A steady-state model for predicting hygrothermal conditions in beds in relation to house dust mite requirements

Abstract

This paper describes the development, testing and validation of a simple steady-state hygrothermal bed model (BED) which predicts conditions of temperature and relative humidity within the bed core (the occupied space between mattress and covering), given the temperature and relative humidity of the bedroom. BED is the second of three simple steady-state models that in combination allow the impact of modifying bedroom hygrothermal conditions on dust mite populations to be assessed. The first of the trio is Condensation Targeter II, an existing validated model that predicts average monthly conditions of temperature and relative humidity within the bedroom. These conditions are then used as boundary conditions for the BED model which predicts hygrothermal conditions within the bed core. Finally, these outputs are in turn used as inputs to a simple Mite Population Index (MPI) model (to be described elsewhere) that predicts their likely effect on house dust mite population growth in the bed. As reported here, BED has been validated using monitored bedroom and bed data for a full year in three dwellings and the results show that the steady state model predicts monthly bed hygrothermal conditions with a reasonable degree of accuracy. Using Condensation Targeter II and BED in combination, a sensitivity study has been carried out to assess the impact of changes in input parameters of both models on hygrothermal conditions in the bed core. This highlights the importance that the design of the fabric and services of the building has on the hygrothermal conditions in a bed. The impact of climate change has also been assessed using future climate change scenarios. Practical application: This paper describes in detail a simple steady-state model, (BED) which is used to predict the monthly average temperature and relative humidity within a bed, given the ambient conditions within the bedroon. The input parameters, output parameters and the model formulae are provided so that the model can be easily implemented. BED is the second of three simple models that are used to predict, first the bedroon conditions (Condensation Targeter II), second the bed conditions (BED) and finally the likely effect on house dust mite population growth using a simple Mite Population Index (MPI).