Applied Water Science最新文献

{"title":"Interpretable machine learning for groundwater-level prediction incorporating pumping-well power consumption","authors":"Sheng-Wei Wang,&nbsp;Masaomi Kimura,&nbsp;Andreas Wunsch,&nbsp;Yen-Yu Chen,&nbsp;Wen-Chi Chen","doi":"10.1007/s13201-026-02935-6","DOIUrl":"10.1007/s13201-026-02935-6","url":null,"abstract":"<div><p>Groundwater-level forecasting is essential for adaptive groundwater management in regions where pumping pressure and climatic variability interact, yet direct abstraction records are often unavailable. This study developed an interpretable extreme gradient boosting (XGB) framework, selected for its suitability for nonlinear tabular prediction under limited-data conditions, to predict monthly groundwater levels at nine monitoring wells in the mid-fan region of the Choushui River alluvial fan, Taiwan, using observations from January 2013 to June 2023. Rather than converting electricity use into pumping volume through a fixed and potentially uncertain coefficient, monthly pumping-well power consumption was used directly as an operational predictor of withdrawal-related stress. Three input configurations were evaluated to distinguish the predictive roles of hydro-meteorological forcing, local pumping-related stress, and cross-well groundwater-memory information. Out-of-sample testing revealed substantial between-well variability under the baseline setting (RMSE = 0.341–3.254 m; MAE = 0.247–2.783 m), with markedly larger errors in several pumping-sensitive wells. Adding pumping-well power consumption and cross-well lagged groundwater-level information produced directional reductions in average testing MAE, but these improvements were substantial in magnitude rather than statistically conclusive across wells under the present sample size. Specifically, average testing MAE decreased by 24.04% from Case A to Case B and by a further 9.27% from Case B to Case C, although one-sided Wilcoxon signed-rank tests on paired well-wise testing MAE values indicated that the differences between Cases A and B and between Cases B and C were not statistically significant at the across-well level. In contrast, relative to a one-step persistence benchmark, the corresponding skill scores were 6.23% for Case A, 28.79% for Case B, and 35.39% for Case C, and the final model significantly outperformed persistence. SHAP analysis showed that lag-1 groundwater level was the dominant predictor, while pumping-related power-consumption variables provided substantial additional explanatory information in pumping-sensitive wells. These results indicate that operational power-consumption data can be integrated into an interpretable machine-learning framework to improve monthly groundwater-level prediction beyond simple persistence in data-scarce aquifers, while also providing a practical basis for month-ahead groundwater-risk screening and future research on human-induced groundwater stress.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"16 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-026-02935-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148682464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Synergistic remediation of arsenite and cadmium co-contaminated water using Fe-Mn oxides modified graphene oxide","authors":"Jizi Wu,&nbsp;Jing Yuan,&nbsp;Bin Lian,&nbsp;Feng Yuan,&nbsp;Qiuchan Wu,&nbsp;Qi Sun,&nbsp;Xin Tian,&nbsp;Jie Wang,&nbsp;Keli Zhao","doi":"10.1007/s13201-026-02920-z","DOIUrl":"10.1007/s13201-026-02920-z","url":null,"abstract":"<div><p>A novel graphene oxide composite incorporating iron (Fe) and manganese (Mn) (GO-FM) was synthesized by co-precipitating Fe and Mn oxides onto graphene oxide to remediate As³⁺ and Cd²⁺ contaminants in water. The spectrum of SEM-EDS and XRD analyses confirmed the successful integration of Fe₂O₃ and MnFe₂O₄ into the graphene oxide matrix. FT-IR characterization indicated increased number of –OH on GO-FM following the incorporation. The adsorption behavior of As³⁺ and Cd²⁺ varied with initial pH. Cd²⁺ reached equilibrium within 2 h, whereas As³⁺ stabilized after 24 h, with adsorption efficiency improving with temperature. Maximum adsorption capacities were recorded at 90.34 mg∙g^− 1 for Cd²⁺ and 141.69 mg∙g^− 1 for As³⁺. In the co-adsorption system, As³⁺ and Cd²⁺ interactions displayed both synergistic and antagonistic effects. At low pH (2–3), Cd²⁺ inhibited As³⁺ adsorption, demonstrating antagonism. At neutral pH (7), a synergistic effect was observed, where As³⁺ increased Cd²⁺ adsorption by 12.4%–429%, and Cd²⁺ elevated As³⁺ adsorption capacity by 1.7%–11%. This synergy was driven partly by electrostatic forces and ternary surface complex formation, but co-precipitation as the dominant process. These findings offer critical insights into the interaction dynamics of As³⁺ and Cd²⁺ on GO-FM, highlighting the potential for effective remediation applications.