Environmental Science: Water Research & Technology最新文献

As more data on virus concentrations in influent water from wastewater treatment plants (WWTPs) becomes available, establishing best practices for virus measurements, monitoring, and statistical modelling can improve the understanding of virus concentration distributions in wastewater. To support this, we assessed the temporal variability of norovirus, adenovirus, enterovirus, and rotavirus concentrations in influent water across multiple WWTPs in Switzerland, the USA, and Japan. Our findings demonstrate that the lognormal distribution accurately describes temporal variations in concentrations for all viruses at all sites, outperforming the gamma and Weibull distributions, which fail to capture high variability. However, notable differences in variability and uncertainty were observed across systems, underscoring the need for site-specific assessments. Using lognormal parameters, we identified optimal monitoring frequencies that balance cost-effectiveness and precision. For most sites, weekly monitoring was sufficient to estimate the annual average concentration of enteric viruses within a 95% confidence interval of 0.5 log₁₀. We further examined the mechanistic basis of the lognormal distribution, highlighting processes that drive its prevalence and shape the behavior of its upper tail. By integrating these insights, this study provides a statistical foundation for optimizing virus monitoring frameworks and informing public health interventions targeting wastewater systems.

Drinking water disinfection by-products (DBPs) are of significant concern due to their carcinogenic, teratogenic, and mutagenic properties, making real-time monitoring essential for ensuring water safety. However, the typically low concentrations of DBPs and the high cost and complexity of conventional detection methods have led researchers to increasingly turn to predictive modeling using easily measurable water quality parameters. This study systematically evaluates the feasibility of machine learning (ML) methods in predicting the concentrations of dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA): multiple linear regression (MLR), while computationally efficient, is limited by its linear assumptions and exhibits poor predictive performance (test set N₂₅ = 23–54%, R² = 0.353–0.640). Support vector regression (SVR), leveraging kernel functions, provided only marginal improvement (N₂₅ = 46–69%, R² = 0.442–0.595). The backpropagation neural network (BPNN) significantly enhanced prediction accuracy through flexible configuration of the hidden layer structure, number of nodes, and activation functions. For DCAA and TCAA, with one hidden layer and 15 nodes, BPNN outperformed both MLR and SVR (test set N₂₅ = 89%, R² = 0.850). Nevertheless, BPNN still suffers from inherent limitations, such as slow convergence due to a fixed learning rate and a tendency to converge to local optima caused by random initialization. To address these issues, this study introduced particle swarm optimization (PSO) to globally optimize the weights of BPNN, further increasing the prediction accuracy to over 98%. The results demonstrate that high-precision prediction can be achieved using only eight conventional water quality parameters, offering an economical, convenient, and reliable technical approach for monitoring DBPs in water supply systems.

Water disinfection using ultraviolet (UV) light is an emerging tool for improving access to safely managed drinking water in rural areas and low-resource regions. However, there is little information comparing existing UV systems in those contexts, towards improving the effectiveness of future UV systems. This work presents 19 case studies of small, decentralized UV water disinfection systems being used during the last 30 years to improve water access. The case studies cover a wide range of project types, including schools, hospitals, communities, households and healthcare facilities, spanning four continents. A variety of energy sources, water sources and social environments are also reviewed. In general, the use of UV immediately improved the microbiological quality of the water; however, long-term tracking of system performance is largely missing. UV system effectiveness was limited by several factors, including the potential for recontamination after UV disinfection, insufficient maintenance, and the absence of regulatory frameworks that allow the more widespread adoption of UV disinfection compared to more conventional disinfectants. This paper is intended to be supporting evidence for the utility of UV technologies for improving safe water access in low-resource settings, and to support practitioners in improving UV system design and implementation.

This study aimed to investigate the removal efficiency of (psycho)pharmaceuticals by ozonation and granular active carbon (GAC) in wastewater effluent, using risk as the metric for adequate removal instead of aqueous concentrations. Conventionally treated effluent was further treated with ozone or GAC until there was a 25% reduced UVA₂₅₄ absorbance, to allow for a direct comparison of the two treatment types. Samples were analysed using Ultra High-Performance Liquid Chromatography-Quadrupole Time of Flight-High Resolution Mass Spectrometry (UHPLC-qTOF-HRMS), where 20 (psycho)pharmaceuticals were quantified, and their risk was assessed using Predicted No Effect Concentrations (PNECs). A further assessment was performed using Quantitative Structural Activity Relationships (QSARs) for both parent compounds and their Oxidation Transformation Products (OTPs) to compare the relative toxicity of new species being formed by the ozone treatment. The total median removal efficiency across all compounds was 60 ± 3% for ozone in terms of concentration, yielding a 73 ± 2% reduction in terms of risk for the parent compounds, while the median removal efficiency for GAC is 57 ± 9% as expressed in concentration, and 46 ± 11% in terms of risk reduction. When factoring in the OTP toxicity, the median risk reduction for ozone flips to −274 ± 124%, indicating that there may be an increase in risk during ozonation. Pearson correlations on molecular descriptors indicated that ozone removal most strongly correlated with the number of activated aromatic rings (r = 0.65), while for GAC the topological polar surface area correlated strongest with removal (r = 0.54), therefore indicating that ozone and GAC target different types of molecules. The study demonstrates the merits of a risk-driven approach over concentration-based removal targets in current legislation, but also highlighted some drawbacks, especially with regards to data gaps and model accuracies.

