International Journal of Biometeorology最新文献

Heat is associated with an increase in Emergency Medical Service (EMS) operations. However, different heat definitions in research, including outside air temperature (T), Heat Index (HI) and Universal Thermal Climate Index (UTCI), impair the assessment of heat onthe frequency of EMS operations. Therefore, this study aims to compare (1) the relationship between different heat definitions and the frequency of days defined as heat events, (2) the percentage change in the number of EMS operations per heat definition, and (3) the goodness of model fit of each heat definition. We analyzed data from EMS operations and 106 weather stations in Bavaria, Germany (2018–2020), comparing 40 heat definitions with varying thresholds, percentiles (e.g. 90th percentile), and durations (≥ 1 or ≥ 2 days) based on T, HI, and UTCI. Negative binomial regression models were adjusted for confounders. All definitions indicate significant increased EMS operations during heat events, with effect sizes ranging from 8.3% (T_night≥20.0 °C; confidence interval: 4.2–12.5%) to 18.7% (HI_mean≥26.7 °C ≥ 2 days; confidence interval: 9.7–28.4%). Definitions with higher thresholds, percentiles, or longer durations have larger effects but worse model fits. Heat definitions based on HI or UTCI are not superior to temperature-based ones, and definitions using mean or maximum values yield similar frequencies, effects, and model fits. All heat definitions show increased EMS operations during heat events, with larger effects for higher thresholds or longer durations. Complex definitions offer no advantage over temperature-based ones, which we recommend for further research. Percentile-based definitions are preferable for better comparability.

The heat index (HI) metric is used in many studies linking weather conditions (observed or climate model-projected temperature and humidity) to health impacts. Because climate models often provide only daily data, a common approximation method estimates the daily maximum HI (hismaxest) from daily maximum temperature (tasmax) and minimum relative humidity (hursmin), assuming they coincide with the actual peak HI (hismax24). This study evaluates the accuracy of this approximation using hourly station-based data from NOAA’s Integrated Surface Database (ISD-Lite) and the U.S. Climate Reference Network (USCRN). Though we find that hismaxest either matches or slightly underestimates hismax24 for most summer days and locations, it significantly underestimates the occurrence of extreme heat days in the hottest regions. Specifically, hismaxest misses over 35% of days exceeding the 95th percentile of June–July–August hismax24 at 7 of the 37 stations examined, despite performing well in cooler, drier regions. This underestimation follows an increasing nonlinear relationship with local HI thresholds, indicating that hismaxest may underestimate extreme heat risks in vulnerable regions of the southern U.S. These discrepancies arise because HI is more sensitive to relative humidity in hotter regions, making hismaxest less reliable. Our findings quantify an often overlooked uncertainty arising from daily climate model data resolution that can be comparable to scenario and model sensitivity uncertainties. These results highlight the need for careful interpretation of climate model heat projections, and emphasize the value of archiving hourly climate model data for multivariate index calculations.

This study characterises heatwave patterns in Burkina Faso using observed data and climate model simulations. Key metrics used include Heat Wave Amplitude (HWA), Heat Wave Frequency (HWF), Heat Wave Duration (HWD), Heat Wave Magnitude (HWM), and Heat Wave Number (HWN). The Bias-Correction Spatial Disaggregation (BCSD) method generated the NEX-GDDP-CMIP6 dataset. The models were subjected to statistical tests using Taylor’s diagram. The Taylor diagram showed that IPSL-CM6A-LR, with the least Root Mean Square Error (RMSE) and Standard Deviation (S.D.) values, and also had the highest R² values for both temperature readings, is the best-substituted model for the observed data. Most models overestimated for minimum temperature with an RMSE of approximately 1, a S.D. of 2.6 and a correlation coefficient of 0.7; maximum temperature was overestimated by about 2.1 RMSE, with a standard deviation close to 3.0 and a correlation ranging between 0.7 and 0.87. MRI-ESM2-0 had the lowest correlation (0.69) for minimum temperature, while EC-Earth3 recorded the lowest correlation for maximum temperature. The observed data reveal a north-south gradient, with higher intensities in the north. Climate models show varying accuracy in replicating this gradient, with models like CMCC-ESM2 and IPSL-CM6A-LR closely mirroring observed patterns. However, models like KIOST-ESM and MRI-ESM2-0 exhibit significant discrepancies. Nighttime and daytime heat wave numbers ranged between 6^oC (24–30 °C) and 11^oC (32–43 °C). The recorded heat wave duration over the northern part of Burkina Faso was about five (5) days, with most models aligning except KIOST-ESM, which recorded over seven (7) days. The study highlights the importance of employing reliable climate models for future heat wave predictions and underscores the increasing threat of heat waves due to climate change. These findings are crucial for informing adaptation and mitigation strategies in Burkina Faso concerning heat stress.

