Green Technologies and Sustainability最新文献

{"title":"Advancing sustainability in academic institutions: A GHRM Framework using fuzzy Delphi and DEMATEL method","authors":"Sahilali Saiyed ,&nbsp;Vimal Kumar ,&nbsp;Md. Shamimul Islam ,&nbsp;Adi Prasetyo Tedjakusuma ,&nbsp;Pratima Verma","doi":"10.1016/j.grets.2025.100294","DOIUrl":"10.1016/j.grets.2025.100294","url":null,"abstract":"<div><div>Sustainability is becoming a significant concern in academic institutions worldwide. This issue is critical in Asian countries, which are more vulnerable to adverse environmental effects. Universities in these regions can play a pivotal role in mitigating their environmental impact by adopting green human resource management (GHRM). While the potential of GHRM in achieving sustainability is significant, research in this context remains limited and requires further exploration. This study applies the AMO theory (Ability–Motivation–Opportunity theory) to develop a framework for GHRM. The framework comprising seven aspects and twenty-five criteria was formed. The fuzzy Delphi (FDM) and decision-making trial and evaluation laboratory (FDEMATEL) hybrid methodology is used to analyze the data. The proposed framework is tested using data collected from several Asian academic institutions. The findings highlight that sustainability policy &amp; institutional support, green hiring, and green organizational culture are necessary aspects of GHRM practices in Asian academic institutions and indicate their essential role in fostering sustainability.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100294"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694393","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 intelligent digital twin approach for optimizing multi-channel supply chains in uncertain environments","authors":"Hamed Nozari ,&nbsp;Zornitsa Yordanova","doi":"10.1016/j.grets.2025.100309","DOIUrl":"10.1016/j.grets.2025.100309","url":null,"abstract":"<div><div>This study develops an innovative framework for the multi-objective optimization of multi-channel supply chains under uncertainty. The framework integrates the D-number model, an extension of Dempster–Shafer Theory (DST) that enables the representation of incomplete and non-exclusive information, and employs a cognitive digital twin (CDT) as a platform for analysis and decision-making. The proposed mathematical model captures the complexity of the supply chain environment by addressing conflicting objectives such as minimizing total cost and delivery delays while enhancing resilience. Small-scale instances are solved using the General Algebraic Modeling System (GAMS), while two meta-heuristic algorithms, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Colonial Competitive Algorithm (CCA), are applied to larger problems. Sensitivity analysis, Pareto front comparisons, and a scalability study demonstrate that the framework remains robust across varying conditions and offers valuable managerial insights. The results support improved decision-making and enhanced supply chain resilience.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100309"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145694388","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":"Design and stability analysis of a robust model predictive control method for voltage regulation in DC-DC buck converters subject to the input and load uncertainties","authors":"Chang Tai,&nbsp;Xiaojuan Zhou","doi":"10.1016/j.grets.2025.100308","DOIUrl":"10.1016/j.grets.2025.100308","url":null,"abstract":"<div><div>In controlling DC-DC buck converters, the issue of input uncertainties as well as load uncertainties is one of the important challenges in controller design. This paper addresses this issue as well as presents a new robust control method according to the model predictive control method for regulating the output voltage of the converter. More specifically, this paper presents an H-Infinity MPC controller in which uncertainty in the converter input voltage is also considered during design, as is uncertainty in the load connected to the converter. Based on these assumptions, this controller is designed to have sufficient resistance to the aforementioned uncertainties. Since this controller solves an optimization problem at each time step, it has an optimal response and minimizes a cost function. Therefore, optimization has been made in the generation of the control law and consequently in energy consumption, which is very important in power electronics applications. In addition, unlike other articles on MPC design for this type of converter, this article examines the stability of the desired control method and theoretically ensures the controller’s asymptotic stability by applying the Lyapunov approach. It should be noted that a saturation constraint is included in the control law generated by this controller to ensure the feasibility of the control signal generation. Ultimately, this problem is transformed into an LMI problem, and by solving this problem, the controller design parameters are optimally extracted. Finally, the performance of the suggested method was investigated through a series of practical experiments on a DC-DC buck converter in the laboratory, and the results confirm the effectiveness of this method in regulating the output voltage.