Pub Date : 2024-12-04DOI: 10.1038/s41545-024-00417-3
Juan Nathaniel, Sara Schwetschenau, Upmanu Lall
Aging infrastructure and climate change present emerging challenges for clean water supply and reliable wastewater services for communities in the United States (US). In Georgia, for example, the failure rates of on-site wastewater systems (OWTS) have increased from 10% to 35% in the last two decades as the systems age. In this work, we develop a hierarchical Bayesian model to understand the different contributions of physical and social factors driving OWTS failures using a long-term collection of 201,000 Georgia’s OWTS inspection records. The out-of-sample validation accuracy of our hierarchical Bayesian model is 70% within Georgia, outperforming other machine learning models that do not consider the multiscale nature of the problem. Overall, we find counties that experience more extreme precipitation and are situated in steeper-sloped regions are significantly associated with increased failure risks. Uncertainties, meanwhile, are largely associated with counties experiencing more precipitation and have lower median housing value.
{"title":"Inferring failure risk of on-site wastewater systems from physical and social factors","authors":"Juan Nathaniel, Sara Schwetschenau, Upmanu Lall","doi":"10.1038/s41545-024-00417-3","DOIUrl":"10.1038/s41545-024-00417-3","url":null,"abstract":"Aging infrastructure and climate change present emerging challenges for clean water supply and reliable wastewater services for communities in the United States (US). In Georgia, for example, the failure rates of on-site wastewater systems (OWTS) have increased from 10% to 35% in the last two decades as the systems age. In this work, we develop a hierarchical Bayesian model to understand the different contributions of physical and social factors driving OWTS failures using a long-term collection of 201,000 Georgia’s OWTS inspection records. The out-of-sample validation accuracy of our hierarchical Bayesian model is 70% within Georgia, outperforming other machine learning models that do not consider the multiscale nature of the problem. Overall, we find counties that experience more extreme precipitation and are situated in steeper-sloped regions are significantly associated with increased failure risks. Uncertainties, meanwhile, are largely associated with counties experiencing more precipitation and have lower median housing value.","PeriodicalId":19375,"journal":{"name":"npj Clean Water","volume":" ","pages":"1-11"},"PeriodicalIF":10.4,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41545-024-00417-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-03DOI: 10.1038/s41545-024-00409-3
Maura C. Allaire, Bianca Brusco, Amal Bakchan, Mark A. Elliott, Mallory A. Jordan, Jillian Maxcy-Brown, Kevin D. White
Uneven access to water and wastewater infrastructure is shaped by local governance. A substantial number of U.S. households lack adequate access and the U.S. is one of the few countries with large populations living outside of city bounds, in unincorporated areas. Few studies address how infrastructure services and local governance are intertwined at a regional scale. We examine the connection between incorporation status and access to centralized infrastructure, using negative binomial regression. A novel dataset informs this analysis, comprised of 31,383 Census block groups located in nine states representing over 25% of the national population. We find evidence that inequities in access are associated with unincorporated status and poverty rates. Sewer coverage rates are significantly lower for unincorporated communities in close proximity to municipal boundaries. Infrastructure equity could be improved by targeting high-poverty unincorporated communities, addressing challenges with noncontiguous service areas, and strengthening regional water planning and participatory governance.
