Search Results (3,827)

This study investigates the systemic interrelations between logistics performance, environmental performance, sustainable development progress, and institutional governance. While the existing literature often examines these dimensions separately, this research conceptualizes them as co-determined drivers of national development. Using data from 123 countries, the analysis integrates four composite indices—Logistics Performance Index (LPI), Environmental Performance Index (EPI), Sustainable Development Goals Index (SDG), and Worldwide Governance Indicators (WGI)—alongside GDP per capita. Methodologically, this study applies multiple linear regressions and correlation analyses to assess the associations among these variables and employs Fuzzy Cognitive Mapping (FCM) to simulate scenario-based systemic interactions. Results show that all ESG indicators are positively and significantly associated with LPI, with WGI exerting the strongest effect. In turn, LPI, EPI, SDG, and WGI jointly explain 81.7% of the variance in GDP per capita, confirming their integrated role in shaping economic performance. FCM simulations further reveal that both environmental and institutional improvements generate reinforcing effects on logistics capacity and GDP outcomes. This study’s originality lies in its multiple-method approach and its synthesis of ESG and logistics performance metrics into a unified explanatory framework. It contributes to development studies by highlighting the structural embeddedness of logistics within broader institutional and sustainability ecosystems. Its policy implication lies in suggesting that integrated reforms—combining infrastructure, regulatory quality, and environmental stewardship—are essential for enhancing long-term national competitiveness and resilience. Full article

This study addressed the persistent limitation of discontinuous and labor-intensive compost monitoring procedures by developing and field-validating a low-cost sensor system for monitoring oxygen (O₂), carbon dioxide (CO₂), and methane (CH₄) under tropical windrow conditions. In contrast to laboratory-restricted studies, this framework integrated rigorous calibration, multi-layer statistical validation, and process optimization into a unified, real-time adaptive design. Experimental validation was performed across three independent composting replicates to ensure reproducibility and account for environmental variability. Calibration using ISO-traceable gas standards generated linear correction models, confirming sensor accuracy within ±1.5% for O₂, ±304 ppm for CO₂, and ±1.3 ppm for CH₄. Expanded uncertainties (U₉₅) remained within acceptable limits for composting applications, reinforcing the precision and reproducibility of the calibration framework. Sensor reliability and agreement with reference instruments were statistically validated using analysis of variance (ANOVA), intraclass correlation coefficient (ICC), and Bland–Altman analysis. Validation against a reference multi-gas analyzer demonstrated laboratory-grade accuracy, with ICC values exceeding 0.97, ANOVA showing no significant phase-wise differences (p > 0.95), and Bland–Altman plots confirming near-zero bias and narrow agreement limits. Ecological interdependencies were also captured, with O₂ strongly anticorrelated to CO₂ (r = −0.967) and CH₄ moderately correlated with pH (r = 0.756), consistent with microbial respiration and methanogenic activities. Nutrient analyses indicated compost maturity, marked by increases in nitrogen (+31.7%), phosphorus (+87.7%), and potassium (+92.3%). Regression analysis revealed that ambient temperature explained 25.8% of CO₂ variability (slope = 520 ppm °C⁻¹, p = 0.021), whereas O₂ and CH₄ remained unaffected. Overall, these findings validate the developed sensors as accurate and resilient tools, enabling real-time adaptive intervention, advancing sustainable waste valorization, and aligning with the United Nations Sustainable Development Goals (SDGs) 12 and 13. Full article

Engineering education for sustainability extends beyond environmental awareness. It is aimed at the cultivation of resilient and self-regulated learners capable of continuous growth. The present work draws upon empirical data from three complementary investigations on first-year engineering students’ affective behavior, mathematical difficulties and the use of online quizzes as self-assessment tools. By integrating these findings, the paper proposes a framework for sustainable learning practices in engineering mathematics. The results highlight that affective factors, such as confidence, self-efficacy and motivation, interact significantly with students’ self-regulatory strategies and performance outcomes. Digital self-assessment tools, when purposefully designed, can promote metacognitive reflection and foster a sustainable cycle of feedback and self-improvement. The study argues that sustainable education in engineering must include pedagogical approaches that empower students with interindividual differences to manage their own learning, overcome affective barriers and develop adaptive resilience in demanding quantitative subjects. The proposed model offers practical implications for designing assessment systems that support long-term learner autonomy and well-being, aligning engineering mathematics education with the broader goals of sustainable development. In alignment with SDG 4.7 and the European Skills Agenda, which both emphasize lifelong learning, learner autonomy and the cultivation of adaptive competences for sustainable futures, the proposed framework positions self-regulation and resilience as core sustainability-oriented outcomes in engineering mathematics education. Full article

