Search Results (1,328)

Produce supply chains play a critical role in ensuring fruits and vegetables reach consumers efficiently, affordably, and at optimal freshness. In recent decades, hub-and-spoke network models have emerged as valuable tools for optimizing sustainable cold food supply chains. Traditional optimization efforts typically focus on removing inefficiencies, minimizing lead times, refining inventory management, strengthening supplier relationships, and leveraging technological advancements for better visibility and control. However, the majority of models rely on deterministic approaches that overlook the inherent uncertainties of crop yields, which are further intensified by climate variability. Rising atmospheric CO₂ concentrations, along with shifting temperature patterns and extreme weather events, have a substantial effect on crop productivity and availability. Such uncertainties can prompt distributors to seek alternative sources, increasing costs due to supply chain reconfiguration. This research introduces a stochastic hub-and-spoke network optimization model specifically designed to minimize transportation expenses by determining optimal distribution routes that explicitly account for climate variability effects on crop yields. A use case involving a cold food supply chain (CFSC) was carried out using several weather scenarios based on climate models and real soil data for California. Strawberries were selected as a representative crop, given California’s leading role in strawberry production. Simulation results show that scenarios characterized by increased rainfall during growing seasons result in increased yields, allowing distributors to reduce transportation costs by sourcing from nearby farms. Conversely, scenarios with reduced rainfall and lower yields require sourcing from more distant locations, thereby increasing transportation costs. Nonetheless, supply chain configurations may vary depending on the choice of climate models or weather prediction sources, highlighting the importance of regularly updating scenario inputs to ensure robust planning. This tool aids decision-making by planning climate-resilient supply chains, enhancing preparedness and responsiveness to future climate-related disruptions. Full article

Oil spill simulation models are essential for predicting the oil spill behavior and movement in marine environments. In this study, we comprehensively reviewed a large and diverse body of peer-reviewed literature obtained from Scopus and Web of Science. Our initial analysis phase focused on examining trends in scientific publications, utilizing the complete dataset derived after systematic screening and database integration. In the second phase, we applied elements of a systematic review to identify and evaluate the most influential contributions in the scientific field of oil spill simulations. Our analysis revealed a steady and accelerating growth of research activity over the past five decades, with a particularly notable expansion in the last two. The field has also experienced a marked increase in collaborative practices, including a rise in international co-authorship and multi-authored contributions, reflecting a more global and interdisciplinary research landscape. We cataloged the key modeling frameworks that have shaped the field from established systems such as OSCAR, OIL-MAP/SIMAP, and GNOME to emerging hybrid and Lagrangian approaches. Hydrodynamic models were consistently central, often integrated with biogeochemical, wave, atmospheric, and oil-spill-specific modules. Environmental variables such as wind, ocean currents, and temperature were frequently used to drive model behavior. Geographically, research has concentrated on ecologically and economically sensitive coastal and marine regions. We conclude that future progress will rely on the real-time integration of high-resolution environmental data streams, the development of machine-learning-based surrogate models to accelerate computations, and the incorporation of advanced biodegradation and weathering mechanisms supported by experimental data. These advancements are expected to enhance the accuracy, responsiveness, and operational value of oil spill modeling tools, supporting environmental monitoring and emergency response. Full article

Accelerated industrialization and surging energy demands have led to continuously rising atmospheric CO₂ concentrations. Developing sustainable methods to reduce atmospheric CO₂ levels is crucial for achieving carbon neutrality. Concurrently, the rapid development of new energy vehicles has driven a significant increase in demand for lithium-ion batteries (LIBs), which are now approaching an end-of-life peak. Efficient recycling of valuable metals from spent LIBs represents a critical challenge. This study employs conventional hydrometallurgical processing to recover valuable metals from spent LIBs. Subsequently, Ni-doped Co₃O₄ (Ni:Co₃O₄) supported on the natural mineral attapulgite (ATP) was synthesized via a sol–gel method. The incorporation of a small amount of Ni into the Co₃O₄ lattice generates oxygen vacancies, inducing a localized surface plasmon resonance (LSPR) effect, which significantly enhances charge carrier transport and separation efficiency. During the photocatalytic reduction of CO₂, the primary product CO generated by the Ni:Co₃O₄/ATP composite achieved a high production rate of 30.1 μmol·g⁻¹·h⁻¹. Furthermore, the composite maintains robust catalytic activity even after five consecutive reaction cycles. Full article

