Jeff Gilchrist Profile picture
Nov 24, 2023 48 tweets 12 min read Read on X
Why can you still smell things wearing an effective mask?

You can smell nasty things like smoke and rotten eggs even with fit tested #N95 respirators which block tiny viruses/bacteria because the smell molecules have atomic masses that are 17 million times less than a virus.🧵1/
Image of a woman wearing an N95 respirator with an expression of disgust from smelling something bad. Generated using Bing Image Creator powered by DALL-E 3 using prompt, "A person wearing an N95 mask with an expression of disgust from smelling something bad"
Graph using logarithmic scale showing difference in atomic mass (Daltons) of various gases like oxygen, carbon dioxide and some you can smell ranging from 32 to 131 Daltons while the COVID-19 virus is millions of times more at 602 million Daltons and the aerosol it travels in is billions of times more at 160 billion Daltons.
This long thread (with info from @Wikisteff) explains how molecules detected in our olfactory receptors as #smells can pass through material in #masks, #respirators, and #filters (HEPA/MERV-13/CR Boxes) while still blocking tiny particles like #viruses and #particulate matter. 2/
An unrolled one-page web view for this long thread that may be easier to read or share can be found here ( ). 3/
First, some background information. A dalton (Da) or unified atomic mass unit (u) is commonly used in physics and chemistry to express the mass of atomic-scale objects such as atoms, molecules, and elementary particles ( ). 4/en.wikipedia.org/wiki/Dalton_(u…
Oxygen (O2) that we breathe is 32 Da and carbon dioxide (CO2) that we exhale is 44 Da. Other gases that we smell like hydrogen sulfide (H2S) which smells like rotten eggs is only 34 Da, and sulfur dioxide (SO2) the burning smell after lighting a match is 64 Da. 5/ Atomic stucture diagrams of Oxygen (O2), sulfur dioxide (SO2), and carbon dioxide (CO2). Diagrams from: https://pubchem.ncbi.nlm.nih.gov/
When you pass gas (fart) the smell comes from a multitude of molecules including:
- Hydrogen Sulfide (H2S) = 34 Da
- Methanethiol (CH3SH)= 48 Da
- Dimethyl Sulfide (CH3)2S = 62 Da
- Indole (C8H7N) = 117 Da
- Skatole (C9H9N) = 131 Da

