Water Research X最新文献

筛选
英文 中文
Soil-derived dissolved organic matter in Inland wetlands along A temperate river: Insights from spectroscopic characteristics coupled with machine learning methods
IF 7.2 2区 环境科学与生态学
Water Research X Pub Date : 2025-03-31 DOI: 10.1016/j.wroa.2025.100339
Wenliang Ju , Dengke Ma , Meilian Chen , Jordi Sardans , Biao Zhu , Ji Liu , Ji Chen , Josep Peñuelas , Xiang Liu
{"title":"Soil-derived dissolved organic matter in Inland wetlands along A temperate river: Insights from spectroscopic characteristics coupled with machine learning methods","authors":"Wenliang Ju ,&nbsp;Dengke Ma ,&nbsp;Meilian Chen ,&nbsp;Jordi Sardans ,&nbsp;Biao Zhu ,&nbsp;Ji Liu ,&nbsp;Ji Chen ,&nbsp;Josep Peñuelas ,&nbsp;Xiang Liu","doi":"10.1016/j.wroa.2025.100339","DOIUrl":"10.1016/j.wroa.2025.100339","url":null,"abstract":"<div><div>Dissolved organic carbon (DOC) is a critical component of wetland carbon cycling, yet the sources and characteristics of soil-derived dissolved organic matter (DOM) that influence DOC dynamics in inland river wetlands remain poorly understood. This study investigated the spatial variations in DOM sources and composition, and their influence on DOC dynamics in 12 river wetlands across China's second-largest inland river basin, the Heihe River Basin. Using UV–Vis spectroscopy and fluorescence excitation-emission matrix (EEM) spectroscopy coupled with parallel factor analysis (PARAFAC), we found that wetland soil DOM predominantly consisted of protein-like components and had low aromaticity and hydrophobicity. Protein-like fluorescence was more pronounced in downstream wetlands than in midstream and upstream wetlands, and it was higher in subsoil compared to topsoil. Spectroscopic indices indicated low aromaticity and humification but high bioavailability, particularly in downstream wetlands. Machine learning analysis revealed that DOM spectral characteristics had a stronger direct influence on DOC dynamics than geographical and soil properties of the sites. The biological and humification indices of DOM were significantly negatively and positively correlated with DOC concentration, respectively. In addition, DOM characteristics were significantly correlated with elevation, climate, and soil properties. Our findings highlight the critical role of environmentally driven DOM characteristics in controlling DOC fate, providing valuable insights for predicting soil carbon biogeochemistry and informing carbon management strategies in inland wetlands.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100339"},"PeriodicalIF":7.2,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
引用次数: 0
Water Research X is expanding its article types
IF 7.2 2区 环境科学与生态学
Water Research X Pub Date : 2025-03-28 DOI: 10.1016/j.wroa.2025.100338
Zhiguo Yuan
{"title":"Water Research X is expanding its article types","authors":"Zhiguo Yuan","doi":"10.1016/j.wroa.2025.100338","DOIUrl":"10.1016/j.wroa.2025.100338","url":null,"abstract":"","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"27 ","pages":"Article 100338"},"PeriodicalIF":7.2,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
引用次数: 0
Micropollutants removal, residual risk, and costs for quaternary treatments in the framework of the Urban Wastewater Treatment Directive
IF 7.2 2区 环境科学与生态学
Water Research X Pub Date : 2025-03-15 DOI: 10.1016/j.wroa.2025.100334
Jessica Ianes, Sara Piraldi, Beatrice Cantoni, Manuela Antonelli
{"title":"Micropollutants removal, residual risk, and costs for quaternary treatments in the framework of the Urban Wastewater Treatment Directive","authors":"Jessica Ianes,&nbsp;Sara Piraldi,&nbsp;Beatrice Cantoni,&nbsp;Manuela Antonelli","doi":"10.1016/j.wroa.2025.100334","DOIUrl":"10.1016/j.wroa.2025.100334","url":null,"abstract":"<div><div>The revised Urban Wastewater Treatment Directive (UWWTD) imposes stringent regulations for the removal of micropollutants from urban wastewater treatment plants. The analyses conducted in this study are based on current knowledge extrapolated from literature WWTPs, to investigate the occurrence, removal and environmental risk related to the 12 target micropollutants: Amisulpride, Benzotriazole, 4,5-Methylbenzotriazole, Carbamazepine, Clarithromycin, Citalopram, Candesartan, Diclofenac, Hydrochlorothiazide, Irbesartan, Metoprolol, and Venlafaxine. The goal is to provide valuable insights into the challenges and opportunities associated with implementing quaternary treatment processes to comply with the UWWTD. Results indicate that the conventional biological treatment