ACS ES&T water最新文献_第10页

Carbon and Mercury Stable Isotope Fractionation during Aqueous Photodemethylation of CH3Hg

IF 4.8

ACS ES&T water Pub Date : 2025-02-04 DOI: 10.1021/acsestwater.4c0041610.1021/acsestwater.4c00416

Luisa M. Malberti-Quintero, Jeroen E. Sonke, Christelle Lagane, Laure Laffont and David Point*,

{"title":"Carbon and Mercury Stable Isotope Fractionation during Aqueous Photodemethylation of CH3Hg","authors":"Luisa M. Malberti-Quintero, Jeroen E. Sonke, Christelle Lagane, Laure Laffont and David Point*, ","doi":"10.1021/acsestwater.4c0041610.1021/acsestwater.4c00416","DOIUrl":"https://doi.org/10.1021/acsestwater.4c00416https://doi.org/10.1021/acsestwater.4c00416","url":null,"abstract":"The photodemethylation of monomethylmercury (CH3Hg) is one of the most important natural degradation processes of this toxic compound and is therefore key to understanding Hg exposure. The isotopic composition of CH3Hg contains information about its sources and transformation pathways. The stable isotopes of Hg during photodemethylation of CH3Hg bound to dissolved organic matter (DOM) have been shown to undergo unique mass-independent fractionation (MIF), as well as mass-dependent fractionation (MDF). Here we present different photodegradation experiments (DOM, Cl– ligands) where, in addition to Hg isotopes and degradation kinetics, the δ13C of CH3Hg was analyzed by compound-specific isotope analysis (CSIA): purge and trap–gas chromatography–combustion–isotope ratio mass spectrometry (PT-GC-C-IRMS). Our results show covariation of odd Hg MIF and light C isotope enrichment in CH3Hg photodemethylation products, with δ13C fractionation factors from −5 to −16‰, depending on the presence of Cl– and DOM. We also find a linear relationship between C MDF and Hg MIF, indicating that both isotope effects occur during C–Hg bond breaking. We suggest that biota Hg MIF can potentially be used to correct for photochemical C MDF, bringing us one step closer to exploring the origin of the methyl group contributing to CH3Hg formation.","PeriodicalId":93847,"journal":{"name":"ACS ES&T water","volume":"5 2","pages":"556–565 556–565"},"PeriodicalIF":4.8,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multicomponent Mass Transfer in Dissolved Gas Analysis: The Impacts of Headspace Pressurization on Reliable Measurement

IF 4.8

ACS ES&T water Pub Date : 2025-02-03 DOI: 10.1021/acsestwater.4c0065210.1021/acsestwater.4c00652

Cole J.C. Van De Ven*, Isabella R. Hearne and Madeline M. Calvert,

{"title":"Multicomponent Mass Transfer in Dissolved Gas Analysis: The Impacts of Headspace Pressurization on Reliable Measurement","authors":"Cole J.C. Van De Ven*, Isabella R. Hearne and Madeline M. Calvert, ","doi":"10.1021/acsestwater.4c0065210.1021/acsestwater.4c00652","DOIUrl":"https://doi.org/10.1021/acsestwater.4c00652https://doi.org/10.1021/acsestwater.4c00652","url":null,"abstract":"Measuring dissolved gas concentrations such as methane (CH4), carbon dioxide (CO2), and hydrogen (H2) (e.g., groundwater or surface water samples) is important for ensuring safe and effective subsurface energy development and storage. A common method is to collect water samples in fixed-volume sealed vessels and then use static headspace equilibrium techniques to quantify the dissolved gas concentrations by gas chromatography. Previously, the presence of multiple gas components was not considered during the analysis of water samples but is necessary. A mass balance approach considering multicomponent mass transfer was developed and validated, and the impact on dissolved gas measurements was quantified. It was found that mass transfer occurring in fixed-volume vessels leads to pressurization of sample headspace during analysis, causing error. Higher solubility gases (e.g., CO2) exhibit higher headspace pressurization and larger errors than lower solubility gases (e.g., CH4). In addition, it was found that the volume of the headspace induced and the co-occurrence of multiple dissolved gas species in a sample can exacerbate headspace pressurization and error. Overall, caution must be taken when using static headspace equilibrium techniques; if multicomponent mass transfer is not considered, error and potential under reporting of dissolved concentrations is possible.","PeriodicalId":93847,"journal":{"name":"ACS ES&T water","volume":"5 2","pages":"639–648 639–648"},"PeriodicalIF":4.8,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of Sedimentation Mechanisms in Small Diameter Gravity Sewers Based on Computational Fluid Dynamics