Near-zero discharge of industrial wastewater is imperative due to the severe environmental risk and resource wastage, but a current integration process is still unavailable to treat and recycle acidic wastewater efficiently and stably. This study proposes an innovative integrated process coupling submerged membrane filtration with reverse osmosis-electrodialysis (RO-ED) for acidic wastewater treatment and resource recovery. The submerged membrane demonstrated exceptional performance in impurity removal, with the effluent below 0.18 NTU, effectively handling wastewater across diverse turbidity levels and pH values. The permeate flux of the submerged membrane remained above 65 L m⁻² h⁻¹ at a pressure of 0.20 bar. Moreover, a slight declining trend caused by membrane fouling appeared after 140 hours and then gradually stabilized. The RO-ED process was implemented in the separation and concentration of the permeate after short-process pretreatment. By regulating the operating pressure and concentration ratio, the synergistic process achieved 8 wt% acid concentration for reuse efficiently. Integration of the short-process pretreatment with the RO-ED process optimized the balance between treatment efficiency and acid recovery requirements. This innovative process significantly reduced acidic wastewater discharge and pollutant release while providing a feasible and sustainable approach for industrial wastewater valorization.

We assessed private-well drinking water (DW) at the point of use (i.e., tapwater, TW) within a rural Nebraska community around a state-closed biofuel facility, which used pesticide-treated corn seed as feedstock for ethanol production. Organic (485), inorganic (34), and microbial (13) analytes were assessed at 15 locations in June 2022, to evaluate the relative contribution of facility-consistent pesticides (seed-treatment fungicides and insecticides) to overall TW-contaminant exposures and predicted human-health risks. Thirty-three organics (12 pesticides) and 28 inorganics were detected, the former including the fungicide sedaxane, insecticide chlorantraniliprole, and multiple neonicotinoid insecticides/degradates, all consistent with seed treatment and respective biofuel-facility waste. Assessment of pesticides only at extant point-of-use (POU) treatment taps at three sites demonstrated complete elimination of all TW-pesticide detections. Based on detection of maximum pesticide concentrations in a home located downstream along a creek capturing facility runoff, pesticides only were assessed in January 2023 again at this home and at three adjacent locations, confirming results at the former and documenting decreasing TW-pesticide concentrations, including neonicotinoids, with increasing distance from the creek. Human-health DW benchmarks are not available for many detected pesticides, including the detected fungicide and insecticides, but precautionary screening levels were exceeded frequently due to multiple inorganics. The results indicate that exposures to multiple (median: 4.5; range: 1–7) co-occurring TW contaminants of potential human-health concern are common, warranting consideration of point-of-entry or POU treatment(s) throughout the community to reduce or eliminate unrecognized exposures to TW contaminants, including facility-associated pesticides in down-gradient locations. More broadly, results emphasize the importance of continued characterization of private-TW exposures, employing a environmentally informative analytical scope, to identify and mitigate risks of unrecognized exposures in private-well-dependent rural communities.

Atmospheric water harvesting (AWH) may present a sustainable solution to global water scarcity, particularly in arid regions where conventional water resources are limited. Sorption-based AWH (SAWH) using covalent organic frameworks (COFs) has emerged as a promising technology for low-humidity conditions (<40% RH), yet challenges in adsorption capacity, energy efficiency, and material stability persist. This review comprehensively analyzes the unique advantages of COFs for low-humidity SAWH, emphasizing their tunable pore structures, hydrophilic engineering, and exceptional cycling stability. We systematically compare COFs with conventional sorbents (e.g., hydrogels, salt composites) and demonstrate their superior performance, such as COF-ok (ortho-ketoenamine)'s working capacity of 0.4 g g⁻¹ at 30% RH and solar-driven regeneration at 45 °C. By elucidating water adsorption mechanisms (surface adsorption, micropore filling, capillary condensation) through isotherm analysis and molecular simulations, we establish design principles for optimizing COFs. Furthermore, we discuss innovative strategies, including topological design, composite systems, and post-synthetic modifications, to enhance low-humidity performance. Finally, we outline future directions, such as computational screening and device engineering, to bridge laboratory-scale achievements with practical applications. This work provides a foundational guide for advancing next-generation SAWH materials to address water scarcity in the most challenging climates.

