Articles | Volume 16, issue 5
https://doi.org/10.5194/amt-16-1311-2023
© Author(s) 2023. 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-16-1311-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Mar 2023
Research article |
| 13 Mar 2023
| 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
School of STEM, University of Washington Bothell, Bothell, WA 98011, USA
Department of Atmospheric Sciences, University of Washington, Seattle, WA 98195, USA
Colleen Miller
School of STEM, University of Washington Bothell, Bothell, WA 98011, USA
now at: Department of Chemistry, University of California, Irvine, Irvine, CA 92697, USA
Katie Thompson
School of STEM, University of Washington Bothell, Bothell, WA 98011, USA
Brandon Finley
School of STEM, University of Washington Bothell, Bothell, WA 98011, USA
Manna Nelson
Department of Civil and Environmental Engineering, Seattle University, Seattle, WA 98122, USA
James Ouimette
independent researcher: Santa Rosa, CA 95409, USA
Elisabeth Andrews
NOAA Global Monitoring Laboratory, Boulder, CO 80305, USA
Cooperative Institute for Research in Environmental Sciences,
University of Colorado Boulder, Boulder, CO 80309, USA
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Cited
13 citations as recorded by crossref.
- Dust Under the Radar: Rethinking How to Evaluate the Impacts of Dust Events on Air Quality in the United States K. Ardon‐Dryer et al. 10.1029/2023GH000953
- Exploration of intra-city and inter-city PM2.5 regional calibration models to improve low-cost sensor performance S. Jain & N. Zimmerman 10.1016/j.jaerosci.2024.106335
- Spatial Variation of PM2.5 Indoors and Outdoors: Results from 261 Regulatory Monitors Compared to 14,000 Low-Cost Monitors in Three Western States over 4.7 Years L. Wallace & T. Zhao 10.3390/s23094387
- Atmospheric heating in the US from saharan dust: Tracking the June 2020 event with surface and satellite observations M. Mehra et al. 10.1016/j.atmosenv.2023.119988
- Indication Variability of the Particulate Matter Sensors Dependent on Their Location A. Wiora et al. 10.3390/s24051683
- Infiltration of Outdoor PM2.5 Pollution into Homes with Evaporative Coolers in Utah County D. Sonntag et al. 10.3390/su16010177
- Highly Time-Resolved Apportionment of Carbonaceous Aerosols from Wildfire Using the TC–BC Method: Camp Fire 2018 Case Study M. Ivančič et al. 10.3390/toxics11060497
- Seasonally optimized calibrations improve low-cost sensor performance: long-term field evaluation of PurpleAir sensors in urban and rural India M. Campmier et al. 10.5194/amt-16-4357-2023
- Five Years of Accurate PM2.5 Measurements Demonstrate the Value of Low-Cost PurpleAir Monitors in Areas Affected by Woodsmoke D. Robinson et al. 10.3390/ijerph20237127
- Technical note: Identifying a performance change in the Plantower PMS 5003 particulate matter sensor N. Searle et al. 10.1016/j.jaerosci.2023.106256
- Fundamentals of low-cost aerosol sensor design and operation J. Ouimette et al. 10.1080/02786826.2023.2285935
- Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire Smoke K. Barkjohn et al. 10.3390/s22249669
- Size-Resolved Field Performance of Low-Cost Sensors for Particulate Matter Air Pollution E. Molina Rueda et al. 10.1021/acs.estlett.3c00030
11 citations as recorded by crossref.
- Dust Under the Radar: Rethinking How to Evaluate the Impacts of Dust Events on Air Quality in the United States K. Ardon‐Dryer et al. 10.1029/2023GH000953
- Exploration of intra-city and inter-city PM2.5 regional calibration models to improve low-cost sensor performance S. Jain & N. Zimmerman 10.1016/j.jaerosci.2024.106335
- Spatial Variation of PM2.5 Indoors and Outdoors: Results from 261 Regulatory Monitors Compared to 14,000 Low-Cost Monitors in Three Western States over 4.7 Years L. Wallace & T. Zhao 10.3390/s23094387
- Atmospheric heating in the US from saharan dust: Tracking the June 2020 event with surface and satellite observations M. Mehra et al. 10.1016/j.atmosenv.2023.119988
- Indication Variability of the Particulate Matter Sensors Dependent on Their Location A. Wiora et al. 10.3390/s24051683
- Infiltration of Outdoor PM2.5 Pollution into Homes with Evaporative Coolers in Utah County D. Sonntag et al. 10.3390/su16010177
- Highly Time-Resolved Apportionment of Carbonaceous Aerosols from Wildfire Using the TC–BC Method: Camp Fire 2018 Case Study M. Ivančič et al. 10.3390/toxics11060497
- Seasonally optimized calibrations improve low-cost sensor performance: long-term field evaluation of PurpleAir sensors in urban and rural India M. Campmier et al. 10.5194/amt-16-4357-2023
- Five Years of Accurate PM2.5 Measurements Demonstrate the Value of Low-Cost PurpleAir Monitors in Areas Affected by Woodsmoke D. Robinson et al. 10.3390/ijerph20237127
- Technical note: Identifying a performance change in the Plantower PMS 5003 particulate matter sensor N. Searle et al. 10.1016/j.jaerosci.2023.106256
- Fundamentals of low-cost aerosol sensor design and operation J. Ouimette et al. 10.1080/02786826.2023.2285935
Latest update: 19 Apr 2024
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.
PurpleAir sensors (PASs) are low-cost tools to measure fine particulate matter (PM)...
