Search Results (63,207)

Urban wetlands and agricultural lands are among the most important socio-ecological systems in urban areas. They support food production, biodiversity conservation, water regulation, climate resilience, and human well-being. However, rapid urbanization negatively affects wetland–agricultural coexistence (WAC) by destroying habitats, fragmenting landscapes, and intensifying land-use conflicts. Our study proposed a Wetland–Agriculture Coexistence Index (WACI) to assess the spatial pattern of WAC in Colombo, Sri Lanka. We considered four components for the WACI framework: wetland condition (WC), agricultural condition (AC), urban pressure (UP), and hydrological connectivity (HC). The WACI was developed using Landsat 8/9, Sentinel-1 Synthetic Aperture Radar (SAR), and Advanced Land Observing Satellite (ALOS) data, along with road network, population, and hydrological network data. Variables used in this study include land surface temperature (LST), Enhanced Vegetation Index (EVI), Modified Soil-Adjusted Vegetation Index (MSAVI), Bare Soil Index (BSI), soil moisture, elevation, slope, population density, distance to roads, hydrological connectivity, and built-up %, which were normalized and integrated into four dimensions using an equal-weighted approach to develop the WACI. The results showed substantial spatial heterogeneity in WAC across Colombo. The average WACI was 0.51, indicating a moderate WAC. This study further identified that favorable environmental conditions, rich hydrological connectivity, and low urban pressure increased coexistence potentials. The spatial pattern of WACI identified priority areas for conservation, restoration, and sustainable urban planning implications in Colombo. Our WACI framework provides a practical and transferable method for assessing WAC in urban areas. The findings of this study support balanced urban wetland–agricultural management, conservation, food security, and long-term sustainability of rapidly urbanizing cities. Full article

High-quality WC-Co composite powder is the prerequisite for achieving cemented carbides with superior mechanical properties. However, achieving homogeneous Co distribution on WC particles remains challenging due to the limited surface activity of WC and the high cost associated with noble-metal activation methods. Therefore, this study employed an electroless plating method based on non-noble-metal activation to prepare Co- coated WC composite powders and to clarify the effects of plating parameters on coating behavior, microstructure evolution, and mechanical properties of WC-Co cemented carbides. Results indicate that when plated with a lower reducing-agent concentration (15 g/L) or a lower temperature (70 °C), insufficient Co coating causes poor fracture toughness of the cemented carbides. Increasing the reducing-agent concentration to 25 g/L or the plating temperature to 80 °C promotes a more uniform Co distribution on WC particles, which suppresses WC grain coalescence during sintering. Under the optimized reducing-agent concentration of 25 g/L, the obtained WC-Co cemented carbide exhibits a homogeneous microstructure with an average WC grain size of 0.91 μm, a Vickers hardness of 2054.5 HV30, and a fracture toughness of 11.39 MPa·m^1/2. Excessive reducing-agent concentration or plating temperature deteriorates the Co coating uniformity, promoting Co aggregation and grain coarsening of the cemented carbides. This work demonstrates that precise control of electroless plating parameters enables the fabrication of high-quality WC-Co composite powders, providing a practical route for tailoring microstructure and optimizing mechanical performance of the cemented carbides. Full article

This study numerically investigates the capability of cylindrical phase change material (PCM) encapsulations to attenuate inlet-temperature fluctuations in water as the heat transfer fluid (HTF). A sinusoidal inlet profile with a 20 K amplitude is imposed, and melting and solidification are modeled using the enthalpy–porosity method. The analysis begins with a single encapsulation, which reduces the outlet temperature amplitude by 45.06%, and extends to three, nine, and 15 cylinders in aligned and staggered arrangements. Increasing the cylinder count enhances fluctuation reduction but with diminishing returns, as the HTF thermal energy reaching downstream cylinders decreases. Spatial arrangement is equally important: a staggered array of nine encapsulations achieves a 65.91% reduction, surpassing a 15-cylinder aligned configuration (65.80%), while the highest reduction, 73.01%, is obtained with a 15-cylinder staggered configuration. Across all configurations, the outlet fluctuation reduction follows a single near-linear relationship with the total melted PCM mass (R² = 0.96), across cylinder count and arrangement, identifying melted mass as a controlling parameter for fluctuation mitigation rather than the cylinder-averaged liquid fraction. These results indicate that the total melted PCM mass is a practical criterion for comparing PCM encapsulation configurations, while the arrangement remains a distinct factor. Full article

