Search Results (567)

Apiculture is among the most weather-dependent sectors of agriculture; however, quantifying the impact of meteorological factors remains challenging. Beehive weight has long been recognized as an important indicator of colony health, strength, and food availability, as well as foraging activity. Atmospheric influences on hive weight dynamics have been a subject of research since the early 20th century. This study aims to estimate hourly hive weight variation by applying linear time-series models to hive weight data collected from active apiaries during intensive foraging periods, considering atmospheric predictors. We employed a rolling 24 h forward ARIMAX and SARIMAX model, incorporating meteorological variables as exogenous factors. The median estimates for the study period resulted in model RMSE values of 0.1 and 0.3 kg/h. From numerous meteorological variables, the hourly maximum temperature was found to be the most significant predictor. ARIMAX model results also exhibited a strong diurnal cycle, pointing out the weather-driven seasonality of hive weight variations. Full article

Urban residential design influences local microclimates and human thermal comfort. This study combines empirical microclimate data with remotely sensed data on tree canopy cover, housing lot size, surface permeability, and roof colour to examine thermal differences between three newly built and three established residential suburbs in Western Sydney, Australia. Established areas featured larger housing lots and mature street trees, while newly developed suburbs had smaller lots and limited vegetation cover. Microclimate data were collected during summer 2021 under both heatwave and non-heatwave conditions in full sun, measuring air temperature, relative humidity, wind speed, and wet-bulb globe temperature (WBGT) as an index of heat stress. Daily maximum air temperatures reached 42.7 °C in new suburbs, compared to 39.3 °C in established ones (p < 0.001). WBGT levels during heatwaves were in the “extreme caution” category in new suburbs, while remaining in the “caution” range in established ones. These findings highlight the benefits of larger green spaces, permeable surfaces, and lighter roof colours in the context of urban heat exposure. Maintaining mature trees and avoiding dark roofs can significantly reduce summer heat and improve outdoor thermal comfort across a range of conditions. Results of this work can inform bottom-up approaches to climate-responsive urban design where informed homeowners can influence development outcomes. Full article

The urban heat island (UHI) effect significantly impacts urban environments, particularly along roads, a phenomenon known as urban linear heat (UHI_ULI). Numerous factors contribute to roads influencing the UHI_ULI; however, effective mitigation strategies remain a challenge. This study examines the relationship between canopy cover percentage, normalized difference vegetation index, land use types, and three road typologies (local, regional, and state) with land surface temperature. This study is based on data from the city of Adelaide, Australia, using spatial analysis, and statistical modelling. The results reveal strong negative correlations between land surface temperature and both canopy cover percentage and normalized difference vegetation index. Additionally, land surface temperature tends to increase with road width. Among land use types, land surface temperature varies from highest to lowest in the order of parkland, industrial, residential, educational, medical, and commercial areas. Notably, the combined influence of the road typology and land use produces varying effects on land surface temperature. Canopy cover percentage and normalized difference vegetation index consistently serve as dominant cooling factors. The results highlight a complex interplay between built and natural environments, emphasizing the need for multi-factor analyses and a framework based on the local climate and the type of roads (local, regional, and state) to effectively evaluate UHI_ULI mitigation approaches. Full article

Urban outdoor thermal comfort (OTC) has become an increasingly critical issue under the pressures of urbanization and climate change. Comparative analyses of urban blocks with distinct spatial morphologies are essential for identifying OTC issues and proposing targeted optimization strategies. However, existing studies predominantly rely on microclimate numerical simulations, while comparative assessments of OTC from the human thermal perception perspective remain limited. This study employs the thermal walk method, integrating microclimatic measurements with thermal perception questionnaires, to conduct on-site OTC investigations across three urban blocks with contrasting spatial morphologies—a business district (BD), a residential area (RA), and a historical neighborhood (HN)—in Beijing, a hot summer and cold winter climate city. The results reveal substantial OTC differences among the blocks. However, these differences demonstrated great seasonal and temporal variations. In summer, BD exhibited the best OTC (mTSV = 1.21), while HN performed the worst (mTSV = 1.72). In contrast, BD showed the poorest OTC in winter (mTSV = −1.57), significantly lower than HN (−1.11) and RA (−1.05). This discrepancy was caused by the unique morphology of different blocks. The sky view factor emerged as a more influential factor affecting OTC over building coverage ratio and building height, particularly in RA (r = 0.689, p < 0.01), but its impact varied by block, season, and sunlight conditions. North–South streets generally perform better OTC than East–West streets, being 0.26 units cooler in summer and 0.20 units warmer in winter on the TSV scale. The study highlights the importance of incorporating more applicable physical parameters to optimize OTC in complex urban contexts and offering theoretical support for designing climate adaptive urban spaces. Full article