is insufficient, with median removal rates below 50 % for most target micropollutants (except for Benzotriazole and Irbesartan). The implementation of quaternary treatment processes, namely ozonation and activated carbon adsorption, significantly enhances WWTP micropollutants removal, with median removal efficiencies exceeding 80 % for all the target micropollutants, with Candesartan being the most recalcitrant. Environmental risk assessment reveals that some micropollutants pose a significant threat to aquatic ecosystems even with 80 % removal efficiency (Irbesartan, Candesartan, Diclofenac, and Venlafaxine), while others do not pose a risk even at WWTP influent concentrations (4,5-Methylbenzotriazole, Hydrochlorothiazide, Amisulpride, Citalopram, and Metoprolol).</div><div>Economic analysis shows that the selection of specific operating parameter values significantly impacts the cost of each treatment process, changing the economic feasibility ranking of the different treatment options.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100334"},"PeriodicalIF":7.2,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
引用次数: 0
Exploration of deep learning leak detection model across multiple smart water distribution systems: Detectable leak sizes with AMI meters
IF 7.2 2区 环境科学与生态学
Water Research X Pub Date : 2025-03-14 DOI: 10.1016/j.wroa.2025.100332
Sanghoon Jun , Donghwi Jung
{"title":"Exploration of deep learning leak detection model across multiple smart water distribution systems: Detectable leak sizes with AMI meters","authors":"Sanghoon Jun ,&nbsp;Donghwi Jung","doi":"10.1016/j.wroa.2025.100332","DOIUrl":"10.1016/j.wroa.2025.100332","url":null,"abstract":"<div><div>Numerous deep learning (DL) models have been developed for leak detection in water distribution systems (WDSs). However, significant lack of knowledge still remains concerning their detectability and the smallest detectable leak sizes across various WDSs. To address these research gaps, this study explores the performance of a DL leak detection model across eleven smart WDSs. A convolutional neural network (CNN) is employed to identify leaks using the spatially distributed pressure response images derived from the difference between advanced metering infrastructure (AMI) measurements and predictions from a well-calibrated hydraulic model (i.e., digital twin). Ten leak magnitudes are evaluated for each WDS, and three performance metrics (recall, precision, and F1 score) are calculated to assess the detectability and the detectable leak sizes of the CNN. The analysis reveals that the DL model's detection ability is highly impacted by WDS type, whether transmission- or distribution-oriented. The former networks exhibit low accuracy in identifying leaks due to the indistinguishability of pressure response images between normal and leak conditions. On the other hand, the latter networks generally achieve higher precision and recall results and can detect smaller leaks. Moreover, the smallest detectable leak sizes are more sensitive to WDS structural parameters (pipe diameter and length) than system hydraulics (system demand). Examining pipe characteristics along the leakage flow path provides most useful information in determining the detectability of leaks.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100332"},"PeriodicalIF":7.2,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143679679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
引用次数: 0
Using wastewater analysis to assess the health status of two distinct populations in China
IF 7.2 2区 环境科学与生态学
Water Research X Pub Date : 2025-03-14 DOI: 10.1016/j.wroa.2025.100335
Zhe Wang , Qiuda Zheng , Jianfa Gao , Jianan Ren , Fahad Ahmed , Yufang Chen , Cong Yang , Han Chen , Yuan Ren , Phong K. Thai
{"title":"Using wastewater analysis to assess the health status of two distinct populations in China","authors":"Zhe Wang ,&nbsp;Qiuda Zheng ,&nbsp;Jianfa Gao ,&nbsp;Jianan Ren ,&nbsp;Fahad Ahmed ,&nbsp;Yufang Chen ,&nbsp;Cong Yang ,&nbsp;Han Chen ,&nbsp;Yuan Ren ,&nbsp;Phong K. Thai","doi":"10.1016/j.wroa.2025.100335","DOIUrl":"10.1016/j.wroa.2025.100335","url":null,"abstract":"<div><div>Wastewater-based epidemiology (WBE) is a powerful tool for monitoring biomarkers of human health conditions. The WBE approach could deliver robust public health data with high temporal and spatial resolution, making it highly effective for assessing the impact of public health interventions across different populations. This study applied WBE to compare substance use and