Abstract View
Seasonal Influence on Urban Particulate and Black Carbon Pollution: Winter, Summer, and Wildfire
REBECCA A. SUGRUE, Chelsea V. Preble, James D.A. Butler, Thomas W. Kirchstetter, University of California, Berkeley
Abstract Number: 292
Working Group: Urban Aerosols
Abstract
Low-cost sensors can be deployed as dense monitoring networks to increase the spatial resolution of air pollution monitoring. This work collocated low-cost black carbon (BC) and fine particulate matter (PM2.5) monitors in two California communities. In Richmond, a densely-populated urban community in the San Francisco Bay Area with a major refinery and surrounded by highways, 50 sensor pairs were installed. Eleven monitoring sites were distributed across Modesto, a sprawling Central Valley community impacted by agricultural and trucking activities. Month-long monitoring campaigns were conducted in summer (August) and winter (January) 2020–2021. Custom-built BC sensors (Aerosol Black Carbon Detectors, UC Berkeley) were collocated with Aeroqual AQY1 and PurpleAir PA-II PM2.5 sensors in Richmond and Modesto, respectively, outside of homes and schools. This short-term monitoring captured seasonality in particulate pollution and spatiotemporal variability in BC/PM2.5 ratios within and between these communities.
Despite differences in land-use and combustion sources, Richmond and Modesto had approximately the same average winter BC concentration, ~0.4 μg m-1. During the summer campaign, both communities were heavily impacted by wildfire smoke, which resulted in more uniform PM2.5 and BC. Compared to non-smoke affected summer periods, PM2.5 and BC concentrations were 2–10× and 1.5–3.5× higher throughout the day, and the BC/PM2.5 ratio was 50% lower when smoke impacted air quality in Richmond. Though historical records indicate a strong seasonal cycle with BC concentrations 2–4× higher in winter, the average winter BC concentration in Richmond during this study was only 50% higher compared to the non-wildfire summer period. Ongoing analysis is examining spatiotemporal differences of local air pollution between Richmond and Modesto, localized hotspots, and the influence of source-specific activity patterns. Additionally, we are examining data-driven approaches to distinguish between smoke and non-smoke impacted days and related wildfire smoke corrections for both low-cost BC and PM2.5 sensor data.