Search Results (248)

Background/Objectives: Global warming and rising CO₂ concentrations pose significant challenges to plant systems. Amid these pressures, this study contributes to understanding how tropical species respond by simultaneously evaluating reproductive and genetic traits. It specifically investigates the effects of maternal exposure to warming and elevated CO₂ on progeny physiology, genetic diversity, and population structure in Stylosanthes capitata, a resilient forage legume native to Brazil. Methods: Maternal plants were cultivated under controlled treatments, including ambient conditions (control), elevated CO₂ at 600 ppm (eCO₂), elevated temperature at +2 °C (eTE), and their combined exposure (eTEeCO₂), within a Trop-T-FACE field facility (Temperature Free-Air Controlled Enhancement and Free-Air Carbon Dioxide Enrichment). Seed traits (seeds per inflorescence, hundred-seed mass, abortion, non-viable seeds, coat color, germination at 32, 40, 71 weeks) and abnormal seedling rates were quantified. Genetic diversity metrics included the average (A) and effective (Ae) number of alleles, observed (Ho) and expected (He) heterozygosity, and inbreeding coefficient (Fis). Population structure was assessed using Principal Coordinates Analysis (PCoA), Analysis of Molecular Variance (AMOVA), number of migrants per generation (Nm), and genetic differentiation index (Fst). Two- and three-way Analysis of Variance (ANOVA) were used to evaluate factor effects. Results: Compared to control conditions, warming increased seeds per inflorescence (+46%), reduced abortion (−42.9%), non-viable seeds (−57%), and altered coat color. The germination speed index (GSI +23.5%) and germination rate (Gr +11%) improved with warming; combined treatments decreased germination time (GT −9.6%). Storage preserved germination traits, with warming enhancing performance over time and reducing abnormal seedlings (−54.5%). Conversely, elevated CO₂ shortened GSI in late stages, impairing germination efficiency. Warming reduced Ae (−35%), He (−20%), and raised Fis (maternal 0.50, progeny 0.58), consistent with the species’ mixed mating system; A and Ho were unaffected. Allele frequency shifts suggested selective pressure under eTE. Warming induced slight structure in PCoA, and AMOVA detected 1% (maternal) and 9% (progeny) variation. Fst = 0.06 and Nm = 3.8 imply environmental influence without isolation. Conclusions: Warming significantly shapes seed quality, reproductive success, and genetic diversity in S. capitata. Improved reproduction and germination suggest adaptive advantages, but higher inbreeding and reduced diversity may constrain long-term resilience. The findings underscore the need for genetic monitoring and broader genetic bases in cultivars confronting environmental stressors. Full article

Supercritical carbon dioxide (s-CO₂) Brayton cycles have emerged as a promising technology for high-efficiency power generation, owing to their compact architecture and favorable thermophysical properties. However, their performance degrades significantly under cold-climate conditions—such as those encountered in Greenland, Russia, Canada, Scandinavia, and Alaska—due to the proximity to the fluid’s critical point. This study investigates the behavior of the recompression Brayton cycle (RBC) under subzero ambient temperatures through the incorporation of low-critical-temperature additives to create CO₂-based binary mixtures. The working fluids examined include methane (CH₄), tetrafluoromethane (CF₄), nitrogen trifluoride (NF₃), and krypton (Kr). Simulation results show that CH₄- and CF₄-rich mixtures can achieve thermal efficiency improvements of up to 10 percentage points over pure CO₂. NF₃-containing blends yield solid performance in moderately cold environments, while Kr-based mixtures provide modest but consistent efficiency gains. At low compressor inlet temperatures, the high-temperature recuperator (HTR) becomes the dominant performance-limiting component. Optimal distribution of recuperator conductance (UA) favors increased HTR sizing when mixtures are employed, ensuring effective heat recovery across larger temperature differentials. The study concludes with a comparative exergy analysis between pure CO₂ and mixture-based cycles in RBC architecture. The findings highlight the potential of custom-tailored working fluids to enhance thermodynamic performance and operational stability of s-CO₂ power systems under cold-climate conditions. Full article

