Search Results (2,833)

Rapid human population growth accelerates biodiversity loss through urban habitat fragmentation, yet ecologically informed urban planning can mitigate these effects. This study evaluates whether and how vegetation characteristics, as captured by Earth observation data varies across forest habitats in a small Mediterranean city in Italy. The Normalized Difference Vegetation Index (NDVI), the Normalized Difference Moisture Index (NDMI), and Land Surface Temperature (LST) for the Functional Urban Area of Campobasso were derived from multitemporal Landsat 8 imagery (2020–2023) acquired during the growing season and combined with elevation data to account for topographic gradients. Different forest habitats were identified using the regional coeval Carta della Natura (Map of Nature) and were sampled by a random stratified strategy yielding more than 900,000 observations. A linear mixed-effects model was used to model NDVI as a function of NDMI, LST, elevation, and habitat type, while accounting for temporal and spatial dependencies. The model explained a large proportion of NDVI variability (marginal R² = 0.75; conditional R² = 0.85), with NDMI emerging as the strongest predictor, followed by weaker effects of LST and elevation. Habitat differences were also evident: oak-dominated forests (i.e., Quercus frainetto, Q. cerris, and Q. pubescens dominated habitats) exhibited the highest NDVI values, while coniferous plantations (i.e., Pinus nigra dominated habitat) had the lowest; forests dominated by Robinia pseudoacacia and riparian Salix alba showed intermediate vegetation greenness values. These results highlight the ecological importance of oak forests in Mediterranean urban landscapes and demonstrate the value of satellite-based monitoring for capturing habitat variability. The reproducible workflow applied here provides a scalable tool to support habitat conservation and planning in urban environments, also accounting for impending climate change scenarios. Full article

This paper is dedicated to investigating how short-term indoor temperature drift influences occupants’ thermal sensation in residential nZEB buildings and how this affects the applicability of steady-state comfort prediction. Residential buildings frequently operate under transient conditions, where the classical PMV approach may deviate from reported sensation. The objective of this paper is to evaluate the agreement between steady-state PMV and occupants’ thermal sensation votes under winter conditions to test a regression-based correction index A_eff and an adjusted indicator PMV_adj while preserving the PMV concept. The study uses high-resolution measurements of indoor air temperature and mean radiant temperature synchronised with TSV responses, followed by statistical evaluation using error metrics and correlation analysis. The results show that baseline PMV correlates well with TSV but exhibits a consistent magnitude mismatch under transient conditions. The proposed PMV_adj reduces this mismatch, decreasing NRMSE from 17.61% to 14.00% and slightly improving agreement with Pearson r = 82.18%, R² = 67.54%. Regression analysis shows that A_eff is strongly associated with the indoor air temperature drift rate ΔT_in/Δt with R² = 0.6805, but has a weaker relationship with ΔT_MRT/Δt, R² = 0.1851. The research provides a practical basis for improving PMV-based comfort assessment during winter operation in residential nZEB. Full article

Quality regulation of extruded expanded foods represents a critical technological challenge in this field. Current research has predominantly focused on the impact of extrusion processing parameters, largely overlooking the regulatory role of die structure. This study presents an integrated “CFD + Extrusion Process” methodology to systematically explore the effects of die design and process conditions on expanded product quality. Computational fluid dynamics (CFD) simulations evaluated the influence of nozzle number (12–15) and L/D ratio (1.25–2.5) on flow uniformity, the CFD results identified an optimal die configuration of 14 nozzles with L/D = 1.25, which minimized flow variance (velocity variance: 1.09 × 10⁻⁵ (m/s)²; viscosity variance: 2.777 (Pa·s)²) and established a stable flow foundation. Building on this, the RSM-based experiments revealed how process parameters specifically fine-tune quality attributes: screw speed and moisture content significantly (p < 0.05) affected Water Absorption Index (WAI) and Water Solubility Index (WSI), whereas moisture and temperature were the dominant factors (p < 0.05) governing bulk density and starch gelatinization. The findings of this study can provide a theoretical reference for the precise control of the quality of expanded food products. Full article