6/
This is very important to understand because by comparison, a single COVID-19 virus particle (virion) has a mass of 602,217,364 Da or 17 million times more than the rotten egg smelling hydrogen sulfide at 34 Da ( ). 7/pnas.org/doi/10.1073/pn…
It is estimated that a COVID-19 infected person carries between 1 billion and 100 billion virions during peak infection ( ). 8/pnas.org/doi/10.1073/pn…
Viruses don't travel on their own through the air, they actually catch rides in aerosols which also contain water, mucins from the lining of the lungs, deep lung fluid and surfactants to make up the complex blob you see in the image ( ). 9/
Image showing respiratory aerosol and its contents (water, mucins from the lining of the lungs, deep lung fluid and surfactants). Image from: https://www.nytimes.com/interactive/2021/12/01/science/coronavirus-aerosol-simulation.html?smid=tw-share
Multiple studies have found the highest concentration of virus in aerosol particles are in the smaller size ranges which can stay in the air for extended periods of time and lowest concentration in larger droplets that fall to the ground quickly. 10/
COVID-19 was detected in aerosol particles ranging in size from 0.34 micrometers (um) to larger than 8.1 um with the highest concentrations found in particle sizes ranging from 0.94 um, to 28.8 um ( ). 11/tandfonline.com/doi/full/10.10…
@Wikisteff estimates the molecular mass of a 0.8 um largely water based aerosol (which is at the smaller end of the aerosol size spectrum but with highest concentrations of COVID-19 virus) would be approximately 160,000,000,000 (160 billion) Da ( ). 12/ncbi.nlm.nih.gov/pmc/articles/P…
You can see from the graph there is a monstrous difference in mass between gases you can smell like hydrogen sulfide (34 Da) and the bare COVID-19 virus (602 million Da) and the aerosols that COVID virus are transported in (160 billion Da). 13/ Graph using logarithmic scale showing difference in atomic mass (Daltons) of various gases like oxygen, carbon dioxide and some you can smell ranging from 32 to 131 Daltons while the COVID-19 virus is millions of times more at 602 million Daltons and the aerosol it travels in is billions of times more at 160 billion Daltons. Note the graph is in logarithmic scale so each number on the vertical axis scale is 100x larger than the one below.
Note the graph is in logarithmic scale so each number on the vertical axis scale is 100x larger than the one below. 14/
We know that people can still breathe while wearing masks and respirators so oxygen (32 Da) and carbon dioxide (44 Da) can pass through the filtering material easily which have similar atomic mass to the smell gases (34 to 131 Da) which can also pass through. 15/
In order for a respirator to be effective at blocking viruses and particulate matter it needs to block particles that are 17 million times larger mass than gas to stop a COVID-19 virus and 4.7 billion times larger mass to stop an aerosol that the virus would be travelling in. 16/
So now you know that smelly gases have a similar mass to oxygen and why they can easily pass through mask/respirator material just like oxygen but can N95 respirators actually filter these million and billion times larger mass particles of viruses and bacteria? Yes! 17/
Scientists and engineers who designed these respirators did actually test them to ensure they did filter viruses and bacteria and even came up with standards for determining the efficiency with real viruses and bacteria. H/T: @ghhughes 18/
Bacterial filtration efficiency (BFE) is tested using the ASTM F2101 standard and multiple tests were conducted in this study using the S. aureus bacteria... 19/
while viral filtration efficiency (VFE) was tested using the single-stranded DNA virus bacteriophage phiX174 ( ). 20/ncbi.nlm.nih.gov/pmc/articles/P…
The study found that the N95 respirators they tested filtered more than 99.62% of the bacteria and more than 99.8% of the virus which is much higher than the required 95% filtration needed by the N95 standard to pass. 21/ Table showing Filtration efficiencies for N95 FFR, surgical N95 FFR, and surgical mask models using the NIOSH NaCl, PFE, BFE, and VFE test methods. Image from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7157953/
So there you have it, N95 respirators can actually filter viruses and bacteria and are actually tested with a standard to ensure so. 22/
To learn more about how N95 respirators and HEPA/HVAC filters can filter out such small particles like virus aerosols and particulate matter from smoke (does not work like a sieve), see this thread which explains the physics ( ). 23/
Ok so we have now confirmed the filtering material itself can filter viruses and bacteria, but what about a respirator on the face of a real person in the real world, does that still work? 24/
Thankfully engineers have also built equipment called a condensation particle counter (CPC) to measure the particles both outside and inside a respirator simultaneously. 25/ Photo showing quantitative fit testing with someone wearing a mask with tubes connected to measure the aerosols in the room and comparing them to inside the mask. Photo from: https://www.youtube.com/watch?v=2xyNg2s1u7c
This testing occurs while the person is wearing the respirator so they can measure exactly how well the respirator is filtering on your face in the real world. 26/
Some of you may have already experienced this through a respirator fit test. You can learn more about how quantitative fit testing with CPC equipment is done in this thread ( ). 27/
As @ghhughes points out, CPC fit testing equipment can measure particle sizes all the way down to 0.02 um in size, much smaller than the COVID-19 virus on its own and the even larger aerosols the virus travels in. 28/
This also demonstrates that N95 respirators can be tested and shown to filter out tiny 0.07 um size particles the size of individual viruses with good fitting N95s measuring less than 0.5% total inward leakage of particles down to 0.02 um. 29/
Since the CPC is testing the level of particles inside the mask while being worn, the results also take into account any gaps around the mask that might be leaking particles in without being filtered ( ). 30/
The most important factor is how well a respirator fits on your face so there is minimal leakage around gaps as some respirators fit people very well and others very poorly. Click "Show replies" 👇 to continue. 31/
You can learn about my fit testing adventure where I found one mask leaked 70x more than another on my face ( ). 32/
The respirator that fit me best was measured to only have 0.2% leakage on my face so filtering 99.8% of particles but when the major wildfire smoke events were happening this summer I could still smell the smoke outside. 33/
Recall that the smoke gas molecules you can smell are billions of times less mass than the smoke particulate matter so while the N95 respirator is filtering out those toxic PM particles. 34/
N95s are not designed to filter out gases so you can still smell and are being exposed to any toxic gases that are in the air. For that kind of protection you need elastomeric respirators with gas filtering cartridges specifically designed for those gases. 35/
What about HVAC, HEPA, and CR box filtration, do they work to filter viruses from the air as well? Yes! The Environmental Protection Agency (EPA) recently conducted some tests with CR boxes which use MERV-13 HVAC filters ( ). 36/s.uconn.edu/EPAresults
The EPA aerosolized non-pathogenic virus (bacteriophage MS2) and measured particle size (0.01 um to 0.6 um) and concentration during the testing in a 3000 square foot test chamber. 37/
They found the virus particle concentration was reduced by 40% after 15 minutes, 97% after 30 minutes, 99.4% after 60 minutes and 99.8% after 90 minutes. 38/ Table and graphs showing EPA bioaerosol results. Reductions calculated by averaging results of three control test replicates and three EPA CR box test replicates. Image from: https://s.uconn.edu/EPAresults
More details about this EPA CR box testing project are described here ( ). 39/
Just like we expect to have access to clean drinking water, we should be demanding that our governments also provide access to clean air. Recently 60-Minutes did an episode on The Air We Breathe which can be seen here ( ). 40/cbsnews.com/video/indoor-a…
Everyone should be aware of the importance of indoor air quality, find out more here ( ). 41/
This thread was inspired by posts made by @jossreimer ( ) and @Wikisteff ( ) on smells while masking. 42/
@threadreaderapp please unroll
It is important to note that masks can also reduce some smells and block others all together, it all depends on how the smell molecules arrive; if they are tiny gases on their own or if they are larger particles that get filtered. 43/
I forgot to highlight that N95 filtering material has the hardest time with 0.3 um particle size but actually does better with smaller and larger particle sizes as shown here ( ). Thanks @ToshiAkima. 44/
The explanation why the filters work better with smaller and larger particles is explained here ( ). 45/
Arg, I added an extra 0 in the graph for the atomic mass of the COVID virus. The text is correct at 602 million Da, but here is the corrected chart. Graph using logarithmic scale showing difference in atomic mass (Daltons) of various gases like oxygen, carbon dioxide and some you can smell ranging from 32 to 131 Daltons while the COVID-19 virus is millions of times more at 602 million Daltons and the aerosol it travels in is billions of times more at 160 billion Daltons. Note the graph is in logarithmic scale so each number on the vertical axis scale is 100x larger than the one below.
Arg, I added an extra 0 in the graph for the atomic mass of the COVID virus. The text is correct at 602 million Da, but here is the corrected chart. 46/ Graph using logarithmic scale showing difference in atomic mass (Daltons) of various gases like oxygen, carbon dioxide and some you can smell ranging from 32 to 131 Daltons while the COVID-19 virus is millions of times more at 602 million Daltons and the aerosol it travels in is billions of times more at 160 billion Daltons. Note the graph is in logarithmic scale so each number on the vertical axis scale is 100x larger than the one below.

