Explore the vast range of titles available.

This book provides fundamental concepts in human thermal physiology and their applications in general public, occupational, military, and athletics settings from the biometeorological perspective. The book includes a section on human physiology, epidemiology and special considerations in aforementioned populations, and behavioral and technological adjustments people may take to combat thermal environmental stress and safeguard their health. The book is the first of its kind to compile multiple disciplines--human physiology, climatology, and medicine--in one to provide fundamental concepts in human thermal physiology and their applications in general public, occupational, military, and athletics settings from the biometeorological perspective; Developed by experts, scientists, and physicians from exercise physiology, climatology, public health, sports medicine, and military medicine; Highlights special considerations and applications of thermal physiology to general public, occupational, military, and athletics settings.

Daily weather conditions for an entire city are usually represented by a single weather station, often located at a nearby airport. This resolution of atmospheric data fails to recognize the microscale climatic variability associated with land use decisions across and within urban neighborhoods. This study uses heat index, a measure of the combined effects of temperature and humidity, to assess the variability of heat exposure from ten weather stations across four urban neighborhoods and two control locations (downtown and in a nearby nature center) in Knoxville, Tennessee, USA. Results suggest that trees may negate a portion of excess urban heat, but are also associated with greater humidity. As a result, the heat index of locations with more trees is significantly higher than downtown and areas with fewer trees. Trees may also reduce heat stress by shading individuals from incoming radiation, though this is not considered in this study. Greater amounts of impervious surfaces correspond with reduced evapotranspiration and greater runoff, in terms of overall mass balance, leading to a higher temperature, but lower relative humidity. Heat index and relative humidity were found to significantly vary between locations with different tree cover and neighborhood characteristics for the full study time period as well as for the top 10% of heat index days. This work demonstrates the need for high-resolution climate data and the use of additional measures beyond temperature to understand urban neighborhood exposure to extreme heat, and expresses the importance of considering vulnerability differences among residents when analyzing neighborhood-scale impacts.

Downscaling methods are critical in efficiently generating high‐resolution atmospheric data. However, state‐of‐the‐art statistical or dynamical downscaling techniques either suffer from the high computational cost of running a physical model or require high‐resolution data to develop a downscaling tool. Here, we demonstrate a recently proposed zero‐shot super‐resolution method, the Fourier neural operator (FNO), to efficiently perform downscaling without the need for high‐resolution data. Because the FNO learns dynamics in Fourier space, FNO is a resolution‐invariant emulator; it can be trained at a coarse resolution and produces emulation at any high resolution. We applied FNO to downscale a 4‐km resolution Weather Research and Forecasting (WRF) Model simulation of near‐surface heat‐related variables over the Great Lakes region. The FNO is driven by the atmospheric forcings and topographic features used in the WRF model at the same resolution. We incorporated a physics‐constrained loss in FNO by using the Clausius–Clapeyron relation to better constrain the relations among the emulated states. Trained on merely 600 WRF snapshots at 4‐km resolution, the FNO shows comparable performance with a widely‐used convolutional network, U‐Net, achieving averaged modified Kling–Gupta Efficiency of 0.88 and 0.94 on the test data set for temperature and pressure, respectively. We then employed the FNO to produce 1‐km emulations to reproduce the fine climate features. Further, by taking the WRF simulation as ground truth, we show consistent performances at the two resolutions, suggesting the reliability of FNO in producing high‐resolution dynamics. Our study demonstrates the potential of using FNO for zero‐shot super‐resolution in generating first‐order estimation on atmospheric modeling. Plain Language Summary High‐resolution climate estimates are crucial for applications like examining heat exposure in populated areas. Downscaling from lower‐resolution estimates is one popular technique for obtaining these estimates. However, developing downscaling tools usually requires expensive computation or difficult‐to‐obtain data; they rely on either numerically solving a physical model or using a pair of existing high‐ and low‐resolution data. To address this issue, we demonstrated a novel deep learning model that can generate high‐resolution results from only low‐resolution data. Our study successfully applied this method to downscale near‐surface heat‐related variables of the Weather Research and Forecasting simulation to 1‐km resolution over the Great Lakes region. Key Points We used the Fourier neural operator (FNO) to perform zero‐shot super‐resolution on near‐surface heat‐related estimates Incorporating a physics‐constrained loss based on the Clausius–Clapeyron equation improves the emulation performance of the trained FNO Trained on a 4‐km Weather Research and Forecasting simulation, the FNO generates a 1‐km emulation that captures fine‐grained climate features induced by topography

