Respiratory infection risk-based ventilation design method

Abstract

A new design method is proposed to calculate outdoor air ventilation rates to control respiratory infection risk in indoor spaces. We propose to use this method in future ventilation standards to complement existing ventilation criteria based on the perceived air quality and pollutant removal. The proposed method makes it possible to calculate the required ventilation rate at a given probability of infection and quanta emission rate. Present work used quanta emission rates for SARS-CoV-2 and consequently the method can be applied for other respiratory viruses with available quanta data. The method was applied to case studies representing typical rooms in public buildings. To reduce the probability of infection, the total airflow rate per infectious person revealed to be the most important parameter to reduce the infection risk. Category I ventilation rate prescribed in the EN 16798-1 standard satisfied many but not all type of spaces examined. The required ventilation rates started from about 80 L/s per room. Large variations between the results for the selected case studies made it impossible to provide a simple rule for estimating the required ventilation rates. Consequently, we conclude that to design rooms with a low infection risk the newly developed ventilation design method must be used.

Keywords: Airborne pathogens; COVID-19; Design method; Event reproduction number; Quanta emission; Respiratory infection; Ventilation criteria; Ventilation standards.

Fig. 1

Illustration of how a viral load of an infectious person leads to aerosol concentration in a room. At about 1.5 m distance from the source the virus concentration has decreased to a constant level depending on the emission rate and removal mechanisms.

Fig. 2

Illustration of the dependency of probability and the number of new disease cases calculated with fixed occupant density of 2.19 m² per person and ventilation rate 3.9 L/s m² so that the number of occupants and floor area is varied. Two persons in the figure correspond a floor area of 4.4 m² and 50 persons to 109 m².

Fig. 3

Probability of infection in some rooms at 5 quanta/h and ventilation rates as reported in Table 4. Category III ventilation rates are calculated additionally for an open plan office and classroom. Solid lines without markers show the effect of steady state approximation, while lines with markers represent a dynamic concentration build-up.

Fig. 4

Probability of infection in rooms with shorter occupancy time, ventilation rates and other input data as reported in Table 4. Solid lines without markers show the effect of steady state approximation, while lines with markers represent a dynamic concentration build-up.

Fig. 5

Respiratory infection-based ventilation rates at three probability of infection levels compared with Category II and I ventilation rates for the case study rooms with sedentary activities with minor oral communication (5 quanta/h), a) without masks and b) with facial masks (mask filtration efficiency 0.5 for an infected person and 0.3 for susceptible persons).

Fig. 6

Required ventilation rates without masks calculated with individual probability values corresponding to R = 0.5, but maximum probability limited to 0.1, with a 2-day occupancy. Occupancy times in offices and classrooms reported in Table 3 are doubled, but the same 2 h occupancy time is used for the meeting rooms.