key: cord-0977399-q3obqr8m authors: Guo, L.; Torii, R.; Epstein, R.; Rubin, J.; Reid, J. P.; Li, H.; Ducci, A.; Balachandran, R.; Tiwari, M. K.; Ventikos, Y.; Lovat, L. B. title: Using portable air purifiers to reduce airborne transmission of infectious respiratory viruses - a computational fluid dynamics study date: 2021-11-02 journal: nan DOI: 10.1101/2021.11.01.21265775 sha: 2394906d9b410d07779c22beb112ed22133a6a8e doc_id: 977399 cord_uid: q3obqr8m Aerosols and droplets generated from expiratory events play a critical role in the transmission of infectious respiratory viruses. Increasingly robust evidence has suggested the crucial role of fine aerosols in airborne transmission of respiratory diseases, which is now widely regarded as an important transmission path of COVID-19. In this report, we used CFD modelling to investigate the efficiency of using portable air purifiers containing HEPA filters to reduce airborne aerosols in hospitals and serve as a potential retrofit mitigation strategy. We used a consulting room to set up our simulations because currently the clearance time between consultations is the controlling factor that limits the patient turnover rate. The results suggest the inlet/suction of the air purifier unit should be lifted above the floor to achieve better clearance efficiency, with up to 40% improvement possible. If multiple air purifiers are used, the combined efficiency can increase to 62%. This work provides practical guidance on a mitigation strategy that can be easily implemented in an expedient, cost-effective and rapid manner, and paves the way for developing more science-informed strategies to mitigate the airborne transmission of respiratory infections in hospitals. Aerosol particles and droplets generated from expiratory events, such as breathing, talking, singing, coughing and sneezing [1, 2] , play a critical role in the transmission of infectious respiratory diseases, such as SARS (Severe Acute Respiratory Syndrome), MERS (Middle East Respiratory Syndrome) and (Coronavirus Disease 2019). To understand how far and fast droplets/aerosols can travel in indoor spaces is essential for developing effective mitigation strategies for infection control, especially in high-risk environments, such as hospitals. Normally, large droplets settle to surfaces over short distances (< 2 m); intermediate droplets deviate from the exhaled jet and evaporate to an equilibrium size; and small droplets travel with the exhaled air eventually also drying to a composition and size governed by the ambient conditions (relative humidity) [3] . Droplets in the last category, also defined as fine aerosols (aerodynamic diameter ≤ 5 μm), remain airborne for much longer and can spread much further than larger droplets [4, 5] . There is evidence that suggests fine aerosols play a crucial role in the airborne transmission of respiratory diseases [6] , and aerosol transmission is now widely regarded as an important transmission path of COVID-19 [2] . Ventilation, particle settling and air disinfection have been suggested as viable mitigation mechanisms [7] . Since aerosol dispersion strongly follows convective air flows [4] , mitigation measures involving ventilation are shown to provide more efficient solutions, such as higher air exchange rates [2, 8] and introducing flow-directing geometries [9] . is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 2, 2021. ; https://doi.org/10.1101/2021.11.01.21265775 doi: medRxiv preprint 3 However, substantial redesign of the entire Heating, Ventilation and Air Conditioning (HVAC) systems might be expensive, whereas portable air purifiers containing highefficiency particulate absorbing (HEPA) filters, which filter more than 99% of particles larger than 200 nm [10] , have the potential to provide a cost-effective, retrofit solution with several advantages, such as flexible positioning, easy maintenance and user-friendly control interfaces. Although there is evidence to support using portable air purifiers to disinfect polluted air [11] , there is little data to demonstrate the most effective usage. This raises a few key questions -Where should we put them in a room? For a given room and existing HVAC setting, do we need to use the maximal flow rates in the purifiers? Higher flow rates can filter more particles, but the stronger outflow jet may disturb the airflow and cause unwanted mixing, not to mention the increased noise level. Here we report a summary of our computational study on the performance of portable air purifiers based on Computational Fluid Dynamics (CFD) simulations. CFD has been extensively applied in studies of aerosol generating activities [12] and ventilation in hospitals [13] . We used the geometry and setup of a consulting room as a starting point to set up the simulations because currently the clearance time between consultations is the controlling factor that limits the patient turnover rate. In this report, we present our CFD modelling results of aerosol dispersion in hospitals and the reduction after introducing portable air purifiers, which offers characterisation of the performance and provides practical guidance to maximise efficiency. We created a model representing a typical consulting room in a UK hospital, with one doctor and one patient in sitting postures. The dimensions of the room are shown in Figure 1a (length: 5.6 m, width: 2.5 m, height: 2.7 m). We generated a computational