Skip to main content
PMC home page
Springer Nature - PMC COVID-19 Collection logoLink to Springer Nature - PMC COVID-19 Collection
. 2017 Jul 10;11(1):193–202. doi: 10.1007/s12273-017-0388-6

Air infiltration induced inter-unit dispersion and infectious risk assessment in a high-rise residential building

Yan Wu 1, Jianlei Niu 2,✉, Xiaoping Liu 3
PMCID: PMC7090850  PMID: 32218902

Abstract

Identifying possible airborne transmission routes and assessing the associated infectious risks are essential for implementing effective control measures. This study focuses on the infiltration-induced inter-unit pollutant dispersion in a high-rise residential (HRR) building. The outdoor wind pressure distribution on the building facades was obtained from the wind tunnel experiments. And the inter-household infiltration and tracer gas transmission were simulated using multi-zone model. The risk levels along building height and under different wind directions were examined, and influence of component leakage area was analysed. It is found that, the cross-infection risk can be over 20% because of the low air infiltration rate below 0.7 ACH, which is significantly higher than the risk of 9% obtained in our previous on-site measurement with air change rate over 3 ACH. As the air infiltration rate increases along building height, cross-infection risk is generally higher on the lower floors. The effect of wind direction on inter-unit dispersion level is significant, and the presence of a contaminant source in the windward side results in the highest cross-infection risks in other adjacent units on the same floor. Properly improving internal components tightness and increasing air change via external components are beneficial to the control of internal inter-unit transmission induced by infiltration. However, this approach may increase the cross-infection via the external transmission, and effective control measures should be further explored considering multiple transmission routes.

Keywords: air infiltration, inter-unit dispersion, infectious risk assessment, multi-zone modeling, wind tunnel experiment

Acknowledgements

The research is financially funded by Health and Medical Research Fund, Hong Kong SAR Government, with the project reference no.13121442.

