Pub Date : 2024-10-30DOI: 10.1016/j.jclepro.2024.144120
An innovative eco-efficient capsule utilizing drinking water treatment sludge (DWTS) as a healing agent for concrete crack sealing was developed. In this study, the core materials comprised a mix of DWTS and calcium hydroxide, granulated by poly (ethylene glycol). A non-toxic polymer, Ethyl cellulose (EC), is applied as the protective shell material. The morphology, internal structure, and leakage mechanism of capsules, self-healing performance of cracked mortars and the composition of resulting healing products were assessed. Obtained results indicated that EC uniformly covered the spherical core material following the designed coating procedures. The main elements released from the capsules were Ca, Al and Si after dissolution of polyethylene glycol (PEG), which would contribute to pozzolanic reactions inside the matrix. Cracks with an initial width of 400 μm were completely healed after 7 days of curing. Such a healing process also led to an 73% enhancement in compressive strength at a healing age of 28 days. The water tightness of capsule-based samples improved by more than 90% in the first 7 days, compared to only 10% in control samples. The predominant healing products were calcium carbonate in the form of calcite, and some content of aluminium-bearing phases derived from the pozzolanic reaction of DWTS.
{"title":"An innovative sludge-derived capsule for self-healing cementitious materials","authors":"","doi":"10.1016/j.jclepro.2024.144120","DOIUrl":"10.1016/j.jclepro.2024.144120","url":null,"abstract":"<div><div>An innovative eco-efficient capsule utilizing drinking water treatment sludge (DWTS) as a healing agent for concrete crack sealing was developed. In this study, the core materials comprised a mix of DWTS and calcium hydroxide, granulated by poly (ethylene glycol). A non-toxic polymer, Ethyl cellulose (EC), is applied as the protective shell material. The morphology, internal structure, and leakage mechanism of capsules, self-healing performance of cracked mortars and the composition of resulting healing products were assessed. Obtained results indicated that EC uniformly covered the spherical core material following the designed coating procedures. The main elements released from the capsules were Ca, Al and Si after dissolution of polyethylene glycol (PEG), which would contribute to pozzolanic reactions inside the matrix. Cracks with an initial width of 400 μm were completely healed after 7 days of curing. Such a healing process also led to an 73% enhancement in compressive strength at a healing age of 28 days. The water tightness of capsule-based samples improved by more than 90% in the first 7 days, compared to only 10% in control samples. The predominant healing products were calcium carbonate in the form of calcite, and some content of aluminium-bearing phases derived from the pozzolanic reaction of DWTS.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":null,"pages":null},"PeriodicalIF":9.7,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
Pub Date : 2024-10-30DOI: 10.1016/j.jclepro.2024.144119
Recycle and reuse of waste asphalt materials is a key strategy for pavement sustainability and carbon reduction. Studies on the recycling agents or rejuvenators have produced fruitful findings but there is still an imperative need for a general principle/guideline on the compositional design of competent rejuvenators. Given the fact that the percentage and aggregation degree of asphaltenes are both increased upon aging, and considering that in theory rejuvenation should reverse such impacts, it is advocated in this study that rejuvenators ought to fulfill the dual functionality of diluting and dispersing asphaltenes. It is then proposed that rejuvenators should be formulated as a small proportion of asphaltene dispersants carried and distributed by a matrix of asphaltene diluents (or the so-called softeners), so as to diffuse into and soften the aged asphalt while in the meantime restoring the microstructural homogeneity by improving the colloidal dispersion. Preliminary verification of this concept was based on three rejuvenation schemes involving three selected additives representative of aromatic softeners as well as phenolic and ionic dispersants. Experimental investigations included rheological evaluations, and analytical characterizations consisting of infrared spectrum and gel permeation chromatography (GPC) analyses. Quantum chemical computations were conducted to probe the mechanisms underlying the different rejuvenating/dispersing performances by means of molecular descriptors in the framework of conceptual density functional theory (CDFT) and by inspecting the molecular interactions. The results suggested that by optimizing the respective dosages, the three rejuvenation schemes would all effectively restore the rheological performance in the full temperature range of interest. All the chemicals considered were physically blending with the aged asphalt without discernible signs of chemical reactions. Incorporation of either dispersant was able to reduce a significant proportion of the softener required while providing similar rejuvenating effectiveness as compared to using the softener alone, which was attributed to the improved asphaltene dispersion. Ranking of the dispersing capability among the three additives was in consistency with the strength of their interactions with the asphaltene. The cation-π and CH-anion interactions were identified as major contributors in the case of the ionic dispersant, and hydrogen bonding and π-π interactions for the phenolic dispersant. The great prospect demonstrated by the ionic additive in terms of high rejuvenating efficiency and significant environmental benefits warrants further investigation into this type of dispersants. It is anticipated that the findings would contribute to the scientific formulation of rejuvenators for improved pavement sustainability.
