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 cooperation 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.

The thermal, evaporative and wicking properties of clothing depend not only on the properties of the fabric but also on the thickness of air layers and the magnitude of the contact area and their variation. The aim of this study was to accurately determine the contact area and the air gap thickness between clothing and the human body in detail. These parameters were measured for a range of typical patterns of garments (tight- and loose fitting) covering either the upper or lower body and made of various types of fabrics (knitted and woven). The method consisted of imposing three-dimensional scans of the nude and dressed manikin and determining the distance between their surfaces by advanced three-dimensional scan post-processing. Due to this method the distribution of the air gap thickness and the contact area over body parts was obtained and this knowledge can be applied in models of heat and mass transfer in the clothing.

In real life conditions, the trapped air between the human body and the garment has uneven shape and vary over the body parts as a consequence of the complex geometry of the human body. However, the existing clothing models assume uniform air layer between the human body and the garment or its full contact, which may cause large error in the output of simulations. Therefore, the aim of this study was to investigate the effect of a heterogeneous vertical air gap with different configuration of folds (size and frequency) on dry heat loss using a heated cylinder (Torso). It was found that the presence of folds in the garment led to an increased heat loss from the body in comparison to a homogeneous air gap of comparable size. Interestingly, the size of folds did not have an influence on the dry heat loss. Additionally, the effect of the contact area on dry heat loss became important when exceeding a threshold of about 42%. The results from this study are useful for modelling of a realistic dry heat loss through the clothing and contribute to the improvement of design of protective and active sport garments.

The measurement of core body temperature is an efficient method for monitoring heat stress amongst workers in hot conditions. However, invasive measurement of core body temperature (e.g. rectal, intestinal, oesophageal temperature) is impractical for such applications. Therefore, the aim of this study was to define relevant non-invasive measures to predict core body temperature under various conditions. We conducted two human subject studies with different experimental protocols, different environmental temperatures (10 °C, 30 °C) and different subjects. In both studies the same non-invasive measurement methods (skin temperature, skin heat flux, heart rate) were applied. A principle component analysis was conducted to extract independent factors, which were then used in a linear regression model. We identified six parameters (three skin temperatures, two skin heat fluxes and heart rate), which were included for the calculation of two factors. The predictive value of these factors for core body temperature was evaluated by a multiple regression analysis. The calculated root mean square deviation (rmsd) was in the range from 0.28 °C to 0.34 °C for all environmental conditions. These errors are similar to previous models using non-invasive measures to predict core body temperature. The results from this study illustrate that multiple physiological parameters (e.g. skin temperature and skin heat fluxes) are needed to predict core body temperature. In addition, the physiological measurements chosen in this study and the algorithm defined in this work are potentially applicable as real-time core body temperature monitoring to assess health risk in broad range of working conditions.

The important requirement that COST Action 730 demanded of the physiological model to be used for the Universal Thermal Climate Index was its capability of accurate simulation of the human thermophysiological responses across a wide range of relevant environmental conditions, such as conditions corresponding to the selection of all habitable climates and their seasonal changes, and transient conditions representing temporal variation of outdoor conditions. In the first part of this study available heat budget/two-node models and multi-node thermophysiological models were evaluated by direct comparison over the wide spectrum of climatic conditions. The UTCI-Fiala model predicted most reliably the average human thermal response which was showed by least deviations from physiologically plausible responses when compared to other models. In the second part of the study, this model was, therefore, subjected to extensive validation using results of human subject experiments for a range of relevant (steady-state and transient) environmental conditions. The UTCI-Fiala multi-node model proved its ability to predict adequately the human physiological response for a variety of moderate and extreme conditions represented in the COST 730 database. The mean skin and core temperatures were predicted with average root-meansquare deviations of 1.35 ± 1.00 °C and 0.32 ± 0.20 °C, respectively. In the first part of this study available heat budget/two-node models and multi-node thermophysiological models were evaluated by direct comparison over the wide spectrum of climatic conditions. The UTCI-Fiala model predicted most reliably the average human thermal response which was showed by least deviations from physiologically plausible responses when compared to other models. In the second part of the study, this model was, therefore, subjected to extensive validation using results of human subject experiments for a range of relevant (steadystate and transient) environmental conditions. The UTCI-Fiala multi-node model proved its ability to predict adequately the human physiological response for a variety of moderate and extreme conditions represented in the COST 730 database. The mean skin and core temperatures were predicted with average root-mean-square deviations of 1.35 ± 1.00 °C and 0.32 ± 0.20 °C, respectively.