Binary mixtures of HFE-73DE and ethyl acetate are investigated as dielectric working fluids for laminar minichannel cooling. Thermophysical properties of the pure components and four mixtures (10/90, 25/75, 50/50 and 75/25 mass % HFE-73DE/ethyl acetate) were measured over the relevant temperature range. Single-phase convective heat transfer tests were then carried out in a heated 1 × 4 × 180 mm minichannel test section under constant heat-flux conditions for pure HFE-73DE. A three-dimensional conjugate CFD model with temperature-dependent liquid properties was developed in Simcenter STAR-CCM+ and validated against these measurements; the average relative temperature difference between CFD and experiment remained below 0.5%, while a grid-convergence study based on the Grid Convergence Index (GCI) confirmed that the numerical uncertainty is comparable to the experimental one. The validated model was subsequently used to predict the axial evolution of wall temperature, fluid-core temperature, velocity and heat transfer coefficient for the four mixtures under identical conditions. The mean Nusselt numbers obtained from CFD were further compared with the classical Shah and London fully developed laminar solution for rectangular ducts, revealing that the present configuration yields values about 35–42% higher than the theoretical prediction owing to asymmetric heating and conjugate heat transfer. The results show that increasing the HFE-73DE mass fraction strengthens convective heat transfer and reduces fluid-temperature rise, while intermediate compositions (50/50 and 75/25) provide a favourable compromise between enhanced heat transfer performance and moderate pressure drop. The study provides guidance for composition selection and the design of dielectric minichannel heat exchangers operating with HFE-73DE/ethyl acetate mixtures. Full article

Urban heat waves are intensifying under climate change, posing growing public health risks, particularly in rapidly urbanizing cities. Green infrastructure is widely promoted as a nature-based solution for heat mitigation, yet its health benefits may vary across urban contexts. This study examines how neighborhood-level green infrastructure modifies heat-related health risks in Tabriz, Iran—a historically cold city experiencing increasing heat stress. The Normalized Difference Vegetation Index (NDVI) was derived from Landsat 8 imagery for 190 neighborhoods and classified into quartiles. Heat waves were defined as two or more consecutive days with mean temperatures at or above the 95th percentile. Emergency department visits for cardiovascular, respiratory, and all-cause conditions (2018–2020) were analyzed using Distributed Lag Non-linear Models with quasi-Poisson regression. Neighborhoods with low-to-moderate greenness (second and third NDVI quartiles) consistently exhibited lower relative risks of heat-related cardiovascular and all-cause visits, while both the lowest and highest NDVI quartiles showed elevated risk estimates. Risk patterns varied by lag period and demographic subgroup, with higher vulnerability observed among males and younger adults in highly vegetated areas, though estimates were imprecise. These findings suggest a non-linear relationship between urban greenness and heat-related health risks. Moderate green infrastructure appears most protective, underscoring the importance of context-sensitive and equitable greening strategies for climate adaptation in heat-vulnerable cities. Full article

The increasing threat of Glacial Lake Outburst Floods (GLOFs), intensified by climate change, underscores the urgency for developing advanced early warning systems. The near-annual, cyclical outbursts of Lake Merzbacher in the Tien Shan mountains present a severe downstream threat, yet its remote location and lack of instrumentation pose a significant challenge to traditional monitoring. To bridge this gap, we develop and validate a dynamic risk assessment framework driven entirely by remote sensing data. Methodologically, the framework introduces an innovative Ice-Water Composite Index (IWCI) to resolve the challenge of lake area extraction under mixed ice-water conditions. This is coupled with a high-fidelity 5 m resolution Digital Elevation Model (DEM) of the lake basin, autonomously generated from GF-7 Dual-Line Camera (DLC) imagery, which enables accurate daily volume retrieval. Through systematic feature engineering, nine key hydro-thermal drivers are quantified from MODIS and other products to train a Random Forest (RF) machine learning model, establishing the non-linear relationship between catchment processes and lake volume. The model demonstrates robust predictive performance on an independent validation set (2023–2024) (R² = 0.80, RMSE = 5.15 × 10⁶ m³), accurately captures the complete lake-filling cycle from initiation to near-peak stage. Furthermore, feature importance analysis quantitatively confirms that Positive Accumulated Temperature (PAT) is the dominant physical mechanism governing the lake’s storage dynamics. This end-to-end framework offers a transferable paradigm for GLOF hazard management, enabling a critical shift from static, regional assessments to dynamic, site-specific early warning in data-scarce alpine regions. Full article

