Feasibility of low-cost particle sensor types in long-term indoor air pollution health studies after repeated calibration, 2019-2021.

Autor: Anastasiou E; Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA., Vilcassim MJR; Department of Environmental Health Sciences, University of Alabama at Birmingham School of Public Health, Birmingham, AL, 205-934-8927, USA., Adragna J; Department of Environmental Science, New York University Grossman School of Medicine, 341 East 25th Street, New York, NY, 10010, USA., Gill E; Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA., Tovar A; Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA., Thorpe LE; Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, New York, NY, 10016, USA., Gordon T; Department of Environmental Science, New York University Grossman School of Medicine, 341 East 25th Street, New York, NY, 10010, USA. terry.gordon@nyulangone.org.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2022 Aug 26; Vol. 12 (1), pp. 14571. Date of Electronic Publication: 2022 Aug 26.
DOI: 10.1038/s41598-022-18200-0
Abstrakt: Previous studies have explored using calibrated low-cost particulate matter (PM) sensors, but important research gaps remain regarding long-term performance and reliability. Evaluate longitudinal performance of low-cost particle sensors by measuring sensor performance changes over 2 years of use. 51 low-cost particle sensors (Airbeam 1 N = 29; Airbeam 2 N = 22) were calibrated four times over a 2-year timeframe between 2019 and 2021. Cigarette smoke-specific calibration curves for Airbeam 1 and 2 PM sensors were created by directly comparing simultaneous 1-min readings of a Thermo Scientific Personal DataRAM PDR-1500 unit with a 2.5 µm inlet. Inter-sensor variability in calibration coefficient was high, particularly in Airbeam 1 sensors at study initiation. Calibration coefficients for both sensor types trended downwards over time to < 1 at final calibration timepoint [Airbeam 1 Mean (SD) = 0.87 (0.20); Airbeam 2 Mean (SD) = 0.96 (0.27)]. We lost more Airbeam 1 sensors (N = 27 out of 56, failure rate 48.2%) than Airbeam 2 (N = 2 out of 24, failure rate 8.3%) due to electronics, battery, or data output issues. Evidence suggests degradation over time might depend more on particle sensor type, rather than individual usage. Repeated calibrations of low-cost particle sensors may increase confidence in reported PM levels in longitudinal indoor air pollution studies.
(© 2022. The Author(s).)
Databáze: MEDLINE
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