Can ventilation combat airborne infection risks in schools?

Keywords: hybrid ventilation, natural ventilation, mechanical ventilation, viral transmission, EN 16798-1, ISO 17772-1, ASHRAE standard 241, SARS-CoV-2, pandemic preparedness.

Abstract

The COVID-19 pandemic caught policy makers, government agencies, school management and facility managers largely off-guard, prompting a review of existing ventilation standards in relation to the mitigating of airborne viral diseases. In light of new guidance in ASHRAE standard 241-2023 ‘Control of Infectious Aerosols’ this paper examines the relative airborne viral prophylaxis benefit of seven different ventilation scenarios, involving natural, mechanical and hybrid ventilation systems. The research aims to assess the relative merits of each approach considering current guidance in European Norm (EN 16798-1) and International Standard (ISO 17772-1) in contrast to the increased minimum equivalent clean airflow rates for classrooms in ASHRAE 241.

The results of this analysis show that increased minimum equivalent clean airflow rates have a marked effect on reducing the airborne viral transmission risk. However, even with the best performing ventilation system the risk of at least one individual becoming infected with the SARS-CoV-2 Omicron variant (after an 8 h long exposure period) was 30% (assuming that one infectious individual was present in a classroom of 20 unmasked, immunologically naïve students). By using a combined strategy involving universal FFP2 masking and ventilation the group infection risk level was dramatically reduced to 2–7% (depending on the ventilation type and flowrate) highlighting the importance of layered prophylaxis strategies at times of elevated community transmission.

Introduction

An international review in 2021 by the Global Health Security (GHS) Index [1] highlighted the sobering fact, that “all countries remain dangerously unprepared to meet future epidemic and pandemic threats.” The GHS Index measures the capacities of 195 countries to prepare for epidemics and pandemics and the average overall GHS country score in 2021 was slightly worse (38.9 out of 100) than in 2019 (40.2 out of 100). Even the “best prepared” countries (USA, Australia, Finland) do not reach the top tier of the GHS Index (i.e. score > 80), indicating that overall pandemic preparedness is “fundamentally weak at all country income levels” (Bell and Nuzzo 2021) (Figure 1).

Figure 1. Overall risk ranking according to 2021 Global Health Security Index, which measures the capacities of countries to prepare for epidemics and pandemics (adapted from GHS Index 2021 data).

The role of schools in the transmission of the SARS-CoV2 virus has been extensively debated. Despite widespread acceptance of the need to maintain in-classroom teaching (WHO Europe 2021) there is no consensus as to what level of mitigation is needed to do this safely (Lessler et al. 2021).

International building services organisations including REHVA, CIBSE, ASHRAE (amongst others) were quick to provide detailed pandemic ventilation guidance and to continually update that information in the light of emerging knowledge. At a policy and advisory level this work is continuing, for example in July 2023 ASHRAE issued Standard 241,Control of Infectious Aerosols (ASHRAE 2023) and has revised many of its existing ventilation standards to reflect emerging scientific findings in relation to the role of ventilation in mitigating the transmission of airborne disease. Pandemic preparedness implies the practical implementation of such changes, typically in a relatively short time scale, and that this requirement is poorly aligned with traditional policy and legislative processes (Caulfield 2013). Moreover, there are financial and resource constraints, wherein for example, retrofitting a single school with an appropriately sized ducted MVHR systems might cost upwards of 10,000 Euros per classroom (Checkatrade 2022). Even ignoring the resource and sustainability implications, rolling out such a strategy at a national scale in every European country would require enormous financial investment [2] and could take years to implement. Even if such a strategy were considered feasible and cost-effective in the more affluent countries of the global North (and could be sustained at a 10–20-year replacement interval) it is almost inconceivable that it could be implemented equitably across the global South. Thus existing health inequalities, highlighted by the disproportionate effects of COVID-19 on poorer nations (Oxfam 2022), could be further exacerbated over the longer term by a lack of affordable public health measures to address further waves and even endemicity.

