Search Results (1,121)

E/W-band millimeter-wave signals are highly promising for long-distance offshore wireless communications. However, the high humidity over the sea surface, together with the continuous fluctuation of sea waves, gives rise to severe near-sea-surface channel impairments, such as strong atmospheric absorption and sea-surface-induced multipath, which significantly hampers long-range E-band transmission. This work proposes a photonic-assisted E-band millimeter-wave 1 × 2 MIMO communication system and conducts a 26 km near-sea-surface transmission experiment in the coastal area of Lianyungang, Jiangsu Province. A 73.5 GHz 5-Gbaud QPSK signal is transmitted, and spatial diversity reception followed by maximal ratio combining (MRC) is applied. Experimental results show that diversity reception improves system performance by about 4 dB, demonstrating that the proposed photonic-assisted E-band spatial diversity system and signal processing method can significantly extend the transmission distance. Full article

The aim of the present study was to evaluate the association between seasonal variation, the temperature–humidity index (THI), and lipid indices related to human health in the milk of Simmental and Montbéliarde cows. The investigation was conducted on a dairy farm located in Central Southern Bulgaria over a 12-month period and included 100 lactating cows, with equal numbers from each breed, housed in semi-open free-stall barns and fed an unchanged total mixed ration. Monthly measurements of microclimatic parameters (temperature, relative humidity, THI, and air velocity) were conducted throughout the study, and composite milk samples were analyzed for fatty acid composition by gas chromatography. The atherogenic index (AI), thrombogenic index (TI), health-promoting index (HPI), hypo-/hypercholesterolemic index (h/H), desaturase indices (DI16 and DI18), and the UFA/SFA, PUFA/SFA, and MUFA/SFA ratios were calculated based on the fatty acid profile. The results indicate that season has a statistically significant effect on all studied lipid indices (p < 0.001). The Kruskal–Wallis H values ranged from 16.68 for AI to 27.82 for DI18, indicating that seasonal variations in microclimatic conditions significantly influence the lipid metabolism of the cows. The data for the studied lipid indices indicate that the most favorable fat profile for human health was observed in autumn, characterized by lower AI (2.24) and TI (1.26) values and higher HPI (0.45) and h/H (0.76) values. Seasonal variation also affected DI 16 and DI 18, with the most favorable values for humans observed in autumn (DI 16: 4.38; DI 18: 74.39). The ratios of unsaturated to saturated fatty acids (UFA/SFA, PUFA/SFA, and MUFA/SFA) indicate that the milk from the studied farm exhibits the most favorable functional properties in autumn. Full article

A dew-point evaporative air cooler incorporating a novel segmented heat exchange design, demarcated according to the humidity state of moist air, is proposed. The system employs a porous fibrous material to create a wetted evaporative surface, which is continuously maintained in a moistened condition through a self-wicking water supply mechanism to enhance latent heat transfer. Circular fins are installed on the heat exchanger’s partition surface once the moist air reaches saturation, thereby improving sensible heat exchange between the dry and wet channels. The performance of a prototype was evaluated under controlled conditions in a standard enthalpy chamber. Experimental results indicate that, under typical summer conditions (inlet dry-bulb and wet-bulb temperatures of 33.8 °C and 25.4 °C, respectively), with an air mass flow ratio of 0.7 and an air velocity of 1.5 m/s, the wet-bulb effectiveness reaches 114.4% and the dew-point effectiveness achieves 84.8%. The maximum temperature reduction occurs in the sensible heat exchange section, reaching up to 6.1 °C, demonstrating its substantial sensible heat recovery capability. The device exhibits an energy efficiency ratio (EER) ranging from 9.1 to 31.8. The proposed compact configuration not only enhances energy efficiency but also reduces material costs by approximately 15.4%, providing a valuable reference for the future development of dew-point evaporative cooling systems in residential buildings. Full article

