Search Results (3,097)

Energy recovery technology is becoming a crucial part of modern approaches that address decarbonization, efficiency, and transitioning into a circular economy. In addition, apart from its advancements in efficiency and environmental benefits, its progress appears to be progressively limited due to its maturity and increasing complexity. In this case, innovation that focuses solely in the firm appears ineffective because more and more important knowledge in terms of innovation in processes and environmental aspects is becoming and remaining outside of organizational boundaries. In this paper, open innovation will be explored in its function as a structural innovation method of advancing energy recovery technology. The paper employs the narrative literature review of peer-reviewed literature indexed in the Scopus database to explore the implications of the outside-in model of open innovation, the inside-out model of open innovation, and the coupled model of open innovation with respect to the primary recovery processes of energy such as combustion, gasification, pyrolysis, anaerobic digestion, and landfill gas recovery. The literature incorporates findings about the implications of knowledge inflows and outflows with respect to the mentioned energy recovery processes. The results show that open innovation efficacy strongly varies according to the degree of technological maturity and performance issues, in that outside-in open innovation tends to be very effective in mature and semi-mature technology sectors, where incremental improvements in efficiency require specialized knowledge outside the industry, while coupled open innovation is crucial for addressing system-wide issues in areas such as emissions, regulatory compatibility, and infrastructure integration, while inside-out innovation is largely a means of facilitating technology dissemination and standardization once a degree of technological maturity had been realized. This study, through the association of selective open innovation practices with corresponding energy recovery technology and challenges, aims to provide a more nuanced perspective on the assistive potential of collaborative innovation in effecting sustainable development in energy recovery technology. Full article

The growing demand for sustainable energy alternatives highlights the need for decision support tools in biodiesel supply chains. This study proposes a mixed-integer programming (MIP) model for tactical planning in the palm oil biodiesel supply chain, focusing on refining, blending, and distribution. The model incorporates economies of scale, inventory, and transport constraints and is enhanced with valid inequalities (VI) and a warm-start heuristic procedure (WS) to improve computational efficiency. Computational experiments on simulated instances with up to 6273 variables and 47 million iterations demonstrated robust performance, achieving solutions within 15 min. The model also reduced time-to-first-feasible (TTFF) solutions by 60–75% and CPU times by 17–21% compared to the baseline, confirming its applicability in realistic contexts. The proposed model provides actionable insights for managers by supporting decisions on facility scaling, product allocation, and profitability under supply–demand constraints. Beyond palm oil biodiesel, the formulation and its VI + WS enhancement provide a transferable blueprint for tactical planning in other process industry and renewable energy supply chains, where (i) multi-echelon flow conservation holds and (ii) discrete operating scales couple throughput with fixed/variable cost structures, enabling fast scenario analyses under changing prices, demand, and capacities. Full article

Rising global electricity demand and the expansion of distribution networks require a critical assessment of component-level greenhouse gas contributions. Distribution transformers, although indispensable, have significant life-cycle carbon impacts due to the use of materials, manufacturing, and in-service losses. This study conducts a life-cycle assessment of a single-phase, 75 kVA oil-immersed distribution transformer manufactured in Newfoundland, one of the provinces with the cleanest, hydro-dominated grids in Canada, and evaluates it over a 40-year lifespan. Using a cradle-to-use boundary, the analysis quantifies embodied emissions from raw material extraction, manufacturing, and transportation, alongside operational emissions derived from empirically measured no-load and load losses. All the data are collected directly during the manufacturing process, ensuring high analytical fidelity. The energy efficiency of the transformer is analyzed in MATLAB version R2023b using measured no-load and load losses to generate efficiency, load characteristics under various operating conditions. Under varying load factor scenarios and based on Newfoundland’s 2025 grid intensity of 18 g CO₂e/kWh, the lifetime operational emissions are estimated to range from 0.19 t CO₂e under no-load operation to 4.4 t CO₂e under full-load conditions. A linear regression-based decarbonization model using Microsoft Excel projects grid intensity to reach net-zero around 2037, two years beyond the provincial target, indicating that post-2037 transformer losses will remain energetically relevant but carbon-neutral. Sensitivity analysis reveals that temporary overloading can substantially elevate lifetime emissions, emphasizing the value of smart-grid-enabled load management and optimal transformer sizing. Comparative assessment with fossil fuel-intensive provinces across Canada demonstrates the dominant influence of grid generation mix on life-cycle emissions. Additionally, refurbishment scenarios indicate up to 50% reduction in cradle-to-gate emissions through material reuse and oil reclamation. The findings establish a scalable framework for integrating grid decarbonization trajectories, life-cycle carbon modelling, and circular-economy strategies into sustainable distribution network planning and transformer asset management. Full article

