Green Technologies and Sustainability最新文献

{"title":"A review on value addition of Agricultural Residues by Chemical and Bio-chemical Processes to abate environmental pollution","authors":"Kalpana Polipalli ,&nbsp;Sharanya Suraboyina ,&nbsp;Monika Kashimalla ,&nbsp;Anand Polumati","doi":"10.1016/j.grets.2025.100241","DOIUrl":"10.1016/j.grets.2025.100241","url":null,"abstract":"<div><div>Agricultural residues, such as crop straws, husks, leaves, and stems, are generated in significant quantities globally, often contributing to environmental pollution when improperly managed. The sustainable utilization of agricultural residues has become a paramount focus in the pursuit of a circular and resource-efficient economy. This review paper provides an extensive analysis of the current state-of-the-art methodologies for extracting value from agricultural residues through chemical/biochemical pretreatment methods. This review explores the potential for adding value to these residues through various chemical and biochemical processes, aiming to mitigate their environmental impact. Chemical processes, including pyrolysis, gasification, combustion, and transesterification, convert biomass into biochar, bio-oil, syngas, and biodiesel, respectively. Biochemical processes, such as anaerobic digestion, fermentation, composting, and enzymatic hydrolysis, produce biogas, biofuels, and soil amendments. These methods not only reduce greenhouse gas emissions and improve waste management but also enhance soil health and promote a circular economy. Despite challenges in technological development, policy support, and public awareness, the integration of these processes within biorefineries holds promise for maximizing resource efficiency and sustainability. This review underscores the importance of continued research and innovation in transforming agricultural residues into valuable products for environmental and economic benefits.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"3 4","pages":"Article 100241"},"PeriodicalIF":0.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144604958","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}

{"title":"A review of non-edible indigenous seeds feedstock in Bangladesh for biodiesel: Production, fuel properties and combustions performance","authors":"Ehsanul Hoque ,&nbsp;Md Ismail Hossen Emon ,&nbsp;Md Tawfiq Anik ,&nbsp;Mohammad Ariful Islam ,&nbsp;Ikramul Hasan ,&nbsp;Tanvir Ahmed ,&nbsp;Zia Ullah Arif ,&nbsp;Mokarram Hossain ,&nbsp;Mohammad Ismail","doi":"10.1016/j.grets.2025.100240","DOIUrl":"10.1016/j.grets.2025.100240","url":null,"abstract":"<div><div>The demand for energy has been escalating daily due to rapid population growth and economic expansion. Heavy reliance on non-renewable energy sources causes significant environmental harm and results in high costs, making renewable resources essential. Biodiesel, a non-toxic and environmentally friendly fuel, closely resembles conventional fossil fuels. It is derived from renewable sources such as palm oil, animal fats, and non-edible seeds. Biodiesel offers notable benefits, including reduced generation of greenhouse gases (GHGs) and hazardous air pollutants. Despite these advantages, widespread adoption of biodiesel remains challenging. This study explores the various non-edible seeds obtained from indigenous plants in Bangladesh, physico-chemical properties of these extracted oil, biodiesel production, and their engine performance study. Among the reported fifteen seeds, the oil content was found to be the highest in Eucalyptus seed (50%–60%), followed by Jatropha, Rubber, Mahua and so on. Stearic acid (C18:0), Oleic acid (C18:1) and Linoleic acid (C18:2) were commonly found in all the seeds whereas the maximum content of palmitic acid and Oleic acid was found in cotton seed oil. The biodiesel yield during the trans-esterification process was found about 95%. A Biodiesel blend of 15%–20% with commercial diesel was found acceptable for smooth performance of the existing engines. The emission of CO, hydrocarbons, smokes etc. reduced by 10%–50% while using biodiesel blend whereas the emissions of CO₂ and in some cases, NOx increased by 10%–20% more than that of the commercial diesel.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"3 4","pages":"Article 100240"},"PeriodicalIF":0.0,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597354","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}

