Water Research最新文献

{"title":"Chemistry for Water Treatment under Nanoconfinement","authors":"Wanyi Fu, Ziyao Liu, Dan Li, Bingcai Pan","doi":"10.1016/j.watres.2025.123173","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123173","url":null,"abstract":"The global freshwater crisis, exacerbated by escalating pollution, poses a significant threat to human health. Addressing this challenge required innovative strategies to develop highly efficient and process-adaptable materials for water decontamination. In this regard, nanomaterials with confinement structures have emerged as a promising solution, outperforming traditional nanomaterials in terms of efficiency, selectivity, stability, and process adaptability, thereby serving as an ideal platform for designing novel functional materials for sustainable water treatment. This Review focuses on recent advancements and employment of nanoconfinement effects in various water treatment processes, emphasizing the fundamental chemistry underlying nanoconfinement effects. Also, the existing knowledge gaps related to nanoconfinement effects and future prospects for expanding their applications in diverse water treatment scenarios are discussed.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"46 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142991008","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":"Tracing the electron transfer behavior driven by hydrophyte-derived carbon materials empowered autotrophic denitrification in iron-based constructed wetlands: Efficacy and enhancement mechanism","authors":"Yuanyuan Fan, Shanshan Sun, Xushun Gu, Pan Yan, Yu Zhang, Yuanjun Peng, Shengbing He","doi":"10.1016/j.watres.2025.123169","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123169","url":null,"abstract":"Iron-based constructed wetlands (ICWs) displayed great potential in deep nitrogen elimination for low-polluted wastewater. However, the unsatisfactory denitrification performance caused by the limited solubility and sluggish activity of iron substrates needs to be improved in an eco-effective manner. To fill this gap, the bioavailability of iron substrates (iron scraps) affected by wetland biomass-derived carbon materials with potential conductivity were explored. Results indicated that the cumulative removal of TN in biochar-added ICW (BC-ICW) and activated carbon-added ICW (AC-ICW) increased by 29.04% and 22.96%, respectively. The carbon matrix of AC played the geo-conductor role to facilitate the rapid release of iron ions, as indicated by the higher TN removal efficiency of AC-ICW (45.36 ± 1.45%) at the early stage, while the reduced conductivity of AC negatively impacted the nitrogen removal. BC-ICW exhibited intensified denitrification potential, with higher TN removal capacity (52.08 ± 3.04%) and effluent Fe²⁺ concentration. Electroactive bacteria (EB) (<em>Geobacter, Desulfovibrio, Shewanella</em>, etc.) associated with extracellular electron transfer were enriched in BC-ICW, as well as the expanded niches breadth and improved microbial community diversity. The electron-shuttling effect of BC was mainly attributed to its oxygenated functional groups (quinone/phenolic moieties), which supported the electron transfer from EB to extracellular iron oxides, as evidenced by the increased Fe(III)(hydro)oxides bioavailability. Besides, biochar concurrently up-regulated the gene expression of electron transport chains/mediators and denitrification reductases, suggesting that BC boosted the active iron cycle and iron-mediated autotrophic denitrification in ICWs by accelerating intracellular and extracellular electron transfer. This work explored the electron transfer behavior of biomass-derived carbon materials coupled with ICWs to enhance denitrification, providing insights into the sustainable application of biomass derived carbon-assisted ICWs in tertiary treatment.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"31 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142990777","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":"Multi-modal learning-based algae phyla identification using image and particle modalities","authors":"Do Hyuck Kwon, Min Jun Lee, Heewon Jeong, Sanghun Park, Kyung Hwa Cho","doi":"10.1016/j.watres.2025.123172","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123172","url":null,"abstract":"Algal blooms in freshwater, which are exacerbated by urbanization and climate change, pose significant challenges in the water treatment process. These blooms affect water quality and treatment efficiency. Effective identification of algal proliferation based on the dominant species is important to ensure safe drinking water and a clean water supply. Traditional algae identification techniques, such as microscopy and molecular techniques, are time-consuming and depend on the expertise of the practitioner. This study introduced an artificial intelligence (AI)-based multi-modal approach, which is a recent advancement in techniques for improving algal identification by integrating algal images and particle properties. We employed multi-modal learning to integrate multiple data modalities, including algal images and particle properties acquired using Flow Cam, to provide robustness and reliability for classifying algal phyla, such as <em>Anabaena, Aphanizomenon, Microcystis, Oscillatoria,</em> and <em>Synedra.