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dc.contributor.authorRowan, Neil J.
dc.contributor.authorJohnstone, Cameron M.
dc.contributor.authorMcLean, R. Craig
dc.contributor.authorAnderson, John G.
dc.contributor.authorClarke, Joe A.
dc.identifier.citationRowan, N.J., Johnstone, C.M., McLean, R.C., Anderson, J.G., Clarke, J.A. (1999)en_US
dc.identifier.otherFaculty of Science & Health -Nursing and Healthcare-Articles-Nursing and Healthcareen_US
dc.description.abstractThere is growing concern about the adverse effects of fungal bioaerosols on the occupants of damp dwellings. Based on an extensive analysis of previously published data and on experiments carried out within this study, critical limits for the growth of the indoor fungi Eurotium herbariorum, Aspergillus versicolor, and Stachybotrys chartarum were mathematically described in terms of growth limit curves (isopleths) which define the minimum combination of temperature (T) and relative humidity (RH) at which growth will occur. Each growth limit curve was generated from a series of data points on a T-RH plot and mathematically fitted by using a third-order polynomial equation of the form RH 5 a3T3 1 a2T2 1 a1T 1 a0. This fungal growth prediction model was incorporated within the ESP-r (Environmental Systems Performance [r stands for “research”]) computer-based program for transient simulation of the energy and environmental performance of buildings. For any specified location, the ESP-r system is able to predict the time series evolution of local surface temperature and relative humidity, taking explicit account of constructional moisture flow, moisture generation sources, and air movement. This allows the predicted local conditions to be superimposed directly onto fungal growth curves. The concentration of plotted points relative to the curves allows an assessment of the risk of fungal growth. The system’s predictive capability was tested via laboratory experiments and by comparison with monitored data from a fungus-contaminated house.en_US
dc.publisherAmerican Society for Microbiologyen_US
dc.relation.ispartofApplied and Environmental Microbiologyen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland*
dc.subjectFungal growthen_US
dc.subjectDampness in buildingsen_US
dc.titlePrediction of toxigenic fungal growth in buildings by using a novel modelling system.en_US
dc.rights.accessOpen Accessen_US
dc.subject.departmentFaculty of Science and Healthen_US

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Attribution-NonCommercial-NoDerivs 3.0 Ireland
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Ireland