Water Research最新文献

{"title":"Tidal fluctuations induce accumulation and transformation of seawater Cr(Ⅵ) in coastal sediments","authors":"Xuanang Gong ,&nbsp;Gaoyang Xu ,&nbsp;Chengpeng Yuan ,&nbsp;Xiaoyun Xu ,&nbsp;Jun Wang ,&nbsp;Xinde Cao","doi":"10.1016/j.watres.2025.123382","DOIUrl":"10.1016/j.watres.2025.123382","url":null,"abstract":"<div><div>Tidal fluctuations play a critical role in regulating the transport and fate of contaminants in coastal environments. This study explored the dynamic redistribution of chromium (Cr) from seawater to sediment under tidal influence, as well as the accumulation and transformation of Cr in sediment through laboratory experiments and numerical simulations. After 35 tidal cycles, Cr concentrations in seawater declined rapidly and stabilized at approximately 27 % of the initial level. Notably, Cr migrated into sediment, ultimately accumulating in the bottom layer. Colloidal particles (350–800 nm) composed of clay minerals served as the primary transport vectors for Cr within sediment. During tidal fluctuations, 94.5 %–98.2 % of Cr(VI) in sediment was reduced to Cr(III), predominantly mediated by Fe(II) in the top sediment and by sulfur-reducing bacteria in the bottom layers. Consistent with experimental findings, numerical reactive transport modeling demonstrated that Cr(III) initially peaked in the middle sediment layer before stabilizing in the bottom layer, whereas Cr(VI) remained confined to the top layer. These findings elucidate tide-induced mobilization and natural reduction mechanisms governing Cr-contaminated seawater infiltration into sediment, offering novel insights into the fate of Cr discharged from coastal wastewater sources within seawater-sediment systems.</div></div>","PeriodicalId":443,"journal":{"name":"Water Research","volume":"278 ","pages":"Article 123382"},"PeriodicalIF":11.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A coupled optimized hedging rule-based reservoir operation and hydrodynamic model framework for riverine flood risk management","authors":"Ashrumochan Mohanty ,&nbsp;Bhabagrahi Sahoo ,&nbsp;Ravindra Vitthal Kale","doi":"10.1016/j.watres.2025.123443","DOIUrl":"10.1016/j.watres.2025.123443","url":null,"abstract":"<div><div>Long-term changes in reservoir inflow due to climate change and human interferences violate the assumptions of hydrologic stationarity, especially in the reservoir operation during high flood season for managing the downstream critical levee (DCL) sections from overtopping. Utilization of uncertain inflow forecast into a reservoir using the operating rule curve of certain forecast horizon reflects the challenges imposed by nonstationary conditions, downstream flood intensification with spatiotemporally distributed lateral flux and floodplain dynamics. Addressing these issues, this study develops four hierarchical frameworks considering single-stage hedging (1SH) and two-stage hedging (2SH) rules-based reservoir operation models optimized with Particle Swarm Optimization (PSO) and informed with rating curve uncertainty at DCL section. Further, these two frameworks are coupled with HEC-RAS-2D (H2D) hydrodynamic model to reduce the existing flood risk at DCL section. The efficiency of the advocated 1SH-PSO, 2SH-PSO, 1SH-PSO<img>H2D and 2SH-PSO<img>H2D are tested in the Rengali reservoir on the Brahmani River in eastern India. The inflow forecasts into the reservoir are simulated by the coupled SWAT-Pothole and Wavelet-based Bidirectional Long-Short-Term Memory (WBiLSTM) models forced with the bias-corrected GFS weather forecasts with up to 10 days’ lead-times. The results demonstrate that the best-performing 2SH-PSO<img>H2D framework-based reservoir operation could reduce the average peak flow depth at the DCL station by 21 % from the baseline with an average reduction in levee failure risk by 22.28 % leading to effective management of high flood events. This advocated framework could be used in other reservoir systems worldwide in reducing the downstream flood hazards through enhanced reservoir operation.</div></div>","PeriodicalId":443,"journal":{"name":"Water Research","volume":"279 ","pages":"Article 123443"},"PeriodicalIF":11.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of organic carbon-Mn oxide interactions on colloid stability and contaminant metals in aquatic environments","authors":"Qianqian Li, Debra Hausladen","doi":"10.1016/j.watres.2025.123445","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123445","url":null,"abstract":"Interactions between organic carbon and Mn oxides can lead to the formation of C-Mn colloids, which play a crucial role in regulating Mn mobility in the environment. Despite the significance of these interactions, however, the impact of C-Mn oxide interactions on the mobility of these colloids, particularly in the presence of contaminant metals, remains poorly understood. This study investigated the aggregation kinetics of C-Mn colloids formed through the