Search Results (237)

Promoting green utilization of cultivated land is the key to balancing resource use and ecological capacity. However, its working mechanisms are still unclear. This study attempts to address this empirical research gap through a three-stage cyclic system (Input-State-Output). It employed the PEST framework (Politics, Economy, Society, Technology) to identify external drivers. Using advanced methods, including the Super-SBM model, Dagum Gini coefficient, and Kernel density estimation, this paper mapped the spatiotemporal drivers of China’s green utilization efficiency of cultivated land (GUECL) between 2000 and 2020. The results indicate that despite some variation, the GUECL exhibited a distinct upward tendency over the study period. Spatially, efficiency was highest in northeastern China, while eastern and western China indicated moderate efficiency, and it was the lowest in central China. Regional differences generally narrowed, with trans-variation remaining the primary source of differences. External drivers varied across regions. At the national level, fiscal support and the R&D staff reduced GUECL, while economic growth increased it. In contrast, at the regional level, environmental regulation helped in western China, while income disparity boosted it in central China. Moreover, farm size and machinery use promoted GUECL in the eastern, central, and northeastern China, while cropping intensity and farmer education had positive effects in the central and eastern regions. This study provides a scientific foundation for developing region-specific strategies to promote the green utilization of cultivated land. It provides a valuable Chinese case for global research on sustainable land use. Full article

This study addresses key challenges in intensive aquaculture, such as passive environmental control, high energy consumption, and neglected fish stress, through the development of a multi-objective environmental regulation system for crucian carp utilizing behavioral stress feedback. It combines YOLOv8s-FasterNet for behavior recognition, a specific growth rate model and an energy cost model to form an intelligent decision-making mechanism that maximizes the output–input ratio. In a 25-day experiment, the system showed strong performance. Final body weight and specific growth rate were comparable to the control group. Economically, the system achieved periodic profits that were 8.93, 1.43, and 1.03 times greater than those of traditional threshold control at external temperatures of 2 °C, 8 °C, and 14 °C, respectively, demonstrating significant energy savings. In terms of animal welfare, principal component analysis confirmed significantly lower stress-induced damage in the experimental group, with a comprehensive score (−0.036) closer to the initial healthy group (0.223) versus the control group (−0.348). These results indicate that the system successfully optimized both economic efficiency and fish health, providing a viable solution for intelligent aquaculture management. Full article

This study aimed to explore the trade-offs between regional economic activity and environmental policy to explore economic approaches for reducing and managing pollutant discharge while maintaining a balance between socioeconomic activities and the marine environment. A linear programming simulation was conducted to model the interactions between socioeconomic activities, pollutant emissions, and reduction policies in the Omura Bay watershed. The model was designed to maximize Gross Regional Product (GRP), using inflow pollutant loads as a constraint. The simulation showed that a 12.7% reduction in 2015 pollutant loads is feasible under total load control. However, this level of reduction would cause a 14% decrease in watershed GRP. Further analysis revealed that reductions beyond 12.4% would significantly lower GRP and increase the cost of mitigation, making a 12.3% reduction the most realistic upper limit. The estimated cost of implementing countermeasures to manage pollutant inflow was JPY 6.7 billion, which would translate to a JPY 37.6 billion reduction in the cost to maintain current conditions and a JPY 26.7 billion reduction in the maximum reduction scenario (12.3%) with minimal economic impact. This analysis highlights the tradeoff between environmental protection and economic performance. A key innovation is the proposal of a “proper nutrient management” scenario, moving beyond uniform reductions to assess region-specific targets that consider ecological needs, such as those of the fishery industry. This approach emphasizes the importance of setting realistic and ecologically balanced reduction targets. Full article

