Stationary and portable multipollutant monitors for high-spatiotemporal-resolution air quality studies including online calibration

Authors

Colby Buehler, Department of Chemical & Environmental Engineering, Yale University, School of Engineering and Applied Science
Fulizi Xiong, Department of Chemical & Environmental Engineering, Yale University, School of Engineering and Applied Science
Misti Levy Zamora, SEARCH (Solutions for Energy, Air, Climate and Health) Center, Yale University
Kate M. Skog, Department of Chemical & Environmental Engineering, Yale University, School of Engineering and Applied Science
Joseph Kohrman-Glaser, Department of Mechanical Engineering, Yale University, School of Engineering and Applied Science
Stefan Colton, Department of Mechanical Engineering, Yale University, School of Engineering and Applied Science
Michael McNamara, Department of Electrical Engineering, Yale University, School of Engineering and Applied Science
Kevin Ryan, Department of Electrical Engineering, Yale University, School of Engineering and Applied Science
Carrie Redlich, Department of Internal Medicine, Yale University, School of Medicine
Matthew Bartos, Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Cockrell School of Engineering
Brandon Wong, Civil and Environmental Engineering, University of Michigan
Branko Berkez, Civil and Environmental Engineering, University of Michigan
Kirsten Koehler, SEARCH (Solutions for Energy, Air, Climate and Health) Center, Yale University
Drew R. Gentner, Department of Chemical & Environmental Engineering, Yale University, School of Engineering and Applied Science

Abstract

The distribution and dynamics of atmospheric pollutants are spatiotemporally heterogeneous due to variability in emissions, transport, chemistry, and deposition. To understand these processes at high spatiotemporal resolution and their implications for air quality and personal exposure, we present custom, low-cost air quality monitors that measure concentrations of contaminants relevant to human health and climate, including gases (e.g., O3, NO, NO2, CO, CO2, CH4, and SO2) and size-resolved (0.3–10 μm) particulate matter. The devices transmit sensor data and location via cellular communications and are capable of providing concentration data down to second-level temporal resolution. We produce two models: one designed for stationary (or mobile platform) operation and a wearable, portable model for directly measuring personal exposure in the breathing zone. To address persistent problems with sensor drift and environmental sensitivities (e.g., relative humidity and temperature), we present the first online calibration system designed specifically for low-cost air quality sensors to calibrate zero and span concentrations at hourly to weekly intervals. Monitors are tested and validated in a number of environments across multiple outdoor and indoor sites in New Haven, CT; Baltimore, MD; and New York City. The evaluated pollutants (O3, NO2, NO, CO, CO2, and PM2.5) performed well against reference instrumentation (e.g., r = 0.66–0.98) in urban field evaluations with fast e-folding response times (≤1 min), making them suitable for both large-scale network deployments and smaller-scale targeted experiments at a wide range of temporal resolutions. We also provide a discussion of best practices on monitor design, construction, systematic testing, and deployment.

Publication Status

Published

Category Tags

Air Quality; Pollution

New Haven Neighborhood

Downtown

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