Building Simulation

, Volume 7, Issue 1, pp 57–71 | Cite as

Contaminant ingress into multizone buildings: An analytical state-space approach

  • Simon Parker
  • Chris Coffey
  • Jens Gravesen
  • James Kirkpatrick
  • Keith Ratcliffe
  • Bryan Lingard
  • James Nally
Research Article Indoor/Outdoor Airflow and Air Quality

Abstract

The ingress of exterior contaminants into buildings is often assessed by treating the building interior as a single well-mixed space. Multizone modelling provides an alternative way of representing buildings that can estimate concentration time series in different internal locations. A state-space approach is adopted to represent the concentration dynamics within multizone buildings. Analysis based on this approach is used to demonstrate that the exposure in every interior location is limited to the exterior exposure in the absence of removal mechanisms. Estimates are also developed for the short term maximum concentration and exposure in a multizone building in response to a step-change in concentration. These have considerable potential for practical use. The analytical development is demonstrated using a simple two-zone building with an inner zone and a range of existing multizone models of residential buildings. Quantitative measures are provided of the standard deviation of concentration and exposure within a range of residential multizone buildings. Ratios of the maximum short term concentrations and exposures to single zone building estimates are also provided for the same buildings.

Keywords

indoor dispersion exposure multizone shelter-in-place state space 

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References

  1. Armour T (2011). European study group with industry 80: Analytical solutions for compartmental models of contaminant transport in enclosed spaces. Technical Report, Industrial Mathematics KTN.Google Scholar
  2. Bekö G, Lund T, Nors F, Toftum J, Clausen G (2010). Ventilation rates in the bedrooms of 500 Danish children. Building and Environment, 45: 2289–2295.CrossRefGoogle Scholar
  3. Bennett JS (2009). A systems approach to the design of safe-rooms for shelter-in-place. Building Simulation, 2: 41–51.CrossRefGoogle Scholar
  4. Casal J, Planas-Cuchi E, Casal J (1999). Sheltering as a measure against airborne virus spread. Journal of Hazardous Materials, 68: 179–189.CrossRefGoogle Scholar
  5. Chan WR, Nazaroff WW, Price PN, Gadgil AJ (2007a). Effectiveness of urban shelter-in-place. I: Idealized conditions. Atmospheric Environment, 41: 4962–4976.CrossRefGoogle Scholar
  6. Chan WR, Nazaroff WW, Price PN, Gadgil AJ (2007b). Effectiveness of urban shelter-in-place. II: Residential districts. Atmospheric Environment, 41: 7082–7095.CrossRefGoogle Scholar
  7. Chan WR, Nazaroff WW, Price PN, Gadgil AJ (2008). Effectiveness of urban shelter-in-place. III: Commercial districts. Building Simulation, 1: 144–157.CrossRefGoogle Scholar
  8. Haas A, Weber A, Dorer V, Keilholz W, Pelletret R (2002). COMIS v3.1 simulation environment for multizone air flow and pollutant transport modelling. Energy and Buildings, 34: 873–882.CrossRefGoogle Scholar
  9. Howard-Reed C, Nabinger SJ, Emmerich SJ (2008). Characterizing gaseous air cleaner performance in the field. Building and Environment, 43: 368–377.CrossRefGoogle Scholar
  10. Jacquez JA (1996). Compartmental Analysis in Biology and Medicine, 3rd edn. Ann Arbor, MI, USA: BioMedware.Google Scholar
  11. Jacquez JA, Simon CP (1993). Qualitative theory of compartmental-systems. SIAM Review, 35: 43–79.MathSciNetCrossRefMATHGoogle Scholar
  12. Kaplan H (2009). A model for the toxic dose under time-varying concentration. Journal of Hazardous Materials, 167: 351–356.CrossRefGoogle Scholar
  13. Konartit C, Sokhi RS, Burton MA, Ravindra K (2010). Activity pattern and personal exposure to nitrogen dioxide in indoor and outdoor microenvironments. Environment International, 36: 36–45.CrossRefGoogle Scholar