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"16 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-026-02920-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148587160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Effective removal of Hg(II) ions from aqueous solutions by functionalized metal–organic frameworks: adsorption models, thermodynamics, and Box-Behnken design optimization","authors":"Salhah H. Alrefaee,&nbsp;Roaa T. Mogharbel,&nbsp;Nadiyah M. Alshammari,&nbsp;Omaymah Alaysuy,&nbsp;Amal T. Mogharbel,&nbsp;Sahar Sallam,&nbsp;Fatmah M. Alkhatib,&nbsp;Nashwa M. El-Metwaly","doi":"10.1007/s13201-026-02913-y","DOIUrl":"10.1007/s13201-026-02913-y","url":null,"abstract":"<div><p>The pollution of groundwater with mercury Hg(II) poses a significant global risk and its elimination is of high importance. In this research, a new MOFs adsorbent was created through the post-functionalization of Th-MOF with tryptophan and used to selectively eliminate Hg(II) ions from aqueous solutions. The identification of the functionalized NH₂-Th-MOF was achieved through FTIR, FESEM, EDX, XRD, XPS, BET, and point of zero charge (pH_pzc). The absorption characteristics of the recently developed MOF adsorbent were examined through batch experiments. The highest observed adsorption capability was 792 mg/g at the most effective pH of 4. The study measured the impact of pH, dosage, temperature, time of contact and original concentration on the absorption procedure. The adsorption procedure was well suited to pseudo-second-order and Langmuir kinetic and isotherm models, respectively. The mode of adsorption was directed towards monolayer and chemisorption, through an adsorption energy of 33.9 kJ/mol. Additionally, the removal rate exhibited a direct relationship with the square of mercury ions concentration. Interestingly, our research uncovered that the complete adsorption–desorption procedure exhibited both an spontaneous and endothermic nature, as evidenced by the thermodynamic factors (ΔH°), (ΔS°), and (ΔG°). The NH₂-Th-MOF adsorbent proved to be easily regenerated with a decrease in removal rate of only 15.6% after six consecutive cycles. The chemical stability of the material was crucial for its reusability, as indicated by the indistinguishable XRD patterns before and after regeneration. Additionally, there were no variations in the functional groups and the FT-IR remained stable. The interaction among NH₂-Th-MOF and Hg(II) was thoroughly investigated, taking into account factors like H-bonding, π-π interaction, and electrostatic contact. Furthermore, compared to other competing metal ions, NH₂-Th-MOF exhibited exceptional discerning adsorption for Hg(II) ions. The Box-Behnken Design was used to optimize the adsorption findings.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"16 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-026-02913-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148538230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Impact of land use and land cover changes on streamflow dynamics using SWAT model in uMhlathuze River Catchment, South Africa","authors":"Mchunu Zanele,&nbsp;Demelash Ademe Malede,&nbsp;Vetrimurugan Elumalai,&nbsp;Peiyue Li","doi":"10.1007/s13201-026-02922-x","DOIUrl":"10.1007/s13201-026-02922-x","url":null,"abstract":"<div><p>Land use and land cover (LULC) change alters catchment scale streamflow and recharge dynamics which are modified by precipitation partition into surface runoff and baseflow processes. Water consumption has increased through industrialization, urbanization, agriculture, and changes in LULC are a major concern for sustainable water resource management of the catchment. This study aimed to investigate the impact of spatiotemporal LULC changes on streamflow and recharge dynamics using multitemporal Landsat imagery integrated with Soil and Water Assessment Tool (SWAT) within the uMhlathuze catchment. Supervised classification methods using maximum likelihood techniques were employed to categorize each LULC class in the Earth Resources Data Analysis System (ERDAS-2015) Imagine software for the years 2001, 2013, and 2023. LULC changes showed an increasing trend in built-up areas, forests, and barren land, by 30 km², 119 km² and 424 km^2, respectively from 2001 to 2023, while a decreased trend was observed in bushland, agricultural land, and water bodies by 427 km², 117 km², and 29 km². The SWAT model pereformed well, with a good correlation between simulated and observed streamflow. During the calibration period, the model achieved R² and NSE values of 0.65 and 0.61, respectively, while validation yielded a values of 0.71 and 0.62, respectively. The findings of the mean annual streamflow in the uMhlatuze catchment declined by 55% between 2001 and 2023. Surface runoff and water yield increased by 13% and 7.6%, respectively, these may attribute to a 46% growth in built-up areas in the study area, while groundwater and evapotranspiration decreased by 19% and 2.1%, respectively. The findings of this study suggest that streamflow dynamics and recharge are contlled by climate variability and LULC. The study recommends that policymakers integrate climate and LULC resilience strategies into urban expansion planning to minimize negative impacts on water resources and support sustainable water resource management.