International Journal of Biometeorology最新文献

Epilepsy is a neurological disorder that significantly impacts individuals and society, contributing to the global disease burden. However, research on the association between meteorological factors and epilepsy across all age groups remains limited. To investigate the relationship between daily average temperature and epilepsy outpatient visits in Chongqing, the most populous city in western China, and to assess susceptibility differences by gender and age. We employed distributed lag non-linear models (DLNM) to investigate the association between daily average temperature and epilepsy outpatient visits from January 2014 to December 2019 (a total of 2,191 days) in Chongqing. Additionally, we conducted subgroup analyses based on gender and age. During the study period, a total of 99,740 outpatient visits for epilepsy were recorded. Using the median daily average temperature (19.5 °C) as a reference, the single-day lag risk ratio (RR) of a low daily average temperature (5th percentile, 7.8 °C) on outpatient visits for epilepsy showed a persistent decrease throughout the entire lag period (from lag 0 to lag 12) and remained statistically significant from lag 0 to lag 3, with values of 1.05 (95% CI: 1.01, 1.10), 1.04 (95% CI: 1.01, 1.07), 1.03 (95% CI: 1.01, 1.05), and 1.02 (95% CI: 1.00, 1.05), respectively. The cumulative RR peaked at lag 0–8 (RR: 1.22, 95% CI: 1.08, 1.36), and then remained relatively stable. The association between higher daily average temperatures and epilepsy outpatient visits was not statistically significant. Subgroup analyses indicated that males and individuals under 18 and over 65 years old were more vulnerable to the effects of low ambient temperatures on epilepsy risk. Season acts as an effect modifier in the association between low daily average temperature and epilepsy outpatient visits.

Silvopastoral systems integrating tree cover into pasturelands offer promising strategies to mitigate heat stress in tropical livestock production. This study evaluated the effects of shade from Eucalyptus urograndis on thermal comfort indices in Gyr and Girolando dairy cattle in the Brazilian Cerrado. Forty-eight lactating cows (24 Gir, 24 Girolando) were monitored over two years in two contrasting environments: no shade (full sun) and shade (silvopasture). Thermal indices, including rectal and surface temperatures (measured via infrared thermography), respiration rates, and panting scores, were analyzed alongside environmental data, such as the Temperature-Humidity Index (THI). Cattle under shade consistently exhibited lower body temperatures, respiration rates, and panting scores, with significant differences amplified under heat stress conditions (THI > 74). Though both benefited from shade, Gyr cattle demonstrated better thermoregulatory responses than Girolando. Discriminant analysis accurately classified animals by system (> 92%) and breed (~ 71%) based on physiological traits. These results confirm that tree shade significantly enhances animal comfort in tropical pasture systems and supports the implementation of silvopastoral practices to improve dairy cattle welfare and resilience under climate stress.

Migratory habit was developed in birds in response to unfavorable winter conditions in their high-latitudinal breeding grounds. Autumn weather conditions should determine the decision on departure in Arctic birds. Large-bodied Bewick’s Swan Cygnus bewickii of the West Pacific population must pass mountain ranges and open sea between their Arctic breeding areas (Chaun delta in this study) and temperate winter quarters (Japan). In this paper we use data from individually telemetry tagged Bewick’s Swans (both families with young and adult individuals presumably non-breeders or failed in breeding) to analyze the prevailing meteorological factors at the point of their departure from their breeding/moulting grounds. We compare these conditions to those at their departure from major autumn stop-over sites in the Kolyma Lowland for the longest migration boot without stops to Sakhalin Island. We hypothesize different meteorolocal factors for a short longitudinal journey of the first migration boot and second the longest migration boot. We also predict a difference between families with young and adult swans in migration strategy. Families departed from their natal site in the Chaun delta significantly later than non-breeding adults; however, both groups left synchronously from stopover sites in the Kolyma Lowland. In the Chaun Delta, swan families were dependent on tailwinds and rainfall for the timing of their departures, with these factors working in conjunction with decreasing temperatures. In contrast, non-breeding swans did not take wind conditions into account but still avoided migration during rainy weather.

