International Journal of Biometeorology最新文献

The aim of this study was to characterize the thermoregulatory, metabolic, and stress responses of rams to winter shearing, with a focus on both short-term and long-term effects. Eleven rams were sheared in mid-winter in a humid subtropical climate, according to the Köppen climate classification (environmental temperature and humidity during the study: 10.3 ± 3.6 °C and 77.7 ± 16.7%, respectively). Meanwhile, another 11 rams served as non-sheared controls. Immediately after shearing, rams increased their blood cortisol concentration, glycemia, hematocrit, and heart rate. Wool removal quickly reduced the surface temperatures at the base of the ear, nose, and lips, but did not affect rectal temperature. During the days following shearing, heart rate, glycemia, hematocrit, and blood concentrations of triiodothyronine and total protein increased. These changes were accompanied by a decrease in the surface temperatures of the eye and the base of the ear, but the rectal temperature remained unchanged. During the 11 days after shearing, rams were observed walking and standing more frequently, displaying increased agonistic interactions, and spending less time lying down. In conclusion, rams exhibited a typical acute stress response immediately after shearing, characterized by thermoregulatory and metabolic changes that persisted for several days. Rams modified their behavioral pattern, increasing thermogenesis and reducing heat loss. Sheared rams displayed an effective heat redistribution, maintaining their core temperature. Rams also increased their aggressiveness, which requires careful management to reduce the risk of injuries.

Long-term changes (1940–2023) in thermal stress and its drivers in Europe were investigated based on the Universal Thermal Climate Index (UTCI) extracted from the ERA5-HEAT reanalysis. Furthermore, a vulnerability index was introduced to assess the impact of thermal stress. The results reveal a rapid continental shift in thermal stress toward milder conditions. Although cold stress is declining fastest in northern regions (more than 4 hours(cdot)decade(^{-1})), heat stress is intensifying across southern Europe (more than 3 hours(cdot)decade(^{-1})). Such changes are driven by an increase in 2 m air temperature (between 0.2 up to 0.6(^circ)C(cdot)decade(^{-1})) and mean radiant temperature, particularly over northern and central Europe, and by changes also in relative humidity and wind speed. One of the key findings of this study is the decline in wind speed in specific areas of central and eastern Europe, leading to an increase in UTCI. Monthly analyzes show that winters warm the fastest (e.g., January cold stress decreases by 1.93%(cdot)decade(^{-1})), while summer heat stress peaks in July (0.27%(cdot)decade(^{-1})). In particular, the late spring months (e.g., May) also exhibit a positive trend, contributing to an extended warm season in Europe. Although European UTCI trends generally show a migration of thermal stress categories toward no to moderate-stress, city-level findings highlight more pronounced effects in continental cities such as Milan, Italy, and less pronounced effects in coastal areas like Madrid, Spain compared to cities of similar latitude. Furthermore, Heat Vulnerability Index reveals that highest vulnerability in southern and eastern Europe. These findings support policymakers in developing science-based measures to mitigate thermal risks, addressing both climatic and socioeconomic vulnerabilities in an era of rapid urbanization and climate change.

Traffic-related PM_2.5 worsens street air quality and affects pedestrian health, and the benefits of street trees in reducing air pollution within street canyons are still controversial. To clarify the influence of street tree parameters on PM_2.5 dispersion, tree height (TH), tree spacing (TS) and leaf area density (LAD) were selected from three different categories to represent the common characteristics of street tree species. Field measurements were conducted to validate ENVI-met model. We carried out 64 simulation scenarios with different parameters (TH, TS and LAD) and a treeless scenario in idealized street canyons (aspect ratio = 1:1) under oblique wind direction. The results showed that the 3D surface plots can effectively display the spatial distribution of PM_2.5 within street canyons. PM_2.5 concentration increased after planting trees; the leeward side showed higher concentrations than windward side, and the downstream showed higher concentration than upstream area. TH and LAD significantly influenced PM_2.5 concentration, while TS had less influence, and their effects differed in spatial position. PM_2.5 reduction efficiency (RE) varied with different street tree parameters on the windward side and leeward sides. Sky view factor (SVF) was significantly negatively correlated with PM_2.5 concentration, while green coverage ratio (GCR) and green plot ratio (GPR) were inversely correlated. TH = 6 m, TS = 6 m and LAD = 1.0 m² m⁻³ could be a suitable parameter combination for street tree planting or pruning. These results could provide practical suggestions for urban planning and landscape design to improve street air quality and promote sustainable urban development.