There have been some studies investigating the effects of air pollutants on male football players, but few have examined the gender-specific impact of air pollution on the athletic performance of female football players. This research gap limits the development of tailored training and competition strategies. Here, generalized mixed modeling was employed to assess the effects of main ambient air pollutants, i.e., particulate matter less than 2.5 μm (PM_2.5), ozone (O₃), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO), on athletic performance indicators (total movement distance (TMD), jogging distance (JD), and walking distance (WD)) among 14 female football players during 16 matches in the 2020 season of the Chinese Football Association Women’s Super League. Our findings indicate a significant negative association between the O₃ concentration and athletic performance, with fixed effect coefficients of −22.426 ± 8.889 for TMD, −10.817 ± 3.697 for JD, and −6.943 ± 3.265 for WD. The NO₂ concentration was significantly correlated with both TMD and JD, while PM_2.5, SO₂, and CO concentrations had minimal or negligible effects. Additionally, aerobic fitness was reduced as the O₃ concentration increased. These results provide valuable insights for optimizing gender-specific training and competition strategies under varying air quality conditions, offering a basis for more targeted health and performance interventions in professional female football players. Full article

The interactive effects between nano-silicon dioxide (n-SiO₂) and elevated CO₂ (eCO₂; 645 ppm) on soybean physiology, nitrogen fixation, and nutrient dynamics under climate stress remain underexplored. This study elucidates their combined effects under ambient (aCO₂; 410 ppm) and eCO₂ conditions. eCO₂ + n-SiO₂ synergistically enhanced shoot length (30%), total chlorophyll (112.15%), and photosynthetic rate (103.23%), alongside improved stomatal conductance and intercellular CO₂ (17.19%), optimizing carbon assimilation. Nodulation efficiency increased, with nodule number and biomass rising by 48.3% and 53.6%, respectively, under eCO₂ + n-SiO₂ versus aCO₂. N-assimilation enzymes (nitrate reductase, nitrite reductase, glutamine synthetase, glutamate synthase) surged by 38.5–52.1%, enhancing nitrogen metabolism. Concurrently, phytohormones (16–21%) and antioxidant activities (15–22%) increased, reducing oxidative markers (18–22%), and bolstering stress resilience. Nutrient homeostasis improved, with P, K, Mg, Cu, Fe, Zn, and Mn elevating in roots (13–41%) and shoots (13–17%), except shoot Fe and Zn. These findings demonstrate that n-SiO₂ potentiates eCO₂-driven benefits, amplifying photosynthetic efficiency, nitrogen fixation, and stress adaptation through enhanced biochemical and nutrient regulation. This synergy underscores n-SiO₂ role in optimizing crop performance under future CO₂-rich climates, advocating nano-fertilizers as sustainable tools for climate-resilient agriculture. Full article

Marine transportation contributes approximately 2.5% of global greenhouse gas emissions. While previous studies have examined biodiesel effects on automotive engines, research on marine applications reveals critical gaps: (1) existing studies focus on single-parameter analysis without considering the complex interactions between biodiesel ratio, engine load, and operating conditions; (2) most research lacks comprehensive lifecycle assessment integration with real-time operational data; (3) previous optimization models demonstrate insufficient accuracy (R² < 0.80) for practical marine applications; and (4) no adaptive algorithms exist for dynamic biodiesel ratio adjustment based on operational conditions. These limitations prevent effective biodiesel implementation in maritime operations, necessitating an integrated multi-parameter optimization approach. This study addresses this research gap by proposing an integrated optimization model for fuel efficiency and emissions of marine diesel engines using biodiesel mixtures under diverse operating conditions. Based on extensive experimental data from two representative marine engines (YANMAR 6HAL2-DTN 200 kW and Niigatta Engineering 6L34HX 2471 kW), this research analyzes correlations between biodiesel blend ratios (pure diesel, 20%, 50%, and 100% biodiesel), engine load conditions (10–100%), and operating temperature with nitrogen oxides, carbon dioxide, and carbon monoxide emissions. Multivariate regression models were developed, allowing prediction of emission levels with high accuracy (R² = 0.89–0.94). The models incorporated multiple parameters, including engine characteristics, fuel properties, and ambient conditions, to provide a comprehensive analytical framework. Life cycle assessment (LCA) results show that the B50 biodiesel ratio achieves optimal environmental efficiency, reducing greenhouse gases by 15% compared to B0 while maintaining stable engine performance across operational profiles. An adaptive optimization algorithm for operating conditions is proposed, providing detailed reference charts for ship operators on ideal biodiesel ratios based on load conditions, ambient temperature, and operational priorities in different maritime zones. The findings demonstrate significant potential for emissions reduction in the maritime sector through strategic biodiesel implementation. Full article

