Design and evaluation of a portable PM_2.5 monitor featuring a low-cost sensor in line with an active filter sampler

Abstract

Measurement of particulate matter (PM) air pollution using a low-cost sensor and in-line filter sample enables gravimetric correction of the real-time PM data and chemical characterization of the collected PM.

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

“…A best practice is to locate air sensors alongside regulatory air monitors to understand their local performance and to develop corrections for each individual sensor (Jiao et al, 2016;Johnson et al, 2018;Zusman et al, 2020). For optical particulate matter (PM) sensors, correction procedures are often needed due to 1) the changing optical properties of aerosols associated with both their physical and chemical characteristics (Levy Zamora et al, 2019;Tryner et al, 2019) and the local meteorological conditions including temperature and relative humidity (RH) (Jayaratne et al, 2018;Zheng et al, 2018) and 2) some models of air sensors having out of the box differences and low precision between sensors of the same model (Feenstra et al, 2019;Feinberg et al, 2018). Although collocation and local correction may be achievable for researchers and some air monitoring agencies, it is unattainable for many sensor users and community groups due to lack of access to regulatory monitoring sites.…”

“…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).…”

Bayesian nonparametric monotone regression

“…We use data from 12 samples collected using three MARS devices during four laboratory experiments. These experiments are described in detail by Tryner et al (2019). During each experiment, one of four different types of aerosol—urban PM (NIST SRM 1648A Urban PM), ammonium sulfate ((NH 4 ) 2 SO 4 ), Arizona road dust, or match smoke—is nebulized into a controlled chamber containing all three MARS.…”

“…In this article we consider inference for data generated by the recently developed Mobile Aerosol Reference Sampler (MARS). MARS was designed to be an affordable, portable monitor for measuring fine particulate matter (PM 2.5 ) concentrations in environmental and occupational health studies (Tryner, Quinn, Windom, & Volckens, 2019). The MARS device is built on the Ultrasonic Personal Aerosol Sampler (UPAS) platform, which has also been previously described in the literature (Volckens et al, 2017).…”

Miniature Optical Particle Counter and Analyzer Involving a Fluidic-Optronic CMOS Chip Coupled with a Millimeter-Sized Glass Optical System

“…An inertial element can filter PM 2.5 from PM 10 before the optical sensing stage [ 36 ]. For instance, this can be achieved by fluidic devices like cyclones [ 37 ] or Virtual Impactors (VI) [ 38 ].…”