Search Results (281)

Achieving synergies between government-led and market-based policy instruments is critical to advancing Energy–Environmental Productivity and Sustainable Urban Development. This study investigates the effects of China’s dual-pilot energy policies (New Energy Demonstration Cities (NEDCs) and Energy Consumption Permit Trading (ECPT)) on urban environmental productivity (UEP) across 279 prefecture-level cities from 2006 to 2023. Utilizing a Non-Radial Directional Distance Function (NDDF) approach, combined with Difference-in-Differences (DID) estimation and spatial econometric models, the analysis reveals that these synergistic policies significantly enhance both comprehensive and net measures of UEP. Mechanism analysis highlights the roles of industrial restructuring, technological innovation, and energy transition in driving these improvements, while heterogeneity analysis indicates varying effects across different city types. Spatial spillover analysis further demonstrates that policy impacts extend beyond targeted cities, contributing to broader regional gains in UEP. These findings offer important insights for the design of integrated energy and environmental policies and support progress toward key Sustainable Development Goals (SDG 7, SDG 11, and SDG 12). Full article

In Japan’s hilly and mountainous areas, which cover over 60% of the national land area, issues such as population outflow, aging, and regional decline are intensifying. This study explored sustainable decarbonization pathways by examining two representative regions (Maniwa City and Hidakagawa Town), while accounting for diverse regional characteristics. A bottom-up approach was adopted to calculate energy consumption and CO₂ emissions within residential and transportation sectors. Six future scenarios were developed to evaluate emission trends and countermeasure effectiveness in different regions. The key findings are as follows: (1) in the study areas, complex regional issues have resulted in relatively high current levels of CO₂ emissions in these sectors, and conditions may worsen without intervention; (2) if the current trends continue, per-capita CO₂ emissions in both regions are projected to decrease by only around 40% by 2050 compared to 2020 levels; (3) under enhanced countermeasure scenarios, CO₂ emissions could be reduced by >99%, indicating that regional decarbonization is achievable. This study provides reliable information for designing localized sustainability strategies in small-scale, under-researched areas, while highlighting the need for region-specific countermeasures. Furthermore, the findings contribute to the realization of multiple Sustainable Development Goals (SDGs), particularly goals 7, 11, and 13. Full article

Progressive research on reducing engine emissions is highly valued due to the emissions’ significant environmental and health impacts. This comprehensive comparative study examines the catalytic efficiency of manganese (Mn) and cerium silica (Ce-Si) synthesis catalyst-based molds in a diesel engine using a selective catalytic reduction (SCR) technique with diesel and diesel–plastic oil blend (DPB) (B50). In addition to Fourier transform infrared spectroscopy (FTIR) studies, X-ray diffraction (XRD), scanning electron microscopy (SEM), and the Brunauer–Emmett–Teller (BET) method are utilized to characterize the produced molds before and after exhaust gas passes. The Ce-Si-based mold demonstrates superior redox capacity, better adsorption capacity, and better thermal stability, attributed to enhanced oxygen storage and structural integrity compared to the Mn-based mold. Under minimum load conditions, nitrogen oxide (NO) reduction efficiency peaks at 80.70% for the Ce-Si-based mold in the SCR treatment with DPB fuel. Additionally, significant reductions of 86.84%, 65.75%, and 88.88% in hydrocarbon (HC), carbon monoxide (CO), and smoke emissions, respectively, are achieved in the SCR treatment under optimized conditions. Despite a wide temperature range, Ce-Si-based mold promotes high surface area and superior gas diffusion properties. Overall, the Ce-Si-based mold provides efficient emission control in diesel engines, which paves a path for developing better environmental sustainability. The outcomes contribute to advancing environmental sustainability by supporting the achievement of SDGs 7, 11, and 13. Full article