In the light of these challenges, it became apparent that low-cost easy to install (e.g. DIY, Do It Yourself) responses to ventilation and air-cleaning enhancement could play an important role in reducing viral transmission in schools, in both the short and medium term. One such idea, for a novel hybrid mechanical extract ventilation (MEV) system, was developed by the Max Plank Institute for Chemistry (MPIC) in Mainz Germany (Klimach et al. 2022) (Figure 2). This concept was subsequently trialled in several hundred schools in Germany and independently tested by the IBPSC at TU Graz, Austria (Pollozhani et al. 2022) (Eibinger et al. 2022). This study builds on previous work [3] by providing a comparative analysis of the airborne infection risk associated with a range of different classroom ventilation strategies whilst also evaluating the additional prophylaxis benefits of using substantially increased ventilation airflow rates, as proposed by ASHRAE 241-2023: Control of Infectious Aerosols (ASHRAE 2023).

Methods

A university seminar room at Graz University of Technology was equipped with a low-cost retrofitted mechanical extract ventilation (MEV) system developed by the Max Planck Institute for Chemistry (MPIC), (Klimach et al. 2022) (Helleis, Klimach, and Pöschl 2023). Adopting the room geometry and using ventilation flow rate data from the experimental setup seven different ventilation scenarios (Table 1) were assessed over a one-year period using the IDA ICE dynamic simulation software (EQUA 2023). Based on the room occupancy and ventilation rates an analytical model based on a method developed by Lelieveld et al. (2020) was then used to predict the corresponding seasonal risk of infection with the SARS-CoV-2 original Omicron variant. Although the original Omicron variant is no longer the prevalent strain of the SARS-CoV-2 virus the results of this analysis are still useful from the perspective of making comparative risk assessments. Moreover, the viral transmission parameters (Table 2) can be readily modified to accommodate emerging variants or viruses.

Scenarios

Seven scenarios were considered in this study, as described in Table 1, to provide a comparative analysis between the MPIC-MEV system and common natural and mechanical alternatives.

Table 1. Ventilation scenarios.

Table 2. Parameters used in the analytical infection risk model (after Lelieveld et al. (2020)).

Experimental setup

The seminar room chosen for this study is typical of many naturally ventilated university teaching rooms, designed for approximately 30 occupants. The room is occupied from 8 a.m. to 5 p.m. daily, during term-time, for a variety of purposes including lectures, workshops, and exams. This means that the room occupancy varies over the course of a day and according to academic cycles. Since occupant density is known to be a significant factor in predicting infection risk (Clayson et al. 2022) a range of typical occupancy levels (n=10, 20 and 30) were investigated in this study.

Figure 3 shows the floor plan of the seminar room with the MPIC-MEV system overlaid. The room is located on the first floor of a five-storey high university building which was constructed in 1994. The room measured 6.5 by 8.1 m with a height of 3.05 m which (minus three vertical columns) results in a net internal volume of 147.3 m³. The exterior wall faces southwest, with five openable (tilt and turn) windows measuring 0.9 by 1.8 m providing a window-to-wall ratio of 33% (8.1 m² of 24.7 m² interior wall). The windows were equipped with external fixed-angle louvers, which shade approximately half of the windows’ solar aperture.

Figure 3. Floor plan of the seminar room showing the layout of the MPIC-MEV system.

Two hydronic wall mounted radiators (measuring 1.4 m by 0.5 m each) with an estimated combined design output of 4,700 W) provide heat to the room during the colder months. The seminar room is illuminated by 16 compact fluorescent lamps with an electric power consumption of 25 W each (400 W in total, with an estimated 30% convective heat fraction). In addition, a ceiling mounted projector with a power consumption of 150 W is installed in the room. Resulting in a maximum total internal heat gain of 550 W for lights and equipment. Occupant sensible and latent heat gains were assumed at 126 W/person at an average metabolic equivalent task (MET) rate of 1.2 (ISO 2005). The thermal specifications of the construction assemblies were sourced from an energy certificate issued in 2012. An average infiltration rate of 0.2 h−1was derived using human-generated CO₂ concentration decays in the space, based on the approach described by Persily (1997) and Cui et al. (2015).