Pre-exercise internal cooling through cold-water-induced hyperhydration may attenuate increases in core body temperature (T_C) and improve endurance performance. Quantifying the extent of reduction in T_C induced by hyperhydration is important for optimizing its timing before exercise. We compared T_C values obtained from a wearable sensor, the CORE, with those of a gastrointestinal temperature telemetric sensor (G_TS) during hyperhydration. Eleven participants (two women; age: 24 ± 4 yrs) completed a 120 min seated period where they consumed, over the first 60 min, four boluses of 4 °C water (7.5 mL · kg fat-free mass [FFM]⁻¹), each containing 0.35 g · kg FFM⁻¹ of glycerol. Measures of T_C were taken every 20 min with both sensors. According to the G_TS, hyperhydration induced a peak T_C decline of −0.76 ± 0.31 °C at min 60; at this time, the change in T_C from baseline estimated by the CORE was −0.09 °C ± 0.20 °C. The greatest decline in T_C detected by the CORE was −0.11 ± 0.19 °C. Bland and Altman analyses revealed that average T_C declines of –0.1, −0.2, −0.3, −0.4, −0.5 and −0.6 °C from baseline were associated with T_C values estimated by the CORE that were respectively +0.29, +0.41, +0.57, +0.65, +0.77 and +0.89 °C higher than the G_TS. An intraclass correlation coefficient of 0.12 suggested poor agreement between instruments. These results raise concerns about the ability of the CORE to detect changes in T_C induced by a hyperhydration protocol generating a substantial heat sink. Full article

Mass concentrations of particulate matter are a fundamental metric for air quality and health impact assessment; however, they are insufficient for accurately characterizing exposure. They do not capture particle size distribution or number concentration. Therefore, aerosol assessment should include particle number concentration (PNC), which better represents toxicologically relevant fractions and enables more precise source identification. The aim of this study was to conduct a comprehensive evaluation of particle number concentration (PNC) measurements in the 0.3–10 µm size range obtained using three low-cost Sensirion SPS30 particle sensors under field conditions in an urban environment. The analyses included an assessment of agreement between the SPS30 sensors, an evaluation of their measurement performance against the OPS 3330 optical particle spectrometer, and the development of calibration models. The SPS30 sensors showed high inter-device repeatability for PNC in the 0.3–1.0 µm range (CV_d < 2%). However, measurement performance declined with increasing particle size, with the index of agreement (IOA) decreasing from 0.8 (0.3–0.5 µm) to −0.5 (2.5–10 µm). Sensor accuracy was influenced by meteorological conditions: relative humidity primarily affected short-term variability (precision and dynamic agreement), while temperature controlled systematic bias. Although incorporating these variables into advanced calibration models improved performance, SPS30 sensors remained unsuitable for PNC measurements in the 2.5–10 µm range, exhibiting systematic errors of ~25% even after nonlinear correction. The findings support the responsible use of low-cost particle sensors for supplementary air quality monitoring, contributing to accessible environmental data and sustainable urban air quality management. Full article

Wildlife-vehicle collisions (WVCs) represent an important ecological and road-safety problem, yet the influence of short-term meteorological variability on their occurrence remains insufficiently understood. This study investigated the associations between temperature extremes, abrupt temperature changes, and broader hydro-meteorological conditions and reported WVC frequency in Serbia over a 10-year period (2016–2025). A municipality-day dataset comprising 6281 police-reported WVCs was analyzed using an event-based methodology. Exploratory analyses were complemented by Poisson regression models to evaluate prolonged temperature episodes, abrupt temperature shocks, and broader hydro-meteorological conditions, while additional regional analyses examined the consistency of the observed associations across Serbia. The results demonstrated pronounced seasonal variation, with the highest reported WVC frequencies occurring during spring and late autumn. At the national level, prolonged cold episodes were associated with significantly lower reported WVC frequencies during their onset and middle phases, whereas heat episodes showed no significant associations. Abrupt cool-down shocks were associated with a short-term increase in reported WVC frequency on the day of the temperature decrease, while warm-up shocks showed no significant effects. Moderate and heavy precipitation, snow-day conditions, and prolonged dry spells were associated with reduced reported WVC frequency, whereas daily mean temperature and atmospheric pressure were not independently associated with reported WVC frequency. Regional analyses generally supported the national findings, although no regional associations remained statistically significant after false discovery rate correction. These findings demonstrate that short-term meteorological variability is associated with reported WVC frequency in a temporally dependent manner and highlight the importance of considering both environmental events and regional variability when investigating wildlife-vehicle collisions. Full article