explore public health implications across two distinct populations: a general urban population and a university population. Daily and weekly wastewater samples were collected from 2017 to 2018, originating from a wastewater treatment plant serving the urban catchment and a pump station encompassing 10 universities. Consumption of over-the-counter (OTC) medications, prescribed drugs, and chronic disease medications in these two populations were estimated. Additionally, previously published data on recreational substances, respiratory and allergy medications, sweeteners, stress markers, and anabolic steroids were analyzed to present a comprehensive overview of human lifestyles and health status. Our results indicated that the university population consumed more OTC painkillers, including ibuprofen and paracetamol, but fewer prescribed opioids, such as codeine and morphine, compared to the general population. In contrast, higher consumption of chronic disease medications in the urban catchment indicated poorer overall health compared to the younger university population. These findings highlight significant differences in pharmaceutical consumption patterns and associated public health profiles between younger and general populations. This study underscores the utility of WBE in identifying public health disparities and guiding targeted health interventions based on population-specific needs and behaviors.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100335"},"PeriodicalIF":7.2,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
引用次数: 0
Ageing underground water pipelines: Time-to-failure models, gaps and future directions
IF 7.2 2区 环境科学与生态学
Water Research X Pub Date : 2025-03-13 DOI: 10.1016/j.wroa.2025.100331
Beenish Bakhtawar , Tarek Zayed , Ibrahim Abdelfadeel Shaban , Nehal Elshaboury , Abdul-Mugis Yussif
{"title":"Ageing underground water pipelines: Time-to-failure models, gaps and future directions","authors":"Beenish Bakhtawar ,&nbsp;Tarek Zayed ,&nbsp;Ibrahim Abdelfadeel Shaban ,&nbsp;Nehal Elshaboury ,&nbsp;Abdul-Mugis Yussif","doi":"10.1016/j.wroa.2025.100331","DOIUrl":"10.1016/j.wroa.2025.100331","url":null,"abstract":"<div><div>Accurate prediction of the failure time of individual pipelines of a water distribution network can assist in preventing sudden bursts and leaks. Failure prediction over time can help eliminate managerial uncertainty in pipe rehabilitation and replacement decision-making. Since time-based deterioration modeling has less focus in past research, the study focuses on a critical review of the current state-of-the-art for time-to-failure/failure age models related to water pipelines. A unique unsupervised learning-based clustering framework is used to perform an in-depth and robust literature analysis. Hierarchical clustering reveals the main modeling approaches, classified as 1) physical data-based models and 2) historical data-based failure models. Critical research gaps are further explored using t-SNE and Gaussian Mixture Models based clustering. Identified gaps include fragmented modeling approaches, lack of integration between physical and data-driven models, limited data related issues, and a lack of insight on practical translation of model findings for effective utility management. Future studies can consider several integration strategies to overcome individual model limitations, use of generative AI to enrich data, IoT implementation for physical data collection, improve feature engineering and feature extraction efforts, and consider domain knowledge from hydraulic models to improve AI models. Overall, the study offers practical insights for predicting the remaining time-to-failure and service life of water pipelines.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100331"},"PeriodicalIF":7.2,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143643093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
引用次数: 0
Leak detection in water supply networks using two-stage temporal segmentation and incremental learning for non-stationary acoustic signals
IF 7.2 2区 环境科学与生态学
Water Research X Pub Date : 2025-03-12 DOI: 10.1016/j.wroa.2025.100333
Xingke Ma , Yipeng Wu , Guancheng Guo , Shuming Liu , Yuexia Xu , Jingjing Fan , Hongbin Wang , Liren Xu