In order to establish the in-situ performance of the non-commercial MPIC-MEV system, a fully functioning system was installed in the seminar room using materials widely available from building merchants, at a total cost of around 500 Euros (for more information about the ventilation system see (Klimach et al. 2021) (Helleis, Klimach, and Pöschl 2022)). The system is designed to extract stale room-air close to the ceiling and supply fresh air nearer to the floor level, through a tilted window (Figure 2). In the context of SARS-CoV-2, CFD studies have demonstrated that properly designed displacement ventilation provides an effective means of mitigating long-range transmission (Bhagat and Linden 2020) (Bhagat et al. 2020). Osman et al. (2023) also showed displacement systems are capable of reducing the range of horizontal droplet transfer from coughing episodes. Experimental evidence from the MPIC shows that the addition of extract hoods can further improve the removal of respiratory aerosols by about 30–50% (Helleis, Klimach, and Pöschl 2023).

A summary of the system parameters and operational schedules used the IDA ICE simulations can be seen in Table 3.

Table 3. List of scenarios and simulation parameters.

Based on the transient ventilation rates and design occupancy assumptions the infection risk, which is the main focus of this study, was analytically assessed based on a method developed by Lelieveld et al. (2020) using the parameters and value set out in Table 2.

For the original Omicron variant of the SARS-CoV-2 virus, 154 inhaled RNA copies were expected to correspond to an infectious dose (D50), the mean number of vial copies that would cause an infection in 50% of susceptible subjects [15]. The individual infection risk Ri(t) for each susceptible individual is calculated with the following formula (Eq.1) depending on the number of inhaled virus particles nv(t) and the probability PRNA that a single virus particle causes an infection:

Whilst the risk of a single individual from a group of individuals becoming infected is expressed as a function of the number of susceptible people in the room according to Eq. 2.

Where,

Ri(t)is the individual infection risk for each person [%],

R(t)is the probability of a single person getting infected from a group of susceptible people [%],

n is the number of susceptible (i.e. non-infected) individuals in the room,

nv(t) is the number of virus particles inhaled per person,

and PRNA is the probability that a single virus particle causes an infection.

The time-dependent airborne virus particle concentration (cv(t)) in the experimental room (under the assumption of one infectious person being present for the duration of time (t)) and the resulting quantity of inhaled virus particles per occupant (nv(t)) were determined for all five scenarios on sample days at different outside boundary temperatures according to the respective air exchange rates resulting from the dynamic simulation with the following formulas:

Where,

cv(t)is the concentration of infectious particles (virions) in the indoor air [No./m³] at time (t),

nvois the number of viral particles already inhaled by a person [No.],

cvo is the existing viral concentration in the room air [No./m³] at the start of the classes (t = 0),

qb,eff is the effective breathing rate [ℓ/min] (as described in table 2),

Eis the Emission factor [No./h] or rate at which viral copies are released (as described in Table 2)

Note, to account for the “hood effect” (ηhood) in the MPIC-MEV system the emission factor is modified as follows, EMPIC = E · (1− ηhood)