The global atmospheric concentration of carbon dioxide (CO₂) has exceeded 420 ppm. Adsorption-based carbon capture technologies, offer energy-efficient, sustainable solutions. Relying on classical adsorption models like Langmuir to predict CO₂ uptake presents limitations due to the need for case-specific parameter fitting. To address this, the present study introduces a universal machine learning (ML) framework using multiple algorithms—Generalized Linear Model (GLM), Feed-forward Multilayer Perceptron (DL), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosted Trees (GBT)—to reliably predict CO₂ adsorption capacities across diverse zeolite structures and conditions. By compiling over 5700 experimentally measured adsorption data points from 71 independent studies, this approach systematically incorporates critical factors including pore size, Si/Al ratio, cation type, temperature, and pressure. Rigorous Cross-Validation confirmed superior performance of the GBT model (R² = 0.936, RMSE = 0.806 mmol/g), outperforming other ML models and providing comparable performance with classical Langmuir model predictions without separate parameter calibration. Feature importance analysis identified pressure, Si/Al ratio, and cation type as dominant influences on adsorption performance. Overall, this ML-driven methodology demonstrates substantial promise for accelerating material discovery, optimization, and practical deployment of zeolite-based CO₂ capture technologies. Full article

This study investigated the physiological regulatory mechanisms by which exogenous trehalose intake enhances the adaptation of the global stored-grain pest T. castaneum to high-concentration carbon dioxide (CO₂) stress. By supplementing exogenous trehalose under high-CO₂ controlled atmosphere stress, we measured the activities of key detoxification enzymes (e.g., carboxylesterase and cytochrome P450) and the levels of carbohydrate substances (e.g., glycogen, glucose, and trehalose). The results demonstrated that trehalose feeding significantly alleviated CO₂ induced mortality in T. castaneum and prolonged their survival time. In terms of detoxification metabolism, a trehalose-rich diet significantly reduced the activities of cytochrome P450 and carboxylesterase, while the glucose content in the beetles decreased markedly. These findings indicate that trehalose accumulation mitigates physiological damage caused by high-CO₂ stress in T. castaneum. Furthermore, exogenous trehalose intake did not disrupt carbohydrate metabolic homeostasis in the beetles, as trehalase activity and the levels of various carbohydrates remained relatively stable. This study elucidates the role of trehalose metabolism in T. castaneum’s adaptation to high-CO₂ environments, providing a theoretical foundation for optimizing controlled atmosphere grain storage technology and developing novel pest control strategies. Full article

Direct air capture (DAC), as a complementary strategy to carbon capture and storage (CCS), offers a scalable and sustainable pathway to remove CO₂ directly from the ambient air. This study presents a detailed evaluation of the amine-functionalised metal-organic framework (MOF) sorbent, mmen-Mg₂(dobpdc), for DAC using a temperature–vacuum swing adsorption (TVSA) process. While this sorbent has demonstrated promising performance in point-source CO₂ capture, this is the first dynamic simulation-based study to rigorously assess its effectiveness for low-concentration atmospheric CO₂ removal. A transient one-dimensional TVSA model was developed in Aspen Adsorption and validated against experimental breakthrough data to ensure accuracy in capturing both the sharp and gradual adsorption kinetics. To enhance process efficiency and sustainability, this work provides a comprehensive parametric analysis of key operational factors, including air flow rate, temperature, adsorption/desorption durations, vacuum pressure, and heat exchanger temperature, on process performance, including CO₂ purity, recovery, productivity, and specific energy consumption. Under optimal conditions for this sorbent (vacuum pressure lower than 0.15 bar and feed temperature below 15 °C), the TVSA process achieved ~98% CO₂ purity, recovery over 70%, and specific energy consumption of about 3.5 MJ/KgCO₂. These findings demonstrate that mmen-Mg₂(dobpdc) can achieve performance comparable to benchmark DAC sorbents in terms of CO₂ purity and recovery, underscoring its potential for scalable DAC applications. This work advances the development of energy-efficient carbon removal technologies and highlights the value of step-shape isotherm adsorbents in supporting global carbon-neutrality goals. Full article

