Search Results (510)

The transportation sector, as a major source of carbon emissions, plays a crucial role in the realization of dual carbon goals worldwide. In this study, an improved least absolute shrinkage and selection operator (LASSO) is used to identify six key factors affecting transportation carbon emissions (TCEs) in China. Aiming at the spatio-temporal characteristics of transportation carbon emissions, a CNN-BiLSTM neural network model is constructed for the first time for prediction, and an improved whale optimization algorithm (EWOA) is introduced for hyperparameter optimization, finding that the prediction model combining spatio-temporal characteristics has a more significant prediction accuracy, and scenario forecasting was carried out using the prediction model. Research indicates that over the past three decades, TCEs have demonstrated a rapid growth trend. Under the baseline, green, low-carbon, and high-carbon scenarios, peak carbon emissions are expected in 2035, 2031, 2030, and 2040. The adoption of a low-carbon scenario represents the most advantageous pathway for the sustainable progression of China’s transportation sector. Consequently, it is imperative for China to accelerate the formulation and implementation of low-carbon policies, promote the application of clean energy and facilitate the green transformation of the transportation sector. These efforts will contribute to the early realization of dual-carbon goals with a positive impact on global sustainable development. Full article

Hydrogen is widely recognized as a key enabler of the clean energy transition, but the lack of safe, efficient, and scalable storage technologies continues to hinder its broad deployment. Conventional hydrogen storage approaches, such as compressed hydrogen storage, cryo-compressed hydrogen storage, and liquid hydrogen storage, face limitations, including high energy consumption, elevated cost, weight, and safety concerns. In contrast, solid-state hydrogen storage using carbon-based adsorbents has gained growing attention due to their chemical tunability, low cost, and potential for modular integration into energy systems. This review provides a comprehensive evaluation of hydrogen storage using carbon-based materials, covering fundamental adsorption mechanisms, classical materials, emerging architectures, and recent advances in computationally AI-guided material design. We first discuss the physicochemical principles driving hydrogen physisorption, chemisorption, Kubas interaction, and spillover effects on carbon surfaces. Classical adsorbents, such as activated carbon, carbon nanotubes, graphene, carbon dots, and biochar, are evaluated in terms of pore structure, dopant effects, and uptake capacity. The review then highlights recent progress in advanced carbon architectures, such as MXenes, three-dimensional architectures, and 3D-printed carbon platforms, with emphasis on their gravimetric and volumetric performance under practical conditions. Importantly, this review introduces a forward-looking perspective on the application of artificial intelligence and machine learning tools for data-driven sorbent design. These methods enable high-throughput screening of materials, prediction of performance metrics, and identification of structure–property relationships. By combining experimental insights with computational advances, carbon-based hydrogen storage platforms are expected to play a pivotal role in the next generation of energy storage systems. The paper concludes with a discussion on remaining challenges, utilization scenarios, and the need for interdisciplinary efforts to realize practical applications. 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

Hydrogen is being increasingly integrated into the international trade system as a clean and flexible energy carrier, motivated by the global energy transition and carbon neutrality objectives. The rapid expansion of the global hydrogen trade network has simultaneously exposed several sustainability challenges, including a centralized structure, overdependence on key countries, and limited resilience to external disruptions. Based on this, we develop a risk propagation model that incorporates the absorption capacity of nodes to simulate the propagation of supply shortage risks within the global hydrogen trade network. Furthermore, we propose a composite sustainability index constructed from structural, economic, and environmental resilience indicators, enabling a systematic assessment of the network’s sustainable development capacity under external shock scenarios. Findings indicate the following: (1) The global hydrogen trade network is undergoing a structural shift from a Western Europe-dominated unipolar configuration to a more polycentric pattern. Countries such as China and Singapore are emerging as key hubs linking Eurasian regions, with trade relationships among nations becoming increasingly dense and diversified. (2) Although supply shortage shocks trigger structural disturbances, economic losses, and risks of carbon rebound, their impacts are largely concentrated in a limited number of hub countries, with relatively limited disruption to the overall sustainability of the system. (3) Countries exhibit significant heterogeneity in structural, economic, and environmental resilience. Risk propagation demonstrates an uneven pattern characterized by hub-induced disruptions, chain-like transmission, and localized clustering. Accordingly, policy recommendations are proposed, including the establishment of a polycentric coordination mechanism, the enhancement of regional emergency coordination mechanisms, and the advancement of differentiated capacity-building efforts. Full article