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More from @jeffgilchrist

Jun 1
*** Ontario Virus Update | June 1 ***

Hospitalizations due to COVID have decreased from 38 to 21 in the last update. Influenza hospitalizations decreased from 51 to 44 and RSV decreased from 20 to 18 so moving in the right direction but still not finished for the season yet. 1/ This stacked bar chart displays weekly new hospitalizations in Ontario specifically attributed to COVID-19, Influenza, and RSV. The data tracks the fluctuating volume of patients over time, highlighting seasonal surges and the relative contribution of each respiratory virus to the overall healthcare burden.
Looking at age groups, those age 75+ had the highest rates of hospitalization due to COVID but decreased since last update. Tied for second place are the 0-4 and 65-74 age groups. 2/ This 100% stacked area chart illustrates the weekly proportion of COVID-19 hospital admissions per 100,000 population in Ontario across different age groups. The graph visualizes how the relative distribution of hospitalizations shifts over time among demographics ranging from infants to seniors aged 75 and older.
COVID case rates decreased across most age groups this past update except for age <1 which had a significant increase and almost matching the same levels as age 80+. The 1-4 and 60-79 age groups currently have the same rates. 3/ This multi-line graph tracks the weekly rate of COVID-19 cases per 100,000 population in Ontario, categorized by various age groups from infants to seniors aged 80 and older. The data trends highlight the fluctuations in infection rates across different demographics over the year.
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May 30
Filtering the air may help prevent your own infection from becoming more severe

