ArticleInternational journal of biometeorology2020
Effects of microclimate and human parameters on outdoor thermal sensation in the high-density tropical context of Dhaka.
Article in International journal of biometeorology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Building the model: a review of input structures in extreme temperature-health.Environmental health : a global access science source · 2026Pooled it
- Association between urban density, built environment quality, and health: a multi-source study in Doha, Qatar.Frontiers in public health · 2026Article
- Application of seasonal-adjusted hybrid models for forecasting Discomfort Index in a heat-prone region of Bangladesh.PloS one · 2026Article
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Authors and funding
2 authors.
Funding
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Abstract
A thermal comfort questionnaire survey was carried out in the high-density, tropical city Dhaka. Comfort responses from over 1300 subjects were collected at six different sites, alongside meteorological parameters. The effect of personal and psychological parameters was examined in order to develop predictive models. Personal parameters included gender, age, activity, profession-type (indoor or outdoor-based), exposure to air-conditioned space and sweat-levels. Psychological parameters, such as 'the reason for visiting the place' and 'next destination is air-conditioned', had statistically significant effects on thermal sensation. Other parameters, such as 'body type', 'body exposure to sun', 'time living in Dhaka', 'travelling in last_30 min', and 'hot food' did not have any significant impact. Respondents' humidity, wind speed and solar radiation sensation had profound impacts and people were found willing to adjust to the thermal situations with adaptive behaviour. Based on actual sensation votes from the survey, empirical models are developed to predict outdoor thermal sensation in the case study areas. Ordinal linear regression techniques are applied for predicting thermal sensation by considering meteorological and personal conditions of the field survey. The inclusion of personal and weather opinion factors produced an improvement in models based on meteorological factors. The models were compared with the actual thermal sensation using the cross-tabulation technique. The predictivity of the three models (meteorological, thermos-physiological and combined parameter) as expressed by the gamma coefficient were 0.575, 0.636 and 0.727, respectively. In all three models, better predictability was observed in the 'Slightly Warm' (71% in meteorological model) and 'Hot' (64.9% in combined parameter model) categories-the most important ones in a hot-humid climate.
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