Search Results (4,885)

Understanding household vehicle ownership dynamics in the post-COVID-19 era is critical for designing equitable, resilient, and sustainable transportation policies. This study employs an interpretable machine learning framework to model household vehicle ownership using data from the 2022 National Household Travel Survey (NHTS)—the first nationally representative U.S. dataset collected after the onset of the pandemic. A binary classification task distinguishes between single- and multi-vehicle households, applying an ensemble of algorithms, including Random Forest, XGBoost, Support Vector Machines (SVM), and Naïve Bayes. The Random Forest model achieved the highest predictive accuracy (86.9%). To address the interpretability limitations of conventional machine learning approaches, SHapley Additive exPlanations (SHAP) were applied to extract global feature importance and directionality. Results indicate that the number of drivers, household income, and vehicle age are the most influential predictors of multi-vehicle ownership, while contextual factors such as housing tenure, urbanicity, and household lifecycle stage also exert substantial influence highlighting the spatial and demographic heterogeneity in ownership behavior. Policy implications include the design of equity-sensitive strategies such as targeted mobility subsidies, vehicle scrappage incentives, and rural transit innovations. By integrating explainable artificial intelligence into national-scale transportation modeling, this research bridges the gap between predictive accuracy and interpretability, contributing to adaptive mobility strategies aligned with the United Nations Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities), SDG 10 (Reduced Inequalities), and SDG 13 (Climate Action). Full article

Cybersecurity is increasingly recognized as a key enabler of Sustainable Development Goals (SDGs) and especially SDG 3 (Good Health and Well-being) as healthcare systems become more digitized. This study prioritizes cybersecurity control families from the NIST 800-53r5 framework using a structured framework combining the Analytic Hierarchy Process (AHP) and the Impact–Feasibility Matrix. From the impact–feasibility perspective, expert judgment reveals that while impact is the primary driver in selecting controls, feasibility—particularly budget and cost constraints—plays a decisive role in real-world implementation. A group of fifteen experts, including cybersecurity officers, health IT professionals, and public health advisors, has participated in structured surveys as per the methodological framework of this paper. Financial and budgetary limitations emerged as the top feasibility barrier, often determining whether high-impact controls are deployed or delayed. This underscores the need for strategic investments and phased implementation approaches, particularly in resource-constrained health systems. The results provide a practical roadmap for policymakers and healthcare administrators to allocate cybersecurity resources effectively, balancing technical necessity with economic feasibility to support resilient digital health infrastructures. Full article

Sustainable development goals were laid out by the United Nations in 2015 as a means to address the profound issues present in the world by 2030. Nations have been encouraged to make amendments to their policies and frameworks by adding the SDGs to promote sustainability. In this era, where nations look for sustainable solutions, 3D printing has emerged as a revolutionary technology that has the potential to aid in accomplishing the SDGs. Advancements and developments in technology have boosted manufacturing efficiency and provide the pathway to achieving the set targets of multiple SDGs. Thus, this article looked into the potential contribution of 3D printing towards Sustainable Development Goal 13—Climate Action. A comprehensive literature review was performed using the PRISMA framework to understand the latest advancements in 3D printing and how 3D printing has been used to achieve the SDG targets. Moreover, an exploration of the impact of 3D printing on SDG 13 was performed. The potential impact topics explored include the reduction in GHG emissions using sustainable AM, decentralized manufacturing, resilient infrastructure to climatic hazards, the circular economy and product lifecycle extension. Qualitative analysis was conducted by looking into the effects of the SDGs on both the environmental and socio-technical aspects. Challenges in the implementation of AM within different economic sectors and its potential solutions are discussed in this article. The literature review and qualitative analysis pointed to a strong correlation between SDG 13 and 3D printing, paving the way for a sustainable future. Full article

This study examines the longitudinal relationship and interactions among comprehensive water management, human development, and fragility. The seventeen Middle Eastern countries were examined for the period from 1996 to 2023. The Human Development Index (HDI) and Fragile States Index (FSI) were considered as a proxy for human development and fragility. In addition, the Water Poverty Index (WPI) was thoroughly assessed using classical and improved methods to measure multidisciplinary water management. Findings highlight that “Resources” and “Environment” are the most critical components of WPI. Iran performed the most consistently across WPI versions, whereas Palestine performed the worst. “Capacity,” “Environment,” and “Access” are the most influential components of HDI. FSI was found to be the most sensitive to “Capacity” and “Environment”, which contribute to both human development and stability. This study provides empirical evidence to inform SDG 6 implementation by demonstrating the linkage between WPI components and progress in human development. Full article