This paper presents the Integrated Energy Community Performance Index (IECPI), a novel multi-criteria evaluation framework designed to assess the systemic performance of energy communities (ECs) across environmental, technological, social, and economic/institutional dimensions. Although ECs are increasingly recognized as pivotal actors in the decentralized energy transition, the absence of integrated assessment tools continues to hinder comparability, strategic planning, and long-term monitoring. The IECPI addresses this critical gap by structuring performance evaluation around nine normalized indicators, with their respective weights empirically derived from an influence matrix calibrated using interdependencies identified in 60 documented case studies. The IECPI integrates both objective and subjective metrics, capturing measurable outcomes alongside governance structures and contextual factors. The results reveal significant disparities in the performance of energy communities, allowing for the identification of five strategic typologies: Technologically Driven, Environmentally Oriented, Socially Embedded, Balanced Performance, and Structurally Fragile. The IECPI facilitates benchmarking, targeted policymaking, and cross-case learning while aligning with international frameworks such as SDG 7, EMAS, and principles of inclusive governance. As a scalable and transferable model, it provides a robust foundation for evidence-based planning, the evaluation of community resilience, and sustainability-oriented decision-making within distributed energy systems. Full article

Petroleum-based insulating liquids have traditionally been used in the electrical industry for cooling and insulation. However, their environmental drawbacks, such as non-biodegradability and ecological risks, have led to increasing regulatory restrictions. As a sustainable alternative, vegetable-based insulating liquids have gained attention due to their biodegradability, non-toxicity to aquatic and terrestrial ecosystems, and lower carbon emissions. Adopting vegetable-based insulating liquids also aligns with United Nations Sustainable Development Goals (SDGs) 7 and 13, which focus on cleaner energy sources and reducing carbon emissions. Despite these benefits, most commercially available vegetable-based insulating liquids are derived from edible seed oils, raising concerns about food security and the environmental footprint of large-scale agricultural production, which contributes to greenhouse gas emissions. In recent years, waste cooking oils (WCOs) have emerged as a promising resource for industrial applications through waste-to-value conversion processes. However, their potential as transformer insulating liquids remains largely unexplored due to limited research and available data. This review explores the feasibility of utilizing waste cooking oils as green transformer insulating liquids. It examines the conversion and purification processes required to enhance their suitability for insulation applications, evaluates their dielectric and thermal performance, and assesses their potential implementation in transformers based on existing literature. The objective is to provide a comprehensive assessment of waste cooking oil as an alternative insulating liquid, highlight key challenges associated with its adoption, and outline future research directions to optimize its properties for high-voltage transformer applications. Full article

The Belt and Road Initiative (BRI) prioritizes infrastructure investment to enhance regional connectivity and foster sustainable economic development. Therefore, this empirical study aims to examine the impact of the BRI, specifically through Chinese foreign direct investment (CFDI) on sustainable growth in Bangladesh. The study employs the Mann–Kendall trend analysis and the generalized method of moments (GMM). For the Mann–Kendall trend analysis, sectoral FDI and output data from four major industrial sectors, obtained from Bangladesh Bank and CEIC for the period 1996–2020, are used to analyze trends in industrial development. Additionally, to assess the BRI’s role in sustainable development, this study compares green gross domestic product (GGDP) and gross domestic product (GDP) using a GMM analysis of CFDI inflows across 16 industrial sectors from 2013 to 2022, sourced from various databases. Findings reveal that CFDI significantly contributes to domestic industrial growth, particularly in the manufacturing and construction sectors. Although Bangladesh joined the BRI in 2016, a notable surge in CFDI appears from 2011–2012, partially driven by Bangladesh’s economic liberalization policies, and reflects early strategic investment consistent with China’s expanding economic diplomacy, which was later formalized under the BRI framework. The two-step system GMM results demonstrate that CFDI has a stronger impact on GGDP (0.0350) than on GDP (0.0146), with GGDP showing faster convergence (0.6027 vs. 0.1800), highlighting more robust and rapid sustainable growth outcomes. This underscores the significant Chinese investment in green sectors in Bangladesh. The study also demonstrates that the BRI supports the achievement of Sustainable Development Goals (SDGs) 7 (green energy) and 9 (sustainable infrastructure). These insights offer valuable direction for future research and policy, suggesting that Bangladesh should prioritize attracting green-oriented CFDI in sectors like energy, manufacturing, and construction, while also strengthen. Full article