Peloid is a matured mud with healing and/or cosmetic properties, composed of a complex mixture of mineral or seawater with a clay-based material, that requires quality control prior to its application in therapeutic and dermocosmetic treatments. In this research, physico-chemical and biological analyses were performed to assess influence of the two mineralized waters on three residual smectitic soils. Seawater increased the electrical conductivity values of peloids (from 0.3 to 0.5 mS/cm to 68.0–73.8 mS/cm) and their organic matter content (from 2.6 to 4.7% to around 7%), whereas thermo-mineral water enhanced the cation exchange capacity (from 38.4 to 70.0 meq/100 g to 55.2–86.6 meq/100 g). The pH of peloids remained alkaline, and zeta potential values were stable throughout the maturation period. The concentrations of Pb, Co, Ni and V in samples exceed the acceptable limits established for cosmetic and pharmaceutical products, hence further dermal bioacessibility assessment are required to substantiate their clinical safety before therapeutic use. Moreover, fecal indicator bacteria were not detected in the peloids, however thermo-mineral water peloids showed fungal contents slightly above recommended microbiological limits. The physico-chemical and microbiological characterization suggests that these peloids have potential therapeutic values, although further thermal and rheological characterization are required to assess their suitability.

In recent decades, escalating extreme climate events (ECEs) have raised significant concerns regarding their effects on public health in South Africa, particularly respiratory illness. This study examined the relationship between ECEs and respiratory health outcomes over a 12-year period (2008–2019). A total of 48 ECEs were analyzed, of which 28 occurred in regions reporting more than 100 medical insurance claims for respiratory diseases. These events included storms, heatwaves, cold waves, floods, and tornadoes. Using a two-week lag period, we assessed their short-term association with respiratory claims. The findings revealed both increases and decreases in claims following ECEs, yet seasonal epidemiological trends exerted a more consistent and pronounced influence on respiratory health than individual extreme events. Percentage variations for statistically significant events ranged from approximately + 16% to + 121%, while decreases ranged from − 5% to − 178%. Although certain events displayed notable impacts, no distinct clustering was observed across seasons or years. These results underscore the importance of strengthening seasonal preparedness measures alongside climate-sensitive surveillance systems. Integrated approaches that address both seasonal and extreme climate risks are vital to safeguard vulnerable populations amid increasing climate variability in South Africa.

This study aims to systematically evaluate the associations between various exposure factors and hyperuricemia. A total of 22,765 participants derived from the Henan rural cohort, and 9 categories containing 60 different exposures. The exposome-wide association study (ExWAS) approach was used to estimate the associations between various exposure factors and hyperuricemia. An adaptive elastic net (AENET) model was implemented to select significant exposure factors, followed by the application of a gradient boosting machine (GBM) model to establish the prediction model of these variables to hyperuricemia. The importance of the indicators was assessed through Shapley Additive Explanations (SHAP). Additionally, the weighted quantile sum (WQS) method was employed to validate the selection of these variables. In ExWAS analysis, 40 exposures were significantly associated with the risk of hyperuricemia. The AENET model selected ten exposures as predictors. GBM model and SHAP result showed that the top three exposures were Creatinine, Triglycerides, and PM_2.5, which interpreted the model as 0.460, 0.331, and 0.314, respectively. Furthermore, the area under characteristics (AUC) of the model was 0.815 (95% CI: 0.802–0.820). WQS shows the same ranking results. The systematic evaluation of this study provides new insights into the complex environment-related factors of hyperuricemia.

Graphical Abstract

This study investigates bioclimatic comfort conditions in Iran by integrating perspectives from traditional Persian Medicine (PM) with modern climatological methodologies. The primary objective is to develop the Persian Medicine (PMI) as a criterion for evaluating comfort zones across Iran and to compare its results with modern climatological indices, specifically the Terjung Index (TI) and the Standard Effective Temperature Index (SETI). Daily meteorological data from 2003 to 2018 were utilized. To construct the PMI, qualitative variables describing temperate regions were extracted from classical PM texts and implemented Python programming, Excel and ArcGIS 10.8 for spatial analysis. The analysis focuses on May, September, and December, months that exhibited the highest degree of similarity among the comfort zones identified by PMI, TI, and SETI. Results indicate that the spatiotemporal distribution of comfort zones derived from SETI corresponds most closely with those identified by PMI, representing the highest levels of climatic and physiological comfort throughout the year. Overall, the findings demonstrate a strong correspondence between modern climatological comfort indices and PMI-based assessments in temperate regions of Iran. This research highlights the potential of integrating traditional medical- environmental knowledge with modern climate science, providing valuable insights for medical geography, environmental health management, and climate adaptation planning under global warming conditions.

