The effect of air purifiers and curtains on aerosol dispersion and removal in multi‐patient hospital rooms

Abstract

Airborne transmission of disease is of concern in many indoor spaces. Here, aerosol dispersion and removal in an unoccupied 4‐bed hospital room were characterized using a transient aerosol tracer experiment for 38 experiments covering 4 configurations of air purifiers and 3 configurations of curtains. NaCl particle (mass mean aerodynamic diameter ~3 μm) concentrations were measured around the room following an aerosol release. Particle transport across the room was 1.5–4 min which overlaps with the characteristic times for significant viral deactivation and gravitational settling of larger particles. Concentrations were close to spatially uniform except very near the source. Curtains resulted in a modest increase in delay and decay times, less so when combined with purifiers. The aerosol decay rate was in most cases higher than expected from the clean air delivery rate, but the reduction in steady‐state concentrations resulting from air purifiers was less than suggested by the decay rates. Apparently, a substantial (and configuration‐dependent) fraction of the aerosol is removed immediately, and this effect is not captured by the decay rate. Overall, the combination of curtains and purifiers is likely to reduce disease transmission in multi‐patient hospital rooms.

Practical Implications.

Air purifiers will remove aerosol particles from rooms approximately at the rate expected from the clean air delivery rate. Horizontal exhausts from purifiers can substantially reduce the travel time of particles across the room, potentially bringing fresh infectious aerosols from one person to another and this situation should be avoided. Curtains around the beds should help isolate patients, but this effect is much less than expected, most likely because air currents from the room ventilation system provide substantial mixing.

1. INTRODUCTION

COVID‐19 has spread globally mainly via inhalation of virus‐containing particles produced via coughing, sneezing, vocalizations, and even normal breathing. ¹ , ² , ³ , ⁴ The particle size most critical to transmission is unclear. ⁵ , ⁶ Particles larger than 5 μm in diameter are commonly referred to as “respiratory droplets”; smaller particles are interchangeably referred to as aerosols, droplet nuclei, and airborne particles ⁷ ; these smaller particles appear to carry most of the airborne viruses. ⁸ Airborne particles >1 μm are easily filtered by almost any building air handling unit but will be distributed by the gentle air currents found in most indoor settings. Larger droplets (~30 μm) will settle to the ground in less than a minute, while a 10 μm particle will settle out of a room in about 10 min. ⁹ These factors suggest that aerosols are most important, but recent analysis of a restaurant outbreak suggests that larger droplets may result in transmission if there are strong air currents (>1 m/s). ¹⁰ Recent work ¹¹ shows that very rapid viral deactivation can be expected within the first minute of exhalation; then, much more gradual deactivation would occur on timescales of 5 min to an hour. Those authors attribute the rapid deactivation to the physical transformations from drying (increased at lower humidity) and change in pH as the exhaled plume entrains air with a low CO₂ concentration. This underlines the importance of the transport time from the source to the receptor and may affect the particle size that is most important to transmission.

Masks reduce airborne transmission, ¹² and both patients and workers in hospitals are expected to wear them. However, the pleated over‐the‐ear surgical masks often fit poorly and patients in a hospital may not always wear their masks correctly. Further, in public spaces such as bars and restaurants, mask wearing is counter to the purpose of the space. Thus, there is a need for a layer of protection on top of mask wearing. ⁵

There is much prior research on the use of portable air filtration systems in buildings. Experiments and modeling of aerosol transport and removal in a house ¹³ outline the basic behavior we study here for the semi‐partitioned space in a hospital room. A simplified mass balance model ¹⁴ was used to assess the use of air purifiers in the event of an external bioterrorism attack. A recent study motivated by COVID‐19 considered the particle removal efficiency of for different filter grades in dental clinics ¹⁵ but did not consider air movement within rooms. Another study focused on effectiveness of air purifiers in a single patient hospital room ¹⁶ but did not consider other interventions such as curtains. Experiments conducted in a 6‐bed hospital ward ¹⁷ showed that a single HEPA filter removed particles at a rate within 30% of the theoretical value, and that the exhaust, aimed to the room center, produced a global circulation that dominated the overall air flow pattern. The experiment was not set up to quantify particle transport from one bed to another. A few recent studies address the effectiveness of air purifiers in minimizing COVID‐19 transmission. Firstly, computer simulations were used to evaluate different configurations of purifiers added to a classroom. ¹⁸ , ¹⁹ Secondly, an experimental study of an occupied classroom determined the concentration decay rate produced by air purifiers and the degree of concentration uniformity in a large room without any ventilation. ²⁰ Similarly, another experimental study determined the effectiveness of air purifiers in an occupied conference room. ²¹

