PM2.5 algorithms

Could someone please explain the basic difference in the algorithms pm2.5_alt, pm2.5_atm and pm2.5_cf_1 used to calculate the ug/m3 value from the sensor particle count data? Which algorithm is best to use when reporting data from different regional areas such as Salt Lake City and Ogden? Which shows the best correlation to EPA measurements? Many thanks.

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Just to echo menzies concern. Here is a plot of pm2.5 values by method of obtaining (pm2.5_alt, pm2.5_atm, and pm2.5_cf_1). Data are 8-hour from mean of several locations in Ogden, UT for first 10 days of Feb. You can see that p,m2.5_alt gives lowest value, with pm2.5_atm being larger (p<0.05) and pm2.5_cf_1 largest (though not sign different from pm2.5_atm), and the latter has more scatter.

EPA has spent a lot of time studying the Plantower conversion factors and how they apply to real-world PM2.5 measurements. You might start by reviewing the papers/presentations linked in the post below. The actual algorithms are proprietary to Plantower.

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Thank you @dwhitemv , that is a very informative link. It describes however the correction factors to apply to the pm2.5_cf_1 and pm2.5_atm variables. No mention is made of pm2.5_alt. Does anyone know what is it?

The API describes it as The ALT Variant estimated mass concentration PM2.5 (ug/m3), but it doesn’t say how it should be used.

The ALT variant is described in the API doc at, in the “Sensor data fields” table in the “Get Sensors Data” section.

All most helpful. Many thanks for the information