Research investigates new ways to model mould growth
In our latest research, we monitor mould growth by testing a laboratory-based model in real people’s homes. Eighty million people in Europe live in buildings contaminated with indoor mould, affecting 15% of homes in the UK. Depending on the timing and level of exposure to mould and mouldy odours, people’s health and wellbeing could be at risk.
Research highlights:
We can predict mould growth using domestic relative humidity and temperature.
Real-time predictions could inform targeted smart control to improve public health.
Results support the use of indoor sensors and modelling to help reduce damp.
Why does mould grow in our homes?
Mould generally needs high levels of humidity to grow, typically around 70% or 80%. Indoor dampness can result from water entering the house, rising damp or condensation. Unless homes have the appropriate ventilation and heating, dampness can lead to mould. Mould can particularly affect homes that are suffering from fuel poverty – exacerbating health conditions like asthma.
Testing models for mould growth
The VTT model of mould growth is one of the most widely used for modelling mould growth using measurements of surface humidity and temperature. The original model was developed in controlled laboratory conditions, so we wanted to test whether it could be adapted to work for domestic settings.
In this study, we tested the usability of the VTT model for sensor readings of air temperature and humidity from the homes of residents who live in Cornwall’s social housing. We compared the results of different models with occupants’ responses about mould in their homes. These responses allowed us to identify the best performing model for predicting mould in the home.
We found that in the living room, mould predictions based on relative humidity and temperature measures correctly related to the presence of mould in the home. Predictions based on measures from the bedroom correctly related to the presence of a mouldy odour.
What do the results tell us?
The results of this study provide evidence for relationships between the model’s predictions and the occupants’ responses, showing that our adapted model can be used for predicting mould growth in people’s homes.
Lead researcher, Dr. Tamaryn Menneer, said: “Our research supports the adoption of indoor sensors and modelling as a way to support housing associations to identify which properties and residents are at risk of indoor damp and mould. Future developments could help homeowners and housing providers to reduce the costs associated with damp and mould related issues, while protecting people’s health and wellbeing.”
Citation: Tamaryn Menneer, Markus Mueller, Richard A. Sharpe, Stuart Townley, Modelling mould growth in domestic environments using relative humidity and temperature, Building and Environment, 2021, 108583, ISSN 0360-1323, https://doi.org/10.1016/j.buildenv.2021.108583.