This study investigated the potential of high-voltage electrical discharge (HVED), as a green, non-thermal extraction technology, for recovering polyphenols from winter savory (Satureja montana L.). Key process parameters, including frequency (40, 70, 100 Hz) and extraction time (1, 5, 15, 30, 45 min), were optimized, using water as a solvent and maintaining a constant solid-to-liquid ratio of 1:100 g/mL. The extracts were characterized for total polyphenol content (TPC), total flavonoid content (TFC), and antioxidant activity (DPPH, ABTS, FRAP), while individual phenolics were quantified via HPLC-DAD. Multivariate chemometric analyses, including Pearson correlation, heatmap clustering, and principal component analysis (PCA), were employed to reveal relationships between extraction conditions, polyphenolic profiles, and antioxidant activities. The results showed strong correlations between TPC, TFC, and antioxidant activity, with compounds such as quercetin-3-D-galactoside, procyanidin A2, and rutin identified as key contributors. Among the tested conditions, extraction at 70 Hz for 45 min provided the highest polyphenol yield and bioactivity. The application of HVED demonstrated its potential as an efficient and environmentally friendly technique for obtaining phenolic-rich extracts. In addition, the use of chemometric tools provided useful insights for optimizing extraction conditions and understanding the contributions of specific compounds to bioactivity. These results support future applications in clean-label product development and contribute to broader efforts in sustainable ingredient production for the food, cosmetic, and nutraceutical sectors. Full article

The impact of black carbon (BC) emissions on climate change, human health, and the environment is well-documented in the scientific literature. Although BC still remains largely unregulated at the international level, efforts have been made to reduce emissions of BC and Particulate Matter (PM_2.5), particularly in sectors such as energy production, industry, and road transport. In contrast, the maritime shipping industry has made limited progress in reducing BC emissions from ships, mainly due to the absence of stringent BC emission regulations. While the International Maritime Organization (IMO) has established emission limits for pollutants such as SO_x, NO_x, and VOCs under MARPOL Annex VI, as of today, BC emissions from ships are still unregulated at the international level. Whereas it was anticipated that PM_2.5 and BC emissions would be reduced with the adoption of the SO_x regulations, especially within the sulfur emission control areas (SECA), this study reveals that BC emissions are only partially affected by the current MARPOL Annex VI regulations. Based on 886 real-world black carbon (BC) emission measurements from ships operating in the southern North Sea, the study demonstrates that SECA-compliant fuels do contribute to a notable decrease in BC emissions. However, it is important to note that the average BC emission factors (EFs) within the SECA remain comparable in magnitude to those reported for non-compliant fuels in earlier studies. Moreover, ships using exhaust gas cleaning systems (EGCSs) as a SECA-compliant measure were found to emit significantly higher levels of BC, raising concerns about the environmental sustainability of EGCSs as an emissions mitigation strategy. Full article