Climate change is a global phenomenon with various impacts on human health, in many cases aggravating the effects of pollen allergies. Several studies show the effects of human-induced temperature rise and changes in meteorological patterns on pollen production and dispersion, causing earlier flowering onset, extended pollen seasons, and increased pollen production. The repercussions on human health concern both allergic asthma and rhinosinusitis, whose symptoms can be worsened by extended exposure and impacts of extreme meteorological events, such as thunderstorm asthma. In this context, traditional aerobiological monitoring techniques are still valid as staple methods, but with a rising importance of new, automatic real-time sensors and atmospheric pollen forecasting systems, which can be important for early warning and prevention, to reduce and avoid exposure to allergenic pollen during peak days and hours. Omics techniques can also give important information about sensitization and response to allergens, granting a more comprehensive picture of the effects of exposure to allergens. In this paper, we carried out a literature review to discuss all these effects, with a focus on innovative tools and preventive measures. As a result, the application of an integrated and multifactorial approach emerges as fundamental in the management of pollen-induced allergies in the context of climate change. Full article

Tool steel TD salt-bath vanadizing generally relies on expensive analytical-grade raw materials, yet systematic investigations into low-cost industrial borax-based vanadizing of 9SiCr steel remain insufficient. This work intends to optimize the industrial salt-bath vanadizing process and clarify the growth mechanism of vanadium carbide coatings. TD thermal diffusion vanadizing was performed on 9SiCr steel using a molten borax salt bath containing industrial-grade borax and V₂O₅. Metallurgical microscopy, XRD, SEM-EDS and microhardness testing were adopted to systematically explore the effects of treatment temperature and holding time on coating thickness, microstructure and hardness. Continuous, dense VC coatings with favorable metallurgical bonding were fabricated. Coating thickness increased linearly with temperature and followed a parabolic growth law with respect to holding time. The optimized parameter was identified as 970 °C for 4 h, yielding a 8.3 μm thick coating with an average microhardness of ~2500 HV and an 8 μm thick diffusion transition layer. Comparative chromizing experiments indicated that the chromium carbide coating (16.7 μm) was approximately twice the thickness of the VC coating under identical conditions, demonstrating that VC coating growth is restricted by the diffusion supply of active carbon from the substrate. This research provides experimental data and theoretical guidance for the industrialized optimization of TD salt-bath vanadizing for 9SiCr steel. Full article

Harmful cyanobacteria blooms (CyanoHABs) have become a common problem in freshwater ecosystems. Monitoring at the federal and state level in response to this threat has increased over the last decade across the United States. In 2018, Pennsylvania environmental agencies began collecting CyanoHAB data to inform state regulatory and management efforts. 998 discrete samples from 138 waterbodies were collected over four years. These data were used to determine if indicators often used in CyanoHAB monitoring co-occurred with toxic conditions. Cyanotoxins were detected in more than half of the samples in Pennsylvania’s monitoring program with anatoxin, saxitoxins, and microcystins detected in similar proportions. It is important to note that the monitoring program is not designed to be representative of all Pennsylvania lakes but instead is targeted toward sites with greater exposure (recreational beaches) or sites with suspected blooms. Our findings suggest that cyanobacteria growth and cyanotoxin production may be driven by independent variables, as only microcystins concentrations were positively correlated with cyanobacteria counts. While increased cyanobacteria counts were related to all environmental variables considered in this study (warmer water temperatures, increased dissolved oxygen concentrations, and reduced water clarity), the relationships between cyanotoxins and environmental variables were mixed. Our analyses highlight the complexities of bloom occurrence and severity, and the challenges of incorporating these factors into monitoring and management strategies. Long-term monitoring approaches like the one analyzed here can inform management strategies that rely on environmental cues and cyanobacteria enumeration to evaluate risk of cyanotoxin presence. Full article