{"title":"Adaptive Neuro-Fuzzy Inference System-Genetic Algorithm approach for global maximum power point tracking in PV systems under different shading conditions","authors":"Nivine Guler ,&nbsp;Zied Ben Hazem ,&nbsp;Ali Gunes ,&nbsp;Firas Saidi","doi":"10.1016/j.grets.2025.100239","DOIUrl":"10.1016/j.grets.2025.100239","url":null,"abstract":"<div><div>Photovoltaic (PV) panels have become popular energy sources; nonetheless, when under partial shading, their efficiency greatly reduces because of the occurrence of several power peaks or spikes arising because of the variation in irradiance. An inherent problem with most conventional global maximum power point tracking (GMPPT) algorithms is that they do not distinguish local and global peaks, and thus energy extraction may not be optimal. To eliminate this, this paper proposes an Adaptive Neuro-Fuzzy Inference System-Genetic Algorithm (ANFIS-GA) solution in improving the GMPPT performance under diverse shading conditions. The ANFIS is ideal in modeling the nonlinearity and uncertain nature of PV systems; the Genetic Algorithm (GA) then dynamically determines the optimal Proportional–Integral–Derivative (PID) controller parameters by minimizing the error between the actual power output and the maximum power output calculated in ANFIS. This means that this controller can respond to nonlinear and time-varying nature of a DC–DC SEPIC converter, enhancing response time and stability in various operating conditions. The proposed ANFIS-GA method, simulated with MATLAB/Simulink, was evaluated in three environments, i.e., no shading, partial shading, and severe shading, and performances were 99.98%, 98.5%, and 97.67% (GMPPT efficiencies), respectively. Besides, a comparative test to ANFIS-only systems at 400 W/m², 700 W/m², and 1000 W/m² also revealed that the hybrid methodology better tracked the global peak particularly in an oscillating environment. Furthermore, to test the strength of the controller, time-varying irradiance profiles that would simulate the real-world cloud motions using randomized step-wise changes are applied to it. The system sustained efficiencies better than 98.5% in such difficult conditions using convergence times that were below 0.25 s. These findings support that the ANFIS-GA approach has a high degree of flexibility, accuracy, and consistency, and it is thus an effective method in improving PV performance in a complex and dynamically varied systems.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"3 4","pages":"Article 100239"},"PeriodicalIF":0.0,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144604957","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}

{"title":"Techno-economic analysis of cement-based composite mortars for energy-efficient buildings","authors":"Jeanne Leclerc,&nbsp;Abdul Wasy Zia","doi":"10.1016/j.grets.2025.100238","DOIUrl":"10.1016/j.grets.2025.100238","url":null,"abstract":"<div><div>This article explores thermal insulating cement-based mortars in aspiration of increasing demand for sustainable materials to improve building energy efficiency. Cement mortars are widely used around the globe, and integrating lightweight and insulating aggregates such as sand replacements offers better energy efficiency and minimize energy losses in buildings. The techno-economic analysis in this work evaluates composite mortars by incorporating aerogel, expanded clay, and expanded polystyrene aggregates, in line with European standards EN998-1. Their performance is assessed as a function of percentage sand replacement, thermal conductivity, compressive strength, density, and cost. Integrating insulating aggregates reduces compressive strength and density, impacting mechanical resistance and structural weight. Therefore, this analysis identifies the optimal material composition by replacing sand with 67% aerogel and 100% expanded clay and expanded polystyrene to maintain a balance between thermal and mechanical performance. It is perceived that the aerogel exhibits the best insulation properties, but they are the most expensive candidate. The techno-economic analysis also examines the optimal thickness, revealing that expanded polystyrene can reduce energy consumption by up to 86% at the break-even point, though it requires an impractically thick layer of over 8 cm. The decision support system developed in this study recommends expanded polystyrene as the most cost-effective option for achieving 50% energy savings and CO₂ reduction of up to 68%.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"3 4","pages":"Article 100238"},"PeriodicalIF":0.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144489699","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}