The Brazilian savanna, South America’s second-largest biome, is vital to Brazil’s economy but has suffered from environmental degradation due to unregulated agricultural and urban expansion. This study assesses climate change in the biome from 1961 to 2021 using the Köppen climate classification, drought indices, historical trend analyses, and the climatological water balance. Fourteen municipalities across the biome were analyzed. According to the Köppen classification, most municipalities were identified as Aw (tropical with dry winters) and Am (tropical monsoon), with Dourados, MS, and Sapezal, MT, alternating between Am and Aw. The standardized precipitation index (SPI) revealed changes in rainfall distribution. The Mann–Kendall test detected rising air temperatures in 13 of the 14 municipalities, with Sen’s slope ranging from 0.0156 to 0.0605 °C per year. Rainfall decreased in seven municipalities, with decreases from −4.54 to −12.77 mm per year. The climatological water balance supported the observed decrease in precipitation. The results indicated a clear warming trend and declining rainfall in most of the Brazilian savanna, highlighting potential challenges for water availability in the face of ongoing climate change. Full article

Climate change is one of the most important current threats to global health. Outdoor workers are among the most vulnerable people to its effects. The aim of this systematic review is to assess the occupational risks related to climate change, investigating health outcomes in outdoor workers and estimating its impact in the occupational context. The review was performed following PRISMA guidelines, screening three databases (PubMed, Web of Science, and Scopus). Studies written in English or Italian languages, performed on outdoor workers, assessing occupational risks linked to climate change, and reporting on health outcomes were included. A quality assessment was performed using the Newcastle–Ottawa Scale. Thirteen studies were included in the review, performed mostly on construction (seven studies, 53.8%) and agricultural (five studies, 38.5%) workers. Twelve of the included studies (92.3%) reported on occupational risks related to heat stress, one on the effects of cold weather. Four studies (30.8%) reported a high prevalence of heat-related symptoms, ranging from 64.0% to 90.3% of workers. This systematic review highlights heat-related stress in outdoor workers as an important occupational risk, but it also underlines an important gap in scientific knowledge regarding other occupational risks relating to climate change. Full article

This study systematically reviews the development and application of remote sensing technology in monitoring and evaluating urban heat island (UHI) effects. The urban heat island effect, characterized by significantly higher temperatures in urban areas compared to surrounding rural regions, has become a widespread environmental issue globally, with impacts spanning public health, energy consumption, ecosystems, and social equity. The paper first analyzes the formation mechanisms and impacts of urban heat islands, then traces the evolution of remote sensing technology from early traditional platforms such as Landsat and NOAA-AVHRR to modern next-generation systems, including the Sentinel series and ECOSTRESS, emphasizing improvements in spatial and temporal resolution and their application value. At the methodological level, the study systematically evaluates core algorithms for land surface temperature extraction and heat island intensity calculation, compares innovative developments in multi-source remote sensing data integration and fusion techniques, and establishes a framework for accuracy assessment and validation. Through analyzing the heat island differences between metropolitan areas and small–medium cities, the relationship between urban morphology and thermal environment, and regional specificity and global universal patterns, this study revealed that the proportion of impervious surfaces is the primary driving factor of heat island intensity while simultaneously finding that vegetation cover exhibits significant cooling effects under suitable conditions, with the intensity varying significantly depending on vegetation types, management levels, and climatic conditions. In terms of applications, the paper elaborates on the practical value of remote sensing technology in identifying thermally vulnerable areas, green space planning, urban material optimization, and decision support for UHI mitigation. Finally, in light of current technological limitations, the study anticipates the application prospects of artificial intelligence and emerging analytical methods, as well as trends in urban heat island monitoring against the backdrop of climate change. The research findings not only enrich the theoretical framework of urban climatology but also provide a scientific basis for urban planners, contributing to the development of more effective UHI mitigation strategies and enhanced urban climate resilience. Full article