Artificial light at night (ALAN) alters natural nocturnal environments and affects ecosystems, human health, and night sky visibility, while cloud cover strongly modulates night sky brightness (NSB) by enhancing or attenuating skyglow. This study investigated the relationship between cloudiness and NSB at three locations in southern Poland representing contrasting light environments: urban Kraków, high-altitude Kasprowy Wierch, and rural Chochołów. Cloudiness was quantified using a custom binary image-processing method applied to monochrome all-sky camera images acquired under automatic exposure conditions. The procedure included exposure-time normalisation, dual-threshold segmentation with hysteresis, and site-specific histogram-based classification. Cloud-cover time series were synchronised with continuous SQM-LU night sky brightness measurements collected during moonless astronomical nights. An independent comparison was performed using a Hukseflux NR01 net radiometer and a radiative cloudiness proxy derived from surface–sky temperature differences. Increasing cloudiness was associated with brighter night skies at all sites, with the strongest effect observed in Kraków ($r=-0.97$; slope ≈−2.8 mag/arcsec${}^2$), a weaker response at Kasprowy Wierch ($r=-0.77$; slope $\approx -0.4$ mag/arcsec${}^2$), and a moderate relationship in Chochołów ($r=-0.48$; slope $\approx -0.7$ mag/arcsec${}^2$). Camera-derived cloudiness showed moderate agreement with the radiometric cloudiness proxy (robust $R^2=0.56$, $r_s=-0.79$). The proposed method proved practically useful across diverse lighting conditions, demonstrating its usefulness for long-term light pollution studies based on monochrome all-sky imagery. Full article

Understanding how urbanization modifies stream thermal regimes is essential for assessing freshwater ecosystem responses to climate variability and land-use and land-cover (LULC) change. This study investigated air temperature (AT)–water temperature (WT) relationships at annual, monthly, and diurnal timescales in two adjacent, relatively flat watersheds with contrasting urbanization levels in North Central Texas: the urbanized Doe Branch and less urbanized Little Elm Creek during 2012–2021. A single harmonic analysis was applied to characterize annual and diurnal thermal patterns, including mean temperature, amplitude, and phase, while statistical analyses were used to evaluate seasonal and daily thermal variability and peak timing. At the annual scale, AT and WT metrics were strongly correlated at both sites (r = 0.85–0.94, p < 0.01) indicating that atmospheric conditions were the dominant control of annual stream temperature variability. Annual mean WT increased with AT, suggesting strong air–water thermal coupling and the potential for warmer stream temperatures under future climate warming. However, Doe Branch exhibited higher annual mean WTs, delayed seasonal peak WTs, and reduced annual temperature ranges compared with Little Elm Creek, reflecting the influence of urban watershed characteristics on seasonal thermal responses. At the diurnal scale, daily mean WT remained strongly coupled with daily mean AT, whereas daily temperature range and peak timing showed weaker relationships with AT. The greater variability in peak WT timing at Doe Branch suggests that short-term stream thermal dynamics were influenced by additional watershed characteristics beyond atmospheric forcing alone. Full article

The maximum carboxylation rate (V_cmax) is a key parameter determining photosynthetic capacity in terrestrial biosphere models, yet its variability is often oversimplified as a plant functional type-dependent constant, increasing uncertainties in gross primary productivity (GPP) simulations. In this study, we inverted the daily V_cmax normalized to 25 °C (V_m25) by coupling the Breathing Earth System Simulator (BESS) model with the light response curves (LRC) method using eddy covariance observations at five maize sites in the United States and China. Then, four machine learning (ML) models—KNN, SVM, Random Forest (RF) and XGBoost—were employed to simulate V_m25, with RF showing the best performance (R² = 0.83, RMSE = 7.57 μmol m⁻²s⁻¹ for testing). Cross-validation further demonstrated the RF model’s ability to capture seasonal trends across sites. Incorporating the RF-simulated V_m25 into the BESS model significantly improved GPP estimates compared to the original BESS, with R² increasing from 0.53–0.81 to 0.77–0.84. Through the SHAP method and ablation experiments, leaf age was identified as the most influential factor, with the largest SHAP value of 8.37 μmol m⁻²s⁻¹, higher than that for temperature (4.47 μmol m⁻²s⁻¹), solar radiation (4.21 μmol m⁻²s⁻¹) and leaf area index (2.32 μmol m⁻²s⁻¹). And vapor pressure deficit had the minimal SHAP value of 0.87 μmol m⁻²s⁻¹. Notably, the effect of leaf age on V_m25 exhibited a unimodal pattern, with a strong coupling effect with leaf area index. This study demonstrates that interpretable machine learning not only provides a robust approach for simulating seasonally dynamic V_cmax, but also enhances our understanding of its driving biological and environmental factors, offering a valuable pathway for improving carbon cycle modeling in agroecosystems. Full article

