International Journal of Biometeorology最新文献

Humid heat extremes are expected to intensify in conjunction with rising global temperatures, leading to prolonged and elevated exposure to hazardous levels of heat stress (HS). Even moderate levels of HS have been observed to trigger a range of health and socioeconomic impacts, underscoring the need for regional climate information. Therefore, we examine the present and future conditions of two different HS indices, wet bulb temperature (WBT) and environmental stress index (ESI), for the first time at such high resolution over northwestern Türkiye using a non-hydrostatic regional climate model, COSMO-CLM. The study is also pioneering in its effort to assess population exposure to these indices at the provincial scale. The findings indicate that the most substantial shifts in the probability density function of both HS indices from the middle of the 21^st century onward are expected to occur in June relative to the reference period. However, WBT intensity with ~ 4 °C increase is projected to undergo the most significant change in September, while ESI has the largest increase in July. According to ESI projections, almost all areas (> 95%) in cities such as Istanbul, Tekirdağ, Edirne and Çanakkale will experience severe HS at least once in July after 2071, while based on WBT projections, the same cities will face similar conditions after 2091. The 2091–2100 period will be subject to the longest exposure duration, the greatest areal expansion, and the highest population exposure levels. Conversely, Kütahya, Bilecik, and Kırklareli are expected to have the least substantial increase in exposure among 12 cities.

The Tibet Autonomous Region, the world’s highest region, faces high tuberculosis (TB) rates, exacerbated by its unique environment and climate. However, the combined impact of air pollution and meteorological factors exposure on the prevalence of TB remains understudied. Daily data on TB cases, air pollutants (PM₁₀, PM_2.5, SO₂, NO₂, O₃, and CO), and meteorological factors (temperature, precipitation, and wind speed) between 2019 and 2023 were collected. Weighted Quantile Sum (WQS) regression and Bayesian Kernel Machine Regression (BKMR) models were employed to assess the combined and individual effects of these environmental factors on TB prevalence. Moreover, gender, occupation, and year-specific distinction were explored using subgroup analysis. A total of 18,347 new TB cases were reported during the study period, with a positive association between environmental factors and the prevalence of TB. The WQS model showed a positive combined effect of environmental factors on daily TB cases (OR:1.58, 95%CI:1.46–1.71), and the weight of precipitation and PM₁₀ were 0.55 and 0.59, respectively. BKMR analysis further confirmed a positive association between overall environmental factors and TB, highlighting precipitation as the most significant independent factor and potential interactions among environmental variables. Subgroup analyses confirmed a consistent positive association between environmental factors and TB cases, with PM₁₀ and precipitation being most influential, precipitation more significant for females, and PM₁₀ dominant among farmers and students. Exposure to air pollution and meteorological factors has a significant impact on the cases of TB. Notably, PM₁₀ and precipitation are identified as primary determinants, with distinct variations observed among females, farmers, and students. Accurate estimates are essential for informing public health interventions, optimizing resource allocation, and developing effective clinical strategies in high-altitude regions.

Urban heat island (UHI) effects have intensified in recent years, bringing increasing attention to urban parks as key green infrastructures for mitigating extreme heat. While existing studies primarily focus on physical cooling mechanisms, limited research integrates residents’ perceptual experiences and equitable access to cooling resources. This study proposes a tri-dimensional analytical framework that combines physical cooling performance, emotional perception, and spatial accessibility, using 113 urban parks in central Shijiazhuang, China as a case study. Land surface temperatures were derived from Landsat imagery, and multiple cooling metrics were quantified. A boosted regression tree (BRT) model identified evapotranspiration and surface albedo as dominant factors influencing cooling effectiveness. Residents’ emotional responses and usage preferences were extracted via sentiment analysis using SnowNLP on park-related reviews from the Dianping platform. To evaluate spatial equity, we developed an enhanced two-step floating catchment area (2SFCA) model incorporating sentiment-based service weights and Huff-based probability functions. Results show that parks with strong cooling effects do not necessarily align with areas of high user satisfaction. The preferences of younger populations are often underrepresented, and less than 50% of the population in central Shijiazhuang has access to effective cooling services. These findings highlight the need for a collaborative optimization strategy that integrates thermal performance, user experience, and service equity. The proposed framework provides a transferable approach for guiding resilient urban park planning and adaptive responses to extreme heat.

