AAAR 36th Annual Conference October 16 - October 20, 2017 Raleigh Convention Center Raleigh, North Carolina, USA
Abstract View
Variations in Wintertime PM among Communities in Sacramento Measured with a Combination of Traditional and Low-Cost Sensor Methods
Anondo Mukherjee, STEVEN G. BROWN, Michael McCarthy, Aleta Kennard, Janice Snyder, Stephen D'Andrea, Sonoma Technology, Inc
Abstract Number: 403 Working Group: Urban Aerosols
Abstract Residential wood smoke is one of the largest contributors to wintertime particulate matter (PM) in Sacramento, CA. To understand how wood smoke and PM varied across Sacramento and between environmental justice (EJ) and non-EJ communities, we conducted measurements during December 2016 and January 2017 of black carbon (BC) with Aethalometers (AE33) at six locations, of PM with low‑cost AirBeam sensors at 15 locations, of hourly PM with beta attenuation monitors (BAMs) and 24‑hour PM via filter measurements at two locations, and of levoglucosan via filter measurements at three locations. Before and after the main study period, 20 AirBeam sensors were collocated with a BAM and a filter PM instrument to determine calibration factors for the sensors. In addition, the AirBeam sensors were collocated with a BAM and a filter PM instrument at two locations throughout the study to assess whether there was drift in the sensor measurements and to determine the comparability of PM measurements among the sensors, BAM, and filter instrument.
The 20 AirBeam sensors had extremely high precision during the pre- and post-study collocations, with AirBeam-to-AirBeam correlation coefficients (r2) greater than 0.95. AirBeams also had very high precision with very little drift at the two locations with collocated AirBeams throughout the study. Since each AirBeam had a consistent PM concentration response relative to the other collocated AirBeams, we developed an AirBeam-specific calibration based on the collocated data, and used the calibrated AirBeam data to assess with high confidence how PM varied across communities. We also determined the extent to which AirBeam data can be corrected to BAM or 24-hr filter measurements using meteorological data.