Search Results (196)

Apiculture is among the most weather-dependent sectors of agriculture; however, quantifying the impact of meteorological factors remains challenging. Beehive weight has long been recognized as an important indicator of colony health, strength, and food availability, as well as foraging activity. Atmospheric influences on hive weight dynamics have been a subject of research since the early 20th century. This study aims to estimate hourly hive weight variation by applying linear time-series models to hive weight data collected from active apiaries during intensive foraging periods, considering atmospheric predictors. We employed a rolling 24 h forward ARIMAX and SARIMAX model, incorporating meteorological variables as exogenous factors. The median estimates for the study period resulted in model RMSE values of 0.1 and 0.3 kg/h. From numerous meteorological variables, the hourly maximum temperature was found to be the most significant predictor. ARIMAX model results also exhibited a strong diurnal cycle, pointing out the weather-driven seasonality of hive weight variations. Full article

In recent years, China has experienced growing impacts from extreme weather events, emphasizing the importance of understanding regional atmospheric moisture dynamics, particularly Precipitable Water Vapor (PWV), to support sustainable environmental and urban planning. This study utilizes ten years (2013–2022) of Global Navigation Satellite System (GNSS) observations in typical cities in eastern China and proposes a comprehensive multiscale frequency-domain analysis framework that integrates the Fourier transform, Bayesian spectral estimation, and wavelet decomposition to extract the dominant PWV periodicities. Time-series analysis reveals an overall increasing trend in PWV across most regions, with notably declining trends in Beijing, Wuhan, and southern Taiwan, primarily attributed to groundwater depletion, rapid urban expansion, and ENSO-related anomalies, respectively. Frequency-domain results indicate distinct latitudinal and coastal–inland differences in the PWV periodicities. Inland stations (Beijing, Changchun, and Wuhan) display annual signals alongside weaker semi-annual components, while coastal stations (Shanghai, Kinmen County, Hong Kong, and Taiwan) mainly exhibit annual cycles. High-latitude stations show stronger seasonal and monthly fluctuations, mid-latitude stations present moderate-scale changes, and low-latitude regions display more diverse medium- and short-term fluctuations. In the short-term frequency domain, GNSS stations in most regions demonstrate significant PWV periodic variations over 0.5 days, 1 day, or both timescales, except for Changchun, where weak diurnal patterns are attributed to local topography and reduced solar radiation. Furthermore, ERA5-derived vertical temperature profiles are incorporated to reveal the thermodynamic mechanisms driving these variations, underscoring region-specific controls on surface evaporation and atmospheric moisture capacity. These findings offer novel insights into how human-induced environmental changes modulate the behavior of atmospheric water vapor. Full article

Understanding temperature variations within the complex urban canopy layer (UCL) is challenging due to limitations and discrepancies between temperature measurements taken in urban canyons and on rooftops. The key question is how much these measurements differ and what factors contribute to these differences. According to the guidance by the World Meteorological Organization (WMO), rooftop observations are not encouraged for urban monitoring, due to potentially anomalous microclimatic conditions, whereas measurements within urban canyons are recommended. This is particularly relevant given the increasing number of rooftop sensors deployed through citizen science, raising questions about the representativeness of such data. This study aimed to address this knowledge gap by comparing temperatures within the UCL using two sensors: one located on a rooftop, and the other positioned within the canyon. The temperature difference between these two nearby locations followed a clear diurnal cycle, peaking at over 1 °C between 12:00 and 16:00 local time, with the canyon warmer than the rooftop. This daytime warming was primarily driven by solar radiation and, to a lesser extent, by wind speed, but only under clear-sky conditions. During the rest of the day, the temperature difference remained negligible. Full article

