Air cleaners

What air cleaner test reports don’t tell you

99.8% pathogen reduction after 60 minutes! FDA approved! Reactive compounds destroy SARS-CoV-2!

The market for air cleaners is booming and you’ve undoubtedly seen these types of claims. I’ve spoken to countless business owners, building managers, engineers, teachers, and concerned citizens over the last several months who have had questions about the effectiveness and safety of a wide variety of air cleaning technologies that are being heavily marketed to combat COVID-19 transmission in indoor environments. The marketing claims are often bold, and sound quite promising:

  • ABC technology uses reactive molecules [or super oxides or positive and negative ions] to destroy SARS-CoV-2 on surfaces and in air!
  • XYZ technology has just been granted emergency FDA approval!
  • DEF technology reduces viable SARS-CoV-2 [or surrogate organism] by 99.99% in 60 minutes!

These claims are frequently made based on results from test reports from third-party test labs such as EMSL, MRI Global, Innovative Bioanalysis, Analytical Lab Group, and Aerosol Research and Engineering Laboratories, to name a few. As far as I can tell, these are generally manufacturer- or distributor-funded lab tests intended to demonstrate the effectiveness of an air cleaning device for removing particles, killing microorganisms, or whatever the device is purported to do.

However, there are consistent problems with many of these test reports. Others have recently pointed out of some these issues. Here I will demonstrate just a few of these common issues using specific examples, primarily from one particular company, but only because they were in the news recently. They are far from alone, and quite typical of how efficacy is reported. 

I recently noticed in test reports made available by a company named Aerus, which utilizes a patented technology they call ActivePure® in a number of products including their Medical Guardian Air device, their smaller Pure & Clean unit, and their subsidiary Vollara’s Air and Surface Pro device. You may have heard of this company, especially recently, as Deborah Birx, the former White House Coronavirus Coordinator in the Trump administration, just joined the company as chief medical and science advisor. The press release I read suggests that “Dr. Birx encourages every indoor environment to have ActivePure Technology.” Let’s look deeper into how this technology performs using test reports provided by the manufacturer.

There are surprisingly few details on the mechanisms involved in their ActivePure® technology on the Aerus website, but a few Youtube videos, as well as their published patent, provide some insights into what the technology is: a combination of UV-PCO (ultraviolet photocatalytic oxidation), often combined with ionization, and sometimes both combined with more conventional HEPA (high efficiency particulate air) filters. Key words used to describe the technology include “oxidizers”, “super oxides”, “active PCO”, “disinfecting molecules”, and more. In other words, it is a form of “additive” air cleaning technology that aims to “seek out and destroy pathogens,” among other claims. Here I focus primarily on inactivation of microorganisms on surfaces or in air (or both), as that’s clearly a high priority for consumer interests and marketing efforts right now.

 

Marketing materials love to show big impacts

You can read some of their marketing materials that summarize test reports conducted by third-party labs directly on their website. Here is a common approach to marketing these results from one of their air cleaners, the Medical Guardian device, in which they show a percentage reduction in the viability of MS2, a bacteriophage commonly used as a surrogate for for influenza virus and other respiratory viruses (it’s much safer and easier to use surrogates than the real deal). 

The graphic reports 99.9999% reduction in MS2 bacteriophage RNA virus after 60 minutes (also note that this approach is in no way unique to this particular company and its technology).

Sounds great, right? Well, let’s look deeper into the report to learn more. You can download a compilation of their third party lab test reports directly from Aerus (and I have also hosted them here in case the link ever disappears). 

 

The first example test report: pathogen surrogates, large chamber, but unconventional reporting

The first report in this packet documents a series of tests conducted by Aerosol Research and Engineering Labs. They tested the viability of several surrogate pathogens in air, with reasonably well documented and detailed methods (which isn’t always the case for some of these third party reports). They show a picture of the unit and mention that it is an ion generator and PCO in Figure 1. They mention the volume of the chamber – 562 cubic feet – and even show a diagram. This is a rather large chamber compared to a lot of other test reports, as we will see later.

They compared results with the air cleaning device operating to a control, which is again another basic competency that I’m glad to see but that is not always done in other lab reports. The unit they tested (Medical Guardian) includes the ActivePure® technology and also a HEPA particle filter. Its data sheet suggests airflow rates of 90 to 300 cfm are achievable depending on fan speed setting. It is not immediately clear what fan speed setting the unit was set to when it was tested.