The generation of solvated electrons (SEs) from solid-state sources represents a transformative approach to driving challenging reduction reactions under ambient conditions. Diamond, with its almost unique negative electron affinity (NEA) and tunable electronic properties, is emerging as a promising candidate for SE generation in aqueous media. This perspective article reviews the current state of diamond-based SE generators and discusses their potential to catalyze sustainable nitrogen reduction (NRR) to ammonia, carbon dioxide reduction (CO₂RR), and the degradation of persistent environmental pollutants. Emphasis is placed on the fundamental processes enabling SE photoinjection from diamond to water, recent experimental breakthroughs, and the prospects for scalable, green applications. Full article

To better inform the public about ambient air quality and associated health risks and prevent cardiovascular and chronic respiratory diseases in Macau, the local government authorities apply the Air Quality Index (AQI) for air quality management within its jurisdiction. The application of AQI requires first determining the sub-indices for several pollutants, including respirable suspended particulates (PM₁₀), fine suspended particulates (PM_2.5), nitrogen dioxide (NO₂), ozone (O₃), sulfur dioxide (SO₂), and carbon monoxide (CO). Accurate prediction of AQI is crucial in providing early warnings to the public before pollution episodes occur. To improve AQI prediction accuracy, deep learning methods such as artificial neural networks (ANNs) and long short-term memory (LSTM) models were applied to forecast the six pollutants commonly found in the AQI. The data for this study was accessed from the Macau High-Density Residential Air Quality Monitoring Station (AQMS), which is located in an area with high traffic and high population density near a 24 h land border-crossing facility connecting Zhuhai and Macau. The novelty of this work lies in its potential to enhance operational AQI forecasting for Macau. The ANN and LSTM models were run five times, with average pollutant forecasts obtained for each model. Results demonstrated that both models accurately predicted pollutant concentrations of the upcoming 24 h, with PM₁₀ and CO showing the highest predictive accuracy, reflected in high Pearson Correlation Coefficient (PCC) between 0.84 and 0.87 and Kendall’s Tau Coefficient (KTC) between 0.66 and 0.70 values and low Mean Bias (MB) between 0.06 and 0.10, Mean Fractional Bias (MFB) between 0.09 and 0.11, Root Mean Square Error (RMSE) between 0.14 and 0.21, and Mean Absolute Error (MAE) between 0.11 and 0.17. Overall, the LSTM model consistently delivered the highest PCC (0.87) and KTC (0.70) values and the lowest MB (0.06), MFB (0.09), RMSE (0.14), and MAE (0.11) across all six pollutants, with the lowest SD (0.01), indicating greater precision and reliability. As a result, the study concludes that the LSTM model outperforms the ANN model in forecasting air pollutants in Macau, offering a more accurate and consistent prediction tool for local air quality management. Full article

Integrating green spaces into urban designs and planning for ecosystem services has become vital; however, in creating these spaces, the growth phase is often overlooked. This study provides insight into the changing energy and carbon dioxide (CO₂) fluxes in a developing forest, “The Forestias” project in Thailand. The eddy covariance technique was applied to determine real-time surface energies and CO₂ fluxes from December 2021 to September 2023. The results suggest that under fast growing conditions of the green areas, the diurnal latent energy flux corresponded with the area gained. This effect was supported by increasing evapotranspiration through the byproduct of canopy gas exchange. Consequently, the influence of green areas on lowering the average ambient temperature compared with the urban non-green surroundings was observed. In terms of CO₂ flux dynamics, the increasing efficacy of photosynthesis was parallel with the growing forest canopy. Changes in flux dynamics due to urban green areas show their potential as a mitigation tool for moderating ambient air temperatures. Moreover, they can serve as a carbon sink within tropical cities and provide a pivotal contribution in reaching carbon neutrality. Full article

