Search Results (362)

When the global energy transition is analyzed through economic lenses, the constraints imposed by the laws of thermodynamics are often overlooked. This study addresses the Latecomer’s Dilemma—the predicament of semi-peripheral nations compelled to decarbonize without the capital stock accumulated following the example of the countries of the Global North during their more than two hundred years of industrial development associated with the saturation of the atmosphere with carbon dioxide. A novel phase space model of the Anthropocene is constructed, synthesizing the political concept of ecological debt with the biophysical reality of entropy debt. The application of the laws of systems ecology and non-equilibrium thermodynamics enables the mapping of national development trajectories against the saturated “atmospheric bathtub”. The analysis identifies a critical Injustice Gap—a region of phase space physically foreclosed by historical emissions. Moreover, it has been demonstrated that a circular economy powered by low-density renewables functions as an entropy trap, converting material debt into radiative debt without achieving a closed loop. Consequently, the Polish correction vector is proposed as a stabilization mechanism. This study’s findings indicate that addressing the emerging phenomenon of adaptation apartheid necessitates the implementation of a high-density energy flux, namely Generation IV nuclear reactors, which would be funded by a retroactive ETS3 mechanism. This approach fulfills the thermodynamic condition for material closure, thereby substantiating the notion that energy justice constitutes a physical necessity for planetary stability. This study quantifies the historical radiative debt of a single early-industrialized hub (Manchester) at approximately 142.8 billion EUR. The novelty lies in the synthesis of biophysical laws and the Latecomer’s Dilemma through the proposed ETS3 mechanism. Full article

The increasing penetration of wind and photovoltaic power intensifies power fluctuations and raises the requirement for reserve capacity allocation in hydro-wind-solar (HWS) systems. To address this issue, this study proposes a two-stage optimization framework for coordinated reserve configuration. In the first stage, the entropy weight method is used to evaluate heterogeneous reserve resources according to unit capacity cost, response time, and carbon emission intensity, thereby determining their response priority and obtaining an initial reserve allocation. In the second stage, alternative preference coefficient ratios for economy, rapidity, and low-carbon performance are assessed, and the resulting allocation proportions are fed back to the first stage to form a closed-loop optimization process. To solve the model, an improved Osprey Optimization Algorithm incorporating a Lens Imaging Opposition-Based Learning mechanism is adopted. A case study based on the Wudongde regional grid shows that the 2:1:2 preference-ratio scenario provides the best overall trade-off among the tested cases, with a reserve cost of 18,640.38 CNY (Chinese Yuan), carbon emissions of 8718.30 kg CO₂, and a response time of 4336.7 s. Compared with representative benchmark models, the proposed method achieves lower carbon emissions and faster response while maintaining competitive economic performance. The results demonstrate that the proposed framework can improve reserve allocation quality and operational adaptability in HWS systems with high renewable penetration. Full article

Unmanned Aerial Vehicle (UAV), particularly rotary-wing platforms such as quadcopters and octocopters, has evolved from controlled remote sensing platforms into autonomous agents capable of active task execution. This evolution from collect-then-analyze workflows to closed-loop perception, reasoning, and action signifies a paradigm shift toward Embodied AI, unlocking opportunities for the low-altitude economy. However, current research on UAV Embodied AI (UAV-EAI) often implicitly frames the field as a direct extension of indoor robotics or autonomous driving, which overlooks the fundamental distinctions of aerial agents. To bridge this gap, we introduce a comparative framework contrasting UAV-EAI with Indoor-EAI and Autonomous Driving Embodied AI (AD-EAI). By systematically decomposing the domain into nine key dimensions, we (i) analyze core tasks such as perception, localization, and exploration; (ii) review enabling infrastructure, including simulators and datasets; and (iii) categorize modeling methods ranging from physics-centric control to cognition-centric models. Our analysis demonstrates that the convergence of 6-DoF motion space, kilometer-scale unstructured environments, and stringent on-device constraints establishes a research regime qualitatively different from ground-based agents. These factors significantly impede the migration of existing VLM/LLM-based embodied systems for UAVs. Finally, we summarize open challenges and outline promising directions for the next generation of UAV-EAI. Full article