{"title":"Fulfilling the dual functionality for asphalt rejuvenator formulation: An experimental and computational exploration","authors":"","doi":"10.1016/j.jclepro.2024.144119","DOIUrl":"10.1016/j.jclepro.2024.144119","url":null,"abstract":"<div><div>Recycle and reuse of waste asphalt materials is a key strategy for pavement sustainability and carbon reduction. Studies on the recycling agents or rejuvenators have produced fruitful findings but there is still an imperative need for a general principle/guideline on the compositional design of competent rejuvenators. Given the fact that the percentage and aggregation degree of asphaltenes are both increased upon aging, and considering that in theory rejuvenation should reverse such impacts, it is advocated in this study that rejuvenators ought to fulfill the dual functionality of diluting and dispersing asphaltenes. It is then proposed that rejuvenators should be formulated as a small proportion of asphaltene dispersants carried and distributed by a matrix of asphaltene diluents (or the so-called softeners), so as to diffuse into and soften the aged asphalt while in the meantime restoring the microstructural homogeneity by improving the colloidal dispersion. Preliminary verification of this concept was based on three rejuvenation schemes involving three selected additives representative of aromatic softeners as well as phenolic and ionic dispersants. Experimental investigations included rheological evaluations, and analytical characterizations consisting of infrared spectrum and gel permeation chromatography (GPC) analyses. Quantum chemical computations were conducted to probe the mechanisms underlying the different rejuvenating/dispersing performances by means of molecular descriptors in the framework of conceptual density functional theory (CDFT) and by inspecting the molecular interactions. The results suggested that by optimizing the respective dosages, the three rejuvenation schemes would all effectively restore the rheological performance in the full temperature range of interest. All the chemicals considered were physically blending with the aged asphalt without discernible signs of chemical reactions. Incorporation of either dispersant was able to reduce a significant proportion of the softener required while providing similar rejuvenating effectiveness as compared to using the softener alone, which was attributed to the improved asphaltene dispersion. Ranking of the dispersing capability among the three additives was in consistency with the strength of their interactions with the asphaltene. The cation-π and CH-anion interactions were identified as major contributors in the case of the ionic dispersant, and hydrogen bonding and π-π interactions for the phenolic dispersant. The great prospect demonstrated by the ionic additive in terms of high rejuvenating efficiency and significant environmental benefits warrants further investigation into this type of dispersants. It is anticipated that the findings would contribute to the scientific formulation of rejuvenators for improved pavement sustainability.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":null,"pages":null},"PeriodicalIF":9.7,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142542065","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}
Pub Date : 2024-10-30DOI: 10.1016/j.jclepro.2024.144104
Ting Guo, Chaoke Bulin, Rongxiang Zheng
Selective recovery of rare earth elements is essential for both sustainable exploitation of rare earth resources and environmental remediation. Herein, Ce(Ⅲ) imprinted diethylenetriamine pentaacetic acid-polyethylenimine modified magnetic graphene oxide (IIP-DTPA-PEI-MGO) was fabricated for selective adsorption of Ce(Ⅲ). Adsorption efficiency and selectivity performance of IIP-DTPA-PEI-MGO towards Ce(Ⅲ) were evaluated via batch adsorption targeted at single and mixed solution, respectively. Adsorption mechanism was elucidated based on versatile adsorption fittings (isotherms, kinetics, thermodynamics) and spectroscopic tests (XPS, FTIR). Result presents, maximum adsorption efficiency of IIP-DTPA-PEI-MGO for Ce(III) is reached at pH = 5 in 30 min, demonstrating superior efficiency. The maximum mono layer adsorption capacity determined by the Langmuir model is 281.69 mg·g-1. After adsorption, 75.65 % of original Ce(Ⅲ) is transferred into Ce(Ⅳ), while 24.35 % remain as Ce(Ⅲ). Furthermore, by virtue of its paramagnetic property, IIP-DTPA-PEI-MGO can be easily recovered for cyclic adsorption, thereby keeping adsorption quantity 90.44 mg·g-1 on Ce(Ⅲ) in five consecutive cycles. Owing to ion imprinting sites, IIP-DTPA-PEI-MGO exhibits selectivity coefficient 1.34, 1.69, 2.32, 2.96, 15.24, 10.51 towards Ce(III) for binary solution Ce/La, Ce/Nd, Ce/Eu, Ce/Dy, Ce/Cu, Ce/Cr, respectively. In terms of adsorption mechanism, versatile functional groups O-H, C-N, C-O in IIP-DTPA-PEI-MGO provide heterogeneous affinity for Ce(Ⅲ), inducing chemical adsorption. This work provides a novel approach towards fabricating magnetic bio adsorbent for selective recovery of Ce(Ⅲ).
