Per- and polyfluoroalkyl substances (PFAS) persist in water systems and resist conventional removal methods such as activated carbon, which shows reduced efficiency with short-chain PFAS and in the presence of dissolved organic matter. Cyclodextrin-based polymers (CDPs) have emerged as sustainable alternatives, with competitive and selective PFAS adsorption capabilities. These polymers consist of glucose-based cyclodextrin (CD) units that can form host–guest inclusion complexes with PFAS pollutants. However, these binding interactions are not fully understood or quantified. We conducted an evaluation of machine learning approaches to model these host–guest interactions, providing insights into predictive capabilities for later CDP design. This study systematically compares molecular representations (Mordred, ECFP, ChemBERTa, UniMol2, etc.) across several machine learning architectures to predict CD-PFAS binding energies. First, we generated molecular embeddings of 3459 experimental host–guest pairs in the OpenCycloDB data set and 63 external CD-PFAS pairs. We then compared these embeddings via AlignedUMAP visualizations and nearest neighbor analyses. Next, we trained and evaluated predictive models using these embeddings on the OpenCycloDB data set, exploring the effectiveness of transfer learning and finetuning techniques. We finally tested model generalizability on two external experimental CD-PFAS binding data sets. All embeddings captured relevant chemical features, where UniMol2 differed most from other methods in embedding space analysis. Predictive models performed variably based on embedding choice and architecture, with the best-performing combination achieving moderate accuracy on the OpenCycloDB data set. Embeddings pretrained on large molecular data sets and finetuning the ChemBERTa embeddings both showed predictive improvements. However, external validation revealed limited generalizability to CD-PFAS complexes, highlighting domain shift challenges. Notably, leave-one-out cross-validation on the external PFAS-specific data indicated that training on in-domain data improved predictive performance at the cost of generalizability. This work demonstrates that molecular representation choice is critical for small-data host–guest binding prediction. However, domain shift between general CD data and specialized CD–PFAS applications remains a fundamental challenge, for which transfer learning and finetuning may offer potential solutions for future data-driven pipelines for CDP design and sustainable PFAS removal.

Mutual symbiosis of electroactive bacteria (EAB) and denitrifier may be the key for solving the refractory carbon and residual nitrogen in wastewater treatment plant effluent. However, its application is hampered by unclear co-metabolic model and uncertain electron transfer. Here, we achieved 3–5 times increase in refractory carbon degradation, 40 % improvement in denitrification, and 36.0 % decrease in N₂O emission by co-culturing P. aeruginosa strain GWP-1 and G. sulfurreducens. Such an enhancement is obtained by both refractory carbon co-metabolism and interspecies electron transfer (IET) between GWP-1 and G. sulfurreducens. Importantly, IET was quantified via isotopic approach, which revealed that G. sulfureducens supplies more electrons to GWP-1 when the system was fed with cellulose (0.071 mM) than glucose (0.012 mM). This study demonstrates that the residual refractory carbon and nitrogen in treated wastewater could be further converted by mutual symbiosis of EAB and denitrifiers, which paves a synergic way for pollution and carbon reduction.

Photochemical weathering and eco-corona formation through natural organic matter (NOM) adsorption play vital roles in the aggregation tendencies of nanoplastics (NPs) in aquatic environments. However, it remains unclear how photochemical weathering alters the adsorption patterns of NOM and the conformation of the eco-corona, subsequently affecting the aggregation tendencies of NPs. This study examined the effect of Suwannee River NOM adsorption on the aggregation kinetics of pristine and photoaged polystyrene (PS) NPs in monovalent electrolyte solutions. The results showed that photochemical weathering influenced the conformation of the eco-corona, which, in turn, determined NP stability in the presence of NOM. Hydrophobic components of NOM predominantly bound to pristine NPs through hydrophobic and π-π interactions, and extended hydrophilic segments in water hindered NP aggregation via steric repulsion. Conversely, hydrogen bonding facilitated the binding of these hydrophilic segments to multiple photoaged NPs, thereby destabilizing them through polymer bridging. Additionally, the stabilization and destabilization capacities of NOM increased with its concentration and molecular weight. These findings shed light on the destabilizing role of NOM in weathered NPs, offering new perspectives on environmental colloidal chemistry and the fate of NPs in complex aquatic environments.

Background: Denitrification in wastewater treatment is severely limited under low-temperature and low-carbon (“dual-low”) conditions, hindering sustainable nitrogen removal. Biofilm systems, though energy-efficient, suffer from reduced efficiency in such environments due to impaired interspecies electron transfer (IET). Granular activated carbon (GAC), a conductive mediator, offers potential to enhance IET between electroactive microorganisms (EAMs) and denitrifiers, yet its role in dual-low systems remains underexplored. This study investigates GAC’s capacity to optimize biofilm functionality and mitigate greenhouse gas (GHG) emissions under these constraints. Results: Under dual-low conditions (4–6°C, C/N = 4), GAC increased denitrification efficiency by 19.4–21.9% and reduced N₂O emissions by 10.6–22.9%. Metatranscriptomes revealed upregulation of denitrifying genes (e.g., nosZ) and electron transport pathways (e.g., omcB in Geobacter). FISH/SEM confirmed GAC-driven coacervates of EAMs and denitrifiers, linked by nanowires, enhancing direct electron transfer. Microbial diversity decreased, but functional redundancy improved, with Pseudomonas fluorescens and Geobacter sulfurreducens dominating. TOC removal rose under low temperatures, indicating enhanced carbon utilization. Conclusions: GAC fosters synergistic EAM-denitrifier partnerships, enabling efficient denitrification and GHG mitigation in cold and carbon-limited (“dual-low”) biofilm systems, advancing sustainable wastewater management.