Industrial packaging systems exert substantial environmental pressures, including material resource depletion, greenhouse gas emissions, and the accumulation of post-consumer waste. As global supply chains expand and sustainability regulations intensify, demand for environmentally responsible packaging solutions continues to rise. This study evaluates the environmental footprint of industrial packaging by integrating recent developments in life cycle assessment (LCA), ecological footprint (EF) methodologies, material innovations, and circular economy models. The assessment examines the sustainability performance of conventional and alternative packaging materials, plastics, aluminum, corrugated cardboard, and polylactic acid (PLA). Findings indicate that although corrugated cardboard is renewable, it still presents a measurable environmental burden, with evidence suggesting that incorporating solar energy into production can reduce its footprint by more than 12%. PLA-based trays demonstrate promising environmental performance when sourced from renewable feedstocks and directed to appropriate composting systems. Despite these advancements, several systemic challenges persist, including ecological overshoot in industrial regions where EF may exceed local biocapacity limitations in waste management infrastructure, and significant economic trade-offs. Transportation-related emissions and scalability constraints for bio-based materials further hinder large-scale adoption. Existing research suggests that integrating sustainable packaging across supply chains could meaningfully reduce environmental impacts. Achieving this transition requires coordinated cross-sector collaboration, standardized policy frameworks, and embedding advanced environmental criteria into packaging design and decision-making processes. Full article

The transition toward a circular economy (CE) is progressively recognized as a strategic pathway to reconcile economic growth with environmental sustainability. Municipal solid waste management in Jordan remains mostly linear, with over 90% of the generated waste disposed of in landfills and open dumpsites. This study critically examines the prospects of adopting CE principles in Jordan’s waste sector by evaluating current practices, policy frameworks, and potential recycling pathways. A mixed-methods approach was adopted, combining quantitative modeling with qualitative insights from stakeholders and public surveys. Three recycling scenarios were assessed against the baseline scenario: 25%, 50%, and 75% waste recovery by 2034. The U.S. EPA WARM model was used to estimate greenhouse gas (GHG) emissions and energy savings. It was inferred that the net avoided emissions (against the baseline) for Scenarios 1, 2, and 3 are 14.5%, 29.0%, and 44%, respectively, with paper/cardboard contributing most to avoided emissions. Nonetheless, only Scenarios 2 and 3 were deemed environmentally sustainable, as their projected net GHG emissions for 2034 were lower than those recorded in the base year. Socio-economic analysis identified the major barriers as limited public awareness and participation, infrastructural gaps, and financial and institutional constraints. The analysis further reveals that despite the relatively high capital and operating costs associated with advancing toward CE in waste management, the long-term environmental and socio-economic gains are expected to outweigh the associated costs, particularly in terms of avoided GHG emissions and reduced landfill dependency. Full article

