Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Intercomparison Of PurpleAir Sensor Performance Over Three Years Indoors and Outdoors at a Home: Bias, Precision, and Limit of Detection Using an Improved Algorithm for Calculating PM2.5

Version 1 : Received: 5 February 2022 / Approved: 9 February 2022 / Online: 9 February 2022 (15:04:56 CET)

A peer-reviewed article of this Preprint also exists.

Wallace, L. Intercomparison of PurpleAir Sensor Performance over Three Years Indoors and Outdoors at a Home: Bias, Precision, and Limit of Detection Using an Improved Algorithm for Calculating PM2.5. Sensors 2022, 22, 2755. Wallace, L. Intercomparison of PurpleAir Sensor Performance over Three Years Indoors and Outdoors at a Home: Bias, Precision, and Limit of Detection Using an Improved Algorithm for Calculating PM2.5. Sensors 2022, 22, 2755.

Journal reference: Sensors 2022, 22, 2755
DOI: 10.3390/s22072755

Abstract

Low-cost particle sensors are now used worldwide to monitor outdoor air quality. However, they have only been in wide use for a few years. Are they reliable? Does their performance deteriorate over time? Are the algorithms for calculating PM2.5 provided by the Plantower company for PurpleAir monitors accurate? We investigate these questions using continuous measurements of four monitors (8 sensors) under normal conditions inside and outside a home for 1.5-3 years. A recently-developed algorithm (called ALT-CF3) is compared to the two existing Plantower algorithms. The Plantower CF1 algorithm was shown to lose 25-50% of all indoor data due to the questionable practice of assigning zero to all concentrations below a threshold. None of these data were lost using the ALT-CF3 algorithm. About 92% of all data showed precision better than 20% using the ALT-CF3 algorithm, but only about 45-75% of data achieved that level using the Plantower CF1 algorithm. The limits of detection (LODs) using the ALT-CF3 algorithm were mostly under 1 ug/m3, compared to about 3-10 ug/m3 using the Plantower CF1 algorithm. The percent of observations exceeding the LOD was 53-92% for the ALT-CF3 algorithm, but only 16-44% for the Plantower CF1 algorithm. For indoor air in homes, the Plantower algorithms are inappropriate.

Keywords

low-cost particle monitors; PurpleAir: PM2.5; bias; precision; limit of detection; Plantower; PMS-5003 sensors

Subject

EARTH SCIENCES, Environmental Sciences

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