References

  1. Ai ZT, Mak CM. A study of interunit dispersion around multistory buildings with single-sided ventilation under different wind directions. Atmospheric Environment. 2014;88:1–13. doi: 10.1016/j.atmosenv.2014.01.049. [DOI] [Google Scholar]
  2. Ai ZT, Mak CM. Large eddy simulation of wind-induced interunit dispersion around multistory buildings. Indoor Air. 2016;26:259–273. doi: 10.1111/ina.12200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. ASHRAE . ASHRAE Handbook—HVAC applications. Atlanta, GA, USA: American Society of Heating, Refrigerating and Air Conditioning Engineers; 2007. [Google Scholar]
  4. Cheng CKC, Lam KM, Leung YTA, Yang K, Li DHW, Cheung SCP. Wind-induced natural ventilation of re-entrant bays in a high-rise building. Journal of Wind Engineering and Industrial Aerodynamics. 2011;99:79–90. doi: 10.1016/j.jweia.2010.11.002. [DOI] [Google Scholar]
  5. Emmerich SJ. Validation of multizone IAQ modeling of residential-scale buildings: A review. ASHRAE Transactions. 2001;107(2):619–628. [Google Scholar]
  6. Gao NP, Niu JL, Perino M, Heiselberg P. The airborne transmission of infection between flats in high-rise residential buildings: Tracer gas simulation. Building and Environment. 2008;43:1805–1817. doi: 10.1016/j.buildenv.2007.10.023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Gao NP, Niu JL, Perino M, Heiselberg P. The airborne transmission of infection between flats in high-rise residential buildings: Particle simulation. Building and Environment. 2009;44:402–410. doi: 10.1016/j.buildenv.2008.03.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Jomehzadeh F, Nejat P, Calautit JK, Yusof MBM, Zaki SA, Hughes BR, Yazid MNAWM. A review on windcatcher for passive cooling and natural ventilation in buildings, Part 1: Indoor air quality and thermal comfort assessment. Renewable and Sustainable Energy Reviews. 2016;70:736–756. doi: 10.1016/j.rser.2016.11.254. [DOI] [Google Scholar]
  9. Karava P, Stathopoulos T, Athienitis AK. Impact of internal pressure coefficients on wind-driven ventilation analysis. International Journal of Ventilation. 2006;5:53–66. doi: 10.1080/14733315.2006.11683724. [DOI] [Google Scholar]
  10. Karava P, Stathopoulos T, Athienitis AK. Wind-induced natural ventilation analysis. Solar Energy. 2007;81:20–30. doi: 10.1016/j.solener.2006.06.013. [DOI] [Google Scholar]
  11. Karava P, Stathopoulos T, Athienitis AK. Airflow assessment in cross-ventilated buildings with operable façade elements. Building and Environment. 2011;46:266–279. doi: 10.1016/j.buildenv.2010.07.022. [DOI] [Google Scholar]
  12. Kobayashi T, Sagara K, Yamanaka T, Kotani H, Takeda S, Sandberg M. Stream tube based analysis of problems in prediction of cross-ventilation rate. International Journal of Ventilation. 2009;7:321–334. doi: 10.1080/14733315.2009.11683822. [DOI] [Google Scholar]
  13. Kobayashi T, Sandberg M, Kotani H, Claesson L. Experimental investigation and CFD analysis of cross-ventilated flow through single room detached house model. Building and Environment. 2010;45:2723–2734. doi: 10.1016/j.buildenv.2010.06.001. [DOI] [Google Scholar]
  14. Lai ACK, Nazaroff WW. Modeling indoor particle deposition from turbulent flow onto smooth surfaces. Journal of Aerosol Science. 2000;31:463–476. doi: 10.1016/S0021-8502(99)00536-4. [DOI] [Google Scholar]
  15. Li Y, Delsante A, Symons J. Prediction of natural ventilation in buildings with large openings. Building and Environment. 2000;35:191–206. doi: 10.1016/S0360-1323(99)00011-6. [DOI] [Google Scholar]
  16. Li Y, Duan S, Yu IT, Wong TW. Multi-zone modeling of probable SARS virus transmission by airflow between flats in Block E, Amoy Gardens. Indoor Air. 2005;15:96–111. doi: 10.1111/j.1600-0668.2004.00318.x. [DOI] [PubMed] [Google Scholar]
  17. Li Y, Leung GM, Tang JW, Yang X, Chao CYH, Lin JZ, Lu JW, Nielsen PV, Niu J, Qian H, et al. Role of ventilation in airborne transmission of infectious agents in the built environment—A multidisciplinary systematic review. Indoor Air. 2007;17:2–18. doi: 10.1111/j.1600-0668.2006.00445.x. [DOI] [PubMed] [Google Scholar]
  18. Liu D-L, Nazaroff WW. Particle penetration through building cracks. Aerosol Science and Technology. 2003;37:565–573. doi: 10.1080/02786820300927. [DOI] [Google Scholar]
  19. Liu XP. Experimental and numerical investigation of air crosscontamination around typical high-rise residential building in Hong Kong. 2011. [Google Scholar]
  20. Liu XP, Niu JL, Kwok KCS, Wang JH, Li BZ. Investigation of indoor air pollutant dispersion and cross-contamination around a typical high-rise residential building: Wind tunnel tests. Building and Environment. 2010;45:1769–1778. doi: 10.1016/j.buildenv.2010.02.003. [DOI] [Google Scholar]