The link between ESG and financial performance is still under debate. In this study, we explore which aspects of ESG specifically drive market valuations through both systematic and idiosyncratic risk channels. We analyze the impact of the three core ESG pillars, 10 subcategories, and associated controversies on market valuations in the energy sector. This analysis reveals that the environmental factor has a stronger impact (regression coefficient = 0.05) than the governance factor (regression coefficient = 0.003), emphasizing the need to prioritize environmental performance in ESG strategies. The positive coefficients for environmental resource use (0.005) and innovation (0.008) indicate that investments in efficiency and clean technologies are beneficial, while the negative coefficient for emissions (−0.004) underscores the risks associated with poor emissions management. These findings suggest that environmental risks currently outweigh governance risks for the energy sector, reinforcing the importance of aligning governance practices with environmental goals. To maximize ESG effectiveness, energy firms should focus on measurable improvements in resource efficiency, innovation, and emissions reduction and transparently communicate this progress to stakeholders. The evidence suggests that energy firms approach the ESG landscape differently, with sustainability leaders benefiting from higher valuations, particularly when ESG efforts are aligned with core competencies. However, many energy companies under-invest in value-creating environmental initiatives, focusing instead on emission management, which erodes value. While they excel in emission control, they lag in innovation, missing opportunities to enhance valuations. This underscores the potential for ESG risk analysis to improve portfolio performance, as sustainability can both create value and mitigate risks by factoring into valuation equations as both risks and opportunities. This study uniquely contributes to the ESG–financial performance literature by disentangling the specific ESG dimensions that drive market valuations in the energy sector, revealing that value is created not through emission control but through strategic alignment with eco-innovation, governance, and social responsibility. Full article

Polymer membranes often face challenges of oil fouling and rapid water flux decline during the separation of oil-in-water emulsions, making them a focal point of ongoing research and development efforts. Coating PVDF membranes with a hydrogel layer equips the developed membranes with robust potential to mitigate oil fouling. However, developing a controllable thickness of a stable hydrogel layer to prevent the blocking of membrane pores remains a critical issue. In this work, atmospheric pressure low-temperature plasma was used to prepare the surface of a PVDF membrane to improve its wettability and adhesion properties for coating with a thin hydrophilic film of an AM-NaA copolymer hydrogel. The AM-NaA/PVDF membrane exhibited superhydrophilic and underwater superoleophobic properties, along with exceptional anti-crude oil-fouling characteristics and a self-cleaning function. The AM-NaA/PVDF membrane achieved high separation efficiency, exceeding 99% for various oil-in-water emulsions, with residual oil content in the permeate of less than 10 mg/L after a single-step separation. Additionally, it showed a high-water flux of 5874 L/m²·h for crude oil-in-water emulsions. The AM-NaA/PVDF membrane showed good stability and easy cleaning by water washing over multiple crude oil-in-water emulsion separation and regeneration cycles. Adding CaCl₂ destabilized emulsions by promoting oil droplet coalescence, further boosting flux. This strategy provides a practical pathway for the development of highly reusable and oil-fouling-resistant membranes for the efficient separation of emulsified oily water. Full article

This study integrates socio-demographic factors and local sustainability indicators to assess their implications for public health and social vulnerability in the Henequén neighborhood of Cartagena, Colombia. This historically marginalized community, primarily composed of women and displaced families, faces chronic exposure to environmental contaminants due to its past as a municipal landfill. Poor housing conditions, overcrowding, and inadequate access to water and sanitation services exacerbate health risks. Additionally, low educational attainment and limited economic opportunities contribute to cycles of poverty and illicit activities, disproportionately affecting children’s development. Using a cross-sectional and correlational approach, the study identifies key variables, such as housing conditions, access to basic services, and marital status, that shape social vulnerability. The findings are analyzed in the context of the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being), SDG 6 (Clean Water and Sanitation), and SDG 11 (Sustainable Cities and Communities). The study highlights critical gaps in sustainability efforts and provides a framework for assessing local progress toward achieving these global development objectives. Full article

