The objective of this paper was to verify the applicability of statistical learning (SL) compared to human reasoning with respect to the Universal Thermal Climate Index (UTCI), a complex tool for the assessment of outdoor thermal stress. UTCI is an equivalent temperature index based on the 48-dimensional output of an advanced model of human thermoregulation formed by 12 variables at four consecutive 30-minute intervals, which were calculated for 105642 thermal conditions from extreme cold to extreme heat. Comparing the performance of SL algorithms to the results accomplished by an international endeavor involving more than 40 experts from 23 countries, we found that random forests and k-nearest neighbors closely predicted UTCI values, but that clustering applied after dimension reduction algorithms (principal component analysis and t-distributed stochastic neighbor embedding) were inadequate for risk assessment in relation to the UTCI stress categories. This indicates a potential supportive role for SL, as it will not (yet) fully replace the bio-meteorological expert knowledge.

This study concerns the application of statistical learning (SL) in thermal stress assessment compared to the results accomplished by an international expert group when developing the Universal Thermal Climate Index (UTCI). The performance of diverse SL algorithms in predicting UTCI equivalent temperatures and in thermal stress assessment was assessed by root mean squared errors (RMSE) and Cohen’s kappa. A total of 48 predictors formed by 12 variables at four consecutive 30 min intervals were obtained as the output of an advanced human thermoregulation model, calculated for 105,642 conditions from extreme cold to extreme heat. Random forests and k-nearest neighbors closely predicted UTCI equivalent temperatures with an RMSE about 3 °C. However, clustering applied after dimension reduction (principal component analysis and t-distributed stochastic neighbor embedding) was inadequate for thermal stress assessment, showing low to fair agreement with the UTCI stress categories (Cohen’s kappa < 0.4). The findings of this study will inform the purposeful application of SL in thermal stress assessment, where they will support the biometeorological expert.

It is generally accepted that acclimation results in a lower core temperature during heat exposure. The reduction of core temperature is explained by physiological mechanisms that reduce heat storage via improved heat loss mechanisms. On the other hand it is hypothesized that acclimation results in a decrease of resting core temperature which might be partly responsible for the attenuation of core temperature during heat exposure. The aim of the present investigation was to examine whether there exists a difference in resting core temperature before and after acclimation. All in all the data support the hypothesis that acclimation causes a reduction in resting core temperature. The results are discussed with respect to their practical relevance.

Increasing wind speed alleviates physiological heat strain; however, health policies have advised against using ventilators or fans under heat wave conditions with air temperatures above the typical skin temperature of 35 °C. Recent research, mostly with sedentary participants, suggests mitigating the effects of wind at even higher temperatures, depending on the humidity level. Our study aimed at exploring and quantifying whether such results are transferable to moderate exercise levels, and whether the Universal Thermal Climate Index (UTCI) reproduces those effects. We measured heart rates, core and skin temperatures, and sweat rates in 198 laboratory experiments completed by five young, semi-nude, heat-acclimated, moderately exercising males walking the treadmill at 4 km/h on the level for three hours under widely varying temperature-humidity combinations and two wind conditions. We quantified the cooling effect of increasing the wind speed from 0.3 to 2 m/s by fitting generalized additive models predicting the physiological heat stress responses depending on ambient temperature, humidity, and wind speed. We then compared the observed wind effects to the assessment performed by the UTCI. Increasing the wind speed lowered the physiological heat strain for air temperatures below 35 °C, but also for higher temperatures with humidity levels above 2 kPa water vapor pressure concerning heart rate and core temperature, and 3 kPa concerning skin temperature and sweat rate, respectively. The UTCI assessment of wind effects correlated positively with the observed changes in physiological responses, showing the closest agreement (r = 0.9) for skin temperature and sweat rate, where wind is known for elevating the relevant convective and evaporative heat transfer. These results demonstrate the potential of the UTCI for adequately assessing sustainable strategies for heat stress mitigation involving fans or ventilators, depending on temperature and humidity, for moderately exercising individuals.