Results and analysis – comparative infection risk assessment

The risk of infection by the original Omicron variant of the SARS-CoV-2 virus, under the seven different ventilation scenarios (Table 1), was analysed for 20 occupants on the coldest (12th January) and warmest (30th June) design days to examine the influence of seasonal temperature variations on the natural and hybrid ventilation scenarios. Figure 4 shows the virus-containing respiratory aerosol concentration in the room air across the day c(t) (left) and the resulting group infection risk as a function of the exposure duration (right). The latter is the combined probability that at least one susceptible person from any of the group members (of n=20 people) will become infected. For the hybrid (MPIC-MEV) and mechanical (AHU) systems the results for airflow rates of 10 ℓ/s.(person) in accordance with EN16798-1:2019 (solid line, Figure 4) and 20 ℓ/s.(person) as recommended by ASHRAE Standard 241 (dashed lines, Figure 4) are shown. Note that the model assumes that the room is unoccupied and unventilated for one hour during the lunch period (12:00-13:00 h) (grey bar, Figure 4) and that the same occupants re-enter the room after lunch.

Figure 4. Virus concentration [No./m³] (left) and the probability of at least one person becoming infected [%] as a function of time (right) for 20 unmasked occupants on the coldest day (12th of January) and the warmest day (30th of June) of the year. Grey bars indicate the lunch break period (12:00-13:00 h) where the ventilation systems are turned off and the room is unoccupied. [Double column fitted]

Note that, due to the significantly higher viral concentration in the base case (scenario 1) it is depicted on a secondary x-axis with a different scaling (Figure 4, left), therefore, the slope of the base case appears disproportionally low compared to the other scenarios. It can be seen that by providing a constant air exchange rate in the hybrid and mechanical scenarios (orange and blue lines, Figure 4, left) a state of equilibrium is reached in the virus particle concentration present in the room. Conversely, as might be expected, varying air exchange rates, as seen in the purge-vent scenario (pale grey line, Figure 4, left), resulted in fluctuating viral particle counts.

Table 4. Infection risk probability [%] results for any one individual in a group of 20 people (with and without universal FFP2 masking) after 8 hours of exposure on the coldest day (12th of January, left) and the warmest day (30th of June, right) of the academic year.

As might be expected, the results (Table 4) show the highest risk of infection occurs in scenario 1 as there is no active ventilation. Under this scenario (assuming an immunologically naïve population) based on an occupancy of 20 persons, there is a probability of 100% that at least one person in the room would get infected during the 8-hour exposure period. If all people present in the room were to wear an FFP2 masks, this value could be reduced to 27%. Scenario 2 resulted in a risk of 47% without masking and 4% with masking that one out of the 20 people present in the room would become infected after a duration of 8 hours for both the best-case (cold outdoor temperatures) and worst-case (warm outdoor temperatures). Despite the same air exchange rates as for scenario 2, scenario 4 displayed a slightly higher risk of one amongst the 20 occupants becoming infected, with 57% without masking and 5% with masking. This difference between scenarios 2 and 4 can be attributed to the reduced room aerosol emission intensity achieved by the distributed (i.e. localised) extraction of potentially infectious aerosols using the MPIC-MEV system extract hoods.

In contrast the infection risk under the naturally ventilated scenarios showed a stronger dependence on the outdoor air temperatures. Due to the relatively high air exchange rates with continually tilted windows in cold weather (on12th of January) scenario 6 resulted in a lower risk (42% without masks and 3% with masks) cf. scenario 7 (purge ventilation) (59% without masks and 5% with masks). This finding is attributed to the 20-minute phases (between purges) in which the room was not ventilated at all, during which the concentration of virus-containing particles sharply increased to relatively high values (≈10 particles per m³ of room air, see Figure 4). In contrast, with warmer external air temperatures in summer, higher risk values were found with tilted windows (72% without masking and 7% with masking) due to the lower air exchange rate. Under the same conditions the use of purge venting resulted in a lower risk (59% without masking and 5% with masking), although it should be noted that the duration of the purge phase opening time was extended from 4 minutes to 15 minutes (every 20 minutes) in the summer months (Table 3). This finding highlights the importance of adjusting purge duration intervals in accordance with outside air temperatures or room CO₂ concentration.