  14. Lai ACK (2004). Modeling of airborne particle exposure and effectiveness of engineering control strategies. Building and Environment, 39: 599–610.CrossRefGoogle Scholar
  15. van Leeuwen D (1992). Protection against toxic substances by remaining indoors. In: Methods for the Determination of Possible Damage to People and Objects Resulting from Releases of Hazardous Materials CPR 16E (Green Book, Chapter 6). Voorburg, The Netherlands: TNO.Google Scholar
  16. Lim T, Cho J, Kim BS (2011). Predictions and measurements of the stack effect on indoor airborne virus transmission in a high-rise hospital building. Building and Environment, 46: 2413–2424.CrossRefGoogle Scholar
  17. Liu X, Zhai ZJ (2009). Prompt tracking of indoor airborne contaminant source location with probability-based inverse multi-zone modeling. Building and Environment, 44: 1135–1143.CrossRefGoogle Scholar
  18. Miller RS (2011). Elevator shaft pressurization for smoke control in tall buildings: The Seattle approach. Building and Environment, 46: 2247–2254.CrossRefGoogle Scholar
  19. Montoya MI, Planas E, Casal J (2009). A comparative analysis of mathematical models for relating indoor and outdoor toxic gas concentrations in accidental releases. Journal of Loss Prevention in the Process Industries, 22: 381–391.CrossRefGoogle Scholar
  20. Parker S, Coffey C (2011). Analytical solutions for exposures and toxic loads in well-mixed shelters in support of shelter-in-place assessments. Journal of Hazardous Materials, 192: 419–422.Google Scholar
  21. Parker ST, Bowman VE (2011). State-space methods for calculating concentration dynamics in multizone buildings. Building and Environment, 46: 1567–1577.CrossRefGoogle Scholar
  22. Persily A, Musser A, Leber D (2006). A collection of homes to represent the U.S. housing stock. Technical Report, NISTIR 7330, National Institute of Standards and Technology.Google Scholar
  23. Persily A, Davis H, Emmerich SJ, Dols WS (2009). Airtightness evaluation of shelter-in-place spaces for protection against airborne chemical and biological releases. Technical Report, NISTIR 7546, National Institute of Standards and Technology.Google Scholar
  24. Singer BC, Hodgson AT, Destaillats H, Hotchi T, Revzan KL, Sextro RG (2005). Indoor sorption of surrogates for sarin and related nerve agents. Environmental Science and Technology, 39: 3203–3214.CrossRefGoogle Scholar
  25. Singer BC, Hodgson AT, Hotchi T, Ming KY, Sextro RG, Wood EE, Brown NJ (2007). Sorption of organic gases in residential rooms. Atmospheric Environment, 41: 3251–3265.CrossRefGoogle Scholar
  26. Sohn MD, Apte MG, Sextro RG, Lai ACK (2007). Predicting size-resolved particle behavior in multizone buildings. Atmospheric Environment, 41: 1473–1482.CrossRefGoogle Scholar
  27. Sorensen JH, Shumpert BL, Vogt BM (2004). Planning for protective action decision making: Evacuate or shelter-in-place. Journal of Hazardous Materials, 109: 1–11.CrossRefGoogle Scholar
  28. Ten Berge W, Zwart A, Appelman L (1986). Concentration-time mortality response relationship of irritant and systemically acting vapours and gases. Journal of Hazardous Materials, 13: 301–309.CrossRefGoogle Scholar
  29. Walton GN, Dols WS (2010). CONTAMW user guide and program documentation. Technical Report, NISTIR 7251, National Institute of Standards and Technology.Google Scholar

Copyright information

© Tsinghua University Press and Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Simon Parker
    • 1
  • Chris Coffey
    • 2
  • Jens Gravesen
    • 3
  • James Kirkpatrick
    • 4
  • Keith Ratcliffe
    • 1
  • Bryan Lingard
    • 1
  • James Nally
    • 1
  1. 1.Dstl, Porton DownSalisbury, WiltshireUK
  2. 2.GexCon UKWest Lancashire Investment CentreSkelmersdale, LancashireUK
  3. 3.Department of MathematicsTechnical University of DenmarkKgs. LyngbyDenmark
  4. 4.Oxford Centre for Collaborative Applied MathematicsOxfordUK

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