For time- and cost-efficient heat stress assessment procedures at workplaces or in experimental studies, short-time measurement periods (e.g. 1 h) are sometimes employed in lieu of whole shift observations assuming that the short time period will provide valid figures of equilibrium physiological responses. We studied the influence of exposure duration on physiological heat strain considering the modifying effects of clothing and heat acclimation using a database of 564 climatic chamber exposures performed by 28 young males under heat stress conditions with widely varying air temperature and humidity levels. We compared heart rates, rectal and mean skin temperatures, and sweat rates recorded after 1 h with the values averaged over the third hour of exposure representing steady-state. One-hour measurements agreed with equilibrium values for rather low strain levels only, with heart rates below 100 bpm and rectal temperatures below 37.2 °C. On average, one-hour values underestimated all heat strain parameters. This underestimation error was only moderately influenced by clothing and heat acclimation status, but increased significantly with air temperature and humidity, reaching considerable magnitude under hot-humid conditions associated with elevated heat strain. Regression analyses of the prediction error depending on the equilibrium response revealed that underestimation increased with equilibrium strain level. This correlation was strongest for heart rate and core temperature, and was shown to potentially cause a misclassification of hazardous working conditions as safe by given heat strain criteria. Practical Relevance : The severe underestimation of heat strain due to short measurement periods, as observed under hot-humid conditions and/or when associated with high physiological strain, will immediately impact the exposed personnel, but will also inform occupational health professionals and standard writers regarding the heat stress assessment for work shifts with high activity levels or with protective clothing.

Heat acclimation (HA) is an essential modifier of physiological strain when working or exercising in the heat. It is unknown whether HA influences the increase of energy expenditure (Q(10) effect) or heart rate (thermal cardiac reactivity TCR) due to increased body temperature. Therefore, we studied these effects using a heat strain database of climatic chamber experiments performed by five semi-nude young males in either non-acclimated or acclimated state. Measured oxygen consumption rate (VO2), heart rate (HR), and rectal temperature (T-re) averaged over the third hour of exposure were obtained from 273 trials in total. While workload (walking 4 km/h on level) was constant, heat stress conditions varied widely with air temperature 25-55 degrees C, vapor pressure 0.5-5.3 kPa, and air velocity 0.3-2 m/s. HA was induced by repeated heat exposures over a minimum of 3 weeks. Non-acclimated experiments took place in wintertime with a maximum of two exposures per week. The influence of T-re and HA on VO2 and HR was analyzed separately with mixed model ANCOVA. Rising T-re significantly (p < 0.01) increased both VO2 (by about 7% per degree increase of T-re) and HR (by 39-41 bpm per degree T-re); neither slope nor intercept depended significantly on HA (p > 0.4). The effects of T-re in this study agree with former outcomes for VO2 (7%/degrees C increase corresponding to Q(10) = 2) and for HR (TCR of 33 bpm/degrees C in ISO 9886). Our results indicate that both relations are independent of HA with implications for heat stress assessment at workplaces and for modeling heat balance.

The standard ISO 8996 provides methods for the determination of metabolic rate from measured oxygen consumption (MVO2), as well as simplified estimation algorithms based on heart rate (MHR). We quantified the accuracy of these methods by comparing MHR with MVO2 measured in 373 climatic chamber experiments under different workloads and widely varying heat stress conditions. While our results confirmed the 5% accuracy level for MVO2, MHR considerably overestimatedMVO2 due to the rise in core temperature concomitantly increasing heart rate by approximately 30 bpm/°C resulting in an overall error of 43%. After individually correcting for this bias the accuracy was 10-15% as stipulated by the standard. Thus, methods correcting for the thermal component of heart rate, e.g. by introducing intermittent resting periods of sufficient length of at least five min when investigating heat stress at workplaces, should become a mandatory element in the ongoing revision of the relevant standards.