{"title":"Fabrication Of Ion Imprinted Diethylenetriamine Pentaacetic Acid-Polyethylenimine Modified Magnetic Graphene Oxide For Selective Adsorption Of Ce(III)","authors":"Ting Guo, Chaoke Bulin, Rongxiang Zheng","doi":"10.1016/j.jclepro.2024.144104","DOIUrl":"https://doi.org/10.1016/j.jclepro.2024.144104","url":null,"abstract":"Selective recovery of rare earth elements is essential for both sustainable exploitation of rare earth resources and environmental remediation. Herein, Ce(Ⅲ) imprinted diethylenetriamine pentaacetic acid-polyethylenimine modified magnetic graphene oxide (IIP-DTPA-PEI-MGO) was fabricated for selective adsorption of Ce(Ⅲ). Adsorption efficiency and selectivity performance of IIP-DTPA-PEI-MGO towards Ce(Ⅲ) were evaluated via batch adsorption targeted at single and mixed solution, respectively. Adsorption mechanism was elucidated based on versatile adsorption fittings (isotherms, kinetics, thermodynamics) and spectroscopic tests (XPS, FTIR). Result presents, maximum adsorption efficiency of IIP-DTPA-PEI-MGO for Ce(III) is reached at pH = 5 in 30 min, demonstrating superior efficiency. The maximum mono layer adsorption capacity determined by the Langmuir model is 281.69 mg·g<sup>-1</sup>. After adsorption, 75.65 % of original Ce(Ⅲ) is transferred into Ce(Ⅳ), while 24.35 % remain as Ce(Ⅲ). Furthermore, by virtue of its paramagnetic property, IIP-DTPA-PEI-MGO can be easily recovered for cyclic adsorption, thereby keeping adsorption quantity 90.44 mg·g<sup>-1</sup> on Ce(Ⅲ) in five consecutive cycles. Owing to ion imprinting sites, IIP-DTPA-PEI-MGO exhibits selectivity coefficient 1.34, 1.69, 2.32, 2.96, 15.24, 10.51 towards Ce(III) for binary solution Ce/La, Ce/Nd, Ce/Eu, Ce/Dy, Ce/Cu, Ce/Cr, respectively. In terms of adsorption mechanism, versatile functional groups O-H, C-N, C-O in IIP-DTPA-PEI-MGO provide heterogeneous affinity for Ce(Ⅲ), inducing chemical adsorption. This work provides a novel approach towards fabricating magnetic bio adsorbent for selective recovery of Ce(Ⅲ).","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142542062","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}
Pub Date : 2024-10-29DOI: 10.1016/j.jclepro.2024.144011
Madita Amoneit, Dagmara Weckowska, Stephanie Spahr, Olaf Wagner, Mohsen Adeli, Inka Mai, Rainer Haag
Green chemistry focuses on designing products and processes that minimize hazardous substances and address pollution, resource depletion, and climate change. Green chemistry products and processes could contribute to the transition to circular economy and reaching Sustainable Development Goals. However, green chemistry philosophy offers none or little guidance on social, ethical, economic, or political aspects that are inherent to complex transition processes. Such broad and future-oriented considerations are at the heart of ‘Responsible Research and Innovation’ (RRI) approach but to date the ideas of RRI and green chemistry remain largely unconnected. This study aims to shed light on how RRI and green chemistry approaches can be combined. A refined responsible roadmapping method is proposed to help researchers to go beyond the 12 principles of green chemistry and develop inter- and transdisciplinary research agendas that address technical, environmental as well as social, ethical, economic and political considerations. The method was piloted in three research projects aspiring to develop sustainable and safe chemical processes and their applications. The study demonstrates that at the early stage of research planning, the responsible roadmapping method can facilitate the integration of RRI and green chemistry practices and the development of interdisciplinary research plans, which address technical, environmental, socio-ethical, economic and political dimensions. The implications of our study for future research on roadmapping methods as well as for policy and innovation practice are discussed.