Although cold atmospheric plasma (CAP) has shown promise in facilitating wound repair due to its non-thermal and non-invasive properties, its dynamic effects on cellular response and metabolic regulation remain poorly characterized, and the mechanism is still unclear. In this study, we developed a microfluidic experimental system that integrates a CAP treatment module with multiparametric in situ sensing capabilities, along with precise environmental control of temperature, humidity, and CO₂ concentration. A stratified microfluidic chip was engineered to co-culture HaCaT keratinocytes and HSF fibroblasts. CAP treatment was applied within this platform, and the dynamic processes of cell migration, proliferation, and multiple metabolic markers were simultaneously monitored. The experimental results show that the system can not only achieve real-time observation in the healing process under plasma intervention, but also find that the healing process is closely related to the concentration of NO₂⁻. In addition, the study also found that keratin KRT14, which is thought to be closely related to wound healing, decreased significantly in the process of plasma-induced healing. The platform provides high-resolution experimental tools to elucidate the biological effects of CAP and has the potential for parameter optimization, material evaluation, and personalized therapeutic development to advance plasma research and clinical translational applications. Full article

Transient increments of X-ray radiation and extreme ultraviolet (EUV) during solar flares are strong drivers of thermospheric dynamics on Mars, yet their class-dependent impacts remain poorly measured. This work provides the first direct, side-by-side study of Martian thermospheric reactions to flares X8.2 on 10 September 2017 and M6.0 on 17 September 2017. This study shows nonlinear, class-dependent effects, compositional changes, and recovery processes not recorded in previous investigations. Species-specific responses deviated significantly from irradiance proportionality, even though the soft X-ray flux in the X8.2 flare was 13 times greater. Argon (Ar) concentrations rose 3.28× (compared to 1.13× for M6.0), and radiative cooling led CO₂ heating to approach a halt at ΔT = +40 K (X8.2) against +19 K (M6.0) at exobase altitudes (196–259 km). N₂ showed the largest class difference, where temperatures rose by +126 K (X8.2) instead of +19 K (M6.0), therefore displaying flare-magnitude dependent thermal sensitivity. The 1.95× increase in O concentrations during X8.2 and the subsequent decrease following M6.0 (−39 K cooling) illustrate the contradiction between photochemical production and radiative loss. The O/CO₂ ratio at 225 km dropped 46% during X8.2, revealing compositional gradients boosted by flares. Recovery timeframes varied by class; CO₂ quickly re-equilibrated because of effective cooling, whereas inert species (Ar, N₂) stabilized within 1–2 orbits after M6.0 but needed >10 orbits of the MAVEN satellite after the X8.2 flare. The observations of the X8.2 flare came from the western limb of the Sun, but the M6.0 flare happened on the far side. The CME shock was the primary driver of Mars’ EUV reaction. These findings provide additional information on atmospheric loss and planetary habitability by indicating that Mars’ thermosphere has a saturation threshold where strong flares induce nonlinear energy partitioning that encourages the departure of lighter species. Full article

