Search Results (334)

This article analyses the role of the Spanish university system in promoting fair Trade (FT) and the sustainable development goals (SDGs), with a particular focus on the Universities for Fair Trade (UxFT) programme. A mixed methodology combining qualitative and quantitative approaches was used to review and analyse the websites of 90 Spanish universities (both public and private) to assess their commitment to FT and the SDGs. This was based on four variables: (1) reference to the SDGs; (2) a structured programme to promote the SDGs; (3) specific actions to promote or raise awareness of the SDGs; and (4) working on FT. The results show that, while most universities include the SDGs in their institutional strategies, only some have structured programmes. Regarding FT, several universities carry out activities linked to this movement, with some actively participating in the UxFT. Public universities demonstrate greater commitment. The SDGs that are most frequently addressed are 12 (Responsible consumption and production), 4 (Quality education) and 13 (Climate action), highlighting the close relationship between FT and sustainability. The study reveals a gap between discursive commitments to sustainability and the actual implementation of FT practices, suggesting that the integration of FT is not automatic even when SDG strategies are present. This has important implications: promoting FT within universities requires not only structured SDG strategies, but also explicit institutional policies, dedicated resources, and greater awareness of FT transformative potential. The findings underscore the need for stronger institutional commitment to move beyond isolated actions and toward a university model grounded in social justice and sustainability. Integrating the UxFT programme more broadly could help foster critical thinking, participatory governance, and more coherent practices aligned with the 2030 Agenda. Full article

This study develops a three-dimensional evaluation framework integrating policy instruments, policy themes, and policy subjects to analyze China’s ESG (Environmental, Social, and Governance) policies. Based on 82 central government policy documents issued between 2007 and 2024, it employs content analysis, Latent Dirichlet Allocation (LDA) topic modeling, and social network analysis. The findings reveal a structural imbalance in policy instruments, with overreliance on environmental instruments and insufficient application of supply side and demand side mechanisms. Four major policy themes are identified: environmental governance, corporate responsibility and disclosure, technological innovation, and financial development. These themes show evolving priorities aligned with national strategies. Social network analysis shows weak coordination among stakeholders, with only a few central agencies driving most policies. This research contributes a systematic and quantitative approach to ESG policy evaluation, offering insights into structural shortcomings and governance fragmentation. It provides actionable recommendations for optimizing instrument use, enhancing thematic design, and improving multi-agency collaboration in ESG policymaking. This study contributes to the achievement of the United Nations Sustainable Development Goals (SDGs), particularly SDG 12 (Responsible Consumption and Production) and SDG 13 (Climate Action), by evaluating China’s ESG policies and proposing a more balanced and pragmatic policy framework. Full article

This systematic review synthesizes evidence on economic instruments that mobilize renewable-energy investment in emerging economies, analyzing 50 peer-reviewed studies published between 2015 and 2025 under PRISMA 2020. We advance an Institutional Capacity Integration Framework that ties instrument efficacy to regulatory, market, and coordination capabilities. Green bonds have mobilized roughly USD 500 billion yet work only where robust oversight and liquid markets exist, offering limited gains for decentralized access. Direct subsidies cut renewable electricity costs by 30–50% and connect 45 million people across varied contexts, but pose fiscal–sustainability risks. Carbon pricing schemes remain rare given their administrative complexity, while multilateral climate funds show moderate effectiveness (coefficients 0.3–0.8) dependent on national coordination strength. Bibliometric mapping with Bibliometrix reveals three fragmented paradigms—market efficiency, state intervention, and international cooperation—and highlights geographic gaps: sub-Saharan Africa represents just 16% of studies despite acute financing barriers. Sixty-eight percent of articles employ descriptive designs, constraining causal inference and reflecting tensions between SDG 7 (affordable energy) and SDG 13 (climate action). Our framework rejects one-size-fits-all prescriptions, recommending phased, context-aligned pathways that progressively build capacity. Policymakers should tailor instrument mixes to institutional realities, and researchers must prioritize causal methods and underrepresented regions through focused initiatives for equitable global progress. Full article