IF 4.8

ACS ES&T water Pub Date : 2025-02-03 DOI: 10.1021/acsestwater.4c0103610.1021/acsestwater.4c01036

Fan Hu, Shangbin Ma, Ximei Zhang, Wenkai Li*, Yingnan Cao, Jianguo Liu*, Junxin Liu and Tianlong Zheng*,

{"title":"Analysis of Sedimentation Mechanisms in Small Diameter Gravity Sewers Based on Computational Fluid Dynamics","authors":"Fan Hu, Shangbin Ma, Ximei Zhang, Wenkai Li*, Yingnan Cao, Jianguo Liu*, Junxin Liu and Tianlong Zheng*, ","doi":"10.1021/acsestwater.4c0103610.1021/acsestwater.4c01036","DOIUrl":"https://doi.org/10.1021/acsestwater.4c01036https://doi.org/10.1021/acsestwater.4c01036","url":null,"abstract":"Small diameter gravity sewers (SDGSs) have a wide range of applications in rural wastewater collection due to their low construction costs, fast implementation, and simple operation and maintenance. However, the mechanism of sediment accumulation urgently needs to be solved. This study investigated the sedimentation mechanisms in different components of SDGS through pilot-scale experiments and computational fluid dynamics (CFD) simulations. The results indicate that the sedimentation rate of SDGSs decreased as the flow velocity increased, with sediment primarily accumulating at the end section of upstream pipes and within manholes, accounting for 90.37 ± 5.15% of the total accumulation. Areas with relatively high sedimentation rates exhibited lower turbulent kinetic energy (TKE), and this trend became more pronounced as the flow velocity decreased. TKE and flow velocity were identified as the key factors influencing the sedimentation process in the SDGSs. This study provides important theoretical foundations and technical support for the design and maintenance of SDGSs.","PeriodicalId":93847,"journal":{"name":"ACS ES&T water","volume":"5 2","pages":"993–1002 993–1002"},"PeriodicalIF":4.8,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spatially Referenced Global River Flow Data for Aquatic Safety Assessment Exposure Models Developed from Publicly Available Global Data Sets

IF 4.8

ACS ES&T water Pub Date : 2025-02-02 DOI: 10.1021/acsestwater.4c0063710.1021/acsestwater.4c00637

Raghu Vamshi, Susan A. Csiszar*, Kathleen McDonough, Ryan Heisler, Chiara M. Vitale, Katherine E. Kapo and Amy M. Ritter,

{"title":"Spatially Referenced Global River Flow Data for Aquatic Safety Assessment Exposure Models Developed from Publicly Available Global Data Sets","authors":"Raghu Vamshi, Susan A. Csiszar*, Kathleen McDonough, Ryan Heisler, Chiara M. Vitale, Katherine E. Kapo and Amy M. Ritter, ","doi":"10.1021/acsestwater.4c0063710.1021/acsestwater.4c00637","DOIUrl":"https://doi.org/10.1021/acsestwater.4c00637https://doi.org/10.1021/acsestwater.4c00637","url":null,"abstract":"The availability of detailed river flow data across large geographic areas is needed for several scientific applications, and the focus of this work was to develop a spatially referenced global river flow data set for use in environmental risk assessments for substances entering rivers. This paper provides a publicly available spatially resolved global spatial data set, which can be readily used in aquatic exposure models. This paper explores applying the well-established curve number (CN) method to estimate surface water runoff, which was used as the basis for estimating river flows. Input needed to implement the CN method was from freely and publicly available global data sets on hydrologic soil groups, land cover, and precipitation. The runoff data were then spatially combined with publicly available global hydrological data sets of catchments and rivers to estimate daily mean annual flows across the globe on a level-12 catchment scale. Estimated daily mean annual flows were compared with measured gauge flows at rivers in several countries, which showed good correlation (R2 of 0.71–0.99) on a river catchment level. Additionally, flows were compared on a sub-basin level, which also correlated well with measured gauge flows, with an R2 of 0.9 (log transformed) across basins in several countries.","PeriodicalId":93847,"journal":{"name":"ACS ES&T water","volume":"5 2","pages":"618–628 618–628"},"PeriodicalIF":4.8,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid Material TiO2-TPA@porous Activated Carbon and Its Activity in the Photocatalytic Degradation of Pharmaceutical Pollutants in Water