Recent studies have shown a close correlation between air pollution and the occurrence of asthma. A distributed lag nonlinear model was used in this research to analyze the relationship between 58,610 asthma outpatient hospital visits and daily PM_2.5, PM₁₀, NO₂, SO₂, CO, and eight hour mean O₃ exposure from 4 hospitals in Xinxiang City, Henan province from January 1, 2016 to December 31, 2021, and a stratified analysis of gender and age were conducted. Results showed that low concentrations of daily PM_2.5 (40 µg/m³), PM₁₀ (20 and 80 µg/m³), CO (0.8 mg/m³), NO₂ (10–30 µg/m³) and SO₂ (15 µg/m³) exposure reduced the number of outpatient visits for asthma patients. High levels of daily PM_2.5 (50–100 µg/m³), PM₁₀ (100–140 and 820 µg/m³), and SO₂ (20–25 µg/m³) exposure increased the number of outpatient visits for asthma patients. Both low (15–60 µg/m³) and high (150–205 µg/m³) concentrations of the eight hour mean O₃ exposure increased asthma outpatient hospital visits. Gender-stratified analysis revealed that, for male asthma patients, the daily outpatient visits decreased when CO exposure concentration of 0.8 mg/m³; while for female asthma patients, the daily outpatient visits decreased when SO₂ exposure concentration of 15 µg/m³, but increased when the concentration was 20 µg/m³. In comparison, both low and high concentrations of eight hour mean O₃ exposure increased the daily male asthma outpatient hospital visits. Additionally, when the eight hour mean O₃ exposure concentration was 10–30 µg/m³ and the daily SO₂ exposure concentration was 20 µg/m³, asthma outpatient hospital visits for adult increased; when the eight hour mean O₃ exposure concentration was 145–220 µg/m³ and the daily SO₂ exposure concentration was 50–110 µg/m³, asthma outpatient hospital visits for adolescent increased. This study suggests that asthma patients should limit going outdoors on days with poor air quality, especially for women and adolescents.

Pediatric intussusception has been linked to seasonality and ambient temperature, but few studies have examined its short-term temperature dependence at a daily resolution. This study investigated the association between daily ambient temperature and the incidence of pediatric intestinal intussusception. Claims data from the National Health Insurance Service were analyzed for pediatric patients (≤ 10 years old) who underwent procedural or surgical treatment for intussusception in Seoul from 2009 to 2019. Daily average temperature data were obtained from the Korea Meteorological Administration. Seasonal case counts were compared, time-series trends were visualized using a spline function, and a distributed lag non-linear model (DLNM) was applied to assess rate ratios (RRs) while accounting for cumulative lag and non-linearity. Analyses were conducted separately for total, complicated, and uncomplicated cases. Total intussusception case counts peaked in summer, followed by autumn, spring, and winter. The DLNM model with a 0–3-day lag showed a significant RR increase for total and uncomplicated intussusception at temperatures around 7 °C to 20 °C compared to 0 °C. Complicated intussusception exhibited an increase from subzero temperatures to approximately 4 °C, though confidence intervals were wider due to lower case counts. No significant risk Change was observed at temperatures above 20 °C in any group. This study demonstrated a significant association between daily ambient temperature and pediatric intestinal intussusception, with short-term (3-day) cumulative effects suggesting that temperature fluctuations may influence disease incidence.

The aim was to examine the effects of Balneotherapy (BT) on blood pressure (BP) and heart rate (HR) and to evaluate its clinical reliability in daily practice. The study was planned as a randomized, controlled, single-blind study. 240 patients were divided into two groups. All received a 2-week, 5-day-per-week, 10-session physical therapy (PT) programme. One group additionally received BT. Demographic data was collected. Arterial BP and HR were measured and recorded before and after the every session. The BT+PT group had a higher incidence of side effects (p<0.05). While systolic BP (SBP) decreased between the first and eighth day measurements in the BT+PT group, it increased on the second, fifth, and tenth days (p<0.05). SBP values in the PT group were higher at the third day and on days one through ten (p>0.05). Diastolic BP (DBP) increased at many measurement points in the PT group, but not in the BT+PT group (p>0.05). HR increased over time in both groups, and the sixth day measurement in the PT group was higher than in the BT+PT group (p<0.05). Slope analysis showed significant changes in SBP and DBP. The improved BP and HR values resulting from BT and PT applications show that these can prevent cardiovascular disease and prolong life. BT is safe when used by a qualified physician, especially in comorbid individuals.