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"16 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-026-02922-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148538229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Groundwater inundation calculation and prediction based on a groundwater connectivity domain algorithm","authors":"Jianjun. Gan,&nbsp;Yanwen Xin,&nbsp;Chengyi Liu,&nbsp;Juanhua Gan,&nbsp;Fangzhou Liu,&nbsp;Chenghui Wan,&nbsp;Ping Zhou","doi":"10.1007/s13201-026-02871-5","DOIUrl":"10.1007/s13201-026-02871-5","url":null,"abstract":"<div><p>Groundwater inundation prediction and simulation are important for water resource management and geological disaster prevention in plain areas. The inundation height and extent are two important indicators for evaluating reservoir inundation. Although inundation models based on groundwater seepage theory can be used to calculate and predict the groundwater inundation process, it is difficult to establish reasonable models for complex geological structures and diverse land types. To improve the reservoir inundation calculation accuracy under complex geological conditions in plain areas, a new method of overlaying river-interstitial block data was proposed. The main idea of this method is that groundwater inundation can only occur in binary geological structures where the upper layer is a weakly permeable layer and the lower layer comprises a moderately permeable layer. This study focused on the development of the groundwater connectivity domain algorithm (GCDA) for calculation and prediction. The GCDA method utilizes drilling data and critically safe ultrahigh-definition three-dimensional geological models, integrates surface land use type digital elevation model (DEM) data, and constructs topological relationships for groundwater inundation connectivity searches. Adopting the river–land blocks between the main and northern branches of the Ganjiang River tail section project as an example, the application and effectiveness of this method were verified. The results showed that the GCDA method can be employed to calculate and predict reservoir inundation in plain areas and can capture groundwater inundation under a series of conditions representing different water levels. Moreover, with the use of the GCDA method, the groundwater inundation severity can be zoned. Overall, the GCDA method is a useful tool for groundwater inundation impact assessment studies because it provides satisfactory reliability in terms of seepage theory and data input operability.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"16 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-026-02871-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148428778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Health hazardous heavy metals separation from water resources using a modified polysulfone (PSf) membrane by covalent organic framework-polyamidoamine dendrimer as a novel nanocomposite","authors":"Ahmad Dehqan,&nbsp;Hosein Khoshsafar,&nbsp;Hasan Bagheri","doi":"10.1007/s13201-026-02910-1","DOIUrl":"10.1007/s13201-026-02910-1","url":null,"abstract":"<div><p>In this study, a novel COF/CS@PAMAM (CCD) dendrimer nanocomposite was synthesized and applied as a functional additive to enhance the performance of polysulfone (PSf) membranes. The CCD nanocomposite was prepared via a stepwise method, starting with covalent organic framework (COF) nanoparticles, followed by chitosan coating and PAMAM dendrimer grafting. FTIR, SEM, and EDS analyses confirmed the successful formation of CCD, revealing characteristic shifts in N–H functional groups, morphological evolution from spherical COF to tree-like CCD structures, and increased nitrogen content, indicating abundant hydrophilic amine groups. The CCD nanocomposite was incorporated into PSf membranes using the non-solvent induced phase separation (NIPS) technique. Membrane characterization demonstrated enhanced porosity, enlarged finger-like structures, reduced thickness, smoother surfaces, and increased hydrophilicity. Among various loadings, 0.50 wt.% CCD yielded the optimum membrane, exhibiting the highest water flux of 275.3 LMH (255% enhancement over bare PSf) while maintaining high BSA rejection (≈99%). Also, the modified membrane displayed superior antifouling performance and reduced total fouling resistance properties due to presence of the CCD nanocomposite. In addition, 0.50 CCD membranes achieved excellent removal efficiencies for heavy metals, including Hg²⁺ (99.3%), Pb²⁺ (98.6%), Th³⁺ (97.6%), As³⁺ (96.7%), Cr³⁺ (96.1%), and Ni²⁺ (95.6%), significantly higher than those of unmodified PSf membranes. The enhanced rejection of organic dyes and antibiotics was also observed, driven by electrostatic repulsion, hydrophobic/hydrophilic interactions, and specific binding of contaminants to functional groups in CCD. Comparison with the literature highlighted the effectiveness of amine-functionalized nanocomposites in improving membrane performance. Overall, this study demonstrates that incorporating CCD nanocomposites is a highly effective strategy for enhancing membrane performance, providing a versatile platform for next-generation water and wastewater treatment applications. The optimum 0.50 wt.