Ammonia (NH₃) is a major anthropogenic pollutant originating from agricultural activity, particularly livestock operations. NH₃ emissions from livestock slurry storage pose risks to environmental quality and human health. Reducing NH₃ emissions aligns with several United Nations Sustainable Development Goals (SDGs), including SDG 3, SDG 12, SDG 14, and SDG 15. This study evaluates the performance of the commercially available SOP^® LAGOON additive under real-scale farm conditions for mitigating NH₃ emissions. Two adjacent slurry storage tanks of a dairy farm in Northern Italy were monitored from 27 May to 7 September: one treated with SOP^® LAGOON and one left untreated (serving as a control). In the first month, the treated tank showed a 77% reduction in NH₃ emissions. Emissions from the treated tank remained consistently lower than those from the control throughout the monitoring period, reaching an 87% reduction relative to the baseline levels by the end of the period. The results suggest that SOP^® LAGOON is an effective and scalable strategy for reducing NH₃ emissions from liquid manure storage, with practical implications for farmers and policy makers in regard to designing sustainable manure management practices. Full article

Glyphosate, a widely used non-selective herbicide, has been a subject of intense scientific debate due to its environmental persistence and potential health risks. This review examines glyphosate’s mechanisms of action, its effects on crop production, and its broader environmental impact, including soil degradation, water contamination, and biodiversity loss. Furthermore, it examines the expanding body of research linking glyphosate exposure to various human health concerns, including metabolic, neurological, reproductive, and oncological disorders. The review also assesses glyphosate’s role in hindering the achievement of the Sustainable Development Goals (SDGs), particularly those related to food security, health, access to clean water, and the protection of marine ecosystems. Finally, potential alternatives to glyphosate-based weed control, including organic and non-chemical methods, are discussed to promote sustainable agricultural practices that balance productivity with ecological and public health considerations. The evidence reviewed highlights glyphosate’s pervasive presence across ecosystems and its potential to disrupt both environmental and human health. The findings underscore the urgent need to regulate glyphosate use, prioritize soil and water protection, and accelerate the transition toward sustainable, low-toxicity weed management strategies that align with global sustainability objectives. Full article

The 2011 Great Flood in Thailand exposed critical deficiencies in water management across the Chao Phraya River Basin, particularly in controlling inflows and discharges from major reservoirs such as Sirikit and Bhumibol. Inadequate rainfall monitoring at the Nakhon Sawan station further intensified the disaster’s impact. As climate change continues to amplify extreme weather events, this study aims to improve flood forecasting accuracy and promote sustainable water resource management aligned with the Sustainable Development Goals (SDGs 6, 11, and 13). Advanced climate data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) were spatially refined and integrated with hydrological models to enhance regional accuracy. The Discrete Wavelet Transform (DWT) was applied for feature extraction to capture hydrological variability, while the Nonlinear Autoregressive Model with Exogenous Factors (NARX) was employed to model complex temporal relationships. A multi-model ensemble framework was developed to merge climate forecasts with real-time hydrological data. Results demonstrate significant model performance improvements, with DWT-NARX achieving 55–98% lower prediction errors (RMSE) compared to baseline methods and correlation coefficients exceeding 0.91 across all forecasting scenarios. Marked seasonal variations emerge, with higher inflows during wet periods and reduced inflows during dry seasons. Under RCP8.5 climate scenarios, wet-season inflows are projected to increase by 15.8–17.4% by 2099, while dry-season flows may decline by up to 33.5%, potentially challenging future water availability and flood control operations. These findings highlight the need for adaptive and sustainable water management strategies to enhance climate resilience and advance SDG targets on water security, disaster risk reduction, and climate adaptation. Full article

