Testing a New “Decrypted” Algorithm for Plantower Sensors Measuring PM2.5: Comparison with an Alternative Algorithm

• Published in: Algorithms Vol. 16; no. 8; p. 392
• Main Author: Wallace, Lance
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2023
• Subjects: Accuracy; Aerosols; algorithm; Algorithms; calibration; Datasets; Humidity; Hypotheses; Laboratories; low-cost monitors; Monitors; Outdoor air quality; PM2.5; precision; Sensors; United States > US; California
• ISSN: 1999-4893; 1999-4893
• DOI: 10.3390/a16080392

Recently, a hypothesis providing a detailed equation for the Plantower CF_1 algorithm for PM2.5 has been published. The hypothesis was originally validated using eight independent Plantower sensors in four PurpleAir PA-II monitors providing PM2.5 estimates from a single site in 2020. If true, the hypothesis makes important predictions regarding PM2.5 measurements using CF_1. Therefore, we test the hypothesis using 18 Plantower sensors from four datasets from two sites in later years (2021–2023). The four general models from these datasets agreed to within 10% with the original model. A competing algorithm known as “pm2.5 alt” has been published and is freely available on the PurpleAir API site. The accuracy, precision, and limit of detection for the two algorithms are compared. The CF_1 algorithm overestimates PM2.5 by about 60–70% compared to two calibrated PurpleAir monitors using the pm2.5 alt algorithm. A requirement that the two sensors in a single monitor agree to within 20% was met by 85–99% of the data using the pm2.5 alt algorithm, but by only 22–74% of the data using the CF_1 algorithm. The limit of detection (LOD) of the CF_1 algorithm was about 10 times the LOD of the pm2.5 alt algorithm, resulting in 71% of the CF_1 data falling below the LOD, compared to 1 % for the pm2.5 alt algorithm.