{"title":"Leak detection in water supply networks using two-stage temporal segmentation and incremental learning for non-stationary acoustic signals","authors":"Xingke Ma ,&nbsp;Yipeng Wu ,&nbsp;Guancheng Guo ,&nbsp;Shuming Liu ,&nbsp;Yuexia Xu ,&nbsp;Jingjing Fan ,&nbsp;Hongbin Wang ,&nbsp;Liren Xu","doi":"10.1016/j.wroa.2025.100333","DOIUrl":"10.1016/j.wroa.2025.100333","url":null,"abstract":"<div><div>Acoustic detection is a primary method for identifying leaks in urban water supply networks. However, acoustic signals within pipelines are highly susceptible to dynamic interference noise. This complicates the differentiation between leak and non-leak signals. To address this challenge, this paper presents a temporal segmentation-based approach for processing acoustic signals. Specifically, the two-stage temporal segmentation approach, which applies long-term segments to isolate non-stationary characteristics and short-term segments for capturing quasi-stationary features in acoustic signals, is introduced. We then applied the CNN model to recognize the Mel spectrogram features of the two-stage segmented signals and compared its performance with other models. Results indicate that this approach enhances both the accuracy and stability of leak detection, with the model achieving an average detection accuracy of 95 %. Moreover, the model is designed as an adaptive and continuous learning model, integrating its detection outcomes and newly labeled data segments into its training dataset. In practical applications, this continuous learning capability enables the model to improve its detection efficacy over time as data volume expands.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100333"},"PeriodicalIF":7.2,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
引用次数: 0
Fungal pretreatment as a promising approach for simultaneous recovery of phosphorus and carbon resource from garden waste: Performance and mechanism
IF 7.2 2区 环境科学与生态学
Water Research X Pub Date : 2025-03-10 DOI: 10.1016/j.wroa.2025.100330
Ruizhe Zhang , Qinyuan Lu , Cong Zhang , Yifeng Chen , Dunjie Li , Wenqiang Qi , Qian Ping , Yongmei Li
{"title":"Fungal pretreatment as a promising approach for simultaneous recovery of phosphorus and carbon resource from garden waste: Performance and mechanism","authors":"Ruizhe Zhang ,&nbsp;Qinyuan Lu ,&nbsp;Cong Zhang ,&nbsp;Yifeng Chen ,&nbsp;Dunjie Li ,&nbsp;Wenqiang Qi ,&nbsp;Qian Ping ,&nbsp;Yongmei Li","doi":"10.1016/j.wroa.2025.100330","DOIUrl":"10.1016/j.wroa.2025.100330","url":null,"abstract":"<div><div>Garden waste (GW), which is rich in organic matter and nutrients such as nitrogen (N) and phosphorus (P), has not been fully utilized for resource recovery. This study investigates a novel approach to recover both P and carbon source from GW by fungal pretreatment. Four types of GW—<em>Zoysia matrella (</em>L.<em>) Merr</em> (ZMM), <em>Lolium perenne</em> L (LPL), <em>Platanus × acerifolia (Aiton) Willd</em> (PAW), and <em>Cinnamomum camphora (</em>L.<em>) Presl</em> (CCP)—were subjected to alkaline, thermal, and fungal pretreatments. Results showed that fungal pretreatment was more effective than alkaline and thermal methods, especially for turfgrass GW. After 7 days of fungal pretreatment, the orthophosphate (PO<sub>4</sub>-P) concentration in the LPL supernatant was 2.15 times that of the control. Enzyme activity and metagenomic data revealed higher abundances of lignin degrading enzymes in turfgrass GW, with laccase being the dominant enzyme. Fungi convert organic phosphorus into PO<sub>4</sub>-P by secreting 3-phytase. Ammonium was also produced during fungal pretreatment, resulting in a weakly alkaline supernatant that promoted the precipitation of P as struvite. Consequently, a 43.51 % recovery of P from LPL as struvite with 91.3 % purity was achieved. The residual leachate served as a carbon source, achieving 78.67 % nitrate removal and 76.48 % total nitrogen removal. This study proposes a sustainable strategy for simultaneous P and carbon recovery from GW.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"29 ","pages":"Article 100330"},"PeriodicalIF":7.2,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143620942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
引用次数: 0
Balancing energy recovery and direct greenhouse gas emissions in wastewater treatment
IF 7.2 2区 环境科学与生态学
Water Research X Pub Date : 2025-03-08 DOI: 10.1016/j.wroa.2025.100328
Kaili Li , Haoran Duan , Shuting Wang , Ziping Wu , Peter Wardrop , James Lloyd , Nathali Christy , Pieter De Jong , Liu Ye