This study examines how El Sistema, a global social music education program active in over 60 countries, contributes to the United Nations Sustainable Development Goals (SDGs). The program is analyzed using Sheerens’ CIPO (Context–Input–Process–Output) framework, which enables comprehensive evaluation of education from design and implementation to outcomes beyond simple result-focused assessment. The framework also accounts for political, social, and economic contexts, making it effective for understanding country-specific cases. Using this approach, this study analyzed how El Sistema has been localized across five representative case countries—Scotland, the United States, Sweden, Republic of Korea, and Japan. Data were collected through a narrative review integrating academic studies and credible non-academic sources, including government and organizational reports, program brochures, official websites, news articles, and multimedia materials. Findings indicate alignment with SDGs 1, 3, 4, 5, 8, 10, 11, 16, and 17. Country-specific strategies include community engagement in Scotland (SDG 17), partnerships in the United States (SDG 17), immigrant integration in Sweden (SDGs 11, 16), inclusive music education and cultural revitalization in the Republic of Korea (SDGs 11, 16, 17), and quality and healing education for disaster-affected and disabled children in Japan (SDG 11). These results suggest that El Sistema can serve as a sustainable model of social music education when supported by localized strategies, stable resources, multi-level governance, systematic evaluation, and proactive engagement with environmental initiatives. Full article

Renewable energy sources can be of significant help to rural communities with inadequate electricity access. This study presents a comprehensive techno-economic assessment of a 500 kWp solar Photovoltaic (PV) energy system designed for Ibadan, Nigeria. A novel hybrid modeling framework was developed in which technical performance analysis was employed using PVSyst, whereas economic and optimization analysis was carried out using HOMER. Simulation outputs from PVSyst were integrated as inputs into HOMER, enabling a more accurate and consistent cross-platform assessment. Nigeria’s enduring energy crisis, marked by persistent grid unreliability and limited electricity access, necessitates need for exploration of sustainable alternatives. Among these, solar photovoltaic (PV) technology offers significant promise given the country’s abundant solar irradiation. The proposed system was evaluated using meteorological and load demand data. PVSyst simulations projected an annual energy yield of 714,188 kWh, with a 25-year lifespan yielding a performance ratio between 77% and 78%, demonstrating high operational efficiency. Complementary HOMER Pro analysis revealed a competitive levelized cost of energy (LCOE) of USD 0.079/kWh—substantially lower than the baseline grid-only cost of USD 0.724/kWh, and a Net Present Cost (NPC) of USD 6.1 million, reflecting considerable long-term financial savings. Furthermore, the system achieved compelling environmental outcomes, including an annual reduction of approximately 160,508 kg of CO₂ emissions. Sensitivity analysis indicated that increasing the feed-in tariff (FiT) from USD 0.10 to USD 0.20/kWh improved the project’s financial viability, shortening payback periods to just 5.2 years and enhancing return on investment. Overall, the findings highlight the technical robustness, economic competitiveness, and environmental significance of deploying solar-based energy solutions, while reinforcing the urgent need for supportive energy policies to incentivize large-scale adoption. Full article

The olive flounder (Paralichthys olivaceus) is a significant aquaculture species in Korea, yet production has stagnated due to rising costs, environmental pressures, and shifting consumer preferences. Enhancing farm efficiency is critical not only for economic viability but also for environmental sustainability, as efficient production reduces resource waste, lowers feed inputs, and minimizes the carbon output of aquaculture operations. This study estimated the production function and efficiency of olive flounder farms in Korea using stochastic frontier analysis, drawing on survey data collected directly from producers. Results indicate that the Cobb–Douglas model is more suitable than the translog model for empirical analysis. The average farm efficiency was 0.38, with the lowest recorded efficiency at 0.13. Key determinants of production efficiency included fry quality, workforce size, and feed management. Regional differences were also observed in the technical inefficiency factor. By identifying inefficiencies and management gaps, this study highlights opportunities to enhance resource use efficiency, reduce environmental and economic waste, and promote more sustainable practices. The findings provide insights for policymakers and farm managers seeking to strengthen both the profitability and sustainability of the Korean olive flounder aquaculture industry. Full article