They aerosolized a number of surrogate organisms to mimic various bacteria, viruses, and molds (fungi), one at a time. And they report “log-reduction” values in both figure and table form, including for both intervention tests (run in triplicate) and a control test without the air cleaning technology operating. Every “log reduction” is a factor of 10^(log reduction) lower than the original starting point (i.e., a log reduction of -3 is 10^3 or 1000 times lower than the original starting point, or 0.001 of the original concentration). In a separate test, they also injected polystyrene latex (PSL) beads as a measure of non-biological particle removal. Let’s look at some of these test results.

First, in Figure 4 of the test report, they show “Log reduction” values over a period of 20-60 minutes for 1 µm particles during the PSL bead injection and decay test, including for both air cleaner on and off periods (i.e., intervention vs. control):

These “Log reduction” values appropriately start at 0, as at time = 0 hours (i.e., the beginning of the test), the initial concentration is at its highest, and therefore this is no reduction at that moment. At a “Log reduction” value of -1, that is the time at which under a given condition the concentration of 1 µm particles have decreased by 1-log, i.e., 90%. Subsequently,  2-log means concentration reductions of another 10x, or 99% from the total. 3-log means 99.9% lower, 4-log means 99.99% lower, 5-log means 99.999% lower, and so on. It is a convenient way to show rapidly decreasing concentrations, and clearly these particles decrease much faster with the air cleaner operating than the control condition without the air cleaner operating, as one would hope to see.

However, “Log reduction” is a fairly unconventional way to show these types of data. The main issue is that it doesn’t allow for easy comparison to other standalone air cleaning devices because no conventional test methodology reports log reductions at a specific time. Instead, a more conventional and useful approach is to use loss rates between air cleaner on and off conditions to calculate the unit’s CADR (clean air delivery rate). This is a well known metric, widely used in the industry (e.g., by AHAM, the Association of Home Appliance Manufacturers), research communities, consumer groups, and recommended by the U.S. Environmental Protection Agency (EPA). 

Fortunately, we can estimate a CADR based on the loss rates shown here. We have to transform the “log reduction” values into “natural log reduction” values to be useful and to confirm to a first-order exponential decay model for a well-mixed chamber environment (read more about that approach here). So what I’ve done is transform the “log reduction” values at each time stamp into linear values (where C/C0 = 1/(10^(log reduction))) and then into the natural logarithm of the concentration at each time step compared to the initial time step (i.e, ln(C/C0)). I first translated “log reduction” values visually into a spreadsheet (so it’s an imperfect, but close, translation), then completed the other two transformations. These are simple calculations to get the results on terms that are more commonly used and from which I can estimate first-order loss constants. Here is a table of those values, followed by a figure showing the ln(C/C0) values over time from both test conditions.

1 µm PSL Control Test
Time (hr) LogReduction C/Co ln(C/C0) LogReduction C/Co ln(C/C0)
0 0 1 0 0 1 0
0.1 0.05 0.89125094 -0.1151293 1 0.1 -2.3025851
0.2 0.12 0.75857758 -0.2763102 2 0.01 -4.6051702
0.3 0.2 0.63095734 -0.460517 3 0.001 -6.9077553

We can fit a straight line through the ln(C/C0) versus time data in the figure above to estimate first order loss rate constants under each condition. My approximations of loss rate constants result in ~1.5 per hour during the control condition (i.e., no air cleaner operating) and ~23 per hour with the air cleaner operating. This “background” loss rate is just due to deposition of particles to chamber surfaces and any ventilation provided to the chamber. A difference of ~21.5 per hour is significant – a good sign that the air cleaner is doing something!

The last step is to multiply this difference in loss rates by the volume of the chamber, then divide by 60 to convert from hours to minutes, and estimate the CADR. Doing that results in an estimated CADR of about 200 CFM (cubic feet per minute) for these sized non-biological particles:

Loss rate summary
  Loss, 1/h
Control 1.46
Test 23
Delta 21.54
Delta, 1/min 0.359
Chamber Vol, ft3 562
CADR, cfm 201.8

That’s not too bad! A typical standalone or portable air cleaner with a HEPA filter would be expected to deliver a CADR of 200 CFM or more (and often quite a bit more). What’s interesting with this finding is that this particular air cleaner device is able to deliver ~200 CFM of clean air in terms of non-biological 1 µm particles, which, since this device includes a combination of ActivePure® technology PLUS a HEPA filter, gives us a sense of what the “baseline” level of performance might be for this device. It’s impossible to know whether or not the bulk of the removal is happening because of the HEPA filter or because of the UV-PCO and/or ionization components, but we do know that UV-PCO doesn’t actually target particle removal, so we can generally rule that out, and my hunch is that the HEPA filter is doing most of the heavy lifting here. Some ionization technologies/products have shown to be effective at removing particles in some studies, but not in others, including a recent study of our own. Regardless, this gives us a good anchor point that characterizes the basic performance of this device.