{"title":"Balancing energy recovery and direct greenhouse gas emissions in wastewater treatment","authors":"Kaili Li ,&nbsp;Haoran Duan ,&nbsp;Shuting Wang ,&nbsp;Ziping Wu ,&nbsp;Peter Wardrop ,&nbsp;James Lloyd ,&nbsp;Nathali Christy ,&nbsp;Pieter De Jong ,&nbsp;Liu Ye","doi":"10.1016/j.wroa.2025.100328","DOIUrl":"10.1016/j.wroa.2025.100328","url":null,"abstract":"<div><div>Achieving net-zero emissions is a critical goal for the water industry. This study provides a comprehensive evaluation of energy recovery and direct greenhouse gas (GHG) emissions from a full-scale wastewater treatment plant (WWTP), highlighting the important balance between carbon capture and emissions reduction. Long-term monitoring results revealed that upstream carbon capture, while recovering significant energy for carbon offset (40 % of total emission), stimulated downstream nitrous oxide (N<sub>2</sub>O) emissions, a major contributor to Scope 1 emissions. In response, integrated mitigation strategies were developed using mechanistic modelling, incorporating process optimizations (adjusting split ratios, DO setpoints, and mixing ratio) and retrofitting solution (raw wastewater diversion). The identified strategies reduced N<sub>2</sub>O emissions by 50 % and the overall carbon footprint by 40 %, despite a 31 % decrease in energy recovery, compared with the baseline case (N<sub>2</sub>O emission factor: 1.31 % of TKN load, net emissions: 354.29 kg CO<sub>2</sub>-e/ML, and energy recovery: 386.02 kg CO<sub>2</sub>-e/ML). The findings demonstrated the need for a holistic assessment of carbon capture, energy recovery, and GHG emissions across the entire treatment process. The outcome offers actionable insights for improving WWTP operations towards net-zero emissions.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"28 ","pages":"Article 100328"},"PeriodicalIF":7.2,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143685113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
引用次数: 0
Integrated social development on analyzing the distribution, risk and source apportionment of antibiotics pollution in mountainous rivers
IF 7.2 2区 环境科学与生态学
Water Research X Pub Date : 2025-03-01 DOI: 10.1016/j.wroa.2025.100327
Wei Fan , Minjie Yang , Ying Shao , Dongjun Shen , Liang Ao , Zhongli Chen
{"title":"Integrated social development on analyzing the distribution, risk and source apportionment of antibiotics pollution in mountainous rivers","authors":"Wei Fan ,&nbsp;Minjie Yang ,&nbsp;Ying Shao ,&nbsp;Dongjun Shen ,&nbsp;Liang Ao ,&nbsp;Zhongli Chen","doi":"10.1016/j.wroa.2025.100327","DOIUrl":"10.1016/j.wroa.2025.100327","url":null,"abstract":"<div><div>Antibiotics, as the widespread drugs stimulate the evolution of antibiotic resistance, threatening human and ecosystem health worldwide. However, studies rarely conducted in rivers among the regional scale with diverse economic development, which limits the management efficient of antibiotic control. Therefore, we investigated the concentration, distribution, risk and source apportionment of 54 antibiotics in 9 mountainous rivers, where the economic social development divers among their watersheds in Chongqing, China. The results showed that the concentrations of antibiotics detected in surface water, effluent of wastewater treatment plants, hospital, livestock and aquaculture sewage were 0.13–290 ng/L, 2.17–590 ng/L, 6.58–2.16 × 10<sup>5</sup> ng/L, 4.5–7.4 × 10<sup>5</sup> ng/L and 4.41–7.49 × 10<sup>3</sup> ng/L, respectively. The order of total antibiotic concentrations along the investigated rivers was Laixi River &gt; Changshou Lake &gt; Longxi River &gt; Fujiang River &gt; Jialing River &gt; Qiongjiang River &gt; Yangtze River &gt; Wujiang River &gt; Qijiang River. The risk quotient indicates that ofloxacin and lincomycin exhibited high risk. Through Mantel test and correlation analysis screened antibiotics associated with anthropogenic factors. Municipal wastewater had a positive impact on QNs. The positive matrix factorization model was used to identify the main sources of antibiotics in surface water with special focus on the Longxi River, revealing the livestock and aquaculture were main contributions, respectively. The ToxPi method was employed to prioritize antibiotics in surface water, and seven compounds were recommended as priority chemicals of concern in the future. This work provides a valuable regional scale dataset of antibiotics in the mountainous rivers, which promises valuable insights for controlling antibiotic contamination.</div></div>","PeriodicalId":52198,"journal":{"name":"Water Research X","volume":"28 ","pages":"Article 100327"},"PeriodicalIF":7.2,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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}
引用次数: 0
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信