The Universal Thermal Climate Index UTCI assesses the outdoor thermal environment based on the multi-node UTCI-Fiala-model of thermoregulation, which was coupled with a clothing model considering the clothing behaviour of an urban population. The applicability of UTCI to exercising, resting or occupational settings is currently limited by the assumed moderate activity level (2.3 MET) and the maximum exposure time of two hours. However, the high level of detail devoted to the modelling of the physiological and clothing system will allow for expanding UTCI to varying exposure times and activity levels, as will be demonstrated by this paper. We calculated UTCI adjustment terms for activity varying from a resting to a high (5 MET) level and for exposure duration covering an 8-hour shift length in 30-min steps. Simulations with the UTCI-Fiala model were performed using the adaptive UTCI-clothing model with air temperatures from -50°C to +50°C for UTCI reference climatic conditions. The adjustment terms indicated that thermal stress decreased with shorter exposure and increased with longer times, and that high activity increased heat stress, whereas low activity increased cold stress. Effect size was moderated by stress category with greater effects of activity and exposure time in the cold compared to moderate or warm climates. These results demonstrate UTCI's capabilities for a comprehensive assessment of dynamic thermal stress in occupational and other relevant outdoor settings. However, extensive simulations are still necessary to include the effects of special leisure and work clothes.

Q10 describes the influence of temperature on physiological processes as the ratio of the rate of a physiological process at a particular temperature to the rate at a temperature 10 °C lower [1]. In terms of rates of oxygen consumption (VO2) related to rectal temperatures (tre), this can be written as [2]: Q10 = (VO2/VO2,ref)10/(tre-tre,ref) (1a) or equivalently, VO2 = VO2,ref . Q10(tre-tre,ref)/10 (1b) Q10 varies between 2 and 3 in biological systems [2], and Q10 = 2 is applied in modelling the rate of metabolic heat production in relation to body temperature [3,4]. This paper aims to determine Q10 for the influence of body temperature on oxygen consumption for light work in warm environments.

The assessment of the thermal environment is one of the main issues in bioclimatic research, and more than 100 simple bioclimatic indices have thus far been developed to facilitate it. However, most of these indices have proved to be of limited applicability, and do not portray the actual impacts of thermal conditions on human beings. Indices derived from human heatbalance models (one-or two-node) have been found to offer a better representation of the environmental impact in question than do simple ones. Indeed, the new generation of multi-node models for human heat balance do allow full account to be taken of heat transfer and exchange, both within the human body and between the body surface and the surrounding air layer. In this paper, it is essential background information regarding the newly-developed Universal Thermal Climate Index UTCI that is presented, this in fact deriving from the Fiala multi-node model of human heatbalance. The UTCI is defined as the air temperature (Ta) of the reference condition causing the same model response as actual conditions. UTCI was developed in 2009 by virtue of international co-operation between leading experts in the areas of human thermophysiology, physiological modelling, meteorology and climatology. The necessary research for this had been conducted within the framework of a special commission of the International Society of Biometeorology (ISB) and European COST Action 730.

In COST Action 730, a multi-segmental thermophysiological model was used to describe physiological strain reactions for different climatic conditions in order to develop a 'Universal Thermal Climate Index' (UTCI). UTCI predictions for warm climates were compared with empirical data from the laboratory tests. The comparison was performed by means of equivalence lines within a psychrometric chart so that the combined influence of air temperature and humidity on physiological strain may be assessed. Within a reasonable regime of air temperatures and relative humidities (RH), the differences between simulated and measured values were as follows: for rectal temperatures below 0.3°C, for skin temperatures below 1.5°C, for sweat rates below 200 g/h and for heart rates (estimated from relative cardiac output) below 30 min−1. This characterises the validity of the model with respect to the description of the influence of heat and humidity on physiological strain. The same comparison to physiological data was also conducted for the equivalent temperature calculated for UTCI. In order to compare UTCI with other thermal indices used in occupational health, the physiological data have also been compared to equivalence lines of WBGT (Wet Bulb Globe Temperature) and PHS (Predicted Heat Strain) indices.

