Field Evaluation of Low-Cost Particulate Matter Sensors for Measuring Wildfire Smoke

Abstract

Until recently, air quality impacts from wildfires were predominantly determined based on data from permanent stationary regulatory air pollution monitors. However, low-cost particulate matter (PM) sensors are now widely used by the public as a source of air quality information during wildfires, although their performance during smoke impacted conditions has not been thoroughly evaluated. We collocated three types of low-cost fine PM (PM2.5) sensors with reference instruments near multiple fires in the western and eastern United States (maximum hourly PM2.5 = 295 µg/m3). Sensors were moderately to strongly correlated with reference instruments (hourly averaged r2 = 0.52–0.95), but overpredicted PM2.5 concentrations (normalized root mean square errors, NRMSE = 80–167%). We developed a correction equation for wildfire smoke that reduced the NRMSE to less than 27%. Correction equations were specific to each sensor package, demonstrating the impact of the physical configuration and the algorithm used to translate the size and count information into PM2.5 concentrations. These results suggest the low-cost sensors can fill in the large spatial gaps in monitoring networks near wildfires with mean absolute errors of less than 10 µg/m3 in the hourly PM2.5 concentrations when using a sensor-specific smoke correction equation.

Development and Application of a United States wide correction for PM<sub>2.5</sub> data collected with the PurpleAir sensor

“…The low cost of outdoor PurpleAir sensors ($230-$260 U.S. dollars) has enabled them to be widely used with thousands of sensors publicly reporting across the U.S. Previous work has explored the performance and accuracy of the PurpleAir sensors (Magi et al, 2019;Feenstra et al, 2019;Mehadi et al, 2019;Malings et al, 2019;Kim et al, 2019;Sayahi et al, 2019;Tryner et al, 2020a;Singer and Delp, 2018;Kelly et al, 2017;Li et al, 2020;Wang et al, 2020b;Gupta et al, 2018;Delp and Singer, 2020;Zou et al, 2020b;Stavroulas et al, 2020;Holder et al, 2020;Ardon-Dryer et al, 2020;Schulte et al, 2020;Zou et al, 2020a;Robinson, 2020;Bi et al, 2020) and their dual Plantower PMS5003 laser scattering particle sensors (He et al, 2020;Tryner et al, 2019;Kuula et al, 2019;Ford et al, 2019;Si et al, 2020;Zou et al, 2020b;Tryner et al, 2020b). Although not true of all types of PM2.5 sensors, previous work with PurpleAir sensors and other models of Plantower sensors have shown that the sensors are precise, with sensors of the same model measuring similar PM2.5 concentrations (Barkjohn et al, 2020a;Pawar and Sinha, 2020;Malings et al, 2019).…”

Long-term air pollution and other risk factors associated with COVID-19 at the census-tract-level in Colorado

“…However, as these surfaces are updated for additional years, we are optimistic that non-regulatory monitors such as those used in the LoveMyAir network in Denver (DDPHE, 2020) or by PurpleAir (PurpleAir, 2020) will allow such an independent comparison to be made. Recent work to calibrate these monitors under a variety of conditions is another crucial step before these sensors can be used to check the performance of PM2.5 models (Holder et al, 2020; Considine et al, 2021). At the moment, without the ability to independently measure the error in the PM2.5 surfaces, it is impossible to identify which surfaces are most accurate in Colorado.…”

Improving the Indoor Air Quality of Residential Buildings during Bushfire Smoke Events

“…Low-cost particle sensors typically use light scattering techniques to count and determine particle size. However, there is inadequate information about the accuracy of low-cost sensors, particularly on how they perform under conditions of heavy smoke [54]. Furthermore, limited performance information is provided by the manufacturers of the sensors.…”

“…The authors conclude that even though the adjustment factor can vary according to location and over time during a fire event, a global adjustment factor can reduce bias significantly. Holder et al [54] collated three types of low-cost fine PM2.5 sensors with reference instruments during a number of fire events and found moderate to strong correlation with reference instruments, however the sensors overpredicted PM2.5 concentrations (with normalized root mean square errors = 80-167%). The authors developed different correction equations for each sensor.…”

“…It was also found that sensor performance was sensitive to the composition of smoke. Holder et al [54] noted that further monitoring and comparison studies focusing on higher particle concentrations are required as optical-based sensors can saturate when the concentrations are very high.…”