Search Results (323)

This work focuses on the sustainable green synthesis of magnetic iron oxide nanoparticles (Fe₃O₄NPs) using bioreductants derived from orange peel extracts for application in the efficient oxygen evolution reactions (OER). The synthesized catalysts were characterized using X-ray diffraction analysis, field emission scanning electron microscopy (FESEM), energy dispersive X-ray analysis (EDS), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR), and UV–visible spectroscopy. The Fe₃O₄NPs exhibit a well-defined spherical morphology with a larger Brunauer–Emmett–Teller surface area and a significant electrochemically active surface area. The green synthesis using orange peel extracts leads to an excellent electrocatalytic activity of the apparent spherical Fe₃O₄NPs (diameter of 9.62 ± 0.07 nm), which is explored for OER in an alkaline medium (1.0 M KOH) using linear-sweep and cyclic voltammetry techniques. These nanoparticles achieved a benchmark current density of 10 mA cm⁻² at a low overpotential of 0.3 V versus RHE, along with notable durability and stability. The outstanding OER electrocatalytic activity is attributed to their unique morphology, which offers large surface area and an ideal porous structure that enhances the adsorption and activation of reactive species. Furthermore, structural defects within the nanoparticles facilitate efficient electron transfer and migration of these species, further accelerating the OER process. Full article

In Central Asian countries (CACs) Yes. we agree to remove Highlights part atmosphere pollution is increasing due to population growth, economic growth, agricultural development, energy consumption and climate change. The countries of the region developed climate change adaptation strategies—Nationally Determined Contributions (NDCs) under the UN Framework Convention on Climate Change (UNFCCC). At the same time, regional integration, which should be a necessary condition for achieving the Sustainable Development Goals (SDGs) in the solving of general environmental problems, is not involved. This article shows the importance of a comprehensive analysis of greenhouse gas (GHG) and non-greenhouse emissions into the atmosphere for the entire Central Asian region as a single ecosystem. The energy intensity of national economies structure was chosen as the main factor determining the level of pollution. The analysis shows that over the past 30 years, the main part of the commodity exports (73.6–81.4%) of Kazakhstan and Turkmenistan has been fossil natural resources. There is a strong economic dependence on coal and other types of fuel, which leads to atmospheric emissions. The analysis shows that limited financial resources, lack of effective systemic monitoring and control of air quality that meets modern international requirements and standards, leads to absence of tangible changes in practice yet. Over 30 years in CACs, the share of CO₂ emissions associated with fuel combustion has not decreased and amounts to 78%. The key mechanisms for reducing atmospheric emissions are significantly increase investments in the transformation of the economies in the context of regional development, interstate cooperation, the introduction of environmental norms, standards harmonized with world ones, green technologies based on alternative energy, sustainable transport and logistics infrastructure. Full article

China has committed to carbon neutrality by 2060 by necessitating a comprehensive transformation of its building sector, particularly in rapidly urbanizing areas such as the Greater Bay Area (GBA), where subtropical climates, urban heat island effects, and extreme weather events present distinct challenges for achieving carbon reduction objectives through green building practices. The goal of this study is to establish an analysis method for green building success in the GBA’s subtropical environment, paying attention to the challenging goals of reducing carbon and making buildings more climate-resilient. Research techniques involved performing building energy simulations with EnergyPlus and DesignBuilder, applying LightGBM models for machine learning, using case studies from 32 buildings in Shenzhen, Hong Kong and Guangzhou and carrying out an evaluation of the policy using a PEI. Energy usage in green buildings was 45.3% less than in conventional structures, with Energy Use Intensity ranging from 65.1 to 72.4 kWh/m²/year, while traditional buildings used between 118.5 and 124.2 kWh/m²/year. Also, the carbon footprint during the life cycle of buildings was decreased by 38.4% and they became more resilient to typhoons, giving residents 72.4 h of power during storms, while conventional buildings gave only 8.3 h. HVAC system efficiency was the leading factor, accounting for 24.3% of the difference in energy performance. A detailed approach is developed for optimizing subtropical green buildings, based on unique design features and helpful policy ideas to promote carbon neutrality in swiftly growing metropolitan areas around the world. Full article