% CCD dosage successfully balances permeability, selectivity, antifouling, and contaminant removal.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"16 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-026-02910-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148409073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Linking drinking water quality to customer complaints: a data-driven study in the barcelona metropolitan area","authors":"Pol V. Lamolla,&nbsp;Andrea Páez-Izquierdo,&nbsp;Félix Carrasco,&nbsp;Miquel Paraira,&nbsp;Marta Ganzer,&nbsp;Sergio Montes,&nbsp;Federico Botta,&nbsp;Diogo Pacheco,&nbsp;Raziyeh Farmani,&nbsp;Joana Tobella,&nbsp;Eduardo Martínez-Gomariz,&nbsp;Narciso Berberana,&nbsp;Manel Poch,&nbsp;María Molinos-Senante","doi":"10.1007/s13201-026-02882-2","DOIUrl":"10.1007/s13201-026-02882-2","url":null,"abstract":"<div><p>This study addresses the challenge faced by urban water utilities in translating technical water quality parameters into actionable insights on customer perception, using a data science approach in the Barcelona Metropolitan Area. Ten years of customer complaint data (2013–2023) from the water utility, Aigües de Barcelona, were integrated with corresponding water quality measurements. A comprehensive data pipeline prioritised high-coverage parameters for predictive analysis, including residual chlorine, conductivity, pH, and temperature. Exploratory Data Analysis revealed strong correlations among mineral-related parameters and identified residual chlorine and turbidity as the most distinctive variables in complaint-associated cases. Predictive modelling with Random Forest and XGBoost achieved consistent discrimination (AUC–ROC = 0.75 on a temporally held-out test set). Threshold optimisation enabled a recall exceeding 0.90, aligning with the operational objective of early detection of potential customer dissatisfaction. Interpretability analyses using SHapley Additive exPlanations confirmed that residual chlorine and conductivity, in interaction with temperature and pH, were the most influential drivers of complaint probability, exhibiting non-linear effects. These patterns were translated into actionable thresholds for operational improvement through heatmaps and logistic regression on discretised quartiles. Overall, the data-driven machine learning approach successfully links technical water quality variables to consumer dissatisfaction, providing actionable insights for utility management.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"16 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-026-02882-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148409072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Assessing future wheat evapotranspiration dynamics in the Kermanshah plain using CMIP6 and GEESEBAL: integration of SSP scenarios and machine learning-based projections","authors":"Neda Baboli,&nbsp;Maryam Hafezparast Mavaddat,&nbsp;Houshang Ghamarnia","doi":"10.1007/s13201-026-02915-w","DOIUrl":"10.1007/s13201-026-02915-w","url":null,"abstract":"<div><p>Climate change is recognized as an influential phenomenon on many natural processes, including the hydrological cycle. One of the key components of this hydrological cycle is evapotranspiration, which will be affected by climatic changes. Given the importance of evapotranspiration in water resource management and agricultural planning, the present study aims to investigate the effect of climate change on this process in the Kermanshah Plain, Located in the west of Iran. In this regard, using the GEESEBAL model, the amount of wheat evapotranspiration was calculated over a period of 10 years in the Kermanshah plain. Furthermore, to examine and forecast the effects of climate change, the MIROC6 and MRI-ESM2-0 models under SSP126, SSP245, and SSP585 scenarios were analyzed. Ultimately, utilizing Machine Learning methods, actual evapotranspiration for the period from 2025 to 2065 was estimated. Based on the results of the simulated models MIROC6 and MRI-ESM2-0, precipitation in future periods will have significant fluctuations. This study integrates remote sensing-based ET estimation with CMIP6 climate projections and machine learning techniques (Random Forest, XGBoost, and Gradient Boosting) to forecast future wheat evapotranspiration under different SSP scenarios. The results of investigation showed that in both models, temperature will increase and relative humidity will decrease. On the other hand, the MIROC6 model tends to predict a decrease in wind speed, whereas the MRI-ESM2-0 model predicts a slight increase across of all scenarios. The examination of the percentage changes in evapotranspiration using Random Forest, XGBOOST, and GBOOST methods indicated that the greatest decrease and increase will occur in March and November respectively, emphasizing the significance of the impact of climatic changes on evapotranspiration. Given the high values of R² and NSE, low MAE, and RMSE close to zero, it can be concluded that the performance of the Random Forest, XGBOOST, and GBOOST models in predicting actual evapotranspiration in the future has been satisfactory.