Plastic barriers have been ubiquitous in the workplace since the start of the pandemic. At the extreme end, sealed partitions can create separate rooms with their own filtration units, reducing the migration of aerosols from the patient space to the neighboring corridor by 98%. ²² Local extraction systems using a tightly sealed enclosure around the patient ²³ , ²⁴ , ²⁵ , ²⁶ , ²⁷ provide excellent patient isolation but would be a serious impediment to provision of health care. Plastic barriers of the kind meant to protect cashiers or office workers are less restrictive, but evidence for their effectiveness is quite conflicting. ²⁸

As summarized in Table 1, the key factors related to the effectiveness of air purifiers in mitigating COVID‐19 transmission have been considered in one or more studies, for particular real or idealized spaces, but there is a dearth of studies simultaneously considering the interaction of real‐world ventilation conditions with air purifiers, barriers, and within‐room aerosol transport. Also, the effect of transport time within the room, critical to droplet transmission and viral deactivation, has not been studied experimentally before.

TABLE 1.

Summary of literature on the effect of air purifiers on aerosol transport and removal

Study	Features of the study
	Modeling	Experimental	Within‐room variations	Filter config.	Barriers/curtains	Particle size	Transport time	Baseline ventilation
[18]	X		X	X		X		X
[14]	X			X		X		X
[32]	X				X	X		X
[19]	X	X	X			X	X
[20]		X				X
[22]		X			X	X
[23]		X			X
[16]		X		X				X
[13]	X	X		X		X		X
[33]		X		X	X			X
[17]		X	X			X		X
[21]		X	X		X			X
This work		X	X	X	X		X	X

2. METHODS

We conducted the experiment in a real hospital room because the objective was to inform a local health authority on the performance of air purifiers in patient care settings. However, given access restrictions during the pandemic, and the large number of uncontrolled factors in an occupied room, we conducted experiments in an unoccupied room. We used a novel transient tracer experiment that allows us to assess the transport delay time, effective decay rate, and spatial inhomogeneity of steady‐state concentrations. Our approach resembles the pulse tracer technique ²⁹ that has been used for gaseous tracers.

2.1. Test room layout

The test room (RM 213 of Delta Hospital, Figure 1) is intended for four patients and has an area of 398 sf (37 m²) including a 48 sf (4.5 m²) entry alcove. The door to the washroom was closed, and this small room is not included in the totals above. The room supply air is located on the alcove drop ceiling and directs air along the center‐line toward the exterior wall. The return air grill is located directly above the room entry door. Thus, the normal ventilation system creates a tumbling pattern of air moving toward the windows at ceiling height and returning along the floor to the entry door. Flow rates are likely variable, but measurements before the present test program suggest that it provides 3.5 ACH with 206 cfm (350 m³/h).

FIGURE 1.

Layout of test room. Air purifiers were either cylindrical upflow units in the corners or horizontal towers on the floor, exhausting to the room center or the walls. Particle sensors (RAMPS) were placed where a patient's head would be or where a healthcare worker would attend the sick patient. All windows and the main entry door to the room were closed during experiments

Each bed space was fitted with sliding curtains. These curtains had gaps of approximately 50 cm at the top and bottom. In addition, we retrofitted curtain extensions to the floor (“Long” curtain configuration). There is nothing to control wrinkling or the foot location of the curtains precisely as expected for real curtains—and this could contribute to experimental variability.

Because tests were conducted in a working hospital applying COVID‐19 protocols, the researchers conducting the tests stayed in the room during all tests, wearing masks and remaining in the SE or NW sections of the room. Undoubtedly, this had some small effect on air flows, but the level of activity was much less than the normal activity in an occupied hospital room.