{"title":"Blockchain’s role in environmental sustainability: Bibliometric insights from scopus","authors":"Ganesh D. Bhatt ,&nbsp;Ali Emdad","doi":"10.1016/j.grets.2025.100236","DOIUrl":"10.1016/j.grets.2025.100236","url":null,"abstract":"<div><div>Blockchain technology is increasingly acknowledged as a transformative tool for advancing environmental sustainability. Although blockchain has the potential to enhance transparency, trust, and accountability, research on blockchain’s sustainability applications remains fragmented with inconsistent methodologies and limited integration of theoretical frameworks. One major barrier to achieving sustainability goals is the lack of standardized verification systems, which hinders regulatory oversight and consistent assessment of environmental claims. This study employs bibliometric analysis using the Scopus database and analytical tools such as VOSviewer to systematically examine the research landscape. By identifying key trends, influential authors, and thematic research clusters, this study synthesizes blockchain’s roles in environmental sustainability. Our findings indicate that blockchain strengthens data integrity, enhances sustainability reporting, and promotes stakeholder collaboration across environmental sectors. However, challenges such as scalability, energy-intensive consensus mechanisms, and regulatory uncertainty persist. This study contributes to the literature by clarifying foundational concepts, identifying research gaps, and proposing directions for future work in blockchain-based sustainability frameworks.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"3 4","pages":"Article 100236"},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144471017","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}

{"title":"Exploring the impact of income, aquaculture production, protein supply, and food production on life expectancy","authors":"Salma Akter ,&nbsp;Funda Kaya ,&nbsp;Shaharier Arafat Sumon ,&nbsp;Md Mahedi Hassan ,&nbsp;Mihir Kumar Das","doi":"10.1016/j.grets.2025.100237","DOIUrl":"10.1016/j.grets.2025.100237","url":null,"abstract":"<div><div>Life expectancy is a key indicator of health and well-being, particularly in countries where fishery exports play a major economic role. However, limited studies have explored how aquaculture production, protein supply, and income levels interact to shape health outcomes. This study examines the impact of aquaculture production, protein consumption, income, and food production on life expectancy in the top 12 fish-exporting nations. Data from the World Bank and the OECD Stat were utilized in this cross-sectional study. The Fully Modified Ordinary Least Squares (FMOLS) method was employed as the baseline estimation technique to examine the long-run relationships. The Pooled Mean Group Autoregressive Distributed Lag (PMG-ARDL) model and the Mean Group (MG) estimator were also applied to check robustness. Aquaculture, income, and food production were all found to improve life expectancy significantly. However, the availability of protein has a significant detrimental effect on longevity. Based on this study’s findings, several directions could be taken with public health policy. First, the results indicate that life expectancy could be increased by implementing policies that boost aquaculture output, real income, and food production. Aquaculture production subsidies, tax incentives for food production, and investments in infrastructure might all be part of such plans. As a second takeaway, the results question the wisdom of initiatives that increase people’s protein intake. Measures along these lines include bans on fast food, charges on sugary beverages, and dietary awareness campaigns. Finally, this research shows the significance of investigating the links between aquaculture, protein intake, GDP, food production, and health.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"3 4","pages":"Article 100237"},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144489698","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}

