Search Results (18,806)

This research evaluates the carbon dioxide emission-reduction efficiency of new energy vehicles (NEVs) in China from 2018 to 2023 by applying a three-stage super-SBM data envelopment analysis (DEA) model that incorporates undesirable outputs. This model offers significant advantages over traditional DEA models, as it effectively disentangles the influences of external environmental factors and stochastic noise, thereby providing a more accurate and robust assessment of true efficiency. Its super-efficiency characteristic also allows for effective ranking of all decision-making units (DMUs) on the efficiency frontier. The empirical findings reveal several key insights. (1) The NEV industry’s carbon-reduction efficiency in China between 2018 and 2023 displayed an upward trend accompanied by pronounced fluctuations. Its mean super-efficiency score was 0.353, indicating substantial scope for improvements in scale efficiency. (2) Significant interprovincial disparities in efficiency appear. Unbalanced coordination between production and consumption in provinces such as Shaanxi, Beijing, and Liaoning has produced correspondingly high or low efficiency values. (3) Although accelerated urbanization has reduced the capital and labor inputs required by the NEV industry and has raised energy consumption, the net effect enhances carbon-reduction efficiency. Household consumption levels and technological advancement exerts divergent effects on efficiency. The former negatively relates to efficiency, whereas the latter is positively associated. Full article

As an important part of global carbon neutrality strategies, carbon dioxide (CO₂) capture, utilization, and storage technologies have emerged as critical solutions for reducing carbon emissions. However, conventional CO₂ applications, including food preservation, industrial synthesis, and enhanced oil recovery, face inherent limitations such as suboptimal gas–liquid mass transfer efficiency and inadequate long-term stability. Recent advancements in CO₂ micro-nanobubbles (CO₂ MNBs) have demonstrated remarkable potential across multidisciplinary domains, owing to their distinctive physicochemical characteristics encompassing elevated internal pressure, augmented specific surface area, exceptional stability, etc. In this review, we try to comprehensively explore the unique physicochemical properties of CO₂ MNBs and their emerging applications, including industrial, agricultural, environmental, and energy fields. Furthermore, we provide a prospective analysis of how these minuscule bubbles can emerge as pivotal in future technological innovations. We also offer novel insights and directions for research and applications across related fields. Finally, we engage in predicting their future development trends as a promising technological pathway for advancing carbon neutrality objectives. Full article

Industrial wastewater pollution has reached acute levels in the environment; consequently, scientists are developing new sustainable treatment methods. Lignocellulosic biomass (LB) stands as a promising raw material because it originates from agricultural waste, forestry residues, and energy crop production. This review examines the application of nanomaterials derived from lignocellulosic resources in wastewater management, highlighting their distinctive physical and chemical properties, including a large surface area, adjustable porosity structure, and multifunctional group capability. The collection of nanomaterials incorporating cellulose nanocrystals (CNCs) with lignin nanoparticles, as well as biochar and carbon-based nanostructures, demonstrates high effectiveness in extracting heavy metals, dyes, and organic pollutants through adsorption, membrane filtration, and catalysis mechanisms. Nanomaterials have benefited from recent analytical breakthroughs that improve both their manufacturing potential and eco-friendly character through hybrid catalysis methods and functionalization procedures. This review demonstrates the ability of nanomaterials to simultaneously turn waste into valuable product while cleaning up the environment through their connection to circular bioeconomic principles and the United Nations Sustainable Development Goals (SDGs). This review addresses hurdles related to feedstock variability, production costs, and lifecycle impacts, demonstrating the capability of lignocellulosic nanomaterials to transform wastewater treatment operations while sustaining global sustainability. Full article

Carbon emission reduction serves as a pivotal strategy for advancing global environmental quality and sustainable socioeconomic development. Private enterprises serve as the primary contributors to industrial carbon emissions. Their low-carbon transition is directly tied to the achievement of China’s Dual Carbon Goals. However, constrained by market failures and the profit-driven nature of capital, these enterprises face significant challenges in both motivation and capacity for carbon emission reduction. As a critical link connecting government and market forces, whether state-owned capital can effectively drive private enterprises to reduce emissions and conserve energy still lacks systematic empirical evidence. Leveraging a panel dataset of private industrial listed companies on China’s Shanghai and Shenzhen A-share markets spanning 2008–2022, we examine the impact of state-owned capital participation on carbon emission reduction and the underlying mechanisms. The empirical results demonstrate that state-owned capital participation can significantly drive carbon emission reduction and propel the low-carbon transformation of private enterprises. Mechanism analysis reveals that state-owned capital participation promotes carbon emission reduction through multiple avenues, including enriching the green resource base, strengthening the value recognition of environmental social responsibility, and improving energy efficiency. Further analysis indicates that the emission reduction effect of state-owned capital participation is more pronounced under conditions of weaker government environmental regulation, lower regional marketization, greater industry competition, and tighter green financing constraints. This study enriches the research on mixed-ownership reform and low-carbon transition of enterprises, deepens the theoretical understanding of the internal mechanism of state-owned capital participation affecting carbon emission reduction, and offers empirical evidence for emerging economies to address the dilemma of emission reduction through property rights integration. Full article

