Literature DB >> 21336880

The perceived temperature - a versatile index for the assessment of the human thermal environment. Part A: scientific basics.

Henning Staiger1, Gudrun Laschewski, Angelika Grätz.   

Abstract

The Perceived Temperature (PT) is an equivalent temperature based on a complete heat budget model of the human body. It has proved its suitability for numerous applications across a wide variety of scales from micro to global and is successfully used both in daily forecasts and climatological studies. PT is designed for staying outdoors and is defined as the air temperature of a reference environment in which the thermal perception would be the same as in the actual environment. The calculation is performed for a reference subject with an internal heat production of 135 W m(-2) (who is walking at 4 km h(-1) on flat ground). In the reference environment, the mean radiant temperature equals the air temperature and wind velocity is reduced to a slight draught. The water vapour pressure remains unchanged. Under warm/humid conditions, however, it is implicitly related to a relative humidity of 50%. Clothing is adapted in order to achieve thermal comfort. If this is impossible, cold or heat stress will occur, respectively. The assessment of thermal perception by means of PT is based on Fanger's Predicted Mean Vote (PMV) together with additional model extensions taking account of stronger deviations from thermal neutrality. This is performed using a parameterisation based on a two-node model. In the cold, it allows the mean skin temperature to drop below the comfort value. In the heat, it assesses additionally the enthalpy of sweat-moistened skin and of wet clothes. PT has the advantages of being self-explanatory due to its deviation from air temperature and being--via PMV--directly linked to a thermo-physiologically-based scale of thermal perception that is widely used and has stood the test of time. This paper explains in detail the basic equations of the human heat budget and the coefficients of the parameterisations.

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Year:  2011        PMID: 21336880     DOI: 10.1007/s00484-011-0409-6

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


  9 in total

1.  A computer model of human thermoregulation for a wide range of environmental conditions: the passive system.

Authors:  D Fiala; K J Lomas; M Stohrer
Journal:  J Appl Physiol (1985)       Date:  1999-11

2.  The adaptive model of thermal comfort and energy conservation in the built environment.

Authors:  R de Dear; G S Brager
Journal:  Int J Biometeorol       Date:  2001-07       Impact factor: 3.787

3.  Applications of a universal thermal index: physiological equivalent temperature.

Authors:  A Matzarakis; H Mayer; M G Iziomon
Journal:  Int J Biometeorol       Date:  1999-10       Impact factor: 3.787

4.  The physiological equivalent temperature - a universal index for the biometeorological assessment of the thermal environment.

Authors:  P Höppe
Journal:  Int J Biometeorol       Date:  1999-10       Impact factor: 3.787

5.  Modelling radiation fluxes in simple and complex environments--application of the RayMan model.

Authors:  Andreas Matzarakis; Frank Rutz; Helmut Mayer
Journal:  Int J Biometeorol       Date:  2006-11-09       Impact factor: 3.787

6.  Tourism climate and thermal comfort in Sun Moon Lake, Taiwan.

Authors:  Tzu-Ping Lin; Andreas Matzarakis
Journal:  Int J Biometeorol       Date:  2007-10-17       Impact factor: 3.787

7.  Computer prediction of human thermoregulatory and temperature responses to a wide range of environmental conditions.

Authors:  D Fiala; K J Lomas; M Stohrer
Journal:  Int J Biometeorol       Date:  2001-09       Impact factor: 3.787

8.  Influences of culture and environmental attitude on thermal, emotional and perceptual evaluations of a public square.

Authors:  Igor Knez; Sofia Thorsson
Journal:  Int J Biometeorol       Date:  2006-03-16       Impact factor: 3.787

9.  Modelling radiation fluxes in simple and complex environments: basics of the RayMan model.

Authors:  Andreas Matzarakis; Frank Rutz; Helmut Mayer
Journal:  Int J Biometeorol       Date:  2009-09-12       Impact factor: 3.787

  9 in total
  14 in total

1.  The effect of seasonal variation and secretion of sunitinib in sweat on the development of hand-foot syndrome.

Authors:  Nienke A G Lankheet; Alwin D R Huitema; Henk Mallo; Sandra Adriaansz; John B A G Haanen; Jan H M Schellens; Jos H Beijnen; Christian U Blank
Journal:  Eur J Clin Pharmacol       Date:  2013-08-31       Impact factor: 2.953

2.  Effects of ventilation behaviour on indoor heat load based on test reference years.

Authors:  Madeleine Rosenfelder; Christina Koppe; Jens Pfafferott; Andreas Matzarakis
Journal:  Int J Biometeorol       Date:  2015-06-07       Impact factor: 3.787

3.  Quantification and assessment of heat and cold waves in Novi Sad, Northern Serbia.

Authors:  Biljana Basarin; Tin Lukić; Andreas Matzarakis
Journal:  Int J Biometeorol       Date:  2015-06-11       Impact factor: 3.787

4.  A comprehensive catalogue and classification of human thermal climate indices.

Authors:  C R de Freitas; E A Grigorieva
Journal:  Int J Biometeorol       Date:  2014-03-30       Impact factor: 3.787

Review 5.  Biometeorology for cities.

Authors:  David M Hondula; Robert C Balling; Riley Andrade; E Scott Krayenhoff; Ariane Middel; Aleš Urban; Matei Georgescu; David J Sailor
Journal:  Int J Biometeorol       Date:  2017-07-27       Impact factor: 3.787

6.  A comparison and appraisal of a comprehensive range of human thermal climate indices.

Authors:  C R de Freitas; E A Grigorieva
Journal:  Int J Biometeorol       Date:  2016-08-27       Impact factor: 3.787

7.  A glossary for biometeorology.

Authors:  Simon N Gosling; Erin K Bryce; P Grady Dixon; Katharina M A Gabriel; Elaine Y Gosling; Jonathan M Hanes; David M Hondula; Liang Liang; Priscilla Ayleen Bustos Mac Lean; Stefan Muthers; Sheila Tavares Nascimento; Martina Petralli; Jennifer K Vanos; Eva R Wanka
Journal:  Int J Biometeorol       Date:  2014-02-19       Impact factor: 3.787

8.  [Influence of extreme weather conditions on the deployment volume of emergency medical services].

Authors:  C Hanefeld; R Klaaßen-Mielke; J Miebach; S Muthers; A Haschemi; H Trampisch; C Kloppe; A Matzarakis; C Krogias; C Schroeder
Journal:  Med Klin Intensivmed Notfmed       Date:  2019-12-04       Impact factor: 0.840

9.  Global forecasting of thermal health hazards: the skill of probabilistic predictions of the Universal Thermal Climate Index (UTCI).

Authors:  F Pappenberger; G Jendritzky; H Staiger; E Dutra; F Di Giuseppe; D S Richardson; H L Cloke
Journal:  Int J Biometeorol       Date:  2014-05-25       Impact factor: 3.787

10.  Comparison of UTCI with other thermal indices in the assessment of heat and cold effects on cardiovascular mortality in the Czech Republic.

Authors:  Aleš Urban; Jan Kyselý
Journal:  Int J Environ Res Public Health       Date:  2014-01-09       Impact factor: 3.390

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