Variations in temperature trends are considerably impacting plants’ phenology. Most predictive models share the concept of Growing Degree Days (GDDs). Among available formulations, the ones not considering the effects of high temperatures on plants’ development seem no longer adequate, due to the increasing frequency of heat waves, leading to misinterpretation of climate effects. The aim of the present work is to compare six different degree-days models, in order to assess which of them could give the best results in terms of GDDs calculation for summer crops in Mediterranean Europe. Specifically, average method, single triangle method (with also three different cut-off techniques: horizontal, vertical, intermediate) and beta-distribution function method were tested. For this purpose 22 years of phenological data were used, comparing “standard” and “warm” years (with average temperature during June – August below and above, or equal to, the median value of the 22-years period, respectively). Models were compared via Mean Absolute Error (MAE), Mean Error (ME), Root Mean Square Error (RMSE) and Diebold-Mariano test, to assess differences in their predictive performance. Results showed that the use of models considering the negative effects of high temperatures in the ripening period significantly boosted predictive accuracy. Among these approaches, the physiologically based beta-distribution function provided the best results. However, simpler methods, which could facilitate the acquisition of modelling novelty in operational contexts, having the advantage of being easy-to-use also proved to be significantly improving, such as intermediate cut-off technique, which among geometrical models can be considered the best approximation of crops physiological response.

Automation and environmental control offer solutions to enhance animal welfare and production efficiency in regions with adverse climates. This study aimed to develop a prototype for thermal environment control in finishing swine pens located in a semi-arid region and to evaluate its performance based on microclimatic traits, physiological responses, animal performance, and thermographic aspects of both the facility and the animals. The experiment involved thirty finishing gilts (Duroc × Large White crossbreeds), grouped by age and weight into three treatments (each with 10 animals per experimental unit). The automated thermal control treatments applied were: (1) no thermal control, (2) automatic activation of a micro-sprinkling system, and (3) automatic activation of micro-sprinkling combined with ventilation. Environmental conditions in all treatments failed to reach optimal thermal comfort levels for finishing pigs, due to the semi-arid characteristics of the region. However, the thermal control treatments reduced floor temperatures by approximately 3 °C compared to the treatment without thermal control. The micro-sprinkling treatment reduced the respiratory rate by 5.32 breaths/min and promoted an average daily weight gain of 0.26 kg/day compared to the control group. Additionally, the pigs’ body temperatures were significantly lower than those in the untreated group, indicating improved animal welfare. These findings demonstrate the efficacy of automated thermal control systems as a strategy to enhance swine production in semi-arid regions.

Several airborne fungal spores, such as Alternaria and Epicoccum, are known for their allergenic potential, yet accurately predicting their atmospheric concentrations remains a challenge. This study presents predictive models for estimating daily concentrations and clinically relevant threshold exceedance events of Alternaria and Epicoccum spores, using long-term aerobiological and meteorological data from five cities in Central Europe. Key meteorological predictors, including time-lagged variables, were identified for each location, and interpretable lasso linear and lasso logistic regression models were developed to forecast spore levels up to seven days in advance. The lasso logistic models achieved high accuracy in threshold exceedance predictions, with F1 scores reaching up to 88.6% for Epicoccum. While lasso linear models effectively captured seasonal patterns and timing, they tended to underestimate peak concentrations, likely due to the sporadic nature of spore release events. Notably, this is the first predictive model developed for Epicoccum, underscoring the need for clinical validation of allergological thresholds. Regional variability in model performance highlights the importance of local calibration and sustained aerobiological monitoring. These models offer a promising foundation for operational spore forecasting systems, supporting both public health advisories and agricultural decision-making.