The COVID-19 pandemic significantly impacted Brazil, amplifying existing socioeconomic disparities and social vulnerabilities, particularly in the State of Alagoas, located in Eastern Northeast Brazil (ENEB). This study evaluated the climatic, environmental, and socioeconomic effects attributed to COVID-19 across the Health Regions (HR) of Alagoas. Daily data on COVID-19 cases and deaths from the 10 h were sourced from DATASUS through the Unified Health System (SUS) for the period from March 2020 to January 2023. Both datasets underwent descriptive statistical analysis, with the Spline method, Principal Component Analysis (PCA), and Case Fatality Rate (CFR %) calculations employed for deeper insights. The resulting data were visualized on Maps using QGIS version 3.16. Climatic data included air temperature (T), wind speed (Ws), water vapor pressure (e), rainfall (Pcp), and reference evapotranspiration (ETo), obtained from the TerraClimate platform on a monthly scale. Socioeconomic and demographic data consisted of population density; municipal Human Development Index (HDI); Lack of Bathroom Facilities (or toilet); illiteracy rate; Low-Income; coverage of the Family Health Strategy, Gini index, SUS establishments, urbanized area, and monthly income per capita of up to 1/2 minimum wage from IBGE (2010 census) and the Basic Guide of SUS for Alagoas (2017). All data were subjected to a correlation matrix, adopting the Spearman correlation coefficient (ρ) with a significance level (p-value < 0.05) for analysis and implemented using the Python language. The results show differences in COVID-19 among the HR. There is a direct and highly significant relationship between social, economic, and demographic determinants and the COVID-19 pandemic, unlike climatic variables, which showed specific correlations in some HR. Regarding socioeconomic and demographic relational patterns, lack of bathrooms, HDI, SUS facilities, population density, and urban area stand out, with high positive and monotonic Spearman correlations. Regarding climatic relational patterns, T, ETo, and e stand out, particularly in the 4th and 7th HR, with the exception of the 3rd HR (Ws). The study’s results indicate that improvements in terms of governance and public management are necessary post-pandemic.

Bioclimatic comfort is an important area of research that focuses on the impact of climatic conditions on human health, comfort and performance. This study examines the differences between simple and complex bioclimatic indices, highlighting their advantages and limitations in different geographical and climatic conditions.In this context, three main bioclimatic indices used namely the Discomfort Index (DI), Physiological Equivalent Temperature (PET) and Universal Thermal Climate Index (UTCI). DI is a simple method that can be calculated using only remote sensing data and has advantages for rapid assessment and planning. PET and UTCI are indices that take into account more environmental parameters and therefore provide more complex but more detailed results.In stable climatic conditions, simple indices may be sufficient for general assessments. However, in regions with rapid climate change or extreme weather events, complex indices are more effective.Considering the topographical and climatic variability of Turkiye, this study evaluated the performance of each index under different geographical and climatic conditions. To better understand the relationship between the three indices, comfort levels were assessed in 11 common classes. In this context, the comfort class includes areas where 18–23 °C is recorded for PET, 9–26 °C for UTCI and 15–20 °C for DI. The study results show that PET values tend to be higher in coastal and lowland areas, but lower in inland areas with continental climates. UTCI generally remains within the comfort range at all altitudes, especially between June and August.The annual average DI value is 23.8 °C, indicating that most of Turkiye experiences warm thermal comfort conditions.

Climate change poses a significant threat to livestock production and animal health globally, with particular implications for Burkina Faso. This study explores the links between climate patterns and the resurgence of five major livestock diseases in Burkina Faso, using climatic records from 1961 to 2020 and veterinary clinical data from 2003 to 2019 collected across the Sahel, Sudan-sahel and Sudan climatic zones. The annual and seasonal climate trends were compared over two climatological periods (1961–1990 and 1991–2020) using two independent t-test. It is was found significant changes in rainfall and temperature patterns from one climatological period to the other, with the Sudan zone influenced by maximum annual temperatures, the Sahel zone by minimum annual temperatures, and the Sudan-Sahel zone by both. Poisson regression analysis revealed complex interactions between disease occurrence and climatic factors, with certain diseases like foot-and-mouth disease and Pasteurellosis of small ruminants favoured by warm and humid conditions, while Contagious Bovine Pleuropneumonia was influenced by dry spells. Lumpy skin disease (LSD) manifests in response to cold and wet days. Newcastle disease’s occurrence is determined by varying combinations of temperature extremes. These findings underscore the importance of climate change in influencing livestock disease occurrence across different climatic zones in Burkina Faso. They highlight the need for resilient livestock breeding practices, improved management strategies, and climate-smart interventions to mitigate the adverse effects of climate change on animal health and enhance overall agricultural sustainability.