This study investigates the variations in the Universal Thermal Climate Index (UTCI) calculated based on meteorological data from six synoptic stations across the Central Region of Poland from 2001 to 2024, focusing on spatial and temporal trends in thermal stress. The average annual UTCI was found to be 7.7 °C, indicating “slight cold stress,” with regional differences. Higher values were recorded in the west and northwest compared to lower values in the southeast. Maximum UTCI values associated with “very strong heat stress” exceeded 40.0 °C, while minimum values denoting “extreme cold stress” occurred in eastern cities more often. A linear trend analysis revealed a general increase in UTCI values across all stations, varying from 0.6 °C to 1.8 °C per decade, and showed distinct positive trends for heat stress categories, particularly “strong heat stress.” In contrast, a decrease in “strong cold stress” was observed. Favorable bioclimatic conditions, defined as “comfort”, predominated during most months, especially from April to October, while extreme thermal conditions were infrequently recorded. This research shows significant changes in thermal comfort and stress patterns, highlighting regional disparities and the implications for public health and urban planning in response to evolving bioclimatic conditions. Full article

This study aims to analyze how the climatic conditions in the city of João Pessoa, Brazil, influence sustainable tourism, with a specific focus on Climate–Tourism/Transfer–Information–Scheme (CTIS), Physiologically Equivalent Temperature (PET), and rainfall patterns. It also compares these aspects with those of Salvador and Rio de Janeiro to identify climatic patterns, local challenges, and adaptive strategies relevant to the growing tourism context, based on hourly and monthly climate data from 2014 to 2024. The results show that João Pessoa presents a more stable thermal regime with fewer extreme heat events, yet consistently higher daytime PET values, especially between 9:00 and 15:00, throughout the year. The city also experiences a greater frequency of moderate-to-heavy rainfall during its defined wet season (April to July), often influenced by low-predictability atmospheric systems such as Easterly Wave Disturbances (EWDs). CTIS results confirm high climatic suitability for tourism and recreation during the dry season but reduced suitability during the rainy season. These findings suggest that integrating climate adaptation strategies into tourism planning, such as diversifying attractions beyond sun-and-beach tourism and improving real-time climate communication, may help reduce the impact of seasonal variability on visitor experience. Full article

Urbanization and climate change present increasing challenges to outdoor human thermal comfort, particularly in university campuses where academic, social, and recreational activities converge. This study assesses microclimatic risk factors along the main avenue of the NOVA FCT campus by analyzing outdoor human thermal comfort using the physiologically equivalent temperature (PET) and modified PET (mPET) indices. Field measurements of air temperature, humidity, wind velocity, and radiation were conducted at multiple Points Of Interest (POIs) to evaluate thermal stress levels and identify critical zones of discomfort. Results indicate significant spatial and temporal variations in thermal stress, with sun-exposed areas (G2) experiencing PET values exceeding 50 °C, during peak summer hours, while shaded locations (G1) showed substantial thermal relief (PET reductions up to 27 °C between G1 and G2 POIs). Wind velocity and urban morphology played crucial roles in modulating microclimatic conditions. Wind velocity above 2.0 m/s was associated with perceptible thermal relief (3–8 °C PET/mPET reduction), especially in narrow, shaded passages. Significant spatial variability was observed, linked to differences in urban morphology, surface materials, and vegetation coverage. This research provides actionable insights for urban planners and campus administrators, contributing to the development of more sustainable and thermally comfortable outdoor environments in educational settings. Full article

The climate of the Hungarian lowland (Central European region, Pannonian Plain area) can be characterized by Köppen’s Cfb climate formula (C—warm temperate, f—no seasonality in the annual course of precipitation, b—warm summer). This characterization does not provide information about the human thermal load and thermal perception. The aim of this work is to fill this gap. We focused on the morning, clear-sky periods of the day, when the heat supply provided by the weather is the lowest. The human thermal load of clear-sky mornings was estimated using the new clothing thermal resistance–operative temperature (r_cl–T_o) model. In contrast to IREQ-type (Required Clothing Insulation) models, this model parametrizes the total metabolic heat flux density (M) as a function of anthropometric data (body mass, height, sex, age). In the simulations, the selected persons walk (M values range between 135 and 170 W m⁻²) or stand (M values range between 84 and 96 W m⁻²), while their body mass index (BMI) varies between 25 and 37 kg m⁻². The following main results should be highlighted: (1) Human activity has a significant impact on r_cl; it ranges between 0 and 3.5 clo during walking and between 0 and 6.7 clo during standing. (2) The interpersonal variability of r_cl increases with increasing heat deficit accordingly; in the case of a walking person, it is around 1 clo in the largest heat deficits and around 0 clo in the smallest heat deficits. Since, in general, anticyclones increase the heat deficit while cyclones reduce it, extreme thermal loads are associated with anticyclones. It should be mentioned that the interpersonal variability of the human thermal load cannot be analyzed without databases containing people’s anthropometric data. Full article