Heat exposure and heat stress/strain is a concern for many workers. There is increasing interest in potential chronic health effects of occupational heat exposure, including cancer risk. We examined potential associations of occupational heat exposure and colorectal cancer (CRC) risk in a large Spanish multi-case--control study. We analyzed data on 1198 histologically confirmed CRC cases and 2690 frequency-matched controls. The Spanish job-exposure matrix, MatEmEsp, was used to assign heat exposure estimates to the lifetime occupations of participants. Three exposure indices were assessed: ever versus never exposed, cumulative exposure and duration (years). We estimated odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression adjusting for potential confounders. Overall, there was no association of ever, compared with never, occupational heat exposure and CRC (OR 1.09, 95% CI 0.92-1.29). There were also no associations observed according to categories of cumulative exposure or duration, and there was no evidence for a trend. There was no clear association of ever occupational heat exposure and CRC in analysis conducted among either men or women when analyzed separately. Positive associations were observed among women in the highest categories of cumulative exposure (OR 1.81, 95% CI 1.09-3.03) and duration (OR 2.89, 95% CI 1.50-5.59) as well as some evidence for a trend (P<0.05). Overall, this study provides no clear evidence for an association between occupational heat exposure and CRC.

BackgroundCorrect evaluation of safe heat exposure distance (SHED) in wildland fire environments improves the safety and efficiency of firefighting operation. However, there is a lack of standard test method for the SHED, let alone the influencing factors of the SHED.AimsThe aim of this study was to develop a novel method to examine the SHED by considering clothing and fire factors under thermal radiation condition.MethodsWe developed a new experimental apparatus for evaluating the SHED of firefighters in fire environments. The testing accuracy and repeatability was verified by calibration and measurement results. The evaluation method was used to investigate the influences of heating source temperature and fabric combination on the SHED, and reveal the relationship between the SHED and safe heat exposure time (SHET).Key resultsThe results showed that there was a significant positive correlation between the heating source temperature and the SHED. When the heating source temperature increased from 200 to 550°C, the SHED of three single-layer fabrics increased by more than 1.23 times. The SHED was negatively correlated with the reflectance, grammage and thickness of the fabric. The SHET increased with the heating source distance, and the rising rate increased gradually.ImplicationsThe findings obtained in this study can be used to provide theoretical support for determining the SHED during fire rescue, and to help engineer clothing that provides higher protection for firefighters.

Extreme urban heat is a powerful environmental stressor which poses a significant threat to human health and well-being. Exacerbated by the urban heat island phenomenon, heat events are expected to become more intense and frequent as climate change progresses, though we have limited understanding of the impact of such events on vulnerable populations at a neighborhood or census block group level. Focusing on the City of Portland, Oregon, this study aimed to determine which socio-demographic populations experience disproportionate exposure to extreme heat, as well as the level of access to refuge in the form of public cooling centers or residential central air conditioning. During a 2014 heat wave, temperature data were recorded using a vehicle-traverse collection method, then extrapolated to determine average temperature at the census block group level. Socio-demographic factors including income, race, education, age, and English speaking ability were tested using statistical assessments to identify significant relationships with heat exposure and access to refuge from extreme heat. Results indicate that groups with limited adaptive capacity, including those in poverty and non-white populations, are at higher risk for heat exposure, suggesting an emerging concern of environmental justice as it relates to climate change. The paper concludes by emphasizing the importance of cultural sensitivity and inclusion, in combination with effectively distributing cooling centers in areas where the greatest burden befalls vulnerable populations.

We use a suite of decadal-length regional climate simulations to quantify potential changes in population-weighted heat and cold exposure in 47 US metropolitan regions during the 21st century. Our results show that population-weighted exposure to locally defined extreme heat (i.e., “population heat exposure”) would increase by a factor of 12.7–29.5 under a high-intensity greenhouse gas (GHG) emissions and urban development pathway. Additionally, end-of-century population cold exposure is projected to rise by a factor of 1.3–2.2, relative to start-of-century population cold exposure. We identify specific metropolitan regions in which population heat exposure would increase most markedly and characterize the relative significance of various drivers responsible for this increase. The largest absolute changes in population heat exposure during the 21st century are projected to occur in major US metropolitan regions like New York City (NY), Los Angeles (CA), Atlanta (GA), and Washington DC. The largest relative changes in population heat exposure (i.e., changes relative to start-of-century) are projected to occur in rapidly growing cities across the US Sunbelt, for example Orlando (FL), Austin (TX), Miami (FL), and Atlanta. The surge in population heat exposure across the Sunbelt is driven by concurrent GHG-induced warming and population growth which, in tandem, could strongly compound population heat exposure. Our simulations provide initial guidance to inform the prioritization of urban climate adaptation measures and policy.

