Seasonal mould growth probability in building envelope insulation

Transcription

1 Seasonal mould growth probability in building envelope insulation Antti Haapala Assistant Professor University of Eastern Finland Filip Fedorik Post-doc researcher University of Oulu, Finland

2 Outline House insulation and mould growth issue Modelling of the contamination probability and mould growth kinetics Case study on single family house Consideration for further work

3 Insulation and energy efficiency Construction industry and EU promote low energy consumption of houses Different requirements for passive house status (structural closure) and moisture transfer (breathability) Use of novel building materials and design of wall structures Materials selection Modification Performance

4 Temperature and moisture Thick insulation substantially improves structure s thermal performance but the entrapped humidity may lead to mould growth In arctic and boreal regions the thermal performance is often critical cost and comfort issue. The modelling of biological activity to predict building health has been under stringent development in recent years. GreenBuildingAdvisor.com

5 Mould growth prediction VTT approach Growth of mould can be estimated by favourable climate conditions Temperature and humidity of structures critical factors

6 VTT s mould index (M i ) model The VTT model accounts for timber species, surface quality, time (of favourable conditions) and experimental coefficients of common mould species growth Output: linear scale from 0 to 6 0 indicates no growth, 1 implies small amounts of mould on surface (microscopic), 6 for heavy and tight growth with 100% coverage

7 Case study: Single family house in Joensuu, FIN

8 Case study: Single family house in Joensuu, FIN Wall design Energy class A Base is moren(rock) with EPS insulation and concrete envelope. The wall itself is made on: - External cladding (UTV 23x120) pine board - Wind-protective panel -Frame 48x148 mm wood filled with cellulose wool -Horizontal wood frame 48x48 mm filled with cellulose wool - Moisture barrier film -Vertical frame 48x48 mm + cellulose wool -Gypsium board For the entire wall the U-value is 0,16 (W/m 2 K)

9 ( allows Analysis and results WUFI model of the thermal and humidity conveyance for the wall structure. Weather data from from the Finnish Meteorological Institute for Joensuu, Finland. M i simulation and data analysis Comparison to other house designs, locations, renovation plans WUFI realistic calculation of the transient coupled one- and two dimensional heat and moisture transport in multi-layer building components exposed to natural weather. It is based on vapor diffusion and liquid transport phenomena in building materials

10 Finnish weather Favourable RH for mould growth Substantial seasonal variation Often too cold, never too warm Humidity often at favourable area ~80% Both must apply simultaneously! Favourable T for mould growth

11 Mould growth probability considered low point Favourable [%] Unfavourable [%] max M index [-] Points 4, 6, 7, 9, ,057 99,943 0, ,046 99,954 0, ,150 74,850 0, ,183 99,817 0, ,560 69,440 1, ,454 88,546 0, ,614 84,386 0, ,274 95,726 0, ,468 73,532 0, ,101 67,899 0, ,562 88,438 0,

12 Mould growth is periodical 15 Drying of structures is critical 14 inside 12 outside

13 Another case study Single family house from 1990s, concreate base and wood frame Increase the energy efficiency by adding external EPS insulation layer However, the model shows that this design would have high moisture intake and reside 100% of the time in the favourable region of mould growth Increase in Mould index up to 6 significant risk for unhealthy structure

14 Concluding remarks Benefits Optimization of structures based on building site climate Energy efficiency Design aid Health and life-span Renovation building design multivariable optimization and decreased risk of unhealthy structures Developments needed Material coefficient library New bio-based materials/coatings Antifungal agent efficiency Different wood species Methods to affect mould growth Model houses with embedded sensors needed to verify the models Climate variation Prolonged trials

15 Thank you for your interest! Contact: January