IF 4.8

ACS ES&T water Pub Date : 2025-01-29 DOI: 10.1021/acsestwater.4c0086110.1021/acsestwater.4c00861

John J. Alvear-Daza, Victoria Melin, Cecilia Torres, Cristian H. Campos, David Contreras, Karina G. Irvicelli, Jorge A. Donadelli, Julián A. Rengifo-Herrera* and Luis R. Pizzio*,

{"title":"Hybrid Material TiO2-TPA@porous Activated Carbon and Its Activity in the Photocatalytic Degradation of Pharmaceutical Pollutants in Water","authors":"John J. Alvear-Daza, Victoria Melin, Cecilia Torres, Cristian H. Campos, David Contreras, Karina G. Irvicelli, Jorge A. Donadelli, Julián A. Rengifo-Herrera* and Luis R. Pizzio*, ","doi":"10.1021/acsestwater.4c0086110.1021/acsestwater.4c00861","DOIUrl":"https://doi.org/10.1021/acsestwater.4c00861https://doi.org/10.1021/acsestwater.4c00861","url":null,"abstract":"The next generation of photocatalysts should exhibit visible-light absorption, high pollutant adsorption capacity, and stability. The activated carbons (AC) obtained from sustainable procedures, such as the pyrolysis of agroindustrial residues, show high adsorption capacities and an interesting ability to photoinduce reactive oxygen species (ROS). For this reason, herein, the synthesis of a hybrid TiO2-TPA@AC material consisting of a UV–visible-light active photocatalyst as the TiO2-TPA and an AC obtained from the pyrolysis of H3PO4-activated sunflower seed shells (SSS) is reported. TiO2-TPA@AC photocatalytic activity was evaluated under simulated sunlight irradiation to oxidize ibuprofen (IB) and diclofenac (DI) in water, finding that the hybrid material exhibited the highest removal of both pollutants (98%) after 1 h through a dark adsorption step and, by a photoinduced process, where both the TiO2-TPA and the AC generated ROS able to oxidize 95% of the adsorbed pollutants. The adsorption–photooxidation capacity of the TiO2-TPA@AC material was stable after four reusing cycles, leaching Ti and W in solution at concentrations of 0.48 and 0.31 mg L–1, respectively.","PeriodicalId":93847,"journal":{"name":"ACS ES&T water","volume":"5 2","pages":"772–785 772–785"},"PeriodicalIF":4.8,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AI and IoT: Supported Sixth Generation Sensing for Water Quality Assessment to Empower Sustainable Ecosystems

IF 4.8

ACS ES&T water Pub Date : 2025-01-28 DOI: 10.1021/acsestwater.4c0036010.1021/acsestwater.4c00360

Suparna Das, Kamil Reza Khondakar*, Hirak Mazumdar*, Ajeet Kaushik* and Yogendra Kumar Mishra,

{"title":"AI and IoT: Supported Sixth Generation Sensing for Water Quality Assessment to Empower Sustainable Ecosystems","authors":"Suparna Das, Kamil Reza Khondakar*, Hirak Mazumdar*, Ajeet Kaushik* and Yogendra Kumar Mishra, ","doi":"10.1021/acsestwater.4c0036010.1021/acsestwater.4c00360","DOIUrl":"https://doi.org/10.1021/acsestwater.4c00360https://doi.org/10.1021/acsestwater.4c00360","url":null,"abstract":"The integration of artificial intelligence (AI) and the Internet-of-Things (IoT) heralds the advent of sixth-generation sensing technologies, offering transformative potential for water quality assessment and the empowerment of sustainable ecosystems. This approach offers efficient monitoring through predictive analysis, risk assessment, and timely decision-making. However, this approach requires diverse expertise and requires connecting multiple dots. This paper explores the convergence of AI and IoT in developing advanced sensor networks capable of real-time monitoring and data analysis, providing comprehensive insights into water quality. AI algorithms can predict pollution events, optimize resource management, and enhance decision-making processes. IoT-enabled sensors provide extensive coverage and connectivity, facilitating continuous monitoring and immediate reporting of water conditions. This synergy ensures accurate detection of contaminants and supports proactive environmental management, aligning with global sustainability goals. Implementing AI and IoT in water quality assessment is crucial for maintaining healthy aquatic ecosystems, fostering biodiversity, and ensuring safe water resources for communities. The paper highlights the effectiveness and scalability of AI and IoT-supported sensing technologies, underscoring their critical role in a sustainable future.","PeriodicalId":93847,"journal":{"name":"ACS ES&T water","volume":"5 2","pages":"490–510 490–510"},"PeriodicalIF":4.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessment of Legionella pneumophila in Rural Homes Supplied by Private Well Water

