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

Related authors

Fingerprints of the COVID-19 economic downturn and recovery on ozone anomalies at high-elevation sites in North America and western Europe
Davide Putero, Paolo Cristofanelli, Kai-Lan Chang, Gaëlle Dufour, Gregory Beachley, Cédric Couret, Peter Effertz, Daniel A. Jaffe, Dagmar Kubistin, Jason Lynch, Irina Petropavlovskikh, Melissa Puchalski, Timothy Sharac, Barkley C. Sive, Martin Steinbacher, Carlos Torres, and Owen R. Cooper
Atmos. Chem. Phys., 23, 15693–15709, https://doi.org/10.5194/acp-23-15693-2023,https://doi.org/10.5194/acp-23-15693-2023, 2023
Short summary
Constraining emissions of volatile organic compounds from western US wildfires with WE-CAN and FIREX-AQ airborne observations
Lixu Jin, Wade Permar, Vanessa Selimovic, Damien Ketcherside, Robert J. Yokelson, Rebecca S. Hornbrook, Eric C. Apel, I-Ting Ku, Jeffrey L. Collett Jr., Amy P. Sullivan, Daniel A. Jaffe, Jeffrey R. Pierce, Alan Fried, Matthew M. Coggon, Georgios I. Gkatzelis, Carsten Warneke, Emily V. Fischer, and Lu Hu
Atmos. Chem. Phys., 23, 5969–5991, https://doi.org/10.5194/acp-23-5969-2023,https://doi.org/10.5194/acp-23-5969-2023, 2023
Short summary
Intensive aerosol properties of boreal and regional biomass burning aerosol at Mt. Bachelor Observatory: larger and black carbon (BC)-dominant particles transported from Siberian wildfires
Nathaniel W. May, Noah Bernays, Ryan Farley, Qi Zhang, and Daniel A. Jaffe
Atmos. Chem. Phys., 23, 2747–2764, https://doi.org/10.5194/acp-23-2747-2023,https://doi.org/10.5194/acp-23-2747-2023, 2023
Short summary
Technical note: Use of PM2.5 to CO ratio as an indicator of wildfire smoke in urban areas
Daniel A. Jaffe, Brendan Schnieder, and Daniel Inouye
Atmos. Chem. Phys., 22, 12695–12704, https://doi.org/10.5194/acp-22-12695-2022,https://doi.org/10.5194/acp-22-12695-2022, 2022
Short summary
Comment on “Comparison of ozone measurement methods in biomass burning smoke: an evaluation under field and laboratory conditions” by Long et al. (2021)
Noah Bernays, Daniel A. Jaffe, Irina Petropavlovskikh, and Peter Effertz
Atmos. Meas. Tech., 15, 3189–3192, https://doi.org/10.5194/amt-15-3189-2022,https://doi.org/10.5194/amt-15-3189-2022, 2022
Short summary

Related subject area

Subject: Aerosols | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
Spatial analysis of PM2.5 using a concentration similarity index applied to air quality sensor networks
Rósín Byrne, John C. Wenger, and Stig Hellebust
Atmos. Meas. Tech., 17, 5129–5146, https://doi.org/10.5194/amt-17-5129-2024,https://doi.org/10.5194/amt-17-5129-2024, 2024
Short summary
Performance Evaluation of Atmotube Pro sensors for Air Quality Measurements
Aishah Shittu, Kirsty Pringle, Stephen Arnold, Richard Pope, Ailish Graham, Carly Reddington, Richard Rigby, and James McQuaid
EGUsphere, https://doi.org/10.5194/egusphere-2024-1685,https://doi.org/10.5194/egusphere-2024-1685, 2024
Short summary
A novel probabilistic source apportionment approach: Bayesian auto-correlated matrix factorization
Anton Rusanen, Anton Björklund, Manousos I. Manousakas, Jianhui Jiang, Markku T. Kulmala, Kai Puolamäki, and Kaspar R. Daellenbach
Atmos. Meas. Tech., 17, 1251–1277, https://doi.org/10.5194/amt-17-1251-2024,https://doi.org/10.5194/amt-17-1251-2024, 2024
Short summary
Towards a hygroscopic growth calibration for low-cost PM2.5 sensors
Milan Y. Patel, Pietro F. Vannucci, Jinsol Kim, William M. Berelson, and Ronald C. Cohen
Atmos. Meas. Tech., 17, 1051–1060, https://doi.org/10.5194/amt-17-1051-2024,https://doi.org/10.5194/amt-17-1051-2024, 2024
Short summary
Enhancing characterization of organic nitrogen components in aerosols and droplets using high-resolution aerosol mass spectrometry
Xinlei Ge, Yele Sun, Justin Trousdell, Mindong Chen, and Qi Zhang
Atmos. Meas. Tech., 17, 423–439, https://doi.org/10.5194/amt-17-423-2024,https://doi.org/10.5194/amt-17-423-2024, 2024
Short summary

Cited articles

Ardon-Dryer, K., Dryer, Y., Williams, J. N., and Moghimi, N.: Measurements of PM2.5 with PurpleAir under atmospheric conditions, Atmos. Meas. Tech., 13, 5441–5458, https://doi.org/10.5194/amt-13-5441-2020, 2020. 
Barkjohn, K. K., Gantt, B., and Clements, A. L.: Development and application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensor, Atmos. Meas. Tech., 14, 4617–4637, https://doi.org/10.5194/amt-14-4617-2021, 2021. 
Borlina, C. S. and Rennó, N. O.: The impact of a severe drought on dust lifting in California's Owens Lake area, Sci. Rep.​​​​​​​, 7, 1784, https://doi.org/10.1038/s41598-017-01829-7, 2017. 
Cahill, T. A., Gill, T. E., Reid, J. S., Gearhart, E. A., and Gillette, D. A.: Saltating particles, playa crusts and dust aerosols at Owens (Dry) Lake, California, Earth Surf. Proc. Land., 21, 7, 621–639, https://doi.org/10.1002/(SICI)1096-9837(199607)21:7<621::AID-ESP661>3.0.CO;2-E, 1996. 
Euphrasie-Clotilde, L., Plocoste, T., and Brute, F.-N.: Particle size analysis of African dust haze over the last 20 years: a focus on the extreme event of June 2020, Atmosphere, 12, 502, https://doi.org/10.3390/atmos12040502, 2021. 
Download
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.