Accurate analysis and forecasting of short-term heavy rainfall (hourly rainfall ≥ 20 mm) are crucial for extending warning, enabling targeted preventive measures, and supporting efficient resource allocation. In recent years, machine learning techniques combined with atmospheric physical variables have offered promising new approaches for analyzing and predicting and forecasting short-term heavy rainfall. However, these methods often lack transparency, which hinders the interpretation of key atmospheric physical variables that drive short-term heavy rainfall and their coupling mechanisms. To address this challenge, the present study integrates the interpretable SHAP (SHapley Additive exPlanations) framework with machine learning to examine potential relationships between widely used atmospheric physical variables and short-term heavy rainfall, thereby improving model interpretability. CatBoost models were constructed based on multiple feature-input strategies using 71 physical variables across five categories derived from ERA5 reanalysis data, and their performance was compared with two benchmark algorithms, XGBoost and LightGBM. The SHAP method was subsequently applied to quantify the contributions of individual features and their interaction effects on model predictions. The results indicate that (1) the CatBoost model, utilizing all 71 physical variables, outperforms other feature combinations, with an AUC of 0.933, and F1 score of 0.930, and a Recall of 0.954, significantly higher than the XGBoost and LightGBM models; (2) Shapley value analysis identified 500 hPa vertical velocity, the A-index, and precipitable water as the most influential features on model performance; (3) The predictive mechanism for short-term heavy rainfall is fundamentally bifurcated: negative instances are classified through the discrete main effects of individual features, whereas positive event detection necessitates a sophisticated coordination of intrinsic main effects and synergistic interactions. Among the feature categories, the horizontal and vertical wind fields, stability and energy indices, and humidity-related variables exhibited the highest contribution ratios, with wind field features demonstrating the strongest interaction effects. The results confirm that integrating atmospheric physical variables with the CatBoost ensemble learning approach significantly improves short-term heavy rainfall identification. Furthermore, incorporating the SHAP interpretability framework provides a theoretical foundation for elucidating the mechanisms of feature influence and optimizing model performance. Full article

Afforestation is recognized as a highly effective strategy for enhancing ecosystem carbon sequestration. However, the changes and drivers of soil organic carbon (SOC) following afforestation are still debated due to climate differences. Clarifying these responses is critical for improving the effectiveness of afforestation-based carbon sequestration strategies. In this study, we analyzed nine 20-year-old afforestation sites (coniferous and broad-leaved) along a Chinese climatic gradient to quantify SOC and its fractional changes following farmland-to-forest conversion, and to identify the dominant factors controlling SOC sequestration across climatic gradients and forest types. The results showed that afforestation enhanced SOC (5.1%–210.5%, p < 0.05) in humid and semi-humid regions, but showed no significant effect in semi-arid regions, and it even reduced SOC in arid regions (−19%–−53.8%). Across all climatic zones, mineral-associated organic carbon was the dominant contributor to SOC accumulation throughout the entire soil profile (0–60 cm). Climatic-scale analyses based on the aridity index determined that root and litter C/N ratios were the primary drivers of SOC sequestration in coniferous forests, whereas in broad-leaved forests, they were more strongly controlled by soil physicochemical properties, particularly total nitrogen, bulk density, and soil water content. This study identified that SOC responses to afforestation are strongly mediated by climate and forest type, which is helpful for managers to take targeted measures to increase soil carbon sequestration in forest management. Full article

This follow-up study investigates the long-term environmental sustainability and remediation outcomes of the UPPER (‘Urban Productive Parks for Sustainable Urban Regeneration’-UIA04-252) project in Latina, Italy, focusing on Nature-Based Solutions (NbS) applied to urban green infrastructure. By integrating proximal and satellite-based remote sensing methodologies, the research evaluates persistent improvements in vegetation health, soil moisture dynamics, and overall environmental quality over multiple years. Building upon the initial monitoring framework, this case study incorporates updated data and refined techniques to quantify temporal changes and assess the ecological performance of NbS interventions. In more detail, ground-based data from meteo-climatic, air quality stations and remote satellite data from the Sentinel-2 mission are adopted. Ground-based measurements such as temperature, humidity, radiation, rainfall intensity, PM10 and PM2.5 are carried out to monitor the overall environmental quality. Updated satellite imagery from Sentinel-2 is analyzed using advanced band ratio indices, including the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI) and the Normalized Difference Moisture Index (NDMI). Comparative temporal analysis revealed consistent enhancements in vegetation health, with NDVI values significantly exceeding baseline levels (NDVI 2022–2024: +0.096, p = 0.024), demonstrating successful vegetation establishment with larger gains in green areas (+27.0%) than parking retrofits (+11.4%, p = 0.041). However, concurrent NDWI decline (−0.066, p = 0.063) indicates increased vegetation water stress despite irrigation infrastructure. NDMI improvements (+0.098, p = 0.016) suggest physiological adaptation through stomatal regulation. Principal Component Analysis (PCA) of meteo-climatic variables reveals temperature as the dominant environmental driver (PC2 loadings > 0.8), with municipality-wide NDVI-temperature correlations of r = −0.87. These multi-scale findings validate sustained NbS effectiveness in enhancing vegetation density and ecosystem services, yet simultaneously expose critical water-limitation trade-offs in Mediterranean semi-arid contexts, necessitating adaptive irrigation management and continued monitoring for long-term urban climate resilience. The integrated monitoring approach underscores the critical role of continuous, multi-scale assessment in ensuring long-term success and adaptive management of NbS-based interventions. Full article

