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Communicating Air Sensor Data on the AirNow Fire and Smoke map
Citation:
Barkjohn, K., A. Holder, A. Clements, S. Frederick, R. Evans, AND S. Larkin. Communicating Air Sensor Data on the AirNow Fire and Smoke map. Air sensor international conference, Pasadena, California, May 11 - 13, 2022.
Impact/Purpose:
Interest and concern about air quality has grown in recent years especially during wildfires. Simultaneously, growth in the popularity and use of air sensors across the US has also occurred. However, with so many sources of sensor and governmental data it can be challenging for users to interpret. In this presentation we will share the methods behind incorporating the PurpleAir sensor data on the AirNow Fire and Smoke map, how this map is used to convey important information to the public, and how the map can be used to reduce smoke exposure. 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 in the Communication Strategies for Understanding, Insight, and Action session.
Description:
Residents and local agencies in smoke impacted areas often use air sensors to provide more localized air quality data. In 2020, air sensor measurements were added to the AirNow Fire and Smoke map. Alongside permanent and temporary smoke monitor measurements, PurpleAir sensor measurements now appear as “Low Cost Sensor” icons. Monitor and sensor icons appear on the map as distinct shapes colored by NowCast AQI category. Clicking on an icon provides information on particulate matter concentrations at various averaging intervals, trends based on the past 30 minutes of air sensor data, and recommendations for health protective actions. Before sensor data is displayed on the map, PurpleAir sensor measurements are corrected and cleaned, resulting in higher accuracy measurements and improved category estimation for the NowCast AQI. However, the uncertainty in the sensor, temporary monitor, and stationary monitor measurements is variable and dependent on time-averaging intervals. In this talk we will discuss how insights into local air quality can be gleaned from data on the map at various averaging intervals and how these insights can be transformed into actions to reduce exposure to smoke. Based on our work with PurpleAir sensors, we will highlight how to quantify and improve the accuracy of data from other sensor networks so that it can be also be utilized to provide insights on local air quality. 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.