If everyone in a household becomes infected with the same virus, does it help to isolate from each other and can you be a danger to yourself? Read on to find out...🧵1/

#AirQuality #IAQ #Ventilation This grouped bar chart, titled "COVID Positive Abnormal Chest CT by Air Quality Setting", displays the percentage of abnormal chest CT scans among COVID-positive patients across three different tiers of air quality control. The graph compares overall and asymptomatic cases, illustrating a clear downward trend in the percentage of abnormal scans as air filtration and ventilation efficiency improve from household levels to high-efficiency aerosol control.
An interesting hypothesis-generating study was published recently that asked if an infected person's condition can become even worse by re-inhaling their own virus particles ( ). 2/sciencedirect.com/science/articl…
Is a transition from a milder upper respiratory tract infection (runny nose, sore throat) to a more severe lower respiratory tract infection like pneumonia is significantly driven by the physical mechanism of inhaling virus containing aerosols deep into the lungs? 3/
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May 24
*** Ontario Virus Update | May 24 ***

Hospitalizations due to COVID have increased from 34 to 38 in the last update. Influenza hospitalizations decreased from 57 to 51 and RSV decreased from 33 to 20. 🧵1/

#Ontario #Virus #COVID #RSV #Influenza #Hospital This stacked bar chart displays weekly new hospitalizations in Ontario specifically attributed to COVID-19, Influenza, and RSV. The data tracks the fluctuating volume of patients over time, highlighting seasonal surges and the relative contribution of each respiratory virus to the overall healthcare burden.
Looking at age groups, those age 75+ had the highest rates of hospitalization due to COVID but decreased since last update. Second place is age 65-74 which increased, and third place is age 0-4 which also increased. 2/ This 100% stacked area chart illustrates the weekly proportion of COVID-19 hospital admissions per 100,000 population in Ontario across different age groups. The graph visualizes how the relative distribution of hospitalizations shifts over time among demographics ranging from infants to seniors aged 75 and older.
COVID case rates were fairly stable across age groups this past update except for age 80+ which had a significant decrease but still maintain the highest rates. The 0-4 and 60-79 age groups currently have similar rates. 3/ This multi-line graph tracks the weekly rate of COVID-19 cases per 100,000 population in Ontario, categorized by various age groups from infants to seniors aged 80 and older. The data trends highlight the fluctuations in infection rates across different demographics over the year.
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May 10
*** Ontario Variant Update | May 10 ***

In Ontario, the NB.1.8.1.* "Nimbus" variant family shot to 74.7% of sequenced genomes from COVID tests while the XFG.* "Stratus" family dropped to 15.8% and the BA.3.2 "Cicada" family decreased below 10% again.🧵1/
#Ontario #COVID #Variant This multi-line chart tracks the lineage frequency of various COVID-19 variant families in Ontario over time, based on sequenced genome samples. The graph illustrates the changing prevalence of specific variant families, showing how different lineages compete and evolve as the dominant strains within the province.
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Apr 28
*** Ontario Variant Update | Apr 28 ***

There was some competition for variant dominance during the month of March but the NB.1.8.1.* "Nimbus" family currently holds first place with 49.5% while the XFG.* "Stratus" family sits at 38.1% of sequenced genomes from COVID tests. 🧵1/ This multi-line chart tracks the lineage frequency of various COVID-19 variant families in Ontario over time, based on sequenced genome samples. The graph illustrates the changing prevalence of specific variant families, showing how different lineages compete and evolve as the dominant strains within the province.
The BA.3.2 "Cicada" family has been slowing climbing and now above 10%. 2/
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Apr 13
*** Ontario Virus & Variant Update | Apr 13 ***

Hospitalizations due to COVID have gone down from 153 to 123 in the last update. Influenza hospitalizations decreased from 59 to 47 and RSV decreased from 110 to 85. 🧵1/

#Ontario #Virus #Variant #COVID #RSV #Influenza #Hospital Graph of New hospitalizations in Ontario due to COVID, Influenza or RSV.
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