Small island developing states (SIDS) face a dual constraint of “environmental vulnerability and energy dependence” in the context of climate change. How to achieve just energy transitions has become a core proposition for SIDS to address. This paper focuses on how SIDS can advance Sustainable Development Goal (SDG) 7 (affordable and clean energy) and Sustainable Development Goal 13 (climate action) through UNCLOS–Paris Agreement integration in energy transitions. Grounded in the theoretical framework of the Multidimensional Vulnerability Index (MVI), this research aims to construct a comprehensive analytical system that systematically examines the energy transition challenges facing SIDS and provide multi-level energy transition solutions spanning from international to domestic contexts for climate-vulnerable SIDS. The research findings reveal that SIDS face a structural predicament of “high vulnerability–low resilience” and the triple challenge of “energy–climate–development”. International climate finance is severely mismatched with the degree of vulnerability in SIDS; the United Nations Convention on the Law of the Sea (UNCLOS) and the Paris Agreement lack institutional synergy and fail to adequately support marine renewable energy development in SIDS. In response to these challenges, this study proposes multi-level solutions to promote the synergistic achievement of SDG 7 and SDG 13: at the international level, improve climate finance rules, innovate financing mechanisms, strengthen technological cooperation, and integrate relevant international legal framework; at the domestic level, optimize the layout of marine renewable energy development, construct sustainable investment ecosystems, and strengthen environmental scientific research and local data governance. Full article

Modular and prefabricated buildings are advantageous in terms of construction, transport, energy efficiency, fixed costs, and the use of environmentally friendly materials. Our research aims to analyze, evaluate, and optimize a lightweight perimeter structure with an integrated active thermal protection (ATP). We have developed a mathematical–physical model of a wall fragment, in which we have analyzed several variants through a parametric study. ATP in the energy function of a thermal barrier (TB) represents a high potential for energy savings. Cold tap water (an average temperature of +6 °C, thermal untreated) in the ATP layer of the investigated building structure increases its thermal resistance by up to 27.24%. The TB’s mean temperature can be thermally adjusted to a level comparable to the heated space (e.g., +20 °C). For the fragment under consideration, optimizing the axial distance between the pipes (in the ATP layer) and the insulation thickness (using computer simulation) reveals that a pipe distance of 150 mm and an insulation thickness of 100 mm are the most suitable. ATP has significant potential in the design of sustainable, resilient, and climate-adaptive buildings, thereby meeting the UN SDGs, in particular the Sustainable Development Goal 7 ‘Affordable and Clean Energy’ and the Goal 13 ‘Climate Action’. Full article

This study investigates the relationship between disclosures related to Sustainable Development Goal 7 (SDG 7) and the financial profitability of Romanian commercial banks during the 2017–2023 period. Using an unbalanced panel dataset of 17 banks and applying fixed-effects regression models, the paper examines how transparency around energy-related sustainability practices influences various dimensions of bank profitability: recurring earning power (REP), loan yield (LY), return on assets (ROA), and return on equity (ROE). Macroeconomic energy indicators, such as the energy intensity level of primary energy (EnInt) and renewable energy consumption (REnC), are also controlled for. The findings indicate that SDG 7.1 disclosures are negatively associated with all profitability measures, except for LY, suggesting potential short-term trade-offs between sustainability transparency and financial outcomes. In contrast, SDG 7.2 disclosures positively impact REP, ROA, and ROE, underscoring the financial relevance of renewable energy financing. SDG 7.a disclosures show no significant relationship with profitability, indicating limited operational involvement in global energy cooperation. Additionally, higher energy intensity negatively affects REP and LY, supporting existing evidence that energy efficiency improves banking performance. These findings have implications for banking strategy, emphasizing the need to align sustainability disclosures with business priorities while recognizing the long-term benefits of green finance and energy efficiency. Full article