{"title":"Water and wastewater infrastructure inequity in unincorporated communities","authors":"Maura C. Allaire, Bianca Brusco, Amal Bakchan, Mark A. Elliott, Mallory A. Jordan, Jillian Maxcy-Brown, Kevin D. White","doi":"10.1038/s41545-024-00409-3","DOIUrl":"10.1038/s41545-024-00409-3","url":null,"abstract":"Uneven access to water and wastewater infrastructure is shaped by local governance. A substantial number of U.S. households lack adequate access and the U.S. is one of the few countries with large populations living outside of city bounds, in unincorporated areas. Few studies address how infrastructure services and local governance are intertwined at a regional scale. We examine the connection between incorporation status and access to centralized infrastructure, using negative binomial regression. A novel dataset informs this analysis, comprised of 31,383 Census block groups located in nine states representing over 25% of the national population. We find evidence that inequities in access are associated with unincorporated status and poverty rates. Sewer coverage rates are significantly lower for unincorporated communities in close proximity to municipal boundaries. Infrastructure equity could be improved by targeting high-poverty unincorporated communities, addressing challenges with noncontiguous service areas, and strengthening regional water planning and participatory governance.","PeriodicalId":19375,"journal":{"name":"npj Clean Water","volume":" ","pages":"1-17"},"PeriodicalIF":10.4,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41545-024-00409-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142760593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-30DOI: 10.1038/s41545-024-00408-4
Simranjeet Singh, Nikhita Sivaram, Bidisha Nath, Nadeem A. Khan, Joginder Singh, Praveen C. Ramamurthy
Metal-Organic Frameworks (MOFs) are versatile materials with tailorable structures, high surface areas, and controlled pore sizes, making them ideal for gas storage, separation, catalysis, and notably wastewater treatment by removing pollutants like antibiotics and heavy metals. Functionalization enhances their applications in energy conversion and environmental remediation. Despite challenges like stability and cost, ongoing innovation in MOFs contributes to the circular economy and aligns with Sustainable Development Goals.
{"title":"Metal organic frameworks for wastewater treatment, renewable energy and circular economy contributions","authors":"Simranjeet Singh, Nikhita Sivaram, Bidisha Nath, Nadeem A. Khan, Joginder Singh, Praveen C. Ramamurthy","doi":"10.1038/s41545-024-00408-4","DOIUrl":"10.1038/s41545-024-00408-4","url":null,"abstract":"Metal-Organic Frameworks (MOFs) are versatile materials with tailorable structures, high surface areas, and controlled pore sizes, making them ideal for gas storage, separation, catalysis, and notably wastewater treatment by removing pollutants like antibiotics and heavy metals. Functionalization enhances their applications in energy conversion and environmental remediation. Despite challenges like stability and cost, ongoing innovation in MOFs contributes to the circular economy and aligns with Sustainable Development Goals.","PeriodicalId":19375,"journal":{"name":"npj Clean Water","volume":" ","pages":"1-22"},"PeriodicalIF":10.4,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41545-024-00408-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142753775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In response to the urgent need for efficient degradation of emerging organic contaminants, this study has developed a novel catalytic system based on an original Fe-doped aerogel catalyst (FeCAS) and its carbonization-enhanced variant (FeCAS-400), designed to improve the activation performance of peracetic acid (PAA). The FeCAS/PAA achieves a remarkable 96.1% degradation of sulfamethoxazole (SMX) without external energy input, while the FeCAS-400/PAA further elevates the SMX removal rate to 98.4% (kobs = 0.326 min−¹) and demonstrates effectiveness across a broad pH range of 3–11. Theoretical calculations reveal that carbonization enhances electron transfer between iron–carbon substrates, which contributes to improved catalytic performance. The system also exhibits versatility in removing a wide range of prevalent contaminants and proves effective in real water matrices. This synergistic approach, combining aerogels with metal–carbon electron transfer, holds promise for an extension to other advanced oxidation processes, contributing to the assurance of water quality safety and sustainability.