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100308"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145651988","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":"Third-order nonlinear sliding-mode controller for improving the performance of a grid-connected PV system","authors":"Noureddine Ech-cherki,&nbsp;Oumaima Echab,&nbsp;Youssef Errami,&nbsp;Abdellatif Obbadi,&nbsp;Smail Sahnoun","doi":"10.1016/j.grets.2025.100280","DOIUrl":"10.1016/j.grets.2025.100280","url":null,"abstract":"<div><div>The performance of Photovoltaic (PV) power generation systems, using traditional Vector Current Controllers based on Proportional–Integral Action (CVC-PI), exhibits marked non-linearity and is strongly influenced by meteorological variations. Due to its robustness in the face of these challenges, Sliding Mode Control (SMC) has been widely used in this field, but SMC has certain inconveniences, notably the phenomenon of chattering and ripples in active (P) and reactive (Q) power. These limitations remain partially unresolved, even with the use of Second-order SMC (SMC-2). To address these limitations, this work proposes a robust, non-linear control based on the Third-order SMC in Dual Mode conversion (DM-SMC-3). To demonstrate the effectiveness of the proposed DM-SMC-3 control, a comparative study was carried out between DM-SMC-3, SMC-2, SMC and CVC-PI in terms of chattering reduction, dynamic response time, overshoot, P and Q power ripples and the Total Harmonic Distortion (THD) of the current injected into the electrical grid. The DM-SMC-3 is also used to guarantee Maximum Power Point Tracking (MPPT). The system is designed and simulated using Matlab/Simulink software. The simulation results demonstrated the significant contribution of the DM-SMC-3, with a 99% reduction in overshoot compared to other controllers. THD was reduced to 0.58%. The average reference tracking efficiency was 99.68%, and 99.41% under the temperature and irradiation conditions used. What is more, the DM-SMC-3 takes just 35ms to reach the Maximum Power Point (MPP). It also reduced P and Q power ripples, demonstrating the robustness of the proposed controller in the face of chattering.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100280"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145652040","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":"Advancing sustainable and green agriculture with AI and IoT: Trends, challenges, and future directions","authors":"Sachin Gupta ,&nbsp;Ashish Kumar Tripathi ,&nbsp;Varun G. Menon ,&nbsp;Varsha Arya ,&nbsp;Brij B. Gupta","doi":"10.1016/j.grets.2026.100351","DOIUrl":"10.1016/j.grets.2026.100351","url":null,"abstract":"<div><div>The agricultural sector contributes significantly to the economic development of nations worldwide. Owing to the population explosion, agriculture must address the complex challenges to meet the growing food demand while safeguarding natural and environmental sustainability. With limited farming land, water scarcity, soil degradation, and climate variability, it is essential to develop innovative, smart methods for sustainable agriculture. This article presents an in-depth analysis of the role of the Internet of Things, sensor networks, and UAVs in sustainable farming. Additionally, the article covers the integration of machine learning, artificial intelligence, computer vision, and deep learning that has transformed traditional practices into sustainable agricultural practices at every stage. The literature paper explores different agricultural applications, including smart irrigation, crop phenotyping, smart greenhouse, crop monitoring, quality assessment, yield prediction, and disease detection, thus covering about eighty seven research articles. The present study provides interconnected and valuable knowledge about smart and sustainable agriculture by integrating varied technologies in multiple agriculture domains instead of specific domains or technologies. Compared to many existing surveys emphasizing smart solutions, the innovation of the present article lies in its focus on sustainability, long-term resilience, resource optimization, and environmental conservation.