Life Cycle Assessment (LCA) is extensively employed to support sustainability evaluation in waste management and manufacturing systems; however, outcomes are highly sensitive to methodological decisions, particularly end-of-life (EoL) allocation approaches. This study examines how cut-off and substitution approaches affect the energy performance and decarbonisation potential of high-density polyethylene (HDPE) injection moulding systems. A dual framework is adopted: first, a literature review examines methodological sensitivities in EoL modelling; second, a quantitative case study assesses industrial-scale primary data for the production of durable HDPE bottles (300 mL). The LCA model integrates specific technical parameters, including a 220 °C melt temperature and a 36 s cycle time, ensuring a realistic representation of manufacturing conditions. The results indicate that allocation choices significantly influence calculated impacts, sometimes reversing the relative ranking of configurations. Substitution-based approaches report higher benefits by crediting avoided primary production, while cut-off logic provides more conservative estimates. Quantitative analysis shows that transitioning from open-loop to fully closed-loop configurations reduces cumulative energy demand by 3.2% and freshwater emissions per functional unit by 2.8%. Furthermore, the study identifies a ‘landfill paradox’ specific to HDPE waste within transitional energy systems: due to the carbon sequestration effect of landfilled polymers and current grid emission factors, landfilling exhibits a lower net carbon footprint (0.03 kg CO₂-eq./kg) than high-efficiency incineration (1.54 kg CO₂-eq./kg). These findings highlight that circular economy evaluations are strongly shaped by methodological assumptions, with direct implications for energy policy. Bridging the gap between specific industrial processing parameters and end-of-life allocation logic underscores the need to incorporate primary industrial data and transparent allocation frameworks to support reliable decision-making in the transition toward low-carbon and energy-efficient manufacturing systems. Full article

Blended polyester (PET)-based textiles comprise a significant portion of post-consumer waste, posing substantial challenges to circular economy initiatives while contributing to microfiber (MF) pollution. Despite the considerable recycling potential of PET textiles, no commercially viable technologies currently exist that can efficiently separate and recycle blended PET-based textile waste on an industrial scale. This review provides a comprehensive analysis of recycling strategies for post-consumer blended PET-based textiles and their subsequent valorization pathways. Mechanical, chemical, and biological recycling processes are mostly not yet market-ready, although chemical approaches are considered particularly promising. The findings highlight a critical need for advanced sorting technologies, enhanced material traceability, and robust MF mitigation strategies to foster circularity and contribute to the United Nations Sustainable Development Goals (SDGs). The results further indicate that mechanical recycling of blended PET textiles leads to significant MF release due to fiber fragmentation, whereas chemical recycling offers the potential for improved material recovery, but remains limited by high energy demand and solvent-related challenges. While closed-loop approaches support true circularity by maintaining textile-to-textile material flows, open-loop pathways repurpose textile waste for high-value non-textile applications. Full article

This paper addresses issues in islanded DC microgrids, including voltage deviation, inaccurate current sharing, and high communication burden, by proposing a distributed secondary control strategy that integrates a dynamic consensus algorithm with an adaptive event-triggered mechanism. Within a hierarchical control framework, the secondary layer employs an improved dynamic consensus algorithm to estimate the average voltage and proportional current through information exchange among neighboring nodes. Corresponding voltage and current compensations are designed to mitigate voltage droop and ensure accurate proportional sharing of load currents. In this study, a 100 V power supply is stepped down to 47.4 V following primary control. Then, by employing the secondary controller with the proposed algorithm, the voltage is precisely restored to the desired value of 48 V. To further reduce the communication burden, a dynamic event-triggered condition is intended for the output current of each power source, enabling communication and control updates only when the state changes significantly. This approach substantially reduces redundant data transmission and the frequency of controller actions. The positions of the triggering points under the action of the event trigger are also illustrated in the corresponding figures in the following sections. The positions of the triggering points under the action of the event trigger are illustrated in the corresponding figures in the following sections. While communication is accomplished, the voltage remains stable at 48 V. Furthermore, the currents of each distributed unit are stabilized around 6.4 A, satisfying the 1:1:1 current-sharing setting. The asymptotic stability of the closed-loop system is proven based on Lyapunov theory, and Zeno behavior is effectively avoided. Simulation results demonstrate that the proposed strategy achieves rapid voltage restoration and high-precision current sharing under scenarios such as load transients and plug-and-play operations while significantly reducing communication frequency and enhancing system economy and reliability. Full article