Flammulina velutipes is a widely cultivated edible mushroom in East Asia, recognized for its nutritional benefits and distinct morphology characterized by a long stipe and a compact, hemispherical pileus. The pileus not only plays a critical biological role in reproduction through spore formation but also serves as a key commercial trait influencing consumer preference and market value. Despite its economic importance, pileus development in F. velutipes is highly sensitive to environmental factors, among which carbon dioxide (CO₂) concentration is particularly influential under indoor cultivation conditions. While previous studies have reported that elevated CO₂ levels can inhibit pileus expansion in other mushroom species, the molecular mechanisms by which CO₂ affects pileus growth in F. velutipes remain poorly understood. In this study, we investigated the impact of CO₂ concentration on pileus morphology and gene expression in F. velutipes by cultivating fruiting bodies under two controlled atmospheric conditions: low (1000 ppm) and high (10,000 ppm) CO₂. Morphometric analysis revealed that elevated CO₂ levels significantly suppressed pileus expansion, reducing the average diameter by more than 50% compared to the low CO₂ condition. To elucidate the underlying genetic response, we conducted RNA sequencing and identified 102 differentially expressed genes (DEGs), with 78 being downregulated under elevated CO₂. Functional enrichment analysis highlighted the involvement of cyclin-dependent protein kinase regulatory pathways in this response. Two cyclin genes were found to be significantly downregulated under elevated CO₂ conditions, and their suppression was validated through quantitative real-time PCR. These genes, possessing conserved cyclin_N domains, are implicated in the regulation of the eukaryotic cell cycle, particularly in mitotic growth. These results indicate that CO₂-induced downregulation of cyclin genes may underlie cell cycle arrest, contributing to inhibited pileus development. This study is the first to provide transcriptomic evidence that elevated CO₂ concentrations specifically repress PHO80-like cyclin genes in F. velutipes, revealing a molecular mechanism by which CO₂ stress inhibits pileus development. These findings suggest that elevated CO₂ triggers a morphogenetic checkpoint by repressing PHO80-like cyclins, thereby modulating cell cycle progression during fruiting body development. This study provides the first evidence of such a transcriptional response in edible mushrooms and offers promising molecular targets for breeding CO₂-resilient strains and optimizing commercial cultivation conditions. Full article

In Italy, beech and Turkey oak are among the most widespread tree species, thriving across various climatic zones. However, rising temperatures and prolonged droughts significantly affect their physiological performance and growth dynamics. To assess their long-term responses to climate change, mature beech and Turkey oak trees were studied in Central Italy at an elevation of 450 m. Using dendrochronological and stable isotope analyses (1981–2020), their growth patterns and physiological adaptations were evaluated. Beech exhibited a higher growth rate, with a basal area increment (BAI) of 17.1 ± 1.1 cm² year⁻¹, compared to Turkey oak, showing a BAI of 12.7 ± 0.96 cm² year⁻¹. Both species actively responded to increasing atmospheric CO₂ levels. Additionally, spring and the previous summer’s climatic conditions played a key role in growth, while summer temperature and precipitation influenced carbon discrimination. For beech, correlations between BAI and iWUE (intrinsic water efficiency, defined as the ratio between photosynthesis and stomatal conductance) were initially weak and not statistically significant. However, the correlation became significant, strengthening steadily into the early 2000s, likely related to thinning of the beech trees. For Turkey oak, the correlation was already significant and strong from the beginning of the analysis period (1981), persisting until the late 1990s. Our findings suggest that both species actively adjust their iWUE in response to an increasing atmospheric CO₂ concentration. However, while Turkey oak’s iWUE and BAI relationship remains unaffected by the likely thinning, beech benefits from reduced competition for light, nutrients, and water. Despite climate change’s impact on marginal populations, microclimatic conditions allow beech to outperform Turkey oak, a species typically better suited to drier climates. Full article

