Serviceability limit state model for fungal growth on wood materials in the built environment

• Published in: Journal of Building Engineering 2022-06, Vol.50, p.104085, Article 104085
• Main Authors: Lepage, Robert, Glass, Samuel V., Bastide, Paul de la, Mukhopadhyaya, Phalguni
• Format: Article
• Language: English
• Subjects: Biodeterioration; Fungi; Serviceability limit state; Wood
• ISSN: 2352-7102; 2352-7102
• DOI: 10.1016/j.jobe.2022.104085

Fungal (mould) growth in wood based building components could have significant detrimental effects on the operational and structural requirements of the built environment. Quite naturally, building designers and material scientists are keen to predict mould growth in wood and wood based building materials. Available surface mould growth models primarily predict the levels of mould growth in different environmental and material conditions. However, modern design practices allow acceptable limit of risk in the design process. Hence, a probabilistic mould growth model is required which takes into account risk tolerance thresholds for mould growth. This paper presents a research initiative that shifts the mould growth narrative from predicted levels to probabilistic predictions, which is the foundation block associated with limit state design approach, widely used in structural design codes and standards. More specifically, this paper presents a serviceability limit state mould growth model for wood using jack pine (Pinus banksiana) wood and the fungal species Penicillium chrysogenum. The outputs from this model were verified using the results obtained from an experimental roof study that investigated the impacts of different surface treatments on mould growth in ventilated roofs. •Building designers and material scientists are keen to predict mould growth in wood and wood based building materials.•Available surface mould growth models predict the levels of mould growth in different environmental and material conditions.•A probabilistic mould growth model is required which takes into account risk tolerance thresholds for mould growth.•This paper presents a study that shifts the mould growth narrative from predicted levels to probabilistic predictions.•The outputs from the probabilistic mould growth model were verified using the results obtained from an experimental study.