Weather change, as a physical risk factor of climate change, increasingly impacts the energy market. This paper investigates China’s major energy futures using a QVAR framework to analyze spillover effects under different market conditions, addressing mean-model limitations. It also reveals state-dependent weather impacts on spillovers, providing physical climate risk evidence. The results show the following: (1) Spillover effects intensify under extreme conditions, with crude oil and fuel oil as main transmitters, and methanol and coking coal as key recipients. Coking coal shows a stronger spillover absorption capacity under extreme conditions. (2) The Total Spillover Index (TSI) displays significant time-varying feature and sensitivity to external shocks, with heightened asymmetry and complexity in extreme markets. (3) Weather change significantly affects spillovers of China’s energy futures, with temperature, cooling and heating loads, and precipitation showing different impacts on TSI across market conditions. These findings provide references for energy finance regulation and risk early warning under climate change conditions. Full article

The present work adopts a cooled cooling air (CCA) technology based on the integrated aircraft/engine thermal management concept, by coupling an air-kerosene heat exchanger with a high-temperature combustor. Using the heat exchanger, kerosene is preheated to near-critical and supercritical conditions, and the combustion characteristics of kerosene at ambient, near-critical, and supercritical states were investigated. The combustion performance tests were carried out in a model combustor under varying fuel-to-air ratios (FARs) and different kerosene injection conditions. The experimental results show that when the combustor’s FAR is increased to 0.055, the supercritical kerosene exhibits significant advantages over kerosene of the ambient state. The comparison of the combustion performance parameters shows that the combustor outlet temperature distribution factor (OTDF) and radial temperature distribution factor (RTDF) decrease by 52.26% and 51.07%, respectively; in terms of the pollutant emissions, the CO emission index (EI_CO) and unburned hydrocarbon emission index (EI_UHC) are reduced by 66.63% and 68.33%, respectively, while the NOx emission index (EI_NOx) increases by 76.26%, and the combustion efficiency improves by 2.0%. It is noteworthy that once the kerosene reaches the supercritical state, the threshold for the optimal FAR in the combustor rises to 0.055, which carries the significant engineering value for enhancing an aero-engine combustor’s operability across variable conditions and its low-emission combustion performance. Full article

This study investigates the influence of scattered (irregular) and grid (regular) settlement layouts on local climate and thermal comfort versus rural open areas. Research in Erzurum, Türkiye, utilized 2022 year-round on-site measurements, satellite imagery, and statistical analysis of climatic parameters and the Physiologically Equivalent Temperature (PET) thermal comfort index. Findings reveal distinct climatic responses: scattered urban forms consistently created cooler conditions year-round, exhibiting a winter cold island effect (−1.8 °C in December) and lower summer air temperatures (−3.4 °C in July). According to land surface temperature (LST) results, the grid urban form (−12.1 °C) is 0.9 °C colder than the scattered urban form (−11.2 °C) in winter. The scattered urban form (27.9 °C) is 1.5 °C warmer than the grid urban form (26.4 °C) in summer. The grid urban form exhibits a wind velocity range from 0.2 m/s to 1.2 m/s, and the scattered urban form’s wind velocity ranges from 0.0 m/s to 0.5 m/s. On the other hand, PET analysis indicated scattered forms offered more favorable thermal comfort. Average PET for scattered forms was 16.6 °C in summer and −3.3 °C in winter, compared to grid forms’ 15.1 °C and −4.7 °C, respectively. Wind velocity was a primary determinant, with lower speeds reducing heat loss and improving comfort in cold regions. This highlights urban planning’s critical role in optimizing thermal comfort across climates. Full article