2.2. Aerosol source and test sequence

A sodium chloride (NaCl) solution was dispersed using a Sonair MedPro ultrasonic nebulizer. The concentration of the solution was set to produce dried aerosol particles with a mass median diameter of approximately 3 μm as measured by at TSI Model 3330 OPS. For 3 μm particles, filtration efficiency would be nearly 100% for all purifiers tested. For this particle size, gravitational settling reduces concentrations at a rate equivalent to 0.5 ACH, on top of the true air exchange or cleaning rate. We expect the true particle losses to room surfaces to be about 30% higher than computed from sedimentation, based on previously reported experiments. ³⁰ The aerosol leaving the nebulizer was not neutralized, so static charges on room surfaces would have increased removal rates (slightly) for all experiments. The nebulizer was placed near the middle of one bed to simulate the cloud of particles produced by an infected patient. The nebulizer produced a jet of particles with a “throw” of 30–50 cm directed toward the foot of the bed, away from the sensor in that space. From a collocation experiment (Supporting Information A) in a sealed room with a fan but no filtration, the source strength is inferred to be 1970 ± 100 μg/min.

Experiments 1–27 were conducted using aerosol generation for 10 min 15 s set by the nebulizer. Experiments 28–41 used 25 min of aerosol generation to provide more accurate estimates of the steady‐state concentrations. After the generator was turned off, there was 15 min in the specified configuration to determine the decay rate, followed by 10 min of clearing with all purifiers on. By the end of this sequence, PM₁₀ concentrations were consistently reduced to less than 1 μg m⁻³ – about 1% of the peak values recorded during the experiment. This manuscript focuses on the configurations that were replicated at least once (and in most cases 3–4 times); data from all 41 experiments are contained in the Supporting Information sections B and C.

2.3. Particle measurements

We used the Remote Affordable Multi‐Pollutant Sensor (RAMP, SENSIT Technologies), which includes low‐cost sensor modules for measuring Particulate Matter (PM₁, PM_2.5, PM₁₀), NO, NO₂, CO, Ozone(O₃), and CO_2. ³¹ The RAMP uses laser scattering to measure PM. Data from the RAMP sensors are uploaded via cellular networks to an online server enabling remote monitoring. The RAMP records data every 15 seconds. A running three‐element median filter was applied to the raw data. The sensors are located as shown in Figure 1. Many factors control the accuracy of low‐cost optical particle sensors; we consider the major issues in the Supporting Information section A. From collocation experiments, examination of humidity and temperature variations, and from experiments in the hospital room with good mixing, it appears that calibration drift should be less than 3% over an experiment and sensors read consistently with each other to better than 10%.

2.4. Air purifier configurations

In addition to the baseline configuration without added air filtration, we tested configurations with 1, 2, or 4 purifiers in the room, in locations that would cause minimal disruption to the activities of patients and healthcare workers.

2.4.1. Single purifier by far wall

One experiment was conducted with a single large purifier (Atmosphere Sky true HEPA CADR 300 CFM). This was located on the center of the SW wall with exhaust directed upwards toward that wall. For completeness, the data from this experiment are included (and identified) in the summary plots to follow.

2.4.2. Corner upflow

In this configuration, a vertical exhaust purifier was placed in the room corner near the head of the bed. The intake was located 1.2 m above the floor. For the corner upflow configuration, we used the Blue Air 411 purifiers (except for experiments 3 and 4 which used 2 Honeywell‐brand towers on their sides, in addition to two Blue Air 411 units). The Blue Air 411 uses radial inflow through cylindrical filters with a nominal efficiency of 99% for PM_2.5. Our tests of the filter material suggest that the actual performance is approximately 99% filtration at 1 μm. These units use a vertical exhaust. Each is rated for 5 ACH in a 161 sf (15 m²) room, equivalent of 103 cfm (175 m³ h⁻¹). Thus, 4 of these units should clean 7.1 room volumes per hour.

2.4.3. Between‐beds horizontal flow

In this configuration, two horizontal axis towers were placed between pairs of beds. We used a Honeywell HFD 310C (Air Genius 4) for the west wall. It uses a true HEPA filter and is rated for a 250 square feet room with 161 cfm (274 m³ h⁻¹). A unit of this type would clean at a rate equivalent to 2.7 ACH. For the east wall (near the aerosol source in most tests), we used a Honeywell HFD 122qc. The filter has a nominal efficiency of 99% at 0.3 μm. The unit is rated for 170 sf (16 m²) with 109 cfm (185 m³ h⁻¹). There are two important variants of the between‐beds configuration: exhaust toward the foot of the beds or exhaust toward the head of the beds (or walls).

2.5. Data analysis

Evaluation of the air purifier and barrier configurations was based on concentration decay time, transport time from source to another patient and estimated steady‐state concentrations.

Approximately 5 min after the aerosol source is turned off, concentrations at all sensors decay at a similar rate. By fitting an exponential we obtained the first order decay time (t _decay), the inverse of the “effective air changes per hour” which is the ventilation rate for a well‐mixed room where the only particle removal mechanism is air exchange. This parameter controls the steady‐state concentrations for steady aerosol generation.

