Exploring the Use of Mould Estimation Software in New Zealand Residential Houses
Regularly being exposed to the types of mould spores that can grow in houses has been shown to lead to adverse health effects such as respiratory diseases, and the exacerbation of asthma. While susceptible groups such as children, the elderly, and atopic persons are more susceptible to these effects, adverse health effects from mould spores have been shown to affect non-topic populations. The 2015 Building Research Association of New Zealand House Condition Survey found that 46% of owner-occupied properties, and 54% of rented properties in a representative sample of the New Zealand housing stock have some form of mould in them. This means that a large portion of the population could be at risk of suffering from the adverse health effects associated with mould growth in houses. Increased air-tightness in new houses could also be at risk of being under-ventilated, potentially exacerbating this mould issue. It is unknown whether the current New Zealand Building Code, at the time of writing, provides sufficient ventilation requirements to prevent new houses from being under-ventilated. It also does not consider existing houses, which is where most of the mould in the HCS was found. This study explored whether data from the House Condition Survey and WuFi-Bio could be used to test mould mitigation strategies in New Zealand residential bathrooms. This was done by modelling a subset of houses from the House Condition Survey in WuFi-Pro, estimating the risk of mould in them with WuFi-Bio, and comparing this to the observations from the House Condition Survey. Parameters in the models were then changed to reflect the impact that strategies would have on the humidity and temperature in the bathrooms. The aim of this was to develop a hierarchy of recommendations that could help home occupiers and designers determine the most appropriate methods they could use to prevent mould from growing in their homes/designs. However, the results did not align with the observations from the House Condition Survey, and testing the validity of the models by exploring the impact of assumptions showed they had no significant impact. The cause of this misalignment could not be determined, however a lack of internal condition time-series data and information about how observed mould from the House Condition Survey were identified of areas of uncertainty and prevented further exploration. The exploration that was conducted revealed the importance of having enough data to understand the conditions that lead to any observed mould if an existing bathroom is being assessed using WuFi-Bio. It was concluded that attempting to assess a large number of houses with little data using WuFi-Bio was impractical. A controlled experimental study aimed at understanding a few houses in-depth would be a more appropriate method to test mould mitigation strategies, and help address the mould issue in New Zealand houses.