{"title":"Green Chemistry and Responsible Research and Innovation: Moving Beyond the 12 Principles","authors":"Madita Amoneit, Dagmara Weckowska, Stephanie Spahr, Olaf Wagner, Mohsen Adeli, Inka Mai, Rainer Haag","doi":"10.1016/j.jclepro.2024.144011","DOIUrl":"https://doi.org/10.1016/j.jclepro.2024.144011","url":null,"abstract":"Green chemistry focuses on designing products and processes that minimize hazardous substances and address pollution, resource depletion, and climate change. Green chemistry products and processes could contribute to the transition to circular economy and reaching Sustainable Development Goals. However, green chemistry philosophy offers none or little guidance on social, ethical, economic, or political aspects that are inherent to complex transition processes. Such broad and future-oriented considerations are at the heart of ‘Responsible Research and Innovation’ (RRI) approach but to date the ideas of RRI and green chemistry remain largely unconnected. This study aims to shed light on how RRI and green chemistry approaches can be combined. A refined responsible roadmapping method is proposed to help researchers to go beyond the 12 principles of green chemistry and develop inter- and transdisciplinary research agendas that address technical, environmental as well as social, ethical, economic and political considerations. The method was piloted in three research projects aspiring to develop sustainable and safe chemical processes and their applications. The study demonstrates that at the early stage of research planning, the responsible roadmapping method can facilitate the integration of RRI and green chemistry practices and the development of interdisciplinary research plans, which address technical, environmental, socio-ethical, economic and political dimensions. The implications of our study for future research on roadmapping methods as well as for policy and innovation practice are discussed.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142542058","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}
Pub Date : 2024-10-29DOI: 10.1016/j.jclepro.2024.144099
Fanbo Li, Hongfeng Zhang
This study explores the impact of green supply chain management on corporate performance, focusing on environmental, economic, operational, and social outcomes. Using Meta-Analytic Structural Equation Modeling, we analyzed data from 98 quantitative studies conducted since 2001. Our findings demonstrate that green supply chain management practices significantly enhance corporate performance. We also identify key moderating factors, such as industry diversity, company size, geographical location, economic development, cultural level, and logistics performance, that influence the effectiveness of green supply chain management. The study highlights the importance of tailoring green supply chain management initiatives to specific industry and regional contexts, providing actionable insights and policy recommendations for promoting sustainable development in the Carbon Trading Era.
{"title":"The impact of green supply chain management on corporate performance under the full process model: A MASEM analysis based on heterogeneous moderation","authors":"Fanbo Li, Hongfeng Zhang","doi":"10.1016/j.jclepro.2024.144099","DOIUrl":"https://doi.org/10.1016/j.jclepro.2024.144099","url":null,"abstract":"This study explores the impact of green supply chain management on corporate performance, focusing on environmental, economic, operational, and social outcomes. Using Meta-Analytic Structural Equation Modeling, we analyzed data from 98 quantitative studies conducted since 2001. Our findings demonstrate that green supply chain management practices significantly enhance corporate performance. We also identify key moderating factors, such as industry diversity, company size, geographical location, economic development, cultural level, and logistics performance, that influence the effectiveness of green supply chain management. The study highlights the importance of tailoring green supply chain management initiatives to specific industry and regional contexts, providing actionable insights and policy recommendations for promoting sustainable development in the Carbon Trading Era.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541771","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}
Pub Date : 2024-10-29DOI: 10.1016/j.jclepro.2024.144056
Electric vehicles (EVs) sales have grown rapidly recently, and more growth is expected over the coming years. A challenging problem arises when managing different battery requirements of moving EVs through reliable Charging Stations (CSs). Current concerns for EV users are long waiting lines at CSs and dropping below a predefined battery capacity limit. For this reason, this paper proposes an Internet of Things (IoT)-based EV charging scheduling system, which with the use of IoT technologies, decides the optimal assignment between EVs and Charging Points (CPs) located at different CSs at given time t. By using cloud computing and real time data such as number of EVs, number of CSs, number of CPs at different CSs … etc; the scheduling controller uses a recursive algorithm to generate all possible scenarios, and then shares the optimal assignment (that minimizes the average waiting time and fulfill battery constraints and charging needs) with all EVs. To test the validity of the IOT based scheduling system, sensitivity analysis by running different scenarios (pertaining to different parameters) was conducted. The different scenarios were compared to a base scenario where the system was not used and real-life random assignment is considered. The different run scenarios show superiority over the base scenario in terms of average waiting time (WT) and battery capacity threshold. For example, in the base scenario, violation of battery capacity threshold occurred 9.1% of the time, making random selection an unreliable choice versus no violations when the IOT scheduling system is used. Also, all tested scenarios under the IOT scheduling system show shorter average WT compared to the base scenario. For instance, scenarios 2 and 3 show more than 35% and 55% decrease in WT compared to the base scenario.