Achieving carbon reduction is essential in advancing China’s dual carbon goals and promoting a green transformation in the transportation sector. Changes in energy structure and intensity constitute key drivers for sustainable and low-carbon development in this field. To explore the spatial spillover effects of the energy structure and intensity on the green transition of transportation, this study constructs a panel dataset of 30 Chinese provinces from 2007 to 2020. It employs a super-efficiency SBM model, non-parametric kernel density estimation, and a spatial Markov chain to verify and quantify the spatial spillover effects of green total factor productivity (GTFP) in the transportation sector. A dynamic spatial Durbin model is then used for empirical estimation. The main findings are as follows: (1) GTFP in China’s transportation sector exhibits a distinct spatial pattern of “high in the east, low in the west”, with an evident path dependence and structural divergence in its evolution; (2) GTFP displays spatial clustering characteristics, with “high–high” and “low–low” agglomeration patterns, and the spatial Markov chain confirms that the GTFP levels of neighboring regions significantly influence local transitions; (3) the optimization of the energy structure significantly promotes both local and neighboring GTFP in the short term, although the effect weakens over the long term; (4) a reduction in energy intensity also exerts a significant positive effect on GTFP, but with clear regional heterogeneity: the effects are more pronounced in the eastern and central regions, whereas the western and northeastern regions face risks of negative spillovers. Drawing on the empirical findings, several policy recommendations are proposed, including implementing regionally differentiated strategies for energy structure adjustment, enhancing transportation’s energy efficiency, strengthening cross-regional policy coordination, and establishing green development incentive mechanisms, with the aim of supporting the green and low-carbon transformation of the transportation sector both theoretically and practically. Full article

With the ongoing transformation of the energy structure and the advancement of smart grid development, green and sustainable development of substations has become an inevitable trend. As the core driving force of substation transformation, novel technologies remain at the pilot application stage, and their performance evaluations are yet to be clarified. In view of this, this paper proposes a comprehensive evaluation framework for the application effectiveness of novel technologies in green construction for substations. Firstly, based on the feature for the whole life cycle of the technologies, an evaluation index system is established covering multiple dimensions and stages, including resource conservation, technical performance enhancement, and economic benefits. Secondly, on the basis of AHP group decision and EWM combination weights, a variable-weight model is constructed by combining projection gray target evaluation to enable significant differentiation in cross-technology comparative analysis. Finally, a case study is conducted on pilot applications of multiple novel technologies in substations within a specific region, and the results indicate that novel technologies which demonstrate better sustainable development effects throughout the entire life cycle have a broader prospect for promotion. Full article

The synthesis of heterocyclic compounds has gained significant attention in organic chemistry due to their diverse pharmacological properties. However, traditional synthetic approaches often involve hazardous chemicals, high energy consumption, and tedious workup procedures, leading to environmental concerns and low yields. In response, green chemistry strategies have emerged, emphasizing safer and more sustainable alternatives. Among these, magnetic nanoparticle (MNP)-based catalysts have shown remarkable promise in facilitating one-pot multicomponent reactions (MCRs), offering enhanced catalytic efficiency, ease of recovery, and reusability. This article provides a comprehensive overview of multicomponent reactions (MCRs) for the construction of a wide range of heterocyclic scaffolds—including chromenes, pyrazoles, phenazines, triazoles, tetrazoles, xanthenes, furans, indoles, imidazoles, pyridines, pyrimidines, oxazoles, and acridine derivatives—catalyzed by magnetic nanoparticles under sustainable and environmentally benign conditions. This review highlights recent advances (2018–2024) in the development and application of modified magnetic nanoparticles for green multicomponent synthesis. Emphasis is placed on their structural features, catalytic roles, and benefits in eco-friendly organic transformations. Full article