The equitable allocation of carbon emission responsibility is fundamental to advancing China’s industrial decarbonization, achieving its dual-carbon goals, and realizing regional sustainable development. However, prevailing interprovincial carbon accounting frameworks often neglect the coupled dynamics of economic benefits, energy flows, and ecological capacity, leading to systematic misattribution of industrial carbon footprint transfers. Here, we develop an integrated analytical framework combining multi-regional input–output (MRIO) modeling and net primary productivity (NPP) assessment to comprehensively quantify industrial carbon footprints and their transfers across 30 Chinese provinces. By embedding both the benefit principle (aligning responsibility with trade-generated economic gains) and the energy flow principle (accounting for interprovincial energy trade), we construct a dual-adjustment mechanism that rectifies spatial and sectoral imbalances in traditional accounting. Our results reveal pronounced east-to-west industrial carbon footprint transfers, with resource-rich provinces (e.g., Inner Mongolia, Xinjiang) disproportionately burdened by external consumption, impacting the balance of sustainable development in these regions. Implementing benefit and energy flow adjustments redistributes responsibility more fairly: high-benefit, energy-importing provinces (e.g., Shanghai, Jiangsu, Beijing) assume greater carbon obligations, while energy-exporting, resource-dependent regions see reduced responsibilities. This approach narrows the gap between production- and consumption-based accounting, offering a scientifically robust, policy-relevant pathway to balance regional development and environmental accountability. The proposed framework provides actionable insights for designing carbon compensation mechanisms and formulating equitable decarbonization policies in China and other economies facing similar regional disparities. Full article

Reducing food loss and waste (FLW) is a global priority under UN SDG 12.3, yet Taiwan has lacked stage-specific FLW data and systematic valuation of its environmental and economic implications. This study addresses these gaps by integrating localized FLW estimates from the APEC-FLOWS database with an enhanced analytical framework—the Environmentally Extended Input–Output Valuation (EEIO-V) model. The EEIO-V extends conventional input–output analysis by monetizing multiple environmental burdens, including greenhouse gases, air pollutants, wastewater, and solid waste, thereby linking FLW reduction to tangible economic benefits and policy design. The simulations reveal substantial differences in environmental cost reductions across supply chain stages, with downstream interventions delivering the largest benefits, particularly in reducing air pollution and greenhouse gases. By contrast, upstream measures contribute relatively smaller improvements. These findings highlight the novelty of EEIO-V in bridging environmental valuation with system-level FLW analysis, and they provide actionable insights for designing cost-effective, stage-specific strategies that prioritize downstream interventions to advance Taiwan’s sustainability and policy goals. Full article

The management of municipal solid waste (MSW) plays a crucial role in advancing sustainable development and circular economy goals across the European Union. In Italy, despite improvements in separate collection, significant regional disparities in MSW performance and costs persist. This study assesses the eco-efficiency of MSW services in 5516 Italian municipalities to uncover performance gaps and their underlying drivers. Eco-efficiency is measured using a Data Envelopment Analysis (DEA) model based on the Generalized Directional Distance Function (GDDF). This model incorporates per capita cost as an input, sorted waste as a desirable output, and residual waste as an undesirable output. A second-stage quantile regression is then utilized to explore how contextual factors influence eco-efficiency across various performance levels. The results reveal significant territorial disparities, with only 0.13% of municipalities achieving full eco-efficiency. Paradoxically, higher levels of separate waste collection—typically a policy goal—are associated with increased costs, especially in more efficient municipalities, suggesting a trade-off between environmental performance and economic sustainability. Similarly, population density negatively affects eco-efficiency but may facilitate economies of scale in collection systems. These findings highlight a tension between achieving optimal sorting rates and maintaining cost-effectiveness. Policy interventions should consider these trade-offs, prioritizing basic performance in lagging areas while promoting cost-control strategies in high-performing municipalities. Full article

