Inspired by an article in PNAS (https://www.pnas.org/content/117/22/11875) by some folks at NIH where they looked aerosols with a laser, I was interested in looking at the rate of aerosol spread from masks during talking and singing. This was in part because in the summer is was very difficult to acquire masks, quality was variable, and we were thinking about return to school in the fall.

I built a prototype from cardboard, but the system was super noisy. Enter the GF. I cut out and decorated a box (because the decoration is very important for the science part). The system looks like this:

Inside:

The basic premise is that the laser fluoresces the floating aerosol particles from that stuff coming out of your mouth and you can determine the size and frequency of the particles by imaging and analyzing the size. For a laser, I got the most powerful green laser pointer from amazon and grabbed my spouseâ€™s mini IPad (in case I accidentally damaged the detector on the camera). Here is an example of droplets in front of the laser (a simulated cough):

So then I took Slo-Mo video (90ish frames a second) of myself speaking into the funnel on top, first counting to 15 in a normal voice and then shouting. I tried out various masks in one sitting including KN95s which are easily available now, a scarf mask my spouse ordered early on, N95 painterâ€™s mask with outflow and and N95 from my friend Josh, a fabric mask with pleats I like to wear and a face shield. I kept myself hydrated. I analyzed the data by writing an OPENCV (computer vision library) program to identify the droplets and estimate size over the length of the movies. The program also deduplicates as good as I can for droplets which appear over multiple frames (floaters) and does some basic getting rid of super small stuff. It is not a perfect algorithm- but is pretty good for comparison purposes. Here is a sample of these droplets plotted the Y axis (down) is the frame number and the X axis (across) is the position on the portion of the laser that is detectible in the movies. Here is example unmasked:

A zoom in where you can my big slobber and lots of small bits coming out:

And the full pictures:

The results are here broken out into Talk period and shout period (without the overlap) and totals. These are all measured in Fluorescent Units (FUs):

And a graph minus the first No Mask attempt (which was for sure the most vigorous):

So a few take homes:

1. Any â€śreal maskâ€ť is better than none at preventing aerosols.
2. Fabric scarfs are not â€śrealâ€ť masks.
3. N95 with outflow filters are the same for others as if you are wearing no mask. High FU units.
4. N95s and K95s are just a bit above background.
5. Shouting is worse in general than talking

In terms of total FUs: KN95 & N95, Pleat Fabric, Face Shield, Scarf, No Mask & Painters

For total particles detected over the sample period:
KN95 55
Painters 275
Scarf 262
Pleat Fabric 119
N95 64
Background 27
Face Shield 128

So for number of particles: KN95, N95, Pleat Fabric, Face Shield, Painters N95

So nothing too surprising! If you can please, wear a mask in order to reduce transmission of COVID/flu and protect yourself and family. Stay Safe!

Just a note on sources of error here:

1. I used a laser pointer here which isnâ€™t a very clean laser source and it has the added problem of slowly fading over time until it is recharged. I didnâ€™t want to shell out for a \$500 laser to improve the source. This accounts for some of the background noise and means that I canâ€™t really do multiple tests over the course of a day as the laser weakens.
2. I only allowed 5 minutes between tests- this mostly is enough for the level of detection her to let the particles mostly pass out of the laser beam. However, this time could be extended.
3. There is no real replication here- for sure doing this 5 times per mask in random order with measurements of background noise in the system would improve the accuracy (but probably require a better laser source for consistency (see #1) .
4. I use pretty standard Canny edge detection in openCV tuned to avoid small repeated sources of error, but this could be much better implemented and tuned.
5. Aerosol droplets are dependent on how much liquid you got to expel, here, I did rehydrate - but it is clear that for my first no mask attempt, which was also the first attempt for this data set, I had some â€śextraâ€ť spit to expel.
6. These masks were all fresh and mostly unworn- for sure after you have been wearing a mask for 8 hours they likely perform differently. For example, I wear one of these doubled, pleated fabric masks as they are comfortable, but I find that they are pretty saturated with spit after a few hours when talking. This likely increases transfer both ways. Iâ€™ve taken to trying to wear disposable KN95s when I am going to speak with people or a group for any length of time.

So these results should only be viewed as a pilot where I tired to maintain a reasonable design.

Disclaimer: I am a scientist, but not an infectious disease expert. My reading from the current science is that aerosol droplets from superspreaders are bad and you shouldnâ€™t inhale them.

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Just plain Awesome.

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Wow, that is impressive work.

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SO impressed with what youâ€™ve done. Thank you for showing us allâ€¦

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I love science. I know itâ€™s not 100% controlled, but itâ€™s interesting to see the results.

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Kind of surprised a face shield registered anything using your method.
What is the explanation for how it got around the sides of a face shield and then returned to the center to penetrate the funnel?
Regardless, fun science is fun.

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Like your methodology for sure. Great practical cut.

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Cool stuff! Making science make sense! A worthy goal of any GF owner! Nice job!

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excellent stuff.

Did you try it with the masks inside out to see what comes through from the outside? Itâ€™d be interesting to see if thereâ€™s a directional component. Itâ€™s not like youâ€™d get someone pushing droplets like you do when breathing out but it would be an indicator of how much they might help keep you safe vs how much youâ€™re helping others stay safe.