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100351"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188320","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":"Digital twin-driven decision support for human capital management under uncertainty","authors":"Hamed Nozari,&nbsp;Zornitsa Yordanova","doi":"10.1016/j.grets.2026.100353","DOIUrl":"10.1016/j.grets.2026.100353","url":null,"abstract":"<div><div>Organizations increasingly face uncertainty in workforce planning, driven by shifting skill demands, rising turnover risks, and pressure to optimize labor investments. Traditional human capital decision models struggle to support strategic trade-offs among productivity, retention, and cost efficiency in dynamic environments. This study proposes a Digital Twin-driven decision support framework that enables adaptive, data-informed workforce optimization under uncertainty. The digital twin continuously mirrors employee profiles, performance trajectories, engagement patterns, and attrition risk, providing a real-time model of workforce dynamics. Using this live data environment, a multi-objective optimization model evaluates competing strategic outcomes, balancing productivity maximization, training and deployment cost minimization, and talent retention in critical roles. The framework is tested through simulation scenarios that reflect realistic organizational uncertainty, including fluctuating workloads, budget constraints, and employee movement. Results demonstrate that the system generates high-quality, interpretable decisions that achieve superior performance across all objectives compared to rule-based or single-factor decision strategies. The findings contribute to human capital analytics and digital transformation research by positioning digital twins as an intelligent capability enabling continuous workforce learning and decision refinement. Practically, the model offers organizations a scalable pathway to integrate real-time analytics, optimization, and predictive workforce intelligence into strategic HR planning.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100353"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188321","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":"Moisture-induced swelling in natural fiber-reinforced composites: A critical review of chemical treatments, hybrid strategies, and environmental durability","authors":"Riduwan Prasetya ,&nbsp;Femiana Gapsari ,&nbsp;Andoko Andoko ,&nbsp;Khairul Anam ,&nbsp;Rudianto Raharjo ,&nbsp;Sanjay Mavinkere Rangappa ,&nbsp;Suchart Siengchin","doi":"10.1016/j.grets.2026.100336","DOIUrl":"10.1016/j.grets.2026.100336","url":null,"abstract":"<div><div>This review aims to critically investigate the swelling behavior of natural fiber-reinforced composites (NFRCs), with a focus on identifying key mechanisms of moisture absorption, the influence of fiber–matrix interactions, and the effectiveness of mitigation strategies such as chemical treatments and hybridization. A systematic synthesis of over 120 peer-reviewed articles published between 2015 and 2025 was conducted. These studies were analyzed to extract data on moisture uptake behavior, microstructural evolution, treatment effects, matrix properties, and performance under various environmental conditions. The review identifies cellulose crystallinity, hemicellulose content, and fiber–matrix interfacial bonding as dominant factors influencing swelling. While Fickian diffusion models describe early-stage absorption, long-term exposure often results in non-Fickian behavior due to matrix plasticization and interface degradation. Chemical treatments such as alkali, silane, and acetylation reduce water absorption but may compromise fiber strength if overapplied. Hybridization with hydrophobic fibers and the use of non-polar matrices improve resistance. Moisture-induced performance degradation is strongly influenced by environmental variables such as temperature, humidity cycling, and salt fog. This review consolidates current knowledge on swelling mechanisms in NFRCs and clarifies the trade-offs between moisture resistance and mechanical performance. It also proposes design guidelines and testing protocols for enhancing long-term durability. The findings are applicable to industries seeking sustainable yet durable composite materials, particularly in automotive, construction, marine, and packaging sectors where environmental exposure is a critical concern.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100336"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977779","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":"Sustainable valorization of red prickly pear seeds: Green technologies for antioxidant compounds recovery","authors":"Salome Mamani-Pari ,&nbsp;María Fernanda Quispe Angulo ,&nbsp;Erick Saldaña ,&nbsp;Elías Escobedo-Pacheco ,&nbsp;Nils Leander Huamán-Castilla","doi":"10.1016/j.grets.2025.100279","DOIUrl":"10.1016/j.grets.2025.100279","url":null,"abstract":"<div><div>Although Prickly pear seeds are agroindustrial wastes, these residues are a natural source of antioxidant compounds. Thus, this study analyzed two green technologies like Pressurized Liquid Extraction (PLE) and Ultrasound-Assisted Extraction (UAE) combined with water-ethanol mixtures at different temperatures (50 °C and 70 °C) to recover antioxidant compounds from red prickly pear seeds. The use of UAE process combined with 60% ethanol at 70 °C was 55% more effective to recover antioxidant compounds compared to the PLE process (60% ethanol–70 °C). Under these conditions, the extracts presented a high total polyphenol content (1.65 mg GAE/g dw), DPPH radical inhibition capacity (IC50: 15.5 mg/mL), and oxygen radical inhibition capacity (48.6 <span><math><mi>μ</mi></math></span>M ET/g dw). For polyphenol profile, increasing the ethanol concentration at 70 °C allowed to recover higher concentrations of caffeic acid, catechin and procyanidins. However, the quercetin was negatively affected by the increased ethanol concentration. Principal component analysis indicated that temperature and solvent composition are key parameters for the selective extraction of antioxidant compounds. Finally, the UAE process was 35% more efficient than conventional extraction to recover antioxidant compounds. These results show the feasibility of scaling up to an industrial level a sustainable process to recover metabolites from agroindustrial waste.