistribution was strongly sector-dependent, with chemical- and industrial gas-related transfers concentrated in a limited number of industrial hubs and major corridors, whereas textile-related transfers were dispersed across fragmented, multi-stage global production chains. Overall, this study provides a comprehensive supply-chain-informed perspective for mitigating TFA pollution at its source, demonstrating an approach to understanding the global drivers of environmental risks for other emerging contaminants.

The spatial variability of gas-liquid hydrodynamics in Biological Aerated Filters (BAFs) is critical for improving the accuracy of process models, yet it remains poorly documented under representative full-scale operating conditions. This study presents the first bed-resolved assessment (bottom and top zones) of gas holdup and porosity in a large pilot-scale BAF operated under field conditions. Both parameters were derived from pressure-drop measurements and related to local fouling induced by suspended-solids filtration and biofilm growth. Porosity ranged from 12 to 30% between the operating biofilter and clean-bed reference conditions, with a difference between top and bottom zones under biofiltration: 12-22% in the bottom zone and 16-25% in the top zone. Porosity was negatively correlated with local fouling. Gas holdup varied from 0.8-8.6% depending on fouling, and the superficial velocities of the mobile phases. The gas-to-liquid volume ratio exhibited a non-monotonic trend with porosity, increasing as porosity decreased above 28%, remaining stable between 28 and 15%, and dropping sharply below 15%, reflecting shifts in bubble hydrodynamics driven by porosity changes. Including fouling as an indicator of bed-structure changes greatly improved gas holdup predictions compared with correlations that omit this effect.

Floc images may enable faster and more objective interpretation of jar tests, but the reliability of image-based classification under year-round changes in raw-water quality remains uncertain. We developed a convolutional neural network (CNN) to assign floc images to three supernatant-turbidity classes and evaluated it using jar tests conducted twice weekly over ten months at a Japanese water purification plant, where raw-water temperature ranged from 5 to 27°C and turbidity from 2 to 425 NTU, including during two typhoons. A ResNet-50 model trained on background-normalized images collected 4-6 min after coagulant addition achieved 80.1% accuracy per image and 83.2% per jar test in jar-test-grouped five-fold cross-validation of 428 jar tests. Model selection repeated with jar-test-grouped inner validation gave nested estimates of 80.0% and 82.5%, and weekly campaign-blocked cross-validation gave 79.7% and 81.1%. In a preliminary external test at a downstream plant (16 jar tests), image-level accuracy was 68.7-77.8% without retraining. Errors were concentrated at low feed-water turbidity and low temperature, under which image descriptors showed smaller and fainter flocs, and in the intermediate class, in which misclassified jar tests had floc sizes similar to those of the neighboring class. Duplicate jar tests differed by a median of 0.11 NTU, and excluding boundary-ambiguous labels (36% of jar tests) increased jar-test accuracy to 94.9%. The model rejected 89.8% of inadequately coagulated jar tests; the false-acceptance rate of 10.2% fell to 2.1% when the least confident 37% of jar tests were referred to an operator. Image-based assessment is best used as a confidence-gated screening aid alongside the conventional jar test.

Identifying aerobic granular sludge (AGS) that is progressing toward instability before visible structural damage occurs remains a key challenge. Existing studies mostly compare stable and disintegrated granules at discrete endpoints, and conventional omics analyses focus on what changed rather than whether different molecular layers remain coordinated. We hypothesised that the transition toward granule instability is associated with progressive loss of functional coordination across genomic, proteomic, and metabolic layers. Aerobic granules were collected at five size classes (0.5, 1.0, 2.0, 3.5, and 5.0 mm) and analysed by morphology, SEM, reactor performance monitoring, metagenomics, metaproteomics, and metabolomics. Module-level coordination analysis and an inter-module coordination index (IMCI) were applied across the size gradient. At 3.5 mm, granules retained largely intact surface architecture and sustained bulk COD removal above 90%, yet metabolomic IMCI had declined continuously from 0.75 to 0.15 and proteomic IMCI had peaked at 2.0 mm before decreasing, revealing asynchronous coordination loss across molecular layers. A candidate pre-destabilisation window (2.0-3.5 mm) was identified where functional coherence had weakened but pronounced structural deterioration had not yet developed. Based on these findings, we propose hierarchical functional decoupling as a mechanistic framework in which cross-layer coordination loss marks the transition toward structural deterioration, providing an early molecular signature of incipient instability prior to macroscopic failure.