Hand hygiene reduces healthcare-associated infections. The World Health Organization (WHO) recommends the multimodal hand hygiene strategy to improve hand hygiene. To compare hand hygiene knowledge and compliance of healthcare practitioners (HCPs) before and after the implementation of the WHO multimodal strategy, a before-and-after cross-sectional study was conducted in two Tunisian University Hospitals (2019–2023). Hand hygiene knowledge and compliance were assessed using the WHO questionnaire and observation tool. In 2019, 42 of 246 HCPs (17%) correctly answered ≥80% of 25 questions on hand hygiene knowledge. By 2023, this increased to 47 HCPs (19%). Knowledge on hand hygiene significantly improved for 10 out of 25 questions (12–38% increases) but declined for eight questions (5–40% decreases). Seven questions showed no significant changes in knowledge. Overall hand hygiene compliance increased from 21% in 2019 to 40% in 2023 (p < 0.001). Improvements were observed across the hospital departments (p < 0.001) and staff categories (p < 0.001). In 2023, the lowest hand hygiene compliance was for/before touching a patient (29%), and before clean/aseptic procedures (37%). Hand hygiene compliance was improved, but progress fell short of the WHO’s desired 80% target. Sustained efforts and complementary interventions are needed to accelerate progress and achieve the desired outcomes. Full article

The development of ultrahigh-concentration photovoltaic (UHCPV) systems plays a pivotal role in advancing sustainable solar energy technologies. As the demand for clean energy grows, the need to align concentrated photovoltaic (CPV) system design with high-efficiency solar cell production becomes critical for maximizing energy yield while minimizing resource use. Despite some experimental efforts in UHCPV development, there remains a gap in integrating Fresnel lens-based systems with the comprehensive thermal modeling of key components in improving system sustainability and performance. To bridge this gap and promote more energy-efficient designs, a detailed numerical model was established to evaluate both the thermal and optical performance of a UHCPV system. This model contributes to the sustainable design process by enabling informed decisions on system efficiency, thermal management, and material optimization before physical prototyping. Through COMSOL Multiphysics simulations, the system was assessed under direct normal irradiance (DNI) ranging from 400 to 1000 W/m². Optical simulations indicated a high theoretical optical efficiency of ~93% and a concentration ratio of 1361 suns, underscoring the system’s potential to deliver high solar energy conversion with minimal land and material footprint. Moreover, the integration of thermal and optical modeling ensures a holistic understanding of system behavior under varying ambient temperatures (20–50 °C) and convective cooling conditions (heat transfer coefficients between 4 and 22 W/m².K). The results showed that critical optical components remain within safe temperature thresholds (<54 °C), while the receiver stage operates between 78.5 °C and 157.4 °C. These findings highlight the necessity of an effective cooling mechanism—not only to preserve system longevity and safety but also to maintain high conversion efficiency, thereby supporting the broader goals of sustainable and reliable solar energy generation. Full article

With the advent of the big data era in ocean remote sensing and fisheries, there is a growing demand for finer temporal scales to predict spatial distribution of the jumbo flying squid (Dosidicus gigas). This can help reduce fuel costs and provide higher quality and faster decision-making. Therefore, this study employed a deep neural network (DNN) model, using sea surface temperature, sea surface height, sea surface salinity, and photosynthetically active radiation as input factors, with catch per unit effort as the output factor. We construct five cases with temporal scales of 3, 6, 10, 15, and 30 days using data spanning 10 years (2012–2021). Additionally, the performance of DNN was compared with those of traditional methods such as generalized additive model (GAM), extreme gradient boosting (XGBoost), and artificial neural network (ANN). The results demonstrated that the DNN model had the best performance. As the temporal scale decreased, the mean squared error and the mean absolute error increased, whereas the area under the precision−recall curve decreased, indicating a decline in model performance. The interpretability analysis indicated that spatial and temporal factors significantly contributed to the model, with longitude exhibiting the highest contribution. To improve the accuracy of finer temporal scales, future research should focus on reducing noise in the data and address the presence-only nature of fishery data, particularly by cleaning the unsampled portions. Full article