This study investigates how various renewable energy technologies influence national carbon intensity (CO₂ emissions per unit of GDP) across 184 countries over the period 2000–2020. In the context of Sustainable Development Goals (SDG 7 and SDG 13) and the post-Paris-Agreement policy landscape, it addresses the gap in understanding technology-specific decarbonization effects and the role of governance. A dynamic panel framework employing the Dynamic Common Correlated Effects (DCCE) estimator accounts for cross-sectional dependence and temporal persistence, while disaggregating total renewables into hydropower, wind, solar, and geothermal generation. Environmental regulation is incorporated as a moderating variable using the World Bank’s Regulatory Quality index. Empirical results demonstrate that higher renewable generation is associated with statistically significant reductions in carbon intensity, with hydropower showing the most consistent negative effect across all income groups. Solar and geothermal technologies yield substantial carbon-reducing impacts in lower-middle-income settings once supportive policies are in place. Wind exhibits heterogeneous outcomes: positive or insignificant effects in some high- and upper-middle-income panels prior to 2015, shifting toward neutral or negative after more stringent regulation. Interaction terms reveal that stronger regulatory environments amplify renewable-driven decarbonization, particularly for intermittent sources such as wind and solar. Key contributions include (1) a comprehensive global assessment of four disaggregated renewable technologies; (2) integration of regulatory quality into decarbonization pathways, illustrating post-2015 policy moderations; and (3) methodological advancement through a large-sample DCCE approach that captures unobserved common shocks and heterogeneous country dynamics. These findings inform targeted policy measures—such as prioritizing hydropower where feasible, strengthening regulatory frameworks, and tailoring technology strategies—to accelerate low-carbon energy transitions worldwide. Full article

In promoting sustainable cities and societies, accelerating the shift from sustainable building design to sustainable building operations is essential. A persistent challenge lies in the absence of a unified, multidimensional metric that enables meaningful performance comparisons across buildings of similar types and functions, both regionally and globally. This study develops and demonstrates the operational sustainability index (OPSi)—a novel metric grounded in case study research that integrates indoor environmental quality (IEQ) and energy utility quality (EUQ). OPSi is applied to six buildings in three comparative cases: (1) LEED-certified and non-certified dormitories, (2) LEED-certified and non-certified event buildings, and (3) male- and female-occupied multifamily housing units. Results show that the LEED-certified dormitory underperformed in two of five OPSi variants compared to its non-certified counterpart despite achieving up to 18% higher objective IEQ performance. The LEED-certified event building outperformed its non-certified counterpart across all OPSi metrics, with up to 88% higher objective IEQ scores. Findings also include higher energy performance in male-occupied housing units than in female-occupied ones, highlighting behavioral differences worthy of future study. This research addresses longstanding criticisms of green certification systems—particularly their limited capacity to holistically measure post-certification operational performance—by offering a practical and scalable evaluation framework. OPSi aligns with global sustainability goals, including SDG 11 (Sustainable Cities and Communities) and SDG 7 (Affordable and Clean Energy), and supports smart, data-driven decision-making. Future applications may extend OPSi to include carbon life cycle assessment and maintenance metrics to further strengthen building sustainability in urban contexts. Full article

This study examines the effects of artificial intelligence investments, green financing, government stability, and institutional quality on renewable energy consumption from a multidimensional perspective. Using panel data for the period 2014–2023, 15 leading countries in the field of green financing were included in the analysis. The Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) method was preferred in the empirical analysis; robustness tests were conducted with Fully Modified OLS (FMOLS) and Dynamic OLS (DOLS) estimators to assess the reliability of the findings. According to the findings, artificial intelligence investments have a significant and positive impact on renewable energy consumption in both the short and long term. Similarly, green financing contributes strongly and statistically significantly by enhancing the feasibility of clean energy projects. Furthermore, stable governments and the effective functioning of institutional structures support this process; both factors are observed to have a positive effect on renewable energy consumption. This study offers concrete policy recommendations in line with the United Nations sustainable development goals (SDGs) 7, 9, 13, and 16. Full article