Livestock management practices like the provision of shade, air movement using fans, and wallowing are important methods to alleviate heat stress (HS) and maintain the productivity of buffaloes during extreme summer seasons. This study evaluated the effectiveness of heat mitigation strategies in lactating Murrah buffaloes under extreme summer conditions, with temperature-humidity index (THI) values ranging from 82.29 to 84.62, indicating periods of critical HS. A total of 84 buffaloes were taken and divided into 7 groups, with each group subjected to different strategies: Group I (tree and shed); Group II (mist and fan system); Group III (shower system); Group IV (mud pool); Group V (water pool); and Group VI (water pond) while Group VII (open area) served as the control. Infrared thermography (IRT) was used to measure muzzle, eye, and forehead temperatures. Milk somatic cell counts (SCC) and cortisol levels were measured in milk samples. Statistical analysis was conducted using ANOVA and Pearson correlation, with P < 0.05 considered significant. Buffaloes under Group III showed the most significant (P < 0.05) reductions in body surface temperatures, milk SCC, and milk cortisol levels, followed by Groups VI and II. Positive correlations were found between muzzle (r = 0.672, P < 0.01) and eye (r = 0.747, P < 0.01) temperatures with milk cortisol. Regression analysis confirmed moderate associations between milk cortisol and both muzzle (R² = 0.452, β = 1.12, P < 0.001) and eye (R² = 0.558, β = 1.26, P < 0.001) temperatures. Results indicated Group III as the most effective method for reducing HS in buffaloes, followed by Group VI and II. These strategies help to sustain buffalo productivity during extreme summer conditions.

Graphical Abstract

Lassa fever is an acute viral haemorrhagic disease caused by the Lassa virus. Transmission to humans primarily occurs through direct contact with Mastomys rats or via the ingestion of food or usage of household items contaminated with the urine or faeces of infected rats. The MaxEnt algorithm was used to estimate the distribution of Lassa fever based on data on the incidence of the disease, ecogeographic features, and human factors. Principal component analysis (PCA) was used to mitigate multicollinearity among the environmental variables. The model’s accuracy was evaluated using the area under the receiver operating characteristic curve (AUC-ROC). The prevalence of Lassa fever is anticipated to be substantially affected by human factors (population density, roads, built-settlement, poverty), climatic variables (Prec11, Tmean01, Bio7, Bio12), and altitude. The model distribution map revealed that Owo, Ose, Akure North, Akure South, Akoko South-West, Akoko South-East, Akoko North-East, Ifedore, Idanre, Ondo, and Akoko North-West are very suitable regions. Our suitability map identifies hotspots, aiding public health officials in resource distribution to mitigate the current Lassa fever epidemic in Ondo State, Nigeria.

Living organisms, including human beings, spending time outdoors may be harmed by ultraviolet radiation. This research aimed to quantify the effects of vegetation, weather, and their interaction on UV-B irradiances (280–315 nm) in outdoor recreational spaces. UV-B irradiances in a playground shaded by trees and a roof garden in Hong Kong were monitored from 9 October 2020 to 3 November 2020. A turf was used as a control site. UV-B values during the after-school hours (12:00–13:00 h and 15:30–16:30 h) of a kindergarten in sunny and cloudy weather were analysed using mixed-effects models. The results showed high UV-B levels on the control turf (3.23 W/m²) and the roof garden (3.34 W/m²) on sunny midday but significantly lower in the playground (2.41 W/m²). Cloudy weather significantly decreased UV-B irradiances by 40%. The sparse and thin tree crowns in the playground implied equivalent UV-B protection factor values at 1.2–1.4, corresponding to a reduction in UV-B by 17–29%. Behaviourally, playtime could be postponed from midday to afternoon and shifted from sunny to cloudy days to avoid excessive UV-B exposure. This research highlighted the necessity of other sun protection measures despite protection from the tree canopy.