The electric arc furnace (EAF) is a key technology in the steel production industry, particularly for recycling scrap iron. It plays a crucial role in the shift to low-carbon metallurgy, responding to the growing demand for more sustainable production methods. Alongside its environmental and energy benefits, the EAF process generates significant amounts of solid by-products, including dust (EAFD) and slag (EAFS). These wastes are not only rich in base metals but also contain critical elements, which have attracted increasing scientific and industrial interest. Depending on the waste type, key metals such as zinc (from EAFD) and chromium, vanadium, and titanium (from EAFS) are targeted for recovery. This review examines the chemical and phase compositions of these wastes, various leaching techniques (often combined with pretreatment stages), and methods for final metal recovery, either in their pure form or as compounds. Key challenges in hydrometallurgical routes include chloride contamination, the dissolution of refractory zinc ferrite, and impurity management. Despite current limited industrial adoption, hydrometallurgical approaches show significant promise as efficient and environmentally friendly solutions for resource recycling, offering high-purity metal recovery. Full article

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

The integration of 5G technology with cloud and edge computing is redefining the digital landscape by enabling ultra-fast connectivity, low-latency communication, and scalable solutions across diverse application domains. This paper investigates the synergistic impact of 5G on cloud-to-edge architectures, emphasizing its transformative role in revolutionizing sectors such as healthcare, smart cities, industrial automation, and autonomous systems. Key advancements in 5G—including Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), and Massive Machine-Type Communications (mMTC)—are examined for their role in enabling real-time data processing, edge intelligence, and IoT scalability. In addition to conceptual analysis, the paper presents simulation-based evaluations comparing 5G cloud-to-edge systems with traditional 4G cloud models. Quantitative results demonstrate significant improvements in latency, energy efficiency, reliability, and AI prediction accuracy. The study also explores challenges in infrastructure deployment, cybersecurity, and latency management while highlighting the growing opportunities for innovation in AI-driven automation and immersive consumer technologies. Future research directions are outlined, focusing on energy-efficient designs, advanced security mechanisms, and equitable access to 5G infrastructure. Overall, this study offers comprehensive insights and performance benchmarks that will serve as a valuable resource for researchers and practitioners working to advance next-generation digital ecosystems. Full article

Traditional crosslinked-polyethylene (XLPE) insulation suffers from high recycling costs and low efficiency due to its thermosetting properties. In contrast, thermoplastic polypropylene (PP), with advantages of melt recyclability, low energy consumption, and excellent comprehensive performance, has emerged as an ideal alternative to XLPE. This study conducts a comparative analysis of low-voltage cables insulated with PP, silane-crosslinked XLPE (XLPE-S), and UV-crosslinked XLPE (XLPE-U), focusing on production processes, mechanical properties, thermal stability, and electrical performance. Tensile test results show that PP exhibits the highest elongation at break (>600%) before aging, and its tensile strength (>20 MPa) after aging outperforms that of XLPE, indicating superior flexibility and anti-aging capability. PP exhibits a lower thermal elongation (<50%) at 140 °C compared to XLPE, and its high-crystallinity molecular structure endows better heat-resistant deformation performance. The volume resistivity of PP reaches 9.2 × 10¹⁵ Ω·m, comparable to that of XLPE-U (3.9 × 10¹⁵ Ω·m) and significantly higher than XLPE-S (3.0 × 10¹⁴ Ω·m). All three materials pass the 4-h voltage withstand test, confirming their satisfied insulation reliability. PP-insulated low-voltage cables demonstrate balanced performance in production efficiency, energy consumption cost, mechanical toughness, and electrical insulation. Notably, their recyclability significantly surpasses traditional XLPE, showing potential to promote green upgrading of the cable industry and providing a sustainable insulation solution for low-voltage power distribution systems. Full article

