Feasibility of Low-Cost Particle Sensor Types in Long-Term Indoor Air Pollution Health Studies After Repeated Calibration Over a 2-Year Timeframe

Abstract

Background Previous studies have explored using calibrated low-cost particulate matter (PM) sensors, but important research gaps remain regarding long-term performance and reliability. Objective Evaluate longitudinal performance of low-cost particle sensors by measuring sensor performance changes over 2 years of use. Methods 51 low-cost particle sensors (Airbeam 1 N=29; Airbeam 2 N=22) were calibrated four times over a 2-year timeframe between 2019-2021. 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. Results 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, failure rate 48.2%) than Airbeam 2 (N=2, failure rate 16.7%) due to electronics, battery, or data output issues. Conclusions 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.