Electric vehicles are an important carrier for achieving energy savings and emission reductions in the transportation sector. As the decision-making core of the powertrain, the energy management strategy is responsible for power allocation and energy scheduling and directly determines vehicle economy, power-source lifetime, and overall performance. Model predictive control can handle multiple constraints and objectives within a prediction horizon and realize online closed-loop decision-making via receding-horizon optimization and has become an important research direction for energy management of electric vehicles. This paper presents the basic principles and typical modeling framework of model predictive control and reviews its research progress in hybrid electric vehicle energy management. The related studies are categorized and comparatively analyzed from three perspectives—prediction methods, solution strategies, and optimization objectives—and the characteristics of different approaches are summarized. The review shows that model predictive control has advantages in multi-objective trade-offs and adaptation to time-varying operating conditions. However, practical implementation still faces significant barriers, including prediction uncertainty and computational complexity. Finally, the challenges and future directions of model-predictive-control-based energy management strategies are discussed. Full article

This study addresses the increasing need to structure knowledge in the field of circular resource management, with a focus on energy efficiency and sustainable resilience. Previous studies have examined various taxonomies for the circular economy, yet a clear gap remains in understanding how energy efficiency and resilience serve as the main pillars for operational stability. This study is designed as a bibliometric analysis based on a selection of relevant scientific articles. The identified factors were extracted based on their frequency of occurrence in the literature and processed using statistical clustering techniques to group them into coherent categories. The results show that the field is defined by a set of interconnected factors that can be structured into distinct clusters, reflecting key dimensions such as operational performance, environmental impact, and system resilience. Specifically, the analysis demonstrates how energy-related attributes and resilience attributes act as stabilizing factors within closed-loop systems. Based on these findings, this study proposes a structured framework that organizes the identified factors into a clear configuration. This framework provides a reference point for researchers who aim to develop models in this area and for practitioners involved in the design and optimization of circular systems. This study contributes by offering a structured view of the field and by supporting the development of consistent analytical and decision-making approaches grounded in the necessity of balancing resource recovery with system stability. Full article

The increasing pressure on natural resources and the environment has intensified the need for sustainable cascade utilization in closed-loop supply chains (CLSCs). This study develops a game-theoretic framework to examine cascade utilization under both constant and heterogeneous quality restoration costs across three collection structures: centralized, manufacturer-led, and third-party collection. The results show that the relative performance of different structures depends on key economic conditions, including material recycling revenue and the comparative advantage of remanufacturing. No single structure dominates across all dimensions: a manufacturer-led collection tends to promote new product sales, while a third-party collection enhances remanufacturing and recovery levels, particularly under cost heterogeneity. Environmental performance, evaluated through collection quantity, cascade utilization efficiency, and an environmental impact indicator, also varies across structures, with cost heterogeneity shifting advantages toward the third-party collection. Policy analysis further indicates that both collection and remanufacturing subsidies increase recovery volumes but operate through distinct mechanisms. The collection subsidy expands return flows but may reduce cascade utilization efficiency by directing more low-quality products to recycling, whereas remanufacturing subsidy promotes higher-value reuse pathways and improves environmental performance. These findings highlight the importance of aligning collection structures and policy instruments under different cost conditions to enhance resource efficiency and support the circular economy and sustainable consumption and production objectives. Full article