The accelerating global demand for sustainable energy, driven by population growth, industrialization, and environmental concerns, has intensified the search for renewable alternatives to fossil fuels. Biofuels, including bioethanol, biodiesel, biogas, and biohydrogen, offer a viable and practical pathway to reducing net carbon dioxide (CO₂) emissions. Yet, their large-scale production remains constrained by biomass recalcitrance, high pretreatment costs, and the enzyme-intensive nature of conversion processes. Recent advances in enzyme immobilization using magnetic nanoparticles (MNPs), covalent organic frameworks, metal–organic frameworks, and biochar have significantly improved enzyme stability, recyclability, and catalytic efficiency. Complementary strategies such as cross-linked enzyme aggregates, carrier-free immobilization, and site-specific attachment further reduce enzyme leaching and operational costs, particularly in lipase-mediated biodiesel synthesis. In addition to biocatalysis, nanozymes—nanomaterials exhibiting enzyme-like activity—are emerging as robust co-catalysts for biomass degradation and upgrading, although challenges in selectivity and environmental safety persist. Green synthesis approaches employing plant extracts, microbes, and agro-industrial wastes are increasingly adopted to produce eco-friendly nanomaterials and bio-derived supports aligned with circular economy principles. These functionalized materials have demonstrated promising performance in esterification, transesterification, and catalytic routes for biohydrogen generation. Technoeconomic and lifecycle assessments emphasize the need to balance catalyst complexity with environmental and economic sustainability. Multifunctional catalysts, process intensification strategies, and engineered thermostable enzymes are improving productivity. Looking forward, pilot-scale validation of green-synthesized nano- and biomaterials, coupled with appropriate regulatory frameworks, will be critical for real-world deployment. Full article

Economic growth is required for making progress in most of the sustainable development goals (SDGs). Energy access and quality education, along with gender equality, are amongst the SDGS and have also been amongst the essential factors to achieve improvement in economic growth. Hence, this research explores the impact of energy poverty alleviation, education quality, and gender equality on per capita GDP across E7 economies for the years of 2000–2024 benefiting from panel econometrics. The panel causality analysis uncovers a bidirectional causality between energy poverty alleviation, gender equality, and economic growth but a bilateral causal nexus from education quality to economic growth. Further, the cointegration coefficients indicate that education quality and gender equality are drivers of economic growth in E7 countries, while energy poverty alleviation is a positive determinant of economic growth in only China, India, and Indonesia. Full article

In the context of the ongoing digital revolution in manufacturing and the simultaneous advancement toward dual carbon objectives, this study investigates the role of intelligent technological advancements, particularly industrial robotics, in improving firm-level energy efficiency. Utilizing panel data from Chinese listed companies spanning the period 2012–2023, the research assesses the relationship between exposure to industrial robots and corporate energy efficiency metrics. The empirical analysis demonstrates that greater exposure to industry-level robotization substantially boosts corporate energy performance, verifying that intelligent modernization and green transition can be mutually reinforcing. This positive effect is particularly pronounced among superstar firms, in more competitive industries, and for capital-intensive enterprises. Mechanism analysis reveals that, first, robotization processes generate a scale effect that effectively dilutes the fixed energy consumption per unit of product. Second, the diffusion of robots intensifies market competition, creating a competition effect that compels all firms within the industry to optimize costs and management with a focus on energy conservation. This study demonstrates that enhancing human capital within organizations significantly amplifies the beneficial impact of robotic integration on energy efficiency metrics. By providing empirical data from an emerging market context, this research not only elucidates the role of industrial robots but also offers policy-relevant insights for developed economies navigating the concurrent challenges of industrial modernization and environmental sustainability. Full article

This paper examines the nexus between transportation infrastructure, economic growth, and carbon dioxide (CO₂) emissions in the United States, with particular emphasis on the moderating role of green energy consumption (GEC). The United States is an economically advanced country with a well-developed transport infrastructure and sustained economic growth; however, this development has been accompanied by increasing environmental pressures, notably rising CO₂ emissions from the transport sector. Drawing on the Environmental Kuznets Curve (EKC) framework, the study investigates whether renewable energy sources—specifically wind, solar, and hydropower—can decouple economic growth from environmental degradation. A Vector Error Correction Model (VECM) was employed to analyze both short-run dynamics and long-run cointegrating relationships among transport infrastructure, economic activity, CO₂ emissions, and green energy consumption. The results indicate that relative to fossil-based energy, green energy significantly mitigates the emission-enhancing effects of transport infrastructure expansion and economic growth. These findings underscore the pivotal role of renewable energy in achieving sustainable development. From a policy perspective, the results highlight the importance of integrating green energy into national transport and infrastructure planning. Overall, the study demonstrates that in transport-intensive economies, the expansion of renewable energy does not constrain economic growth but is essential for ensuring its long-term environmental sustainability. Full article

