Articles | Volume 17, issue 3
https://doi.org/10.5194/amt-17-1051-2024
https://doi.org/10.5194/amt-17-1051-2024
Research article
 | 
13 Feb 2024
Research article |  | 13 Feb 2024

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

Data sets

Datasets Used in this Work Milan Y. Patel https://github.com/milan-y-patel/Plantower-Calibration-Paper

Model code and software

Example Code for the Calibration Developed in this Work Milan Y. Patel https://github.com/milan-y-patel/Plantower-Calibration-Paper

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Short summary
Low-cost particulate matter (PM) sensors are becoming increasingly common in community monitoring and atmospheric research, but these sensors require proper calibration to provide accurate reporting. Here, we propose a hygroscopic growth calibration scheme that evolves in time to account for seasonal changes in hygroscopic growth. In San Francisco and Los Angeles, CA, applying a seasonal hygroscopic growth calibration can account for sensor biases driven by the seasonal cycles in PM composition.