Should a filter for particle counts with a "less than diameter" be added?

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I think it might be useful to see the particle counter below 1 microns. Currently it only allows filtering >= X microns. Particles below 1 microns can loosely be considered ultrafine particles, and some studies suggest they are the most dangerous as they can lodge more deeply into the lungs.

One caveat with this request would be that the sensor can detect particles 0.3 microns and larger, so the expected range would be 0.3 to 1 micron. This isn’t the full picture for ultrafine particles as they can go far smaller before being basically considered gases.

However, I think this filter would still be quite useful as one often doesn’t get much differentiation of ultrafine particles with the other filter options such as micrograms per cubic meters (density). While a density filter for 1 microns and less does exist, it frequently shows values that are very tightly ranged and homogenous across the majority of the meters of a city. However, if you jump to particle counts, the spread becomes much more noticeable.

Take this area near Dallas right now for example.

The less than equal to 2.5 micron density is very homogenous:

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However, the greater than equal to 2.5 micron particle counter is quite heterogenous:

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The reason for this is that the weight of the particles the smaller they get are far smaller and it takes more and more smaller particles to contribute the same amount of weight when compared with larger particles.

I would like to see particle counter filters with less than equal operators because I believe these filters will truly show the massive amounts of smaller particles that belie equivalent density and mass readings.

If this filter were to exist, I would expect the second map to show very high particle counts for smaller “ultrafine” particles. Essentially the green circles that have 0’s for large particles should show very high values for smaller particles to make up the majority of the roughly equivalent mass.

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It would be nice if the PA devices were proper particle counters, but they are not; they are nephelometers. The particle count outputs are synthesized, and use assumed density factors (one is applied by the sensor software and another is selected on the map). Use caution trusting any of the particle count outputs.

Also – and I have not reviewed the literature on this recently – but PM2.5 is considered the diameter where ‘deep inhalation’ is a concern, which includes PM1.0. I’m not sure dividing it any further would be beneficial given the current science. Could always change in the future.

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Thank you for the reply, Doug!

I need to look into how they calculate counts and mass. However, it would appear that both measurements are indirectly determined by algorithms depending on assumptions of density factors. If that is the case, would that suggest that we would need to take equal caution interpreting both?

My concern with relying on PM1 is that it can severely underrepresent ultrafine particle counts in certain situations, especially closer to vehicular pollution sources. But I do admit that if the counts and masses can only be inferred from assumed density factors, then we simply do not have the ability to distinguish particle sizes.

All this begs the question: why even have any of these filters and representations (e.g. pm1, 2.5, 10) if PurpleAir monitors cannot actually measure them differently? Are these buckets created simply by applying different assumed density factors? If that’s the case, couldn’t that be very misleading?

I’m still new to this, but very curious to learn how it all works.

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After reviewing research papers on the topic, I retract the statement that the particle counts are synthesized. A light-scattering type nephelometer is capable of discriminating particle sizes, typically into classes or bins of a certain width. The conversion from a count (particles/dL) to a gravimetric weight (μg/m^3) is impacted by (assumed) density.

I would advise against taking the particle counts too literally, as it isn’t actually counting individual particles.

As with all sensors, there are limits. For the Plantower PMS5003 used in the PA-II Classic, the lower size limit is 0.3μm, accuracy below 0.5μm drops precipitously and there is noise from particles below those limits. (See the 3rd paper below for a study on sub-1μm particle measurement with this sensor.)

The sensor outputs summations of diameters at the level and higher (i.e., >0.3μm, >0.5μm, >1.0μm, etc.). A less-than reading is computed by subtracting the higher bound from the lower and should be expressed as ‘0.3μm >= x >= Yμm’ to accurately portray the available data.

To answer your last question – The hardware is capable of size discrimination and adjustments can be developed & applied to obtain meaningful data, but it can’t tell us density. This is the limitation of nephelometer technology. They work best when the optical properties of the material under test are known. With air pollution, the components are different depending on what your pollution sources are, and its very difficult to come up with general rules that apply well everywhere. And yes, if the adjustment factors are off, you get useless data; GIGO.

If you want more details on how the hardware works and how the adjustment factors are developed, I’ve linked some research papers below that may be of interest.