Radioactive iodide ([131/125]I[-]) removal from nuclear medicine wastewater remains challenging, as the current decay storage method requires months of passive storage and substantial infrastructure. Herein, we report the first application of the Kornblum oxidation reaction for synthesizing covalent triazine framework (KO-CTF) as robust hosts for AgCl nanoparticles toward rapid iodide capture. The KO-CTF was synthesized using p-methylbenzenesulfonate/p-xylylene dibromide as aldehyde precursors, which undergo controlled in situ oxidation via the Kornblum reaction to generate aldehyde intermediates for condensation with terephthalamidine. This neutral-condition strategy enabled precise kinetic control over aldehyde generation through leaving group selection, facilitating crystalline framework formation. AgCl nanoparticles were subsequently immobilized onto KO-CTF, yielding AgCl@KO-CTF composites that combine the chemical stability of the crystalline framework with the strong iodide-binding affinity of AgCl. The composite exhibited rapid adsorption kinetics, high capacity, and outstanding selectivity for I[-] in the presence of competing anions and simulated urine, confirming its applicability under clinically relevant conditions. Notably, up to 99.9% removal efficiency was achieved for trace-level radioactive [131]I[-] in simulated nuclear medicine wastewater. Density functional theory calculations further confirm that the triazine nitrogen atoms serve as the anchoring sites for AgCl and that I[-] preferentially binds at the AgCl sites rather than on the bare CTF framework, facilitating the subsequent ion exchange between Cl[-] and I[-] to form AgI. This work establishes Kornblum oxidation as a versatile strategy for constructing CTF while providing a new material for rapid radioiodine removal from medical liquid waste.

Iron-carbon (FeC) materials can be incorporated into floating structures for in situ nitrogen and phosphorus removal during remediation of surface water with low C/N ratio. Plant incorporation may alleviate nitrification inhibition and limited reactive interfaces associated with FeC materials alone, yet the effects on nutrient removal performance and the underlying mechanisms remain poorly understood. Herein, an ecological floating bed coupling aquatic plants with FeC materials (EFB-FeC) was constructed, with a plant-gravel system (EFB-G) as control. At C/N ratio of 2, EFB-FeC achieved TN and TP removal efficiencies of 93.77 ± 3.19% and 91.22 ± 7.48%, representing increases of 51.11 and 42.43% over EFB-G. FeC promoted autotrophic denitrification and phosphorus immobilization through micro-electrolysis, and enhanced plant photosynthetic activity and growth. More importantly, FeC-plant coupling reconfigured the root microenvironment, which was the key to overcoming nitrification suppression associated with FeC application alone and expanding reactive interfaces for nutrient removal. Specifically, compared with EFB-G, EFB-FeC showed higher abundances of nitrifying bacteria and nitrification-related genes on root surface. Meanwhile, genes involved in iron acquisition and utilization were also enriched on root surface of EFB-FeC, accompanied by the enrichment of autotrophic denitrifying bacteria. Besides, root iron plaque expanded the reactive interface for phosphorus immobilization. Mass balance analysis further revealed that the root microenvironment contributed more to nitrogen and phosphorus removal than direct plant assimilation. These findings advance the understanding of FeC-based EFBs by identifying root microenvironment as a key functional interface for enhanced nutrient removal during surface water remediation.

Hydrogen sulfide (H2S) accumulation in sewers threatens occupational safety, infrastructure integrity, and the urban environment. Although ventilation is operationally attractive, its multi-level mechanisms and the translation of laboratory-derived parameters to engineering conditions remain unclear. This study combined laboratory optimization with long-term field validation to evaluate the performance, mechanisms, sulfur-load characteristics, and end-of-pipe implications of enhanced ventilation in gravity sewers. Laboratory experiments using a simulated gravity-flow sewer reactor showed simultaneous decreases in gas-phase H2S and dissolved sulfide, accompanied by increases in dissolved oxygen, oxidation-reduction potential, and sulfate, together with decreased sulfate-reducing bacteria and increased sulfur-oxidizing bacteria, indicating that the control mechanism extended beyond gas-phase dilution. An S-equivalent assessment showed that 10 min air renewal time combined a lower gas-phase H2S-S exhaust rate with greater dissolved sulfide depletion, sulfate-S accumulation, and suppression of sulfide production. Field application in a 300 m sewer reach, with an equivalent air renewal time of 8-9 min, reduced mean H2S concentrations by 92.74% and 85.05% at two fixed monitoring points, while P90 reductions exceeded 84%. Over nearly 8 months of monitoring, time-above-threshold ratios for high-risk concentrations were markedly compressed, H2S levels declined progressively along the sewer, and concentrations within the ventilation zone remained systematically lower than outside the zone. The near-exhaust H2S-S load fell from 9.47 to a low of 0.28 g S/h, remaining below the initial operating-stage level during most of the monitoring period. These findings provide a mechanistic basis and practical parameter reference for engineering applications of enhanced ventilation in sewer H2S management.