There is a trend towards decentralized source separation (DSS) for wastewater treatment and resource recovery. An assessment framework is required to assess whether implementing a DSS treatment over a conventional centralized one is advantageous. This framework needs to account for the performance of the wastewater treatment plant (WWTP) and the effect that resource recovery has on closely-linked sectors such as food and energy production. A framework is lacking that covers the economic dimension, the circularity, the nature reciprocity of resource recovery and that can be applied to real-life cases. A novel WFE framework has been developed here to compare a conventional centralized and a DSS-based WWTP. This novel WFE framework contains assessment methods that are reproducible, and applicable to real-life cases. It also accounts for the local climatic conditions that determine irrigation water requirements. The comparison results revealed that the need to construct new DSS infrastructure leads to a lower economic efficiency of water treatment. Further, chemical-intensive treatment reduces the DSS's material resource circularity and efficiency. Using heat pumps increases the energy use of the DSS WWTP, causing a reduction in water treatment energy efficiency. However, the advantages of DSS show up in the freshwater and nutrient efficiency of food production as well as in the energy self-sufficiency of the WWTP. The novel WFE framework contains indicators specific to water treatment and the food production sectors to improve inter-sectoral communication. Also, including the nature reciprocity assessment can help demonstrate the issue with treated wastewater discharge, especially in arid regions with low stream flows. It can potentially help improve the acceptance of treated wastewater-based reuse. To conclude, the novel framework helps to assess real-life case studies in a more integrated and holistic way. It can help make decisions related to decentralization and source separation by simultaneously considering the water treatment, energy production, and food production sectors.

In this study, we investigated the use of BiVO₄/TiO₂-GO heterojunction photoanode in a PEC based AOP to simultaneously remove four organic micropollutants (OMPs): benzotriazole (BTA), carbamazepine (CBZ), caffeine (CAF) and diclofenac (DIC) from demineralized water. Each OMP had an initial concentration of 40 µg L⁻¹. Ultrasonic spray pyrolysis (USP) was used to deposit BiVO₄ and TiO₂-GO layers on fluorine doped tin oxide (FTO) electrodes. The heterojunction photoanode at an applied voltage of 1 V (vs Ag/AgCl) achieved simultaneous removal efficiencies of 100 % for DIC, 54 % for CBZ, 36 % for BTA and 33 % for BTA under simulated solar light. Compared to the pristine BiVO₄ photoanode, the heterojunction photoanode showed 50 % higher removal efficiency for BTA, CBZ and CAF. The reaction kinetics revealed that the first order rate coefficient for DIC removal was about nine times higher than that of CBZ and fifteen times higher than those of BTA and CAF. To assess scalability, a computational fluid dynamics (CFD) model incorporating the experimentally determined reaction kinetics was developed for a conceptually designed up-scaled PEC reactor. The model analyzed the effect of reactor design and fluid flow conditions on the removal of OMPs. Under turbulent flow conditions, enhanced removal efficiency was observed for all four OMPs, which was attributed to the effects of eddy diffusion and convective mixing. The optimized reactor design under turbulent flow condition achieved an 80 % removal efficiency for all four OMPs within 25 min under a light intensity of 400 W m⁻². The findings highlight the potential of BiVO₄/TiO₂-GO heterojunction photoanodes for efficient and scalable PEC water treatment, showing a promising approach for the elimination of OMPs from wastewater.

Optimising rainwater harvesting (RWH) systems’ design involves sizing the storage and catchment areas to enhance cost-effectiveness, self-sufficiency, and water quality indicators. This paper considers the design of RWH systems under long-term uncertainty in precipitation and demands. In this work, we formulate and solve a multi-objective stochastic optimisation problem that allows explicit trade-offs under uncertainty, maximising system efficiency and minimising deployment cost. We use the yield after spillage (YAS) approach to incorporate the physical and operational constraints and the big-M method to reformulate the nonlinear min\max rules of this approach as a mixed-integer linear programming (MILP) problem. By posing a risk averseness measure on efficiency as a conditional value at risk (CVaR) formulation, we guarantee the designer against the highest demand and driest weather conditions. We then exploit the lexicographic method to effectively solve the multi-objective stochastic problem as a sequence of equivalent single-objective problems. A detailed case study of a botanical garden in Amsterdam demonstrates the framework's practical application; we show significant improvements in system efficiency of up to 15.5% and 28.9% in the driest scenarios under risk-neutral and risk-averse conditions, respectively, compared to deterministic approaches. The findings highlight the importance of taking into account multiple objectives and uncertainties when designing RWH systems, allowing designers to optimise efficiency and costs based on their specific requirements without extensive parameterisation.