Next, we can move into reviewing the biological test results to see if the additional oxide generation or other active/additive technologies are doing more to reduce the concentration of viable biological particles, whether through removal by HEPA or by inactivation by active technologies or both, than the baseline rate of non-biological particle removal.

Table 3 of the report summarizes “net log reduction” results, which are the same types of values as “log reduction” presented above, albeit with the background loss rates from the control (i.e., air cleaner off) test subtracted out such that they are just the additional loss rates added by the use of the air cleaner. The units and magnitudes are otherwise similar (i.e., -5.6 log reduction means 10^-5.6 = 1/2.5^10-6 of the original value, or 99.9977% lower than the original value). The two viral surrogate tests (MS2 and Phi X174) are flagged for having concentrations after 60 minutes of testing that were low enough to be at or near the detection limits of the measurement methods they were using, so I’m not going to use those values. This means the loss rates are underestimated because the true value could have been lower and the methodological approach just couldn’t measure that low. It is worth noting that after 60 minutes for both of these tests, the net log reduction was around 4-log for one and 5.6 log for another. Let’s pick an even better performer to be generous: their Staphylococcus epidermidis results, which is used as a surrogate for methicillin resistant Staphylococcus aureus (MRSA) and achieved an average net log reduction of almost 6-log after 60 minutes of testing. The figure below shows their reported results using the “log reduction” approach (not the “net log reduction” approach), which shows results for both the control period (i.e., air cleaner off) and the air cleaner on period.

Similar to the non-biological removal tests, the table below transforms the “log reduction” values at each time stamp into linear values (where C/C0 = 1/(10^(log reduction))) and then into the natural logarithm of the concentration at each time step compared to the initial time step (i.e, ln(C/C0)). Below is a table of those values, followed by a figure showing the ln(C/C0) values over time from both test conditions.

MRSA surrogate Control Test
Time (mins) Time (hr) LogReduction C/Co ln(C/C0) LogReduction C/Co ln(C/C0)
0 0 0 1 0 0 1 0
15 0.25 0.35 0.44668359 -0.8059048 2.05333333 0.00884437 -4.7279747
30 0.5 0.44 0.36307805 -1.0131374 4.54 2.884E-05 -10.453736
45 0.75 0.5 0.31622777 -1.1512925 5.83333333 1.4678E-06 -13.431746
60 1 0.44 0.36307805 -1.0131374 6.39333333 4.0427E-07 -14.721194

Again, we fit a straight line through the ln(C/C0) versus time data in the figure above to estimate first order loss rate constants under each condition. My approximations of loss rate constants for these biological tests result in ~1.4 per hour during the control condition (i.e., no air cleaner operating) and ~16.6 per hour with the air cleaner operating. A difference of ~15.3 per hour isn’t bad, but is actually a bit lower than the ~21.5 per hour from the non-biological particle tests. Again multiplying this difference in loss rates by the volume of the chamber, then dividing by 60 to convert from hours to minutes, the effective CADR for this surrogate organism test is about 130 CFM:

Loss rate summary
  1/h
Control 1.68
Test 15.27
Delta 13.59
Delta, 1/min 0.2265
Chamber Vol, ft3 562
CADR, cfm 127.3

In other words, the operation of this air cleaner with its combination of fan, HEPA filter, and patented UV-PCO and ionizer combination and whatever else is included in this particular device, yields an effective CADR for biological inactivation or removal of about 130 CFM, which is actually lower than the non-biological test results. So while 99.9999% reduction in airborne MRSA surrogate after an hour sounds super impressive in the marketing materials below, it’s actually not that great. It’s not zero, so that’s good! But 130 CFM of air free of MRSA surrogate is not that impressive and is easily achievable by conventional technologies. Moreover, since this unit actually has a HEPA filter in the device, it’s quite plausible that the HEPA filter is doing most of the heavy lifting here to inactivate or remove surrogate organisms. In addition to that, none of these tests mention anything about the chemical compounds that are emitted by the device via the UV-PCO + ionization process or their impacts on indoor chemistry and potential for chemical byproduct formation. This is something we recently studied using a popular bipolar ionization device, and we found that while the technology as tested appeared to remove some volatile organic compounds (VOCs), it increased the concentration of several others and even generated a few new previously undetected compounds. This potential for chemical byproduct formation is concerning, yet almost none of these test labs have ventured into this territory, and the peer-reviewed literature on this topic is extremely scarce. 