This paper discusses EPA’s early efforts to develop a nationwide correction for PM2.5 from PurpleAir sensors. The paper is a good primer on the difficulties of calibrating air quality sensors, and dealing with the limitations of the Plantower sensors compared to Federal spec air quality measuring equipment (note that the current adjustment is vastly different than the one presented here). EPA evaluated particle counts as a basis for calculating PM2.5 but discarded it due to complex interactions with humidity:

Lance Wallace, who frequents this board, published a study in 2022 that uses the particle counts to derive a PM2.5 measurement with better limits-of-detection than the Plantower-derived PM2.5 output:

There’s certainly opportunities for research on PurpleAir performance with ultrafine particles. This paper, while a bit more technical, discusses sensor performance (and its quirks) with small particle sizes:

https://doi.org/10.1080/02786826.2019.1696015

For further reading, the board maintains a list of research papers on PurpleAir sensors which can be found here:

Hope this helps!

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Thank you so much! I’ll take some time to look over what you shared. The size binning now has me very curious.

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Hi Doug, I found this paper (from the first paper you linked by AMT) that more clearly confirms that your earlier comment is actually correct. It appears the particle compositions (distribution of sizes) are a provided standard, and sizes are not actually physically differentiated nor measured in any way by the sensor.

The mention within your AMT article:

In addition to PM2.5 concentration data, the PurpleAir sensors also provide the count of particles per 0.1 liter of air above a specified size in µm (i.e. >0.3, >0.5, >1.0, >2.5, >5.0, >10 µm); however, these are actually calculated results as opposed to actual size bin measurements (He et al., 2020)

Within that referenced paper:

The sensor provides data in 6 size channels for accumulated particle number concentration (>0.3, >0.5, >1.0, >2.5, >5.0, and >10.0 µm) and 3 channels for mass concentration (PM1, PM2.5, and PM10). The three mass concentrations are further reported as standard and environment by the sensor manufacturer, though the distinction is not entirely clear.

I think this makes sense as it is not individual particles that are passing through the laser beam at a time, but rather a stream of air. They must simply be measuring total scattered light by an unknown number of particles and particle sizes. I earlier found a video that shows the dissected device to confirm that it’s simply a fan that blows air through the area shown by the laser; no physical channels or binning: https://youtu.be/bBYBETl_X0I?t=321

So you’re definitely right to be skeptical about the counts. In fact, the mass reporting is also based on standards.

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Personally I don’t see what the AMT paper is referencing when it says “calculated results,” and it doesn’t make sense compared to what this type of hardware is capable of. Maybe they mean the summation?

I mean, “a fan that blows air through the area shown by the laser” is how all nephelometers work. It’s not a particle counter like the type used for liquids.

Also, you will see references to “CF_1” and “CF_ATM”, these are the Plantower-proprietary calibration factors called “standard and environment” in the He, et.al. paper.

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Do you have a source that indicates it is capable of differentiating size?

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A couple more papers related to your inquiry:

James Ouimette seemed to think that most of the bins included in the plantower data were actually directly related to the >=0.3um bin, which would be the total scattering signal.

A paper published this year by Dan Jaffe (for which James Ouimette is a co-author) seems to suggest that the larger particles bins at least (5 and 10 um) are independent to some degree of the total scattering signal, and can be used to reasonably determine a coarse aerosol fraction.

So, suffice to say, it’s not completely clear how these sensors operate, but they are able to discern a bit more beyond total scattering.

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Just the datasheet. I haven’t looked for a third-party confirmation.

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I can supply a Word document of references to studies involving either PurpleAir or Plantower sensors. I tried to upload it just now but got a message that it was not one of the allowed extensions, such as .jpg. So here is the whole thing. These are only references that I have used in my five or six papers on PurpleAir studies.

I should state that I have a much larger file with many more full papers. I could make that available if there is any interest.

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Barkjohn, K., Gantt, B., Clements A.L. Development and application of a United States wide correction for PM2.5 data collected with the PurpleAir sensor. Atmos Meas. Techniques 2020 4 (6):10.5194 https://doi.org/10.5194/amt-2020-413

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