In recent decades, forest fires have become one of the most disruptive and complex natural hazards from both environmental and territorial perspectives. The Canary Islands represent a particularly suitable setting for analysing wildfire risk. This study aims to characterise the Large Forest Fires (LFFs) that occurred across the archipelago between 2012 and 2024 through an integrative approach combining geospatial, meteorological, and socio-environmental information. A total of 13 LFFs were identified in Tenerife, Gran Canaria, La Palma, and La Gomera, affecting 55,167 hectares—equivalent to 7.4% of the islands’ total land area. The results indicate a temporal concentration during the summer months and an altitudinal range between 750 and 1500 m, corresponding to transitional zones between laurel forest and Canary pine woodland. Meteorological conditions showed average temperatures of 24.3 °C, minimum relative humidity of 23.7%, and thermal inversion layers at around 270 m a.s.l., creating an environment conducive to fire spread. Approximately 81% of the affected area lies within protected natural spaces, highlighting a high level of ecological vulnerability. Analysis of the Normalized Burn Ratio (NBR) index reveals a growing trend in fire severity, while social impacts include the evacuation of more than 43,000 people. These findings underscore the urgency of moving towards proactive territorial management that integrates prevention, ecological restoration, and climate change adaptation as fundamental pillars of any disaster risk reduction strategy. Full article

The effects of extreme heat events on Surface Urban Heat Island Intensity (SUHII) were investigated in Lecce (southern Italy) during the summer months (June–August) from 2018 to 2025. The analysis began with the identification of heatwave frequency, duration, and intensity using the Warm Spell Duration Index (WSDI), based on a homogenized long-term temperature record, which indicated a progressive increase in persistent extreme events in recent years. High-resolution ECOSTRESS land surface temperature (LST) data were then processed and combined with CORINE Land Cover (CLC) information to examine the thermal response of different urban fabrics, compact residential areas, continuous/discontinuous urban fabric, and industrial–commercial zones. SUHII was derived from each ECOSTRESS acquisition and evaluated across multiple diurnal intervals to assess temporal variability under both normal and WSDI conditions. The results show a consistent diurnal asymmetry: daytime SUHII becomes more negative during WSDI periods, reflecting enhanced rural warming under dry and highly irradiated conditions, despite overall higher absolute LST during heatwaves, whereas nighttime SUHII intensifies, particularly in dense urban areas where higher thermal inertia promotes persistent heat retention. Statistical analyses confirm significant differences between normal and extreme conditions across all classes and time intervals. These findings demonstrate that extreme heat events alter the urban–rural thermal contrast by amplifying nighttime heat accumulation and reinforcing daytime negative SUHII values. The integration of WSDI-derived heatwave characterization with multi-year ECOSTRESS observations highlights the increasing thermal vulnerability of compact urban environments under intensifying summer extremes. Full article

Climate change is expected to increasingly intensify the water stress that directly impacts crop productivity in the near future. This study integrates the crop water stress index (CWSI) with high-resolution regional climate simulations produced by the weather research and forecasting (WRF) model to evaluate water stress that winter wheat and olive trees will potentially experience in Greece in the future. Decadal, high-resolution climate simulations were generated for both the present and near-future periods using the most recent shared socioeconomic pathways (SSP) framework. A bias-corrected dataset based on 18 models from the Coupled Model Intercomparison Project 6 was used for boundary conditions to mitigate errors associated with individual global model biases. Projections indicated a mean air temperature increase of 1.1–1.7 °C and a relative humidity decrease of up to 3.5%. Mean CWSI increases of up to 6% and 4% were projected in most of the country for winter wheat and olive trees, respectively. The water stress of the winter wheat was also assessed over the three growing stages defined by the FAO. The analysis showed that water stress may occur during all growing stages, inducing potential impacts on tillering, photosynthetic efficiency, biomass accumulation, or yield. Additionally, a water stress threshold (i.e., CWSI > 0.5) was applied for both species in order to carry out a spatial assessment of the water stress that is projected to occur in the future in key winter wheat-, olive oil- and table olive-producing Greek regions. The findings of this study can support the irrigation scheduling and the development of climate-resilient agricultural practices in Greece. The modeling framework that was established in this study can also be applied to other crops and regions in the Mediterranean. Full article