This research investigated how detergent type and concentration, solution temperature, and flow rate affect ultrasonic cleaning efficiency in jewelry manufacturing. A silver bracelet without gemstones served as the test sample, and the study combined harmonic response analysis to assess acoustic pressure distribution with computational fluid dynamics to examine fluid flow patterns inside an ultrasonic cleaning machine. Cleaning tests were performed under real factory conditions to verify the simulations. Results showed that cleaning efficiency depends on the combined chemical and ultrasonic effects. Adding detergent lowered surface tension, encouraging cavitation bubble formation; higher temperatures (up to 60 °C) softened dirt, making removal easier; and moderate solution flow improved the cleaning, helping to carry dirt away from jewelry surfaces. Too much flow, however, decreased cavitation activity. The highest cleaning efficiency (93.890%) was achieved with 3% U-type detergent at 60 °C and a flow rate of 5 L/min, while pure water at room temperature (30 °C) without flow had the lowest efficiency (0.815%), confirmed by weighing and scanning electron microscope measurements. Interestingly, maximum ultrasonic power concentration did not always match the highest cleaning efficiency. The study supports sustainable practices by limiting detergent use to 3%, in line with Sustainable Development Goal (SDG) 9 (Industry, Innovation, and Infrastructure). Full article

In this study, we provide, to our knowledge, one of the first multidimensional, data-driven evaluations of green education performance in Turkish higher education, combining the THE Education Score, THE Impact Score, and the UI GreenMetric Education & Research Score (GM-ED) with institutional characteristics, and situating the analysis within SDG 4 (Quality Education). While universities worldwide increasingly integrate sustainability into their missions, systematic evidence from middle-income systems remains scarce. To address this gap, we compile a dataset of 50 Turkish universities combining three global indicators—the Times Higher Education (THE) Education Score, THE Impact Score, and the UI GreenMetric Education & Research Score (GM-ED)—with institutional characteristics such as ownership and student enrollment. We employ descriptive statistics; correlation analysis; robust regression models; composite indices under equal, PCA, and entropy-based weighting; and exploratory k-means clustering. Results show that integration of sustainability into curricula and research is the most consistent predictor of SDG-oriented performance, while institutional size and ownership exert limited influence. In addition, we propose composite indices (GECIs). GECIs confirm stable top performers across methods, but mid-ranked universities are volatile, indicating that governance and strategic orientation matter more than structural capacity. The study contributes to international debates by framing green education as both a measurable indicator and a transformative institutional practice. For Türkiye, our findings highlight the need to move beyond symbolic initiatives toward systemic reforms that link accreditation, funding, and governance with green education outcomes. More broadly, we demonstrate how universities in middle-income contexts can institutionalize sustainability and provide a replicable framework for assessing progress toward SDG 4. Full article

This research presents Geographic Information System (GIS) mapping and development of biomass for combined heat and power (CHP) generation in Nigeria. It includes crop and forest classification, thermodynamic, and exergo-economic analyses using ArcGIS, Engineering Equation Solver, and Microsoft Excel. Syngas generated from biomass residues powered an integrated CHP system combining a gas turbine (GT), dual steam turbine (DST), and a cascade organic Rankine cycle (CORC) plant. The net power output of the integrated system stood at 2911 MW, with a major contribution from the gas turbine cycle (GTC) unit. The system had a total exergy destruction of 6480 MW, mainly in the combustion chamber (2143 MW) and HP-HRSG (1660 MW), and produced 3370.41 MW of heat, with a flue gas exit temperature of 74 °C. The plant’s energy and exergy efficiencies were 87.16% and 50.30%, respectively. The BCHP system showed good economic and environmental performance, with an annualized life cycle cost of USD 93.4 million, unit cost of energy of 0.0076 USD/kWh, and a 7.5-year break-even. The emissions and impact factors align with those of similar existing plants. It demonstrates that biomass residue can significantly support Nigeria’s energy needs and contribute to clean energy goals under the Paris Agreement and UN-SDGs. This work suggests a pathway to tackle energy insecurity, inform policymakers on biomass-to-energy, and serve as a foundation for future techno-economic–environmental assessment of biomass residues across suitable locations in Nigeria. Full article