</em> This study involved acquiring images and particle modalities, which were conducted to integrate the dataset using early, late, and hybrid fusion methods. In addition, explainable AI approaches, including SHapley Additive exPlanations (SHAP) and gradient-weighted class activation mapping (Grad-CAM), were used to investigate the contributions of the algal image and particle modalities to the proposed multi-modal algorithm. The multi-modal algae identifier with late fusion achieved an average F1 score of 0.91 and 0.88 for training and tests related to identifying algal phyla, respectively. Furthermore, compared with other modalities, the image and particle modalities showed significant potential as complementary and reliable components of deep-learning algorithms for algal identification in the water treatment process. These findings can contribute to a safe and clean water supply by effectively identifying the dominant algal species in the water treatment process.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"57 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992501","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":"Interactions between iron mineral and low-molecular-weight organic acids accelerated nitrogen conversion and release in lake sediments","authors":"Wan Yang, Yunfei Liang, Taige Li, Wenjing Li, Xiaolin Liao, Bing Wang, Xiaozhi Wang, Shengsen Wang","doi":"10.1016/j.watres.2025.123174","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123174","url":null,"abstract":"Endogenous nitrogen (N) release from lake sediments is one of main causes affecting water quality, which can be affected by the presence of iron (Fe) minerals and organic matter, especially low-molecular-weight organic acids (LMWOAs). Although these substances always coexist in sediments, their interaction effect on N fate is not yet clear. In this study, the role and mechanisms of the coexistence of iron mineral (ferrihydrite, Fh) and LMWOAs, i.e. citric acid (CA) and galacturonic acid (GA) on the release and transformation of N in lake sediments were systematically evaluated via microcosm cultivation for 45 d. Results showed that the addition of Fh+LMWOAs significantly accelerated N mineralization and conversion in lake sediments, accompanied by increasing ferrous iron content and decreasing redox potential. Biotic pathways played more critical roles than abiotic oxidation pathways during this process, and Fh+LMWOAs strengthened cooperation among microbial species by forming complex topologies and higher positive correlations. Correspondingly, cellular functions, iron respiration, and N metabolism modules were increased. CA with high carboxyl content showed greater total nitrogen removal and metabolic abundance. The present findings facilitate understanding the synergies of iron minerals and organic matter on N fate and N biogeochemical cycling in lake sediments.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"1 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142992498","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":"Monitoring phycocyanin in global inland waters by remote sensing: Progress and future developments","authors":"Chong Fang, Kaishan Song, Zhaojiang Yan, Ge Liu","doi":"10.1016/j.watres.2025.123176","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123176","url":null,"abstract":"Cyanobacterial blooms are increasingly becoming major threats to global inland aquatic ecosystems. Phycocyanin (PC), a pigment unique to cyanobacteria, can provide important reference for the study of cyanobacterial blooms warning. New satellite technology and cloud computing platforms have greatly improved research on PC, with the average number of studies examining it having increased from 5 per year before 2018 to 17 per year thereafter. Many empirical, semi-empirical, semi-analytical, quasi-analytical algorithm (QAA) and machine learning (ML) algorithms have been developed based on unique absorption characteristics of PC at approximately 620 nm. However, most models have been developed for individual lakes or clusters of them in specific regions, and their applicability at greater spatial scales requires evaluation. A review of optical mechanisms, principles and advantages and disadvantages of different model types, performance advantages and disadvantages of mainstream sensors in PC remote sensing inversion, and an evaluation of global lacustrine PC datasets is needed. We examine 230 articles from the <em>Web of Science</em> citation database between 1900 and 2024, summarize 57 of them that deal with construction of PC inversion models, and compile a list of 6526 PC sampling sites worldwide. This review proposed the key to achieving global lacustrine PC remote sensing inversion and spatiotemporal evolution analysis is to fully use existing multi-source remote sensing big data platforms, and a deep combination of ML and optical mechanisms, to classify the object lakes in advance based on lake optical characteristics, eutrophication level, water depth, climate type, altitude, population density within the watershed. Additionally, integrating data from multi-source satellite sensors, ground-based observations, and unmanned aerial vehicles, will enable future development of global lacustrine PC remote estimation, and contribute to achieving United Nations Sustainable Development Goals inland water goals.