Articles | Volume 15, issue 21
Research article
02 Nov 2022
Research article |  | 02 Nov 2022

Calibrating networks of low-cost air quality sensors

Priyanka deSouza, Ralph Kahn, Tehya Stockman, William Obermann, Ben Crawford, An Wang, James Crooks, Jing Li, and Patrick Kinney

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Cited articles

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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,, 2021. 
Bean, J. K.: Evaluation methods for low-cost particulate matter sensors, Atmos. Meas. Tech., 14, 7369–7379,, 2021. 
Bi, J., Wildani, A., Chang, H. H., and Liu, Y.: Incorporating Low-Cost Sensor Measurements into High-Resolution PM2.5 Modeling at a Large Spatial Scale, Environ. Sci. Technol., 54, 2152–2162,, 2020. 
Short summary
How sensitive are the spatial and temporal trends of PM2.5 derived from a network of low-cost sensors to the calibration adjustment used? How transferable are calibration equations developed at a few co-location sites to an entire network of low-cost sensors? This paper attempts to answer this question and offers a series of suggestions on how to develop the most robust calibration function for different end uses. It uses measurements from the Love My Air network in Denver as a test case.