This research paper explores the key role of energy analysis in the initial phases of architectural design. The main research question is as follows: How can energy analysis shape and optimize architectural design variables? To address this question, the research paper identifies key architectural design variables, including structural system, roof, window-to-wall ratio (WWR), and building envelope, all of which are influenced by energy efficiency strategies. Through case studies of residential buildings in Bahrain, the research investigates the optimization of these design variables. Energy models are employed to explore the impact of energy analysis on the design and performance of the selected residential buildings. The findings reveal a significant potential for energy reduction in annual consumption through the collective optimization of passive strategies. Furthermore, specific energy reduction for each sole variable is observed, as follows for structural system material (3.63% to 11.29%), roof thermal insulation (0.75% to 3.37%), WWR optimization (0.61% to 1.27%), and building envelope (7.39% to 13.5%). These findings establish energy analysis as a fundamental design approach for initial design phases or selection between design alternatives, and can be generalized to similar arid, humid climates and residential building designs. Full article

Pellets produced from raw or torrefied shredded logging residues have been investigated in the study. The research material came from pine and spruce stands in Poland, Slovakia, Czechia and Hungary. Torrefaction temperatures (T_t) of 250, 300, and 400 °C were applied. Before pressure agglomeration, 3% wheat flour was added to the torrefaction material as a binding agent. Pellets with a diameter of 8 mm were produced at constant humidity, compaction pressure (P) of 140 or 180 MPa and agglomeration temperature (T_a) of 100, 120 or 140 °C. The produced pellets were assessed for their physicomechanical parameters (density, radial compressive strength, compression ratio, modulus of elasticity), chemical parameters (extractive compounds, cellulose, lignin) and energy parameters (ash content, elemental composition, calorific value). The results were subjected to basic statistical analysis and multi-way ANOVA. The produced pellets varied in physical, mechanical, chemical and energy properties. A significant effect of torrefaction temperature, agglomeration temperature and compaction pressure on the results was observed. In terms of physicomechanical parameters, the best pellets were produced from the raw material, while in terms of energy parameters, those produced from the torrefied material were superior. Pellets of satisfactory quality produced from torrefied logging residues could be obtained at T_t = 250 °C, T_a = 120 °C and P = 180 MPa. Pellets with specific density of approximately 1.1 g·cm⁻³, radial compressive strength of 3–3.5 MPa, modulus of elasticity of 60–80 MPa and calorific value of 20.3–23.8 MJ·kg⁻¹ were produced in the process. Full article

To enhance the climate adaptability and diagnostic precision of university sustainability frameworks, this study presents a critical advancement to the PICSOU (Performance Indicators for Core Sustainability Objectives of Universities) framework’s Indoor Environmental Quality (IEQ) module. The research employs a comparative approach across two distinct climate zones: the campus of Chengdu Jincheng College in a humid subtropical climate (CDJCC; Köppen Cwa) with natural ventilation, and the campus of Tallinn University of Technology in a temperate climate (TalTech; Köppen Dfb) with mechanical ventilation. A key innovation at CDJCC was the deployment of a novel, integrated sensor that combines a Frequency-Modulated Continuous Wave (FMCW) radar module for real-time occupancy detection with standard IEQ sensor suite (CO₂, PM_2.5, temperature, humidity), enabling unprecedented analysis of occupant-IEQ dynamics. At TalTech, comprehensive IEQ monitoring was conducted using standard sensors. Results demonstrated that mechanical ventilation (TalTech) effectively decouples indoor conditions from external fluctuations. In contrast, natural ventilation (CDJCC) exhibits strong seasonal coupling, reflected by a Seasonal Ventilation Efficacy Coefficient (${\lambda }_{\mathit{season}}$), indicating that seasonal differences in effective ventilation are present but vary by indoor space type under occupied conditions. Consistent with this stronger indoor–outdoor linkage, PM_2.5 infiltration was also pronounced in naturally ventilated spaces, as evidenced by a high infiltration factor ($I/O$ ratio) that remained consistently elevated. This work conclusively validates a conditional, climate-resilient workflow for PICSOU’s IEQ category, integrating these empirical coefficients to transform its IEQ assessment into a dynamic and actionable tool for optimizing campus sustainability strategies globally. Full article