  21. Liu XP, Niu JL, Kwok KC, Wang JH, Li BZ. Local characteristics of cross-unit contamination around high-rise building due to wind effect: Mean concentration and infection risk assessment. Journal of Hazardous Materials. 2011;192:160–167. doi: 10.1016/j.jhazmat.2011.09.014. [DOI] [PubMed] [Google Scholar]
  22. Nicas M, Nazaroff WW, Hubbard A. Toward understanding the risk of secondary airborne infection: emission of respirable pathogens. Journal of Occupational and Environmental Hygiene. 2005;2:143–154. doi: 10.1080/15459620590918466. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Niu J, Tung TCW. On-site quantification of re-entry ratio of ventilation exhausts in multi-family residential buildings and implications. Indoor Air. 2008;18:12–26. doi: 10.1111/j.1600-0668.2007.00500.x. [DOI] [PubMed] [Google Scholar]
  24. Nore K, Blocken B, Thue JV. On CFD simulation of windinduced airflow in narrow ventilated facade cavities: Coupled and decoupled simulations and modelling limitations. Building and Environment. 2010;45:1834–1846. doi: 10.1016/j.buildenv.2010.02.014. [DOI] [Google Scholar]
  25. Parker ST, Lorenzetti DM, Sohn MD. Implementing state-space methods for multizone contaminant transport. Building and Environment. 2014;71:131–139. doi: 10.1016/j.buildenv.2013.09.021. [DOI] [Google Scholar]
  26. Ramponi R, Blocken B. CFD simulation of cross-ventilation for a generic isolated building: Impact of computational parameters. Building and Environment. 2012;53:34–48. doi: 10.1016/j.buildenv.2012.01.004. [DOI] [Google Scholar]
  27. Riley EC, Murphy G, Riley RL. Airborne spread of measles in a suburban elementary school. American Journal of Epidemiology. 1978;107:421–432. doi: 10.1093/oxfordjournals.aje.a112560. [DOI] [PubMed] [Google Scholar]
  28. Riley RL. Airborne infection. The American Journal of Medicine. 1974;57:466–475. doi: 10.1016/0002-9343(74)90140-5. [DOI] [PubMed] [Google Scholar]
  29. Sandberg M. An alternative view on the theory of crossventilation. International Journal of Ventilation. 2004;2:409–418. doi: 10.1080/14733315.2004.11683682. [DOI] [Google Scholar]
  30. Seifert J, Li Y, Axley J, Rösler M. Calculation of wind-driven cross ventilation in buildings with large openings. Journal of Wind Engineering and Industrial Aerodynamics. 2006;94:925–947. doi: 10.1016/j.jweia.2006.04.002. [DOI] [Google Scholar]
  31. Standard ANZ. AS/NZS 1170.2: 2011 Structural Design Actions—Part 2: Wind actions. 2011. [Google Scholar]
  32. Temenos N, Nikolopoulos D, Petraki E, Yannakopoulos PH. Modelling of indoor air quality of Greek apartments using CONTAM (W) software. Journal of Physical Chemistry & Biophysics. 2015;5:190. doi: 10.4172/2161-0398.1000190. [DOI] [Google Scholar]
  33. Tung TCW, Chao CYH, Burnett J. A methodology to investigate the particulate penetration coefficient through building shell. Atmospheric Environment. 1999;33:881–893. doi: 10.1016/S1352-2310(98)00299-4. [DOI] [Google Scholar]
  34. Walton GN, Dols WS. NISTIR 7251, CONTAM 2.4 User Guide and Program Documentation. Gaithersburg, MD, USA: National Institute of Standards and Technology; 2003. [Google Scholar]
  35. Wang JH, Niu JL, Liu XP, Yu CWF. Assessment of pollutant dispersion in the re-entrance space of a high-rise residential building, using wind tunnel simulations. Indoor and Built Environment. 2010;19:638–647. doi: 10.1177/1420326X10386669. [DOI] [Google Scholar]
  36. Wang LL, Dols WS, Chen Q. Using CFD capabilities of CONTAM 3.0 for simulating airflow and contaminant transport in and around buildings. HVAC&R Research. 2010;16:749–763. doi: 10.1080/10789669.2010.10390932. [DOI] [Google Scholar]
  37. Wu Y, Niu J. Assessment of mechanical exhaust in preventing vertical cross-household infections associated with single-sided ventilation. Building and Environment. 2016;105:307–316. doi: 10.1016/j.buildenv.2016.06.005. [DOI] [Google Scholar]
  38. Wu Y, Niu J. Numerical study of inter-building dispersion in residential environments: Prediction methods evaluation and infectious risk assessment. Building and Environment. 2017;115:199–214. doi: 10.1016/j.buildenv.2017.01.029. [DOI] [Google Scholar]
  39. Wu Y, Tung TCW, Niu JL. On-site measurement of tracer gas transmission between horizontal adjacent flats in residential building and cross-infection risk assessment. Building and Environment. 2016;99:13–21. doi: 10.1016/j.buildenv.2016.01.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Yu IT, Li Y, Wong TW, Tam W, Chan AT, Lee JH, Leung DY, Ho T. Evidence of airborne transmission of the severe acute respiratory syndrome virus. New England Journal of Medicine. 2004;350:1731–1739. doi: 10.1056/NEJMoa032867. [DOI] [PubMed] [Google Scholar]

Articles from Building Simulation are provided here courtesy of Nature Publishing Group

RESOURCES