Articles | Volume 16, issue 5
https://doi.org/10.5194/amt-16-1311-2023
https://doi.org/10.5194/amt-16-1311-2023
Research article
 | 
13 Mar 2023
Research article |  | 13 Mar 2023

An evaluation of the U.S. EPA's correction equation for PurpleAir sensor data in smoke, dust, and wintertime urban pollution events

Daniel A. Jaffe, Colleen Miller​​​​​​​, Katie Thompson, Brandon Finley, Manna Nelson, James Ouimette, and Elisabeth Andrews

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Latest update: 04 Mar 2024
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Short summary
PurpleAir sensors (PASs) are low-cost tools to measure fine particulate matter (PM) concentrations. However, the raw PAS data have significant biases, so the sensors must be corrected. We analyzed data from numerous sites and found that the standard correction to the PAS Purple Air data is accurate in urban pollution events and smoke events but leads to a 6-fold underestimate in the PM2.5 concentrations in dust events. We propose a new correction algorithm to address this problem.