Resistance against water penetration is one of the key indicators of concrete durability in humid and pressurized environments. An intelligent model based on the XGBoost machine-learning algorithm was developed to predict the water penetration depth, using 1512 independent experimental measurements. The influential variables included water pressure, pressure duration, thermal cycles, fiber content, curing, and compressive strength. The investigated concrete specimens and field-tested structures in this study were exposed to arid and hot climatic conditions, and the proposed model was developed within this environmental context. To accurately simulate the water transport behavior, a cylindrical-chamber test was employed, enabling non-destructive and in-situ evaluation of structures. Correlation analysis revealed that compressive strength had the strongest negative influence (r = −0.598), while free curing exhibited the strongest positive influence (r = +0.654) on penetration depth. After hyperparameter optimization, the XGBoost model achieved the best performance (R² = 0.956, RMSE = 1.08 mm, MAE = 0.81 mm). Feature importance analysis indicated that penetration volume, pressure, and curing were the most significant predictors. According to the partial dependence analysis, both pressure and duration exhibited an approximately linear increase in penetration depth, while a W/C ratio below 0.45 and curing markedly reduced permeability. Microstructural interpretation using MIP, XRD, and SEM tests supported the physical interpretation of the trends identified by the machine-learning model. The results demonstrate that machine-learning-models can serve as fast and accurate tools for assessing durability and predicting permeability under severe environmental conditions. Finally, the permeability of several real structures was evaluated using the machine-learning approach, showing excellent prediction accuracy. Full article

Agrivoltaics integrates photovoltaic (PV) power generation with agricultural practices, enabling dual land-use and mitigating land-use competition between agriculture and energy production. China has 3.43 million hectares of tea fields, offering significant potential for PV-integrated tea plantations (PVtea) to address land scarcity in clean energy development. This study aimed to investigate the impact of PV modules above tea bushes in PVtea on the yield and quality of tea, as well as tea plant resistance to environmental stresses. The PV system uses a single-axis tracking system with a horizontal north–south axis and ±45° tilt. It includes 70 UL-270P-60 polycrystalline solar panels (270 Wp each), arranged in 5 columns of 14 panels, spaced 4500 mm apart, covering 280 m². The panels are mounted 2400 mm above the ground, with a total capacity of 18.90 kWp (656 kWp/ha). Tea yield, quality-related components, leaf photosystem II (PSII) activity, and plant resistance to environmental stresses were investigated in comparison to an adjacent open-field tea plantation (control). The mean photosynthetic active radiation (PAR) reaching the plucking table of PVtea was 52.9% of the control, with 32.0% of the control on a sunny day and 49.0% on a cloudy day, accompanied by an increase in ambient relative humidity. These changes alleviated the midday depression of leaf PSII activity caused by high light, resulting in a 9.3–15.3% increase in leaf yield. Moreover, PVtea summer tea exhibited higher levels of amino acids and total catechins, resulting in tea quality improvement. Additionally, PVtea enhanced the resistance of tea plants to frost damage in spring and heat stress in summer. PVtea integrates photovoltaic power generation with tea cultivation practices, which not only facilitates clean energy production—an average annual generation of 697,878.5 kWh per hectare—but also increases tea productivity by 9.3–15.3% and the land-use equivalence ratio (LER) by 70%. Full article

This study examines the performance of a proton exchange membrane fuel cell operated in electrochemical hydrogen compression (EHC) mode, focusing on the effects of temperature, relative humidity (RH), and pressure on water management and efficiency. Two humidification strategies were investigated: (i) a dry cathode with humidified anode hydrogen and (ii) a flooded cathode with controlled anode humidification. Experiments were conducted at different temperatures (from 35 to 70 °C), RH levels (from 0 to 100%), and compression ratios of 1 and 2, using polarization curves, electrochemical impedance spectroscopy, and linear sweep voltammetry (LSV). In the dry cathode configuration, optimal performance occurred at 70 °C with fully humidified anode gas, achieving current densities above 2 A cm⁻² at voltages below 0.3 V. Partial humidification caused instability due to membrane dehydration. In the flooded cathode, high cathode pressure increased mass transport resistance, while excessive inlet humidification promoted flooding and consequently reduced the efficiency. LSV results highlighted the trade-off between proton conductivity and hydrogen back diffusion, particularly for thin membranes used in this study. The findings demonstrate that precise water balance is essential for stable and efficient EHC operation and provide guidelines for optimizing compression performance, supporting the development of high-efficiency and low-maintenance hydrogen compression systems for stationary and mobile applications. Full article