Mountain forests play a key role in buffering local climate, yet their climate sensitivity is seldom mapped in a way that is directly usable for spatial planning. This study investigates how phenological thermal and vegetation variability are organized within the forested landscape of Namyangju, a mountainous region in central Korea, and derives spatial indicators of forest climate sensitivity. Using monthly, cloud-screened Landsat-8/9 land surface temperature (LST) and normalized difference vegetation index (NDVI) images over a recent multi-year period, we calculated phenological coefficients of variation for 34,123 forest grid cells and applied local clustering analysis to identify belts of high and low variability. Forest areas where LST and NDVI variability simultaneously occupied the upper tail of their distributions (top 5%/10%/20%) were interpreted as climate-sensitivity hotspots, whereas co-located coldspots were treated as microclimatic refugia. Across the mountainous terrain, sensitivity hotspots formed continuous belts along high-elevation ridges and steep, dissected slopes, while coldspots were concentrated in sheltered valley floors. Notably, the most sensitive belts were dominated by high-elevation conifer stands, despite the limited seasonal fluctuation typically expected in evergreen canopies. This pattern suggests that elevation strongly amplifies the coupling between thermal responsiveness and vegetation health, whereas valley-bottom forests act as stabilizers that maintain comparatively constant microclimatic and phenological conditions. We refer to these patterns as “forest climate-sensitivity belts,” which translate satellite observations into spatially explicit information on where climate-buffering functions are most vulnerable or resilient. Incorporating climate-sensitivity belts into forest plans and adaptation strategies can guide elevation-aware species selection in new afforestation, targeted restoration and fuel-load management in upland sensitivity zones, and the protection of valley refugia that support biodiversity, thermal buffering, and hydrological regulation. Because the framework relies on standard satellite products and transparent calculations, it can be updated as new imagery becomes available and transferred to other seasonal, mountainous regions, providing a practical basis for climate-resilient forest planning. Full article

The sensitivity of model outputs to parameter variations is crucial for effective model calibration and application. This study assessed the sensitivity of N₂O and CH₄ emissions to varying weather conditions and fertilization practices in a winter wheat–rice cropping system. Using the Sobol first-order sensitivity index within the SPACSYS model, key parameters and input variables influencing gas emissions were identified. The results showed that the index effectively detected highly sensitive parameters, particularly those related to soil water content, oxygen dynamics and microbial processes. Both N₂O and CH₄ emissions were sensitive to carbon availability and soil oxygen levels. For N₂O emissions, microbial process parameters and soil water content had substantial impacts, whereas CH₄ emissions were more responsive to methane consumption, oxygen levels, and carbon substrates. Fertilization, rainfall and temperature showed high sensitivity for N₂O emissions, while temperature emerged as the dominant factor controlling CH₄ emissions. The identified parameters offer valuable insights for improving model performance and informing strategies to mitigate greenhouse gas emissions. Full article

The increasing demand for sustainable food requires the development of raw materials and products that provide not only high-quality proteins but also valuable lipids. The aim of this study was to compare the lipid quality of insect powders with that of selected cereal flours (millet, oat, and rice) during four months of storage at room temperature. To simulate increased oxidative conditions, the packages were filled only halfway, thereby increasing oxygen availability. Lipids were extracted using the Bligh–Dyer method, and their oxidation status was assessed based on peroxide value (PV), p-anisidine value (p-AsV), and the total oxidation (Totox) index. Fatty acid composition, antioxidant activity, and oxidative stability were determined using differential scanning calorimetry (DSC). Directly after purchase, none of the analyzed flours or insect powders exceeded a PV of 10 meq O₂/kg lipids or a p-AsV of 20. After four months of storage, lipid oxidation increased in all samples, with changes ranging from 4.6% to 30%, depending on the parameter analyzed. Lipids extracted from insect powders consistently showed significantly higher oxidation levels than those from cereal flours. The proportion of PUFAs in the lipids of the flours ranged from 36.40% to 64.21%, whereas in insect powders it ranged from 30.01% to 37.29%. After storage, only minor changes in PUFA content were observed, and these did not indicate advanced destructive oxidative degradation. Overall, the lipids present in the analyzed flours demonstrated favorable nutritional quality indices, including AI (0.10–0.48), h/H (2.23–10.47), and TI (0.22–1.14). The results indicate that insect powders can serve as a valuable source of fatty acids; however, their susceptibility to lipid oxidation necessitates careful consideration during processing and storage. Full article