Abstract
Based on results from a field survey campaign conducted in Switzerand, we show that occupants’ variations in clothing choices, which are relatively unconstrained, are best described by the daily mean outdoor temperature and that major clothing adjustments occur rarely during the day. We then develop an ordinal logistic model of the probability distribution of discretised clothing levels, which results in a concise and informative expression of occupants’ clothing choices. Results from both cross-validation and independent verification suggest that this model formulation may be used with confidence. Furthermore, the form of the model is readily generalisable, given the requisite calibration data, to environments where dress codes are more specific. We also observe that, for these building occupants, the prevailing metabolic activity levels are mostly constant for the whole range of surveyed environmental conditions, as their activities are relatively constrained by the tasks in hand. Occupants may compensate for this constraint, however, through the consumption of cold and hot drinks, with corresponding impacts on metabolic heat production. Indeed, cold drink consumption was found to be highly correlated with indoor thermal conditions, whilst hot drink consumption is best described by a seasonal variable. These variables can be used for predictive purposes using binary logistic models.
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Notes
Note that our model is developed from a field survey of the behaviours and preferences of a relatively esoteric group of academics accommodated in a relatively atypical passive solar building (which is warmer than average in winter and may induce correspondingly lower than average clothing levels. The generality of the calibration parameters presented in association with Eq. 3 may thus be placed under scrutiny. We would, however, contest that the form of the model is generalisable (following the above steps and data permitting).
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Acknowledgements
Financial support received from the European Commission as part of the CONCERTO II Project HOLISTIC is gratefully acknowledged. We warmly thank the present and former collaborators of our laboratory who contributed to the installation and maintenance of the data acquisition sensors, particularly René Altherr, Antoine Guillemin, David Lindelöf and Laurent Deschamps. We are particularly grateful to Prof. Fergus Nicol for giving us access to the data of the SCATs project and to Revd. Prof. Michael A. Humphreys for his valuable remarks.
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Haldi, F., Robinson, D. Modelling occupants’ personal characteristics for thermal comfort prediction. Int J Biometeorol 55, 681–694 (2011). https://doi.org/10.1007/s00484-010-0383-4
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DOI: https://doi.org/10.1007/s00484-010-0383-4