reaction between humic acid and Mn oxides at three C:Mn molar ratios in the presence of divalent cations (Ca²⁺ and Mg²⁺). The introduction of organic carbon increased the stability (i.e., ability to resist aggregation) of C-Mn colloids compared to pure Mn(IV) colloids, as reflected in the higher critical coagulation concentration (CCC). As C:Mn molar ratios rose from 0.5 to 3 during colloid formation, the CCCs for the resulting C-Mn colloids increased from 3.6 mM to 7.2 mM Ca²⁺. However, at the highest C:Mn ratio (C:Mn=15), the CCCs decreased slightly to 7.0 mM Ca²⁺, with a similar trend observed for Mg²⁺. The stability of C-Mn colloids was affected by their characteristics, including electrostatic repulsion, surface functional groups, and Mn(II) content, which resulted upon reaction with dissolved organic carbon. Based on CCCs, C-Mn colloids were most stable in the presence of Mn²⁺ (6.9 mM), followed by Co²⁺ (5.9 mM), Zn²⁺ (2.7 mM), and Cd²⁺ (1.9 mM). The capacity of contaminant metals to destabilize C-Mn colloids followed the reverse order, with Cd²⁺ having the greatest destabilizing effect. Variations among the different metals were influenced by factors such as atomic radius, hydration shell, electronegativity, and electrostatic repulsion. These results provide new insights into the aggregation behavior of C-Mn colloids and the mechanisms controlling the fate and mobility of associated contaminant metals. This knowledge has important implications for understanding contaminant transport in natural waters and optimizing water treatment processes.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"3 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of reservoir size in driving methane emissions in China","authors":"Zilin Wang ,&nbsp;Meili Feng ,&nbsp;Matthew F. Johnson ,&nbsp;Aldo Lipani ,&nbsp;Faith Chan","doi":"10.1016/j.watres.2025.123441","DOIUrl":"10.1016/j.watres.2025.123441","url":null,"abstract":"<div><div>Reservoirs play a crucial role as sources of methane (CH₄) emissions, with emission rates and quantities varying widely depending on reservoir size due to factors such as surface area, water depth, usage, operational methods, and spatial distribution. Gaining insights into emission characteristics across different reservoir sizes can aid in designing and managing reservoirs to mitigate CH₄ emissions effectively. In this study, machine learning models were applied to estimate both diffusive and ebullitive CH₄ emissions across 97,435 reservoirs in China, spanning five categories of storage capacity. This comprehensive assessment covers nearly all reservoirs within the country, revealing total CH₄ emissions of approximately 5,414 Gg. Reservoirs &gt; 0.01 km³ are responsible for about 90 % of these emissions, primarily due to high diffusive flux rates and extensive surface areas. Elevated CH₄ diffusion in reservoirs &gt; 0.01 km³ is largely influenced by their thermal stratification and capacity for organic matter accumulation. Furthermore, these reservoirs are particularly vulnerable to climate warming, which could accelerate CH₄ emission rates more rapidly in larger reservoirs than in smaller ones (below 0.01 km³). Consequently, prioritising CH₄ management in reservoirs &gt; 0.01 km³ is imperative. Nevertheless, the high ebullitive flux of CH₄ in reservoirs &lt; 0.01 km³, linked to their shallow depth, highlighting the potential for significant CH₄ ebullition from smaller aquatic systems. Given large and small-ranged reservoirs' distinct spatial distribution patterns, targeted management strategies are recommended: project-level management for large reservoirs and basin-level approaches for smaller reservoirs.</div></div>","PeriodicalId":443,"journal":{"name":"Water Research","volume":"279 ","pages":"Article 123441"},"PeriodicalIF":11.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust biogas upgrading process via homoacetogens against ammonia and sulfide toxicities","authors":"Linjie Zhou,&nbsp;Mengxiong Wu,&nbsp;Jianhua Guo","doi":"10.1016/j.watres.2025.123440","DOIUrl":"10.1016/j.watres.2025.123440","url":null,"abstract":"<div><div>Using hydrogen derived from surplus green energy (e.g., solar and wind) to convert carbon dioxide to acetate via homoacetogens represents a promising technology for simultaneous biogas upgrading and biochemical production. However, effects of hydrogen sulfide and ammonia on activities of homoacetogens remain unknown, hindering their applications in biogas upgrading. This study investigated the impacts of ammonia and sulfide on homoacetogen-dominated microbial community for biogas upgrading process by combining short-term batch tests and long-term membrane biofilm reactor (MBfR) operation. Results showed that sulfide concentrations ≤ 2 mM TDS (total dissolved sulfide) increased H₂ and CO₂ uptake rates and acetate production both in the short-term and long-term tests. The relative abundance of <em>Acetobacterium</em> (typical homoacetogens) in the MBfR