D-tagatose, a low-calorie sugar substitute, widely used in the food and pharmaceutical industries, can be produced from the substrate D-galactose using L-arabinose isomerase (L-AI). L-AI genes derived from Lactobacillus fermentum (LFAI), Lactobacillus brevis (LBAI), Lactobacillus plantarum (LPAI), and Lactobacillus sakei (LSAI) for the bioconversion of D-galactose into D-tagatose using whole Escherichia coli (E. coli) cells were investigated. The temperature, time, pH, whole-cell concentration, and metal ion concentration were optimized to enhance catalytic production. The results revealed that at the low substrate concentration of 10 g/L, LFAI, LBAI, LPAI, and LSAI exhibited considerable catalytic activity, with conversion rates of 55.31%, 68.17%, 61.45%, and 58.22%, respectively. In contrast, at the high substrate concentration of 250 g/L, their conversion rates were 19.78%, 18.47%, 20.26%, and 36.24%, respectively, with LSAI demonstrating superior catalytic performance. In order to facilitate the industrial production of D-tagatose, site-directed mutagenesis was performed on LSAI. Among the engineered LSAI variants, the P99H, K142R, and L465R mutants all showed increased catalytic rates for D-tagatose. Specifically, at the high substrate concentration of 250 g/L, the P99H mutant achieved a conversion rate of 45.73%, representing a 32.7% improvement compared to the optimized LSAI. These results indicate that the designed site-directed mutagenesis strategy effectively enhanced whole-cell bioconversion performance of LSAI toward D-galactose. Full article

This study investigates the mechanisms and performance of oxygen-reduced air flooding (ORAF) and oxygen-reduced air gravity drainage (ORAGF) through laboratory experiments on crude oil and cores from the Kunbei Oilfield. PVT experiments show that injecting N₂ or oxygen-reduced air (5% and 10% O₂) increases saturation pressure and reduces oil viscosity comparably. Low-temperature oxidation (LTO) tests reveal that oxygen consumption rate declines exponentially with decreasing initial O₂ concentration; at 5% O₂, oxidation products are nearly indistinguishable from the original crude oil. Long-core displacement experiments demonstrate that vertical (gravity-assisted) injection significantly outperforms horizontal injection, with oil recovery reaching 39.8% (10% O₂) versus 26.2% horizontally, owing to gravity segregation suppressing gas fingering and enhancing oil–gas contact. Among injection strategies, gas-assisted gravity drainage (GAGD) and water-alternating-gas (WAG) improve recovery by 7.7% and 7.2% over continuous waterflooding, respectively, with GAGD being more suitable for high water cut reservoirs. Reservoir rhythm and permeability contrast affect performance and gravity-driven injection mobilizes low-permeability layers more effectively than horizontal injection, exhibiting good adaptability to heterogeneous reservoirs. Fracture orientation relative to injection direction plays a critical role—horizontal fractures achieve the highest recovery (~50%), whereas through-going fractures impair performance. These findings provide experimental guidance for optimizing oxygen-reduced air gravity flooding in tight and heterogeneous oil reservoirs. Full article

Extreme heatwaves intensify urban heat islands and pose increasing risks to urban sustainability and human health. However, how urban morphology is associated with daytime and nighttime land surface temperature (LST) across urban functional zones (UFZs), particularly under heatwave conditions, remains insufficiently understood. To address this gap, this study integrates daytime and nighttime LST data derived from SDGSAT-1, multi-dimensional urban morphology indicators, and two interpretable ensemble models (XGBoost and GWRF) to investigate overall sample-level nonlinear model-based associations between urban morphology and LST and to explore spatial variation in local predictor importance within Beijing and Nanjing, China. Because the daytime and nighttime scenes were not always paired within the same heatwave episode, the analysis focuses on selected heatwave-condition observations. The results show marked contrasts between the selected daytime and nighttime observations in UFZ-level thermal patterns. Industrial zones generally exhibited the highest daytime LST, whereas residential zones showed the highest nighttime LST. Building density was identified as the primary model-based predictor of daytime LST in both cities, although its association with LST was nonlinear and varied across density ranges. In contrast, nighttime LST was characterized by more heterogeneous predictor associations, involving vegetation structure, sky openness, building form, anthropogenic indicators, and material-related variables, with their relative importance differing across cities and UFZ types. Local predictor-importance patterns also varied across neighborhoods, cities, and observation times, indicating that model-identified locally important predictors were not spatially uniform within each city. These findings highlight the potential of SDGSAT-1 daytime and nighttime thermal observations and interpretable machine learning for screening candidate local thermal priority areas and key morphology-related factors under heatwave conditions. Full article