{"title":"Electric vehicles charging infrastructure framework using internet of things","authors":"","doi":"10.1016/j.jclepro.2024.144056","DOIUrl":"10.1016/j.jclepro.2024.144056","url":null,"abstract":"<div><div>Electric vehicles (EVs) sales have grown rapidly recently, and more growth is expected over the coming years. A challenging problem arises when managing different battery requirements of moving EVs through reliable Charging Stations (CSs). Current concerns for EV users are long waiting lines at CSs and dropping below a predefined battery capacity limit. For this reason, this paper proposes an Internet of Things (IoT)-based EV charging scheduling system, which with the use of IoT technologies, decides the optimal assignment between EVs and Charging Points (CPs) located at different CSs at given time t. By using cloud computing and real time data such as number of EVs, number of CSs, number of CPs at different CSs … etc; the scheduling controller uses a recursive algorithm to generate all possible scenarios, and then shares the optimal assignment (that minimizes the average waiting time and fulfill battery constraints and charging needs) with all EVs. To test the validity of the IOT based scheduling system, sensitivity analysis by running different scenarios (pertaining to different parameters) was conducted. The different scenarios were compared to a base scenario where the system was not used and real-life random assignment is considered. The different run scenarios show superiority over the base scenario in terms of average waiting time (WT) and battery capacity threshold. For example, in the base scenario, violation of battery capacity threshold occurred 9.1% of the time, making random selection an unreliable choice versus no violations when the IOT scheduling system is used. Also, all tested scenarios under the IOT scheduling system show shorter average WT compared to the base scenario. For instance, scenarios 2 and 3 show more than 35% and 55% decrease in WT compared to the base scenario.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":null,"pages":null},"PeriodicalIF":9.7,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536602","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}
Pub Date : 2024-10-29DOI: 10.1016/j.jclepro.2024.144111
Solid waste management (SWM) is an interdisciplinary field which requires a range of metrics to make informed decisions. Social indicators are of high interest to decision-makers but are particularly difficult to integrate into optimization frameworks, largely due to challenges of quantification. This study presents a methodology for quantifying a social metric for integration into sustainability assessment of solid waste management (SWM) systems using optimization. To identify social indicators, waste managers were consulted in Columbia, Missouri, USA. Meetings were held prior to indicator creation and reviewed mid-project with stakeholders. A number of concerns that could be categorized as social were raised. For the two most pressing issues to managers, quantitative metrics were created. First, SWM experiences high employee turnover, largely due to low wages. Turnover leads to less efficiency in collection and treatment, gaps in service, and cost to citizens. Hence, the first social metric proposed represents turnover of employees including loss of productivity, hiring and replacement costs, and quit rate. Second, this work estimated the value of exposure risk associated with manual material handling activities. This second social metric considered a worker's physical exposure to risk via activities of lifting, carrying, placing, emptying, and sitting. These social metrics were used within a multi-criterion decision-making framework for SWM, extending the traditional focus on economic and environmental objective functions. Results illustrate the trade-offs among these conflicting criteria and provide managerial insights into the costs and benefits of different waste management strategies.
{"title":"Quantification of social metrics for use in optimization: An application to solid waste management","authors":"","doi":"10.1016/j.jclepro.2024.144111","DOIUrl":"10.1016/j.jclepro.2024.144111","url":null,"abstract":"<div><div>Solid waste management (SWM) is an interdisciplinary field which requires a range of metrics to make informed decisions. Social indicators are of high interest to decision-makers but are particularly difficult to integrate into optimization frameworks, largely due to challenges of quantification. This study presents a methodology for quantifying a social metric for integration into sustainability assessment of solid waste management (SWM) systems using optimization. To identify social indicators, waste managers were consulted in Columbia, Missouri, USA. Meetings were held prior to indicator creation and reviewed mid-project with stakeholders. A number of concerns that could be categorized as social were raised. For the two most pressing issues to managers, quantitative metrics were created. First, SWM experiences high employee turnover, largely due to low wages. Turnover leads to less efficiency in collection and treatment, gaps in service, and cost to citizens. Hence, the first social metric proposed represents turnover of employees including loss of productivity, hiring and replacement costs, and quit rate. Second, this work estimated the value of exposure risk associated with manual material handling activities. This second social metric considered a worker's physical exposure to risk via activities of lifting, carrying, placing, emptying, and sitting. These social metrics were used within a multi-criterion decision-making framework for SWM, extending the traditional focus on economic and environmental objective functions. Results illustrate the trade-offs among these conflicting criteria and provide managerial insights into the costs and benefits of different waste management strategies.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":null,"pages":null},"PeriodicalIF":9.7,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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}
Pub Date : 2024-10-29DOI: 10.1016/j.jclepro.2024.144087
This work presents, for the first time, the development of magnetic composites using activated biochar (BC-Act) derived from yerba mate waste. It includes an analysis of the effect of the activation process on the formation of iron oxides using the most applied methodologies, an aspect that has not been studied before. Three methodologies have been considered for Fe oxides grown: coprecipitation (COP), impregnation-pyrolysis (IP), and alkaline oxidation in the presence of nitrates (AOPN). The materials with magnetic response and good enough BET area have been used to sorb Paracetamol (PCT) and Atenolol (ATE) from aqueous solutions. The activation process has resulted in the formation of mesopores, an increase of surface area due to the destruction/release of impurities, the transformation of whewellite to calcite, and changes in magnetic behavior. These changes seem to affect the formation of Fe oxides. The COP and IP methods allow the development of magnetic composites based on BC-Act, BC-Act-COP and BC-Act-IP, with saturation magnetization of 3.1 Am2/kg and 1.5 Am2/kg, respectively, attributed to magnetite/maghemite formation and a minimal distance for manipulation by a magnetic field of 12.1 mm and 7.9 mm, respectively. These distances must be considered when developing efficient removal systems using magnetic composites. PCT was sorbed faster and more efficiently than ATE, associated with its smaller molecular size. This presents a valuable contribution to environmental sustainability and advancements in water purification, highlighting the dual advantage of converting the widely available waste product, predominantly found in South America, into an effective sorbent with magnetic characteristics, capable of removing pharmaceutical contaminants from aqueous solutions. This is done in the circular economy, avoiding the final deposition of yerba mate waste in landfills, increasing their lifespan, and safeguarding other natural and non-renewable resources, such as clays, whose preservation rather than exploitation improves environmental quality and saves energy.
