Search Results (98,596)

Clay-based composite materials offer a low-carbon pathway for improving the environmental performance of the construction sector while maintaining relevance for architectural and heritage applications. A structured qualitative literature review was conducted, supported by thematic classification and exploratory bibliometric mapping (VOSviewer), based on peer-reviewed studies published between 2015 and 2025 relevant to the topic of clay minerals, stabilization, fibers, polymers, alkali activation, properties, performance, and applicability in architecture. According to the results obtained from the synthesized literature, it is seen that clay-based composites achieve performance improvement through complementary mechanisms: fiber reinforcement improves ductility, crack behavior, and energy absorption, polymer modification helps improve cohesion and water resistance and alkali activation transforms calcined aluminosilicate precursors into high-strength binding systems. The synthesis identifies three dominant performance mechanisms governing clay-based composites. Selected alkali-activated clay composite materials are reported to exhibit compression strengths higher than 60 MPa, and certain optimized systems may be able to provide lower thermal conductivity and lower levels of carbon emission in comparison with ordinary cement-based materials. The contribution of this paper lies in the synthesis of these material modification techniques and resulting performance aspects for their applicability in architecture, clarifying the potential of clay-based composites for sustainable construction, heritage compatible interventions, and future material development. By integrating material science with architectural applications, this study identifies the potential of clay-based composites for sustainable and heritage-compatible approaches to contribute to sustainable and circular construction practices, while also outlining key challenges and future research directions focused on optimization, large-scale implementation, and heritage-compatible innovation. Full article

This study examines agricultural and rural carbon emission efficiency and the underlying “low-carbon efficiency illusion” in China, where measured efficiency gains fail to translate into genuine environmental improvements. Using panel data from 30 Chinese provinces spanning 2000 to 2022, this study employs a meta-frontier slack-based measure (SBM) model to assess agricultural and rural carbon emission efficiency across meta-frontier and group-frontier benchmarks and investigates the efficiency illusion from the perspective of carbon emission reduction cost constraints. We further combine the Extreme Gradient Boosting (XGBoost) model and Shapley Additive Explanations (SHAP) explainability methods to identify core drivers of agricultural carbon emission reduction costs. We find that technical inefficiency is the primary constraint on China’s agricultural and rural carbon emission efficiency; the number of provinces with an efficiency illusion shows an initial increase followed by a decrease between 2005 and 2022; and core drivers of emission reduction costs exhibit heterogeneous impacts and significant threshold effects across the two frontier frameworks. These findings offer evidence-based guidance for designing differentiated, targeted emission reduction strategies to mitigate the efficiency illusion, advance low-carbon agricultural transition, and support the sustainable development of agricultural and rural systems in the context of the United Nations Sustainable Development Goals. Full article

This paper is based on data from 121 cities in China’s ecologically fragile regions from 2008 to 2022; it constructs an indicator system for the efficiency of pollution control and carbon reduction in agricultural practices. This system includes expenditures on agriculture, forestry, and water affairs, arable land area, agricultural laborers, total agricultural output value, agricultural carbon emissions, and agricultural non-point source pollution. It uses a super-efficiency SBM model that incorporates non-desirable outputs to measure the synergistic efficiency and analyzes its dynamic evolution using the Malmquist–Luenberger index to reveal the spatiotemporal characteristics of the synergistic efficiency. A Tobit model identifies the influence of factors, such as the level of rural economic development, crop planting structure, the strength of fiscal support for agriculture, rural education level, urbanization rate, and mechanization level on the synergistic efficiency. The results show that, from a temporal perspective, the average synergistic efficiency was only 0.58, significantly below the effective value of 1, indicating substantial room for overall improvement. Only 10 cities met the benchmark, with distinctly different reasons for compliance, while the remaining 111 cities remained inefficient. Regarding influencing factors, crop planting structure, the strength of fiscal support for agriculture, and urbanization rate significantly and positively drive efficiency; the level of rural economic development and mechanization level significantly inhibit efficiency, and rural education level shows no significant impact. These findings provide targeted policy recommendations for the synergy effect in ecologically fragile areas, as well as for low-carbon agricultural development. Full article