Integrating renewable energy with biomass valorization offers a scalable pathway toward circular and climate-resilient campus operations. This study presents a replicable model implemented at Alanya Alaaddin Keykubat University (ALKU, Türkiye), where post-consumer food waste from 30 cafeteria menus is converted into pet food and compost using a 150 L ECOAIR-150 thermal drying and grinding unit powered entirely by a 1.7 MW rooftop photovoltaic (PV) system. The PV infrastructure, established under Türkiye’s first public-sector Energy Performance Contract (EPC), ensures zero-electricity-cost operation. On average, 260 kg of organic waste are processed monthly, yielding 180 kg of pet food and 50 kg of compost, with an energy demand of 1.6 kWh h⁻¹ and a conversion efficiency of 68.4%, resulting in approximately 17.5 t CO₂ emissions avoided annually. Economic analysis indicates a monthly revenue of USD 55–65 and a payback period of ~36 months. Sensitivity analysis highlights the influence of input quality, seasonal waste composition, PV output variability, and operational continuity during academic breaks. Compared with similar initiatives in the literature, this model uniquely integrates EPC financing, renewable energy generation, and waste-to-product transformation within an academic setting, contributing directly to SDGs 7, 12, and 13. Full article

This paper investigates technological pathways for the conversion of coal-fired power plants toward sustainable energy sources, using an integrated multi-criteria decision-making approach that combines Proknow-C, AHP, and PROMETHEE. Eight alternatives were identified: full conversion to natural gas, full conversion to biomass, coal and natural gas hybridization, coal and biomass hybridization, electricity and hydrogen cogeneration, coal and solar energy hybridization, post-combustion carbon capture systems, and decommissioning with subsequent reuse. The analysis combined bibliographic data (26 scientific articles and 13 patents) with surveys from 14 energy experts, using Total Decision version 1.2.1041.0 and Visual PROMETHEE version 1.1.0.0 software tools. Based on six criteria (environmental, structural, technical, technological, economic, and social), the most viable option was full conversion to natural gas (ϕ = +0.0368), followed by coal and natural gas hybridization (ϕ = +0.0257), and coal and solar hybridization (ϕ = +0.0124). These alternatives emerged as the most balanced in terms of emissions reduction, infrastructure reuse, and cost efficiency. In contrast, decommissioning (ϕ = −0.0578) and carbon capture systems (ϕ = −0.0196) were less favorable. This study proposes a structured framework for strategic energy planning that supports a just energy transition and contributes to the United Nations Sustainable Development Goals (SDGs) 7 and 13, highlighting the need for public policies that enhance the competitiveness and scalability of sustainable alternatives. Full article

Traditional urbanization prioritizes economic growth but often degrades the environment, challenging SDGs 9 and 13. China’s New-Type Urbanization Policy (NTUP) balances economic expansion, energy conservation, and environmental protection. By applying the difference-in-differences (DID) method, this study examines the causal effect of NTUP on urban air quality, taking the full implementation of NTUP in 2014 and the designated pilot cities as the policy shock and treatment group, respectively. Furthermore, we explore the mediating roles of land use efficiency and innovation efficiency in this relationship. The results show the following: (1) NTUP significantly lowers urban PM2.5, robust to confounders and selection bias; (2) land use and innovation efficiency mediate this effect, verified by Sobel and Bootstrap tests; and (3) policy effectiveness varies by city level, industrial base, and economic structure. These findings highlight NTUP’s environmental benefits and inform sustainable urbanization strategies globally. Full article

The aim of the study was to evaluate the digital business transformation across EU countries and its relationship with key Sustainable Development Goals (SDGs): SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 13 (Climate Action). The Digital Business Transformation Index, developed from eleven digital technology indicators related to e-business and e-commerce, is constructed using Principal Component Analysis to provide a comprehensive framework for assessing digitalization at the enterprise level. The results reveal substantial disparities among member states, with northern and western countries leading, while southern and eastern countries are lagging behind. Regression analyses show a strong positive relationship between digital business transformation and SDG 9 and a negative association with SDG 13. Cluster analysis identifies six groups of countries with varying levels of digital and sustainability performance and emphasizes the need for tailored policy responses. Evidence confirms a digital–green trade-off in many EU countries; however, strategic policy integration can mitigate this challenge. The findings underline the importance of targeted investments in R&D, digital infrastructure, and ICT training, particularly in underperforming regions. Tailored measures are essential to ensure that digital business transformation aligns with inclusive and sustainable development across the EU. Full article