We were also concerned about the potential for air purifiers to create drafts that could rapidly transport large droplets from an infected person to other people in the room. As a surrogate for this risk, we extracted the time delay (t _trans) between the start of aerosol generation and the detection of particles at the 4 sensors away from the aerosol source (as a model for 3 other patients and a healthcare worker in the center of the room). This transport time is indicative of the time available for particles to settle to the ground before the air parcel reaches another person. Practically, in order to extract the delay time, a line was fit to the first few points at concentrations exceeding a threshold (typically 0.5 μg/m³); this line was extrapolated to find the time to cross the 1 μg/m³ level. This provided robust and consistent (if arbitrary) estimates of the delay time. Almost certainly this time is less than the average transport time from one location to another, but we expect it to be useful in comparing alternative interventions.

Although the experiments were transient, concentrations approached a plateau before the source was turned off, and assuming an exponential approach (accounting for the delay time), an estimate of the steady‐state concentration was obtained for each sensor. The uncertainty in these steady‐state concentration estimates includes the statistical uncertainty from the fitting process. For the shorter experiments, the 95% confidence intervals on the estimates are about 5%, except for the west sensor, where the confidence interval is often as large as the mean value. However, the total uncertainty in this fit is certainly larger as the true functional form might be more complex than assumed, and from inspection of the graphs, the uncertainty might be 50% for the short‐duration experiments. Later, we will present medians for 4 sensors, which would thus have uncertainties of (conservatively) 25%. However, in all of the longer experiments, the 95% confidence interval of the steady‐state estimates is always <2% and the fit appeared to be excellent.

Given the steady‐state concentrations (for a hypothetical continuous source) and the concentration decay rate, the source strength can be estimated for a well‐mixed room. The discrepancy between this source estimate and true source rate is an indication of the importance of the direct removal of aerosols by the exhaust or filter, before the aerosols are distributed through the room.

3. RESULTS AND DISCUSSION

A summary of all experiments is included in Table 2. The delay time is the average time delay [minutes] between the atomizer being turned on and the concentration reaching 1 microgram per cubic meter. The decay time [tau, minutes] is obtained by fitting an exponential to the latter portion of the experiment, over which all sensors show a consistent decay rate (this can be assessed in the plots in the next section). For the whole‐room metric, we have taken the median values rather than the average because in some experiments with long curtains, the north sensor exhibited a very long delay time as a result of never truly exhibiting the log‐linear decay. The steady‐state concentration (SSsource, μg/m³) is estimated assuming an exponential approach to the steady‐state value at the sensor closest to the source. In a few cases (Expt. 7,25), the concentrations did not exhibit a clear plateau (see Supporting information concentration plots) resulting in anomolously high SSsource estimates. SSaway is computed in the same way but for the 4 sensors in the other zones. The coefficient of variation reported here is the standard deviation of the SSaway values divided by the mean value—it is an indicator of spatial inhomogeneity.

TABLE 2.