Boron mud is a nearly zero-cost, abundant industrial waste characterized with multiple active components, strong alkalinity, and a large specific surface area. However, its application in sulfur-based autotrophic denitrification (SAD) processes to the simultaneous removal of NO₃⁻–N and PO₄³⁻–P has remained unexplored until now. In this study, a sulfur–boron mud autotrophic denitrification (SBMAD) system was constructed. Batch experiments demonstrated that the SBMAD system could achieve simultaneous NO₃⁻–N and PO₄³⁻–P removal, with significantly superior denitrification performance compared to the conventional sulfur–limestone (SLAD) system. The optimal parameters (HRT 2 h, temperature 22–26 °C) of the NO₃⁻–N and PO₄³⁻–P removal of the SBMAD system were determined by column experiments with high removal efficiencies of NO₃⁻–N (>99.45%) and PO₄³⁻–P (up to 96.27%). Pilot-scale experiment further validated the system's effectiveness, showing average removal efficiencies of 91.07% for NO₃⁻–N and 81.24% for PO₄³⁻–P at an HRT of 1 h, with effluent concentrations (1.31 mg L⁻¹ NO₃⁻–N and 0.17 mg L⁻¹ PO₄³⁻–P) consistently meeting the national discharge standard. Notably, incorporating boron mud significantly enhanced the NO₃⁻–N and PO₄³⁻–P removal effect of the SAD process, with Fe²⁺ from the boron mud contributing 6.90% to the NO₃⁻–N removal efficiency. These findings demonstrate that the SBMAD system is a promising technology for efficient simultaneous NO₃⁻–N and PO₄³⁻–P removal in low C/N ratio wastewater treatment.

The effective removal of toxic pollutants like m-cresol from wastewater remains challenging despite technological advancements. This study optimized total organic carbon (TOC) removal from m-cresol-contaminated wastewater using sodium percarbonate (SPC) oxidation through artificial neural network (ANN) and response surface methodology (RSM) modeling. TOC was selected as the optimization target due to its comprehensive representation of organic pollution levels. Six operational parameters were evaluated: initial pH, reaction time, SPC dosage, temperature, catalyst dosage, and initial m-cresol concentration. The ANN model demonstrated superior performance over RSM, achieving near-perfect R² values with significant improvement in predictive accuracy. Under optimal ANN-derived conditions (pH 2.3, 35.7 min, 2.9 g L⁻¹ SPC, 45.7 °C, 12.9 g L⁻¹ catalyst, 75 mg L⁻¹m-cresol), maximum experimental TOC removal reached 67.8%, significantly exceeding RSM's 38.2%. These findings demonstrate ANN's superior capability to model complex, nonlinear relationships in advanced oxidation processes, providing a robust optimization framework for enhancing wastewater treatment efficiency.

Indirect potable reuse (IPR) is increasingly adopted as a sustainable strategy for augmenting urban water supplies while maintaining environmental flows. However, the behavior of persistent trace contaminants such as per- and polyfluoroalkyl substances (PFAS) across the complete IPR treatment train, including natural attenuation processes, remains insufficiently characterized, particularly for emerging replacement compounds. This study presents a comprehensive two-year investigation (2022–2024) of 31 PFAS across a surface water-based IPR scheme in the Llobregat River basin (Spain), tracing their presence from the discharge of reclaimed water to the production of drinking water. Eight PFAS were consistently detected, with 6 : 2 fluorotelomer sulfonate (6 : 2FTS), a replacement PFAS, exhibiting the highest concentrations in reclaimed water (46.6 ± 4.8 ng L⁻¹) and measurable propagation downstream in river water (22.1 ± 2.5 ng L⁻¹). Modest increases were observed for PFHxA and PFOA, while most other PFAS showed negligible contribution from reclaimed water discharges. Within the advanced drinking water treatment train, reverse osmosis demonstrated >99% removal efficiency for all detected PFAS. In contrast, ozonation and ultrafiltration were ineffective, while granular activated carbon exhibited variable removal performance (13–99%) dependent on compound chain length. PFAS levels in finished drinking water were consistently below European regulatory limits. Seasonal fluctuations in ∑PFAS, PFOS, and PFBS were observed in river water but not in treated drinking water, indicating effective barrier performance. This work provides novel insights into PFAS fate within full-scale IPR systems and underscores the relevance of monitoring replacement PFAS in Mediterranean contexts. The findings support the development of targeted regulatory strategies and treatment optimization for safe potable reuse.