The digital economy, as an advanced economic form, exerts a profound yet unclear influence on water environmental quality within large-scale watersheds. Focusing on the Yellow River Basin (YRB), the second-largest river in China, this study investigates this complex relationship. We developed a novel dual-engine coupling model integrating Support Vector Machines (SVM) and Light Gradient Boosting Machines (LightGBM) to establish comprehensive multi-input, multi-output linkages between digital economy indicators and water quality parameters. Results show that (1) There are notable spatial disparities and synergies in the basin, regions with more developed digital economy generally have better water environmental quality. (2) The SVM model effectively captures the complex spatial relationship between digital economy inputs and water quality outputs, with an average training accuracy above 0.80 and average validation accuracy above 0.70, indicating that digital economy variables are sensitive to water quality changes. (3) The LightGBM model identifies key driving factors and contributions, revealing that digital industrialization has a more significant impact on water quality improvement than industrial digitization. Thus, digital industrialization is a crucial pathway for green transformation in large—scale catchments. Full article

This study introduces a novel informatics framework for assessing regional sustainability by integrating Twin Mean-Variance Two-Stage Data Envelopment Analysis (TMV-TSDEA) with a desirability-based decision analytics system. The model evaluates both the efficiency and stability of economic and environmental performance across regions, supporting evidence-based policymaking and strategic planning. Applied to 16 Thai provinces, the framework incorporates a wide range of indicators—such as investment, population, tourism, industrial output, electricity use, forest coverage, and air quality. The twin mean-variance approach captures not only average efficiency but also the consistency of performance over time or under varying scenarios. A two-stage DEA structure models the transformation from economic inputs to environmental outcomes. To ensure comparability, all variables are normalized using desirability functions based on standardized statistical coding. The TMV-TSDEA framework generates composite performance scores that reveal clear disparities among regions. Provinces like Bangkok and Ayutthaya demonstrate a consistent high performance, while others show underperformance or variability requiring targeted policy action. Designed for integration with smart governance platforms, the framework provides a scalable and reproducible tool for regional benchmarking, resource allocation, and sustainability monitoring. By combining informatics principles with advanced analytics, TMV-TSDEA enhances transparency, supports decision-making, and offers a holistic foundation for sustainable regional development. Full article

This study focuses on Hohhot (the capital city of Inner Mongolia Autonomous Region, northern China), a representative arid-semi-arid town in northern China. Against the backdrop of concurrent rapid urbanization and ecological constraints, it undertakes a systematic investigation into the spatiotemporal evolution and driving mechanisms of ecological asset utilization efficiency, aiming to furnish scientific evidence for sustainable development in ecologically fragile urban areas. Employing a “technology-scale-structure” analytical framework and constructing an “input-output-benefit” evaluation system, this research integrates the super-efficiency slack-based measure (SBM) model with spatial analysis methodologies to conduct multidimensional assessments of ecological asset utilization efficiency across all administrative districts and counties from 2000 to 2020. Empirical results demonstrate an overall upward trajectory in Hohhot’s ecological asset utilization efficiency, with comprehensive efficiency increasing from 1.132 in 2000 to 1.397 in 2020. However, pure technical efficiency and scale efficiency exhibit significant asynchrony, reflecting inherent tensions between technological advancement and scale expansion. Spatially, efficiency distribution manifests substantial spatial clustering and heterogeneity, with identified hotspots demonstrating temporal migration patterns. Peripheral counties exhibit distinct “technological isolation” phenomena and diseconomies of scale. Mechanism analysis reveals that industrial structure optimization constitutes the primary driver of efficiency enhancement, while the catalytic effects of economic development and governmental investment exhibit diminishing marginal returns. Urbanization maintains a moderate influence, transitioning from extensive spatial expansion toward intensive functional upgrading. This study recommends a synergistic enhancement of ecological asset utilization efficiency through strategic pathways, including the following: First, advancing green industrial transformation. Second, establishing regional technology-sharing platforms. Third, implementing systematic ecological compensation mechanisms. Fourth, adopting spatially differentiated governance approaches. These measures are projected to foster coordinated environmental and economic development. This research provides theoretical underpinnings and policy implications for urban ecological asset management in arid and semi-arid regions globally. Full article

