Dataset Information

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.

SUBMITTER: Holder AL

PROVIDER: S-EPMC7506753 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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

Holder Amara L AL Mebust Anna K AK Maghran Lauren A LA McGown Michael R MR Stewart Kathleen E KE Vallano Dena M DM Elleman Robert A RA Baker Kirk R KR

Sensors (Basel, Switzerland) 20200825 17

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 (PM<sub>2.5</sub>) sensors with reference instruments near mul ...[more]

PMID: 32854443

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Project description:ObjectiveFinely resolved PM2.5 exposure measurements at the level of individual participants or over a targeted geographic area can be challenging due to the cost, size and weight of the monitoring equipment. We propose re-purposing the low-cost, portable and lightweight Shinyei PPD42NS particle counter as a particle counting device. Previous field deployment of this sensor suggests that it captures trends in ambient PM2.5 concentrations, but important characteristics of the sensor response have yet to be determined. Laboratory testing was undertaken in order to characterize performance.MethodsThe Shinyei sensors, in-line with a TSI Aerosol Particle Sizer (APS) model 3321, tracked particle decay within an aerosol exposure chamber. Test atmospheres were composed of monodisperse polystyrene spheres with diameters of 0.75, 1, 2 3 and 6 um as well as a polydisperse atmosphere of ASHRAE test dust #1.ResultsTwo-minute block averages of the sensor response provide a measurement with low random error, within sensor, for particles in the 0.75-6?m range with a limit of detection of 1 ?g/m3. The response slope of the sensors is idiomatic, and each sensor requires a unique response curve. A linear model captures the sensor response for concentrations below 50 ?g/m3 and for concentrations above 50 ?g/m3 a non-linear function captures the response and saturates at 800 ?g/m3. The Limit of Detection (LOD) is 1 ?g/m3. The response time is on the order of minutes, making it appropriate for tracking short-term changes in concentration.ConclusionsWhen paired with prior evaluation, these sensors are appropriate for use as ambient particle counters for low and medium concentrations of respirable particles (< 100 ug/m3). Multiple sensors deployed over a spatial grid would provide valuable spatio-temporal variability in PM2.5 and could be used to validate exposure models. When paired with GPS tracking, these devices have the potential to provide time and space resolved exposure measurements for a large number of participants, thus increasing the power of a study.

Dataset Information

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

Publications

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

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