The present study aimed to (i) characterize the seasonal dynamics of coat morphology and skin evaporation (SE) as adaptive indicators, (ii) evaluate milk production and composition throughout the lactation period, and (iii) investigate the relationships between these adaptative traits and milk production in Majorera and Palmera goats raised on Tenerife Island (28°N). Morphological data, skin evaporation and milk production (MP) and composition of 30 Majorera and 20 Palmera lactating and non-pregnant goats of similar reproductive age were collected over 18 months period. Except for coat diameter, all variables showed an interaction effect (p < 0.001) between season and breed. Coat thickness was greater (p < 0.001) in the Palmera breed than in Majorera goats in all seasons. Hair length was greater (p < 0.001) by more than 200% in Palmera goats than in Majorera goats in all seasons. Except for summer, skin evaporation (SE) was higher (p < 0.001) for the Palmera than Majorera. Majorera goats showed higher MP (p < 0.001) throughout all months of the lactation period compared to Palmera goats. The average total MP over the 210-day lactation period was 338.46 for Majorera and 207.3 L for Palmera. Regarding milk composition, Palmera goats had higher fat (p = 0.007) content than Majorera goats, whereas protein content was similar (p = 0.358) between breeds. Canonical correlation analysis indicated that the climate of Tenerife Island exerts a greater influence on coat morphological traits and SE in Palmera goats (r_c²= 0.38; p < 0.001). These climate effects on adaptive traits showed a stronger tendency to be associated with MP (r_c²= 0.29; p = 0.058). In contrast, although the climatic influence on morphological traits and SE was lower in Majorera goats (r_c²=0.22; p < 0.001), these adaptive variables were not significantly related to MP (r_c²=0.25; p = 0.160). Majorera and Palmera goats exhibited distinct seasonal responses in coat traits and SE under the climate of Tenerife. Palmera goats, with longer and denser coats, showed greater susceptibility to heat stress and a stronger tendency for adaptive traits to influence MP. In contrast, Majorera goats, whose coats favored heat dissipation, had higher MP and greater productive stability under environmental fluctuations. These findings highlight the importance of including coat traits in genetic improvement programs for dairy goats in temperate regions.

Soldiers working in cold zones and Arctic regions face physiological challenges that lead to hypothermia, frostbite, and cold-induced conditions, which lowers their chances of survival and operational effectiveness. Nanomedicine is the innovative approach in drug delivery and the development of nanomaterials and diagnostic tools to produce ground-breaking solutions. This paper reviews advancements in thermoregulation control using nanotechnology, hypothermia treatment using nanoparticles, protective solutions for treating frostbite, and wearable nanosensors to investigate the current nanomedicine advancements applied to military cold-zone mission. AI technology integrated with nanotechnology enables clinical staff to provide personal care, diagnosis of diseases at an early stage and manage them effectively in extreme cold conditions. The current research innovations suggest connecting AI to the development of regenerative nanomedicine and diagnostic systems, as well as to standard protocols for nanomedical interventions that require international cooperation. Army protection has been improved by investigating previous military incidents and incorporating advancements in modern nanomedicine formulations. Advancements in modern medical technology offer significant opportunities to increase military operation success and readiness within extremely cold environments through superior medical equipment provided to army.

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The growing season is the period when weather conditions (e.g., precipitation, temperature, wind, etc.) in a given area support plant growth and development. This study examines how climate change has influenced the growing season duration in Poland over the past nearly 80 years, based solely on phenological observations. The research was conducted for two 15-year periods: the pre-warming period (1946–1960), before significant global climate warming became evident, and the warming period (2007–2021), characterized by the additional influence of the “greenhouse component” on climate trends. The former dataset was sourced from the Yearbooks of Phenological Observations, which had not been previously available to a wider audience and were digitized by the authors for this study. The latter dataset was obtained from the database of the Institute of Meteorology and Water Management–National Research Institute. The results indicate an increasingly earlier onset of the vegetation period and a slight delay in its end over time, leading to an extended growing season. Today, as a result of climate change, its duration has increased to over 240 days in the west, while in the central lowlands and the Lublin Upland, it has reached 220–230 days. However, it remains almost unchanged along the coast and in northeastern Poland. Due to its location in a transitional temperate climate zone, Poland experiences high weather variability, which is also reflected in fluctuations in the start dates and duration of growing seasons.

Amid the effects of climate change and rising urbanization, the interaction between urban heat islands (UHIs) and background climate factors has become critical to study. This study investigates the spatiotemporal variation of atmospheric urban heat island intensity (AUHII) in Guangdong Province, China, and evaluates the long-term influence of key climate variables: precipitation, relative humidity, and wind speed on AUHI. An integrated modeling approach was used, combining econometric techniques (Fully Modified Ordinary Least Squares and Dynamic Ordinary Least Squares) with machine learning and deep learning methods. The Random Forest (RF) model served as an initial benchmark, followed by a Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) framework to improve predictive accuracy. Results showed significant spatial and seasonal variations, with AUHII ranging from − 2.6 to 2.3 °C for daytime, nighttime, and mean values. Seasonal extremes were observed in winter (-4.1 to 3.9 °C) and summer (-1.8 to 1.4 °C), with nighttime and winter exhibiting the strongest AUHI effects, particularly in western and southern cities. Relative humidity was the most influential factor, followed by precipitation. While the RF model identified key predictors, the CNN-LSTM model demonstrated stronger generalization, achieving testing R² values above 0.75 across most cities. Our findings enhance the understanding of the linkages between background climate variables and the AUHI effect, providing insight that can help urban planners and policymakers develop strategies to mitigate the effects of atmospheric urban heat islands.