Articles | Volume 14, issue 6
https://doi.org/10.5194/amt-14-4617-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-4617-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jun 2021
Research article |
| 22 Jun 2021
| 22 Jun 2021
Development and application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensor
Karoline K. Barkjohn
CORRESPONDING AUTHOR
Office of Research and Development, US Environmental Protection
Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA
Brett Gantt
Office of Air Quality Planning and Standards, US Environmental
Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA
Andrea L. Clements
Office of Research and Development, US Environmental Protection
Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA
Related authors
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Lena Francesca Weissert, Geoff Stephen Henshaw, Andrea Lee Clements, Rachelle Monique Duvall, and Carry Croghan
Atmos. Meas. Tech., 18, 3635–3645, https://doi.org/10.5194/amt-18-3635-2025, https://doi.org/10.5194/amt-18-3635-2025, 2025
Short summary
Short summary
This study evaluates a remote calibration tool, referred to as MOment MAtching (MOMA), for calibrating PurpleAir PM2.5 sensors, especially for varying PM sources, and compares it with the Environmental Protection Agency (EPA) correction. MOMA improved the accuracy of PurpleAir sensor data comparable to the EPA correction. Although reliant on nearby reference sites, MOMA offers valuable insights into potential PM sources, thereby increasing the overall value of PurpleAir sensor networks.
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Short summary
Although widely used, air sensor measurements are often biased. In this work we develop a correction with a relative humidity term that reduces the bias and improves consistency between different United States regions. This correction equation, along with proposed data cleaning criteria, has been applied to PurpleAir PM2.5 measurements across the US on the AirNow Fire and Smoke Map and has the potential to be successfully used in other air quality and public health applications.
Although widely used, air sensor measurements are often biased. In this work we develop a...