This study explored the innovative foaming behavior of a novel biodegradable polymer blend consisting of polylactic acid/poly(butylene succinate)/poly(butylene adipate-co-terephthalate) (PLA/PBS/PBAT) enhanced with nanohydroxyapatite (nHA), using supercritical carbon dioxide (SCCO₂) as an environmentally friendly physical foaming agent. The aim was to investigate the effects of various foaming strategies on the resulting cell structure, aiming for potential applications in tissue engineering. Eight foaming strategies were examined, starting with a basic saturation process at high temperature and pressure, followed by rapid decompression to ambient conditions, referred to as the (1T-1P) strategy. Intermediate temperature and pressure variations were introduced before the final decompression to evaluate the impact of operating parameters further. These strategies included intermediate-temperature cooling (2T-1P), intermediate-temperature cooling with rapid intermediate decompression (2T-2P), and intermediate-temperature cooling with gradual intermediate decompression (2T-2P, stepwise ΔP). SEM imaging revealed that the (2T-2P, stepwise ΔP) strategy produced a bimodal cell structure featuring small cells ranging from 105 to 164 μm and large cells between 476 and 889 μm. This study demonstrated that cell size was influenced by the regulation of intermediate pressure reduction and the change in intermediate temperature. The results were interpreted based on classical nucleation theory, the gas solubility principle, and the effect of polymer melt strength. Foaming results of average cell size, cell density, expansion ratio, porosity, and opening cell content are reported. The hydrophilicity of various foamed polymer blends was evaluated by measuring the water contact angle. Typical compressive stress–strain curves obtained using DMA showed a consistent trend reflecting the effect of foam stiffness. Full article

The air we breathe contains contaminants such as particulate matter (PM), carbon dioxide (${\mathrm{CO}}_2$), nitrogen dioxide (${\mathrm{NO}}_2$), and nitric oxide (NO), which, when inhaled, bring about several changes in the autonomous responses of our body. Our previous work showed that we can use the human body as a sensor by making use of autonomous responses (or biometrics), such as changes in electrical activity in the brain, measured via electroencephalogram (EEG) and physiological changes, including skin temperature, galvanic skin response (GSR), and blood oxygen saturation (${\mathrm{SpO}}_2$). These biometrics can be used to estimate pollutants, in particularly ${\mathrm{PM}}_1$ and ${\mathrm{CO}}_2$, with high degree of accuracy using machine learning. Our previous work made use of the Welch method (WM) to obtain a power spectral density (PSD) from the time series of EEG data. In this study, we introduce a novel approach for obtaining a PSD from the EEG time series, developed by Astrapi, called the Astrapi Spectrum Analyzer (ASA). The physiological responses of a participant cycling outdoors were measured using a biometric suite, and ambient ${\mathrm{CO}}_2$, ${\mathrm{NO}}_2$, and NO were measured simultaneously. We combined physiological responses with the PSD from the EEG time series using both the WM and the ASA to estimate the inhaled concentrations of ${\mathrm{CO}}_2$, ${\mathrm{NO}}_2$, and NO. This work shows that the PSD obtained from the ASA, when combined with other physiological responses, provides much better results (RMSE = 9.28 ppm in an independent test set) in estimating inhaled ${\mathrm{CO}}_2$ compared to making use of the same physiological responses and the PSD obtained by the WM (RMSE = 17.55 ppm in an independent test set). Small improvements were also seen in the estimation of ${\mathrm{NO}}_2$ and NO when using physiological responses and the PSD from the ASA, which can be further confirmed with a large number of dataset. Full article

This study aims to evaluate the drying performance of a multi-stage solar-assisted heat pump drying system for tomatoes. The method involves theoretical calculations based on the optimal drying process and experimental investigations to assess the impact of different drying temperatures and relative humidity on drying characteristics. The results from the theoretical calculations reveal that the multi-stage solar-assisted heat pump drying system outperforms a single-stage system, particularly under lower ambient temperatures or higher fresh air volumes. In spring/autumn, with 25% fresh air, solar energy accounts for 85.12% of the total energy consumption, achieving a performance coefficient of 39.16, a moisture extraction rate of 40.7 kg/kWh, and energy consumption of 0.02 kWh/kg. Carbon dioxide emissions amount to 10.45 kg/year, with a net reduction of 7.88 kg/year. The experimental results indicate that higher relative humidity increases drying time and reduces the diffusion coefficient, which results in higher material temperatures and greater nutrient loss. The optimal drying process is achieved at 70 °C and 20% relative humidity. In conclusion, the multi-stage solar-assisted heat pump drying system demonstrates superior performance in energy efficiency and sustainability compared to single-stage systems. The optimal drying conditions for tomatoes are identified, and the findings contribute to improving drying processes in food preservation while minimizing environmental impact. Full article