Summary of all experiments

Expt	Purifiers	Curtains	Source Location	delay [min]	tau [min]	SSsource [mg/m3]	SSaway [mg/m3]	Coef_var	Description
1			East	2.8	14.4	387	156	0.28	Baseline
2			East	2.8	14.1	713	247	0.47	Baseline
3	2 corners		East	3.1	9	362	80	0.21	Two purifiers (Blueair 411 in opposite corners), no curtains
4	2 corners	Short	East	2.3	8.8	409	174	0.71	Two purifiers (as above) + short curtains
5	4 corners		East	2.1	4.1	457	80	0.2	4 corners, no curtains
6	4 corners	Short	East	2.9	4.2	157	62	0.94	4 purifiers (as above) + short curtains
7		Short	East	2.4	7.9	2939	145	1.11	Baseline, short curtains
8	4 corners	Short	East	1.3	4.2	229	86	0.38	4 corners short curtains
9	4 corners*	Short	East	1.5	4.1	189	85	0.32	4 corners short curtains, diffusers
10	4 corners*	Short	East	2.4	3.7	222	69	0.19	4 corners short curtains, diffusers
11	Btw beds–> center	Short	East	1.4	3.4	57	47	1.38	Btw beds–> center, short curtains
12	Btw beds–> wall	Short	East	2.5	4.6	256	104	0.72	Btw beds–> wall, short curtains
13	Btw beds–> wall	Short+	East	1.8	5.1	191	74	0.1	Btw beds–> wall, short curtains, exhaust fan on
14		Short+	East	2.2	8	110	100	1.29	Exhaust fan only, curtains
15	4 corners*	Short	East	2.5	3.5	332	59	0.48	4 corners short curtains, diffusers
16	Large purifier –>wall	Short	East	2.8	4.3	79	38	1.92	large purifier –> wall, short curtains
17		Short	West	3.5	NaN	235	111	0.94	Atomizer in West; baseline+ short curtains
18	4 corners*	Short	West	3.1	3.8	199	141	0.73	Atomizer in West; curtains, 4 Blueair with diffuser
19	Btw beds–> wall	Short	West	3.6	4.8	240	60	1.74	Atomizer in West; Btw beds–>wall, short curtains
20		Short	East	2.8	8.3	439	20	2.73	Baseline + curtains (exhaust fan sealed hereafter)
21	4 corners*	Short	East	2.6	3.7	113	24	0.47	4 corners (diffusers, short curtains)
22	Btw beds–> center	Short	East	1.1	3	22	46	0.36	Btw beds–>center, short curtains
23	Btw beds–> wall	Short	East	3.1	2.8	62	33	0.99	Btw beds–>wall, short curtains
24	4 corners*	Long	East	2.9	3.3	276	28	1.69	4 corners (diffusers, long curtains)
25	4 corners	Long	East	1.5	3.9	51 371	75	0.41	4 corners long curtains
26	Btw beds–> wall	Long	East	3.1	3	26	15	1.03	Btw beds–>wall, long curtains
27		Long	East	3	8.2	207	66	1.76	Baseline with long curtains
28			East	2.6	13.7	694	97	0.25	Baseline with no curtains. Long experiments hearafter
29	4 corners		East	2.4	5.2	755	50	0.14	4 corners, with no curtains
30	Btw beds–> center		East	2.4	5.6	70	59	0.05	2 HW to center with no curtains
31		Long	East	3.4	8.9	432	76	0.11	Baseline with long curtains
32	4 corners	Long	East	3.2	4.1	578	49	0.21	4 Blueair with long curtains
33	Btw beds–> center	Long	East	3	4.9	209	57	0.32	Btw beds–> center with long curtains
34		Long	East	5.2	17.2	436	87	0.53	Baseline; long curtains
35	4 corners	Long	East	3.3	4.9	325	53	0.19	4 corners; long curtains
36	Btw beds–> center	Long	East	2.8	5.7	186	61	0.26	Btw beds–> center; long curtains
37			East	2	12.6	108	85	0.51	Baseline
38	4 corners		East	2.25	5.39	280	61	0.13	4 corners; no curtains
39	Btw beds–> center		East	1.75	6.66	104	72	0.1	Btw beds–>center; no curtains
40			East	2.29	12.03	633	80	0.25	Baseline
41	4 corners	Short	East	2.8	4.83	511	57	0.09	4 corners; short curtains

The description includes some minor configuration variations that have been grouped into major categories reported in the main manuscript. For example, there was a small window‐mounted exhaust fan operated in Experiment 13, off but unsealed in experiments 1–12, 14–19, and sealed from experiments 20–41. There is no detectable impact from this on any of configurations repeated through the 5 days.

In total, 41 experiments were conducted over 5 days and the complete results are included in the Supporting Information. The nebulizer was placed in the West corner for three experiments; given the inherent variability of the experiments (discussed at length below) and the lack of replicates for these three experiments, they are not discussed further.

We consider next the concentration time series of experimental runs with different purifier and curtain configurations. After this, results from the complete experimental set summarized graphically.

3.1. Evolution of concentrations in typical experimental runs

Figure 2 shows the progress of a baseline experiment and one with upflow corner purifiers with long curtains. Although the atomizer is directed away from the nearest sensor (East bed), circulation in the room brings the particles back to that sensor in approximately 2 minutes. As expected, the concentrations at the 4 sensors away from the atomizer are much lower and show a delayed response indicating a finite travel time (2–4 min). Generally, the concentrations at the East sensor, nearest the source, show the largest fluctuations, about a factor of 3. This is consistent with a concentrated aerosol plume wafted intermittently toward the sensor. Already at 2.5 m away, the sensors are reading roughly room‐averaged concentrations, to within a factor of 2–3. This is entirely consistent with detailed simulations of similar rooms ¹⁹ and experimental studies. ²⁰ , ³⁰

FIGURE 2.