In the pursuit of global industrial sustainable development and carbon neutrality goals, the aviation manufacturing sector serves as a strategic pillar for advancing global economic growth, driving technological innovation and enhancing national competitiveness. Its green innovation has thus become a critical pathway to achieving carbon neutrality targets and spearheading the sustainable transformation of the industrial sector. This study investigates the enabling effect of artificial intelligence (AI) on green innovation within aviation manufacturing enterprises. The findings indicate that AI exerts a promotional impact on green innovation via three primary channels: technological empowerment, labor structure optimization and resource access improvement. Specifically, AI drives the digital transformation of operational processes in aviation manufacturing, rationalizes the human resource framework of the sector, and eases the financing pressures confronted by aviation manufacturing enterprises. A heterogeneity analysis reveals that regional resource endowments, enterprise production attribute characteristics and external market attention can form synergistic interactions with AI technology. What is more prominent is that the positive influence of AI on green innovation is especially distinct in three scenarios: in economically developed urban areas, among enterprises with traditional production attributes, and for enterprises that garner high levels of analyst attention. Full article

The rapid demand for sustainable and efficient energy storage solutions has prompted the pursuit of eco-friendly electrode materials. Biomass-derived carbons from food waste offer a promising pathway to meet this need by combining waste valorization, environmental benefits, and high electrochemical performance. This review highlights that food waste biomass is an effective and inexpensive source of precursors for producing high-performance carbon materials for supercapacitors. Food waste, which includes fruit peels and vegetable residues, cereal husks, and oilseed residues, is a good source of lignocellulosic components, heteroatoms, and structural features that determine the electrochemical characteristics of the derived carbons. These wastes produce hierarchically porous carbons with high surface areas (>1500 m² g⁻¹) on pyrolysis and activation that provide superior ion transport, wettability and pseudocapacitive behaviour. Their electrochemical performance includes capacitances up to 520 F g⁻¹ and energy densities of 35–70 Wh kg⁻¹ in optimized systems, particularly under extended voltage windows or in hybrid supercapacitor configurations, and high cycling stability is equal to or even better than traditional carbons such as activated carbon and graphene. Additionally, biomass valorization contributes to a high level of greenhouse gas capture, decreases landfill, and correlates with the idea of a circular economy. The commercialization potential of biomass-based supercapacitors is supported by recent developments in AI-based optimization, combined with scalable synthesis methods, which would support ecologically, economically, and technologically sustainable energy storage on a large scale. Full article

The need to create lightweight materials with better mechanical properties has led to the use of Fiber Reinforced Composites (FRCs)s in the aerospace and automotive industries. The mechanical behavior of FRCs is heterogeneous, especially in conditions of low-velocity impact (LVI). The impact events cause structural damage, where most of the available literature deals with mono- or bi-composites in controlled situations. This work will present the results of studying the behavior of mono, bi- and tri-hybrids with carbon, glass and Kevlar fiber-reinforced epoxy. The sequences of the laminate stacks, number of plies and laminate thickness in the drop weight testing were across velocities of 1.91 to 3.91 m/s at drop heights of 19 to 79 cm. The dominant pillars of LVI, such as peak load, energy absorption and the modes of damage, were analyzed. The glass-dominated laminates peaked at 5.67 kN, while the Kevlar-dominated laminates reached peak flow in ductile collapse with greater quantities of absorbed energy. The leaders in strength and energy were the hybrids of Kevlar–glass (KG) cross-ply at 8.08 kN and 47.28 J and quasi-isotropic Kevlar–carbon–glass (KCG) at 9.12 kN and 47.25 J, showcasing a balance of strength and toughness. The rest, holding a greater quantity of Kevlar, ranging in thickness and cross-plies, were shaped with a load center. The experimental conclusion is that hybridization improved impact resistance and ductility, which is best supported by the glass/carbon rigidity-layered laminates. Such understanding directs the design work of future composite materials for better impact control. Full article

