Localized primary emissions of carbonaceous aerosol are the major drivers of intracity variability of submicron particulate matter (PM 1 ) concentrations. We investigated spatial variations in PM 1 composition with mobile sampling in Pittsburgh, Pennsylvania, United States and performed sourceapportionment analysis to attribute primary organic aerosol (OA) to traffic (HOA) and cooking OA (COA). In high-source-impact locations, the PM 1 concentration is, on average, 2 μg m −3 (40%) higher than urban background locations. Traffic emissions are the largest source contributing to populationweighted exposures to primary PM. Vehicle-miles traveled (VMT) can be used to reliably predict the concentration of HOA and localized black carbon (BC) in air pollutant spatial models. Restaurant count is a useful but imperfect predictor for COA concentration, likely due to highly variable emissions from individual restaurants. Near-road cooking emissions can be falsely attributed to traffic sources in the absence of PM source apportionment. In Pittsburgh, 28% and 9% of the total population are exposed to >1 μg m −3 of traffic-and cooking-related primary emissions, with some populations impacted by both sources. The source mix in many U.S. cities is similar; thus, we expect similar PM spatial patterns and increased exposure in high-source areas in other cities.

Organic aerosol (OA) is a major component of fine particulate matter (PM) in urban environments. We performed in-motion ambient sampling from a mobile platform with an aerosol mass spectrometer (AMS) to investigate the spatial variability and sources of OA concentrations in Pittsburgh, Pennsylvania, a midsize, largely postindustrial American city. To characterize the relative importance of cooking and traffic sources, we sampled in some of the most populated areas (∼18 km) in and around Pittsburgh during afternoon rush hour and evening mealtime, including congested highways, major local roads, areas with high densities of restaurants, and urban background locations. We found greatly elevated OA concentrations (10s of μg m) in the vicinity of numerous individual restaurants and commercial districts containing multiple restaurants. The AMS mass spectral information indicates that majority of the high concentration plumes (71%) were from cooking sources. Areas containing both busy roads and restaurants had systematically higher OA concentrations than areas with only busy roads and urban background locations. Elevated OA concentrations were measured hundreds of meters downwind of some restaurants, indicating that these sources can influence air quality on neighborhood scales. Approximately 20% of the population (∼250 000 people) in the Pittsburgh area lives within 200 m of a restaurant; therefore, restaurant emissions are potentially an important source of outdoor PM exposures for this large population.

Characterizing intracity variations of atmospheric particulate matter has mostly relied on fixed-site monitoring and quantifying variability in terms of different bulk aerosol species. In this study, we performed ground-based mobile measurements using a single-particle mass spectrometer to study spatial patterns of source-specific particles and the evolution of particle mixing state in 21 areas in the metropolitan area of Pittsburgh, PA. We selected sampling areas based on traffic density and restaurant density with each area ranging from 0.2 to 2 km. Organics dominate particle composition in all of the areas we sampled while the sources of organics differ. The contribution of particles from traffic and restaurant cooking varies greatly on the neighborhood scale. We also investigate how primary and aged components in particles mix across the urban scale. Lastly we quantify and map the particle mixing state for all areas we sampled and discuss the overall pattern of mixing state evolution and its implications. We find that in the upwind and downwind of the urban areas, particles are more internally mixed while in the city center, particle mixing state shows large spatial heterogeneity that is mostly driven by emissions. This study is to our knowledge, the first study to perform fine spatial scale mapping of particle mixing state using ground-based mobile measurement and single-particle mass spectrometry.

Abstract. We investigated spatial and temporal patterns in the concentration and composition of submicron particulate matter (PM1) in Oakland, California, in the summer of 2017 using an aerosol mass spectrometer mounted in a mobile laboratory. We performed ∼160 h of mobile sampling in the city over a 20-day period. Measurements are compared for three adjacent neighborhoods with distinct land uses: a central business district (“downtown”), a residential district (“West Oakland”), and a major shipping port (“port”). The average organic aerosol (OA) concentration is 5.3 µg m−3 and contributes ∼50 % of the PM1 mass. OA concentrations in downtown are, on average, 1.5 µg m−3 higher than in West Oakland and port. We decomposed OA into three factors using positive matrix factorization: hydrocarbon-like OA (HOA; 20 % average contribution), cooking OA (COA; 25 %), and less-oxidized oxygenated OA (LO-OOA; 55 %). The collective 45 % contribution from primary OA (HOA + COA) emphasizes the importance of primary emissions in Oakland. The dominant source of primary OA shifts from HOA-rich in the morning to COA-rich after lunchtime. COA in downtown is consistently higher than West Oakland and port due to a large number of restaurants. HOA exhibits variability in space and time. The morning-time HOA concentration in downtown is twice that in port, but port HOA increases more than two-fold during midday, likely because trucking activity at the port peaks at that time. While it is challenging to mathematically apportion traffic-emitted OA between drayage trucks and cars, combining measurements of OA with black carbon and CO suggests that while trucks have an important effect on OA and BC at the port, gasoline-engine cars are the dominant source of traffic emissions in the rest of Oakland. Despite the expectation of being spatially uniform, LO-OOA also exhibits spatial differences. Morning-time LO-OOA in downtown is roughly 25 % (∼0.6 µg m−3) higher than the rest of Oakland. Even as the entire domain approaches a more uniform photochemical state in the afternoon, downtown LO-OOA remains statistically higher than West Oakland and port, suggesting that downtown is a microenvironment with higher photochemical activity. Higher concentrations of particulate sulfate (also of secondary origin) with no direct sources in Oakland further reflect higher photochemical activity in downtown. A combination of several factors (poor ventilation of air masses in street canyons, higher concentrations of precursor gases, higher concentrations of the hydroxyl radical) likely results in the proposed high photochemical activity in downtown. Lastly, through Van Krevelen analysis of the elemental ratios (H ∕ C, O ∕ C) of the OA, we show that OA in Oakland is more chemically reduced than several other urban areas. This underscores the importance of primary emissions in Oakland. We also show that mixing of oceanic air masses with these primary emissions in Oakland is an important processing mechanism that governs the overall OA composition in Oakland.

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