Literature DB >> 27568190

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

C R de Freitas1, E A Grigorieva2.   

Abstract

Numerous human thermal climate indices have been proposed. It is a manifestation of the perceived importance of the thermal environment within the scientific community and a desire to quantify it. Schemes used differ in approach according to the number of variables taken into account, the rationale employed, and the particular design for application. They also vary considerably in type and quality, method used to express output, as well as in several other aspects. In light of this, a three-stage project was undertaken to deliver a comprehensive documentation, classification, and overall evaluation of the full range of existing human thermal climate indices. The first stage of the project produced a comprehensive register of as many thermal indices as could be found, 165 in all. The second stage devised a sorting scheme of these human thermal climate indices that grouped them according to eight primary classification categories. This, the third stage of the project, evaluates the indices. Six evaluation criteria, namely validity, usability, transparency, sophistication, completeness, and scope, are used collectively as evaluation criteria to rate each index scheme. The evaluation criteria are used to assign a score that varies between 1 and 5, 5 being the highest. The indices with the highest in each of the eight primary classification categories are discussed. The work is the final stage of a study of the all human thermal climatic indices that could be found in literature. Others have considered the topic, but this study is the first detailed, genuinely comprehensive, and systematic comparison. The results make it simpler to locate and compare indices. It is now easier for users to reflect on the merits of all available thermal indices and decide which is most suitable for a particular application or investigation.

Entities:  

Keywords:  Human climate assessment; Index evaluation; Thermal indices

Mesh:

Year:  2016        PMID: 27568190     DOI: 10.1007/s00484-016-1228-6

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


  59 in total

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Journal:  Med Sci Sports Exerc       Date:  2005-01       Impact factor: 5.411

5.  Sensible climates in monsoon Asia.

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Journal:  Int J Biometeorol       Date:  1991-06       Impact factor: 3.787

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10.  Biometeorological classification of daily weather types for the humid tropics.

Authors:  L B Lecha Estela
Journal:  Int J Biometeorol       Date:  1998-12       Impact factor: 3.787

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  17 in total

1.  The UTCI and the ISB.

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

Review 2.  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

3.  Use of Thermoregulatory Models to Evaluate Heat Stress in Industrial Environments.

Authors:  Irena I Yermakova; Adam W Potter; António M Raimundo; Xiaojiang Xu; Jason W Hancock; A Virgilio M Oliveira
Journal:  Int J Environ Res Public Health       Date:  2022-06-29       Impact factor: 4.614

4.  Roundtable on Preseason Heat Safety in Secondary School Athletics: Environmental Monitoring During Activities in the Heat.

Authors:  Yuri Hosokawa; William M Adams; Douglas J Casa; Jennifer K Vanos; Earl R Cooper; Andrew J Grundstein; Ollie Jay; Brendon P McDermott; Hidenori Otani; Neha P Raukar; Rebecca L Stearns; Brady L Tripp
Journal:  J Athl Train       Date:  2021-01-05       Impact factor: 2.860

5.  Nonlinear reconstruction of bioclimatic outdoor-environment dynamics for the Lower Silesia region (SW Poland).

Authors:  Arkadiusz Głogowski; Paolo Perona; Krystyna Bryś; Tadeusz Bryś
Journal:  Int J Biometeorol       Date:  2021-03-27       Impact factor: 3.787

6.  Spatiotemporal Prediction of Increasing Winter Perceived Temperature across a Sub-Tropical City for Sustainable Planning and Climate Change Mitigation.

Authors:  Hung Chak Ho; Sawaid Abbas; Jinxin Yang; Rui Zhu; Man Sing Wong
Journal:  Int J Environ Res Public Health       Date:  2019-02-11       Impact factor: 3.390

7.  A free software to predict heat strain according to the ISO 7933:2018.

Authors:  Leonidas G Ioannou; Lydia Tsoutsoubi; Konstantinos Mantzios; Andreas D Flouris
Journal:  Ind Health       Date:  2019-03-27       Impact factor: 2.179

8.  Approaching environmental human thermophysiological thresholds for the case of Ankara, Turkey.

Authors:  A Santos Nouri; Y Afacan; O Çalışkan; Tzu-Ping Lin; A Matzarakis
Journal:  Theor Appl Climatol       Date:  2020-10-27       Impact factor: 3.409

9.  Identification, Classification, and Prioritization of Effective Factors in Producing Thermal Strain in Men at Workplaces using Fuzzy AHP Technique.

Authors:  Saeid Yazdanirad; Farideh Golbabaei; Mohammad Reza Monazzam; Habibollah Dehghan; Abbas Rahimi Foroushani
Journal:  Indian J Occup Environ Med       Date:  2020-08-19

10.  Outdoor thermal comfort in public space in warm-humid Guayaquil, Ecuador.

Authors:  Erik Johansson; Moohammed Wasim Yahia; Ivette Arroyo; Christer Bengs
Journal:  Int J Biometeorol       Date:  2017-03-10       Impact factor: 3.787

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