Carbon monoxide (CO) is a highly toxic, colorless, and odorless gas posing significant risks to human health and the environment. Catalytic oxidation offers a promising, economically viable solution by converting CO into nontoxic CO₂ under mild conditions without energy-intensive regeneration. However, existing MnO₂-based catalysts often exhibit poor activity and stability in harsh environments, particularly at low temperatures and high humidity. In this study, we propose a Cu²⁺ ion-exchange modification strategy to activate lattice oxygen species in δ-MnO₂, thereby significantly enhancing its low-temperature CO oxidation performance. Structural characterization by XRD and SEM confirms that Cu-doped δ-MnO₂ retains its original birnessite-type structure and porous morphology. ICP-OES and XPS analyses verify that Cu²⁺ ions effectively replace interlayer K⁺ ions. The resulting MnO₂-150Cu catalyst demonstrates exceptional activity, achieving 100% CO conversion at 40 °C in dry air and maintaining full conversion at 80 °C in the presence of 1.3 vol.% H₂O at a weight hourly space velocity of 150 L/g·h. H₂-TPR and O₂-TPD results confirm that Cu doping enhances the reducibility and mobility of lattice oxygen. Furthermore, in situ DRIFTS analysis reveals that the migration of active oxygen species is the rate-limiting step at low temperatures. This work provides a novel and effective strategy for activating lattice oxygen in MnO₂-based catalysts, offering a promising pathway for developing high-performance materials for low-temperature CO oxidation under practical environmental conditions. Full article

Monitoring dissolved carbon dioxide (CO₂) in aquatic and sediment systems is critical for understanding carbon cycling and climate feedback. This study develops and characterizes a compact, low-cost microbolometer-based attenuated total reflectance (ATR) mid-infrared sensor for direct dissolved CO₂ measurement in liquid and soil-water environments. The system integrates a ZnSe ATR crystal with custom suspended SiN membrane microbolometers and uses evanescent-wave absorption at 4.26 μm with a broadband LED source and computational spectral reconstruction, eliminating the need for an interferometer. Calibration shows excellent linearity (R² ≈ 0.99) over 50–1000 ppm CO₂, with a practical limit of detection (LOD) of ~26–35 ppm at 5–25 °C. UV-induced CO₂ generation from soil-water mixtures was investigated across UV wavelengths, revealing UV-C (254 nm) as optimal, producing net ΔCO₂ ≈ 339 ppm above ambient levels in 30 min. Environmental factors (temperature 5–35 °C, pH 5–11, pressure 1–1.5 ATM, dissolved organic carbon) were systematically evaluated, confirming robust sensor performance (accuracy >90%, correlation r > 0.98 with reference instrument). This sensor represents the first integration of MEMS microbolometer detectors with ATR evanescent-wave spectroscopy for liquid-phase dissolved CO₂, enabling real-time monitoring and rapid sediment organic carbon assessment in a field-deployable platform. Full article

Ensuring the quality, reliability, and efficiency of cold chain logistics for thermolabile pharmaceutical products, particularly vaccines, remains a critical challenge in global health supply chains. These biologics require stringent temperature control throughout storage, transport, and distribution to preserve their efficacy. Persistent issues such as maintaining product integrity, accurately forecasting vaccine demand, and fostering trust among stakeholders often result in inefficiencies, waste, and public mistrust. This study proposes an intelligent digital management framework specifically designed for vaccine cold chains, integrating blockchain, the Internet of Things (IoT), and machine learning (ML) to address these challenges in a holistic and sustainable manner. The main innovation of the study lies in combining secure traceability, real-time cold chain monitoring, and predictive decision support within a unified vaccine cold chain management framework rather than treating these functions as isolated technological solutions. Using WHO immunization coverage data and vaccine-related review data, the framework supports vaccine demand forecasting through the Informer model and stakeholder trust assessment through BERT-based sentiment analysis. In the sentiment analysis task, the BERT model achieved ~80% accuracy on dominant sentiment classes, with a weighted F1-score of 0.6974, demonstrating strong performance on imbalanced datasets. By minimizing vaccine spoilage and enabling more accurate demand planning, the system reduces excess production and distribution, thus lowering resource consumption, carbon emissions, and financial waste. Moreover, trust-informed analytics support better alignment of supply with actual community needs, fostering equity and resilience in vaccine distribution. While this framework has been validated through simulations and experimental evaluation, further real-world testing is needed to assess long-term stability and stakeholder adoption. Nonetheless, it provides a scalable and adaptive foundation for advancing sustainability and transparency in pharmaceutical cold chains. Full article

