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Prediction of toxigenic fungal growth in buildings by using a novel modelling system

Rowan, N.J., Johnstone, C.M., McLean, R.C., Anderson, J.G. and Clarke, J.A.
1999
Applied and Environmental Microbiology, 65 (11): 4814-4821
Water relations, stachybotrys chartarum, aspergillus versicolor, toxin production, home dampness, mold growth, indoor air, health, exposure, requirements

Rowan, N.J., Johnstone, C.M., McLean, R.C., Anderson, J.G. and Clarke, J.A., (1999), "Prediction of toxigenic fungal growth in buildings by using a novel modelling system", Applied and Environmental Microbiology, 65 (11): 4814-4821.
Abstract:
There 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 a(3)T(3) + a(2)T(2) + a(1)T + a(o). 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.
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Author Information and Other Publications Notes
Rowan, N. J.
Department of Bioscience and Biotechnology, University of Strathclyde, Glasgow, UK
  1. A technique for the prediction of the conditions leading to mould growth in buildings  
Johnstone, C. M.
Energy Systems Research Unit, Department of Mechanical Engineering, University of Strathclyde, Glasgow, UK
  1. A technique for the prediction of the conditions leading to mould growth in buildings
  2. Development of a simulation tool for mould growth prediction in buildings
  3. On the use of simulation in the design of embedded energy systems  
McLean, R. C.
Energy Systems Research Unit, Department of Mechanical Engineering, University of Strathclyde, Glasgow, UK
  1. A technique for the prediction of the conditions leading to mould growth in buildings
  2. Development of a simulation tool for mould growth prediction in buildings
  3. Evaluation of discretized transport properties for numerical modelling of heat and moisture transfer in building structures
  4. Moisture permeability data presented as a mathematical relationship
  5. Nonisothermal moisture diffusion in porous building materials
  6. The application of X-ray absorption to building moisture transport studies
  7. The determination of vapour and liquid transport coefficients as input to combined heat mass transfer models
  8. The effect of temperature on the moisture permeability of building materials
  9. The selection of appropriate flow potentials for moisture transport models
  10. The use of differential permeabilty in moisture transport modelling  
Anderson, J. G.
     
Clarke, J. A.
Energy Systems Research Unit, Department of Mechanical Engineering, University of Strathclyde, Glasgow, UK
  1. A technique for the prediction of the conditions leading to mould growth in buildings
  2. Development of a simulation tool for mould growth prediction in buildings
  3. Energy simulation in building design
  4. Further developments in the conflation of CFD and building simulation
  5. Integrated Building Performance Simulation
  6. Integrated building simulation: state-of-the-art, Introducing Building Energy Simulation Classes on the Web
  7. Integrating CFD and building simulation
  8. Numerical modelling and thermal simulation of PCM¨Cgypsum composites with ESP-r
  9. On the use of simulation in the design of embedded energy systems
  10. Performance Prediction Tools for Low Impact Building Design
  11. Simulation Tools For The Exploitation Of Renewable Energy In The Built Environment: The Entrack-Gis System  


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