LAUSR

Abstract During wintertime, Salt Lake City experiences periods of high-pressure atmospheric stagnation that leads to prolonged periods with stable atmospheric boundary layers (ABL) due to the unique orography of the region. These atmospheric conditions typically lead to persistent cold air pool (PCAP) events, where the stable ABL remains over several days, degrading air quality in the Salt Lake Valley. In this work, we applied novel source apportionment methods to identify sources that were the greatest contributors to elevated secondary PM2.5 concentrations during PCAP events in winter 2007. A source-oriented modeling approach that relies on emissions inventory data (i.e., source-specific data) was utilized for source characterization. A correction was applied to chemical transport model (CTM) outputs to improve the estimates of source contributions to secondary PM2.5 components (organic carbon, nitrate, sulfate, and ammonium). As a result, gasoline vehicles (25%), natural gas combustion (21%), and other sources (29%) were identified as the largest sources of nitrate, which was the dominant aerosol component during the PCAP periods ([NO3−]max = 37.5 μg m−3). Further, receptor-oriented source apportionment modeling was conducted using the chemical mass balance method with gas constraints (CMB-GC) with location-specific, mathematically optimized PM2.5 source profiles to examine the multi-year trend in PCAP pollution. These optimized profiles were enhanced by integrating the initial guess profiles with CTM results and observations. CMB-GC was applied for the period 2007–2015 at an urban monitor, and the use of seasonally varying optimized source profiles improved results by resolving more mass than when using static source profiles, increasing the predicted-observed PM2.5 mass ratio from 0.91 to 1.03. The averaged biomass burning impacts exhibited the most significant change, increasing from an average of 0.85 to 1.87 μg m−3 when using the static profiles and the optimized profiles, respectively. The static and optimized CMB-GC results were similar for secondary components but differed slightly for mobile impacts. Stratification of PCAP vs. non-PCAP CMB-GC source impacts revealed that the dominant sources of PM2.5 varied under the two meteorological conditions.