In the digital economy era, artificial intelligence, big data, and 5G are widely applied across various industries. The deep integration of digitalization and traditional sectors has been facilitated by this trend, which has injected new momentum into industrial development. In this context, this paper employs panel data from 29 Chinese provinces that span the years 2017 to 2023. This paper transcends the constraints of current research by integrating the digital economy with the export of new energy vehicles. Furthermore, this paper provides a regional analysis of this impact, thereby contributing to the existing literature. The following are the conclusions: (1) The export of new energy vehicles is substantially stimulated by the development of the digital economy. (2) Exports are indirectly facilitated by the digital economy, which promotes technological innovation and financial services. (3) The digital economy shows a significantly greater impact on the export of new energy vehicles in the eastern and inland areas than in other regions. Based on these discoveries, the paper suggests four critical policy recommendations: expanded openness, technological innovation, intelligent digital marketing, and government support. The objective is to foster the sustainable growth of China’s new energy vehicle export trade. This paper offers theoretical support for the sustainability of Chinese enterprises’ competitiveness in the international market. It also provides policymakers and industry stakeholders with practical advice. Full article

A friction composite material which contains cellulose fiber, carbon fiber, wollastonite, graphite, and resin for use in oil-cooled friction units, hydromechanical boxes, and couplings was developed. The fabrication technique includes the formation of a paper layer based on the mixture of stated fibers via a wet-laid process, impregnation of the layer with phenolic resin, and hot pressing onto a steel carrier. The infrared spectra of the polymeric base (phenolic resin) were studied by solvent extraction. The structural-phase analysis of the obtained material was carried out by the SEM method, and the particle size distribution parameters of the composite components were estimated based on the images of the sample surface. The surface roughness parameters of the samples are as follows: Ra = 5.7 μm Rz = 31.4 μm. The tribotechnical characteristics of the material were tested in an oil medium at a load of 5.0 MPa and a rotation mode of 2000 rpm for 180 min in a pair with a steel 45 counterbody. The coefficient of friction of the developed material was 0.11–0.12; the degree of wear was 6.17 × 10⁻⁶ μm/mm. The degree of compression deformation of the composite is 0.36%, and the compressive strength is 7.8 MPa. The calculated kinetic energy absorbed and power level are 205 J/cm² and 110 W/cm², respectively. The main tribotechnical characteristics of the developed friction material correspond to industrial analogues. Full article

Accurate parameter identification in dynamic models of robotic arms is essential for performing high-performance control and energy-efficient procedures. However, classic methods often encounter difficulties when modeling nonlinear, high-dimensional systems, particularly in the presence of real-world uncertainties. To address these challenges, this study focuses on identifying mass center positions and inertia matrix elements in a six-jointed industrial robotic arm and comparing the influence of optimized algorithms: the classical Particle Swarm Optimization (PSO) and the Quantum-behaved Particle Swarm Optimization (QPSO). The robot’s kinematic model was validated by comparing it with actual motion data, utilizing a high-precision neural network to ensure accuracy before conducting a dynamic analysis. A comprehensive dynamic model was created using Computer-Aided Optimization (CAO) in SolidWorks Premium 2023 to simulate realistic mass parameters, thereby validating the model’s reliability in a practical setting. The real (Referenced) and optimized dynamic models of the robot arm were validated using trajectory tracking simulations under sliding mode control (SMC) to assess the impact of the optimized model on the robot’s performance metrics. Results indicate that QPSO estimates inertia and mass center parameters with Mean Absolute Percentage Errors (MAPE) of 0.76% and 0.43%, outperforming PSO significantly and delivering smoother torque profiles and greater resilience to external disturbances. Full article

Cryogenic upgrading represents a promising route for the production of high-purity biomethane, aligning with current decarbonization goals and the increasing demand for renewable gases. This review provides a critical assessment of cryogenic technologies applied to biogas purification, focusing on process fundamentals, technological configurations, energy and separation performance, and their industrial integration potential. The analysis covers standalone cryogenic systems as well as hybrid configurations combining cryogenic separation with membrane or chemical pretreatment to enhance efficiency and reduce operating costs. A comparative evaluation of key performance indicators—including methane recovery, specific energy demand, product purity, and technology readiness level—is presented, along with a discussion of representative industrial applications. In addition, recent techno-economic studies are examined to contextualize cryogenic upgrading within the broader landscape of CO₂ separation technologies. Environmental trade-offs, investment thresholds, and sensitivity to gas prices and CO₂ taxation are also discussed. The review identifies existing technical and economic barriers, outlines research and innovation priorities, and highlights the relevance of process integration with natural gas networks. Overall, cryogenic upgrading is confirmed as a technically viable and environmentally competitive solution for biomethane production, particularly in contexts requiring liquefied biomethane or CO₂ recovery. Strategic deployment and regulatory support will be key to accelerating its industrial adoption. The objectives of this review have been met by consolidating the current state of knowledge and identifying specific gaps that warrant further investigation. Future work is expected to address these gaps through targeted experimental studies and technology demonstrations. Full article