{"title":"Synergistic iron enhanced aerogel and peracetic acid for degradation of emerging organic contaminants","authors":"Lili Jin, Tong Li, Xiaoya Fang, Zhao Xue, Hui Huang, Hongqiang Ren","doi":"10.1038/s41545-024-00415-5","DOIUrl":"10.1038/s41545-024-00415-5","url":null,"abstract":"In response to the urgent need for efficient degradation of emerging organic contaminants, this study has developed a novel catalytic system based on an original Fe-doped aerogel catalyst (FeCAS) and its carbonization-enhanced variant (FeCAS-400), designed to improve the activation performance of peracetic acid (PAA). The FeCAS/PAA achieves a remarkable 96.1% degradation of sulfamethoxazole (SMX) without external energy input, while the FeCAS-400/PAA further elevates the SMX removal rate to 98.4% (kobs = 0.326 min−¹) and demonstrates effectiveness across a broad pH range of 3–11. Theoretical calculations reveal that carbonization enhances electron transfer between iron–carbon substrates, which contributes to improved catalytic performance. The system also exhibits versatility in removing a wide range of prevalent contaminants and proves effective in real water matrices. This synergistic approach, combining aerogels with metal–carbon electron transfer, holds promise for an extension to other advanced oxidation processes, contributing to the assurance of water quality safety and sustainability.","PeriodicalId":19375,"journal":{"name":"npj Clean Water","volume":" ","pages":"1-14"},"PeriodicalIF":10.4,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41545-024-00415-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142753778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-29DOI: 10.1038/s41545-024-00419-1
Sethu Kalidhasan, Jonghoon Choi, Hee-Young Lee
Novel iron oxide-incorporated porous polydimethylsiloxane sponges were developed using a simple, non-toxic two-step process. Characterized through various techniques, these sponges serve as effective photocatalysts, absorbents, and adsorbents for pollutant removal. They demonstrated nearly 100% degradation of rhodamine B under optimal conditions ( ~ 100% with Xe arc lamp, 50 mg, pH 3-9, and 4 h), following a pseudo second-order kinetic model (r2 = 0.9999). The sponges also exhibited good activity for other pollutants, including methylene blue (76–87%), 1,4-dichlorobenzene (57–71%), and azithromycin (82–87%), and maintained high performance over 11 reuse cycles with minimal iron loss. In addition, fresh and used catalysts effectively separated oils (173–680 mg with 50 mg of absorbent, and 10–15 s) and chromium (VI) [~87% with 1 ppm, 50 mg, pH 7, and 24 h] from water. This environmentally sustainable approach produces no toxic waste and allows for simple regeneration, making it a promising solution for the water treatment industry.
{"title":"Floating 3D-PDMS-Iron oxide molecular baskets for decontaminating diverse pollutants and analyzing structural composition impacts","authors":"Sethu Kalidhasan, Jonghoon Choi, Hee-Young Lee","doi":"10.1038/s41545-024-00419-1","DOIUrl":"10.1038/s41545-024-00419-1","url":null,"abstract":"Novel iron oxide-incorporated porous polydimethylsiloxane sponges were developed using a simple, non-toxic two-step process. Characterized through various techniques, these sponges serve as effective photocatalysts, absorbents, and adsorbents for pollutant removal. They demonstrated nearly 100% degradation of rhodamine B under optimal conditions ( ~ 100% with Xe arc lamp, 50 mg, pH 3-9, and 4 h), following a pseudo second-order kinetic model (r2 = 0.9999). The sponges also exhibited good activity for other pollutants, including methylene blue (76–87%), 1,4-dichlorobenzene (57–71%), and azithromycin (82–87%), and maintained high performance over 11 reuse cycles with minimal iron loss. In addition, fresh and used catalysts effectively separated oils (173–680 mg with 50 mg of absorbent, and 10–15 s) and chromium (VI) [~87% with 1 ppm, 50 mg, pH 7, and 24 h] from water. This environmentally sustainable approach produces no toxic waste and allows for simple regeneration, making it a promising solution for the water treatment industry.","PeriodicalId":19375,"journal":{"name":"npj Clean Water","volume":" ","pages":"1-11"},"PeriodicalIF":10.4,"publicationDate":"2024-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41545-024-00419-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142753777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-28DOI: 10.1038/s41545-024-00416-4
Mahdi Barati, Heidar Raissi, Afsaneh Ghahari
Antibiotic pollutants from pharmaceutical waste pose a severe threat to ecosystems. This study explores the use of gallium-metal organic frameworks (Ga-MOFs) and imide-functionalized MOFs (F-MOFs) for antibiotic removal through adsorption. Using molecular dynamics simulations, we evaluated the adsorption of amikacin (AMC), kanamycin (KMC), and tobramycin (TMC) on MOF and F-MOF surfaces. The simulation results suggest that these adsorbents could be effective in adsorbing a significant portion of these antibiotics. π-π stacking interactions contributed to strong binding between antibiotics and substrates. Additionally, metadynamics simulations revealed free energy minima of –254.29 KJ/mol for KMC/MOFs and –187.62 KJ/mol for KMC/F-MOFs, confirming complex stability. This theoretical approach highlights the potential of Ga-MOF-based materials in mitigating antibiotic pollution’s environmental and health impacts.
