Calibration of PurpleAir PA-I and PA-II Monitors Using Daily Mean PM2.5 Concentrations Measured in California, Washington, and Oregon from 2017 to 2021

Sensors (Basel). 2022 Jun 23;22(13):4741. doi: 10.3390/s22134741.

Abstract

Large quantities of real-time particle data are becoming available from low-cost particle monitors. However, it is crucial to determine the quality of these measurements. The largest network of monitors in the United States is maintained by the PurpleAir company, which offers two monitors: PA-I and PA-II. PA-I monitors have a single sensor (PMS1003) and PA-II monitors employ two independent PMS5003 sensors. We determine a new calibration factor for the PA-I monitor and revise a previously published calibration algorithm for PA-II monitors (ALT-CF3). From the PurpleAir API site, we downloaded 83 million hourly average PM2.5 values in the PurpleAir database from Washington, Oregon, and California between 1 January 2017 and 8 September 2021. Daily outdoor PM2.5 means from 194 PA-II monitors were compared to daily means from 47 nearby Federal regulatory sites using gravimetric Federal Reference Methods (FRM). We find a revised calibration factor of 3.4 for the PA-II monitors. For the PA-I monitors, we determined a new calibration factor (also 3.4) by comparing 26 outdoor PA-I sites to 117 nearby outdoor PA-II sites. These results show that PurpleAir PM2.5 measurements can agree well with regulatory monitors when an optimum calibration factor is found.

Keywords: ALT-CF3; PM2.5; PMS1003; PMS5003; PurpleAir; algorithm; calibration factor; low-cost particle monitors; particles; sensors.

MeSH terms

  • Air Pollutants* / analysis
  • Air Pollution* / analysis
  • Calibration
  • California
  • Environmental Monitoring / methods
  • Oregon
  • Particulate Matter / analysis
  • Washington

Substances

  • Air Pollutants
  • Particulate Matter

Grants and funding

This research received no external funding.