International Journal of Biometeorology最新文献

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.

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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.

Occupational heat stress is an escalating global health concern, particularly for outdoor workers exposed to rising temperatures due to climate change. This narrative review synthesizes evidence from 42 peer-reviewed articles and 13 policy documents published between 2014 and 2025, focusing on the health impacts, determinants, and adaptation strategies for outdoor workers. The review identifies a high prevalence of heat-related illnesses—including heat exhaustion, dehydration, kidney disorders, and productivity loss—across sectors such as agriculture, construction, and informal labour. Key vulnerability factors include individual health status, environmental conditions, and inadequate workplace policies. Adaptation strategies found to be most acceptable and effective include improved hydration, loose breathable clothing, scheduled rest breaks in shaded areas, and modification of work practices. Policy case studies from California, India, Qatar, and Europe highlight the importance of context-specific regulations, enforcement, and community outreach in reducing heat-related morbidity and mortality. However, significant gaps remain in the implementation of adaptive measures, especially for informal and vulnerable worker populations. The review underscores the urgent need for integrated, gender-sensitive, and enforceable adaptation strategies, alongside further research to strengthen resilience among outdoor workers facing increasing heat stress due to climate change.

Thinning is an important forest management measure and would benefit sustainable forest development. However, it is also a great disturbance to forests and disrupts their original balance and thus their response characteristics to the environment. Based on continuous eddy covariance and climatic observations in a subtropical coniferous plantation, this study aimed to clarify the thinning-induced changes in the response of gross primary productivity (GPP) to key environmental factors (net radiation (Rn), air temperature (Ta), vapor pressure deficit (VPD), and soil water content (SWC)). The results indicated that for both pre- and post-thinning, the GPP exhibited an “increase-peak-decrease” response pattern to Rn, Ta and VPD. The GPP was dominated by Rn, and Rn regulated the response of GPP to Ta and VPD to some extent. The direct effects of SWC on GPP were weak and without obvious regularity. Thinning weakened the control effects of environmental factors on GPP. However, we found that thinning increased the response sensitivities of GPP to Rn, Ta and VPD before the response curves reached their peaks, that is, when the environmental factors were lower before the inhibitory effects manifested. After the response peaks, thinning generally alleviated the inhibitory effects of these factors. Although SWC did not have direct effects on GPP, it had potential effects on GPP. Under relatively high SWC conditions, weakened inhibitory effects of VPD on GPP were found after thinning. These results indicated that thinning altered the ecosystem response and may improve the natural resource use efficiency of this subtropical plantation.

There is less evidence on the association between long-term PM_2.5, O₃, greenness exposure and cardiometabolic multimorbidity (CMM), and the aim of this study was to investigate the combined effects of PM_2.5, O₃ and greenness exposure on the risk of developing CMM.Our findings demonstrated that a 10 µg/m³ rise in PM_2.5 concentration led to a 23.8% increased CMM risk (HR = 1.238, 95%CI: 1.202,1.275). A 0.1 increase in NDVI reduced CMM risk by 18.9% (HR = 0.811, 95% CI: 0.779,0.845). A 10 µg/m³ O₃ concentration increase surprisingly lowered CMM risk by 30.8% (HR = 0.692, 95% CI: 0.649,0.738). Positive interactions were seen between high PM_2.5+low O₃ and low O₃ + low NDVI, while high PM_2.5+low NDVI had negative interactions regarding CMM. PM_2.5 mediated the link between NDVI and CMM, heart disease, and stroke.This study emphasizes that long-term high PM_2.5 exposure ups CMM risk in Chinese middle-aged and older adults, yet NDVI exposure reduces it, with PM_2.5 as a mediator. The O₃-CMM relationship remains unclear.

The thermal environment of urban public spaces is becoming increasingly prominent. As a mountainous, high-density city in southwestern China, Chongqing’s unique landscape and dense viaducts have fostered riverside parks and under-bridge parks, shaping diverse microclimate spaces for recreation. Field monitoring of microclimates in different outdoor activity spaces in the riverside and under-bridge parks in Chongqing during winter and spring analyzed the relationship between visitor numbers and thermal comfort, and explored the influence of thermal comfort on recreational activity types. Findings: (Peng et al. 2019) In spring, the thermal comfort in under-bridge spaces is enhanced compared to non-under-bridge spaces, with the thermal perception in under-bridge spaces reaching up to “slightly warm,” while the thermal perception in non-under-bridge spaces can reach “warm” even “hot” (ASHRAE 2010). In winter, visitor numbers at most of the outdoor spaces increased with rising PET values; conversely, they decreased with rising PET in spring (Cetina-Quiñones et al. 2024). thermal perception significantly influenced activity occurrence probability. When thermal comfort is “Cool” or “Slightly Cool”, people prefer low-intensity activities. When “Neutral”, all activity types occurred readily. When “Slightly Warm”, probabilities increased for fitness activities and social activities. The under-bridge spaces narrower thermal comfort range encourages fitness/ social activities (Lu et al. 2019). The non-under-bridge spaces maintained some activities at “Warm”/ “Hot” thermal perception with facility support. Based on the research findings, design strategies for microclimate adaptability are proposed, including the establishment of seasonally responsive facility optimization measures and dynamic activity guidance mechanisms for winter and spring, to enhance the recreational experience and urban space vitality in mountainous, high-density cities.