(1) Background: Soil fertility in organic systems depends on interactions between physicochemical properties and biological processes that regulate nutrient availability along the soil profile. However, information on their vertical distribution remains limited, particularly for root crops such as sugar beet. This study evaluated depth-related patterns in soils from three organic farms growing sugar beet. (2) Methods: Soil profiles (0–120 cm) were sampled and analyzed for physicochemical properties, mineral nitrogen (N) forms, and biological indicators, including the QBS-ar index, microbial abundance, and functional genes involved in N and carbon cycling. (3) Results: Nitrate-N and total mineral N were mainly concentrated in the 0–40 cm layer and declined markedly with depth. Microbial abundance and most N-cycling functional genes were similarly enriched in the topsoil, showing clear vertical stratification. Statistical analyses suggested that functional gene composition was associated with mineral N gradients after accounting for soil depth. (4) Conclusions: These findings provide an exploratory indication of relationships between mineral N forms and microbial indicators in an organically managed sugar beet system. Given the limited number of sampling units, results should be interpreted cautiously. However, these results highlight the value of soil profile approaches for understanding N redistribution and improving nutrient management strategies. Full article

The decarbonization of international shipping has accelerated interest in ammonia as a zero-carbon marine fuel. However, its acute toxicity poses safety challenges fundamentally different from those associated with LNG. This study presents a structured comparative regulatory analysis of the IGF Code and the IMO Interim Guidelines for Ships Using Ammonia as Fuel through a chapter-by-chapter review of key safety domains. The results show that, despite structural similarities, the two frameworks diverge significantly in their underlying safety logic: LNG regulation is primarily oriented toward flammability and explosion prevention, whereas ammonia regulation adopts a toxicity-driven safety architecture. This shift is reflected in ppm-level gas detection thresholds, ammonia release mitigation systems (ARMS), toxic area and Safe Haven concepts, broader secondary containment measures, and enhanced personnel protection requirements. These findings suggest that ammonia safety cannot be adequately addressed through incremental extensions of LNG-based rules alone. Instead, it requires a dedicated regulatory approach that explicitly incorporates toxic exposure management into ship design and operation. Full article

Although numerous studies have focused on the potential application of heterotrophic nitrification–aerobic denitrification (HNAD) bacteria in wastewater treatment, research exploring their potential in aquaculture biofloc systems remains limited. In this study, a promising HNAD strain, identified as Stutzerimonas stutzeri MJ20, was isolated from mature biofloc. This strain efficiently utilized low-cost carbon sources (e.g., glucose) and small-molecule carbon sources (e.g., sodium acetate and sodium succinate). Under conditions with glucose as the carbon source, a carbon-to-nitrogen (C/N) ratio of 15, pH 6–9, temperature 25–35 °C, salinity 0–35‰, and shaker speed of 0–150 rpm, it achieved removal rates of 95–100% for NH₄⁺-N, NO₂⁻-N, and NO₃⁻-N at initial concentrations of 100 mg/L each. Even at higher concentrations (up to 200 mg/L NH₄⁺-N and 500 mg/L for both NO₂⁻-N and NO₃⁻-N), removal rates exceeded 99%. Under mixed nitrogen sources, strain MJ20 demonstrated efficient nitrogen removal, preferentially utilizing NH₄⁺-N, with only minimal and transient accumulation of nitrite and nitrate. Genomic analysis revealed that MJ20 carries key denitrification genes, including napA, nirS, norB and nosZ, and possesses complete pathways for nitrate reduction to nitrogen gas and ammonia assimilation, although typical autotrophic nitrification genes were not detected. Combined genomic data and autotrophic culture experiments indicated that, in addition to utilizing various organic carbon sources, the strain also exhibited certain autotrophic growth capabilities. Furthermore, MJ20 showed strong flocculation ability (flocculation rate > 96% within 16 h), sensitivity to multiple common antibiotics, and no toxicity to zebrafish, demonstrating favorable biosafety. In simulated seawater aquaculture wastewater with a C/N ratio of 5, it achieved a total nitrogen removal rate exceeding 94% within 72 h. These results indicate that strain MJ20 possesses comprehensive advantages, including efficient nitrogen removal, broad carbon source adaptability, strong environmental resilience, minimal accumulation of intermediate nitrogen products, excellent flocculation ability, and high biosafety. These traits highlight its potential for application in biofloc systems and in treating aquaculture tail water with a low C/N ratio. This study provides theoretical insights and practical guidance for screening HNAD bacteria suitable for biofloc systems. Full article