Background: The growing emphasis on sustainability has increased interest in understanding how environmentally oriented supply chain practices translate into organizational outcomes. However, empirical research examining how circular economy principles, technological integration, and sustainable supply chain management (SSCM) practices jointly influence green supply chain performance remains limited, particularly in developing economies. Methods: A quantitative research design was employed using survey data collected from 333 professionals in the Lebanese consumer goods industry through structured Likert-scale questionnaires. The proposed conceptual model was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate the measurement model and test the relationships among circular economy practices, technological integration, SSCM practices, green supply chain performance, and organizational performance. Results: The findings indicate that technological integration, circular economy practices, and SSCM practices collectively enhance green supply chain performance. The results further show that improved green supply chain performance supports stronger organizational outcomes. Conclusions: This study contributes to sustainable supply chain literature by integrating circular economy principles, technological capabilities, and SSCM practices within a unified framework. It highlights the strategic role of green supply chain performance in linking sustainability initiatives to organizational outcomes and provides insights for managers seeking to implement integrated sustainability strategies. Full article

The transition toward sustainable food systems requires innovative approaches to managing perishable products, where inefficient inventory practices contribute significantly to global food loss and environmental degradation. This study develops a circular-economy-oriented inventory optimisation framework for dairy supply chains that integrates environmental externalities and waste valorisation pathways into operational decision-making. Departing from traditional linear “produce–consume–dispose” models, this study embeds three core sustainability mechanisms into a stochastic dynamic-programming framework: (1) progressive environmental cost internalisation aligned with EU Emissions-Trading System carbon pricing, capturing both waste-related emissions and cold-chain energy footprints; (2) circular-economy value-recovery channels that redirect near-expiry products to secondary applications (animal feed, biogas production, industrial processing) rather than disposal; and (3) deterioration-aware demand management that minimises resource throughput while maintaining service levels. Empirical calibration using Ukrainian dairy industry data demonstrates that sustainability-integrated inventory policies reduce waste generation by 4.8–10% relative to conventional approaches, with high-deterioration products showing the greatest potential for improvement. The authors identify a critical threshold in the circular economy: when salvage recovery rates exceed 35%, waste becomes an economic and ecological asset, fundamentally altering the sustainability calculus of inventory decisions. Environmental costs account for 4.6% of total operating expenses at current carbon prices, a share projected to increase substantially as climate regulations tighten. The findings provide actionable guidance for dairy supply chain stakeholders pursuing the Sustainable Development Goals (SDGs 2, 12, 13): processors should establish circular-economy partnerships that achieve salvage rates above 35%, implement product-specific policies for high-deterioration items, and proactively integrate carbon pricing into inventory optimisation. The framework bridges sustainable operations theory and circular economy practice, offering a replicable model for transitioning perishable food supply chains toward closed-loop, low-waste configurations that simultaneously reduce environmental impact and enhance economic performance. Full article

Sulfide-alkaline wastewater (SAW) from petrochemical plants, particularly from pyrolysis and hydrotreating units, presents a significant environmental challenge due to its high toxicity, extreme alkalinity (pH > 12), and high concentrations of sulfides and organic pollutants. Traditional treatment methods like acid neutralization or air oxidation are often inefficient, generate secondary waste, or fail to recover valuable components. This study investigates the effectiveness of a novel electrochemical system for the simultaneous treatment of SAW and recovery of valuable products. A lab-scale four-chamber electrodialyzer, equipped with cation-exchange membranes and nickel bipolar electrodes, was designed and tested using real industrial wastewater. The wastewater was characterized by a pH of 13.06, chemical oxygen demand of 12,600 mg/L, and a sulfide content of approximately 5000 mg/L. The process leverages anodic oxidation to convert sulfide ions into elemental sulfur, while sodium cations migrate through cation-exchange membranes to the cathodic compartments. There, water reduction generates high-purity hydrogen (≥99.9%) and a concentrated, purified sodium hydroxide solution. The results demonstrate the ineffectiveness of electrodialysis with anion-exchange membranes due to rapid membrane degradation. In contrast, the proposed electrodialyzer with bipolar electrodes achieved excellent performance: a caustic soda solution with a concentration of 2.3–2.5% was recovered with a current efficiency of 83–85%, containing only trace amounts of sulfides (0.0052%) and organic impurities (0.053%). The process completely removed the original sulfide alkalinity. The study confirms the chemical and mechanical stability of the cation-exchange membranes under harsh SAW conditions. The proposed technology offers a path towards a closed-loop system in refineries by enabling the reuse of recovered caustic, utilization of hydrogen, and potential recovery of sulfur, aligning with the principles of green chemistry and circular economy. Full article