also increased from 30 % without TDS addition to 40 % with the addition of 2 mM TDS. These results suggest that sulfide addition (≤ 2 mM TDS) likely promoted the growth of homoacetogens, thereby enhancing the biogas upgrading efficiency. In terms of ammonia, results suggested that 0.5 g NH₄⁺-N/L has negligible impacts on the homoacetogens’ activities, while concentrations ≥ 1 g NH₄⁺-N/L significantly inhibited homoacetogens’ activities, resulting in negligible acetate production during the short-term tests. However, the long-term biogas upgrading performance remained unaffected by 1 g NH₄⁺-N/L. Moreover, with the simultaneous additions of typical concentrations of sulfide (2 mM TDS, equivalent to the H₂S concentration of 0.8 % in biogas) and ammonia (1 g NH₄⁺-N/L, equivalent to the NH₃ concentration of 0.1 % in biogas) in raw biogas, our MBfR still achieved high H₂ and CO₂ utilization efficiencies (95 % and 97 %, respectively) and acetate production rate (550 mg/L/d). These highlight the robustness of MBfR against ammonia and sulfide toxicities. Additionally, the injection of extra H₂ could alleviate the ammonia and sulfide inhibitions on homoacetogens with acetate production increased by 13–80 times. This provides a new strategy to enhance the tolerance of homoacetogens against high concentrations of hydrogen sulfide and ammonia. Collectively, our findings advance the understanding of the response of homoacetogens to ammonia and sulfide stress and facilitate the development of a resilient and efficient homoacetogen-mediated bioprocess for upgrading biogas to biomethane and chemicals simultaneously.</div></div>","PeriodicalId":443,"journal":{"name":"Water Research","volume":"279 ","pages":"Article 123440"},"PeriodicalIF":11.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DFT-assisted machine learning for polyester membrane design in textile wastewater recovery applications","authors":"Peng Liu ,&nbsp;Hangbin Xu ,&nbsp;Pengrui Jin ,&nbsp;Xuewu Zhu ,&nbsp;Junfeng Zheng ,&nbsp;Yanling Liu ,&nbsp;Jiaxuan Yang ,&nbsp;Daliang Xu ,&nbsp;Heng Liang","doi":"10.1016/j.watres.2025.123438","DOIUrl":"10.1016/j.watres.2025.123438","url":null,"abstract":"<div><div>Resource recovery from textile wastewater has attracted increasing interest because it simultaneously addresses wastewater treatment and maximizes the utilization of the residual dyes. Although polyester membranes have demonstrated great potential for textile wastewater recovery, tailoring high-performance polyester membranes remains a multidimensional challenge because of the complex nonlinear relationships between the membrane materials and their performance. Here we developed density functional theory (DFT)-assisted machine learning models that integrates DFT descriptors with fabrication and operation parameters to facilitate the generative design of polyester membranes. The developed machine learning model demonstrated the ability to accurately predict permeance and separation performance. The contribution analysis revealed that the fabrication parameters emerged as the critical factors influencing permeance, whereas the DFT descriptors played important roles in determining the dye and salt rejection. Additionally, optimal combinations of monomer, fabrication, and operation conditions were identified from a chemical space of 8,000 candidates using the developed model combined with Bayesian optimization, targeting dye/salt and dye/dye selectivity. Five polyester membranes were then fabricated under these identified combinations. These membranes surpassed the current performance upper bound and achieved efficient recovery of the dyes from textile wastewater. Overall, a feasible and universal machine learning model aimed at driving a paradigm shift in the inverse design of polyester membranes was developed.</div></div>","PeriodicalId":443,"journal":{"name":"Water Research","volume":"279 ","pages":"Article 123438"},"PeriodicalIF":11.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Understanding the role of biofilms and estimation of life-span of a tire derived aggregates-based underground stormwater treatment system” [Water Research 257 (2024) 121716]","authors":"Rajneesh Singh ,&nbsp;John S. Gulliver","doi":"10.1016/j.watres.2025.123390","DOIUrl":"10.1016/j.watres.2025.123390","url":null,"abstract":"","PeriodicalId":443,"journal":{"name":"Water Research","volume":"278 ","pages":"Article 123390"},"PeriodicalIF":11.