As the transformative influence of novel technologies sweeps across industries, organisations are called upon to position their staff in the equally dynamic operational environment, which includes embedding technical and legal communication skills in their training programs. For many organisations, internal and external communication of data modelling and related concepts, reporting, and monitoring still pose major challenges. The aim of this research is to develop an effective data training framework for learners with or without mathematical or computational maturity. It also addresses subtle aspects such as the legal and ethical implications of dealing with organisational data. Data was collected from a training course in Python, delivered to government employees in different departments in the United Arab Emirates (UAE). A structured questionnaire was designed to measure the effectiveness of the training program using Python, from the employees’ perspective, based on three key attributes: their personal characteristics, professional characteristics, and technical knowledge. A descriptive analysis of aggregations, deviations, and proportions was used to describe the data attributes gathered for the study. The main findings revealed a huge knowledge gap across disciplines regarding the core skills of big data analytics. In addition, the findings highlighted that previous knowledge about statistical methods of data analysis along with prior programming knowledge made it easier for employees to gain skills in data analytics. While the results of this study showed that their training program was beneficial for the vast majority of participants, responses from the survey indicate that providing a solid knowledge of technical communication, legal and ethical aspects would offer significant insights into the big data analytics field. Based on the findings, we make recommendations for adapting conventional data analytics approaches to align with the complexity or the attainment of the non-orthogonal United Nations Sustainable Development Goals (SDG). Associations of selected responses from the survey with some of the key data attributes indicate that the research highlights vital roles that technology and data-driven skills will play in ensuring a more prosperous and sustainable future for all. Full article

Contract manufacturing is a pivotal strategy for brand owners, yet small-to-medium enterprises (SMEs) in emerging economies struggle to evolve beyond transactional roles into sustainable strategic partners. This study addresses this gap by empirically validating and refining the Mahove–Matope Sustainable Contract Manufacturing Company Maturity Model (SCMC-MM), a novel framework designed to guide SMEs through a holistic transformation. Through a seven-month longitudinal case study grounded in design science research approach within a South African food manufacturing SME, the model was implemented and evaluated using structured assessments, in-depth interviews, and longitudinal operational data. The application catalysed a system-wide transformation, yielding significant results, including a 133% increase in revenue, ISO 22000 certification, and perfect delivery reliability. Furthermore, the study theoretically refines the framework by identifying and incorporating novel critical success factors for contract manufacturing companies, such as industrial clustering and transformational leadership. The results demonstrate that the SCMC-MM offers a practical, actionable, and scalable tool for building resilient supply chain partnerships. It provides a structured pathway for SMEs to achieve simultaneous gains in economic performance, social equity through enhanced workforce capability and ethical practices, and environmental stewardship via formalised safety, health, and environmental and risk management systems, thereby contributing directly to the United Nations Sustainable Development Goals (SDGs) 8 and 9 in emerging markets. Full article

Over the 21st century, the confluence between engineering and universal accessibility has emerged as a key research domain, reflecting the growing awareness of the importance of inclusive layout in technological innovation. Despite the growing number of studies on sustainability and inclusion, there is still a lack of comprehensive analyses exploring how engineering contributes to universal accessibility within the framework of the United Nations Sustainable Development Goals. This study addresses this gap by providing the first large-scale mapping of research trends, collaborations, and thematic evolution in this field. The present bibliometric analysis examines the evolution of engineering research in relation to the United Nations Sustainable Development Goals, stressing its role in encouraging universal accessibility. Through a systematic review of scholarly works produced over the last twenty years, this study uncovers dominant issues, evolving research fronts, and the global relevance of engineering-based approaches to improve accessibility for persons with disabilities. Analyzing citation dynamics, publication trajectories, and institutional involvement, this study underlines the contribution of engineering to building inclusive societies and ensuring equitable access to technology and infrastructure. Discoveries underscore that cross-sector collaboration and technological innovation are essential to overcoming accessibility challenges among disfavored populations, directly advancing SDG 10 on reducing disparities and SDG 11 on sustainable urban development. Full article