{"title":"Performance of machine learning algorithms to evaluate the physico-mechanical properties of nanoparticle panels","authors":"Derrick Mirindi ,&nbsp;James Hunter ,&nbsp;David Sinkhonde ,&nbsp;Tajebe Bezabih ,&nbsp;Frederic Mirindi","doi":"10.1016/j.grets.2025.100235","DOIUrl":"10.1016/j.grets.2025.100235","url":null,"abstract":"<div><div>Nanoparticles significantly enhance the properties of wood-based materials, especially particleboards and wood panels. This review analyzes secondary data on nanoparticle integration in board production, aiming to evaluate the relationships among physical (water absorption (WA) and thickness swelling (TS)) and mechanical (modulus of rupture (MOR), modulus of elasticity (MOE); and internal bond (IB) strength) properties and to predict performance using machine learning (ML) algorithms. These algorithms include Pearson correlation, hierarchical clustering, and decision tree (DT) models. Results indicate that nanoparticles such as graphene oxide (GO), reduced graphene oxide (rGO), hydrolysis lignin, and calcium carbonate improve mechanical properties, with MOR values of 27.38–52.65 MPa and MOE of 2591.6–4680 MPa, meeting EN312 load-bearing standards. Zinc oxide nanoparticles yield superior dimensional stability by achieving a low TS of 9.33%. However, according to the American National Standard for Particleboard (ANSI/A208.1-1999), most nanoparticle boards produced met general-purpose standards except for WA and TS, which exceeded the maximum limits of 8% and 3%, respectively. Only crosslinked chitosan and zinc oxide nanoparticle panels meet the minimum requirements for TS (17%) and the maximum MOR (11.00 MPa) and MOE (1,800.00 MPa) for general purposes in dry conditions (furniture and interior fitments) according to the Brazilian standard (ABNT NBR). The Pearson correlation analysis reveals a strong relationship between board properties (R = 0.94 for WA–TS; R = 0.93 for MOR–MOE), confirming that nanoparticle treatments enhance performance while maintaining inherent material behavior. Hierarchical clustering grouped nanoparticles by performance: zinc oxide and chitosan+UF+epoxy formed a cluster with the lowest WA and TS, indicating optimal dimensional stability, while GO, rGO, and chitosan-based composites clustered with moderate values. For mechanical properties, APTES-modified nanocellulose, aluminum oxide, and zinc oxide formed a high-performance cluster (high MOR, MOE, IB). DT algorithms demonstrated high predictive accuracy (R<span><math><mrow><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup><mo>=</mo><mn>0</mn><mo>.</mo><mn>92</mn></mrow></math></span> for WA-TS, 0.96 for MOR-MOE, and 0.80 for IB-MOE), identifying critical thresholds: WA below 29.73% corresponded to minimal TS (9.94%), MOR above 38.18 MPa led to MOE above 3598.86 MPa, and IB above 0.88 MPa corresponds to MOE greater than 2,747.99 MPa. This data-driven framework enables targeted nanoparticle selection to fabricate engineered wood products and can be included in industry quality control standards to advance sustainable material development through ML-guided optimization.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"3 4","pages":"Article 100235"},"PeriodicalIF":0.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144471016","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}

{"title":"An interval valued intuitionistic fuzzy approach to evaluate the challenges for adopting the smart textiles in readymade garment industries: Implications for sustainable business development","authors":"MD Shafikul Islam ,&nbsp;Saifur Rahman Tushar ,&nbsp;Mahathir Mohammad Bappy ,&nbsp;Mohammad Ali ,&nbsp;Abdullah Al Nadim","doi":"10.1016/j.grets.2025.100225","DOIUrl":"10.1016/j.grets.2025.100225","url":null,"abstract":"<div><div>The readymade garment (RMG) sector is critical in the economic structure of numerous developing countries including Bangladesh making up around 83% of its overall exports. Despite its significance, the sector faces substantial risks and uncertainties, including fluctuating global markets, limited product diversification, and vulnerabilities accentuated by the COVID-19 pandemic. To sustain growth and navigate global market uncertainties, the garment industry must diversify product offerings and integrate smart textiles to enhance resilience and competitiveness. However, there are significant challenges to be overcome in incorporating smart textiles into the industry to achieve sustainable business growth. This study identifies and evaluates the key challenges impeding the adoption of smart textiles in Bangladesh’s RMG sector using data obtained from a structured expert survey comprising 12 industry specialists and academicians. Employing an Interval-Valued Type 2 Intuitionistic Fuzzy (IVT2IF) integrated with Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology, the analysis highlighted <em>“Incompatibility with current production infrastructure”</em> with <em>“Inadequate scalability of production”</em> being the main cause, and <em>“Incompatibility among the suppliers”</em> being the most affected outcome. These findings provide actionable insights for industry stakeholders and policymakers, emphasizing strategic infrastructural investments and collaboration improvements, thus facilitating sustainable business development in the RMG sector.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"3 3","pages":"Article 100225"},"PeriodicalIF":0.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242823","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}