By using larger fans and increasing the mechanical ventilation flow rate from 10 to 20 ℓ/s.(person), in line with ASHRAE Standard 241, the infection risks were further reduced for the MPIC-MEV system (scenario3) (to 30% without masking and 2% with masking) and for the AHU-HRV system (scenario 5) (to 37% without masking and 3% with masking). The additional benefit achieved by the MPIC system can be attributed to the use of hoods above the occupants.

Conclusion and limitations

The findings of this study have shown that the infectious virus particle load suspended in room air, and the resultant infection risk are closely dependent on the ventilation rate. During the colder months natural ventilation using tilted windows and the use of the Max Plank Institute for Chemistry Mechanical Extract Ventilation (MPIC-MEV) system (at a flow rate of 10 ℓ/s.(person) both provided a risk reduction of more than 50% relative to the base case scenario (which assumed no purposeful ventilation in the room). During the warmer months extended purge ventilation cycles had a greater effect than tilt ventilation, however only the MPIC-MEV system was able to reduce the (unmasked) transmission risk by over 50% year-round.

When the mechanical ventilation flow rates were increased from 10 to 20 ℓ/s.(person), in accordance with recommendations for classrooms in ASHRAE Standard 24-2023, a significant reduction in the infection risk was observed (with a 17% improvement in the MPIC-MEV system and a 20% improvement in the AHU-MVHR system). Accordingly, the lowest overall risk of one individual becoming infected after an 8 h exposure period was 30% in the case of the MPIC-MEV system, operating at 20 ℓ/s.(person), and the highest risk was 72% on a warm day using tilted windows.

Applying universal FFP2 masking in the base case scenario (in the absence of any purposeful ventilation over an 8 h period) reduced the risk of infection from 100% to 27%. These benefits are further amplified when ventilation was used in conjunction with masking. Notably using the MPIC-MEV system (at 20 ℓ/s.(person) in conjunction with FFP2 masking reduced the risk of any individual becoming infected (after an 8 h exposure period, in a room with one infectious individual) to 2%.

It should be noted that the infection model used here assumes complete mixing of the room air, and therefore the displacement effect was not incorporated in the infection risk model of the mechanical systems. The benefits of using hoods above the occupants to capture viral aerosols were incorporated in the model (for the MPIC-MEV system) using a conservative figure of 30% (based on secondary evidence). Further research is needed to quantify the additional benefits of using displacement ventilation and hood capture in combination, which are likely to be influenced by seasonal changes in the supply air temperature and a number of other factors.

In practical terms these findings highlight the benefit of using higher ventilation flow rates as well as the use of multiple prophylaxis measures, in combination, when community transmission rates are high. Since few existing ventilation systems will be capable of delivering the equivalent clean airflow rates in ASHRAE Standard 241-2023, ways of providing additional clean air capacity (e.g. via filtration units) without creating a significant energy burden and/or exacerbating thermal or acoustic discomfort need to be carefully considered.

References

ASHRAE. 2023. ‘ASHRAE Standard 241-2023, Control of Infectious Aerosols’. https://www.ashrae.org/technical-resources/bookstore/ashrae-standard-241-control-of-infectious-aerosols.

Bell, EnhaJessica A., and Jennifer B. Nuzzo. 2021. ‘Global Health Security Index: Advancing Collective Action and Accountability Amid Global Crisis, 2021’. www.GHSIndex.org.

Bhagat, Rajesh K., M. S. Davies Wykes, Stuart B. Dalziel, and P. F. Linden. 2020. ‘Effects of Ventilation on the Indoor Spread of COVID-19’. Journal of Fluid Mechanics 903 (November): F1. https://doi.org/10.1017/jfm.2020.720.

Bhagat, Rajesh K., and P. F. Linden. 2020. ‘Displacement Ventilation: A Viable Ventilation Strategy for Makeshift Hospitals and Public Buildings to Contain COVID-19 and Other Airborne Diseases’. Royal Society Open Science 7 (9). https://doi.org/10.1098/RSOS.200680.