Maize production is affected by several biotic and abiotic factors, with diseases being a major cause of yield and quality loss. The maize white spot (MWS) is one of the most important diseases and is widespread in tropical and subtropical production areas. Its development depends on the interactions among plants, pathogens and environmental conditions. Understanding the environmental conditions that favor disease development is essential for predicting disease occurrence in different regions and for implementing effective crop management strategies. This study evaluated the relationships between agrometeorological variables and the severity of MWS, as well as the impact of the disease on maize yield under field conditions. The analysis was based on 25 years of MWS severity and yield data collected from 29 production sites in São Paulo, Brazil. Statistical approaches include correlation analysis, linear regression models, and pattern identification in the data distribution. The observed trend suggests that the maize yield decreases by approximately 45.7 kg ha⁻¹ (≈ 1%) for each 1% increase in MWS severity. The variables most strongly associated with increased MWS severity are relative humidity (> 55%), soil moisture (> 0.3), mean temperature (15–22 °C), maximum temperature (20–30 °C), diurnal temperature range (8–16 °C), and wind speed (< 3 m s⁻¹). These findings improve the understanding of the effects of the environment on disease progression, expand the knowledge of key factors and reveal new associations. The results provide valuable input for predictive models and management strategies to mitigate the impact of MWS on maize production.

As global temperatures continue to rise, heat stress presents significant risks to animal health, particularly affecting kidney function that is of vital importance due to its essential role in detoxification and fluid balance. This study investigates the effects of a carbohydrate rich diet (CRD) on renal health in albino rats subjected to prolonged heat and humidity stress. A total of 180 rats (90 males, 90 females) were assigned to Routine Diet (RD) and CRD groups, each further divided into no-stress, heat stress, and humidity stress subgroups. Stress exposure lasted 4 h daily for 30 days, with sample collection at 10, 20, and 30 days. The results demonstrated that heat and humidity stress significantly impacted renal biomarkers (urea, creatinine, uric acid, and BUN) in both male and female albino rats. Males generally exhibited higher serum levels of these markers compared to females, indicating greater susceptibility to stress-induced renal strain. Under no-stress conditions, CRD-fed males and females showed elevated renal markers compared to RD-fed counterparts, with females exhibiting relatively lower values. Humidity stress caused the most pronounced increase in renal markers, with RD-fed males and females reaching peak urea and BUN levels. The CRD diet partially mitigated these elevations in both sexes, although values remained significantly higher than in the no-stress group. Moreover, decapitation interval analysis revealed a consistent increase in urea, creatinine, and uric acid levels over time in both sexes, suggesting cumulative physiological stress. These findings highlight the complex interplay between diet, environmental stress, and gender in renal health, underscoring the potential of dietary strategies to mitigate stress-induced kidney damage. Further research is needed to elucidate the mechanisms underlying these gender-specific and dietary effects.

The unique climate of plateau regions increases the risk of cold-related conditions, such as hypothermia and frostbite. Therefore, it is essential to study and improve severe-cold protective equipment for use in these environments. This research involved an experiment simulating a plateau at an altitude of 4,500 m, with an ambient temperature of -9℃ and 23℃. Sixteen healthy male participants performed two types of physical activities—weighted hiking and heavy lifting—while thermophysiological and subjective thermal responses were recorded, including local skin temperature and thermal sensation. Statistical analysis revealed that different physical activities and environmental temperatures in plateau environments significantly influence human thermophysiology. During hiking, the back and shoulders exhibited weaker correlations with other body segments, likely due to insulation effects of the carried backpack. During lifting, weak correlations were primarily observed in the upper and lower limbs, which were more actively engaged. Time-series analysis further showed that skin temperatures in the head, chest, shoulders, armpits, forearms, thighs, and feet remained relatively stable, while the back, pelvis, hands, and calves displayed consistent declines, indicating insufficient insulation in these areas. Thermal perception results aligned with objective measurements. Hiking under severe-cold conditions was perceived as more thermally comfortable, whereas lifting induced colder sensations in the extremities and a warmer feeling in the torso. These findings provide an important reference for the targeted design of cold-protective equipment and offer practical insights for improving thermal safet in high-altitude, low-temperature environments.