Radon’s radioactive decay is the main natural source of small air ions near the ground. Its exhalation from soil is affected by meteorological factors, while aerosol pollution reduces air ion concentrations through ion-particle attachment. This study aimed to analyze correlations between radon, ions, and air pollution under varying conditions and to assess potential health impacts. Measurements were taken at two sites: in early autumn at a suburban part of Belgrade with relatively clean air, and in late autumn in central Belgrade under polluted conditions, with low temperatures and high humidity. Parameters measured included radon, small air ions, particle size distribution, PM mass concentration, temperature, humidity, and pressure. Results showed lower radon concentrations in late autumn due to high soil moisture and absence of nocturnal inversions. Radon and air ion concentrations exhibited a strong positive correlation for both polarities under suburban conditions, whereas measurements in the urban setting revealed a weak negative correlation, despite radon concentrations in soil gas being approximately equal at both sites. Small ion levels were also reduced, mainly due to suppressed radon exhalation and increased aerosol concentrations, especially ultrafine particles. A strong negative correlation (r < −0.5) was found between small air ion concentrations and particle number concentrations in the 20–300 nm range, while larger particles (300–1000 nm and >1 µm) showed weak or no correlation due to their lower and more stable concentrations. In contrast, early autumn measurements showed a diurnal cycle of radon, characterized by nighttime maxima and daytime minima, unlike the consistently low values observed in late autumn. Full article

Understanding optical turbulence within the atmospheric boundary layer (ABL) is essential for refining atmospheric motion analyses, enhancing numerical weather prediction models, and improving light propagation assessments. This study develops an optical turbulence model for the boundary layer over the South China Sea (SCS) by integrating multiple observational and reanalysis datasets, including ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF), radiosonde observations, coherent Doppler wind lidar (CDWL), and ultrasonic anemometer (CSAT3) measurements. Utilizing Monin–Obukhov Similarity Theory (MOST) as the theoretical foundation, the model’s performance is evaluated by comparing its outputs with the observed diurnal cycle of near-surface optical turbulence. Error analysis indicates a root mean square error (RMSE) of less than 1 and a correlation coefficient exceeding 0.6, validating the model’s predictive capability. Moreover, this study demonstrates the feasibility of employing ERA5-derived temperature and pressure profiles as alternative inputs for optical turbulence modeling while leveraging CDWL’s high-resolution observational capacity for all-weather turbulence characterization. A comprehensive statistical analysis of the atmospheric refractive index structure constant ($C_n^2$) from November 2019 to September 2020 highlights its critical implications for optoelectronic system optimization and astronomical observatory site selection in the SCS region. Full article

Effectively managing carbon monoxide (CO) pollution in complex industrial cities like Jubail remains challenging due to the diversity of emission sources and local environmental dynamics. This study analyzes spatiotemporal CO patterns and builds accurate predictive models using five years (2018–2022) of data from ten monitoring stations, combined with meteorological variables. Exploratory analysis revealed distinct diurnal and moderate weekly CO cycles, with prevailing northwesterly winds shaping dispersion. Spatial correlation of CO was low (average 0.14), suggesting strong local sources, unlike temperature (0.92) and wind (0.5–0.6), which showed higher spatial coherence. Seasonal Trend decomposition (STL) confirmed stronger seasonality in meteorological factors than in CO levels. Low wind speeds were associated with elevated CO concentrations. Key predictive features, such as 3-h rolling mean and median values of CO, dominated feature importance. Spatiotemporal analysis highlighted persistent hotspots in industrial areas and unexpectedly high levels in some residential zones. A range of models was tested, with ensemble methods (Extreme Gradient Boosting (XGBoost) and Categorical Boosting (CatBoost)) achieving the best performance ($R^2>0.95$) and XGBoost producing the lowest Root Mean Squared Error (RMSE) of 0.0371 ppm. This work enhances understanding of CO dynamics in complex urban–industrial areas, providing accurate predictive models ($R^2>0.95$) and highlighting the importance of local sources and temporal patterns for improving air quality forecasts. Full article