Coffee silverskin (CS), the principal solid by-product from coffee roasting, is a promising raw material for sustainable food applications aligned with circular economy principles. Due to its high flammability at roasting temperatures, effective management of CS is not only an environmental but also a safety concern in coffee processing facilities. To the best of our knowledge, this is the first study evaluating the chemical composition, bioactivity, safety, and environmental impact of torrefacto (CT) and natural (CN) coffee silverskin. CT (from Arabica–Robusta blends subjected to sugar-glazing) and CN (from 100% Arabica) were characterized in terms of composition and function. Oven-dried CT showed higher levels of caffeine (13.2 ± 0.6 mg/g vs. 8.7 ± 0.7 mg/g for CN), chlorogenic acid (1.34 ± 0.08 mg/g vs. 0.92 ± 0.06 mg/g), protein (18.1 ± 0.2% vs. 16.7 ± 0.2%), and melanoidins (14.9 ± 0.3 mg/g vs. 9.6 ± 0.2 mg/g), but CN yielded more total phenolics (13.8 ± 0.6 mg GAE/g). Both types exhibited strong antioxidant capacity (ABTS: 48.9–59.2 µmol TE/g), and all oven-dried samples met food safety criteria (microbial loads below 10² CFU/g, moisture 7.9%). Oven drying was identified as the most industrially viable, ensuring preservation of bioactives and resulting in a 19% lower greenhouse gas emissions impact compared to freeze-drying. Sun drying was less reliable microbiologically. The valorization of oven-dried CT as a clean-label, antioxidant-rich colorant offers clear potential for food reformulation and waste reduction. Renewable energy use during drying is recommended to further enhance sustainability. This study provides scientific evidence to support the safe use of coffee silverskin as a novel food, contributing to regulatory assessment and sustainable food innovation aligned with SDGs 9, 12, and 13. Full article

Urban agriculture in space-constrained cities requires compact, reproducible propagation systems. Therefore, the aim of this Technical Note is to design, implement, and functionally validate a low-cost, modular hydroponic chamber (SSHG) for early-stage vegetative propagation. This system couples DHT11-based temperature/RH monitoring with rule-based actuation—irrigation 4×/day and temperature-triggered ventilation—under the control of an Arduino Uno microcontroller; LED lighting was not controlled nor analyzed. Two 15-day trials with basil (Ocimum basilicum L.) yielded rooting rates of 61.7% (37/60) and 43.3% (26/60) under a deliberate minimal-input configuration without nutrient solutions or rooting hormones. Environmental summaries and spatial survival maps revealed edge-effect patterns and RH variability that inform irrigation layout improvements. The chamber, bill of materials, and protocol are documented to support replication and iteration. Thus, the SSHG provides a transferable baseline for educators and researchers to audit, reproduce, and improve small-footprint, controlled-environment propagation. Beyond its technical feasibility, the SSHG contributes to sustainability by leveraging low-cost, readily available components, enabling decentralized seedling production in space-constrained settings, and operating under a minimal-input configuration. In line with widely reported hydroponic efficiencies (e.g., lower water use relative to soil-based propagation), this open and replicable platform aligns with SDGs 2, 11, 12, and 13. Full article

Soil is fundamental to life on Earth through the provision of many ecosystem services. The current model of economic development exerts significant pressure on this resource, leading to degradation processes that are accelerated by the effects of climate change. This situation hinders the achievement of the UN Sustainable Development Goals, and some parts of the world have started a process to reverse this trend, among them the European Union, which has chosen the living labs approach as a strategic solution. The growing interest in this subject within the EU has led to the establishment of a new framework to design and test sustainable policies to improve soil health and management at the continental scale. This review presents State-of-the-Art information on the use of the living labs approach to improve soil health. It also introduces the SOILL Support Structure for Soil Health Living Labs (SHLLs) and Lighthouses and the significant role of the SOILL-Startup project to help establish a network of 100 such structures across the EU. Following the PRISMA methodology, the review describes the main features of SHLLs (definition, types of stakeholders, field and scale of application), as well as their current geographical distribution. The work provides information that can be used by the scientific community, policy makers, and soil stakeholders who prioritise soil health, regardless of the context in which they operate. Full article

In many developing countries, including South Africa, electricity providers have consistently faced challenges in meeting rising energy demands. Since 2008, South Africa has implemented widespread electricity rationing—commonly referred to as “loadshedding”—due to a combination of operational inefficiencies and structural constraints. Loadshedding continues to be a critical challenge in South Africa, significantly affecting the economy, livelihoods, public health, and broader socio-economic conditions. This study explores the link between loadshedding and air quality by analyzing atmospheric emissions during two contrasting periods: 2019, a year with minimal loadshedding; and 2023, which experienced severe and prolonged outages. The analysis reveals a decline in nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) levels during the intense loadshedding period of 2023. The results indicate that, beyond the influence of weather patterns, reductions in emissions—such as those caused by decreased electricity generation—contribute meaningfully to improved air quality. Overall, the data suggest that reduced power production during high levels of loadshedding links with lower emissions and enhanced air quality. These findings reinforce the potential benefits of transitioning to cleaner, alternative energy sources for achieving long-term reductions in air pollution and fostering a healthier environment. Remote sensing is a critical tool for environmental monitoring in developing countries, offering cost-effective, wide-area data collection to address issues like air pollution, and climate impact. It supports policy-making by providing timely, objective insights for sustainable development, resource management, and disaster response, aligning with SDGs. Full article

