Skip to main content
SpringerLink
Log in

Optimising multi-vent module-based adaptive ventilation using a novel parameter for improved indoor air quality and health protection

  • Research Article
  • Indoor/Outdoor Airflow and Air Quality
  • Published:
Building Simulation Aims and scope Submit manuscript

Abstract

As infectious respiratory diseases are highly transmissible through the air, researchers have improved traditional total volume air distribution systems to reduce infection risk. Multi-vent module-based adaptive ventilation (MAV) is a novel ventilation type that facilitates the switching of inlets and outlets to suit different indoor scenarios without changing ductwork layout. However, little research has evaluated MAV module sizing and air velocity selection, both related to MAV system efficiency in removing contaminants and the corresponding level of protection for occupants in the ventilated room. Therefore, the module-source offset ratio (MSOR) is proposed, based on the MAV module size and its distance from an infected occupant, to inform selection of optimal MAV module parameters. Computational fluid dynamics simulations illustrated contaminant distribution in a two-person MAV equipped office. Discrete phase particles modelled respiratory contaminants from the infected occupant, and contaminant concentration distributions were compared under four MAV air distribution layouts, three air velocities, and three module sizes considered using the MSOR. Results indicate that lower air velocities favour rising contaminant levels, provided the ventilation rate is met. Optimal contaminant discharge can be achieved when the line of outlets is located directly above the infected occupant. Using this parameter to guide MAV system design, 85.7% of contaminants may be rendered harmless to the human body within 120 s using the default air vent layout. A more appropriate supply air velocity and air vent layout increases this value to 91.4%. These results are expected to inform the deployment of MAV systems to reduce airborne infection risk.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

C :

location of contaminant source (x, y)

C e :

averaged tracer-gas or particle concentration at the two exhausts (ppm)

C p :

particle concentration at the measured location (ppm)

C s :

particle concentration at the air supply inlet (ppm)

G s :

supply airflow rate (m3/s)

L :

length of line connecting two adjacent air vents (m)

MSOR :

module source offset ratio (—)

O :

centre point of MAV module air vents (0, 0)

R c :

particle release rate

s :

largest offset of the source from the origin (m)

x :

distance from C to x-axis

y :

distance from C to y-axis

ε :

dimensionless particle concentration (—)

References

  • Bauman F, Webster T (2001). Outlook for underfloor air distribution. ASHRAE Journal, 43(6): 18–27.

    Google Scholar 

  • Boyle R (1899). Natural and Artificial Methods of Ventilation, London: Robert Boyle & Son, Ltd.

    Google Scholar 

  • Cao G, Nielsen PV, Jensen RL, ET AL. (2015). Protected zone ventilation and reduced personal exposure to airborne cross-infection. Indoor Air, 25: 307–319.

    Article  Google Scholar 

  • Gupta JK, Lin C-H, Chen Q (2010). Characterizing exhaled airflow from breathing and talking. Indoor Air, 20: 31–39.

    Article  Google Scholar 

  • Karimipanah T, Awbi HB (2002). Theoretical and experimental investigation of impinging jet ventilation and comparison with wall displacement ventilation. Building and Environment, 37: 1329–1342.

    Article  Google Scholar 

  • Kutter JS, Spronken MI, Fraaij PL, et al. (2018). Transmission routes of respiratory viruses among humans. Current Opinion in Virology, 28: 142–151.

    Article  Google Scholar 

  • Lin Z, Chow TT, Tsang CF, et al. (2009). Stratum ventilation—A potential solution to elevated indoor temperatures. Building and Environment, 44: 2256–2269.

    Article  Google Scholar 

  • Melikov AK (2004). Personalized ventilation. Indoor Air, 14: 157–167.

    Article  Google Scholar 

  • Melikov AK (2011). Advanced air distribution. ASHRAE Journal, 53(11): 73–77.

    Google Scholar 

  • Melikov AK (2016). Advanced air distribution: Improving health and comfort while reducing energy use. Indoor Air, 26: 112–124.

    Article  Google Scholar 

  • Morawska L, Cao J (2020). Airborne transmission of SARS-CoV-2: The world should face the reality. Environment International, 139: 105730.

    Article  Google Scholar 

  • Morawska L, Johnson GR, Ristovski ZD, et al. (2009). Size distribution and sites of origin of droplets expelled from the human respiratory tract during expiratory activities. Journal of Aerosol Science, 40: 256–269.

    Article  Google Scholar 

  • Müller D, Kandzia C, Kosonen R, et al. (2013). Mixing ventilation. Guide on mixing air distribution design. REHVA: Federation of European Heating and Air-conditioning Associations.

    Google Scholar 

  • Nielsen PV (2009). Control of airborne infectious diseases in ventilated spaces. Journal of the Royal Society, Interface, 6: S747–S755.

    Article  Google Scholar 

  • Nielsen PV, Olmedo I, de Adana MR, et al. (2012). Airborne cross-infection risk between two people standing in surroundings with a vertical temperature gradient. HVAC&R Research, 18: 552–561.