In the era of increasing generation of various waste streams, the possibility of utilizing them as secondary resources is of utmost importance and fully corresponds to the goals of the circular economy. Industrial residues from the pulp and paper industry, such as biomass combustion ash (FARP) and sludge from industrial wastewater treatment (PPWS), together with natural zeolite as a modifying additive, represent valuable sources enabling their integrated valorization. The present study aims to investigate the potential for their reuse through the development of sustainable material blends. A comprehensive analysis of the chemical composition and morphology of the obtained mixtures was carried out using inductively coupled plasma optical emission spectroscopy (ICP-OES), X-ray diffraction (XRD), and scanning electron microscopy (SEM). The results indicate a tendency for the formation of mineral matrices dominated by calcium–sulfur–oxygen (Ca–S–O) phases, with the presence of calcium sulfate and aluminosilicate structures. The blends are associated with the formation of stable crystalline structures exhibiting potential pozzolanic activity. In this way, carbon is captured and fixed in a stable mineral form. The obtained results suggest the potential of these blends for use in low-carbon systems focused on waste valorization and carbon retention. The materials may be suitable for applications in construction, soil remediation, and environmental technologies, contributing to closing the resource loop “from farm to table and back again”. Full article

Research on the urban circular economy (CE) in developing regions often overlooks cross-sectoral interactions, social dimensions, data uncertainty, circularity metrics, and nonlinear trends, underscoring the need for integrated adaptive assessment. To address these gaps, we propose an integrated framework combining a nonlinear autoregressive with exogenous inputs (NARX) neural network and a fuzzy dynamic network slack-based measure (DNSBM) model to evaluate and improve urban CE performance across economic, environmental, and social dimensions in 107 cities of the Yangtze River Economic Belt (YREB) from 2011 to 2023. The results show a steady increase in aggregate efficiency and robustness across α-cut levels, alongside marked regional and stage heterogeneity. Downstream cities perform better because of more effective resource coordination, whereas upstream cities show greater potential for improvement. The main constraint is the social health dimension, reflecting persistent underinvestment in public health. ANN-based slack adjustment enhances efficiency estimation accuracy. Most cities need to reduce redundant inputs, curb pollution emissions, and increase health investment. This study contributes a closed-loop, multidimensional framework that captures temporal dynamics, data uncertainty, and cross-sectoral feedback and supports performance optimization and region-specific sustainability pathways. Full article

Background: Circular economy (CE) practices, such as glass bottle refilling, are critical to the beverage industry’s sustainability. However, coordinating manufacturer marketing efforts with collector reverse logistics investment remains a strategic challenge. Methods: This study develops a Stackelberg game-theoretic model featuring a manufacturer and a collector. The model incorporates communication effort as a demand driver and analyzes the role of bottle quality (damage rates) and the reusable bottle unit cost on the optimal decisions of the players and the collection rate. Results: Equilibrium analysis shows that the quality of the reusable bottle and the rate of bottle damage are crucial in reducing the operational costs of the refilling program. Additionally, these factors significantly influence the decisions made by manufacturers and collectors regarding their investments in communication and collection systems. Conclusions: The study demonstrates that successful refilling requires strategic coordination between manufacturers and collectors, particularly in terms of communication and investment in reverse logistics. Managerial insights indicate that investing in the quality of bottles is the key factor for achieving joint profitability. Full article