这项研究首次介绍了利用从叶巴伴侣废料中提取的活化生物炭（BC-Act）开发磁性复合材料的情况。其中包括使用最常用的方法分析活化过程对铁氧化物形成的影响，这是以前从未研究过的方面。研究考虑了三种铁氧化物生长方法：共沉淀法（COP）、浸渍-热解法（IP）和硝酸盐存在下的碱性氧化法（AOPN）。这些材料具有磁性响应和足够好的 BET 面积，已被用于从水溶液中吸附扑热息痛（PCT）和阿替洛尔（ATE）。活化过程导致中孔的形成，杂质的破坏/释放导致比表面积的增加，麦饭石转变为方解石，以及磁性行为的变化。这些变化似乎影响了铁氧化物的形成。采用 COP 和 IP 方法可以开发出基于 BC-Act、BC-Act-COP 和 BC-Act-IP 的磁性复合材料，其饱和磁化率分别为 3.1 Am2/kg 和 1.5 Am2/kg，这归因于磁铁矿/方镁石的形成，以及磁场操纵的最小距离分别为 12.1 mm 和 7.9 mm。在开发使用磁性复合材料的高效去除系统时，必须考虑这些距离。与 ATE 相比，PCT 的吸附速度更快、效率更高，这与其分子尺寸更小有关。这为环境的可持续发展和水净化的进步做出了宝贵的贡献，凸显了将广泛存在于南美洲的废品转化为具有磁性特征的有效吸附剂的双重优势，能够去除水溶液中的药物污染物。这是在循环经济中实现的，避免了耶巴马黛茶废弃物在垃圾填埋场的最终沉积，延长了其使用寿命，并保护了粘土等其他不可再生的自然资源。
{"title":"Fe oxide modification of yerba mate waste-derived biochar and activated biochar via three methodologies: Effects of material surface properties on the Fe oxides grown and implications for paracetamol and atenolol sorption","authors":"","doi":"10.1016/j.jclepro.2024.144087","DOIUrl":"10.1016/j.jclepro.2024.144087","url":null,"abstract":"<div><div>This work presents, for the first time, the development of magnetic composites using activated biochar (BC-Act) derived from yerba mate waste. It includes an analysis of the effect of the activation process on the formation of iron oxides using the most applied methodologies, an aspect that has not been studied before. Three methodologies have been considered for Fe oxides grown: coprecipitation (COP), impregnation-pyrolysis (IP), and alkaline oxidation in the presence of nitrates (AOPN). The materials with magnetic response and good enough BET area have been used to sorb Paracetamol (PCT) and Atenolol (ATE) from aqueous solutions. The activation process has resulted in the formation of mesopores, an increase of surface area due to the destruction/release of impurities, the transformation of whewellite to calcite, and changes in magnetic behavior. These changes seem to affect the formation of Fe oxides. The COP and IP methods allow the development of magnetic composites based on BC-Act, BC-Act-COP and BC-Act-IP, with saturation magnetization of 3.1 Am<sup>2</sup>/kg and 1.5 Am<sup>2</sup>/kg, respectively, attributed to magnetite/maghemite formation and a minimal distance for manipulation by a magnetic field of 12.1 mm and 7.9 mm, respectively. These distances must be considered when developing efficient removal systems using magnetic composites. PCT was sorbed faster and more efficiently than ATE, associated with its smaller molecular size. This presents a valuable contribution to environmental sustainability and advancements in water purification, highlighting the dual advantage of converting the widely available waste product, predominantly found in South America, into an effective sorbent with magnetic characteristics, capable of removing pharmaceutical contaminants from aqueous solutions. This is done in the circular economy, avoiding the final deposition of yerba mate waste in landfills, increasing their lifespan, and safeguarding other natural and non-renewable resources, such as clays, whose preservation rather than exploitation improves environmental quality and saves energy.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":null,"pages":null},"PeriodicalIF":9.7,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541772","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}
Pub Date : 2024-10-29DOI: 10.1016/j.jclepro.2024.144114
A simple hydrothermal method was used to prepare the single-metal atom oxide (SMAO) catalyst. The prepared dual Cobalt and tungsten (CoW) single metal atom oxide anchored on the TiO2-Bi2MoO6-reduced graphene oxide (rGO), an interstitial atomic line of tungsten and cobalt. The prepared photocatalyst showed good photocatalytic hydrogen (H2) evolution and organic contaminant degradation. As co-catalysts, surface-dispersed CoW sites were created using a Co mono-substituted hetero-polyacid (HPA-Co). A larger quantity of single atoms were uniformly decorated on the TiO2-Bi2MoO6-Ethylenediamine (ED)-rGO catalyst. The presence of the CoW species was verified employing extended X-ray absorption near edge structure (XANES), high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), and extended X-ray absorption fine structure (EXAFS) analyses