Jiang, Y;
Wang, Z;
Lin, B;
Mumovic, D;
(2020)
Development of a health data-driven model for a thermal comfort study.
Building and Environment
, 177
, Article 106874. 10.1016/j.buildenv.2020.106874.
Preview |
Text
Mumovic_Develop big-data model and dataset originated from public health to study thermal comfort.pdf - Accepted Version Download (996kB) | Preview |
Abstract
The objective of this study is to develop a thermal comfort model by incorporating public health datasets and influencing parameters associated with both health and thermal comfort. There are three systematic influencing parameters identified in this study: socioeconomic development, population density, and annual mean temperature. The thermal comfort neutral temperatures predicted with the new model are in good agreement with the measured field data, and the correlation coefficient is 0.91. The current study introduces large-scale spatial data and longitudinal health-temperature data from the public health field for contributing to thermal comfort research. For instance, the required numbers of intensive field experiments and modeling works regarding thermal comfort can be reduced. Moreover, studies on the impacts of certain factors (such as variations in time, gender, and age) on thermal comfort have not reached any conclusive results, mainly owing to a lack of large demographic datasets. Recent findings from the public health field indicate that there are observable variations in health-temperature data in response to climate changes. There are no significant health-temperature differences between genders, although females are more inclined to use resources for better environmental management. Other factors are also discussed in this study, such as age and the prevalence of air conditioners.
Type: | Article |
---|---|
Title: | Development of a health data-driven model for a thermal comfort study |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1016/j.buildenv.2020.106874 |
Publisher version: | https://doi.org/10.1016/j.buildenv.2020.106874 |
Language: | Finnish |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | thermal comfort, public health, big data, climate change |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources |
URI: | https://discovery.ucl.ac.uk/id/eprint/10108205 |
Archive Staff Only
View Item |