Representative experiments for baseline (Expt. 40, no purifiers or curtains) and corner purifiers with long curtains (Expt. 35). Dashed lines indicate the fitted curves used to estimate steady‐state concentrations. Aerosol injection started at t = 0

After the nebulizer switches off, an exponential fit to the concentrations provides an estimate of the decay rate or effective air changes per hour; a fine dashed vertical line shows the start of that fitted decay curve (about 27 min for the longer experiments). Dashed curves indicate the exponential fit used to estimate the steady‐state concentrations at each sensor for the period that the atomizer is on.

Distinctly different concentration patterns are produced by air purifiers placed between beds with horizontal exhausts. When directed toward the room center (Figure 3), the exhausts produce a high degree of mixing, especially when there are no curtains. Long curtains result less uniform concentrations. When the purifier is turned 180 degrees (Supporting Information Figures C12, C13, C23, C26), concentrations are markedly less uniform, especially with long curtains.

FIGURE 3.

Representative experiments using 2 purifiers between beds, exhausting toward the room center. Left panel is without curtains (Expt. 39) and right is with long curtains (Expt. 36)

3.2. Effect of purifiers and curtains on whole‐room metrics

Figure 4 compiles some key metrics for all experiments with the source on the East corner bed. The decay times are the medians for all sensors, while the delay times are the averages for the 4 sensors away from the source bed area (i.e., South, West, North, and Center sensors). The steady‐state concentrations plotted in the figure are the medians for the 4 sensors away from the source. As expected, the concentration decays faster with purifiers (3–7 min decay time) than without (8–18 min). From the nominal air supply flow and an estimate of particle losses (settling and additional 30% for non‐vertical surfaces and turbulence, see Section 2.2), the baseline case should have a decay rate equivalent to 4.15 air changes per hour (ACH), which is equivalent to 14.5 min decay time. However, the average of the no‐purifier data is 11.5 min (5.2 ACH), shown as a vertical dashed black line in the figure. For the cases with the purifiers, we expect the effective ACH to be increased by the clean air delivery rate (CADR), and thus, the decay time can be estimated for each configuration. These estimates are shown as vertical dashed lines with the appropriate color. Concentrations decay faster in nearly all cases than this estimated time. Several factors may contribute to this bias. Dead spaces (under beds, in entry vestibule, in furniture) make the effective room volume smaller than used in the decay time estimate. Also, aerosol losses to surfaces could be larger than assumed. Decay time is more consistent when purifiers are used, particularly for the 4 corners and between‐bed‐to‐wall configuration. We speculate that for the between‐beds‐to‐center configuration, results may be sensitive the precise alignment of the exhaust jet with respect to curtains (which are pinned back about 2 feed to avoid interference with the exhaust jet).

FIGURE 4.

Delay time (top) and estimated steady‐state concentrations (bottom) as a function of the particle concentration decay time. Vertical dashed lines indicated the estimated decay time for each purifier configuration. The “perfect mixing” line uses the measured decay times and aerosol generation rate to predict the steady‐state concentration

Our results are broadly consistent with the literature. Curtius et al find that the incremental effect of air purifiers is consistently 80% of that expected from the CADR. In those experiments, the two measurement locations were in corners of the room, far from the purifiers, where ventilation might indeed have been lower. Meanwhile, Lindsley et al ²¹ find that effect of air purifiers varies with the location of air purifiers in the room; it is lower or higher than that expected from the CADR.

The delay time (top panel of Figure 4) is relevant to disease transmission because it would affect viral deactivation and the settling of large droplets (were we to consider a source with broader size range). Long curtains (large symbols) tend to result in larger delay times but here too there is large variability. Note that the RAMPs record 15‐s averages (which are then smoothed using a 3‐element median filter), and further that there could be errors of up to 10 s in the startup of the atomizer: Practically, the resolution of delay time will be about 1/2 min. Typically, the delays were under 3 min, implying air velocities fast enough to carry droplets of 20 microns across the room. The range of delay times is potentially significant: for SARS‐CoV‐2; it could change the viable virus concentration by more than a factor of 2. ¹¹

