Featured Image: Mould In A Service Family’s Accommodation Highlighted in this week’s Forces.net
As we know, Britain is a draughty country containing castles and forts and moats. There’s also a massive housing stock across the social, private and military estates that desperately needs some tender, loving care.
After the death of Awaab Ishak, the creation of Awaab’s Law, through the campaign of the family, the work of Christian Weaver and the family’s legal team, the scale of the work to be done in maintenance and repair makes you realise that the whole country is affected.
Below are facts and statistics from Statista, the House of Commons Library and a University of East London Study Assessing the Risk of Damp and Mould Growth In Renovated Properties
There are 38.3 million homes in the UK: 15% are affected by mould, 16% have humidity problems, 23% have visible mould and 13% have a mouldy odour.
In numbers that’s 5,750,000 with mould, 6,000,000 with humidity problems, 8,809,000 have visible mould 4,979000 with a mouldy odour.
Condensation increases without air conditioning, fans or dehumidifier: when you realise that 48% (in mubers that’s 15,320,000 households in the UK that don’t use or consider air conditioning, fans or a dehumidifier: it could really make a difference.
Mould spores are ubiquitous outside, they vary seasonally and can influence the indoor environment.
Damp inside (caused by water ingress, rising damp and condensation) where rooms aren’t warm and well ventilated can lead to increased mould contamination. Not switching on gas and electricity where the cost is seen as prohibitive doesn’t just affect private rented and social housing tenants, it’s as prevalent in the privately owned sector.
Getting a conversation going across society about how important insulation, warmth, circulation of air, condensation, using fans and dehumidifiers are as important as interventions to alleviate risk of fuel poverty.
Mould or a mouldy odour exacerbates a range of allergic and non-allergenic diseases: the health impact depends on the extent of exposure to a range of physical, chemical and biological agents and the variable risk of allergic diseases throughout the life course.
Mould growth, including its impact on health, is further modified by a complex interaction between diverse built environment and resident characteristics. These include interactions between built age, build type, architectural design, building materials, geographic location and resident behaviours such as variable heating, ventilation and maintenance patterns.
Mould growth depends on the material and species modified by duration of exposure to humidity. Some species can survive in very dry environments. However, the optimum fungal growth conditions require a humidity typically above 70–80%. Mould prediction models are influenced by a range of factors such as fungal diffusion, fungal production and available nutrients. However, to our knowledge, all models incorporate levels of RH and temperature.
The VTT (Valtion teknillinen tutkimuskeskus) model of mould growth is a mathematical model that predict mould growth from surface relative humidity and temperature. It’s a model used to test different methods of insulation in a heritage building and to show no increased risk of mould growth in a house designed to have low energy usage.
Other models of mould growth, based on relative humidity and temperature, include the use of isopleth curves which separate favourable and unfavourable relative humidity and temperature steady-state conditions for mould growth.
Isopleth (in an isopleth the horizontal axis shows time, the vertical axis shows depth/elevation, and the body of the graph shows the value of a given parameter). Isopleth systems are often used in conjunction with different mould types and building materials to provide biohygrothermal analysis (a biohygrothermal model has been developed to assess mold growth under transient hygrothermal boundary conditions). The method is based on comparison of the measured or calculated transient boundary conditions with the growth conditions for typical molds found on building materials which can also account for fluctuation in the conditions over time by taking into account effect of current conditions on mould spores. They have, for example, been applied to the study of mould growth on different building facades
Comparisons of such models with the VTT model show some differences in mould growth predictions, in part due to different behaviours under the same starting conditions, and under conditions that fluctuate or are unfavourable for mould growth, but there is also a strong positive relationship between the outputs for the two types of models. Specifically, the VTT model allows a decline in the mould level under unfavourable conditions, has a smaller growth rate when there is a low mould level, includes a maximum mould level, and to some extent takes into account duration of mould-favourable conditions.
More generally, differences between mould growth models are attributable to the complexity of the mould germination and growth processes combined with the assumptions and simplifications in each type of model. These studies and others suggest that unreliability under fluctuating conditions is due to limited experimental data when conditions are unfavourable for mould growth, and that more measurement research is required.
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