Aligning urban morphology with carbon emission intensity categories is essential for advancing sustainable urban development and achieving dual carbon objectives. This study utilizes data from 336 Chinese cities across 2010, 2015, and 2020 to construct multi-dimensional morphological indicators. Spectral clustering categorizes cities into four distinct classes: high-emission intensity, medium-emission ecological, medium-emission developmental, and low-emission. An integrated gradient boosting framework, combined with SHAP and PDP interpretability tools, identifies key morphological drivers and their nonlinear contributions to class assignments. Results demonstrate that morphological features exert nonlinear and threshold-dependent effects on carbon emission intensity category assignments, exhibiting substantial spatial heterogeneity across urban clusters. Core drivers, such as economic density and the landscape shape index, follow distinctly different decision pathways in each category. Furthermore, morphological factors produce non-additive interactive effects that generate region-specific shifts in classification probability. Through this classification-oriented approach, the study provides policymakers with a systematic and readily interpretable reference to inform the formulation of context-specific low-carbon spatial planning strategies. Full article

Background:Pinellia ternata is a major medicinal herb widely utilized in traditional medicine, but is sensitive to high temperature, which often triggers a severe “sprout tumble” phenomenon. Methods: To elucidate the molecular mechanisms of heat tolerance in P. ternata, we screened two contrasting germplasms: the heat-tolerant JBX1 and the heat-sensitive XBX4. In the present study, a combined analysis of physiology, transcriptome, and metabolome was performed on JBX1 and XBX4 under heat stress at 40 °C. Results: JBX1 exhibited significantly greater leaf thickness, higher basal chlorophyll content, more stable antioxidant enzyme activities, and lower oxidative damage than XBX4 under heat stress. Transcriptomically, JBX1 maintained elevated basal expression of genes encoding key enzymes in carbon fixation, amino acid metabolism, and phenylpropanoid biosynthesis, as well as those encoding heat shock transcription factors (HSFs), heat shock proteins (HSPs), and the thermosensor Thermo-With ABA-Response 1 (TWA1). Metabolomically, JBX1 accumulated higher levels of key primary metabolites, antioxidants, and protective phenylpropanoids under both control and heat conditions. Notably, a “polarity reversal” emerged in nitrogen metabolism, where core amino acids accumulated in JBX1 but were depleted in XBX4. Integrated analysis revealed a more coordinated gene–metabolite network in JBX1 involving the phenylpropanoid, ATP-binding cassette (ABC) transporter, and glutathione pathways. Conclusions: Our findings demonstrate that JBX1 possessed stronger basal thermotolerance, which is derived from coordinated establishment of higher constitutive metabolic reserves and efficient dynamic metabolic reprogramming. This study provides insights into the molecular mechanisms of heat stress in P. ternata. Full article

Grasslands are key terrestrial ecosystems in which root dynamics regulate soil carbon and nutrient cycling. Although grazing constitutes the predominant land use practice in grassland ecosystems, its impacts on root dynamics remain inadequately elucidated, particularly across a gradient of grazing intensities. In this two-year field experiment, an improved root window method was applied to investigate the effects of four grazing intensities (no grazing, light grazing, moderate grazing, heavy grazing) on root production, root mortality, root standing crop, root turnover, and root lifespan in the saline–alkaline grassland in northern China. The results showed that root production and root mortality exhibited pronounced seasonal dynamics, with peaks in June and August for root production and in September for root mortality. These seasonal patterns were primarily driven by precipitation and were not significantly altered by grazing intensity. Moderate grazing significantly increased root production by 51.2% through changes in soil bulk density and selective livestock grazing, supporting the intermediate disturbance hypothesis. Root turnover was predominantly shaped by plant community composition and interannual precipitation, as opposed to grazing intensity. Overall, these findings indicate that moderate grazing promotes root growth, providing important insights into the sustainable utilization of saline–alkali grassland resources. In other words, appropriate measures must be taken to effectively manage grazing activities in the fragile saline–alkaline grasslands of northern China. Full article