In high-altitude cold regions, significant diurnal and seasonal temperature variations intensify freeze-thaw damage to rocks, critically impacting slope stability. This study examines a Xinjiang mine slope to assess freeze-thaw effects through laboratory experiments on three lithologies under varying freeze-thaw cycles. Mechanical parameters were determined via the Hoek–Brown criterion, and FLAC3D simulations analyzed stress-deformation characteristics and safety factor trends, validated against field monitoring. After 90 cycles, the results show progressive degradation: uniaxial compressive strength declined by 29.7–45.8%, elastic modulus by 42.7–63.3%, Poisson’s ratio by 16.0–42.1%, cohesion by 71.7–77.1%, internal friction angle by ~52.0%, and tensile strength by 79.3–83.6%. The slope safety factor decreased exponentially (44.5% reduction). Both simulations and monitoring revealed “step-like” displacement growth, with minor discrepancies attributed to modeling assumptions. These findings provide critical insights for safe mining operations in cold regions, highlighting the severe mechanical deterioration induced by freeze-thaw cycles and its implications for slope stability. Full article

As a primary construction material, concrete plays a vital role in the development of infrastructure, including bridges, highways, and large-scale buildings. In Northeast China, the structural integrity of concrete faces severe challenges due to freeze–thaw cycles and substantial diurnal temperature variations. This study involved a thorough examination of concrete’s performance under varying numbers of temperature differential cycling (60 to 300) and freeze–thaw cycles (75 to 300). The results showed that both freeze–thaw and temperature differential cycling led to increasing mass loss with the number of cycles. Peak mass losses reached 3.1% and 1.2% under freeze–thaw and temperature differential cycles, respectively, while the combined action resulted in a maximum mass loss of 4.1%. The variation trends in dynamic elastic modulus and compressive strength differed depending on the environmental conditions. Under identical freeze–thaw cycling, both properties exhibited an initial increase followed by a decrease with increasing temperature differential cycles. After 120 temperature differential cycles, the dynamic modulus and compressive strength increased by 4.7–6.2% and 7.5–10.9%, respectively. These values returned to near their initial levels after 180 cycles and further decreased to reductions of 17.0–22.6% and 15.3–29.4% by the 300th cycle. In contrast, under constant temperature differential cycles, dynamic modulus and compressive strength showed a continuous decline with increasing freeze–thaw cycles, reaching maximum reductions of 5.0–11.5% and 18.1–31.8%, respectively. Notably, the combined effect of temperature differential and freeze–thaw cycles was significantly greater than the sum of their individual effects. Compared to the superposition of separate effects, the combined action amplified the losses in dynamic modulus and compressive strength by factors of up to 3.7 and 1.8, respectively. Additionally, the fatigue life of concrete subjected to combined temperature differential and freeze–thaw cycles followed a two-parameter Weibull distribution. Analysis of the S-N_f curves revealed that the coupled environmental effects significantly accelerated the deterioration of fatigue performance. Full article

The apparent respiratory quotient (ARQ) of tree stems, defined as the ratio of net stem CO₂ efflux (E_{S_CO2}) to net stem O₂ influx (E_{S_O2}), offers insights into the balance between local respiratory CO₂ production and CO₂ transported via the xylem. Traditional static chamber methods for measuring ARQ can introduce artifacts and obscure natural diurnal variations. Here, we employed an open flow-through stem chamber with ambient air coupled with cavity ring-down spectrometry, which uses the molecular properties of CO₂ and O₂ molecules to continuously measure E_{S_CO2}, E_{S_O2}, and ARQ, at the base of a California cherry tree (Prunus ilicifolia) during the 2024 growing season. Measurements across three stem chambers over 3–11-day periods revealed strong correlations between E_{S_CO2} and E_{S_O2} and mean ARQ values ranging from 1.3 to 2.9, far exceeding previous reports. Two distinct diurnal ARQ patterns were observed: daytime suppression with nighttime recovery, and a morning peak followed by gradual decline. Partitioning E_{S_CO2} into local respiration and xylem-transported CO₂ indicated that the latter can dominate when ARQ exceeds 2.0. Furthermore, transported CO₂ exhibited a higher temperature sensitivity than local respiration, with both processes showing declining temperature sensitivity above 20 °C. These findings underscore the need to differentiate stem CO₂ flux components to improve our understanding of whole-tree carbon cycling. Full article