The venting process is one of the most important events during the thermal runaway (TR) of lithium-ion batteries (LIBs) in determining fire accidents, while different ambient pressures will exert an influence on the venting events as well as the TR. Ternary nickel–cobalt–manganese (NCM) batteries with a 75% state of charge (SOC) were employed to conduct TR tests under different ambient pressures in a sealed chamber with dilute oxygen. It was found that elevated ambient pressure results in milder ejections in terms of jet temperature and mass loss. Gas venting characteristics were also obtained. Additionally, the amount of carbon dioxide (CO₂), hydrogen (H₂), methane (CH₄), and ethylene (C₂H₄) released increase with ambient pressure, while carbon monoxide (CO) varies inversely with ambient pressure. The higher the ambient pressure is, the greater the flammability risk is. The molar amount of C, H, O, and total gases released shows a positive correlation with the maximum battery temperature and ambient pressure. This study will support the design of safety valves and help reveal the effects of venting events on the evolution of TR. Full article

Carbon capture and sequestration have been recently presented as a viable option to reduce atmospheric carbon dioxide emissions and mitigate global climate change. The concept entails the capture, compression, transportation, and injection of the gas into a medium suitable for storage. This paper examines the thermodynamic and transport properties of carbon dioxide that are pertinent to its sequestration and storage, describes the various methods that have been recommended for its separation from the mixture of the flue gases, and determines the mechanical power and heat rate required for the capture of the gas. The power required for the compression and transportation of the gas by a pipeline is also determined, as well as the effect of the ambient temperature on the transportation power. Calculations for the total power required are performed for two cases, one a cement production unit and the second a coal power plant. The mechanical power needed for the sequestration of CO₂ is substantial in both cases, with the cement unit needing less power because of the availability of high-temperature waste heat. In both cases, the equivalent mechanical work needed for the sequestration and storage of this gas is on the order of 1 MJ per kg CO₂ sequestered. Full article

Most existing epidemiological studies on the impact of air pollution on noncommunicable diseases have focused on urban areas, rather than nationwide studies that include rural areas. This study utilized a time-stratified case-crossover study that included deaths registered in the National Mortality Surveillance System from 2008 to 2020. Atmospheric particulate matter (PM₁₀ and PM_2.5), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO) were evaluated via the National Nested Air Quality Prediction Modeling System. Conditional logistic regression was used to assess the associations between short-term air pollution exposure and the risk of respiratory disease and cardiovascular disease (CVD) mortality. There were increases in the risk of respiratory diseases (0.12%, 0.10%, 0.10%, 0.05%, and 0.40%) and CVDs (0.08%, 0.07%, 0.03%, 0.02%, and 0.22%) for each 10 μg/m³ increase in the concentrations of PM₁₀, PM_2.5, NO₂, and SO₂, respectively, and for each 1 mg/m³ increase in the concentration of CO, which may be associated with the participants’ characteristics. The results of these national analyses indicate that ambient air pollutants are significantly associated with increased risks of respiratory disease and CVD death in both urban and rural areas, which is critical for air pollution control, especially in low- and middle-income areas. Full article

Devices for assessing the quality of animal environments are important for maintaining production animals, thus improving animal well-being and mitigating pollutant emissions. Therefore, an IoT system was developed and preliminarily assessed across various livestock housing types, including those for pigs, dairy cows, and rabbits. This system measures and transmits key parameters, such as ambient temperature; relative humidity; light intensity; sound pressure; levels of carbon dioxide, ammonia, and hydrogen sulfide; and particulate matter and volatile organic compound concentrations. These data are sent from the sensors to a gateway and then displayed on a dashboard for monitoring. A preliminary evaluation of the system’s performance in controlled conditions revealed that the device’s accuracy and precision were within 2.7% and 3.3% of the measured values, respectively. The system was deployed in three case studies involving rabbit, pig, and dairy cow farms. The results demonstrated its effectiveness in assessing pollutant emissions and identifying critical situations where gas concentrations exceeded threshold levels, thus posing a risk to the animals. By systematically applying this technology on livestock farms to obtain a detailed understanding of the microclimatic and air quality conditions in which the animals live, animal welfare can be significantly improved. Full article