Oil consumption brings both energy security risks and environmental responsibilities. While traditional studies assign environmental responsibility primarily to oil producers, our research uncovers a geographical displacement of accountability: substantial oil volumes are embedded in traded goods and ultimately consumed in distant regions. Although China’s “dual control” policy regulates fossil energy use, it fails to account for the complexities of embodied oil flows. This oversight leads to imbalanced interregional responsibility allocation and resource exploitation issues. Adopting the “consumer pays” principle, this study makes methodological advances by innovatively combining multi-regional input–output (MRIO) modeling with geographically and temporally weighted regression (GTWR) analysis. The integrated approach provides spatial–temporal resolution in tracking embodied oil flows and their drivers across China’s provinces. Key findings include (1) strong concentration of oil inflows in developed eastern and central provinces, alongside rapid growth in southwestern regions; (2) evolving temporal patterns where economic growth and distance remain persistent drivers, while green technology and urbanization emerge as growing mitigating factors; (3) spatially, northwestern regions rely heavily on external supplies due to economic growth and urbanization, southeastern areas face rising transport costs, while green technologies in coastal regions have yet to significantly curb inflows due to rebound effects. These insights provide a new analytical framework for energy policy, supporting region-specific solutions to balance development and sustainability from a consumption perspective. Full article

This study evaluates the viability of a specific hybrid renewable energy system (HRES) installation designed for a remote community as a case study in Cuba. The system integrates solar, wind, and biomass resources to address localised challenges of energy insecurity and environmental degradation. Rather than offering a generalised evaluation of HRES technologies, this work focuses on the performance, impacts, and viability of this particular configuration within its unique geographical, social, and technical context. Using life cycle assessment (LCA) and input–output modelling, the research assesses environmental and socioeconomic impacts. The proposed HRES reduces greenhouse gas emissions by 60% (from 1.14 to 0.47 kg CO₂eq/kWh) and fossil energy consumption by 50% compared to diesel-based systems. Socioeconomic analysis reveals that the system generates 40.3 full-time equivalent (FTE) jobs, with significant employment opportunities in operation and maintenance. However, initial investments primarily benefit foreign suppliers due to Cuba’s reliance on imported components. The study highlights the potential for local economic gains through workforce training and domestic manufacturing of renewable energy technologies. These findings underscore the importance of integrating multiple renewable sources to enhance energy resilience and sustainability in Cuba. Policymakers should prioritise strategies to incentivise local production and capacity building to maximise long-term benefits. Future research should explore scalability across diverse regions and investigate policy frameworks to support widespread adoption of HRES. This study provides valuable insights for advancing sustainable energy solutions in Cuba and similar contexts globally. Full article

Our contemporary society is powered by fossil fuels, which results in environmental catastrophes. The combustion of these materials results in the release of CO₂, which accelerates the progression of climate change and its catastrophic consequences. The environmental repercussions of fossil fuel extraction have been highlighted through research into alternative energy sources. This inquiry uses the Tapio-Z decoupling approach to assess energy inputs and emissions. Furthermore, the fuzzy logic model is used to inspect the economic growth of the USA and China, as well as the impact of environmental factors, energy sources, and utilization, through decoupling effects from 1994 to 2023. The findings are substantiated by the individual perspectives of the environmental factors regarding decoupling, which ultimately lead to the acquisition of valuable results. We anticipate a substantial reduction in the total volume of CO₂ emissions in both the USA and China. Compared to China, the USA shows a significant increase in CO₂ emissions due to its reliance on fossil fuels. It is evident that a comprehensive transition to renewable resources and a broad range of technology is required to mitigate CO₂ emissions in high-energy zones. In their pursuit of sustainability, these two nations are making remarkable strides. The percentage change in CO₂ emissions indicates that effective changes in economic growth, energy input, and energy utilization, particularly sustainable energy, transmute energy output, as does the sustained implementation of robust environmental protection policies. The percentage change in CO₂ emissions indicates a remarkable transformation in energy input, energy consumption, and economic growth. This transition has been most visible in the areas of energy transformation, sustainability, and the maintenance of strong environmental protection measures. Full article