Against the background of global climate change and increasing ecological vulnerability, enhancing ecosystem resilience has become a core task for coping with environmental shocks and achieving sustainable development. The urban energy structure plays a critical role in influencing the green development of the economy and the enhancement of environmental resilience. Existing studies have revealed the role of energy structure transformation in the identification of macroeconomic performance and environmental outcomes, but have neglected its impact on ecosystem resilience. This paper exploits the implementation of the New Energy Demonstration City pilot policy as a quasi-natural experiment. Using panel data of Chinese prefecture-level cities from 2010 to 2022, it constructs a multidimensional evaluation system of urban ecosystem resilience and employs a difference-in-differences (DID) model to empirically examine the impact of energy structure transformation on urban ecosystem resilience. It is found that energy structure transition significantly enhances urban ecosystem resilience, and this conclusion is verified through a series of robustness tests. Mechanism analysis shows that energy structure transformation comprehensively enhances urban ecosystem resilience through strengthening institutional regulation, optimizing resource allocation, promoting energy substitution, and enhancing public awareness. Heterogeneity analysis indicates that the strengthening effect of energy structure transition on urban ecosystem resilience is inclusive, and that this positive effect is greater in cities characterized by lower resource endowment and weaker governance capacity. This paper reveals the intrinsic mechanism of urban energy transition for ecological resilience enhancement, and provides an energy transition path for building more resilient urban ecosystems. Full article

By integrating statistical modeling and data analysis techniques, we systematically assess the carbon emission performance of the ceramic industry and propose targeted emission reduction pathways. Firstly, the entropy weight TOPSIS model is employed to quantitatively evaluate the carbon emission performance of the three major Chinese ceramic production areas: Foshan, Jingdezhen, and Zibo. Through data-driven quantitative analysis, it is disclosed that the carbon emission intensity in Foshan is significantly higher than that in the other two regions (with a relative closeness degree of $0.5185$). The key issues identified include high energy consumption in the production process, a high reliance on raw coal, and insufficient investment in environmental protection. Furthermore, through the XGBoost-SHAP combined modeling, the key drivers of carbon emissions are precisely identified from multi-dimensional data. It is found that the elasticity coefficient of raw coal in the carbon emission proportion is as high as 25.84%, while the potential for substitution with natural gas is remarkable. Based on statistical prediction techniques, a carbon emission trend model under the scenario of energy structure optimization is constructed, predicting that after reaching a peak in 2017, Foshan’s carbon emissions will continue to decline, with the proportion of raw coal dropping to 48% and that of natural gas rising to 10%, thereby verifying the feasibility of the green transformation. Additionally, a multi-agent carbon trading simulation model is constructed to explore the emission reduction behaviors of enterprises under different carbon price scenarios. This study not only achieves precise quantitative analysis of carbon emissions through statistical method innovation but also verifies the feasible paths of low-carbon transformation through data modeling. Full article

This paper proposes the Open Competency Optimization (OCO) approach, based on adaptive combinatorial operators, to solve the Dynamic Green Traveling Salesman Problem (DG-TSP), which extends the classical TSP by incorporating dynamic travel conditions, realistic road gradients, and energy consumption considerations. The objective is to minimize fuel consumption and emissions by reducing the total tour length under varying conditions. Unlike conventional metaheuristics based on real-coded representations, our method directly operates on combinatorial structures, ensuring efficient adaptation without costly transformations. Embedded within a dynamic metaheuristic framework, our operators continuously refine the routing decisions in response to environmental and demand changes. Experimental assessments conducted in practical contexts reveal that our algorithm attains a tour length of 21,059, which is indicative of a 36.16% reduction in fuel consumption relative to Ant Colony Optimization (ACO) (32,994), a 4.06% decrease when compared to Grey Wolf Optimizer (GWO) (21,949), a 2.95% reduction in relation to Particle Swarm Optimization (PSO) (21,701), and a 0.90% decline when juxtaposed with Genetic Algorithm (GA) (21,251). In terms of overall offline performance, our approach achieves the best score (21,290.9), significantly outperforming ACO (36,957.6), GWO (122,881.04), GA (59,296.5), and PSO (36,744.29), confirming both solution quality and stability over time. These findings underscore the resilience and scalability of the proposed approach for sustainable logistics, presenting a pragmatic resolution to enhance transportation operations within dynamic and ecologically sensitive environments. Full article