To accurately investigate the loss characteristics of fuel cell vehicles (FCVs) under actual operating conditions and enhance their power performance and economic efficiency, this study establishes a numerical model of the proton exchange membrane fuel cell (PEMFC) stack based on real-world data from the second-generation Mirai. The stack model incorporates leakage current losses and imposes a limit on maximum current density. Besides, this study analyzes the effects of operating parameters (PEM water content, hydrogen partial pressure, current density, oxygen partial pressure, and operating temperature) on stack power output, efficiency, and eco-performance coefficient (ECOP). Furthermore, Non-Dominated Sequential Genetic Algorithm (NSGA-II) is employed to optimize the PEMFC stack performance, yielding the optimal operating parameter set for FCV operation. Further simulations are conducted on dynamic performance characteristics of the second-generation Mirai under two typical driving cycles, evaluating the power performance and economy of the FCV before and after optimization. Results demonstrate that the established PEMFC stack model accurately analyzes the output performance of an actual FCV when compared with real-world performance test data from the second-generation Mirai. Through optimization, output power increases by 7.4%, efficiency improves by 1.95%, and ECOP rises by 3.84%, providing guidance for enhancing vehicle power performance and improving overall vehicle economy. This study provides a practical framework for enhancing the power performance and overall energy sustainability of fuel cell vehicles, contributing to the advancement of sustainable transportation. Full article

Glass wool waste constitutes a rapidly increasing fraction of construction and demolition residues, yet it remains one of the most challenging insulation materials to recycle. Its non-combustible nature, extremely low bulk density, and high fibre elasticity preclude energy recovery and severely limit conventional mechanical recycling routes, resulting in long-term landfilling and loss of mineral resources. Converting glass wool waste into a fine mineral powder represents a potentially viable pathway for its integration into low-carbon construction materials, provided that industrial scalability, particle-size control, and chemical compatibility with cementitious binders are ensured. This study investigates the industrial-scale milling of end-of-life glass wool waste in a ventilated horizontal ball mill. It compares two grinding routes: a corundum-free route (BK) and an abrasive-assisted route (ZK) employing α-Al₂O₃ corundum to intensify fibre fragmentation. Particle size distribution was quantified by laser diffraction using cumulative and differential analyses, as well as characteristic diameters. The results confirm that abrasive-assisted milling significantly enhances fragmentation efficiency and reduces the coarse fibre fraction. However, the study demonstrates that this gain in fineness is inherently coupled with the incorporation of α-Al₂O₃ into the milled powder, introducing a chemically foreign crystalline phase that cannot be removed by post-processing. From a cement-oriented perspective, this contamination represents a critical limitation, as α-Al₂O₃ may interfere with hydration reactions, aluminate–sulfate equilibria, and microstructural development in Portland and calcium sulfoaluminate binders. In contrast, the corundum-free milling route yields a slightly coarser, chemically unmodified powder, offering improved process robustness, lower operational complexity, and greater compatibility with circular economy objectives. The study establishes that, for the circular reuse of fibrous insulation waste in cementitious systems, particle fineness alone is insufficient as an optimization criterion. Instead, the combined consideration of fineness, chemical purity, and binder compatibility governs the realistic and sustainable reuse potential of recycled glass wool powders. Full article

Selecting a sustainable healthcare waste treatment method is a complex multi-criteria problem influenced by environmental, economic, social and technological factors. This study addresses key gaps in the literature by proposing an intuitionistic fuzzy AHP–TOPSIS framework that explicitly models cognitive uncertainty and expert hesitation, while demonstrating its application through a real-world case study in Adana, Türkiye. In contrast to prior studies utilizing fewer criteria, our framework evaluates four treatment alternatives—incineration, steam sterilization, microwave, and landfill—across 17 comprehensive criteria that directly integrate circular economy principles such as resource recovery and energy efficiency. The results indicate that steam sterilization is the most sustainable option, demonstrating superior performance across environmental, economic, social, and technological dimensions. A 15-scenario sensitivity analysis ensures ranking resilience across varying decision contexts. Furthermore, a systematic comparative analysis highlights the methodological advantages of the proposed framework in terms of analytical granularity and robustness compared to existing models. The study also offers step-by-step operational guidance, creating a transparent and policy-responsive decision-support tool for healthcare waste management authorities to advance sustainable practices. Full article

