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. 2022 Apr 2;22(7):2755.
doi: 10.3390/s22072755.

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

Lance Wallace  1
Affiliations

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

Lance Wallace. Sensors (Basel). .

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 concentrations provided by the sensor manufacturers accurate? We investigate these questions using continuous measurements of four PurpleAir 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 algorithms (CF1 and CF_ATM) provided by the Plantower manufacturer of the PMS 5003 sensors used in PurpleAir PA-II monitors. Results. The Plantower CF1 algorithm lost 25-50% of all indoor data due in part to the practice of assigning zero to all concentrations below a threshold. None of these data were lost using the ALT-CF3 algorithm. Approximately 92% of all data showed precision better than 20% using the ALT-CF3 algorithm, but only approximately 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 µg/m3, compared to approximately 3-10 µg/m3 using the Plantower CF1 algorithm. The percentage of observations exceeding the LOD was 53-92% for the ALT-CF3 algorithm, but only 16-44% for the Plantower CF1 algorithm. At the low indoor PM2.5 concentrations found in many homes, the Plantower algorithms appear poorly suited.

Keywords: ALT-CF3; CF1; PM2.5; PMS-5003 sensors; Plantower; PurpleAir; limit of detection; low-cost particle monitors; precision.

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Conflict of interest statement

The author declares no conflict of interest.

Figures

Figure 1
Figure 1
Indoor and outdoor PM2.5 concentrations (N = 353,256) over 18 months using the ALT-CF3 algorithm. The three middle points centered on the median at 0 provide the interquartile range (25th and 75th percentiles).
Figure 2
Figure 2
Same observations as in Figure 1 using the Plantower CF1 algorithm. Many measurements have been assigned a value of zero and cannot be shown on the logarithmic graph.
Figure 3
Figure 3
Total observations remaining after applying an upper precision limit of 0.2 (20%).
Figure 4
Figure 4
Percent of observations exceeding the LOD compared for the ALT-CF3 and Plantower CF1 algorithms. Monitor/Location shown on x-axis.
Figure 5
Figure 5
Ratios of the ALT-CF3 and Plantower CF1 PM2.5 estimates with the co-located SidePak estimates for 17 sources. Error bars are propagated standard errors.
See this image and copyright information in PMC

References

    1. AQ-SPEC Field Evaluation Purple Air PM Sensor. [(accessed on 30 March 2022)];2016 Available online: http://www.aqmd.gov/docs/default-source/aq-spec/field-evaluations/purple....
    1. He M., Kuerbanjiang N., Dhaniyala S. Performance characteristics of the low-cost Plantower PMS optical sensor. Aerosol Sci. Technol. 2020;54:232–241. doi: 10.1080/02786826.2019.1696015. - DOI
    1. Kelly K.E., Whitaker J., Petty A., Widmer C., Dybwad A., Sleeth D., Martin R., Butterfield A. Ambient and laboratory evaluation of a low-cost particulate matter sensor. Environ. Pollut. 2017;221:491–500. doi: 10.1016/j.envpol.2016.12.039. - DOI - PMC - PubMed
    1. Singer B.C., Delp W.W. Response of consumer and research grade indoor air quality monitors to residential sources of fine particles. Indoor Air. 2018;28:624–639. doi: 10.1111/ina.12463. - DOI - PubMed
    1. Tryner J., Quinn C., Windom B.C., Volckens J. Design and evaluation of a portable PM2.5 monitor featuring a low-cost sensor in line with an active filter sampler. Environ. Sci. Process. Impacts. 2019;21:1403–1415. doi: 10.1039/C9EM00234K. - DOI - PubMed