This study investigates the relationship between Green View Index (GVI) and street thermal environment in Hangzhou’s main urban area during summer, quantifying urban greenery’s impact on diurnal/nocturnal thermal conditions to inform urban heat island mitigation strategies. Multi-source data (3D morphological metrics, LCZ classifications, mobile measurements) were integrated with deep learning-derived street-level GVI through image analysis. A random forest-multiple regression hybrid model evaluated spatiotemporal variations and GVI impacts across time, street orientation, and urban-rural gradients. Key findings include: (1) Urban street Ta prediction model: Daytime model: R² = 0.54, RMSE = 0.33 °C; Nighttime model: R² = 0.71, RMSE = 0.42 °C. (2) GVI shows significant inverse association with temperature, A 0.1 unit increase in GVI reduced temperatures by 0.124°C during the day and 0.020 °C at night. (3) Orientation effects: North–south streets exhibit strongest cooling (1.85 °C daytime reduction), followed by east–west; northeast–southwest layouts show negligible impact; (4) Canyon geometry: Low-aspect canyons (H/W < 1) enhance cooling efficiency, while high-aspect canyons (H/W > 2) retain nocturnal heat despite daytime cooling; (5) Urban-rural gradient: Cooling peaks in urban-fringe zones (10–15 km daytime, 15–20 km nighttime), contrasting with persistent nocturnal warmth in urban cores (0–5 km); (6) LCZ variability: Daytime cooling intensity peaks in LCZ3, nighttime in LCZ6. These findings offer scientific evidence and empirical support for urban thermal environment optimization strategies in urban planning and landscape design. We recommend dynamic coupling of street orientation, three-dimensional morphological characteristics, and vegetation configuration parameters to formulate differentiated thermal environment design guidelines, enabling precise alignment between mitigation measures and spatial context-specific features. Full article

This study examines the climate adaptability of traditional Hani ‘Mushroom Houses’ located in the rice terrace region of Honghe Hani Autonomous Prefecture, Yunnan, China. By analyzing 30 years of meteorological data, the study identifies the local climatic characteristics of high temperatures, high humidity, and significant diurnal temperature variations. The thermal comfort voting method was used to establish a quantitative relationship between the Physiological Equivalent Temperature (PET) index and residents’ subjective thermal perceptions, thereby assessing seasonal variations in thermal comfort. Field measurements of indoor and outdoor temperature, humidity, and wind speed were conducted in May and December 2023 to evaluate thermal interactions between rooms. This study demonstrated: (1) the critical roles of building orientation (e.g., northwest-facing design), functional layout (e.g., multi-story zoning), and structural forms (e.g., thick walls, thatched roofs) in regulating temperature and humidity. (2) Confirmed that Hani ‘Mushroom Houses’ stabilize indoor environments through passive strategies, including material selection (wood, rammed earth), natural ventilation (cross-draft design), and spatial organization (climate-buffering storage layers). (3) Provided empirical evidence for optimizing traditional dwellings (e.g., enhanced insulation, ventilation improvements) and advancing sustainable practices in similar climatic regions. Full article

Human populations are scattered worldwide and live under widely different climates. Like other mammals, humans respond to climatic influences through various processes involving behavior, physiology, and various forms of adaptation. Human populations can be explored in investigating patterns of adaptation because many of their biological attributes have been monitored for over a century. Here, we evaluated the association between several thermal indices and human birth weight (BW) and offered some initial observations on the temporal integration of thermal cues associated with pregnancy outcomes. We compiled three datasets: (1) a dataset with global coverage of recent BWs; (2) an extended time series for seven European countries; and (3) a time series for four countries in equatorial Africa. Each dataset was analyzed for associations between BW and mean annual temperature, as well as seasonal and daily amplitudes. Mean annual temperatures, as well as seasonal and daily amplitudes, delivered consistent and comparable impacts in our analyses. The thermal indices can explain approx. 80% of the global variation in BW and 25–50% of the BW variation in time series covering the last 70 to 120 years. Mean BW in larger aggregates of humans (i.e., millions) is associated with several thermal indices, likely associated with systematic differences in proximate factors (e.g., maternal height, weight, food intake) between populations. This study underlines the diverse impact of the thermal environment on human reproduction, but it also underscores that this impact is less pronounced for differences in mean BW with respect to different communities, and it is possibly undetectable and/or irrelevant with respect to differences between individuals. Full article