In the context of the “Dual Carbon” goals, achieving synergistic development between digitalization and green transformation in the coal power industry is essential for ensuring a just and sustainable energy transition. The core scientific problem addressed is the lack of a robust quantitative tool to evaluate the comprehensive performance of diverse transition scenarios in a complex environment characterized by multi-objective trade-offs and high uncertainty. This study establishes a sustainability-oriented four-dimensional performance evaluation system encompassing 22 indicators, covering Synergistic Economic Performance, Green-Digital Strategy, Synergistic Governance, and Technology Performance. Based on this framework, a Fuzzy DEMATEL–MultiMOORA–Borda integrated decision model is proposed to evaluate seven transition scenarios. The computational framework utilizes the Interval Type-2 Fuzzy DEMATEL (IT2FS-DEMATEL) method for robust causal analysis and weight determination, addressing the inherent subjectivity and vagueness in expert judgments. The model integrates MultiMOORA with Borda Count aggregation for enhanced ranking stability. All model calculations were implemented using Matlab R2022a. Results reveal that Carbon Price and Digital Hedging Capability (C13) and Digital-Driven Operational Efficiency (C43) are the primary drivers of synergistic performance. Among the scenarios, P3 (Digital Twin Empowerment and New Energy Co-integration) achieves the best overall performance (score: 0.5641), representing the most viable pathway for balancing industrial efficiency and environmental stewardship. Robustness tests demonstrate that the proposed model significantly outperforms conventional approaches such as Fuzzy AHP (Analytic Hierarchy Process) and TOPSIS under weight perturbations. Sensitivity analysis further identifies Financial Return (C44) and Green Transformation Marginal Economy (C11) as critical factors for long-term policy effectiveness. This study provides a data-driven framework and a robust decision-support tool for advancing the coal power industry’s low-carbon, intelligent, and resilient transition in alignment with global sustainability targets. Full article

In pursuit of global climate goals and sustainable development, countries have adopted a wide range of environmental policy instruments. This study examines the relationship between environmental policy stringency (EPS) and environmental outcomes, measured by carbon intensity (CI) and renewable energy intensity (REI), in 16 G20 countries from 1990 to 2020. The empirical findings reveal that more stringent environmental policy is a significant predictor of reduced CI and increased REI, although effects vary by policy type, time horizon, and country group. A novel sub-index-level analysis reveals that market-based incentive instruments, particularly trading schemes on CO₂ emissions and renewable energy, as well as technology support instruments, particularly wind and solar initiatives, exhibit the strongest and most robust effects. Emerging economies generally display greater responsiveness to policy interventions than advanced economies. By identifying which specific policy instruments are most effective across different development contexts, this study provides actionable insights for designing targeted climate policies that support both energy transition and sustainable development pathways. Full article

In this analysis, the dynamic nexus between green governance, energy transition, and carbon emissions in the period spanning 1990 and 2022 for the twenty-one member economies of the Organization for Economic Cooperation and Development (OECD) and partner economies is examined. Employing Feasible Generalized Least Squares (FGLS), Driscoll–Kraay Standard Errors (DKSE), and Quantile-on-Quantile Regression (QQR), this analysis encompasses the effects of the use of renewable energy sources, economic growth, and changes in the population on carbon emissions. Results for the analysis show that the adoption of renewable energy sources, tough environmental regulations, and green innovation play a significant role in offsetting carbon emissions since the results are more pronounced at the tail ends of the distribution of carbon emissions. Conversely, changes in the level of population and economic growth are identified as potential exacerbators of environmental concerns. In offering implications for policymakers, this analysis argues that environmental laws and taxation and green innovation are potential means of improving environmental governance in achieving the United Nations’ Sustainable Development Goals and climate change commitments. By addressing the issue of differential environmental effects based on varying levels of carbon emissions, this analysis makes contributions to the expanding literature on sustainable environmental governance in the twenty-first-century energy economy. Full article