In recent years, growing concerns over environmental degradation and deepening awareness of the necessity of sustainable development have propelled green and low-carbon energy transition into a focal issue for both academia and policymakers. By decomposing energy transition into the transformation of energy structure and the upgrading of energy efficiency, this study investigates the impact and mechanisms of green finance on energy transition across 30 provinces (municipalities and autonomous regions) in China, with the exception of Tibet. In addition, the impact of climate change is incorporated into the analytical framework. Empirical results demonstrate that green finance development significantly accelerates energy transition, a conclusion robust to rigorous validation. Analysis of the mechanism shows that green finance promotes energy transition through the facilitation of technological innovation and the upgrade of industrial structures. Moreover, empirical evidence reveals that climate change undermines the promotional influence of sustainable finance on energy system transformation. The magnitude of this suppression varies nonlinearly across provincial jurisdictions with differing energy transition progress. Regional heterogeneity analyses further uncover marked discrepancies in climate–finance interactions, demonstrating amplified effects in coastal economic hubs, underdeveloped western provinces, and regions with mature eco-financial markets. According to these findings, actionable policy suggestions are put forward to strengthen green finance and accelerate energy transition. Full article

This mini-review emphasizes the potential of biomass-derived materials as sustainable components for next-generation electrochemical energy storage systems. Biomass obtained from abundant and renewable natural resources can be transformed into carbonaceous materials. These materials typically possess hierarchical porosities, adjustable surface functionalities, and inherent heteroatom doping. These physical and chemical characteristics provide the structural and chemical flexibility needed for various electrochemical applications. Additionally, biomass-derived materials offer a cost-effective and eco-friendly alternative to traditional components, promoting green chemistry and circular resource utilization. This review provides a systematic overview of synthesis methods, structural design strategies, and material engineering approaches for their use in lithium-ion batteries (LIBs), lithium–sulfur batteries (LSBs), and supercapacitors (SCs). It also highlights key challenges in these systems, such as the severe volume expansion of anode materials in LIBs and the shuttle effect in LSBs and discusses how biomass-derived carbon can help address these issues. Full article

The green transformation of traditional energy structures and the development of the new energy industry are crucial drivers of sustainable development in the country. The ASEAN Plan of Action for Energy Cooperation (2016–2025; APAEC [2016–2025]), established in 2016, has significantly promoted the growth of the new energy sector and enhanced energy structures across Association of Southeast Asian Nations (ASEAN). This initiative has also inspired these countries to develop corresponding industrial policies aimed at supporting the new energy vehicle (NEV) industry, resulting in significant growth in this sector within the ASEAN region. This paper analyzes the factors influencing the development of the NEV industry in the context of ASEAN’s new energy policies, drawing empirical insights from data collected across six ASEAN countries from 2013 to 2024. Following the implementation of the APAEC (2016–2025), it was observed that ASEAN countries reached a consensus on energy development and cooperation, collaboratively advancing the NEV industry through regional policies. Furthermore, factors such as national governance, financial development, education levels, and the size of the automotive market positively contribute to the growth of the NEV industry in ASEAN. Conversely, high energy consumption can hinder its progress. Additionally, further research indicates that the APAEC (2016–2025) has exerted a more pronounced impact on countries with robust automotive industry foundations or those prioritizing relevant policies. The findings of this paper offer valuable insights for ASEAN countries in the formulating policies for the NEV industry, optimizing energy structures, and achieving low-carbon energy transition and sustainable development. Full article

Rail transit as a high-energy consumption field urgently requires the adoption of clean energy innovations to reduce energy consumption and accelerate the transition to new energy applications. As an energy-saving fluid machinery, the ejector exhibits significant application potential and academic value within this field. This paper reviewed the recent advances, technical challenges, research hotspots, and future development directions of ejector applications in rail transit, aiming to address gaps in existing reviews. (1) In waste heat recovery, exhaust heat is utilized for propulsion in vehicle ejector refrigeration air conditioning systems, resulting in energy consumption being reduced by 12~17%. (2) In vehicle pneumatic pressure reduction systems, the throttle valve is replaced with an ejector, leading to an output power increase of more than 13% and providing support for zero-emission new energy vehicle applications. (3) In hydrogen supply systems, hydrogen recirculation efficiency exceeding 68.5% is achieved in fuel cells using multi-nozzle ejector technology. (4) Ejector-based active flow control enables precise ± 20 N dynamic pantograph lift adjustment at 300 km/h. However, current research still faces challenges including the tendency toward subcritical mode in fixed geometry ejectors under variable operating conditions, scarcity of application data for global warming potential refrigerants, insufficient stability of hydrogen recycling under wide power output ranges, and thermodynamic irreversibility causing turbulence loss. To address these issues, future efforts should focus on developing dynamic intelligent control technology based on machine learning, designing adjustable nozzles and other structural innovations, optimizing multi-system efficiency through hybrid architectures, and investigating global warming potential refrigerants. These strategies will facilitate the evolution of ejector technology toward greater intelligence and efficiency, thereby supporting the green transformation and energy conservation objectives of rail transit. Full article