The Universal Thermal Climate Index (UTCI) aimed for a one-dimensional quantity adequately reflecting the human physiological reaction to the multi-dimensionally defined actual outdoor thermal environment. The human reaction was simulated by the UTCI-Fiala multi-node model of human thermoregulation, which was integrated with an adaptive clothing model. Following the concept of an equivalent temperature, UTCI for a given combination of wind speed, radiation, humidity and air temperature was defined as the air temperature of the reference environment, which according to the model produces an equivalent dynamic physiological response. Operationalising this concept involved (1) the definition of a reference environment with 50% relative humidity (but vapour pressure capped at 20 hPa), with calm air and radiant temperature equalling air temperature and (2) the development of a one-dimensional representation of the multivariate model output at different exposure times. The latter was achieved by principal component analyses showing that the linear combination of 7 parameters of thermophysiological strain (core, mean and facial skin temperatures, sweat production, skin wettedness, skin blood flow, shivering) after 30 and 120 min exposure time accounted for two-thirds of the total variation in the multi-dimensional dynamic physiological response. The operational procedure was completed by a scale categorising UTCI equivalent temperature values in terms of thermal stress, and by providing simplified routines for fast but sufficiently accurate calculation, which included look-up tables of pre-calculated UTCI values for a grid of all relevant combinations of climate parameters and polynomial regression equations predicting UTCI over the same grid. The analyses of the sensitivity of UTCI to humidity, radiation and wind speed showed plausible reactions in the heat as well as in the cold, and indicate that UTCI may in this regard be universally useable in the major areas of research and application in human biometeorology.

The UTCI-Fiala mathematical model of human temperature regulation forms the basis of the new Universal Thermal Climate Index (UTC). Following extensive validation tests, adaptations and extensions, such as the inclusion of an adaptive clothing model, the model was used to predict human temperature and regulatory responses for combinations of the prevailing outdoor climate conditions. This paper provides an overview of the underlying algorithms and methods that constitute the multi-node dynamic UTCI-Fiala model of human thermal physiology and comfort. Treated topics include modelling heat and mass transfer within the body, numerical techniques, modelling environmental heat exchanges, thermoregulatory reactions of the central nervous system, and perceptual responses. Other contributions of this special issue describe the validation of the UTCI-Fiala model against measured data and the development of the adaptive clothing model for outdoor climates.

Acclimation as an adaptive response of the human body to repeatedly occurring heat stress causes a reduction of core temperature (Tco) and heart rate (HR) at the end of heat exposure. The analysis of three acclimation series (WBGT =33.5°C) showed that the lowering of Tco and HR occurred already in the resting period preceding heat stress. The lowered resting values accounted for a substantial part of the beneficial effects of acclimation and may be mainly induced by the physical exercise, as a similar reduction of resting values was also observed under thermally neutral conditions. Expanding the database with short-term acclimation series revealed that the resting values were less reduced for females compared to males, but that the same relations between resting and final Tco and HR existed. The results further suggest that the reduction of resting Tco reflects long term effects of adaptation whereby the resting HR also depends on unspecific situational influences. The lowering of the initial values might be a suitable instrument when considering the effects of acclimation in thermoregulatory models for the assessment of heat stress at the workplace.

Four mine rescue brigadesmen performed three different standardized trainings in uncompensable heat stress with different equipment, clothing and climatic stress. The strain during these trainings may be considered as typical for training and missions of firemen, mine rescue brigadesmen and subjects working under protective clothing. – During ten years the diverse trainings were repeated. Heart rates and body temperatures were recorded throughout the exposures. A significant linear trend over time only was found for body mass (increase in three of the subjects). Specific physical fitness (fitness per body mass) as well as heart rate or body temperature showed no significant trend over time for initial or final values. The variability of the physiological strain is described in good approximation by normal distributions and shows quite a high magnitude. On base of the whole data set inter-individual components of variance are estimated by a 2-factorial ANOVA (person, time of measurement) with the factor time of measurement nested under the factor person. Confidence intervals for the estimated mean values and respectively, the calculation of the required number of measurements for a given confidence interval are determined by performing a two factorial ANOVA with both factors fully crossed.