    Article  Google Scholar 

  • Olmedo I, Nielsen PV, Ruiz de Adana M, et al. (2013). The risk of airborne cross-infection in a room with vertical low-velocity ventilation. Indoor Air, 23: 62–73.

    Article  Google Scholar 

  • Owen MS (2009). ASHRAE Handbook: Fundamentals, Atlanta: American Society of Heating, Refrigeration, and Air-Conditioning Engineers.

    Google Scholar 

  • Pantelic J, Tham KW, Licina D (2015). Effectiveness of a personalized ventilation system in reducing personal exposure against directly released simulated cough droplets. Indoor Air, 25: 683–693.

    Article  Google Scholar 

  • Pascal PH, Oesterlé B (2000). On the dispersion of discrete particles moving in a turbulent shear flow. International Journal of Multiphase Flow, 26: 293–325.

    Article  Google Scholar 

  • Sehulster LM, Chinn RYW, Arduino MJ, et al. (2003). Guidelines for Environmental Infection Control in Health-care Facilities: Recommendations from CDC and the Healthcare Infection Control Practices Advisory Committee (HICPAC). Chicago: American Society for Healthcare Engineering/American Hospital Association.

    Google Scholar 

  • Skistad H, Mundt E, Nielsen PV, et al. (2002). Displacement Ventilation in Non-industrial Premises. PREHVA Guidebook No. 1. REHVA: Federation of European Heating and Air-conditioning Associations.

    Google Scholar 

  • Wei X, Yi D, Xie W, et al. (2021). Protection against inhalation of gaseous contaminants in industrial environments by a personalized air curtain. Building and Environment, 206: 108343.

    Article  Google Scholar 

  • Xu Y, Cao C, Ma M, et al. (2022). Direction air supply design and optimization in industrial settings to reduce gaseous contaminant exposure. Building and Environment, 216: 109003.

    Article  Google Scholar 

  • Yao T, Lin Z (2014). An experimental and numerical study on the effect of air terminal layout on the performance of stratum ventilation. Building and Environment, 82: 75–86.

    Article  Google Scholar 

  • Yin Y, Gupta JK, Zhang X, et al. (2011). Distributions of respiratory contaminants from a patient with different postures and exhaling modes in a single-bed inpatient room. Building and Environment, 46: 75–81.

    Article  Google Scholar 

  • Yin H, Li A, Liu Z, et al. (2016). Experimental study on airflow characteristics of a square column attached ventilation mode. Building and Environment, 109: 112–120.

    Article  Google Scholar 

  • Zhang C, Heiselberg P, Nielsen PV (2014). Diffuse ceiling ventilation—A review. International Journal of Ventilation, 13: 49–64.

    Article  Google Scholar 

  • Zhang R, Li Y, Zhang AL, et al. (2020). Identifying airborne transmission as the dominant route for the spread of COVID-19. Proceedings of the National Academy of Sciences, 117: 14857–14863.

    Article  Google Scholar 

  • Zhang H, Zhang W, Zhang W, et al. (2022). Multi-vent module-based adaptive ventilation to reduce cross-contamination among indoor occupants. Building and Environment, 212: 108836.

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China [No. 52078009]; the special fund of Beijing Key Laboratory of Indoor Air Quality Evaluation and Control [No. BZ0344KF20-05]; and the joint research project of the Wind Engineering Research Center, Tokyo Polytechnic University (MEXT (Japan) Promotion of Distinctive Joint Research Center Program) [No. JPMXP0619217840, No. JURC 20202007].

Author information

Authors and Affiliations

  1. Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China

    Haotian Zhang, Xiaoxiao Ding, Weirong Zhang & Weijia Zhang

  2. Department of Architecture, Tokyo Polytechnic University, Tokyo, Japan

    Yingli Xuan

Authors
  1. Haotian Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaoxiao Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Weirong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Weijia Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yingli Xuan
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: Haotian Zhang, Weijia Zhang; methodology: Haotian Zhang; validation: Haotian Zhang; visulaization: Haotian Zhang; data curation: Xiaoxiao Ding; project administration: Weirong Zhang; writing—original draft preparation: Haotian Zhang; writing—review and editing: Weirong Zhang; funding acquisition: Weirong Zhang, Yingli Xuan; wupervision: Weirong Zhang.

Corresponding author

Correspondence to Weirong Zhang.

Ethics declarations

Declaration of competing interest

The authors have no competing interests to declare that are relevant to the content of this article.

Ethical approval

This study does not contain any studies with human or animal subjects performed by any of the authors.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, H., Ding, X., Zhang, W. et al. Optimising multi-vent module-based adaptive ventilation using a novel parameter for improved indoor air quality and health protection. Build. Simul. 17, 113–130 (2024). https://doi.org/10.1007/s12273-023-1063-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12273-023-1063-8

Keywords

Search

Navigation