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Performance Evaluations of Six PM2.5 Sensors in Research Triangle Park, NC
Citation:
Frederick, S., K. Johnson, C. Johnson, R. Yaga, AND A. Clements. Performance Evaluations of Six PM2.5 Sensors in Research Triangle Park, NC. Air Sensors International Conference, Pasadena, CA, May 12 - 15, 2020.
Impact/Purpose:
In recent years, interest and concern about air quality has grown alongside the increasing popularity and use of air sensors across the United States. Despite increased interest in this technology, its adoption remains limited due to uncertainty and variation in the quality of data produced by various sensor models and among individual sensors of the same model. This work evaluates numerous low-cost air quality sensors at the Ambient Air Innovation Research Site (AIRS) in Research Triangle Park, North Carolina to determine the accuracy and precision of pollutant data for individual devices within sensor models. This work seeks to provide meaningful information regarding the reliability of low-cost air sensor data when compared to regulatory methods. This abstract is for a poster presentation which will be on display to attendees of the Air Sensor International Conference located in Pasadena, CA in May 2020.
Description:
In recent years, numerous low-cost air quality sensors have emerged which offer consumers increasing access to higher spatially and temporally resolved measurements of air pollutants while encouraging scientific engagement. These devices often measure multiple pollutants, adding both to their potential usefulness and complexity. With new devices constantly entering the market, the prospect of their wide adoption necessitates evaluation of sensor performance and accuracy. This work summarizes the results for evaluations of several low-cost air quality devices at the Ambient Air Innovation Research Site (AIRS) in Research Triangle Park, North Carolina. At least three of each sensor model were deployed simultaneously in order to evaluate precision between sensors of the same type. Sensor measurements at 1-hour averages were analyzed for accuracy against government monitors, and pollutants evaluated include PM1, PM2.5, PM10, O3, NO2, and CO. The influence of environmental conditions, including temperature and relative humidity, have been explored. These results provide valuable information regarding the reliability of low-cost air sensor data when compared to regulatory methods.