Despite numerous global initiatives, such as the Sustainable Development Goals (SDGs) and the implementation of environmental, social, and governance (ESG) metrics aimed at mitigating climate change, promoting social welfare, and addressing a variety of other causes, progress has been significantly slower than expected, particularly in developing economies. Thus, we attempted to link corporate ESG to sustainable development. It was also investigated whether ESG contributes to a reduction in corporate risk. Using panel data and the Generalized Method of Moments (GMM) technique, we examine the relationship between ESG scores and important financial risk indicators such as systematic risk (beta), stock price volatility, unsystematic risk, and the cost of capital (WACC). The findings show that corporations place a disproportionate emphasis on governance (G) rather than environmental (E) and social (S) characteristics. ESG and G governance were also found to be statistically significant predictors of financial risk. This disparity shows that companies may be using high governance scores to conceal underperformance in environmental and social issues, raising worries about greenwashing and superficial compliance. As a result, their contributions to SDGs such as affordable and clean energy (SDG 7), climate action (SDG 13), and reduced inequalities (SDG 10) are minimal. The findings highlight the need for a more open, balanced, and integrated ESG approach, one that not only promotes sustainable development but also improves long-term financial resilience. Full article

Background: Access to healthy food in emerging-economy cities is challenged by last-mile constraints and poor infrastructure. Aligned with the UN SDGs on Zero Hunger and Sustainable Cities, this study examines how a strategically located nanostores network can help close these gaps while fostering local resilience. Focusing on Colombia’s Sabana Centro region, we designed a nanostore network that maximizes spatial coverage, proximity, and affordability. Methods: A competitive facility-location model combined with a discrete choice model captures consumer heterogeneity in price and location preferences. Results: Results show that locating nanostores in peripheral rather than central areas improves equity: the proposed network meets about 65,400 kg of weekly demand—51% fruit, 36% vegetables, 13% tubers—representing 16% of total regional demand and reaching underserved municipalities. This is notable given that existing nanostores already satisfy roughly 37% of household needs. Conclusions: By linking consumer behavior with sustainable spatial planning, the research offers both theoretical insight and practical tools for equitable distribution. Future work should evaluate supportive policies and supply chain innovations to secure nanostores’ long-term viability and community impact. Full article

The Tibetan Plateau’s lakes, serving as critical water towers for over two billion people, exhibit divergent responses to climate change that remain poorly quantified. This study develops a deep learning framework integrating Synthetic Aperture Radar (SAR) altimetry from Sentinel-3A with bias-corrected CMIP6 (Coupled Model Intercomparison Project Phase 6) climate projections under Shared Socioeconomic Pathways (SSP) scenarios (SSP2-4.5 and SSP5-8.5, adjusted via quantile mapping) to predict lake-level changes across eight Tibetan Plateau (TP) lakes. Using a Feed-Forward Neural Network (FFNN) optimized via Bayesian optimization using the Optuna framework, we achieve robust water level projections (mean validation R² = 0.861) and attribute drivers through Shapley Additive exPlanations (SHAP) analysis. Results reveal a stark north–south divergence: glacier-fed northern lakes like Migriggyangzham will rise by 13.18 ± 0.56 m under SSP5-8.5 due to meltwater inputs (temperature SHAP value = 0.41), consistent with the early (melt-dominated) phase of the IPCC’s ‘peak water’ framework. In comparison, evaporation-dominated southern lakes such as Langacuo face irreversible desiccation (−4.96 ± 0.68 m by 2100) as evaporative demand surpasses precipitation gains. Transitional western lakes exhibit “peak water” inflection points (e.g., Lumajang Dong’s 2060 maximum) signaling cryospheric buffer loss. These projections, validated through rigorous quantile mapping and rolling-window cross-validation, provide the first process-aware assessment of TP Lake vulnerabilities, informing adaptation strategies under the Sustainable Development Goals (SDGs) for water security (SDG 6) and climate action (SDG 13). The methodological framework establishes a transferable paradigm for monitoring high-altitude freshwater systems globally. Full article