W ciągu ostatnich stu lat powstalo kilkadziesiąt roŜnych wskaźnikow oceniającychoddzialywanie środowiska atmosferycznego na czlowieka. Wiekszośc z nich nie majednak bezpośredniego odniesienia do reakcji fizjologicznych zachodzących worganizmie pod wplywem warunkow termicznych otoczenia. W latach 90. ubieglegowieku powstaly tzw. wielowezlowe (multi node) modele bilansu cieplnego czlowieka,ktore opisują wszystkie mechanizmy gospodarki cieplnej organizmu. Na bazie jednegoz tych modeli powstal nowy wskaźnik termiczny oceniający obciąŜenia cieplneczlowieka (UTCI – Universal Thermal Climate Index). Artykul przedstawia zaloŜenia ipodstawy interpretacji wskaźnika oraz probe jego wykorzystania do oceny warunkowklimatoterapii uzdrowiskowej.

The present article summarizes essential results of the research project ``Testing of the application of the Predicted-Heat-Strain-(PHS-)model for the design of work-rest-cycles while working in hot environment'' which has been executed on behalf of the Federal Institute for Occupational Safety and Health (BAuA). A pragmatic proposal has been tested on the basis of laboratory experiments and model calculations using the PHS-Model according to ISO 7933. The results show, that the pragmatic proposal could be verified either by physiological measurements and also by the PHS-Model. A procedure to calculate required cooling phases is presented. Based on the results, a guideline is presented, which may be used for the design of work-rest-cycles for work in hot environments.

The decrease in resting core temperature (T (co)) and its relation to the reduced physiological strain during heat acclimation was analysed with rectal temperature data measured in three groups of eight semi-nude persons (6 males, 2 females) who were acclimated for 15 consecutive days to dry, humid and radiant heat, respectively, with equivalent WBGT (33.5 degrees C), by performing 2-h treadmill work. A fourth group followed the same protocol for 12 days in a neutral climate. After acclimation, both resting T (co), prior to heat exposure, and final T (co), measured at the end of work, were significantly reduced. The reduction in final T (co) increased with decreasing ambient water vapour pressure and was higher for the data pooled over the heat conditions (0.46 +/- 0.31 degrees C) than in the neutral climate (0.21 +/- 0.25 degrees C), whereas resting T (co) declined similarly in the heat (0.20 +/- 0.25 degrees C) and the neutral environment (0.17 +/- 0.23 degrees C). The lowering of resting and final T (co) after heat acclimation showed a significant correlation (r = 0.67) and regression analysis showed that 37% of the average reduction in final T (co) was attributable to the lowering of resting T (co). The same analysis was applied after extending the database by short-term series of clothed persons (17 females, 16 males) acclimated at 29.5 and 31.5 degrees C WBGT for 5 days. A significant correlation was found between the lowering of resting and final T (co) (r = 0.57) that did not depend on climatic conditions and gender, although the reduction in resting T (co) was significantly smaller for females (0.06 +/- 0.22 degrees C) than for males (0.21 +/- 0.23 degrees C). It is concluded that the lowering of resting core temperature contributes to the reduced physiological strain during heat acclimation. Similar effects under neutral conditions point to the exercise stimulus as a probable explanation.

TÜ Bd.48 (2007) Nr.1/2 Jan./Febr. 47 nen Bereiche sowie die ausgewählten Klimabedingungen. Grundlage für die Darstellung bildet ein psychrometrisches Diagramm, wobei die Lufttemperatur sowie Luftfeuchte die Eingangsgrößen bilden. In Anlehnung an Angaben in DIN EN ISO 27243 [5] wurde als Bezugszeitraum eine Stunde gewählt, die anteilig in Arbeitsund Entwärmungsphasen aufgeteilt wird. So bedeutet z. B. die Angabe „30 min Entwärmungsphase pro Stunde“, dass auf eine Expositionsbzw. Arbeitsphase von 30 min eine Entwärmungsphase von mindestens 30 min folgt. Weiter sind Randbedingungen angegeben, die es darüber hinaus zu beachten gilt (vgl. [2]): Handlungshilfe zur Gestaltung von Entwärmungsphasen in wärmebelasteten Arbeitsbereichen