{"title":"Selectivity and morphological engineering of a unique gallium−organic framework for antibiotics exclusion in water","authors":"Mahdi Barati, Heidar Raissi, Afsaneh Ghahari","doi":"10.1038/s41545-024-00416-4","DOIUrl":"10.1038/s41545-024-00416-4","url":null,"abstract":"Antibiotic pollutants from pharmaceutical waste pose a severe threat to ecosystems. This study explores the use of gallium-metal organic frameworks (Ga-MOFs) and imide-functionalized MOFs (F-MOFs) for antibiotic removal through adsorption. Using molecular dynamics simulations, we evaluated the adsorption of amikacin (AMC), kanamycin (KMC), and tobramycin (TMC) on MOF and F-MOF surfaces. The simulation results suggest that these adsorbents could be effective in adsorbing a significant portion of these antibiotics. π-π stacking interactions contributed to strong binding between antibiotics and substrates. Additionally, metadynamics simulations revealed free energy minima of –254.29 KJ/mol for KMC/MOFs and –187.62 KJ/mol for KMC/F-MOFs, confirming complex stability. This theoretical approach highlights the potential of Ga-MOF-based materials in mitigating antibiotic pollution’s environmental and health impacts.","PeriodicalId":19375,"journal":{"name":"npj Clean Water","volume":" ","pages":"1-11"},"PeriodicalIF":10.4,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41545-024-00416-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142753773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-28DOI: 10.1038/s41545-024-00421-7
Suvidha Gupta, Jorge M. Marchetti
The study examined the feasibility of co-culturing high-value microalgae sp. (Chlorella vulgaris (C.), and Scenedesmus (S.)) with filamentous microalgae sp. (Tribonema (T.) and Lyngbya (L.)) to remediate dairy wastewater (DW) and enhance biomass production and harvesting. The results showed that biomass productivity increased by 12‒174% compared to monocultures, and the best consortium was S:T. This consortium achieved the highest biomass productivity of 84.25 mg L−1 d−1 while removing 86.7% of chemical oxygen demand (COD), >88.7% of NO3−-N and >98.5% of PO43–-P. The study also tested the effect of harvesting time on the accumulation of biochemical components and found the optimal harvesting times of day 9 and day 11 to achieve maximum carbohydrate and lipid productivity, respectively. Additionally, the microalgae consortium S:T achieved a high biomass recovery of 78.5%, compared to 32.4% obtained for S. alone, highlighting its potential for efficient DW remediation and resource recovery.