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100279"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145652039","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":"Comparing TiO2 and CuO nanoparticles as additives to improve the efficiency and exhaust gases of a four-stroke engine fueled with n-butanol-diesel mixture","authors":"Qais Hussein Hassan ,&nbsp;Hayder A. Alalwan ,&nbsp;Alaa Hani Alminshid ,&nbsp;Malik M. Mohammed","doi":"10.1016/j.grets.2025.100278","DOIUrl":"10.1016/j.grets.2025.100278","url":null,"abstract":"<div><div>This study evaluates the effects of TiO₂ and CuO nanoparticles as additives to a 15% n-butanol-diesel blend (BuD) on the performance and emissions of a four-stroke diesel engine. Tests at varying torque loads revealed that while n-butanol blending alone increased fuel consumption and energy use compared to pure diesel, the addition of 50 ppm TiO₂ or CuO nanoparticles significantly mitigated these drawbacks, enhancing fuel efficiency and ignition quality. Key emission pollutants – CO, HC, and particulate matter – were notably reduced with nanoparticles, attributed to their catalytic and oxygen-supplying roles promoting more complete combustion. However, NOx emissions increased with n-butanol and nanoparticle use, highlighting a trade-off that needs further mitigation strategies. This work uniquely compares TiO₂ and CuO nanoparticles under identical conditions, providing new insights into their differential catalytic effects on butanol-diesel combustion and emissions. The findings support TiO₂ and CuO as cost-effective additives to optimize biofuel blends for cleaner and more efficient engine operation.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100278"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145652044","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":"Integrating renewable propulsion systems in sailing yachts: An interdisciplinary life-cycle assessment and sustainable energy model","authors":"Hamdi Sena Nomak ,&nbsp;İsmail Çiçek","doi":"10.1016/j.grets.2026.100341","DOIUrl":"10.1016/j.grets.2026.100341","url":null,"abstract":"<div><div>Sailing yachts can achieve operationally zero-emission propulsion by integrating solar photovoltaic (PV), wind and hydrokinetic generation with battery-electric drive systems. This study applies a systems engineering modeling framework to quantify the environmental, operational-energy and techno-economic performance of a renewable-electric retrofit for a 12 m cruising monohull, evaluated against diesel and battery-electric alternatives. An ISO 14040/14044-consistent life-cycle assessment (LCA) implemented in an Excel toolchain is coupled with time-resolved energy-balance simulations and a retrofit-oriented cost model (baseline year 2025). Over the functional unit (20 years or 20,000 nautical miles), the diesel baseline produces <span><math><mo>∼</mo></math></span>65 t CO₂-eq, while the battery-electric case yields <span><math><mo>∼</mo></math></span>28 t CO₂-eq under a moderately clean grid and the renewable-electric configuration achieves <span><math><mo>∼</mo></math></span>10–12 t CO₂-eq (<span><math><mo>∼</mo></math></span>80%–85% reduction versus diesel). In both electric cases, onboard operational CO₂ emissions are eliminated, while life-cycle impacts persist due to manufacturing, replacement and end-of-life processes. Energy simulations show that integrated PV, wind and hydro generation can supply &gt;80% of combined hotel and propulsion demand under representative cruising profiles, with storage buffering variability and an energy management strategy prioritizing real-time renewable utilization. The principal constraint is prolonged motoring in low-renewable conditions: a 30 kWh usable battery provides approximately 4 h at 5–6 kn (<span><math><mo>∼</mo></math></span>2.6–3.1 m/s). Sensitivity results emphasize that life-cycle outcomes are strongly influenced by electricity carbon intensity, battery production impacts, recycling rates and renewable availability. Overall, the study provides a transparent, replicable framework for designing and evaluating renewable-electric propulsion in recreational and small-scale marine craft within the broader scope of green technologies and sustainability.</div></div>","PeriodicalId":100598,"journal":{"name":"Green Technologies and Sustainability","volume":"4 2","pages":"Article 100341"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977778","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}