Urban morphology plays a pivotal yet underexplored role in mitigating urban heat. This study investigates the impact of geometric configurations of three typical residential neighborhoods in Tehran, Iran, on outdoor thermal comfort (OTC) using computational fluid dynamics (CFD) simulations conducted with the ENVI-met model. The dynamic thermal comfort (dPET) index was used to assess pedestrian thermal comfort, focusing on the following vulnerable groups: children and the elderly. Meteorological measurements, including air temperature, relative humidity, wind speed, and mean radiant temperature, were obtained at each neighborhood site during July 1–3, 2024. These measurements were used to evaluate ENVI-met simulation performance by comparing observed to simulated data. We additionally examined the effect of a suite of adaptation strategies aimed at improving OTC through the following modifications: (1) raised material albedo to 0.5 and 0.75, and (2) added street trees with 50% and 75% fractional coverage. A final, maximum deployment scenario, incorporating 75% vegetation coverage and a material albedo of 0.75, was evaluated for all neighborhoods. Our analysis indicates that children could benefit from lower dPET values compared to the elderly during sunlit hours. However, both age groups benefit from enhanced OTC in high-rise neighborhoods. Maximum deployment of vegetation was highly effective in reducing dPET, particularly in high-rise configurations, with reductions of nearly 2 °C at noon. This study demonstrates the critical role of urban morphology and biophysical adaptation in shaping thermal environments and provides actionable insights for designing thermally comfortable and resilient urban spaces in hot and arid regions.

Varicella is a highly contagious disease that represents an escalating public health concern. This study aimed to assess the influence of meteorological factors on varicella incidence, identify vulnerable populations, and estimate the disease burden associated with meteorological exposure. Data were collected from Chongqing Municipality (2010–2019), including varicella case counts and seven meteorological variables. We employed a method combining a quasi-Poisson generalized additive model with a distributed lag nonlinear model and adjusting for potential confounders. A total of 183,692 varicella cases were reported. The analysis revealed that meteorological factors exhibited nonlinear relationships with varicella incidence. Notably, the strongest cumulative effects were observed for mean temperature (14.0 °C, RR = 1.246, 95% CI: 1.157–1.340), diurnal temperature range (0.6 °C, RR = 1.249, 95% CI: 0.993–1.571), relative humidity (97%, RR = 1.995, 95% CI: 1.639–2.429), aggregate rainfall (119.5 mm, RR = 5.062, 95% CI: 1.001–25.593), and mean air pressure (991.4 hPa, RR = 1.438, 95% CI: 1.331–1.554). Sunshine hours ≥ 5.6 h and wind speeds ≥ 2.1 m/s were protective. Adolescents aged 12 to 18 years exhibited the highest prevalence during periods of moderate temperature, high rainfall, and high humidity. Furthermore, the attributable risk analysis confirmed that meteorological factors significantly contribute to the varicella burden. These findings underscore the importance of incorporating meteorological patterns into public health strategies, including early warning systems and meteorologically specific interventions, to mitigate varicella transmission risk, particularly in the context of climate change.

Unresolved issues still exist regarding urban-rural disparity of temperature-related mortality among different regions. We collected daily all-cause mortality data from 7,439,777 individuals in 300 counties across six temperature zones in China, ranging from the coldest to hottest regions, from 2017 to 2021. Additionally, we obtained the daily average temperature, relative humidity, and concentrations of PM_2.5 and O₃ in these regions during the same period. Distributed lag non-linear model and meta-regression were used to analyse the data; the fraction of mortality attributable to low temperature was calculated. The results showed that there is a significant difference in the attributable fraction of low temperature between urban and rural areas in temperate regions (North China); this difference was relatively small in subtropical and tropical regions (South China), indicating that man-made protective facilities were more reliable in resisting the low temperature than people’s physiological adaptation. Central heating in urban areas in temperate regions resulted in a lower attributable fraction of low temperature at each age group, central heating was also necessary in the northern and middle subtropical regions to achieve the highest cold burden.

Environmental factors play a pivotal role in determining sprinter performance, with ambient wind being particularly influential. This study provides a detailed analysis of the effects of ambient wind on sprinting, using the National Stadium of China (NSC) as a case study and incorporating local meteorological wind data. Wind speed and direction data were obtained from the Beijing Meteorological Tower (BMT) for the period 2013 to 2017, enabling an analysis of local wind climate characteristics and the wind field. A local wind field model was developed and simulated in a wind tunnel, and wind environment tests on a refined NSC model yielded the wind speed distribution along the 100 m track, which was then integrated with the enhanced Mureika sprint model to assess the impact of ambient wind on sprint performance. The results, taking local wind climate characteristics into account, suggest that summer is the optimal season for holding 100 m competitions at the NSC, as the dominant wind direction and average wind speed during this period exert relatively small impact on performance. Specifically, a 2 m/s tailwind at the track’s midpoint improves performance by 0.082 to 0.111s, whereas a 2 m/s headwind generally reduces performance by no more than 0.13s.