Caulfield, John. 2013. ‘Are Building Codes Revised Too Often?’ Builder Magazine. 2013. https://www.builderonline.com/building/code/are-building-codes-revised-too-often_o.

CEN. 2019. EN 16798-1:2019. Energy Performance of Buildings. Ventilation for Buildings. Indoor Environmental Input Parameters for Design and Assessment of Energy Performance of Buildings Addressing Indoor Air Quality, Thermal Environment, Lighting and Acoustics. https://bit.ly/3eW89D8.

Checkatrade. 2022. ‘MVHR Cost Guide’. Checkatrade Website. 2022. https://www.checkatrade.com/blog/cost-guides/mvhr-cost/.

Clayson, Anne, Catherine Lewis, Janet, Ubido, Sarah Daniels, Damien McElvenny, Paniz Hosseini, Surakshya Dhakal, Mazhar Hussain, Martie van Tongeren, and Yiqun Chen. 2022. ‘A Systematic Review of Risk Factors for Workplace Outbreaks of COVID-19’. https://rb.gy/jq0uo.

Cui, Shuqing, Michaël Cohen, Pascal Stabat, and Dominique Marchio. 2015. ‘CO₂ Tracer Gas Concentration Decay Method for Measuring Air Change Rate’. Building and Environment 84 (January): 162–69. https://doi.org/10.1016/J.BUILDENV.2014.11.007.

Doremalen, Neeltje van, Trenton Bushmaker, Dylan H. Morris, Myndi G. Holbrook, Amandine Gamble, Brandi N. Williamson, Azaibi Tamin, et al. 2020. ‘Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1’. New England Journal of Medicine 382 (16): 1564–67. https://doi.org/10.1056/NEJMC2004973/SUPPL_FILE/NEJMC2004973_DISCLOSURES.PDF.

Eibinger, V, F Pollozhani, D Wright, R.S McLeod, and C.J Hopfe. 2022. ‘Testing User Perceptions of COVID-19 Ventilation Systems in Naturally Ventilated Spaces’. In BauSIM 2022. Weimar: IBPSA.

EQUA. 2023. ‘Validations & Certifications ’. EQUA Web Page. 2023. https://www.equa.se/en/ida-ice/validation-certifications.

GHS Index. 2021. ‘GHS Index Map’. Global Health Security Index. 2021. https://www.ghsindex.org/.

Helleis, Frank, Thomas Klimach, and Ulrich Pöschl. 2022. ‘Vergleich Verschiedener Lüftungsmethoden Gegen Die Aerosolübertragung von COVID-19 Und Für Erhöhte Luftqualität in Klassenräumen: Fensterlüften, Abluftventilatoren, Raumlufttechnik Und Luftreiniger’. Zenodo, February. https://doi.org/10.5281/ZENODO.6049289.

Helleis, F. et al. 2023. ‘Wirksamkeit, Energieeffizienz Und Nachhaltigkeit Verschiedener Lüftungsmethoden Hinsichtlich Luftqualität Und Infektionsschutz in Innenräumen: Fensterlüften, Abluftventilatoren, Raumlufttechnik Und Luftreiniger’, January. https://doi.org/10.5281/ZENODO.7586167.

ISO. 2005. ‘ISO 7730:2005 - Ergonomics of the Thermal Environment — Analytical Determination and Interpretation of Thermal Comfort Using Calculation of the PMV and PPD Indices and Local Thermal Comfort Criteria’. Edition 3. November 2005. https://www.iso.org/standard/39155.html.

Klimach, Thomas, Frank Helleis, Robert S. McLeod, Christina J. Hopfe, and Ulrich Pöschl. 2022. ‘The Max Planck Institute for Chemistry Mechanical Extract Ventilation (MPIC-MEV) System against Aerosol Transmission of COVID-19’, May. https://doi.org/10.5281/ZENODO.6545276.

