Water Research最新文献

{"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}

{"title":"Responses of fish to nationwide improvements in the water quality of a densely populated and heavily modified country over four decades","authors":"Andy D. Nunn, Rachel F. Ainsworth, Yueming Qu, Virginie D.J. Keller, Nuria Bachiller-Jareno, Vasileios Antoniou, Michael Eastman, Clarissa Rizzo, Graeme Peirson, Frances Eley, Andrew C. Johnson, Ian G. Cowx","doi":"10.1016/j.watres.2025.123163","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123163","url":null,"abstract":"Globally, fish have been severely affected by the widespread, chronic degradation of fresh waters, with a substantial proportion of species declining in abundance or range in recent decades. This has especially been the case in densely populated countries with an industrial heritage and intensive agriculture, where the majority of river catchments have been affected by deteriorations in water quality and changes in land use. This study used a spatially and temporally extensive dataset, encompassing 16,124 surveys at 1180 sites representing a wide range of river typologies and pressures, to examine changes in the fish populations of England's rivers over four decades (1980s–2010s). The analyses revealed gradual, nationwide increases in mean fish species richness and diversity across the range of pressure gradients. In the majority of cases, increases were most pronounced in the 1980s, since when any further changes have been comparatively minor, but there were no declining trends across the full time series. There were also temporal, nationwide changes in fish assemblage structure, driven largely by variations in the densities of brown trout <em>Salmo trutta</em> or roach <em>Rutilus rutilus</em>, but no consistent increases in the abundance of sensitive, pollution-intolerant species in response to improvements in wastewater treatment and, consequently, water quality. Although the increases in fish species richness and diversity over the last four decades are encouraging, subtle and contrasting changes in the abundance of a range of species require further investigation, and causal relationships between fish assemblage structure and putative drivers should be modelled at a national scale. This study is the first to examine long-term, nationwide trends in the freshwater fish populations of England, and significantly advances our understanding of the ecological health of rivers in densely populated and heavily modified countries.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"8 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989174","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":"Establishing performance criteria for evaluating watershed-scale sediment and nutrient models at fine temporal scales","authors":"Aayush Pandit, Sarah Hogan, David T. Mahoney, William I. Ford, James F. Fox, Christopher Wellen, Admin Husic","doi":"10.1016/j.watres.2025.123156","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123156","url":null,"abstract":"Watershed water quality models are mathematical tools used to simulate processes related to water, sediment, and nutrients. These models provide a framework that can be used to inform decision-making and the allocation of resources for watershed management. Therefore, it is critical to answer the question “when is a model good enough?” Established performance evaluation criteria, or thresholds for what is considered a ‘good’ model, provide common benchmarks against which model performance can be compared. Since the publication of prior meta-analyses on this topic, developments in the last decade necessitate further investigation, such as the advancement in high performance computing, the proliferation of aquatic sensors, and the development of machine learning algorithms. We surveyed the literature for quantitative model performance measures, including the Nash-Sutcliffe efficiency (NSE), with a particular focus on process-based models operating at fine temporal scales as their performance evaluation criteria are presently underdeveloped. The synthesis dataset was used to assess the influence of temporal resolution (sub-daily, daily, and monthly), calibration duration (&lt; 3 years, 3 to 8 years, and &gt; 8 years), and constituent target units (concentration, load, and yield) on model performance. The synthesis dataset includes 229 model applications, from which we use bootstrapping and personal modeling experience to establish sub-daily and daily performance evaluation criteria for flow, sediment, total nutrient, and dissolved nutrient models. For daily model evaluation, the NSE for sediment, total nutrient, and dissolved nutrient models should exceed 0.45, 0.30, and 0.35, respectively, for ‘satisfactory’ performance. Model performance generally improved when transitioning from short (&lt; 3 years) to medium (3 to 8 years) calibration durations, but no additional gain was observed with longer (&gt; 8 years) calibration. Performance was not significantly influenced by the selection of concentration (e.g. mg/L) or load (e.g. kg/s) as the target units for sediment or total nutrient models but was for dissolved nutrient models. We recommend the use of concentration rather than load as a water quality modeling target, as load may be biased by strong flow model performance whereas concentration provides a flow-independent measure of performance. Although the performance criteria developed herein are based on process-based models, they may be useful in assessing machine learning model performance and we demonstrate one such assessment on a recent deep learning model of daily nitrate prediction across the United States. The guidance presented here is intended to be used alongside, rather than to replace, the experience and modeling judgement of engineers and scientist who work to maintain our collective water resources.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"23 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989269","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":"Aerosol particles released from grit chambers of nine urban wastewater treatment plants in typical regions: fugitive characteristics, quantitative drivers, and generation process","authors":"Wenwen Wang, Kaixiong Yang, Lin Li, Yunping Han","doi":"10.1016/j.watres.2025.123162","DOIUrl":"https://doi.org/10.1016/j.watres.2025.123162","url":null,"abstract":"The flow through the grit chamber is non-biochemically treated wastewater, which contains microorganisms mainly from the source of wastewater generation. There are limited reports on aerosol particles generated by grit chambers compared with those produced by biochemical treatment tanks. This study analyzed the fugitive characteristics of aerosol particles produced in grit chambers at nine wastewater treatment plants in three regions of China. There were 160.41–432.13 μg/m³ of total particles and 455 ± 34–2181 ± 221 CFU/m³ of bacteria in aerosol particles. The chemicals in aerosol particles contained 7.35–53.70 μg/m³ of total organic carbon and 36.10–227.94 μg/m³ of water-soluble inorganic ions. The aerated grit chambers produced significantly more aerosol particles than the vortex-type grit chambers. Indoor treatment facilities were more prone to aerosol particle accumulation than outdoor facilities. The microorganisms in wastewater were the main contributing source of dominant microorganisms in aerosol particles, with a degree of explanation of 73.33% ± 35.56%. Mantel analysis and the partial least squares path modeling determined that the components and biodiversity of wastewater were direct determinants of aerosol emission levels and biodiversity, respectively. Geographic regions contributed to the differences in aerosol particles, primarily indirectly by affecting the components of wastewater. The bubble bursting trajectory simulation experiment simulated the bioaerosol generation process in aerated grit chambers and predicted droplet behaviours. A higher number of small film droplets corresponded to a higher concentration of bioaerosols. <em>Arcobacter, Aeromonas, Acinetobacter</em>, and <em>Flavobacterium</em> were the major pathogenic genera in aerosol particles produced by grit chambers. The annual probability of infection and the disease burden of these pathogenic bacteria cannot be ignored. This study provides a scientific basis for further understanding of aerosol particle generation and potential hazards in grit chambers of wastewater treatment plants.","PeriodicalId":443,"journal":{"name":"Water Research","volume":"31 1","pages":""},"PeriodicalIF":12.8,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142989268","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}