after a TiO2-Bi2MoO6-CoW-ED-rGO composite synthesized. The findings demonstrate that TiO2-Bi2MoO6-CoW-ED-rGO catalysts were more capable of producing hydrogen and degrading Ciprofloxacin (CIP) (21.46 mmol/g/h, 97.2%) than other bare and binary catalysts. Furthermore, it showed remarkable stability and reusability after five consecutive CIP photodegradation and H2 production cycles. Gas chromatography/mass spectroscopy (GC/MS) techniques were used to identify the intermediates in the photodegradation process. The prepared photocatalyst was significantly increased, and the separation of charge carriers was further boosted, thanks to the CoW material and the synergistic effect. A possible Z-scheme mechanism was proposed for the photocatalytic H2 production activity. More electrons can contribute to the reduction of H2 evolution because of the processability of the Z-scheme. This work created a recyclable, inexpensive, highly effective, and non-toxic catalytic material for H2 generation and CIP degradation.
采用简单的水热法制备了单金属原子氧化物（SMAO）催化剂。所制备的钴和钨（CoW）双金属单原子氧化物锚定在 TiO2-Bi2MoO6 还原型氧化石墨烯（rGO）（钨和钴的原子间隙线）上。所制备的光催化剂具有良好的光催化氢（H2）进化和有机污染物降解性能。作为助催化剂，使用 Co 单取代杂多酸（HPA-Co）创建了表面分散的 CoW 位点。在 TiO2-Bi2MoO6-Ethylenediamine (ED)-rGO 催化剂上均匀地装饰了大量的单原子。在合成了 TiO2-Bi2MoO6-CoW-ED-rGO 复合材料后，利用扩展 X 射线吸收近边缘结构 (XANES)、高角度环形暗场扫描透射电子显微镜 (HAADF-STEM) 和扩展 X 射线吸收精细结构 (EXAFS) 分析验证了 CoW 物种的存在。研究结果表明，与其他裸催化剂和二元催化剂相比，TiO2-Bi2MoO6-CoW-ED-rGO 催化剂更能产生氢气和降解环丙沙星（CIP）（21.46 mmol/g/h，97.2%）。此外，该催化剂在连续进行五次 CIP 光降解和 H2 生产循环后，表现出卓越的稳定性和可重复使用性。气相色谱/质谱（GC/MS）技术用于鉴定光降解过程中的中间产物。得益于 CoW 材料和协同效应，所制备的光催化剂显著提高了电荷载流子的分离能力。研究人员提出了光催化产生 H2 活性的一种可能的 Z 型机制。由于 Z 型方案的可加工性，更多电子可促进减少 H2 的演化。这项工作创造了一种可回收、廉价、高效、无毒的催化材料，用于产生 H2 和降解 CIP。
{"title":"Effective photocatalytic hydrogen generation and degradation for single cobalt and tungsten metal atom oxide anchored on titanium dioxide-bismuth molybdate-reduced graphene oxide","authors":"","doi":"10.1016/j.jclepro.2024.144114","DOIUrl":"10.1016/j.jclepro.2024.144114","url":null,"abstract":"<div><div>A simple hydrothermal method was used to prepare the single-metal atom oxide (SMAO) catalyst. The prepared dual Cobalt and tungsten (CoW) single metal atom oxide anchored on the TiO<sub>2</sub>-Bi<sub>2</sub>MoO<sub>6</sub><strong>-</strong>reduced graphene oxide (rGO), an interstitial atomic line of tungsten and cobalt. The prepared photocatalyst showed good photocatalytic hydrogen (H<sub>2</sub>) evolution and organic contaminant degradation. As co-catalysts, surface-dispersed CoW sites were created using a Co mono-substituted hetero-polyacid (HPA-Co). A larger quantity of single atoms were uniformly decorated on the TiO<sub>2</sub>-Bi<sub>2</sub>MoO<sub>6</sub>-Ethylenediamine (ED)-rGO catalyst. The presence of the CoW species was verified employing extended X-ray absorption near edge structure (XANES), high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), and extended X-ray absorption fine structure (EXAFS) analyses after a TiO<sub>2</sub>-Bi<sub>2</sub>MoO<sub>6</sub>-CoW-ED-rGO composite synthesized. The findings demonstrate that TiO<sub>2</sub>-Bi<sub>2</sub>MoO<sub>6</sub>-CoW-ED-rGO catalysts were more capable of producing hydrogen and degrading Ciprofloxacin (CIP) (21.46 mmol/g/h, 97.2%) than other bare and binary catalysts. Furthermore, it showed remarkable stability and reusability after five consecutive CIP photodegradation and H<sub>2</sub> production cycles. Gas chromatography/mass spectroscopy (GC/MS) techniques were used to identify the intermediates in the photodegradation process. The prepared photocatalyst was significantly increased, and the separation of charge carriers was further boosted, thanks to the CoW material and the synergistic effect. A possible Z-scheme mechanism was proposed for the photocatalytic H<sub>2</sub> production activity. More electrons can contribute to the reduction of H<sub>2</sub> evolution because of the processability of the Z-scheme. This work created a recyclable, inexpensive, highly effective, and non-toxic catalytic material for H<sub>2</sub> generation and CIP degradation.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":null,"pages":null},"PeriodicalIF":9.7,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541770","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}
