Wintertime Spatial Patterns of Particulate Matter in Fairbanks, AK during ALPACA 2022
ELLIS ROBINSON, William Simpson, Peter F. DeCarlo,
Johns Hopkins University Abstract Number: 330
Working Group: Urban Aerosols
AbstractFairbanks-North Star Borough (FNSB), Alaska perennially experiences some of the worst winter-time air quality in the United States. FNSB was labeled a ''serious'' nonattainment area by the EPA in 2017 with respect to fine particulate matter (PM
2.5). The ALPACA (Alaskan Layered Pollution And Chemical Analysis) field campaign was established to better understand the sources of air pollution, pollutant transformations, and the meteorological conditions contributing to FNSB's air quality problem. We performed on-road mobile sampling during ALPACA to identify and understand the spatial patterns of PM across the study domain, which contained multiple stationary field sites.
These measurements demonstrate the following results, which are important both for the PM exposure of residents of FNSB and the spatial context of the ALPACA study: 1.) Both the between-neighborhood and within-neighborhood variations in PM
2.5 concentrations and composition are large (>10 μg m
-3). 2.) Spatial variations of PM in Fairbanks are tightly connected to meteorological conditions; dramatic between-neighborhood differences exist during stark temperature inversion conditions, but are significantly reduced when atmospheric conditions are more stable. 3.) During inversion conditions, total PM
2.5 and black carbon (BC) are tightly spatially correlated and have angstrom exponent values (AAE > 1.4) indicative of woodsmoke, but are relatively uncorrelated during stable conditions, implying that much of the spatial differences in PM are driven by the interplay between local emissions of woodsmoke and meteorology. 4.) PM
2.5, BC, and total particle number (PN) concentrations decreased with increasing elevation, with the fall-off being more dramatic during strong temperature inversion conditions. 5.) Lastly, mobile sampling reveals important air pollutant concentration differences between the multiple fixed sites of the ALPACA study, and demonstrates the utility of adding mobile sampling to better understand the spatial context of large urban air quality field campaigns.