Vibrio parahaemolyticus is the leading cause of bacterial diarrhea in humans from shellfish consumption. In Thailand, blood clam is a popular shellfish, but homemade cooking often results in insufficient heating. Therefore, consumers may suffer from food poisoning due to Vibrio infection. This study aimed to determine the effect of chitooligosaccharide conjugated with epigallocatechin gallate (COS-EGCG) at different concentrations (200 and 400 ppm) combined with high-voltage atmospheric cold plasma (HVACP) on inhibiting V. parahaemolyticus in vitro and in challenged blood clam meat. Firstly, HVACP conditions were optimized for gas composition and treatment time (20 and 60 s); a 70% Ar and 30% O₂ gas mixture resulted in the highest ozone formation and a treatment time of 60 s was used for further study. COS-EGCG conjugate at 400 ppm with HVACP (ACP-CE400) completely killed V. parahaemolyticus after incubation at 37 °C for 6 h. Furthermore, an antibacterial ability of ACP-CE400 treatment against bacterial cells was advocated due to the increased cell membrane damage, permeability, and leakage of proteins and nucleic acids. Scanning electron microscopy (SEM) showed cell elongation and pore formation, while confocal microscopy revealed disrupted biofilm formation. Additionally, the shelf life of challenged blood clam meat treated with ACP-CE400 was extended to nine days. SEM analysis revealed damaged bacterial cells on the meat surface after ACP-CE400 treatment, indicating the antibacterial activity of the combined treatment. Thus, HVACP combined with COS-EGCG conjugate, especially at a highest concentration (400 ppm), effectively inhibited microbial growth and extended the shelf life of contaminated blood clam meat. Full article

Increasing soil carbon storage is an important strategy for achieving sustainable development. Enhancing soil carbon sequestration capacity can effectively reduce the concentration of atmospheric carbon dioxide, which not only contributes to the carbon neutrality goal but also helps maintain ecosystem stability. Based on 146 soil samples collected at plot locations selected across Beijing, we examined relationships between soil organic carbon (SOC) and key characteristics of urban forests, including their spatial structure and species complexity. The results showed that SOC in the topsoil with a depth of 20 cm was highest over forested plots (6.384 g/kg–20.349 g/kg) and lowest in soils without any vegetation cover (5.586 g/kg–6.783 g/kg). The plots with herbaceous/shrub vegetation but no tree cover had SOC values in between (5.586 g/kg–15.162 g/kg). The plot data revealed that SOC was better correlated with the physical structure than the species diversity of Beijing’s urban trees. The correlation coefficients (r) between SOC and five physical structure indicators, including average diameter at breast height (DBH), average tree height, basal area density, and the diversity of DBH and tree height, ranged from 0.32 to 0.52, whereas the r values for four species diversity indicators ranged from 0.10 to 0.25, two of which were not statistically different from 0. Stepwise linear regression analyses revealed that the species diversity indicators were not very sensitive to SOC variations among a large portion of the plots and were about half as effective as the physical structure indicators for explaining the total variance of SOC. These results suggest that urban planning and greenspace management policies could be tailored to maximize the carbon co-benefits of urban land. Specifically, trees should be planted in urban areas wherever possible, preferably as densely as what can be allowed given other urban planning considerations. Protection of large, old trees should be encouraged, as these trees will continue to sequester and store large quantities of carbon in above- and belowground biomass as well as in soil. Such policies will enhance the contribution of urban land, especially urban forests and other greenspaces, to nature-based solutions (NBS) to climate change. Full article