Motivated by the growth of global energy demand and the goal of carbon neutrality, lead-cooled fast reactors, which are core reactor types of fourth-generation nuclear energy systems, have become a global research hotspot due to their advantages of high safety, nuclear fuel breeding capability, and economic efficiency. However, its engineering implementation faces key challenges, such as material compatibility, closed fuel cycles, and irradiation performance of structures. This paper comprehensively reviews the latest progress in the core design of lead-cooled fast reactors in terms of the innovation of nuclear fuel, optimization of coolant, material adaptability, and design of assemblies and core structures. The research findings indicate remarkable innovation trends in the field of lead-cooled fast reactor core design, including optimizing the utilization efficiency of nuclear fuel based on the nitride fuel system and the traveling wave burnup theory, effectively suppressing the corrosion effect of liquid metal through surface modification technology and the development of ceramic matrix composites; replacing the lead-bismuth eutectic system with pure lead coolant to enhance economic efficiency and safety; and significantly enhancing the neutron economy and system integration degree by combining the collaborative design strategy of the open-type assembly structure and control drums. In the future, efforts should be made to overcome the radiation resistance of materials and liquid metal corrosion technology, develop closed fuel cycle systems, and accelerate the commercialization process through international standardization cooperation to provide sustainable clean energy solutions for basic load power supply, high-temperature hydrogen production, ship propulsion, and other fields. Full article

The colour degradation of murals presents a significant challenge in the conservation of architectural heritage. Previous research has often concentrated on localized pigment changes while paying insufficient attention to the interaction between colour variation and indoor environmental conditions. Although non-destructive analytical techniques are widely used in heritage studies, their integrated application in combination with colourimetry has been limited, particularly in the context of Tibetan Buddhist murals in highland continental climates. This study investigates the murals of Liuli Hall in Meidai Lamasery, Inner Mongolia, as a representative case. We employed a comprehensive methodology that combines non-destructive analytical tools, gas chromatography–mass spectrometry, and quantitative colour analysis to examine pigment composition, binding material, and surface deterioration. Through joint analysis using the CIE Lab and CIE LCh colour space systems, we quantified mural colour changes and explored their correlation with material degradation and environmental exposure. The pigments identified include cinnabar, atacamite, azurite, and chalk, with animal glue and drying oils as binding materials. Colourimetric results revealed pronounced yellowing on the east and west walls, primarily caused by the ageing of organic binders. In contrast, a notable reduction in brightness on the south wall was attributed to dust accumulation. These findings support tailored conservation measures such as regular surface cleaning for the south wall and antioxidant stabilization treatments for the east and west walls. Initial cleaning efforts proved effective. The integrated approach adopted in this study provides a replicable model for mural diagnostics and conservation under complex environmental conditions. Full article

With the global emphasis on sustainable growth and development, the depletion of natural energy reserves due to reliance on fossil fuels and non-renewable sources remains a critical concern. Despite strides in transitioning to electrical mobility, rural and agricultural communities depend heavily on liquefied petroleum gas and firewood for cooking, lacking viable, sustainable alternatives. This study focuses on community-led efforts to advance biogas adoption, providing an eco-friendly and reliable energy alternative for rural and farming households. By designing and developing balloon-type anaerobic biodigesters, this initiative provides a robust, cost-effective, and scalable method to convert farm waste into biogas for household cooking. This approach reduces reliance on traditional fuels, mitigating deforestation and improving air quality, and generates organic biofertilizer as a byproduct, enhancing agricultural productivity through organic farming. The study focuses on optimizing critical parameters, including the input feed rate, gas production patterns, holding time, biodigester health, gas quality, and liquid manure yield. Statistical tools, such as descriptive analysis, regression analysis, and ANOVA, were employed to validate and predict biogas output data based on experimental and industrial-scale data. Artificial neural networks (ANNs) were also utilized to model and predict outputs, inspired by the information processing mechanisms of biological neural systems. A comprehensive database was developed from experimental and literary data to enhance model accuracy. The results demonstrate significant improvements in cooking practices, health outcomes, economic stability, and solid waste management among beneficiaries. The integration of statistical analysis and ANN modeling validated the biodigester system’s effectiveness and scalability. This research highlights the potential to harness renewable energy to address socio-economic challenges in rural areas, paving the way for a sustainable, equitable future by fostering environmentally conscious practices, clean energy access, and enhanced agricultural productivity. Full article