This mini review explores the potential of visible light–driven bismuth vanadate (BiVO₄)-based photoanodes for removing trace organic pollutants from water. It highlights the advantages of using BiVO₄-based photoanodes over conventional UV-driven photoanodes in water treatment. The mechanism of reactive species generation through water oxidation is discussed. The review also highlights the role of sulfate and sulfite radicals in enhancing pollutant degradation. Furthermore, it evaluates how heterojunction formation improves the removal efficiency of BiVO₄-based photoanodes by reducing charge carrier recombination. Limited research on BiVO₄-based photoanodes for the simultaneous removal of multiple organic pollutants at low concentrations (<1 mg L⁻¹) from real wastewater is identified as a key knowledge gap. Addressing this gap could advance the application of BiVO₄-based photoanodes in photoelectrocatalytic-based advanced oxidation processes.

Nitrate concentrations exceed standards in many drinking water sources. Solid carbon source (SCS) is usually used to increase the biological denitrification in waters with a low carbon‑nitrogen ratio. However, there is a lack of research on the enhanced denitrification in drinking water sources with nitrate exceeding limits by the introduction of SCS. In this study, a SCS composite was prepared using agricultural waste corncob and polybutylene succinate and the SCS carbon release performance, denitrification effect and potential chemical and biological risks were investigated via a series of batch and column experiments. The SCS composite presented a long-term, stable carbon release performance and good microbial utilization capability for denitrification: SCS composite has a sustained release capacity for over 28 days in dynamic waters. Short-chain fatty acids accounted for over 60 % of the released carbon, and predominant fluorescence compounds were protein organic compounds and soluble microbial metabolites. The introduction of SCS composite evidently improved bio-rope biomass and its denitrification effect. The removal percentage of NO₃⁻ by SCS reactor pretreatment reached 90.9 %, remaining stable within 28 days. The SCS pretreatment increased formation potentials of trihalomethanes, but formation potentials of haloacetonitriles with higher toxicity were effectively reduced, so the comprehensive toxicity risk of disinfection by-products was reduced. The SCS pretreatment has slight negative impact on drinking water biological stability only during the first 10 days, which needs attention. This study demonstrated that the prepared SCS composite has excellent carbon release performance and denitrification effect, and its chemical and biological risks were controllable.

The mechanisms and by-product formation of electrochemical oxidation (EO) for As(III) oxidation in drinking water treatment using groundwater was investigated. Experiments were carried out using a flowthrough system, with an RuO ₂/IrO ₂ MMO Ti anode electrode, fed with synthetic and natural groundwater containing As(III) concentrations in a range of around 75 and 2 µg/L, respectively. Oxidation was dependent on charge dosage (CD) [C/L] and current density [A/m ²], with the latter showing plateau behaviour for increasing intensity. As(III) concentrations of <0.3 µg/L were obtained, indicating oxidation of 99.9 % of influent As(III). Achieving this required a higher charge dosage for the natural groundwater (>40 C/L) compared to the oxidation in the synthetic water matrix (20 C/L), indicating reaction with natural organic matter or other compounds. As(III) oxidation in groundwater required an energy consumption of 0.09 and 0.21 kWh/m ³, for current densities of 20 and 60 A/m ², respectively. At EO settings relevant for As(III) oxidation, in the 30–100 C/L CD range, the formation of anodic by-products, as trihalomethanes (THMs) (0.11–0.75 µg/L) and bromate (<0.2 µg/L) was investigated. Interestingly, concentrations of the formed by-products did not exceed strictest regulatory standards of 1 µg/L, applicable to Dutch tap water. This study showed the promising perspective of EO as electrochemical advanced oxidation process (eAOP) in drinking water treatment as alternative for the conventional use of strong oxidizing chemicals.

The occurrence and removal of microplastics (MPs) in drinking water treatment plants (DWTPs) have been evaluated based on particle number, while the mass concentration and removal characteristics based on the mass of MPs, and especially nanoplastics (NPs), remain unknown. This study employed pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) to determine the mass concentration of MPs and NPs with different size ranges (0.01-1, 1-50, and 50-1000 μm) across the entire treatment process in a DWTP. The total polymers were measured at 9.63 ± 1.52 μg/L in raw water and 0.77 ± 0.05 μg/L in treated water, with the dominant polymers being polypropylene and polyethylene terephthalate. NPs (0.01-1 μm) accounted for only 3.2-5.3% of the total polymers, with an average concentration of 0.38 μg/L in raw water and 0.04 μg/L in treated water. Notably, NPs and sub-MPs (1-50 μm) demonstrated relatively low efficiency in the DWTP at 88.9 ± 3.2 and 88.0 ± 2.5%, respectively, compared with that of the large MPs (50-1000 μm) at 92.9 ± 0.3%. Overall, this study examined the occurrence of MPs and NPs, in a DWTP, emphasizing the significance of considering the mass concentration of MPs and NPs when assessing their pollution levels and removal characteristics.