Sustainable cropland management is essential in maintaining national food security. In the black soil regions of China, which are key areas for commercial grain production, sustainable land use must be achieved urgently. To address the absence of integrated, large-scale, remote sensing-based sustainability frameworks in China’s black soil zones, we developed a comprehensive evaluation system with 13 indicators from four dimensions: the soil capacity, the natural capacity, the management level, and crop productivity. With this system and the entropy weight method, we systematically analyzed the spatiotemporal patterns of cropland sustainability in the selected black soil regions from 2010 to 2020. Additionally, a diagnostic model was applied to identify the key limiting factors constraining improvements in cropland sustainability. The results revealed that cropland sustainability in Heilongjiang Province has increased by 7% over the past decade, largely in the central and northeastern regions of the study area, with notable gains in soil capacity (+15.6%), crop productivity (+22.4%), and the management level (+4.8%). While the natural geographical characteristics show no obvious improvement in the overall score, they display significant spatial heterogeneity (with better conditions in the central/eastern regions than in the west). Sustainability increased the most in sloping dry farmland and paddy fields, followed by plain dry farmland and arid windy farmland areas. The soil organic carbon content and effective irrigation amount were the main obstacles affecting improvements in cropland sustainability in black soil regions. Promoting the implementation of technical models, strengthening investment in cropland infrastructure, and enhancing farmer engagement in black soil conservation are essential in ensuring long-term cropland sustainability. These findings provide a solid foundation for sustainable agricultural development, contributing to global food security and aligning with SDG 2 (zero hunger). Full article

Electric vehicles (EVs) are central to the decarbonisation of transport systems and achievement of the Sustainable Development Goals (such as SDGs 7 and 13, affordable and clean energy and climate action, respectively). This study adopts a hybrid methodological framework, merging panel econometric models with machine learning (ML), to examine the drivers of EV adoption across Africa, China, and the European Union between 2015 and 2023. We analyse the influence of charging station density (CSD), GDP per capita, renewable energy share (RES), urbanisation, and electricity access using both first-difference and fixed-effects models for causal insight and Random Forest, XGBoost, and neural network algorithms for predictive analytics. While CSD emerges as the most significant driver across models, results reveal a paradox—GDP per capita demonstrates a negative relationship with EV adoption in econometric models yet ranks among the top predictive features in ML models. This divergence highlights the limitations of assuming linear causality in high-income settings and underscores the value of combining causal and predictive approaches. SHAP and PCA analyses further illustrate regional disparities, with Africa showing low feasibility scores due to infrastructure and grid limitations. Sub-regional case studies (Kenya, South Africa, Morocco, Nigeria) emphasise the need for tailored, integrated policies that address both energy infrastructure and transport equity. Findings highlight the value of combining interpretable models with predictive algorithms to inform inclusive and region-specific EV transition strategies. Full article

Understanding how sectoral CO₂ emissions shape sustainable development outcomes is essential for designing effective energy and economic strategies within the European Union (EU). This study presents a multidimensional analysis of CO₂ emissions, the contributions of individual sectors, and their connections to the Sustainable Development Goals (SDGs). Using Bayesian network analysis, the research identifies significant interdependencies between emission reductions and progress in sustainable development, highlighting the complex relationship between energy transition, economic growth, and social justice. The findings show that total CO₂ emissions in the EU have decreased since 1990; however, the rate of reduction varies across sectors and member states. The most substantial decreases have been recorded in the energy sector, while industrial processes and agriculture show slower progress. Economic crises, such as the 2008 financial collapse and the COVID-19 pandemic, have led to temporary declines in emissions; however, lasting achievements in sustainability require structural transformations rather than short-term disruptions. The Bayesian model reveals strong connections between emission reductions and progress on clean energy (SDG 7), responsible consumption (SDG 12), and climate action (SDG 13), while also indicating indirect impacts on economic growth (SDG 8) and social equity. This highlights the importance of integrated policymaking to maximise the benefits of sustainable development. This study provides a data-driven foundation for enhancing EU climate strategies, ensuring that emission reductions support environmental goals, economic resilience, and social well-being. Full article