The aim of this study was to expand the monitoring network and evaluate the accuracy of inexpensive WoMaster ES-104 sensors for monitoring particulate matter (PM) in temperate latitudes, using the example of the Southern Baikal region. The research methods included continuous measurements of PM_2.5 and PM₁₀ concentrations, temperature, and humidity at three stations (Listvyanka, Patrony, and Tankhoy) from October 2023 to October 2024, using the LCS WoMaster ES-104. ERA5-Land reanalysis data and the HYSPLIT model were used to analyze meteorological conditions and air mass trajectories. The results of this study showed a high correlation between the WoMaster ES-104 and the DustTrak 8533; the correlation coefficient was 0.94 (R² = 0.85) for both fractions. The seasonal dynamics of PM_2.5 and PM₁₀ were characterized by a dual-mode distribution with maxima in summer (secondary aerosols, high humidity) and winter (anthropogenic emissions, inversions). The diurnal cycles showed morning/evening peaks associated with transport activity and atmospheric stratification. Extreme concentrations were recorded in anticyclonal weather (weak north-westerly winds, stable atmosphere). This study confirms the suitability of the LCS WoMaster ES-104 for real-time monitoring of PM_2.5 and PM₁₀, which contributes to sustainable development by increasing the availability of air quality data for ecologically significant regions such as Lake Baikal. Full article

To ensure a high crop profit in Chinese solar greenhouses (CSGs), it is crucial to effectively manage major environmental variables such as temperature, humidity, and CO₂ concentrations, among others, to mitigate harmful effects on crop growth. The objectives of this study were to assess the spatial, vertical, and temporal variability of major environmental variables in CSGs during summer, and to provide fundamental information that could facilitate the monitoring and control of environmental factors in CSGs. The experiments were conducted in two CSGs: one with crops and another without crops. The measured environmental variables included air temperature, humidity, CO₂ concentration, light intensity, and wind conditions. Significant variations in the spatial, vertical, and temporal distribution of environmental factors were observed in both greenhouses. The results revealed significant diurnal patterns in temperature and humidity, with higher daytime temperatures and lower humidity levels. The greenhouse with crops exhibited warmer bottom layers due to restricted air mobility. CO₂ concentrations peaked at night, aligning with plants’ respiration and photosynthesis cycles, whereas light intensity showed substantial daytime peaks, slightly affected by the presence of crops. The study emphasized the necessity of stratified control of the environment and dynamic management of CO₂. The deployment of a wireless sensor network (WSN) and placement of an error-based sensor ensured precise monitoring, highlighting the importance of continuous data collection and adaptive management for optimal greenhouse conditions. Full article

In the context of global warming, which is mainly due to the increasing atmospheric concentration of carbon dioxide, the prediction of climate change requires a good assessment of the involvement of vegetation in the global carbon cycle. In particular, determining when vegetative activity ceases in deciduous forests remains a great challenge. Remote sensing of solar-induced fluorescence (SIF) has been considered as a potential proxy for ecosystem photosynthesis and, therefore, a relevant indicator of the end of the vegetation period as compared to other vegetation indices, such as EVI (Enhanced Vegetation Index) and NDVI (Normalized Difference Vegetation Index). However, many challenges remain to be addressed due to the lack of knowledge of the response of SIF at different time scales, different species and different environmental conditions. The aim of this study was to explore the diurnal and seasonal variations in the SIFA and SIFB signals in a pubescent oak forest undergoing senescence. We show that apparent SIFA yield may be considered an earlier indicator of the end of the vegetation period compared to NDVI, which primarily reflects the ratio of SIFB/SIFA. The apparent SIFA yield signal was positively and highly correlated with PRI (Photochemical Reflectance Index), EVI and NDVI. Air contents in CO₂ and O₃ were similarly significantly correlated to SIFs emission but only during the growth phase of the phenology of Q. pubescens. At the seasonal scale, the results show that SIF variations were mainly driven by variations in PAR, air VPD and temperature. A higher dependence of the SIF signal on these last three variables was observed at the diurnal scale through Pearson correlation coefficients, which were greater than seasonal ones. Full article