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"16 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-026-02915-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148433421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Sustainable reverse osmosis thin-film composite membranes based on cellulose acetate and recycled acrylic fiber waste","authors":"Ahmed E. Abdelhamid,&nbsp;Alaa Eldesoky Elsayed,&nbsp;Eman AboBakr Ali","doi":"10.1007/s13201-026-02901-2","DOIUrl":"10.1007/s13201-026-02901-2","url":null,"abstract":"<div><p>Thin-film composite reverse osmosis (RO) membranes were developed using recycled acrylic fiber waste as a sustainable support material and cellulose acetate (CA) as the selective layer. Acrylic fiber wastes were transformed into nanofiltration support membranes by using the phase inversion technique, followed by dip-coating with CA/acetone solutions to form RO composite membranes. The effects of CA concentration, pore former (methanol) content, and evaporation time prior to immersion precipitation on membrane structure and RO performance were systematically investigated. Membrane morphology and physicochemical properties were characterized using Fourier transform infrared, scanning electron microscopy, X-ray diffraction, thermal gravimetric analysis and water uptake analysis. Desalination performance was evaluated using a 2000 ppm NaCl solution in a dead-end RO system at 15.5 bar. Increasing evaporation time enhanced salt rejection but reduced water flux due to the formation of a denser CA selective layer. The optimized membrane, prepared using 5 wt% CA with 5 wt% methanol and an evaporation time of 5 min, achieved high salt rejection (85–92%) with acceptable water permeability. The results demonstrate the feasibility of utilizing recycled acrylic fiber waste for the fabrication of efficient RO membranes, offering a cost-effective and environmentally sustainable approach for water desalination applications.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"16 8","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-026-02901-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148433485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Mitigation of high-strength pesticide wastewater through integrated biological–membrane treatment: mechanistic insights and water reuse potential","authors":"Ali Y. Alzahrani,&nbsp;Sahar. S. M. Alabdullah,&nbsp;Asma O. Obaid,&nbsp;Jawza Sh. Alnawmasi,&nbsp;Seraj O. Alzahrani,&nbsp;Ahmed M. Hameed,&nbsp;Ali Sayqal,&nbsp;Fathy Shaaban","doi":"10.1007/s13201-026-02822-0","DOIUrl":"10.1007/s13201-026-02822-0","url":null,"abstract":"<div><p>Chlorpyrifos contamination in industrial wastewater poses significant environmental and health risks due to its persistence, bioaccumulation, and neurotoxicity. Conventional treatment methods often cannot achieve complete removal, necessitating advanced, integrated approaches. This study shows that a sequential anoxic-aerobic system with MBR and NF polishing can stably treat unusually high-strength chlorpyrifos effluent (up to 1500 mg/L) from industrial wastewater. Anoxic pretreatment increases sludge settleability (SVI 115 to 69 mL/g) and minimises fouling. The combined process achieves ≥ 99.7% removal, including TCP attenuation, resulting in effluents that fulfill water reuse criteria. Pre-acclimatized sludge, developed over 90 days, demonstrated high tolerance to chlorpyrifos. The biological system, consisting of a 6 L anoxic tank and 60 L aerobic reactor, was optimized for hydraulic retention time (HRT), food-to-microorganism (F/M) ratio, pH, and contaminant concentration. Kinetic analysis yielded μ_max = 0.437 h⁻¹, K = 12.4 d⁻¹, Y_C = 0.49 g MLVSS/g CP, and k_d = 0.00381 d⁻¹. The anoxic/aerobic system achieved 90.6% removal at HRT 5 h and F/M 0.45 d⁻¹, outperforming a single aerobic stage (83.5%). Subsequent MBR polishing achieved up to 99.0–99.3% chlorpyrifos removal with permeate fluxes of 122.9 L/m²·h, while an additional NF step increased overall removal to ≥ 99.7% and provided permeate fluxes of 28–75 L/m²·h with flux recovery ratios above 99%. Anoxic pretreatment improved sludge settleability (SVI reduced from 115 to 69 mL/g) and significantly mitigated membrane fouling (flux recovery ratio: 99.05%). The integrated system consistently achieved ≥ 99.7% chlorpyrifos removal with stable operation, demonstrating its potential for sustainable treatment of high-strength pesticide-laden industrial effluents and supporting water reuse initiatives.</p></div>","PeriodicalId":8374,"journal":{"name":"Applied Water Science","volume":"16 7","pages":""},"PeriodicalIF":5.7,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s13201-026-02822-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148380535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}