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PurpleAir PM2.5 Performance Across the U.S.
Citation:
Johnson, K., B. Gantt, I. VonWald, AND A. Clements. PurpleAir PM2.5 Performance Across the U.S. Webinar Presentation with State/Local/Tribal Project Partners, RTP, NC, December 09, 2019.
Impact/Purpose:
Interest and concern about air quality has grown in recent years. Simultaneously, growth in the popularity and use of air sensors across the US has also occurred. However, adoption of this technology is limited due to uncertainty and variation in the quality of the data provided. This work evaluates the performance of a popular low-cost PM2.5 sensor (PurpleAir) across the U.S.. This presentation will inform state/local/tribal agencies, who are partners on this project, about our work and findings to date.
Description:
PurpleAir sensors are widely used by individuals, community groups, and other organizations including air monitoring agencies. Previous performance evaluations have studied a limited number of PurpleAir sensors in select geographic areas or laboratory environments; these results may not be translatable to areas with different environmental conditions, varying aerosol compositions or a wider range of concentrations. Here, we evaluate the performance of PurpleAir sensors operated by air monitoring agencies and collocated with regulatory-grade monitoring instruments, at monitoring sites across the United States. In total, >12,000 24-hour averaged collocated PurpleAir and Federal Reference Method (FRM) or Federal Equivalent Method (FEM) measurements were identified across diverse regions of the US, including 14 states (AK, AZ, CA, DE, CO, FL, GA, IA, KS, NC, OK, VT, WA, and WI). Performance based on 1) the raw data, 2) a simple U.S. linear correction, and 3) a multi-linear regression including temperature and relative humidity (RH) has been considered for 24-hour averaged data. Preliminary results suggest that the PurpleAir original PM2.5 data output overestimates PM2.5 by ~60% in most states. For some states, where bias remains after applying a linear correction, a correction including temperature and RH reduces the remaining bias. An evaluation of daily Air Quality Index (AQI) category derived using the raw and corrected PurpleAir PM2.5 compared to the AQI from regulatory data is also presented. The results are synthesized to determine the feasibility of a broadly-applicable correction equation that could be applied to PurpleAir reported values.