Landslides pose persistent threats to mountainous regions in Taiwan, particularly in areas such as Nanfeng Village, Nantou County, where steep terrain and concentrated rainfall contribute to chronic slope instability. This study investigates spatiotemporal patterns of vegetation change as a proxy for identifying potential landslide-prone zones, with a focus on the Tung-An tribal settlement in the eastern part of the village. Using high-resolution satellite imagery from SPOT 6/7 (2013–2023) and Pléiades (2019–2023), we derived annual NDVI layers to monitor vegetation dynamics across the landscape. Long-term vegetation trends were evaluated using the Mann–Kendall test, while spatiotemporal clustering was assessed through Emerging Hot Spot Analysis (EHSA) based on the Getis-Ord Gi* statistic within a space-time cube framework. The results revealed statistically significant NDVI increases in many valley-bottom and mid-slope regions, particularly where natural regeneration or reduced disturbance occurred. However, other valley-bottom zones—especially those affected by recurring debris flows—still exhibited declining or persistently low vegetation. In contrast, persistent low or declining NDVI values were observed along steep slopes and debris-flow-prone channels, such as the Nanshan and Mei Creeks. These zones consistently overlapped with known landslide paths and cold spot clusters, confirming their ecological vulnerability and geomorphic risk. This study demonstrates that integrating NDVI trend analysis with spatiotemporal hot spot classification provides a robust, scalable approach for identifying slope hazard areas in data-scarce mountainous regions. The methodology offers practical insights for ecological monitoring, early warning systems, and disaster risk management in Taiwan and other typhoon-affected environments. By highlighting specific locations where vegetation decline aligns with landslide risk, the findings can guide local authorities in prioritizing slope stabilization, habitat conservation, and land-use planning. Such targeted actions support the Sustainable Development Goals, particularly SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 15 (Life on Land), by reducing disaster risk, enhancing community resilience, and promoting the long-term sustainability of mountain ecosystems. Full article

Forest litter plays a critical role in regulating the water balance of forest ecosystems, particularly in semi-arid regions where hydrological stability is under pressure due to climate change. This study investigates the maximum water holding capacity (MWHC) of litter layers across three ecologically distinct regions in Türkiye—Kastamonu, Kütahya, and Muğla—to evaluate how structural and physicochemical characteristics influence the maximum water holding capacity (MWHC) of litter layers. Litter samples classified into humus, fermenting debris, and needles were analyzed for MWHC, pH, electrical conductivity (EC), and total dissolved solids (TDSs). The results revealed that both the type of litter and regional ecological conditions significantly affect MWHC, with humus layers and moist environments exhibiting the highest water holding capacity. Additionally, MWHC showed moderate positive correlations with EC and TDS, highlighting the importance of chemical composition in water dynamics. The findings underscore that forest litter should be regarded as a dynamic and functional hydrological component, not merely residual biomass. This perspective is vital for sustainable watershed planning and adaptive forest management. The study supports the development of integrated management strategies aligned with the United Nations Sustainable Development Goals (SDGs), particularly SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), and SDG 15 (Life on Land). Full article