{"title":"Current state of medical waste management in an emerging city of Bangladesh","authors":"Sajjad Hossain Shozib ,&nbsp;A.R.M. Towfiqul Islam ,&nbsp;Masum A. Patwary ,&nbsp;Mohammed A. Mamun ,&nbsp;Md. Naimur Rahman ,&nbsp;Kevin Lo","doi":"10.1016/j.grets.2025.100223","DOIUrl":"10.1016/j.grets.2025.100223","url":null,"abstract":"<div><div>A rising concern of inappropriate medical waste management in developing countries like Bangladesh brings higher health risk problems specially during viral outbreak. In this study, we analyzed the medical waste management in the rapid urbanizing area of Rangpur City, northern Bangladesh. In all, 20 healthcare centers were used for collecting data, random stratified sampling and waste weighing methods. The statistical data analysis used for the purposes of the study was linear regression, Pearson’s correlation, and logistic regression. We find that Rangpur City generates around 3.22 tons (<span><math><mo>±</mo></math></span> 1.02 SD) of medical waste daily, among which about 20% is hazardous according to WHO classification standards. Hazardous waste varied markedly in amount and proportion between healthcare establishments of different size and type. The study reveals how healthcare waste is mismanaged in the city and offers important insights for policymakers to drive healthcare waste better the management practices.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"3 3","pages":"Article 100223"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144229759","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}

{"title":"Green Human Resource Management: Analyzing sustainable practices and organizational impact through a Word2Vec approach","authors":"Shoeb Ahmad ,&nbsp;Uzma Javed ,&nbsp;Chetan Sharma ,&nbsp;Mohd Shuaib Siddiqui","doi":"10.1016/j.grets.2025.100224","DOIUrl":"10.1016/j.grets.2025.100224","url":null,"abstract":"<div><div>Green Human Resource Management (GHRM) integrates environmental sustainability into HR practices, aligning corporate strategies with ecological responsibility. The organization may achieve sustainability by educating and implementing green practices to employees, emphasizing their value, and showing them how their actions affect the environment. In this study, the authors analyzed 3,233 articles extracted from the Scopus database from 1996 to 2024. This study explores GHRM trends using a bibliometric analysis and Word2Vec-based natural language processing (NLP) approach to analyze keyword relationships. This study highlights how the Word2Vec model effectively maps the semantic relationships within a textual corpus with its sophisticated configuration of twenty hidden layers and a batch size of 1000. The input discusses the importance of adopting eco-friendly policies and procedures, specifically through Green Human Resource Management (GHRM), to address the environmental consequences of technological advancement. The study underscores organizations’ need to embed GHRM into corporate culture, linking it to employee training, performance evaluation, and strategic decision-making. It suggests that companies leverage AI-driven environmental monitoring systems for real-time sustainability assessments. Future research should examine the impact of emerging technologies on GHRM adoption and its long-term influence on corporate sustainability and employee engagement. Policymakers and businesses must collaborate to develop adaptable, region-specific GHRM frameworks, ensuring global environmental goals are met through human-centric sustainability initiatives. Additionally, it emphasizes the need for policy development and global adoption of GHRM and other sustainable corporate practices to achieve sustainable development. The analysis provides a novel insight into the significant keywords Related to GHRM by applying advanced natural language processing techniques to a substantial dataset spanning multiple decades.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"3 4","pages":"Article 100224"},"PeriodicalIF":0.0,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144230988","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}