The increasing number of heat wave (HW) days, combined with the urban heat island (UHI) phenomenon, poses a threat to the health and comfort of city residents. This study investigates the impact of HWs on the diurnal cycles of intensity and spatial structure of the atmospheric UHI (AUHI) and surface UHI (SUHI). A comparative analysis is conducted on the simultaneous night–day variability of AUHI and SUHI intensities in Kraków in two 24 h summer periods: one representing normal summer conditions (Period W) and the other HW conditions (Period H). Evaluating sub-daily UHI patterns based on integrated in situ and satellite data is a relatively novel approach. This study utilizes (1) air temperature from 21 measurement points located in different local climate zones and vertical (altitude) zones; and (2) land surface temperature from six NOAA/AVHRR satellite images. The findings indicate that AUHI and SUHI intensities in Kraków were generally up to 3 °C higher at night and up to 3 °C lower during the daytime in Period H compared to Period W, particularly in the valley floor. These results provide valuable insights into the increased heat load risk due to the co-occurrence of UHI and HW, with implications for sustainable urban planning strategies. Full article

Forests play a crucial role in carbon cycling, contributing significantly to global carbon cycling and climate change mitigation, but their capture strength is sensitive to the climatic zone in which they operate and its adjoining environmental stressors. This research investigated the carbon dynamics of a typical deciduous forest, the Daniel Boone National Forest (DBNF), in the Mixed-Humid climate of Kentucky, USA, employing the Eddy Covariance technique to quantify temporal CO₂ exchanges from 2016 to 2020 and to assess its controlling biometeorological factors. The study revealed that the DBNF functioned as a carbon sink, sequestering −1515 g C m⁻² in the study period, with a mean annual Net Ecosystem Exchange (NEE) of −303 g C m⁻²yr⁻¹. It exhibited distinct seasonal and daily patterns influenced by ambient sunlight and air temperature. Winter months had the lowest rate of CO₂ uptake (0.0699 g C m⁻² h⁻¹), while summer was the most productive (−0.214 g C m⁻² h⁻¹). Diurnally, carbon uptake peaked past midday and remained a sink overnight, albeit negligibly so. Light and temperature response curves revealed their controlling effect on the DBNF trees’ photosynthesis and respiration. Furthermore, clear seasonality patterns were observed in the control of environmental variables. The DBNF is a carbon sink consistent with other North American deciduous forests. Full article

Hydraulic engineering projects in high-altitude environments are subject to significant diurnal temperature variations, necessitating concrete with high freeze–thaw resistance. Aggregates play a crucial role in the freeze–thaw durability of concrete. However, the impact of different parent rock types on concrete’s freeze–thaw resistance remains underexplored. This study investigated the effect of five common coarse aggregate types—granite (Gr), tuff (Tu), sandstone (Sa), limestone (Li), and pebble (Pe)—on the freeze–thaw resistance of dam concrete subjected to freeze–thaw cycles. The relationship between the rock type’s properties and the degradation patterns of concrete with different aggregates under freeze–thaw conditions was analyzed. Additionally, the damage mechanisms at the paste–aggregate interface were explored using SEM-EDS, pore structure analysis, and nano-indentation, along with the characteristics of the hydration products in the transition zone. The results showed that the aggregate type significantly influences freeze–thaw resistance, with Gr performing best (Gr > Li > Pe > Tu > Sa), correlating with pore structure and pore spacing. Gr, due to its superior freeze–thaw resistance, was optimal for regions with stringent freeze–thaw conditions. Although the interface zone exhibited a lower elastic modulus and hardness compared to the paste region due to a lower total amount of hydration products, these differences did not substantially affect the freeze–thaw performance of the concrete. This study, contributing to the expansion of the existing knowledge base on the effects of aggregate types on freeze–thaw resistance, provided valuable engineering insights for the selection of coarse aggregates in hydraulic concrete applications in high-altitude regions. Full article