Hydrogen energy is considered a crucial clean energy carrier for replacing fossil fuels in the future. Liquid hydrogen (LH₂), with its economic advantages and high purity, is central to the development of future hydrogen refueling stations (HRSs). However, leakage poses significant fire and explosion risks, challenging its safe industrial use. In this study, a numerical model of LH₂ leakage at an HRS in Chongqing was established using Computational Fluid Dynamics (CFD) software. The diffusion law of a flammable gas cloud (FGC) was examined under the synergistic effect of the leakage direction, rate, and wind speed of an LH₂ storage tank in an HRS. The phase transition of LH₂ presents dual risks of combustion and frostbite owing to the spatial overlap between low-temperature areas and FGCs. The findings revealed that the equivalent stoichiometric gas cloud volume (Q9) reached 685 m³ in the case of crosswind leakage, with the superimposed effect of reflected waves from the LH₂ transport vehicle resulting in a peak explosion overpressure of 0.61 bar. The low-temperature hazard area and the FGC (with a concentration of 30–75%) show significant spatial overlap. These research outcomes offer crucial theoretical underpinning for enhancing equipment layout optimization and safety protection strategies at HRSs. Full article

In cognitive radio networks (CRNs), primary users (PUs) have the highest priority in channel resource allocation. Secondary users (SUs) can generally only utilize temporarily unused channels of PUs, share channels with PUs, or cooperate with PUs to gain priority through the interweave, underlay, and overlay modes. Traditional optimization schemes for channel resource allocation often lead to structural wastage of channel resources, whereas approaches such as reinforcement learning—though effective—require high computational power and thus exhibit poor adaptability in industrial deployments. Moreover, existing works typically optimize a single performance metric with limited scenario scalability. To address these limitations, this paper proposes a CR network algorithm based on the hybrid users (HU) concept, which links the Interweave and Underlay modes through an adaptive threshold for mode switching. The algorithm employs the Hungarian method for SU channel allocation and applies a multi-level power adjustment strategy when PUs and SUs share the same channel to maximize channel resource utilization. Simulation results under various parameter settings show that the proposed algorithm improves the average signal to interference plus noise ratio (SINR) of SUs while ensuring PU service quality, significantly enhances network energy efficiency, and markedly improves Jain’s fairness among SUs in low-power scenarios. Full article

Climate change and air pollution are associated with a range of health outcomes, including cardiovascular and respiratory disease. Evaluation of the synergic effects of air pollution and increasing natural temperature on mortality is important for understanding their potential joint health effects. In this study, the modification effects of air temperature on the short-term association of ambient fine particulate matter (PM_2.5) and ozone (O₃) with non-accidental death (NAD) and cardiovascular disease (CVD) mortality were evaluated by using the generalized additive model (GAM) combined with the distributed lag nonlinear model (DLNM) in urban areas of Taiyuan, a representative of energy and heavy industrial cities in Northern China. The data on the daily cause-specific death numbers, air pollutants concentrations, and meteorological factors were collected from January 2013 to December 2019, and the temperature was divided into low (<25th percentile), medium (25–75th percentile), and high (>75th percentile) categories. Significant associations of PM_2.5 and O₃ with NAD and CVD mortality were observed in single-effect analysis. A statistically significant increase in the effect estimates of PM_2.5 and O₃ on NAD and CVD mortality was also observed on high-temperature days. But the associations of those were not statistically significant on medium- and low-temperature days. At the same temperature level, the effects of PM_2.5 and O₃ on the CVD mortality were larger than those on NAD (1.74% vs. 1.21%; 1.67% vs. 0.57%), and the elderly and males appeared to be more vulnerable to both higher temperatures and air pollution. The results suggest that the acute effect of PM_2.5 and O₃ on NAD and CVD mortality in urban Taiyuan was enhanced by increasing temperatures, particularly for the elderly and males. It highlights the importance of reducing PM_2.5 and O₃ exposure in urban areas to reduce the public health burden under the situation of global warming. Full article