 

The second example test report: SARS-CoV-2, a cabinet, and more of the same

Now, it’s worth noting that this particular test report dates back to March of 2019 — well before COVID-19. These types of tests and the resulting reports are commonplace for technologies that purport to kill or inactivate or destroy microorganisms. Since COVID-19, numerous device manufacturers have also tested their products in commercial laboratories for their effectiveness in removing or killing SARS-CoV-2. It seems that even fewer labs are equipped to handle this dangerous virus. Aerus turned to a different lab this time, MRI Global, to conduct testing of the decontaminating ability of ActivePure® technology for SARS-CoV-2.

The test lab used what looks to be the same, or at least similar, Medical Guardian unit with 300 CFM of airflow. The lab placed the device in a biosafety cabinet that was 6 feet x 4 feet x 4 feet, or 96 cubic feet. That’s a 300 CFM air cleaner in a cabinet the size of a closet. If you divide 300 CFM by 96 cubic feet, that’s an effective recirculation rate (flow divided by volume) of about 187 per hour. There isn’t an indoor environment on planet earth for which these conditions would be relevant. 

The lab conducted tests with a control where the unit was operating without the ActivePure® technology operating, although they don’t show their control data in the test report (they only show comparisons on what appears to be a net-log reduction basis, i.e., with the control rates subtracted out). They didn’t aerosolize SARS-CoV-2 but rather inoculated test coupons and placed them on the floor of the cabinet. They sampled after 1 hour, 3 hours, 6 hours, and again at a 7th hour. Between the 6th and 7th hour, for some reason, the lab increased the relative humidity (RH) in the cabinet, which seemed to escalate the loss rate (but that seems quite unrelated to the performance of the unit itself). For that reason, I will look only at the 1 h, 3 h, and 6 h data:

There isn’t much data to work with here, but since there was no reduction in viable SARS-CoV-2 after 1 hour, I will use that as the time zero starting point, and shift the time since that time for the next two time stamps to 2 hours later and 5 hours later. I use the reported net log viable reduction, presumably with the control rates subtracted out, to again calculate a linear C/C0 value at each time step followed by a ln(C/C0) value at each time step. A brief table of these results is below, followed again by a figure showing the “net” ln(C/C0) values over time, which I can use to estimate net, i.e., additional, loss rates over the control condition. 

Time (hr) Time (hr) Net Log reduction C/Co ln(C/C0)
1 0 0 1 0
3 2 1.17 0.0676083 -2.6940246
6 5 1.69 0.02041738 -3.8913688

Once again, 97.9% reduction in viable SARS-CoV-2 on test coupons after 6 hours sounds pretty impressive! But if you calculate an effective first order loss rate constant from these data, you obtain a value of only ~0.9 per hour. The fit isn’t perfect — there are a small number of data points and some deviation from a perfect first order decay profile, but it’s not an unreasonable estimate. What does that mean practically? Well, converting this to an effective SARS-CoV-2 CADR yields a CADR of almost nothing (~2 CFM):

Loss rate summary
  Loss, 1/h
Delta (net) 0.8567
Delta, 1/min 0.01427833
Chamber Vol, ft3 96
CADR, cfm 1.4

About 2 CFM. This is with an air cleaning device with an airflow rate of 300 CFM, which is enough to cover a large room like a classroom or large bedroom, operating in a cabinet that was not much larger than the device itself. And the additional CADR for viable SARS-CoV-2 introduced by the use of the ActivePure® technology was essentially zero. Another impressive looking claim (99.7% removal after 6 hours) that doesn’t translate to reality. (I would also note that I would really like to see the background condition loss rate data because my hunch is that they left the HEPA filter installed but UV-PCO + ionization functions turned off, and that the loss rates were probably a lot higher in magnitude with the HEPA filter only compared to the additional benefit from turning these functions on). 

Now, operating a big air cleaner in a small cabinet seems a bit ridiculous, I know. But it gets worse.