Background Occupational exposure to extreme heat without sufficient protection may not only increase the risk of heat-related illnesses and injuries but also compromise economic productivity. With predictions of more frequent and intense bouts of hot weather, workplace heat exposure is presenting a growing challenge to workers’ health and safety. This study aims to investigate workers’ perceptions and behavioural responses towards extreme heat exposure in a warming climate. Methods A cross-sectional questionnaire survey was conducted in 2012 in South Australia among selected outdoor industries. Workers’ heat risk perceptions were measured in the following five aspects: concerns about heat exposure, attitudes towards more training, policy and guideline support, the adjustment of work habits, and degree of satisfaction of current preventive measures. Bivariate and multivariate logistic regression analyses were used to identify factors significantly associated with workers’ heat perceptions. Results A total of 749 respondents participated in this survey, with a response rate of 50.9 %. A little more than half (51.2 %) of respondents were moderately or very much concerned about workplace heat exposure. Factors associated with workers’ heat concerns included age, undertaking very physically demanding work, and the use of personal protective equipment, heat illness history, and injury experience during hot weather. Less than half (43.4 %) of the respondents had received heat-related training. Workers aged 25–54 years and those with previous heat-related illness/injury history showed more supportive attitudes towards heat-related training. The provision of cool drinking water was the most common heat prevention measure. A little more than half (51.4 %) of respondents were satisfied with the current heat prevention measures. About two-thirds (63.8 %) of respondents agreed that there should be more heat-related regulations and guidelines for working during very hot weather. More than two-thirds (68.8 %) of the respondents were willing to adjust their current work habits to adapt to the likely increasing extreme heat, especially those with previous heat illness experience. Conclusions The findings suggest a need to strengthen workers’ heat risk awareness and refine current heat prevention strategies in a warming climate. Further heat educational programmes and training should focus on those undertaking physically demanding work outdoors, in particular young workers and those over 55 years with low education levels.

A robust estimation of how heat stress is changing worldwide is complicated by the variety of heat stress metrics in use. This study compares heat stress changes between 1979–2000 and 2001–2023 across five commonly used metrics calculated with ERA5 reanalysis data. We identify regions where all metrics indicate significant increases in heat stress, highlighting a high‐certainty need for urgent adaptation efforts. Conversely, we also find regions where metrics disagree, even on the direction of change. The substantial inter‐metric spread in population heat exposure is comparable to the spread across five reanalysis products and 17 CMIP6 climate models. We attribute these inter‐metric discrepancies to differing temperature‐humidity relative weight across metrics. Our findings highlight metric choice as a significant source of uncertainty in heat stress projections and emphasize the need for a better understanding of the suitability of different metrics for specific climate regimes and impacts.

Global climate is changing as a result of anthropogenic warming, leading to higher daily excursions of temperature in cities. Such elevated temperatures have great implications on human thermal comfort and heat stress, which should be closely monitored. Current methods for heat exposure assessments (surveys, microclimate measurements, and laboratory experiments), however, present several limitations: measurements are scattered in time and space and data gathered on outdoor thermal stress and comfort often does not include physiological and behavioral parameters. To address these shortcomings, Project Coolbit aims to introduce a human-centric approach to thermal comfort assessments. In this study, we propose and evaluate the use of wrist-mounted wearable devices to monitor environmental and physiological responses that span a wide range of spatial and temporal distributions. We introduce an integrated wearable weather station that records (a) microclimate parameters (such as air temperature and humidity), (b) physiological parameters (heart rate, skin temperature and humidity), and (c) subjective feedback. The feasibility of this methodology to assess thermal comfort and heat stress is then evaluated using two sets of experiments: controlled-environment physiological data collection, and outdoor environmental data collection. We find that using the data obtained through the wrist-mounted wearables, core temperature can be predicted non-invasively with 95 percent of target attainment within ±0.27 °C. Additionally, a direct connection between the air temperature at the wrist ( T a , w ) and the perceived activity level (PAV) of individuals was drawn. We observe that with increased T a , w , the desire for physical activity is significantly reduced, reaching ‘Transition only’ PAV level at 36 °C. These assessments reveal that the wearable methodology provides a comprehensive and accurate representation of human heat exposure, which can be extended in real-time to cover a large spatial distribution in a given city and quantify the impact of heat exposure on human life.