Pub Date : 2024-10-29DOI: 10.1016/j.jclepro.2024.144112
Fatemeh Faal, Mohammad Reza Nikoo, Seyed Mohammad Ashrafi, Jirka Simunek
Groundwater vulnerability maps are crucial for safeguarding groundwater quality. A research gap exists in using advanced data fusion techniques to identify areas subject to seawater intrusion. To address this gap, this research enhances the GALDIT method and applies diverse deep learning models, combined with machine learning techniques, to improve the precision of aquifer vulnerability mapping. The new GALDITMW model incorporates the seawater mixing index and the parameters related to the production well density and aquifer porous medium. For the first time, supervised and unsupervised deep learning models, such as deep neural networks, deep belief networks, deep stacked autoencoders, and convolutional neural networks, are used for vulnerability mapping. In the second stage, the results of various machine learning models are fused to improve performance. The models' effectiveness is evaluated using a vulnerability index based on total dissolved solids (TDS) in an aquifer hydraulically connected with Salt Lake in central Iran, which faces groundwater depletion and salinization. The evaluation of the models based on performance metrics and the confusion matrix demonstrates that initial deep-learning models perform well. Significant improvements were observed in the second stage involving machine learning models, confirming their strong correlation (R2 > 0.985) with observed chloride values. The GPR model achieved an F1 score of 86.92%, an NSE of 0.911, and an RMSE reduction of 0.026 mg/L compared to the first-stage models. The proposed method offers a novel and accurate method for identifying vulnerable areas and provides helpful information for groundwater resource management.
{"title":"Advancing Aquifer Vulnerability Mapping through Integrated Deep Learning Approaches","authors":"Fatemeh Faal, Mohammad Reza Nikoo, Seyed Mohammad Ashrafi, Jirka Simunek","doi":"10.1016/j.jclepro.2024.144112","DOIUrl":"https://doi.org/10.1016/j.jclepro.2024.144112","url":null,"abstract":"Groundwater vulnerability maps are crucial for safeguarding groundwater quality. A research gap exists in using advanced data fusion techniques to identify areas subject to seawater intrusion. To address this gap, this research enhances the GALDIT method and applies diverse deep learning models, combined with machine learning techniques, to improve the precision of aquifer vulnerability mapping. The new GALDITMW model incorporates the seawater mixing index and the parameters related to the production well density and aquifer porous medium. For the first time, supervised and unsupervised deep learning models, such as deep neural networks, deep belief networks, deep stacked autoencoders, and convolutional neural networks, are used for vulnerability mapping. In the second stage, the results of various machine learning models are fused to improve performance. The models' effectiveness is evaluated using a vulnerability index based on total dissolved solids (TDS) in an aquifer hydraulically connected with Salt Lake in central Iran, which faces groundwater depletion and salinization. The evaluation of the models based on performance metrics and the confusion matrix demonstrates that initial deep-learning models perform well. Significant improvements were observed in the second stage involving machine learning models, confirming their strong correlation (R<sup>2</sup> > 0.985) with observed chloride values. The GPR model achieved an F1 score of 86.92%, an NSE of 0.911, and an RMSE reduction of 0.026 mg/L compared to the first-stage models. The proposed method offers a novel and accurate method for identifying vulnerable areas and provides helpful information for groundwater resource management.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":null,"pages":null},"PeriodicalIF":11.1,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142519930","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}
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