China’s national strategies emphasize both achieving carbon peaking and neutrality (“dual carbon” objectives) and fostering high-quality economic development. This dual focus highlights the critical importance of the Green and Low-Carbon Transition (GLCT) of the economy and the development of New Quality Productive Forces (NQPF). Firms are central actors in this transformation, prompting the core research question: How does corporate engagement in GLCT contribute to the formation of NQPF? We investigate this relationship using panel data comprising 33,768 firm-year observations for A-share listed companies across diverse industries in China from 2012 to 2022. Corporate GLCT is measured via textual analysis of annual reports, while an NQPF index, incorporating both tangible and intangible dimensions, is constructed using the entropy method. Our empirical analysis relies primarily on fixed-effects regressions, supplemented by various robustness checks and alternative econometric specifications. The results demonstrate a significantly positive relationship: corporate GLCT robustly promotes the development of NQPF, with dynamic lag structures suggesting delayed productivity realization. Mechanism analysis reveals that this effect operates through three primary channels: improved access to financing, stimulated collaborative innovation and enhanced resource-allocation efficiency. Heterogeneity analysis indicates that the positive impact of GLCT on NQPF is more pronounced for state-owned enterprises (SOEs), firms operating in high-emission sectors, those in energy-efficient or environmentally friendly industries, technology-intensive sectors, non-heavily polluting industries and companies situated in China’s eastern regions. Overall, our findings suggest that corporate GLCT enhances NQPF by improving resource-utilization efficiency and fostering innovation, with these effects amplified by specific regional advantages and firm characteristics. This study offers implications for corporate strategy, highlighting how aligning GLCT initiatives with core business objectives can drive NQPF, and provides evidence relevant for policymakers aiming to optimize environmental governance and foster sustainable economic pathways. Full article

The green synthesis of zinc oxide nanoparticles (ZnO NPs) using Artemisia absinthium L. extract has gained considerable attention due to its eco-friendly approach and potential applications in food science. This study investigates the synthesis and characterization of Artemisia-mediated ZnO NPs, focusing on their physicochemical properties. The nanoparticles were characterized using ultraviolet–visible spectroscopy (UV–Vis), Fourier transform infrared spectroscopy (FT-IR), field emission scanning electron microscopy (FE-SEM), and energy dispersive X-ray spectroscopy (EDX). Successful synthesis was achieved through a co-precipitation method, resulting in an average particle size of 36.6 nm. The presence of polyphenols and flavonoids in A. absinthium L. extract acted as both a reducing agent and stabilizer for the nanoparticles. The physicochemical characterization revealed strong absorption peaks indicative of ZnO, confirming successful nanoparticle formation. In addition to the structural findings, this study presents novel insights by demonstrating that Artemisia-mediated ZnO NPs possess significantly enhanced antimicrobial activity compared to both pure ZnO NPs and the plant extract alone. The biosynthesized nanoparticles exhibited notably lower minimum inhibitory concentration (MIC) and minimum bactericidal/fungicidal concentration (MBC/MFC) values against Staphylococcus aureus, Escherichia coli, and Candida albicans, suggesting a strong synergistic effect between ZnO and the phytochemicals of A. absinthium L. Thus, the study confirms and quantifies the superior antibacterial potential of Artemisia-derived ZnO NPs, offering promising implications for food, biomedical and pharmaceutical applications. Full article