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Neat experiment!
Itâ€™s difficult to conceptualize what are ordinarily invisible particles, but if you think about what your breath looks like on a cold day itâ€™s easier to picture how we spew with every exhale and how much wearing a mask would mitigate transmission.

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The face shield is a little different because I just couldnâ€™t cover the funnel with it so this is measuring about 6 inches above the funnel. Itâ€™s one of the light mylar ones (ordered from amazon). Whats happening here seems to be the face shield is creating a few larger floaters which are bumping up the counts a bit above the background. Overall it not hugely different than background (but looks bigger on FU units). I probably need to tweak the counting for it to make the counting a bit cleaner. I did notice that when you shout into a face shield you are moving air heavily out the sides of the shield. There has been some work showing that face shields arenâ€™t generally protective when worn without a mask- as you create a vacuum when you breath in. Regardless- I need a different methodology for measuring it- the mask counts are relying on particles being funneled into the laser and most of the outflow on the face shields is out the bottom and sides.

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Well done. I hope some anti maskers get to see your results.

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I did not, to do so you would need a negative pressure supply to pull air through a mask and an aerosol source. The rating for the mask (when rated) are based on how many microparticles pass through. This might be a bit above my weekend tinkering skills, but Iâ€™ll think about it a bit.

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I thought about that but a surrogate might be simply running the test with the masks turned inside out and probably not running a shouting test because you really shouldnâ€™t see anyone generating that kind of pressure on the front of your mask. It wouldnâ€™t be as exact as your thoughts relative to using a negative pressure supply & aerosol generator but it could identify if there is a difference in the way a mask works through the various layers. That does assume masks that have different materials for the front/exterior and the interior/face side layers.

Very impressive results plus I like that I can actually see the differences in the filters.

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This is really amazing work and such a coll use of your GF! Have you posted this elsewhere for others to see? Iâ€™d love to share it with some folks.

And if you do any more testing, itâ€™d be interesting to compare a gaiter and a gaiter with the filter insert. I prefer them and itâ€™d be cool to see how well they work.

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I have bad news about gaitersâ€¦ (I prefer them too!) The medical clinic we go to has just started not allowing gaiters and bandannas, I think because theyâ€™re basically just too thin. But I did read an article where researchers found the microfiber ones actually disperse MORE virus because they break up the breath droplets into smaller particles.

Iâ€™m still hoping non-microfiber gaiters are okay. For non-work purposes, I wear one folded in half and covered by another one, to make 3 layers. I think a filter insert would be a good idea, too.

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Yeah, I donâ€™t think regular gaiters are viable, but I have two that have the same insert that comes with masks and Iâ€™d love to know what difference it makes.

I do think there is a difference of single ply lycra gaiters and thicker (industrial style) gaiters. This is writeup that describes the early proof of principle that led to gaiter â€śbadâ€ť becoming common thinking:

There is a link to a talk from Virginia tech by Jin Pan in that article which suggests doubled gaiters block 90% of 0.5 -5um aerosols. And that any face covering is better than none. For larger drops gaiters block them handily (so you wonâ€™t be spitting in otherâ€™s peoples faces :). Just a science aside here, it is super strange to link to a PDF of a talk as evidence of any science proof. Covid has completely upended any of the normal science (slow) process for validation and publication and made unpublished papers the norm for anything virus related.

The pleated 2 play fabric ones do get saturated with condensation over time and for sure silk or lycra gaiters do also when I have worn them. I didnâ€™t have a gaiter around to check with my setup, but i can order one. The scarf is effectively a very thin two ply material. For gaiter with a filter, I would think that as long it fits properly and the filter is changed it wouldnâ€™t differ from any other rated disposable mask. One should note that for incoming particles the N95s have electrostatic charged layer to capture very small particles just like your furnace filter, so they are directional for tiny floating particles. They stick to outside, but donâ€™t move into your mouth. So some of the benefits of the N95/K95s go beyond just a physical barrier such as you get from cloth based masks. Hence why you have to discard them if you are interested in small particle filtering. This describes the differences well https://guardianrfid.com/blog/a-quick-guide-to-n95-kn95-and-surgical-masks

This is a good quote from the site to remember:

â€śKeep in mind that surgical masks do not provide the wearer with a reliable level of protection from inhaling smaller airborne particles and are not considered respiratory protection.â€ť

This means maybe in high contact scenarios you should go with the N95 over the very cheap 3 ply surgical masks for your protection. My youngest kids are back in school and they were 3ply pleated surgical masks, but we send out oldest in high school every day in a KN95 and she wears them only once.

Keep in mind all this aerosol particle testing stuff is about protecting other people from inhaling your floating aerosols, not that these face coverings all protect you equally.

If you can see through the ads, these are some nice charts, explaining that masks donâ€™t stop the spread of covid, they just greatly reduce the number of cases and slow the spread.

Based on recent pubs, the severity may be linked to how much of the virus you intake, so even if masks do not stop spread they may greatly reduce the severity of cases.

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