Sustainable energy entrepreneurs promote sustainable development by focusing more on energy efficiency. This study examines the interdependence and driving–dependent relationships among the socioeconomic factors (SEFs) influencing sustainable energy enterprises (SEEs). A mixed-methods approach is used, beginning with a literature review and expert consensus, followed by total interpretive structural modeling (TISM) and cross-impact matrix multiplication applied to classification (MICMAC) analysis. Seven key SEFs are finalized through interviews with 12 experts. Data are then collected from 11 SEEs. The study reveals that the regulatory and institutional framework emerges as the primary driving factor influencing other SEFs, including financial accessibility, market demand, technological innovation, and infrastructure readiness. Social and cultural acceptance is identified as the most dependent factor. The study proposes future research directions by identifying the United Nations sustainable development goals (SDGs) related to the antecedents, decisions, and outcomes with theoretical linkages through the Antecedents–Decisions–Outcomes (ADO) framework. The major SDGs identified are SDG 4 (education), SDG 7 (energy), SDG 9 (industry), SDG 11 (communities), and SDG 13 (climate). The study highlights that regulatory support, funding access, skill development, and technology transfer are required areas for strategic focus. Understanding the hierarchy of SEs supports business model innovation, investment planning, and risk management. Full article

In 2024, significant increases in surface temperature were recorded in Batam City and Bintan Regency, marking the highest levels observed in regional climate monitoring. The rapid conversion of vegetated land into residential and industrial areas has been identified as a major contributor to the acceleration of local climate warming. Climatological analysis also revealed extreme temperature fluctuations, underscoring the urgent need to understand spatial patterns of temperature distribution in response to climate change and weather variability. This research uses a Cellular Automata–Artificial Neural Network (CA−ANN) approach to model spatial and temporal changes in land surface temperature across the Riau Islands. To overcome the limitations of single-model predictions in a geographically diverse and unevenly developed region, Landsat satellite imagery from 2014, 2019, and 2024 was analyzed. Surface temperature data were extracted using the Brightness Temperature Transformation method. The CA−ANN model, implemented via the MOLUSCE platform in QGIS, incorporated additional environmental variables, such as rainfall distribution, vegetation density, and drought indices, to simulate future climate scenarios. Model validation yielded a Kappa accuracy coefficient of 0.72 for the 2029 projection, demonstrating reliable performance in capturing complex climate–environment interactions. The projection results indicate a continued upward trend in surface temperatures, emphasizing the urgent need for effective mitigation strategies. The findings highlight the essential role of remote sensing and spatial modeling in climate monitoring and policy formulation, especially for small island regions susceptible to microclimatic changes. Despite the strengths of the CA−ANN modeling framework, several inherent limitations constrain its application, particularly in the complex and heterogeneous context of tropical island environments. Notably, the accuracy of model predictions can be limited by the spatial resolution of satellite imagery and the quality of auxiliary environmental data, which may not fully capture fine-scale microclimatic variations. Full article

The Vietnamese Mekong Delta (VMD) is experiencing accelerated coastal erosion, driven by upstream sediment trapping, sea-level rise, and local anthropogenic pressures. This study evaluates the effectiveness of pilot breakwater structures in mitigating erosion and supporting mangrove regeneration along the western coast of Ca Mau Province—one of the delta’s most vulnerable shorelines. An integrated methodology combining field-based wave monitoring, remote sensing analysis of shoreline and mangrove changes (2000–2024), and high-resolution Flow-3D hydrodynamic modeling was employed to assess the performance of four breakwater typologies: semi-circular, pile-rock, Busadco, and floating structures. The results show that semi-circular breakwaters achieved the highest wave attenuation, reducing maximum wave height (H_max) by up to 76%, followed by pile-rock (69%), Busadco (66%), and floating structures (50%). Sediment accretion and mangrove stabilization were most consistent around the semi-circular and pile-rock types. Notably, mangrove loss slowed significantly after breakwater installation, with the annual deforestation rate dropping from 7.67 ha/year (2000–2021) to 1.1 ha/year (2021–2024). Simulations further revealed that mangrove width strongly influences wave dissipation, with belts under 5 m offering minimal protection. The findings highlight the potential of hybrid coastal protection strategies that combine engineered structures with ecological buffers. Modular solutions such as floating breakwaters offer flexibility to adapt with evolving shoreline dynamics. These findings inform scalable coastal protection strategies under sediment-deficit conditions. This study contributes to Vietnam’s Coastal Development Master Plan and broader resilience efforts under Sustainable Development Goals (SDGs) 13 and 14, providing evidence to inform the design and scaling of adaptive, nature-based infrastructure in sediment-challenged deltaic environments. Full article