Human activities at unprecedented levels have exacerbated the greenhouse effect and escalated the frequency of extreme weather. In response, the Chinese government has pledged to reach “carbon peak” by 2030 and achieve “carbon neutrality” by 2060. Leveraging the GOSAT L3 and L4B CO₂ datasets, this study investigated the spatiotemporal and vertical characteristics of atmospheric carbon dioxide (CO₂) concentration across China, alongside quantifying the relative importance of key influencing factors. The results show that there is a distinct regional disparity in CO₂ column concentration, with eastern China having a higher concentration level (406.85 × 10⁻⁶) than the western regions (400.92 × 10⁻⁶). Vertically, the concentration of CO₂ (390–420 × 10⁻⁶) reaches its peak at the near-surface layer (975 hPa) and then decreases with increasing altitude. High values of CO₂ levels in the mid-lower layer are concentrated in eastern China, while those in the upper layer are mainly located in southern China. In addition, CO₂ concentration shows seasonal variations, with the highest concentration occurring in spring (406.39 × 10⁻⁶) and the lowest in summer. Biospheric emissions and fossil fuel combustion emerge as the two most significant factors affecting CO₂ variation, with relative importance of 24% and 22%, respectively. Full article

Air pollution monitoring in ungauged zones presents unique challenges yet remains critical for understanding environmental health impacts and socioeconomic dynamics in the Eastern Mediterranean region. This study investigates air pollution patterns in northwestern Syria during 2019–2024, analyzing NO₂ and CO concentrations using Sentinel-5P TROPOMI satellite data processed through Google Earth Engine. Monthly concentration averages were examined across eight key locations using linear regression analysis to determine temporal trends, with Spearman’s rank correlation coefficients calculated between pollutant levels and five meteorological parameters (temperature, humidity, wind speed, atmospheric pressure, and precipitation) to determine the influence of political governance, economic conditions, and environmental sustainability factors on pollution dynamics. Quality assurance filtering retained only measurements with values ≥ 0.75, and statistical significance was assessed at a p < 0.05 level. The findings reveal distinctive spatiotemporal patterns that reflect the region’s complex political-economic landscape. NO₂ concentrations exhibited clear political signatures, with opposition-controlled territories showing upward trends (Al-Rai: 6.18 × 10⁻⁸ mol/m²) and weak correlations with climatic variables (<0.20), indicating consistent industrial operations. In contrast, government-controlled areas demonstrated significant downward trends (Hessia: −2.6 × 10⁻⁷ mol/m²) with stronger climate–pollutant correlations (0.30–0.45), reflecting the impact of economic sanctions on industrial activities. CO concentrations showed uniform downward trends across all locations regardless of political control. This study contributes significantly to multiple Sustainable Development Goals (SDGs), providing critical baseline data for SDG 3 (Health and Well-being), mapping urban pollution hotspots for SDG 11 (Sustainable Cities), demonstrating climate–pollution correlations for SDG 13 (Climate Action), revealing governance impacts on environmental patterns for SDG 16 (Peace and Justice), and developing transferable methodologies for SDG 17 (Partnerships). These findings underscore the importance of incorporating environmental safeguards into post-conflict reconstruction planning to ensure sustainable development. Full article

Algal and cyanobacterial blooms are anticipated to increase in frequency, duration, and geographic extent as a result of environmental changes, including climate warming, elevated nutrient concentrations, and increased runoff in both marine and freshwater ecosystems. The eutrophication of aquatic environments represents a substantial threat to human health. As eutrophication progresses, airborne algae and cyanobacteria, particularly harmful genera originating from aquatic environments, are released into the atmosphere and may pose potential risks to human health. Furthermore, respiratory distress has been documented in individuals exposed to aerosols containing harmful algal bloom (HAB) toxins. This review investigates the generation of aerosolised harmful algal blooms, their responses to environmental factors, and their associated health risks. Evidence suggests that airborne algae, cyanobacteria, and their toxins are widespread. When these are aerosolised into micrometre-sized particles, they become susceptible to atmospheric processing, which may degrade the HAB toxins and produce byproducts with differing potencies compared to the parent compounds. Inhalation of aerosolised HAB toxins, especially when combined with co-morbid factors such as exposure to air pollutants, could present a significant health risk to a considerable proportion of the global population. A more comprehensive understanding of the chemical transformations of these toxins and the composition of harmful algal and cyanobacterial communities can improve public safety. Full article