You are here:
Evaluation of AQY1 Sensors and Implications for Community-led Projects
Citation:
Stratton, J., J. Barone, N. Kaltenhauser, D. Druckenbrod, R. Leta-Graham, L. Lim, O. Boyko, J. Munyan, K. Barkjohn, S. Frederick, AND A. Clements. Evaluation of AQY1 Sensors and Implications for Community-led Projects. Air sensor international conference, Pasadena, California, May 11 - 13, 2022.
Impact/Purpose:
Air sensors have grown in popularity in recent years. They have the potential to provide more spatially dense measurement than conventional monitors. However, to gather accurate data co-location with conventional air monitors, correction of bias, and other quality assurance methods are often needed. In this project a network of air sensors was deployed across the Rider University Campus by undergraduate students to identify potential hotspots across campus. The project explores the accuracy of the AQY sensors, highlights the potential utility of these sensors for community air monitoring, and what resources may be needed from nontechnical users operating air sensor projects. This abstract is for a presentation that will be presented to attendees of the Air Sensor International Conference May 11-13, 2022 in Pasadena, CA.
Description:
While access to lower-cost sensors has greatly increased over the last decade, questions remain about their reliability for community-led projects. This study aimed to compare Aeroqual’s AQY1 sensors (n=6) with state operated real time ozone (O3) (ultraviolet absorption), nitrogen dioxide (NO2) (chemiluminescence) and fine particulate matter (PM2.5) monitors (beta-attenuation) under real-world conditions in New Jersey (USA). Aeroqual AQY1 sensors were evaluated to understand their potential for community-led hotspot monitoring projects utilizing high-time-resolution data (<60 min averages). Undergraduate students operated, maintained, and analyzed the data from these sensors as part of a larger project to understand potential pollutant hotspots around campus. During collocation, AQY1 O3 concentrations were correlated (R2 = 0.62-0.82) with the reference monitor concentrations (monitor mean =33 ppb and maximum = 80 ppb) but were largely underestimated (slope = 0.22-0.29). NO2 concentrations were low (monitor mean = 8 ppb and maximum = 25 ppb) with little correlation between sensors and the reference monitor. NO2 measurements were found to exhibit a dependence on relative humidity and a shifting response over the study period. A calibration from this study period corrected for large underestimations of O3, but NO2 remained inaccurate. O3 and PM2.5 measurements show promise for community-led projects based on the accuracy following correction. However, data correction, harmonization, and interpretation will likely require some significant amount of effort from community groups likely necessitating partnerships with local air monitoring agencies and EPA regional offices. Disclaimer: Although this abstract was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.