Early prediction of common bean (Phaseolus vulgaris L.) yield is essential for improving productivity in tropical agricultural systems. In this study, we integrated canopy structural metrics obtained with the Tracing Radiation and Architecture of Canopies (TRAC) system, unmanned aerial vehicle (UAV)-based multispectral measurements (normalized difference vegetation index—NDVI, projected canopy area), and phenological variables collected from stages R6 to R8 under non-limiting nitrogen conditions. Exploratory analyses (correlation, variance inflation factors—VIF), dimensionality reduction (principal component analysis—PCA), and regularized regression (Elastic Net/LASSO), combined with bootstrap stability selection, were applied to identify a parsimonious subset of robust predictors. The final model, composed of six variables, explained approximately 72% of the variability in plant-level grain yield, with acceptable errors (RMSE ≈ 10.67 g; MAE ≈ 7.91 g). The results demonstrate that combining early vigor, radiation interception, and canopy architecture provides complementary information beyond simple spectral indices. This non-destructive framework delivers an efficient model for early yield estimation and supports site-specific management decisions in common bean with high spatial resolution. By enhancing input-use efficiency and reducing waste, this approach contributes to sustainable development and aligns with the global Sustainable Development Goals (SDGs) for climate-resilient agriculture. Full article

As global urbanization accelerates, cities increasingly shape economic growth and environmental outcomes, making sustainable urban and transport planning critical. Sustainable city branding (SCB) is emerging as a strategic tool that not only enhances a city’s global competitiveness but actively drives urban sustainability by integrating environmental, social, and economic dimensions aligned with the UN Sustainable Development Goals (SDGs). However, the direct link between SCB and transport planning remains largely unexplored, limiting actionable policy. This study introduces a novel conceptual framework connecting SCB with transport planning, positioning public transportation as a key lever for sustainable urban development. It identifies core interactions between city branding and sustainable mobility, proposes methodologies to evaluate SCB effectiveness, and addresses potential risks, challenges, and research gaps. A policy roadmap for decision-makers based on the framework is outlined. This roadmap is structured into three phases spanning a five-year program. In Phase 1, cities should lay the foundation by integrating SCB into municipal transport and sustainability plans and establishing measurable indicators aligned with the SDGs. Phase 2 focuses on engagement and experimentation, encouraging the creation of participatory branding platforms and the implementation of pilot projects, such as green mobility corridors or climate-resilient transit hubs. Finally, Phase 3 emphasizes monitoring and scaling, utilizing digital technologies for real-time tracking, evaluating pilot outcomes, and expanding successful initiatives based on key performance indicators, including ridership growth, carbon reduction, and citizen engagement. By linking SCB explicitly to transport planning and providing a concrete roadmap, this study offers a unique contribution to both urban sustainability research and practical policy-making, enabling cities to simultaneously strengthen their brand, enhance mobility, and achieve measurable sustainability outcomes. Full article

The construction industry is one of the most resource-intensive and environmentally impactful sectors, responsible for nearly 40% of global greenhouse gas emissions, over one-third of energy consumption, and a significant share of raw material depletion. These figures underscore the urgent need to transform conventional approaches to project delivery and resource management. Integrating construction management with environmental engineering offers a comprehensive pathway to enhance efficiency, mitigate environmental pressures, and align the sector with international sustainability commitments. This paper presents a systematic review of peer-reviewed studies published between 2000 and 2025 to evaluate sustainable practices that connect these two domains. The review focuses on five thematic areas: project delivery and management strategies with sustainability goals, environmental engineering tools such as pollution control and life cycle assessment, green certification frameworks, waste reduction and circular economy practices, and the integration of emerging digital and material technologies. Together, these areas illustrate how managerial systems and engineering solutions can jointly foster sustainable outcomes. The review indicates notable progress in fields such as green certification adoption, the use of Building Information Modeling for resource efficiency, and advanced recycling technologies. However, persistent challenges remain. These include the uneven uptake of sustainable practices between developed and developing economies, limited application of digital innovations such as artificial intelligence and the Internet of Things, and insufficient policy coordination to support the United Nations Sustainable Development Goals. By synthesizing dispersed insights across disciplines, this review contributes an integrated perspective that clarifies current achievements, highlights unresolved gaps, and suggests directions for future research and practice. The analysis is intended to support policymakers, industry professionals, and scholars in accelerating the transition toward a more resource-efficient and environmentally responsible construction sector. Full article