 

The third example test report: SARS-CoV-2, an even smaller chamber, and again more of the same

Aerus also contracted with the University of Texas Medical Branch (UTMB) to test another of its devices that utilizes their ActivePure® technology for inactivating SARS-CoV-2. This is the third report in the packet linked above. In these tests, the lab placed one of two Aerus devices — their Pure & Clean unit and their subsidiary Vollara’s Air & Surface Pro unit — in a small (150 L) chamber and tested the impact on aerosolized SARS-CoV2. The Pure & Clean unit appears to operate at an airflow rate of 40 to 60 CFM, while the small 150 L chamber is only about 5 cubic feet in volume. Divide flow rate by volume in this setup and you get an effective recirculation rate of between 450 and 680 per hour! Again, a relatively large air cleaner in a very, very small volume:

Here are the test results:

Once again, great looking results like >99.8% inactivation of SARS-CoV-2 within minutes. Those kinds of results will get you FDA approval for use in hospitals. And once again, I took a similar approach here in attempting to calculate effective CADR values for SARS-CoV-2 from this somewhat bizarre test configuration. However, I could only use one data point for the air cleaner on condition because SARS-CoV-2 was reduced below detection limits within 3 minutes in this configuration. So the CADR is likely an under-estimate, but I don’t know by how much. Here are my results in table form:

    Control Test
Time (mins) Time (hr) LogReduction C/Co ln(C/C0) LogReduction C/Co ln(C/C0)*
0 0 0 1 0 0 1 0
3 0.05 0.71 0.19498446 -1.6348354 3.07666667 0.00083817 -7.0842868
10 0.16666667 1.30333333 0.04973552 -3.0010359 3.07666667 0.00083817 -7.0842868
15 0.25 1.27333333 0.05329257 -2.9319584 3.07666667 0.00083817 -7.0842868
30 0.5 2.41 0.00389045 -5.5492301 3.07666667 0.00083817 -7.0842868

Again, I plot these ln(C/C0) values over time from both test conditions to estimate loss rates:

This results in an estimated loss rate of ~12 per hour in the control condition and ~142 per hour with the technology activated. These are huge values, but largely because of the size of the air cleaner compared to the small chamber. Multiplying the difference in loss rate estimates by the chamber volume yields another small effective CADR for viable SARS-CoV-2, this time about 12 CFM:

Loss rate summary
  1/h
Control 11.9
Test 141.7
Delta 129.8
Delta, 1/min 2.16333333
Chamber Vol, ft3 5.295
CADR, cfm 11.5

A CADR of 12 CFM is again lower than the airflow rate of 40 to 60 cfm of the unit, assuming they operated it at one of those flow rates (it is unclear). Once again, an additional 12 CFM of inactivation in a real room achieves almost no additional removal.

 

Why does this matter? 

So what have we learned here? Using just one example air cleaning technology and three different commercial test lab reports, we have gained some insights into how limited many of these tests and reports are, often lacking important details to even understand how tests were performed and/or reporting results in a way that look quite favorable to manufacturers. In turn, marketing materials make those results look even more impressive with big claims like 99.99% inactivation of pathogens and so on.

None of this is new in this industry, but it is certainly in greater focus than ever before with so much attention on reducing the transmission of COVID-19 in indoor environments. And while I use this particular company Aerus and its technology to demonstrate these issues, they are in no way unique to this company. These issues are widespread throughout the industry, and have been for years. Other technologies that I’m aware of that have similar issues in their published test reports include the Aerisa 2000 ion generator (I estimate a CADR of about 57 CFM for MS2 in the test configuration reported), GPS bipolar ionization units (I can’t estimate a CADR from many of their test reports because they don’t report a chamber volume!), and many more.

With something like $170 billion in the recently signed COVID relief bill being directed to K-12 schools and colleges for upgrading ventilation systems and portable air cleaning units (see screenshot from the actual bill below), it is imperative that we understand how to interpret manufacturer claims of the effectiveness of air cleaning technologies in addition to the potential safety concerns associated with many “additive” air cleaning technologies that rely on the addition of reactive constituents to indoor air to do their dirty work.

 

Learn more by analyzing air cleaner test reports on your own!

If you find yourself reviewing test reports like these, you may be interested in analyzing them on your own. Fortunately, my colleague Elliott Gall at Portland State University has developed an online air cleaning efficacy calculator tool that you can use. You can input data from test reports in a variety of ways that data are commonly shown — including % reduction over time, log reduction over time, or translating from a plot of log reduction over time — and calculate an effective CADR for the test conditions. You can then translate that to an effective air change rate equivalent or your space.