{"title":"Co-cultivation of high-value microalgae species with filamentous microalgae for dairy wastewater treatment","authors":"Suvidha Gupta, Jorge M. Marchetti","doi":"10.1038/s41545-024-00421-7","DOIUrl":"10.1038/s41545-024-00421-7","url":null,"abstract":"The study examined the feasibility of co-culturing high-value microalgae sp. (Chlorella vulgaris (C.), and Scenedesmus (S.)) with filamentous microalgae sp. (Tribonema (T.) and Lyngbya (L.)) to remediate dairy wastewater (DW) and enhance biomass production and harvesting. The results showed that biomass productivity increased by 12‒174% compared to monocultures, and the best consortium was S:T. This consortium achieved the highest biomass productivity of 84.25 mg L−1 d−1 while removing 86.7% of chemical oxygen demand (COD), >88.7% of NO3−-N and >98.5% of PO43–-P. The study also tested the effect of harvesting time on the accumulation of biochemical components and found the optimal harvesting times of day 9 and day 11 to achieve maximum carbohydrate and lipid productivity, respectively. Additionally, the microalgae consortium S:T achieved a high biomass recovery of 78.5%, compared to 32.4% obtained for S. alone, highlighting its potential for efficient DW remediation and resource recovery.","PeriodicalId":19375,"journal":{"name":"npj Clean Water","volume":" ","pages":"1-11"},"PeriodicalIF":10.4,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41545-024-00421-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142753771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-28DOI: 10.1038/s41545-024-00420-8
Alexandros Maziotis, Ramon Sala-Garrido, Manuel Mocholi-Arce, Maria Molinos-Senante
Understanding the water-energy-carbon nexus in water supply is essential for water regulators and utilities. This study employs a non-radial Data Envelopment Analysis (DEA) model to assess eco-productivity (ecoP) change, a synthetic indicator that integrates carbon emissions, energy costs, and water delivered. It also evaluates its components—eco-efficiency change and eco-technological change—across water companies in England and Wales from 2011 to 2018. The analysis reveals an annual improvement in ecoP of 1.1%, driven by a 2.1% gain in eco-efficiency but offset by a 1.0% decline in technological advancement. The reduction in GHG emissions emerged as the most significant positive contributor, enhancing ecoP by 3.22% annually, while energy costs detracted ecoP by –0.09%. The results underscore the negative impacts of increased water delivery (–1.74%) and the number of connected properties (–1.27%) on ecoP, highlighting the need for demand management policies.
{"title":"Understanding water-energy-carbon nexus in English and Welsh water industry by assessing eco-productivity of water companies","authors":"Alexandros Maziotis, Ramon Sala-Garrido, Manuel Mocholi-Arce, Maria Molinos-Senante","doi":"10.1038/s41545-024-00420-8","DOIUrl":"10.1038/s41545-024-00420-8","url":null,"abstract":"Understanding the water-energy-carbon nexus in water supply is essential for water regulators and utilities. This study employs a non-radial Data Envelopment Analysis (DEA) model to assess eco-productivity (ecoP) change, a synthetic indicator that integrates carbon emissions, energy costs, and water delivered. It also evaluates its components—eco-efficiency change and eco-technological change—across water companies in England and Wales from 2011 to 2018. The analysis reveals an annual improvement in ecoP of 1.1%, driven by a 2.1% gain in eco-efficiency but offset by a 1.0% decline in technological advancement. The reduction in GHG emissions emerged as the most significant positive contributor, enhancing ecoP by 3.22% annually, while energy costs detracted ecoP by –0.09%. The results underscore the negative impacts of increased water delivery (–1.74%) and the number of connected properties (–1.27%) on ecoP, highlighting the need for demand management policies.","PeriodicalId":19375,"journal":{"name":"npj Clean Water","volume":" ","pages":"1-12"},"PeriodicalIF":10.4,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41545-024-00420-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142753767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-27DOI: 10.1038/s41545-024-00406-6
Rongsheng Liu, Tarek Zayed, Rui Xiao
Detecting and mitigating leaks in water distribution networks are vital for water conservation. Machine-learning-based (ML) acoustic leak detection models were introduced as effective alternatives for leak management. However, ML model training requires sufficient labeled data, which hinders related development. To address this challenge, this study employed contrastive learning (CL) for leak detection using limited labeled signals. Experimental results indicate that flip-x and amplitude scaling are optimal combinations for contrastive learning. Besides, ablation and t-distributed stochastic neighbor embedding (t-SNE) results reveal that increasing the model depth does not always yield performance improvement, and five convolutional blocks are more suitable for the leak detection problem in this study. Comparison experiments demonstrate that contrastive learning outperforms supervised learning (SL) when trained with insufficient labeled data. The out-of-sample validation results indicate that the proposed leak detection model is robust and effective in unexplored pipelines. The proposed framework significantly advances ML-based leak detection research and supports sustainable water management practices.