Energy efficiency in hospitals—where continuous operation with high internal gains and strict comfort needs—demands facade strategies tailored to climate. This study quantifies how the window-to-wall ratio (WWR) distribution and city-specific envelope properties affect the annual heating and cooling loads of a four-story, 3000 m² hospital in Turkey. Energy simulations were conducted using DesignBuilder (2021) with EnergyPlus under a controlled modeling framework, following ASHRAE healthcare guidelines for internal loads and TS 825:2024 for envelope compliance. Three locations were selected to span national variability: Bursa (Marmara—temperate/transition), Mersin (Mediterranean—hot–humid), and Kars (humid continental—cold). Scenario 1 (S1) assigned a graduated WWR on the south facade by floor—20%, 30%, 40%, and 50% from ground to top—while the north, east, and west facades were held at 20%, 30%, and 20%. Scenario 2 (S2) preserved the same geometry and WWR values but applied the graduated WWR to the north facade instead, keeping the south at 20%, east at 30%, and west at 20%. Within each city, opaque and glazing properties were kept constant across scenarios to isolate WWR–orientation effects. For every city–scenario combination, annual space-heating and space-cooling loads were computed, and window heat gains and losses were analyzed on the facade with variable WWR to support interpretation of performance mechanisms. The results indicate that S2 outperforms S1 in Mersin, S1 outperforms S2 in Kars, and S2 offers a moderate advantage in Bursa. Full article

In response to new and emerging challenges in animal transport, including more stringent biosecurity and public demand for enhanced animal welfare, an innovative prototype trailer with mechanical ventilation and air filtration systems was developed. The performance of the trailer in maintaining acceptable environmental conditions for the pigs during transport in both cold and warm weather was evaluated through a series of road tests. In these tests, the general welfare of the animals during transport was also assessed. Results showed that temperatures inside the animal compartment during cold ambient conditions were above 10 °C for more than 60 to 90% of the trip despite the frequent occurrence of cold temperatures (below 0 °C) at the inlet. On the other hand, the temperature in the animal compartment ranged from 16 to 19.4 °C most of the time during transport in warm weather. The average moisture levels in the animal compartment ranged from 4.15 to 6.3 g/kg dry air and 5.05 to 78.8 g/kg dry air during cold and warm transport conditions, respectively, which is comparable to the humidity ratios measured in conventional pig transport trailers. Carbon dioxide concentration inside the animal compartment ranged from 912 to 1192 ppm in cold conditions and from 1008 to 1414 ppm in warm weather, indicating good air quality in the trailer during transport. Furthermore, there was no significant change in the levels of blood cortisol and in the rectal and body temperatures of pigs measured at the start and end of each monitoring trip, indicating that the pigs showed reduced or minimal stress during transport. The study demonstrated that the trailer design with a mechanical ventilation system significantly improved the thermal comfort and environmental conditions for pigs, contributing to their welfare during transport. Full article

The microclimate of traditional blocks, a key component of urban fabric, directly affects the overall urban thermal environment. Creating a suitable microclimate is crucial for improving urban living quality. Field measurements, ENVI-met simulations, and the PET index were used to analyze the spatiotemporal variations and core drivers of thermal comfort. Temporally, five open space types showed a unimodal “rise–stabilization–fall” PET curve, with peak heat stress occurring at 11:00–14:00. Courtyards heated fastest, but green spaces had the most stable thermal environment because trees provided shading and transpiration for gentle cooling. Spatially, thermal comfort varied significantly. For example, green spaces rich in trees performed best (PET 5–8 °C lower than pure grassland), while squares and courtyards faced severe midday heat stress (PET mostly moderate or above). Alley comfort depended on aspect ratio and orientation—north–south alleys with an aspect ratio > 2 were 2–3 °C cooler than open spaces, but east–west or narrower alleys (aspect ratio < 1.5) and low-enclosed courtyard control apply to southern Hunan’s hot-humid zone. However, the synergistic principles can be extended to similar southern regions, providing technical reference for traditional block livability and climate-resilient cities. Full article