Steady‐state concentration estimates (lower panel of Figure 4) are lower for the configurations with purifiers but there is again large variability between experiments. If the particles in the room were well mixed, we would expect the steady‐state concentrations C to depend only on the decay time τ, particle generation rate S and room volume V as C = Sτ∕V as shown as the “perfect mixing” line in Figure 4. All configurations produce lower concentrations than expected from perfect mixing. This implies that the apparent aerosol source rate is lower than the true source rate. Furthermore, the discrepancy is greater for the baseline cases with no purifiers and yet the same atomizer and salt concentration is used in all cases. The most likely explanation is that a portion of the aerosol is carried directly to either the room exhaust or one of the purifiers. By chance, this portion is larger for the baseline configuration and smallest for the 4 corner purifiers. This is consistent with the observed circulation created by the room air supply ejecting air southwest along the ceiling and returning northeast near the floor—this puts the aerosol source just upstream of the return grill. This pattern cannot be generalized to all rooms or even all source locations within the test room, but generally, there would be special locations with more local source capture.

3.3. Spatial variability

Although the well‐mixed model is often used to interpret indoor air concentrations of pollutants, we see some important deviations from this idealization. As noted above, near the source, concentrations are highly non‐uniform and this will influence the fluctuations experienced by the nearest sensor and also the extent to which nearby filters might capture particles immediately. Beyond this, the time series shown in Figures 2 and 3 suggest that people in zones away from the source might experience different levels of risk.

In Figure 5, the steady‐state concentrations for individual sensors away from the source are illustrated independent of delay time and decay time. There are few clear trends on the effect of curtains on aerosol dispersion. While it may be the case that, in the no‐purifier scenario, curtains reduce steady‐state concentrations in the Center or North space, they may do the opposite in the South. With purifiers, there is less of a spread between experiments and less of an indication that the configuration of curtains has a strong role in reducing concentrations.

FIGURE 5.

Spread of steady‐state concentrations for the 4 sensors away from the aerosol source zone. The number of experiments per configuration is indicated as “N”

Figure 6 shows the steady‐state concentrations and delay times for individual sensors away from the source. The averages for all sensors and experiments are superimposed on the plots as a reference (dashed lines). The risk of infection from a sick patient would be increased with short delay times and higher concentration, that is the upper left quadrant of each plot. In a configuration without purifiers, it is apparent that the patient in the south bed or a worker in the center zone would be at the highest risk; the patients in the west and north beds would have the lowest risk. The configurations with curtains tend to have lower risk but the effect of curtains is less pronounced and less spatially uniform than the effect of purifiers. Regardless of the configuration of curtains, or even the configuration/location of the purifiers, the use of purifiers appears to mitigate risks of exposure within all spaces of the room adjacent to the source.

FIGURE 6.

Steady‐state concentrations and delay times for the 4 sensors away from the aerosol source zone. Dashed lines indicate the averages for the full dataset; these lines divide the plot into quadrants. The lower right quadrant (long delay and low concentration) is expected to indicate lower than average risk of infection

3.4. Study limitations

Several aspects of this study warrant discussion vis‐a‐vis limitations and repeatability of results.

The number of experiments undertaken combined with the number of experimented scenarios prohibits this study from inferring results in a statistical format. Figure 5 visualized the spread of steady‐state concentrations observed across all experiments, but one should not infer from these data the means and variances of results. While there was an observable pattern of results between experiments with no purifiers (i.e., high variation in steady‐state concentrations) versus with purifiers (i.e., low variation and low value for steady‐state concentrations), evidence for or against the use of curtains was inconclusive. The same applied for reported findings regarding delay time and decay time. A larger number of repeat experiments are still required.

It is likewise understood that experiments were undertaken in a real‐world hospital room, with an interior design and HVAC system unique to the specific hospital tested. It is understood by the authors that the room was designed to widely used standards (i.e., ASHRAE), and the room's HVAC concept was configured to produce “fully mixed” indoor air conditions, where the supply air diffuser emits a high volume of air that should spread and mix fully in the room before returning through the exhaust grille. One must still surmise, though, that even if the system was designed to a known standard, the airflow patterns in the tested room were possibly unique to the room itself and not identical to any other room elsewhere. The sensitivity of room air flows to furniture placement, nuances of how the room itself was outfitted with HVAC equipment, possible unique HVAC control settings, and variable large‐scale air motions all make it challenging to use this study's findings to optimize the spatial location of both purifiers and curtains in general settings. Computational fluid dynamics (CFD) could have an important role in designing these interventions in the future. A future CFD study should consider variations in boundary conditions representative of real rooms and be experimentally validated under realistic conditions.