{"title":"Contrastive learning method for leak detection in water distribution networks","authors":"Rongsheng Liu, Tarek Zayed, Rui Xiao","doi":"10.1038/s41545-024-00406-6","DOIUrl":"10.1038/s41545-024-00406-6","url":null,"abstract":"Detecting and mitigating leaks in water distribution networks are vital for water conservation. Machine-learning-based (ML) acoustic leak detection models were introduced as effective alternatives for leak management. However, ML model training requires sufficient labeled data, which hinders related development. To address this challenge, this study employed contrastive learning (CL) for leak detection using limited labeled signals. Experimental results indicate that flip-x and amplitude scaling are optimal combinations for contrastive learning. Besides, ablation and t-distributed stochastic neighbor embedding (t-SNE) results reveal that increasing the model depth does not always yield performance improvement, and five convolutional blocks are more suitable for the leak detection problem in this study. Comparison experiments demonstrate that contrastive learning outperforms supervised learning (SL) when trained with insufficient labeled data. The out-of-sample validation results indicate that the proposed leak detection model is robust and effective in unexplored pipelines. The proposed framework significantly advances ML-based leak detection research and supports sustainable water management practices.","PeriodicalId":19375,"journal":{"name":"npj Clean Water","volume":" ","pages":"1-13"},"PeriodicalIF":10.4,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41545-024-00406-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142753776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-26DOI: 10.1038/s41545-024-00412-8
Siyang Xing, Congle Li, Jialin Wang, Mengmeng Sun, Yingying Zhao, Yixing Gou, Panpan Zhang, Jingtao Bi
Adsorption capacity is a critical indicator of adsorbent performance, its assessment often requires precise but complicated measurements of adsorbate concentration in the liquid phase. This study presents a colorimetric sensing method based on a fabricated model for directly assessing the adsorption capacity of colored cations through the absorbance of the adsorbent. The exceptional analytical capability of the proposed method was demonstrated by the rapid determination of colored cation adsorption capacity in single-cation (Co(II), Ni(II), Cu(II), and U(VI)) systems, mixed-cation systems, and real wastewater samples. Additionally, a series of colorimetric cards have been developed to enable rapid and effective real-time monitoring of adsorption capacity in industrial production, resource extraction, wastewater treatment, and other applications. This research is expected to significantly enhance the methods available for adsorption capacity measurement.
{"title":"A colorimetric sensing method for direct determination of the adsorption capacity of colored cations in adsorbents","authors":"Siyang Xing, Congle Li, Jialin Wang, Mengmeng Sun, Yingying Zhao, Yixing Gou, Panpan Zhang, Jingtao Bi","doi":"10.1038/s41545-024-00412-8","DOIUrl":"10.1038/s41545-024-00412-8","url":null,"abstract":"Adsorption capacity is a critical indicator of adsorbent performance, its assessment often requires precise but complicated measurements of adsorbate concentration in the liquid phase. This study presents a colorimetric sensing method based on a fabricated model for directly assessing the adsorption capacity of colored cations through the absorbance of the adsorbent. The exceptional analytical capability of the proposed method was demonstrated by the rapid determination of colored cation adsorption capacity in single-cation (Co(II), Ni(II), Cu(II), and U(VI)) systems, mixed-cation systems, and real wastewater samples. Additionally, a series of colorimetric cards have been developed to enable rapid and effective real-time monitoring of adsorption capacity in industrial production, resource extraction, wastewater treatment, and other applications. This research is expected to significantly enhance the methods available for adsorption capacity measurement.","PeriodicalId":19375,"journal":{"name":"npj Clean Water","volume":" ","pages":"1-7"},"PeriodicalIF":10.4,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41545-024-00412-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142714710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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