Microplastics (MPs) act as vectors for disseminating antibiotic resistance genes (ARGs) across ecosystems, posing potential threats to environmental and public health. Seagrass meadows serve as vital ecotones between land and sea, where MPs pollution is widely recognized. However, plastisphere resistome (plastiome) in this ecosystem and its modulation by native phyllosphere and rhizosphere microbiomes remain poorly understood. Herein, MPs were in-situ exposed to seagrass meadows to investigate differences in resistome profiles of phyllosphere-associated (SL-MPs) vs. rhizosphere-associated plastisphere (SR-MPs). The potential health risk was evaluated by profiling ARGs, virulence factor genes (VFGs)-associated pathogenicity and mobile genetic elements (MGEs)-mediated motility. Results showed that SL‑MPs harbored more abundant putative pathogens, ARGs and VFGs than SR-MPs. Specifically, SL-MPs were dominated by WHO critical-priority pathogens Pseudomonas aeruginosa and Klebsiella pneumoniae, and enriched ARGs conferring multidrug resistance. Additionally, SL‑MPs exhibited greater potential health risks and more abundant high-risk ARGs (e.g., bacA and floR). These traits appeared to be primarily associated with the dense biofilms, high cell motility, pronounced reactive oxygen species response, DNA recombination and distinct membrane features of plastisphere beneath leaf canopy. Since phyllosphere-associated plastisphere can be readily dispersed by waves to other coastal ecosystems, it is necessary to integrate ecological connectivity into "One Health" frameworks.

Smart Water Distribution Systems (WDSs) are physical water networks whose pumps, valves, and tanks are operated through a digital layer of sensors, Programmable Logic Controllers (PLCs), and Supervisory Control and Data Acquisition (SCADA) systems. This connectivity improves operational efficiency but also exposes critical water infrastructure to cyber-attacks. Studying how to operate such systems resiliently requires simulators that reproduce both the hydraulic process and the control network. Existing cyber-physical testbeds, however, are largely passive: they model a single control architecture and record how an attack manifests, without letting an operator's defense logic act while the attack unfolds. We introduce WaCSim (Water and Cyber Simulation), an open-source cyber-physical co-simulation framework that addresses this gap. WaCSim couples the EPANET hydraulic engine with an emulated industrial control network (Mininet and MiniCPS), introducing two critical capabilities. First, it supports decentralized (PLC-to-PLC), centralized (SCADA), and hybrid control within a single framework. In hybrid mode, a PLC receives the same physical measurement via two independent paths, enabling attackers to target them differentially and exposing semantic conflicts that single-architecture tools cannot represent. Second, it establishes the defender as an active, in-loop actor, allowing researchers to embed custom control, detection, and conflict-resolution algorithms directly into the simulation loop to actively alter the hydraulic trajectory as an attack progresses. Through case studies, we demonstrate how WaCSim models cyber-attacks, evaluates defense mechanisms, and supports the development of intelligent control systems. These examples illustrate WaCSim's utility as a research and development platform for advancing the robustness, security, and operational intelligence of smart water networks.

Freshwater ecosystems contribute approximately half of global methane emissions; phytoplankton-mediated aerobic methane production is a key process resolving the "methane paradox" in oxic surface waters. However, the role of invasive cyanobacteria in aerobic methane production and its regulation by temperature remain poorly understood. Here, we combined 7‑month in situ field monitoring in a subtropical drinking water reservoir, controlled laboratory incubations, and transcriptomic sequencing to elucidate the mechanisms linking blooms of the invasive cyanobacterium Raphidiopsis raciborskii to freshwater methane release under climate warming. Field monitoring revealed unimodal temporal patterns for both surface R. raciborskii abundance and methane flux, with peaks co-occurring in August; surface methane flux was significantly positively correlated with R. raciborskii cell density (p < 0.001). Linear mixed-effects models identified water temperature, dissolved oxygen and electrical conductivity as key environmental drivers of methane emissions, while water temperature and total phosphorus predominantly regulate R. raciborskii growth. Incubation experiments confirmed 25 °C as the optimal temperature for R. raciborskii growth with methylphosphonate as the sole phosphorus source, whereas 30 °C maximized methane release. Transcriptomic analysis showed that warming upregulated methylphosphonate-degrading gene clusters and synergistically enhanced the expression of genes related to carbon fixation, methyl donor generation, nitrogen fixation and iron uptake, thereby boosting the aerobic methane production capacity of R. raciborskii. Our findings demonstrate that R. raciborskii is a key biogenic source of aerobic methane in freshwaters, with temperature as a key regulator, providing a scientific basis for assessing the ecological risks of R. raciborskii invasion and for managing cyanobacterial blooms and aquatic methane emissions.

