Literature DB >> 21336921

Physiological responses to temperature and humidity compared to the assessment by UTCI, WGBT and PHS.

Bernhard Kampmann1, Peter Bröde, Dusan Fiala.   

Abstract

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.

Mesh:

Year:  2011        PMID: 21336921     DOI: 10.1007/s00484-011-0410-0

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


  3 in total

1.  Development and validation of the predicted heat strain model.

Authors:  J Malchaire; A Piette; B Kampmann; P Mehnert; H Gebhardt; G Havenith; E Den Hartog; I Holmer; K Parsons; G Alfano; B Griefahn
Journal:  Ann Occup Hyg       Date:  2001-03

2.  Deriving the operational procedure for the Universal Thermal Climate Index (UTCI).

Authors:  Peter Bröde; Dusan Fiala; Krzysztof Błażejczyk; Ingvar Holmér; Gerd Jendritzky; Bernhard Kampmann; Birger Tinz; George Havenith
Journal:  Int J Biometeorol       Date:  2011-05-31       Impact factor: 3.787

3.  Validation of the Fiala multi-node thermophysiological model for UTCI application.

Authors:  Agnes Psikuta; Dusan Fiala; Gudrun Laschewski; Gerd Jendritzky; Mark Richards; Krzysztof Błażejczyk; Igor Mekjavič; Hannu Rintamäki; Richard de Dear; George Havenith
Journal:  Int J Biometeorol       Date:  2011-06-08       Impact factor: 3.787

  3 in total
  19 in total

1.  UTCI--why another thermal index?

Authors:  Gerd Jendritzky; Richard de Dear; George Havenith
Journal:  Int J Biometeorol       Date:  2011-12-21       Impact factor: 3.787

2.  The uncertainty of UTCI due to uncertainties in the determination of radiation fluxes derived from numerical weather prediction and regional climate model simulations.

Authors:  Stefan F Schreier; Irene Suomi; Peter Bröde; Herbert Formayer; Harald E Rieder; Imram Nadeem; Gerd Jendritzky; Ekaterina Batchvarova; Philipp Weihs
Journal:  Int J Biometeorol       Date:  2012-02-26       Impact factor: 3.787

3.  Prediction of human core body temperature using non-invasive measurement methods.

Authors:  Reto Niedermann; Eva Wyss; Simon Annaheim; Agnes Psikuta; Sarah Davey; René Michel Rossi
Journal:  Int J Biometeorol       Date:  2013-06-13       Impact factor: 3.787

4.  Deriving the operational procedure for the Universal Thermal Climate Index (UTCI).

Authors:  Peter Bröde; Dusan Fiala; Krzysztof Błażejczyk; Ingvar Holmér; Gerd Jendritzky; Bernhard Kampmann; Birger Tinz; George Havenith
Journal:  Int J Biometeorol       Date:  2011-05-31       Impact factor: 3.787

5.  UTCI-Fiala multi-node model of human heat transfer and temperature regulation.

Authors:  Dusan Fiala; George Havenith; Peter Bröde; Bernhard Kampmann; Gerd Jendritzky
Journal:  Int J Biometeorol       Date:  2011-04-19       Impact factor: 3.787

6.  Estimated work ability in warm outdoor environments depends on the chosen heat stress assessment metric.

Authors:  Peter Bröde; Dusan Fiala; Bruno Lemke; Tord Kjellstrom
Journal:  Int J Biometeorol       Date:  2017-04-19       Impact factor: 3.787

7.  The UTCI and the ISB.

Authors:  Gerd Jendritzky; Peter Höppe
Journal:  Int J Biometeorol       Date:  2017-06-20       Impact factor: 3.787

8.  Relationship among environmental quality variables, housing variables, and residential needs: a secondary analysis of the relationship among indoor, outdoor, and personal air (RIOPA) concentrations database.

Authors:  Fausto Garcia; Derek G Shendell; Jaime Madrigano
Journal:  Int J Biometeorol       Date:  2016-08-30       Impact factor: 3.787

9.  Heat stress mortality and desired adaptation responses of healthcare system in Poland.

Authors:  Anna Błażejczyk; Krzysztof Błażejczyk; Jarosław Baranowski; Magdalena Kuchcik
Journal:  Int J Biometeorol       Date:  2017-09-01       Impact factor: 3.787

10.  Summer UTCI variability in Poland in the twenty-first century.

Authors:  Agnieszka Krzyżewska; Sylwester Wereski; Mateusz Dobek
Journal:  Int J Biometeorol       Date:  2020-07-17       Impact factor: 3.787

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