mesh using non-uniform structured hexahedral elements, with local refinement at surfaces. A detailed mesh convergence study was conducted on four different mesh sizes, and the one used in this report has around 800,000 elements. We performed 3D is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 2, 2021. ; https://doi.org/10.1101/2021.11.01.21265775 doi: medRxiv preprint 4 in the simulations. The continuous medium was air at atmospheric conditions (density ρ = 1.16 kg/m 3 , reference pressure p = 101,325 Pa). The air flow and temperature field were simulated by solving 3D incompressible Navier-Stokes and heat transfer equations using the finite volume method with SIMPLEC pressure correction [14] . The standard k-ε model was used to account for the effects of turbulence [15] . Gravity and buoyancy forces were fully accounted for. A variety of schemes, of different degrees of spatial and temporal accuracy, were used to ascertain the sensitivity of these specific results to such numerical factors. The discrete phase of aerosols was tracked in a Lagrangian manner, with representative populations of around 200,000 particles being tracked. The sensitivity of the results and conclusions on the number of representative particles tracked was also confirmed. The particle drag force is a function of the local Reynolds number. The material of aerosols was assumed to be water at atmospheric conditions, and they were set to adhere to the wall upon contact. We used a fixed diameter of 1 μm (single size) to represent fine aerosols and evaporation was not considered based on the experimental evidence on aerosol particle diameter equilibration times [4] . In effect, we assumed the size distribution of such small aerosol was already equilibrated to the environmental conditions at the first step of the simulation and only heat but no mass transfer between the aerosols and the air flow occurred. The difference in temperature between the human models, and therefore the exhaled air and aerosols, and the ambient temperature created buoyant (initially rising) plumes that affected the particle distributions and were fully accounted for. We also used a stochastic model for turbulent dispersion of particles [16] . In the simulations, viscous drag, turbulent flow dispersion and buoyancy are the main forces that determine the trajectories of aerosols. Although the void fraction of particles is small, we chose to employ two-way (i.e. full) momentum coupling between particles and fluid, to enhance the accuracy of the results and to prepare for further developments regarding the physics included, like evaporation of droplets. Previous research suggested that normal breathing and talking are responsible for a portion of the virus-laden aerosols [17] . Therefore, we prescribed time-varying velocity boundary conditions at the mouth of the human models. More specifically, the patient was assumed to be breathing in a normal way (12 breaths per minute), ! = 2.8 × sin(1.26 ); and the doctor was assumed to be talking (15 breaths per . CC-BY 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 2, 2021. ; https://doi.org/10.1101/2021.11.01.21265775 doi: medRxiv preprint minute), " = 2.8 × sin(1.57 ), where t is time in seconds [18] . The door was closed (yellow area in Figure 1a ), but air was allowed to leak from small gaps around the door (blue strips in Figure 1a) , where a fixed (atmospheric) pressure boundary condition was applied. There was only one vent of the air conditioner on the ceiling, with a constant vertically downward velocity of 0.16 m/s, which is equivalent to an air change rate of 3/hour and is the normal working condition for clinical consulting rooms [13] . No-slip boundary conditions were applied at the walls, floor, ceiling and human models. Rectangular openings were cut around the mouth of human models to inject aerosols with the exhaled air at a constant rate depending on the local mesh. The room temperature was 23 °C and the human body temperature was set at 37 °C. Figure 1 shows the aerosol dispersion in the consulting room at t = 180 s; the baseline simulation is shown in the centre and different scenarios of using portable air purifiers are arranged in a circular manner. We cut off the simulations at 180 s because it can be seen from the plots in Figure 2 that the aerosol particle number reaches a plateau around that time, which therefore can be assumed to represent a steady state. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 2, 2021. ; https://doi.org/10.1101/2021.11.01.21265775 doi: medRxiv preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 2, 2021. ; https://doi.org/10.1101/2021.11.01.21265775 doi: medRxiv preprint 7 a local spherical region of diameter 1.6 m with its centre at the same vertical level as the mouth of the human models, to represent the region of room from which aerosols might be inhaled by the patient or doctor. Because the breathing velocities of human models were assumed to follow sinusoidal curves, we observe clear fluctuations in the local spherical region. The spatial distributions of the particles were also analysed at the end of the simulations (t = 180 s), where particle counts were binned in slabs of 0.1 m in the x, y and z directions, respectively. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 2, 2021. ; https://doi.org/10.1101/2021.11.01.21265775 doi: medRxiv preprint 8 magenta ones (from the patient sitting on the left) because the doctor was assumed to be talking so exhaled more aerosols, which was implemented as higher aerosol concentration from the mouth in the simulations. Then, we added portable air purifiers into the simulations. First, we simulated Air Purifier I (AP-I). Normally, this type of air purifier is placed on the floor; however, from the baseline simulation we can see more aerosols floating above the breathing level thus we compared different vertical positions -on the floor (Figure 1c) The results suggest that using multiple air purifiers can be more effective, but their relative positions are important. In this case, the large purifier works better on the floor together with the small one on the desk. This is because there is less mixing of the jets from different air purifiers to disturb each other's suction zone (Figure 1g, h) , which turned out to be the most effective mitigation solution simulated in this report. Compared with the baseline simulation, where only the air conditioning is working, using air purifiers is equivalent to increasing the air change rate. Depending on the . CC-BY 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 2, 2021. ; https://doi.org/10.1101/2021.11.01.21265775 doi: medRxiv preprint energy requirement of the central HVAC system, using portable air purifiers may be more energy-efficient. This short report summarises our CFD modelling work so far; however, more research still needs to be done, such as validation with experiments and generalisation to other settings. From the infection control perspective, statistical models can be introduced to model uncertainty and therefore predict the risk of exposure [19] ; and quantitative models to link aerosol concentration and probability of infection are also worth exploring [9] . We used CFD modelling to investigate the efficiency of using portable air purifiers to clear fine aerosols in hospitals. The results suggest that air purifiers can effectively reduce airborne aerosols. More specifically, the inlet of suction should be lifted above the floor to achieve higher reduction in steady-state aerosol concentration (40%); and using multiple air purifiers can further increase the efficiency up to 62%. This work provides practical guidance on a mitigation strategy that can be easily implemented, and paves the way for developing more science-informed strategies to mitigate the airborne transmission of respiratory infections in hospitals, especially for high-risk and aerosol-generating procedures, such as endoscopy, dentistry and speech therapy. This article has no additional data. Programme Manager at University College London Hospitals NHS Foundation Trust and Matthew Day, Regional Director at DSSR Limited for their support. Support from UCL Mechanical Engineering is also gratefully acknowledged. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 2, 2021. ; https://doi.org/10.1101/2021.11.01.21265775 doi: medRxiv preprint . CC-BY 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted November 2, 2021. ; https://doi.org/10.1101/2021.11.01.21265775 doi: medRxiv preprint Spatiotemporal droplet dispersion measurements demonstrate face masks reduce risks from singing: results from the COvid aNd FacEmaSkS Study (CONFESS). medRxiv 2021 A guideline to limit indoor airborne transmission of COVID-19 How far droplets can move in indoor environments -revisiting the Wells evaporation-falling curve Accurate representations of the microphysical processes occurring during the transport of exhaled aerosols and droplets Extended lifetime of respiratory droplets in a turbulent vapor puff and its implications on airborne disease transmission Airborne transmission of respiratory viruses Toward understanding the risk of secondary airborne infection: emission of respirable pathogens Modelling the transmission of airborne infections in enclosed spaces 2021 Mitigation strategies for airborne disease transmission in orchestras using computational fluid dynamics Should homes and workplaces purchase portable air filters to reduce the transmission of SARS-CoV-2 and other respiratory infections? A systematic review The effectiveness of an air cleaner in controlling droplet/aerosol particle dispersion emitted from a patient's mouth in the indoor environment of dental clinics On coughing and airborne droplet transmission to humans Spatial distribution of infection risk of SARS transmission in a hospital ward Enhancements of the simple method for predicting incompressible fluid flows The numerical computation of turbulent flows Aspects of computer simulation of liquid-fueled combustors Infectious virus in exhaled breath of symptomatic seasonal influenza cases from a college community Characterizing exhaled airflow from breathing and talking Modelling uncertainty in the relative risk of exposure to the SARS-CoV-2 virus by airborne aerosol transmission in well mixed indoor air LG and YV would like to acknowledge the financial and technical support provided LG: study conceptualisation, study design, data collection, data analysis, data interpretation, manuscript preparation, manuscript revision. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint We declare we have no competing interests. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprintThe copyright holder for this this version posted November 2, 2021. ; https://doi.org/10.1101/2021.11.01.21265775 doi: medRxiv preprint