Low-altitude unmanned aerial vehicle (UAV) technology serves as a crucial pathway for developing a low-carbon circular economy and achieving the Sustainable Development Goals (SDGs). In order to achieve the diffusion of low-altitude UAV technology in sustainable development, a dynamic model of technology adoption decisions within enterprise clusters is constructed. This model is based on complex network evolutionary game theory. The present study investigates the mechanism through which government policies influence the diffusion of low-altitude UAV technology. The research findings indicate that government subsidy mechanisms and diffusion constraints play critical roles in the diffusion process of low-altitude UAV technology. Core Enterprises and Marginal Enterprises within clusters exhibit different responsiveness to subsidies, with Core Enterprises demonstrating higher sensitivity. The intensity of government subsidies is positively correlated with the diffusion rate of low-altitude UAV technology, while the penalty from constraints is negatively correlated with the diffusion rate. These findings establish a foundation for governments to devise pertinent subsidy mechanisms, establish and enhance the management system of the low-altitude economy, and cultivate a policy ecosystem conducive to the diffusion of low-altitude UAV technology, thereby propelling sustainable societal development. Full article

This study presents a holistic framework for adaptive thermal energy storage (A-TES) in solar-assisted systems. This framework aims to support a reliable industrial energy supply, particularly during periods of limited sunlight, while also facilitating industrial decarbonization. In previous studies, the focus was not on addressing the framework of the entire problem, but rather on specific parts of it. Therefore, the innovation in this study lies in bringing these aspects together within a unified framework through a data-driven approach that combines the analysis of efficiency, technology, environmental impact, sectoral applications, operational challenges, and policy into a comprehensive system. Sensible thermal energy storage with an adaptive approach can be utilized in numerous industries, particularly concentrated solar power plants, to optimize power dispatch, enhance energy efficiency, and reduce gas emissions. Simulation results indicate that stable regulations and flexible incentives have led to a 60% increase in solar installations, highlighting their significance in investment expansion within the renewable energy sector. Integrated measures among sectors have increased energy availability by 50% in rural regions, illustrating the need for partnerships in renewable energy projects. The full implementation of novel advanced energy management systems (AEMSs) in industrial heat processes has resulted in a 20% decrease in energy consumption and a 15% improvement in efficiency. Making the switch to open-source software has reduced software expenditure by 50% and increased productivity by 20%, demonstrating the strategic advantages of open-source solutions. The findings provide a foundation for future research by offering a framework to analyze a specific real-world industrial case. Full article

The shift from techno-centric to human-centric development is essential for smart cities to effectively leverage technological innovations and enhance the quality of life of citizens. Despite this recognition, there are limited studies that address the challenges and frame the conditions and impacts involved. This study employs a mixed-method approach, namely the combination of literature review, expert consultation, and case analysis, to investigate human-centered smart city development based on the example of Saudi Arabia. Drawing from the literature, it develops a conceptual framework that provides guidance for achieving human-centric smart cities. The findings indicate that while Saudi Arabia has achieved notable progress in smart city development, inclusivity, centralized planning, public engagement, capacity building, and data security hinder advancement. This study demonstrates that smart city initiatives must aim to go beyond mere buzzwords and integrate components in line with human values and societal expectations. The study’s findings may help in framing urban humanization policies aligned with of Saudi Arabia’s Vision 2030 and offer guidance for cities with similar contexts. Full article

Aligning with the UN Sustainable Development Goals (SDGs 11 and 13), this study examines how dynamic subsidy thresholds steer environmental resilience, social inclusion, and fiscal sustainability in China’s urban renewal. Using evolutionary game theory (EGT) and system dynamics (SD), stakeholder strategies are modeled under varying policy interventions, with key parameters calibrated through Chongqing’s LZ case and MATLAB simulations. These include government subsidies (M₁, M₂), penalties (S₂), and stakeholder benefits (R₁–R₅). The results reveal the following two distinct types of critical thresholds: a universal and robust fiscal warning line for developers (M₁ > 600 k RMB) and a threshold for residential subsidies that is moderated by psycho-social factors (M₂), with its value fluctuating within a certain range (approximately 550 k RMB to 850 k RMB). A sequential synergy pathway is proposed: “government-led facilitation → developer-driven implementation (when R₃ > 450 k RMB) → resident participation (triggered by R₂ > 150 k RMB).” The study advocates differentiated incentives and penalties, prioritizing early-stage governmental leadership to foster trust, promote inclusive participation, and align with environmental, social, and economic sustainability goals. This integrated framework reveals critical policy leverage points for enhancing social and fiscal resilience, providing a replicable model for sustainable and resilient urban governance in the Global South. Full article