IF 4.8

ACS ES&T water Pub Date : 2025-01-28 DOI: 10.1021/acsestwater.4c0112710.1021/acsestwater.4c01127

Gemma G. Clark*, Guorui Zhang, Shenyi Zhao and Thanh H. Nguyen,

{"title":"Assessment of Legionella pneumophila in Rural Homes Supplied by Private Well Water","authors":"Gemma G. Clark*, Guorui Zhang, Shenyi Zhao and Thanh H. Nguyen, ","doi":"10.1021/acsestwater.4c0112710.1021/acsestwater.4c01127","DOIUrl":"https://doi.org/10.1021/acsestwater.4c01127https://doi.org/10.1021/acsestwater.4c01127","url":null,"abstract":"Legionella pneumophila is a major cause of waterborne disease in the United States, but little is known about its prevalence in rural homes supplied by domestic well water. With a citizen science campaign involving 57 such homes in Illinois, conclusive results from 39 homes showed intact L. pneumophila in 31% and 28% of warm and hot water samples, respectively. We conducted a quantitative microbial risk assessment (QMRA) for L. pneumophila infection risk using L. pneumophila data from three studies (ours, another on rural homes in North Carolina, and another on a public water supply). The risk of illness was non-negligible in all cases and sometimes exceeded the 10–4 target annual risk. The L. pneumophila concentration and exposure time had the greatest impact on the risk of illness due to a one-time exposure. Aerosol concentration had the greatest impact on the annual risk of illness. A maximum L. pneumophila concentration of 6 × 10–3 copies/mL was needed to achieve the 10–4 target. This study showed that L. pneumophila risk could be present in homes supplied by private wells, like those studied here, but can be mitigated by reducing L. pneumophila concentration, reducing exposure time, and careful consideration of fixtures that produce high concentrations of respirable aerosols.","PeriodicalId":93847,"journal":{"name":"ACS ES&T water","volume":"5 2","pages":"1041–1054 1041–1054"},"PeriodicalIF":4.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantifying Footprints of Perfluorinated Compounds in China: From Production to Discharge into the Seas

IF 4.8

ACS ES&T water Pub Date : 2025-01-28 DOI: 10.1021/acsestwater.4c0093310.1021/acsestwater.4c00933

Yaya Cai, Qianqian Zhang* and Guangguo Ying,

{"title":"Quantifying Footprints of Perfluorinated Compounds in China: From Production to Discharge into the Seas","authors":"Yaya Cai, Qianqian Zhang* and Guangguo Ying, ","doi":"10.1021/acsestwater.4c0093310.1021/acsestwater.4c00933","DOIUrl":"https://doi.org/10.1021/acsestwater.4c00933https://doi.org/10.1021/acsestwater.4c00933","url":null,"abstract":"Understanding the emission sources and environmental footprints of perfluorinated compounds (PFASs) is essential for tracing their pervasive presence in the environment. This study aims to comprehensively assess the emissions and footprints of 10 commonly reported PFASs in China from production to their final release into the sea. In 2022, China produced 120 t target PFASs, with 104 t utilized in secondary industrial production. One-third of those applied PFASs emit into the environment primarily from industrial processes. Domestic use resulted in the emission of 4.21 t of PFASs, half of which was sourced from wastewater treatment plants. River water received 57.6% of the total PFAS emissions, with 11.4% eventually flowing into China’s surrounding seas. During 2015–2022, China experienced a cumulative PFAS emission of 467 t, with 40.3 t emitted into neighboring seas, predominantly into the Bohai and East China Seas. The spatial distributions of PFAS emissions and pollution levels were consistent with China’s topographical three-tiered stepped lines. Economic and topographical factors strongly influenced the footprint processes and transport patterns of PFASs into the ocean. This study traces and quantifies the major PFAS pathways from production to discharge into the sea, highlighting the need for targeted interventions to reduce PFAS emissions and protect ecosystems.","PeriodicalId":93847,"journal":{"name":"ACS ES&T water","volume":"5 2","pages":"920–933 920–933"},"PeriodicalIF":4.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effects of Human Activities on the Distribution Patterns and Health Risks of Sb, As, Hg, and Se in a Typical Urban River System of Southern China

IF 4.8

ACS ES&T water Pub Date : 2025-01-28 DOI: 10.1021/acsestwater.4c0102710.1021/acsestwater.4c01027