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"COVID-19 impacts on characterization of N-nitrosamines and their precursors during transport in sewer systems","authors":"Bo Zhao ,&nbsp;Jing Zhou ,&nbsp;Norihide Nakada ,&nbsp;Masaru Ihara ,&nbsp;Yuqing Liu ,&nbsp;Yong Jie Wong ,&nbsp;Ryo Honda ,&nbsp;Hiroaki Tanaka","doi":"10.1016/j.watres.2025.123439","DOIUrl":"10.1016/j.watres.2025.123439","url":null,"abstract":"<div><div>During the COVID-19 outbreak, N-nitrosodimethylamine (NDMA) and N-nitrosomorpholine (NMOR) and their specific precursors (N,N-dimethylformamide [DMF] for NDMA and morpholine [MOR] for NMOR) were widely detected in sewerage systems of an urban area, in which chlorine-containing disinfectants were discharged with effluent of hospitals, etc. However, little is known about the effect of chlorine influx on formation and distribution of NDMA and NMOR in sewer systems in a sudden major public health event. We investigated the spatiotemporal patterns of NDMA, NMOR, DMF and MOR in influents of sewage treatment plants (STPs), as well as its upstream sewer sites during the COVID-19 pandemic. During the pandemic, there was a significant decrease of industry-related NMOR and DMF, however, with an increase of concentration (up to 243 ng/L) and detection frequency for NDMA in influents of the biggest STP in Kyoto Prefecture. Moreover, it was found that NDMA reached a maximum of 187 ng/L with 57 % detection frequency, while NMOR reached a maximum of 101 ng/L with 51 % detection frequency in the sewer systems connecting to all the STPs for service area during the pandemic. Especially, during the pandemic, concentration (median value) of NDMA increased from 40.9 ng/L with 42 % detection frequency in 2020 to 72.5 ng/L with 77 % detection frequency in 2021, which was coincident with the change of infected population. In addition, this research clearly exhibited the possibility that unintentional chlorination and nitrosation of precursors formed NDMA and NMOR in sewer systems influenced by COVID-19 pandemic. The NDMA formation was ranked according to increased concentration (median value) as follows: addition of ClO⁻ (669 ng/L) &gt; addition of NO₂⁻ (138 ng/L) &gt; without addition (34.3 ng/L), while additional ClO⁻ and NO₂⁻ did not significantly increase NMOR formation probably caused by low existence of NMOR precursors (e.g., MOR) in raw sewage. Therefore, it is necessary to make an urgent attention on environmental issues caused by high-dose chlorine-containing disinfectants residue, because increased byproducts induced by disinfectants in raw sewage caused higher risk during the future pandemic by unexpected pollution from insufficiently treated sewage (e.g. combined sewer overflow and primary effluent bypass discharge) to receiving water bodies.</div></div>","PeriodicalId":443,"journal":{"name":"Water Research","volume":"279 ","pages":"Article 123439"},"PeriodicalIF":11.4,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spectral physics-informed neural network for transient pipe flow simulation","authors":"Vincent Tjuatja,&nbsp;Alireza Keramat,&nbsp;Mostafa Rahmanshahi,&nbsp;Huan-Feng Duan","doi":"10.1016/j.watres.2025.123427","DOIUrl":"10.1016/j.watres.2025.123427","url":null,"abstract":"<div><div>Accurate wave propagation models are essential for effective monitoring and automated localization in water supply pipelines. The recently-established Physics-Informed Neural Networks (PINNs) can enhance the wave analysis and reduce uncertainties by integrating mathematical models with sensor data. However, the application of PINN in modelling transient waves remains limited to the time domain, though frequency domain models are preferred for system identification due to their sensitivity to anomalies. This paper develops a PINN-based water hammer model in the frequency domain referred to as Physics-Informed Complex-Valued Neural Network (PICVNN) to enhance the wave prediction for monitoring and assessment applications. Results indicate that the proposed model can effectively reconstruct transient pressures generated using analytical solutions, even in the face of uncertainties including input parameters, mathematical models, and unknown leaks. PICVNN is also compared with two benchmark models of classical complex valued neural network (CVNN) with the same and a doubled number of observation points. PICVNN is found to outperform both CVNN models in terms of accuracy. Unfortunately, this accuracy comes at a cost as PICVNN requires a significantly longer training time than the classical CVNN. Regardless, the developed PICVNN model serves as a reliable signal fusion tool, effectively integrating diverse sensor data to enhance accuracy and reliability.</div></div>","PeriodicalId":443,"journal":{"name":"Water Research","volume":"279 ","pages":"Article 123427"},"PeriodicalIF":11.4,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143546263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum to “Whole genome sequencing of the novel polyvalent bacteriophage Malk1: A powerful biocontrol agent for water pollution” [Water Research 276 (2025) 120/ 123259]","authors":"Mohamed Ibrahim Azzam ,&nbsp;Mohamed A. Nasr-Eldin ,&nbsp;Fafy A. Mohammed ,&nbsp;Kawthar A. Omran","doi":"10.1016/j.watres.2025.123391","DOIUrl":"10.1016/j.watres.2025.123391","url":null,"abstract":"","PeriodicalId":443,"journal":{"name":"Water Research","volume":"278 ","pages":"Article 123391"},"PeriodicalIF":11.4,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}