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"9 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142991007","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 novel micromagnetic carrier-modified integrated fixed-film activated sludge system for simultaneous efficient removal of tetracycline and mitigation of antibiotic resistance genes proliferation and dissemination from swine wastewater","authors":"Yuan-Mo Zhu, Yi Xue, Kai Jin, Yongsheng Chen, Hongqiang Ren, Ke Xu","doi":"10.1016/j.watres.2025.123166","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123166","url":null,"abstract":"To address the challenge of antibiotic-containing wastewater, a novel micromagnetic carrier-modified integrated fixed-film activated sludge system (MC-IFAS) was developed for treating tetracycline (TC)-containing swine wastewater in this study. The magnetic effects of the MC significantly enhanced TC removal by improving TC biosorption and biodegradation in both the suspended activated sludge and the carrier-attached biofilm in the MC-IFAS. The increased electrostatic attraction and number of binding sites in both the activated sludge and the biofilm enhanced their TC biosorption capacities, particularly in the activated sludge. Additionally, the MC shifted microbial community assembly from stochastic to deterministic factors, amplifying the selection pressure induced by TC on the microbial community, thus enriching organic compound-degrading genera <em>Dokdonella</em> and <em>TM7a</em>; it also stimulated ammonia monooxygenase-mediated and cytochrome P450-mediated TC metabolisms and upregulated functional genes encoding lyases, transferases, hydrolases, and oxidoreductases- all of which enhanced TC biodegradation capacity in the MC-IFAS, particularly in the biofilm. While enhancing TC removal efficiency, the MC mitigated the proliferation and dissemination of antibiotic resistance genes (ARGs) by suppressing the abundances of ARGs hosts, the mobile genetic element <em>intI1</em>, and genes encoding ATP-binding cassette transporters and putative transposases. This study provides novel insights into the large-scale applications of magnetic field-enhanced TC removal strategies.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"31 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142990099","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":"Making waves: report your quality assurance and control (QA/QC) information when publishing analytical data","authors":"Gretchen L. Lescord, Adam T. Lepage","doi":"10.1016/j.watres.2025.123167","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123167","url":null,"abstract":"Quantitative analytical chemistry is an important tool for the aquatic sciences, turning environmental samples into meaningful data that support waterbody management and novel research. However, proper use of analytical data must include full and transparent reporting of quality assurance and control (QA/QC) information, something we have noted as consistently lacking in recent literature. Herein, we briefly discuss QA/QC theory and approaches, with the goal of informing interdisciplinary researchers who may not have received formal training in analytical labs. The core of this perspective is eight recommendations for effective QA/QC reporting in scientific products, including discussions on how and where to construct a transparent and concise QA/QC summary. We also discuss how to report detection limits and sample sizes - two commonly excluded parts of QA/QC reporting in our experiences. We end with a discussion of recent positive examples of effective QA/QC reporting in water science, as well as five points around the importance of QA/QC information for the broader aquatic science community (i.e., students, supervisors/mentors, data managers, and journal editors). Collectively, improved QA/QC reporting will extend the reach, usefulness, and longevity of our scientific data and research, enhancing the fundamental purpose of scientific publishing.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"37 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142991009","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":"Novel knowledge for identifying point pollution sources in watershed environmental management","authors":"Yuqing Tian, Zongguo Wen, Yanhui Zhao","doi":"10.1016/j.watres.2025.123168","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123168","url":null,"abstract":"Identifying point pollution sources (PPSs) is essential for enforcing penalties against illegal discharge behaviours that violate acceptable water quality (WQ) standards. However, there are existing knowledge gaps in understanding the association between the pollutants in water bodies and the pollutants emitted by PPSs, as well as how to utilize the knowledge to identify PPSs in water pollution accidents. This study developed a novel framework for identifying PPSs based on the conventional chemical pollutants and matrix calculations model (CCI-MCM). A two-step statistical analysis and correlation analysis extracted pollutant information in sewage wastewater from 256,025 PPSs and further developed the similarity matrix of industrial sewage wastewater indicators (SM-ISWI) and the correlation matrix of industrial sewage wastewater indicators (CM-ISWI). The SM-ISWI and CM-ISWI comprised 820 and 7790 pollution units, which could distinguish 41 industries and further identify the PPSs in these industries. Single factor index analysis and Pearson correlation analysis developed the WQ concentration matrix (WQ-CM) and WQ concentration