Chenqi Guo, Hongru Feng, Zechen Yu, Xuezhi Yang*, Tao Zeng, Shuang Song and Haiyan Zhang*,

{"title":"Effects of Human Activities on the Distribution Patterns and Health Risks of Sb, As, Hg, and Se in a Typical Urban River System of Southern China","authors":"Chenqi Guo, Hongru Feng, Zechen Yu, Xuezhi Yang*, Tao Zeng, Shuang Song and Haiyan Zhang*, ","doi":"10.1021/acsestwater.4c0102710.1021/acsestwater.4c01027","DOIUrl":"https://doi.org/10.1021/acsestwater.4c01027https://doi.org/10.1021/acsestwater.4c01027","url":null,"abstract":"The anthropogenic input of heavy metals and metalloids (metal(loid)s) into aquatic environments is a global concern. Here, we investigated the spatial distributions and health risks of antimony (Sb), mercury (Hg), arsenic (As), and selenium (Se) and their associations with socioeconomic variables in the Qiantang River basin. In river water, Sb decreased from the southern tributaries to the northeastern mainstream, peaking at 25.3 μg L–1 near industrial zones, whereas As and Hg displayed a gradual increase in urban areas. Industrial and domestic wastewater contributed 86.5% of the total Sb flow in the river. Correlation analysis revealed that Sb concentrations in river water positively correlated with industrial wastewater emissions, while Hg, As, and Se were associated with variables such as population density. Structural equation models further indicated that industrial wastewater emissions directly affected Sb levels, while population density and energy consumption influenced Se levels. Monte Carlo simulations revealed low health risks (HI < 1, CR < 1 × 10–4), but compared to background areas, residents in urban areas experienced a 69.8% increase in noncarcinogenic risks, while those in industrial areas faced a 277% increase. These findings underscore the link between metal(loid) contamination and socioeconomic factors, providing data for managing metal(loid) contamination in urban river systems.","PeriodicalId":93847,"journal":{"name":"ACS ES&T water","volume":"5 3","pages":"1248–1260 1248–1260"},"PeriodicalIF":4.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143608961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning Approach for Predicting Perfluorooctanesulfonate Rejection in Efficient Nanofiltration Treatment and Removal

IF 4.8

ACS ES&T water Pub Date : 2025-01-28 DOI: 10.1021/acsestwater.4c0100310.1021/acsestwater.4c01003

Saurabh Singh*, Gourav Suthar, Akhilendra Bhushan Gupta and Achintya N. Bezbaruah,

{"title":"Machine Learning Approach for Predicting Perfluorooctanesulfonate Rejection in Efficient Nanofiltration Treatment and Removal","authors":"Saurabh Singh*, Gourav Suthar, Akhilendra Bhushan Gupta and Achintya N. Bezbaruah, ","doi":"10.1021/acsestwater.4c0100310.1021/acsestwater.4c01003","DOIUrl":"https://doi.org/10.1021/acsestwater.4c01003https://doi.org/10.1021/acsestwater.4c01003","url":null,"abstract":"Perfluorooctanesulfonic acid (PFOS) is a persistent environmental contaminant posing significant health risks, requiring efficient remediation methods. This study explores the use of advanced nanofiltration techniques, combined with machine learning (ML) optimization, to enhance PFOS removal from water. Key parameters such as membrane type, temperature, PFOS concentration, pH, pressure, and cation presence were analyzed for their influence on PFOS rejection efficiency. Five ML models─multiple linear regression (MLR), lasso regression, ridge regression, random forest (RF), and artificial neural networks (ANN)─were applied to improve predictive accuracy and optimize the filtration process. Data from various studies were analyzed, revealing that PFOS rejection was highly sensitive to trivalent cations and pH changes. The ANN model achieved the highest accuracy (R2 = 0.89) in predicting PFOS rejection, followed by RF, ridge, lasso, and MLR, in that order. The study highlights the importance of optimizing operational conditions to improve nanofiltration efficiency. ML integration provided valuable insights into treatment processes, offering practical solutions for more effective water purification. This study provides novel insights into PFOS rejection mechanisms, focusing on operational parameters and their interactions to optimize nanofiltration. It provides practical guidance for improving water treatment efficiency and protecting public health and the environment.","PeriodicalId":93847,"journal":{"name":"ACS ES&T water","volume":"5 3","pages":"1216–1228 1216–1228"},"PeriodicalIF":4.8,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143609016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0