Biotechnology is increasingly recognized as a key driver for achieving the United Nations 2030 Agenda and its Sustainable Development Goals (SDGs). However, public awareness of its role remains uncertain. This study aimed to assess the knowledge, perceptions and opinions regarding the relationship between the SDGs and biotechnology among the general adult population in Spain. A validated online survey was distributed, yielding 274 responses. Although 84.3% of the respondents were familiar with the 2030 Agenda, positive perceptions of the SDGs were especially common among women and individuals with higher levels of education. Regarding biotechnology, 54.4% considered themselves knowledgeable, and nearly half (48.2%) recognized its potential contribution to health (SDG 3) and environmental sustainability, but its role in social and economic SDGs was less recognized. This study highlights the need for targeted educational and communication strategies to raise awareness and show how concrete biotechnological applications can contribute to sustainable development. Emphasizing these practical contributions can position biotechnology as a visible driver of progress and foster greater public engagement with science in achieving the 2030 Agenda. Full article

Environmental information fraud, such as greenwashing, severely impedes the achievement of global Sustainable Development Goals (SDGs). Blockchain technology, as an innovation tool with a sustainability orientation, offers new possibilities for improving the reliability of supply chain information oversight. However, its practical application mechanisms and policy value in green supply chain governance remain unclear. This study focuses on the greenwashing behavior of core enterprises and constructs an incomplete information game model to compare and analyze the inherent mechanisms of traditional regulation (TR) and blockchain-based digital supply chain regulation (DSCR). By simulating the strategic choices of enterprises between “genuine production” and “greenwashing” within a supply chain network, this research finds that when the quality of on-chain information reaches a certain threshold, the blockchain consensus mechanism can more accurately reveal corporate moral hazards, such as information manipulation, significantly reducing the incidence of greenwashing. As the number of enterprises participating in the blockchain network increases, the reliance on high-quality information in the DSCR model decreases, and regulatory efficiency is further enhanced through network effects. The findings provide theoretical support for designing regulatory strategies against greenwashing: Blockchain technology can build a trustworthy supply chain ecosystem through cross-enterprise data verification, directly supporting the SDG 12 goal of “Responsible Production.” Its decentralized nature helps optimize industrial infrastructure (SDG 9) and indirectly promotes climate action (SDG 13). This study suggests that regulatory agencies use policy tools such as “establishing on-chain information quality standards” and “incentivizing enterprises to join the blockchain network” to strengthen the practical application of the model, while also addressing implementation challenges such as data authenticity and digital infrastructure compatibility. Full article

Quartz in high-purity form, i.e., with an iron content <100 mg/kg, has valuable properties such as superior UV transmission, thermal stability, and resistance to devitrification, which are highly useful for optical applications. In this study, acid leaching was tested to optimize the production of optical-grade quartz from mined quartz, transforming an environmentally polluting process into a sustainable one, aligning with several United Nations Sustainable Development Goals (SDGs). Initially, when iron removal was obtained with direct, cross-current, and counter-current leaching methods, the results were unsatisfactory. However, a variation consisting of incorporating sulfuric acid regenerated via membrane filtration into the typical counter-current scheme was proven effective, reducing acid consumption and enhancing water recycling in the process, mitigating the environmental impact. The best optimized combination was the three-step counter-current method, with acid regeneration and fresh make-up after each cycle. The conditions were temperature 90 °C, solid-to-liquid ratio 30% wt/vol, time 3 h, and H₂SO₄ concentration of 1 M. The iron extraction yield was close to 89%. Full article