correlation matrix (WQ-CCM), highlighting concentration anomalies of conventional chemical pollutants in natural water bodies and supply data for matrix calculation model to identify PPSs. The matrix calculation model with the Z_f, Z_c and Z_f-c scores indicated the relative probability of each PPS responsible for the water pollution. Four publicly reported water pollution incidents in China were selected as case studies to validate the effectiveness of the CCI-MCM in PPSs identification. The TE values in four case areas ranged from 25.0% to 53.9%, demonstrating a practical enhancement in identifying PPSs relative to random sampling identifying PPSs methods. The proposed CCI-MCM method provided specialized knowledge in understanding the association between the pollutants in water bodies and the pollutants emitted by PPSs, as well as how to utilize the knowledge to identify PPSs in water pollution accidents.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"30 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142991010","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":"Online monitoring of water quality in industrial wastewater treatment process based on near-infrared spectroscopy","authors":"Cheng Peng, Zeming Wu, Shudi Zhang, Boran Lin, Lei Nie, Weilu Tian, Hengchang Zang","doi":"10.1016/j.watres.2025.123165","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123165","url":null,"abstract":"Water quality monitoring is one of the critical aspects of industrial wastewater treatment, which is important for checking the treatment effect, optimizing the treatment technology and ensuring that the water quality meets the standard. Chemical oxygen demand (COD) is a key indicator for monitoring water quality, which reflects the degree of organic matter pollution in water bodies. However, the current methods for determining COD values have drawbacks such as slow speed and complicated operation, which hardly meet the demand of online monitoring. This article firstly proposed a novel quantitative analysis method based on NIR spectroscopy and multi-preprocessing stacking, successfully enabling real-time online monitoring of COD values during industrial wastewater treatment. First, the existing swarm intelligence algorithm was enhanced to optimize the hyperparameters of various base models. Next, multiple spectral preprocessing techniques were innovatively combined with a stacking strategy to construct multi-preprocessing stacking models, enabling comprehensive extraction of effective spectral information. Finally, various combinations of base models were evaluated, leading to the selection of the multi-preprocessing stacking model with optimal performance. The results indicate that the model achieves excellent predictive performance and strong generalization ability. For equalization tank samples, the R² and RMSE values were 0.8640 and 326.6845 mg/L, respectively. For secondary settling tank samples, the R² and RMSE values were 0.8798 and 15.1917 mg/L, respectively. Compared to traditional single and stacking models, the RMSE was reduced by at least 12.75% and 5.11%, respectively. In addition, the method has a relatively low modeling cost and offers interpretability. This study presents an efficient and straightforward solution for the online monitoring of COD values in industrial wastewater treatment, laying a solid technical foundation for the efficient management of industrial wastewater and the protection of water resources and the ecological environment.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"16 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989218","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":"Biokinetic soft-sensing using Thiothrix and Ca. Microthrix bacteria to calibrate secondary settling, aeration and N2O emission digital twins","authors":"Vince Bakos, Yuge Qiu, Marta Nierychlo, Per Halkjær Nielsen, Benedek Gy. Plósz","doi":"10.1016/j.watres.2025.123164","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123164","url":null,"abstract":"Enhancing climate resilience in activated sludge water resource recovery facilities (WRRFs) requires model-based and data-driven decision support and process optimization tools. Traditional data-driven learning methods are widely used for soft-sensor development due to e.g., their simplicity and high predictive accuracy. Unlike for mechanistic models, transferring machine-learning-based insights across systems is largely infeasible, thus hindering communication and knowledge sharing amongst practitioners. To harness the benefits of both approaches, this study introduces a mechanistic online soft-sensor (MOSS) developed to calibrate digital twins of secondary settling tanks (SSTs), aeration systems and nitrous oxide (N₂O) emission. MOSS integrates biokinetic models of filamentous microbial predictors to calibrate digital twins through meta-models (data-driven part), updated using offline settling column tests and amplicon sequencing data for microbial analysis. For the first time, this approach employs multi-filamentous-community predictors for dynamic calibration, i.e., <em>Thiothrix</em> and <em>Ca.</em> Microthrix. The effectiveness of the MOSS method is demonstrated using simulations of experimental data from a laboratory-scale WRRF.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"101 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989219","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}