Abstract View
Leveraging a PurpleAir Sensor Network to Inform Air Quality Action in Phoenix, Arizona
IAN VONWALD, Karoline Barkjohn, Samuel Frederick, Sue Kimbrough, Ben Davis, Nikki Peterson, Ira Domsky, Ron Pope, Andrea Clements, U.S. EPA Office of Research and Development
Abstract Number: 62
Working Group: Urban Aerosols
Abstract
Affordable air sensors are revolutionizing how air quality is monitored. While many air sensor studies have focused on measurement accuracy and data correction, an important use of sensors is informing air quality action, since sensors can be deployed in dense networks that can capture local variations in pollution. For example, air quality in Phoenix, Arizona is adversely affected by seasonal woodburning, especially in the winter. The local agency mitigates this issue through control strategies including fireplace change-out programs and information campaigns on when or what not to burn. Programs such as these might benefit greatly from the neighborhood-level air quality measurements derived from a dense air sensor network.
Here, we use a distributed network of more than 30 PurpleAir particulate matter (PM) sensors deployed in Phoenix since November 2018 to identify local spatiotemporal air quality trends. We incorporate local meteorological data to focus on fine PM mass transport between areas where PM originates to areas that are most impacted, with three particular interests: (1) short-lived events that worsen air quality, such as fireworks from holiday celebrations, (2) seasonal events such as woodburning, and (3) unanticipated, unknown duration events such as the COVID-19 pandemic, in which travel restrictions and stay-at-home orders have been imposed. These results will demonstrate the potential of a distributed sensor network for tracking local air quality hotspots, improving understanding of how air quality is affected on shorter and longer time scales, and identifying areas that would benefit the most from control or mitigation actions.
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