Plants can exhibit phosphorus luxury uptake, absorbing several-fold more P than required under P-sufficient conditions. Harnessing this underutilized capacity helps to overcome substrate adsorption saturation and improve the phosphorus removal efficiency and sustainability of subsurface flow constructed wetlands (SFCWs). Here, we engineered a dense, fiber filter-like mat-structured root system to replace conventional inert substrates and systematically investigated its P removal performance, mechanisms, and engineering feasibility. From late spring to early winter, the root-mat system more than halved the effluent P compared with a conventional SFCW despite operating at an eight-fold hydraulic loading. Root-exudated aliphatic and carboxylic compounds scavenged the root-surface hydroxyl radicals, protecting the significantly more exudated histidine and lysine from being degraded. During the daytime, these amino acids coordinated with Fe3O4 and FeOOH in root-surface iron plaque via Fe(III)-COOH bonding, and their protonation formed a positively charged coating that increased P accumulation capacity by 77.8% through electrostatic attraction. The coordination enhanced the electron-transfer capacity of Fe by 62.9%, and increased nighttime Fe(III) reduction by 75%. The cleavage of Fe(III)-COOH released coordinated lysine and histidine, and their subsequent degradation at the iron plaque-water interface released electrostatically bound P, substantially elevating root-surface P supply and triggering plant luxury uptake. This pathway accounted for 91.2% of total P removal, with microorganisms assimilating the remainder. The root mat increased auxin and cytokinin synthesis, rebalanced their root-shoot allocation, and facilitated the growth of P storage sites. At the pilot scale, the root-mat system outperformed conventional SFCWs under 67% higher hydraulic loading, and seasonal stability can be improved using cold-hardy plants. Overall, these results advanced the current understanding and provide a scalable substrate-independent strategy that leverages plant luxury uptake to achieve efficient, economical, and sustainable P removal in SFCWs.

This study proposes an integrated deep-learning framework for rapid urban flood hazard mapping and damage prediction from compact rainfall descriptors. A simulation-based reference database linked synthetic rainfall scenarios with grid-based flood-depth maps generated by a validated rainfall-runoff and inundation model and category-specific damage indicators derived from damage assessment. For hazard mapping, a principal component analysis-integrated deep neural network predicted retained component scores and reconstructed full inundation maps through inverse transformation. For damage prediction, two pathways were compared: a hybrid pathway using surrogate-generated inundation maps and a latent-assisted deep neural network using principal component analysis-derived inundation features. Across real rainfall events, refinement reduced the mean root mean square error from 0.11 to approximately 0.09 m and increased the mean Nash-Sutcliffe efficiency from 0.48 to approximately 0.57, although further improvement remains necessary under complex observed conditions. The latent-assisted damage pathway achieved a mean normalized root mean square error of 0.02 and a mean coefficient of determination of 0.86 across ten damage indicators, outperforming the hybrid pathway. Overall, the framework reproduced dominant inundation patterns and provided reliable scenario-level damage estimates, offering a computationally efficient basis for rapid flood assessment and forecast-linked decision support.

Microalgae-driven photosynthetic hydrogen production has emerged as a promising approach to tackle the global energy crisis and reduce carbon emissions. Simultaneously, microalgae can remove phosphorus and nitrogen from wastewater while sequestering CO2 during hydrogen production. However, challenges such as the intrinsic oxygen sensitivity of hydrogenases and the relatively low hydrogen productivity remain major hurdles that constrain the process viability of microalgae for combined wastewater treatment and hydrogen production. A 3D-bioprinted algal-bacterial microreactor (ABMR) with a core-shell structure was constructed for simultaneous actual wastewater treatment and photobiological hydrogen production. 3D bioprinting was employed to achieve precise spatial segregation of Chlamydomonas reinhardtii in the core and Shewanella sp. in the shell, thereby promoting hydrogen production. The ABMR achieved effective pollutant removal (COD 98.3 %, TN 95.7 %, TP 94.0 %) and a cumulative hydrogen yield of 1681.5 μmol H2/mg Chl. Metabolomics revealed that algal-bacterial symbiosis promoted [Fe-Fe]-hydrogenase (HydA) maturation, strengthened photosynthetic carbon fixation, and activated pyruvate metabolism to supply additional electrons. Interspecies AI‑2 signalling and the stringent response regulator ppGpp were upregulated, enhancing metabolic coordination. The ABMR fixed CO2 at 53.8 g/(L·d) and achieved a net carbon emission of only -0.21 kg CO2/m[3], substantially lower than conventional processes such as A/A/O and oxidation ditch. This study demonstrated that the 3D‑printed algal‑bacterial microreactor is a promising green platform integrating wastewater treatment, renewable hydrogen generation, and carbon reduction.