Forty years of Fanger’s model of thermal comfort: comfort for all?
Open accessAbstract
UNLABELLED: The predicted mean vote (PMV) model of thermal comfort, created by Fanger in the late 1960s, is used worldwide to assess thermal comfort. Fanger based his model on college-aged students for use in invariant environmental conditions in air-conditioned buildings in moderate thermal climate zones. Environmental engineering practice calls for a predictive method that is applicable to all types of people in any kind of building in every climate zone. In this publication, existing support and criticism, as well as modifications to the PMV model are discussed in light of the requirements by environmental engineering practice in the 21st century in order to move from a predicted mean vote to comfort for all. Improved prediction of thermal comfort can be achieved through improving the validity of the PMV model, better specification of the model's input parameters, and accounting for outdoor thermal conditions and special groups. The application range of the PMV model can be enlarged, for instance, by using the model to assess the effects of the thermal environment on productivity and behavior, and interactions with other indoor environmental parameters, and the use of information and communication technologies. Even with such modifications to thermal comfort evaluation, thermal comfort for all can only be achieved when occupants have effective control over their own thermal environment. PRACTICAL IMPLICATIONS: The paper treats the assessment of thermal comfort using the PMV model of Fanger, and deals with the strengths and limitations of this model. Readers are made familiar to some opportunities for use in the 21st-century information society.
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Van Hoof's later review established that differences in preferred ambient temperatures were evident in several studies, stating that older people preferred higher temperatures, which the author ascribed to lower activity levels and lower basal metabolic rate.
“In contrast, a later review by van Hoof [61] established that differences in preferred ambient temperatures were evident in several studies, stating that older people preferred higher temperatures, which the author ascribed to lower activity levels and lower basal metabolic rate.”
From Drivers of diversity in human thermal perception – A review for holistic comfort models (2018) · cites this paper as [61]
Five review papers were identified that discuss the influence of age on preferred temperature or synonymous concepts such as neutral temperature or thermal comfort.
“Five review papers have been identified that discuss the influence of age on preferred temperature or synonymous concepts such as neutral temperature or thermal comfort (Table 3) [58–62].”
From Drivers of diversity in human thermal perception – A review for holistic comfort models (2018) · cites this paper as [61]
Most original studies identified by the review papers presented in Table 4 report women to be more sensitive to temperature fluctuations, women to be more often dissatisfied than men, women to have smaller comfort zones and to be more often uncomfortably hot or cold than men.
“In summary, most original studies identified by the review papers presented in Table 4 report women to be more sensitive to temperature fluctuations, women to be more often dissatisfied than men, women to have smaller comfort zones and to be more often uncomfortably hot or cold than men [59–61,67].”
From Drivers of diversity in human thermal perception – A review for holistic comfort models (2018) · cites this paper as [61]
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Schweiker, M., Huebner, G. M., Kingma, B. R. M., Kramer, R., & Pallubinsky, H. (2018) · Temperature · doi:10.1080/23328940.2018.1534490 · Cited by 231 · see citing works
Schellen, L., Loomans, M. G. L. C., de Wit, M. H., Olesen, B. W., & Lichtenbelt, W. D. V. M. (2012) · Physiology & Behavior · doi:10.1016/j.physbeh.2012.07.008 · Cited by 206 · see citing works
Thermal comfort of heterogeneous and dynamic indoor conditions — An overview
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Self-citationPredicting thermal comfort in office buildings in a Brazilian temperate and humid climate
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The influence of a moderate temperature drift on thermal physiology and perception
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Influences on the predictive performance of thermal sensation indices
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- Authors
- van Hoof, J.
- Venue
- Indoor Air
- Publisher
- Wiley
- Published
- 2008-06
- Volume
- 18
- Issue
- 3
- Pages
- 182-201
- ISSN
- 0905-6947 (ISSN-L)
- 1600-0668
- OpenAlex
- W2107186450
- Cited by
- 733
- References
- 89
- Citations by year
- 2026: 52 · 2025: 59 · 2024: 56 · 2023: 63 · 2022: 72 · 2021: 53 · 2020: 55 · 2019: 62 · 2018: 44 · 2017: 37 · 2016: 34 · 2015: 25 · 2014: 34 · 2013: 30 · 2012: 19
- FWCI
- 2.24
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Indoor Air (publishedVersion)
- PubMed (publishedVersion)
- TU/e Research Portal (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Physical Sciences › Environmental Science › Environmental Engineering › Urban Heat Island Mitigation
- Social Sciences › Psychology › Social Psychology › Facilities and Workplace Management
- Keywords
- thermal comfort, predicted mean vote, Fanger model, thermal comfort prediction, special groups, indoor environmental quality, information and communication technologies, model validity
- MeSH terms
- Air Conditioning, Environment, Facility Design and Construction, Humans, Models, Biological, Thermosensing, Workplace
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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