Last, it is acknowledged that in analyses of indoor aerosol dispersion, particularly in cases where the relationship between dispersion and building materials is concerned, the static charge of airborne particles and the surfaces they near are important physical characteristics. For example, if the curtains tested in this study's experiments were pre‐charged, they may have had an impact on attracting or repelling aerosols. The question is then whether the nebulized aerosols emitted in our experiments were neutral, charged, and/or whether they emulated the state of charge of aerosols emitted by a sick patient. Further work is needed.

4. CONCLUSIONS AND OUTLOOK

Transient injections of sodium chloride aerosols were used to assess the ventilation patterns of a 4‐bed hospital room using various configurations of air purifiers and curtains around beds. These experiments allowed us to estimate the aerosol concentration decay rate resulting from the purifiers, the transport delay time across the room, steady‐state concentrations, and the portion of aerosol that is immediately removed from the room. We believe that transient release experiments can provide metrics critical to assessing the effectiveness of infection control measures, but can recommend some improvements in future applications of the method. Delay times will often be on the order of several minutes, so it would be useful to have sensor time response of only a few seconds. On the contrary, concentrations will approach steady‐state within 2 or 3 air change times, so experiments should run over 4–6 air change times in order to recover all the features relevant to particle distribution and removal.

Across 38 experiments, we found that the addition of stand‐alone air purifiers increased the concentration decay rate by at least as much as expected from the purifier clean air delivery rate (CADR). On the contrary, the change in steady‐state concentrations was generally smaller than one would expect based on CADR. This apparent paradox is resolved by noting that a large portion of the aerosol source is immediately removed from the air and not subject to the well‐mixed removal behavior characterized by the concentration decay portion of the experiment. Furthermore, this immediately removed portion of the aerosol is altered by the air purifier configuration and shows that there is scope for optimizing the location of purifiers for particular rooms and source‐receptor positioning.

The particle transport time from one bed to another was only a few minutes, which would provide ample time for 15–30 μm droplets to disperse widely within the room before settling out. Also, given the low velocities in the room (<<1 m∕s) and large dimensions of the obstacles, inertial impaction of particles is expected to be negligible. Our observations here imply that the plastic barriers used in bars, restaurants, and stores will be ineffective for the smaller droplets and aerosols believed to be largely responsible for transmission of COVID‐19. Indeed, curtains that surround the beds and extend from the floor to within 50 cm of the ceiling reduce concentrations by less than a factor of 2 and more commonly less than 20%. The surprisingly small effect of the barriers might be because the purifiers introduced air circulations larger than the zone around each bed, and this provided relatively efficient transport past the curtains. Nevertheless, the delay times measured here are large enough to affect the degree of viral deactivation that occurs due to the physical and chemical changes that occur on drying.

The effect of partial barriers on COVID‐19 transmission has been reviewed recently. ²⁸ Several CFD studies showed potentially very large impacts at close range, while the epidemiological evidence was very mixed. For example, CFD modeling ³² predicted that small barriers would reduce concentrations by over 90% for the student nearest the “source” student in a conventional classroom. In light of our experiments, this appears possible for a perfectly aimed source under steady conditions. However, this would not be representative of ensemble average conditions for real rooms, in which variations in large‐scale air motions would tend to move the concentrated aerosol plumes around the room. This would reduce (on average) the very highest concentrations, even without barriers, and it would make it all but impossible to place small barriers in a useful location.

In summary, air purifiers should substantially reduce airborne disease transmission in hospital rooms, and the use of air purifiers with curtains might further reduce transmission, if only slightly.

AUTHOR CONTRIBUTIONS

Steven Rogak original conception of study, data analysis, and writing. Adam Rysanek review and revision of manuscript, and data analysis. Jim Myungjik Lee and Surya Venkatesh Dhulipala conducting experiments and preliminary data analysis. Naomi Zimmerman supervision of proper use of RAMPS and manuscript review. Martin Wright provided access and setup of experimental facilities. Mitch Weimer access and setup of experimental facilities, and involved in original conception of study design.

FUNDING INFORMATION

Funding was provided by the Mitacs Accelerate internship program and Fraser Health Authority.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

Supporting information

Appendix S1

Rogak SN, Rysanek A, Lee JM, et al. The effect of air purifiers and curtains on aerosol dispersion and removal in multi‐patient hospital rooms. Indoor Air. 2022;32:e13110. doi: 10.1111/ina.13110

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are openly available in Borealis (dataverse) at https://doi.org/10.5683/SP3/Y5NKNT.