Klimach, Thomas, Frank Helleis, Robert S Mcleod, Christina J Hopfe, and Ulrich Pöschl. 2021. ‘Technical Note: The Max Planck Institute for Chemistry Mechanical Extract Ventilation (MPIC-MEV) System against Aerosol Transmission of COVID-19’. Zenodo. www.tugraz.at/en/institutes/ibpsc/home/.

Lelieveld, Jos, Frank Helleis, Stephan Borrmann, Yafang Cheng, Frank Drewnick, Gerald Haug, Thomas Klimach, Jean Sciare, Hang Su, and Ulrich Pöschl. 2020a. ‘Model Calculations of Aerosol Transmission and Infection Risk of COVID-19 in Indoor Environments’. International Journal of Environmental Research and Public Health 17 (21): 1–18. https://doi.org/10.3390/IJERPH17218114.

Lessler, Justin, M. Kate Grabowski, Kyra H. Grantz, Elena Badillo-Goicoechea, Jessica C.E. Metcalf, Carly Lupton-Smith, Andrew S. Azman, and Elizabeth A. Stuart. 2021. ‘Household COVID-19 Risk and in-Person Schooling’. Science 372 (6546): 1092–97. https://doi.org/10.1126/SCIENCE.ABH2939/SUPPL_FILE/ABH2939_MDAR-REPRODUCIBILITYCHECKLIST.PDF.

McLeod, Robert, and Michael Swainson. 2017. ‘Chronic Overheating in Low Carbon Urban Developments in a Temperate Climate’. Renewable and Sustainable Energy Reviews 74. https://www.sciencedirect.com/science/article/pii/S1364032116305925.

Mourkos, Konstantinos, Robert S. McLeod, Christina J. Hopfe, Chris Goodier, and Michael Swainson. 2020. ‘Assessing the Application and Limitations of a Standardised Overheating Risk-Assessment Methodology in a Real-World Context’. Building and Environment 181 (August): 107070. https://doi.org/10.1016/J.BUILDENV.2020.107070.

MPIC. 2021. ‘COVID-19 Risikorechner Für Aerosolübertragung Aerosolübertragung von COVID-19 Und Ansteckungsgefahr in Innenbereichen’. Max-Planck-Institut Für Chemie Risk Calculator. 2021. https://www.mpic.de/4747361/risk-calculator.

Osman, Omar, Mervat Madi, Efstratios L. Ntantis, and Karim Y. Kabalan. 2023. ‘Displacement Ventilation to Avoid COVID-19 Transmission through Offices’. Computational Particle Mechanics 10 (3): 355–68. https://doi.org/10.1007/S40571-022-00492-8/FIGURES/29.

Oxfam. 2022. ‘Pandemic of Greed: A Wake-up Call for Vaccine Equity at a Grim Milestone’. www.oxfam.org.

Persily, A.K. 1997. ‘Evaluating Building IAQ and Ventilation with Indoor Carbon Dioxide.’ https://www.aivc.org/resource/evaluating-building-iaq-and-ventilation-indoor-carbon-dioxide.

Pollozhani, F, RS McLeod, T Klimach, U Pöschl, and CJ Hopfe. 2022. ‘Energy Performance and Infection Risk Evaluation of Retrofitted Ventilation Systems in Times of Covid’. In BauSIM 2022. Weimar: IBPSA.

UBA. 2021. ‘Richtig Lüften in Schulen ’. Umweltbundesamt. 22 October 2021. https://www.umweltbundesamt.de/richtig-lueften-in-schulen.

WHO Europe. 2021. ‘All Schools in Europe and Central Asia Should Remain Open and Be Made Safer from COVID-19, Say WHO and UNICEF’. World Health Organization. 30 August 2021. https://www.euro.who.int/en/media-centre/sections/press-releases/2021/all-schools-in-europe-and-central-asia-should-remain-open-and-be-made-safer-from-covid-19,-say-who-and-unicef.

Endnotes