Disparity in air pollution exposure arises from variation at multiple spatial scales: along urban-to-rural gradients, between individual cities within a metropolitan region, within individual neighborhoods, and between city blocks. Here, we improve on existing capabilities to systematically compare urban variation at several scales, from hyperlocal (<100 m) to regional (>10 km), and to assess consequences for outdoor air pollution experienced by residents of different races and ethnicities, by creating a set of uniquely extensive and high-resolution observations of spatially variable pollutants: NO, NO2, black carbon (BC), and ultrafine particles (UFP). We conducted full-coverage monitoring of a wide sample of urban and suburban neighborhoods (93 km2 and 450,000 residents) in four counties of the San Francisco Bay Area using Google Street View cars equipped with the Aclima mobile platform. Comparing scales of variation across the sampled population, greater differences arise from localized pollution gradients for BC and NO (pollutants dominated by primary sources) and from regional gradients for UFP and NO2 (pollutants dominated by secondary contributions). Median concentrations of UFP, NO, and NO2 are, for Hispanic and Black populations, 8 to 30% higher than the population average; for White populations, average exposures to these pollutants are 9 to 14% lower than the population average. Systematic racial/ethnic disparities are influenced by regional concentration gradients due to sharp contrasts in demographic composition among cities and urban districts, while within-group extremes arise from local peaks. Our results illustrate how detailed and extensive fine-scale pollution observations can add new insights about differences and disparities in air pollution exposures at the population scale.

On-road gasoline vehicles are a major source of secondary organic aerosol (SOA) in urban areas. We investigated SOA formation by oxidizing dilute, ambient-level exhaust concentrations from a fleet of on-road gasoline vehicles in a smog chamber. We measured less SOA formation from newer vehicles meeting more stringent emissions standards. This suggests that the natural replacement of older vehicles with newer ones that meet more stringent emissions standards should reduce SOA levels in urban environments. However, SOA production depends on both precursor concentrations (emissions) and atmospheric chemistry (SOA yields). We found a strongly nonlinear relationship between SOA formation and the ratio of nonmethane organic gas to oxides of nitrogen (NO_x) (NMOG:NO_x), which affects the fate of peroxy radicals. For example, changing the NMOG:NO_x from 4 to 10 ppbC/ppbNO_x increased the SOA yield from dilute gasoline vehicle exhaust by a factor of 8. We investigated the implications of this relationship for the Los Angeles area. Although organic gas emissions from gasoline vehicles in Los Angeles are expected to fall by almost 80% over the next two decades, we predict no reduction in SOA production from these emissions due to the effects of rising NMOG:NO_x on SOA yields. This highlights the importance of integrated emission control policies for NO_x and organic gases.

Secondary organic aerosol (SOA) formation from in-use vehicle emissions was investigated using a potential aerosol mass (PAM) flow reactor deployed in a highway tunnel in Pittsburgh, Pennsylvania. Experiments consisted of passing exhaust-dominated tunnel air through a PAM reactor over integrated hydroxyl radical (OH) exposures ranging from ∼ 0.3 to 9.3 days of equivalent atmospheric oxidation. Experiments were performed during heavy traffic periods when the fleet was at least 80% light-duty gasoline vehicles on a fuel-consumption basis. The peak SOA production occurred after 2-3 days of equivalent atmospheric oxidation. Additional OH exposure decreased the SOA production presumably due to a shift from functionalization to fragmentation dominated reaction mechanisms. Photo-oxidation also produced substantial ammonium nitrate, often exceeding the mass of SOA. Analysis with an SOA model highlight that unspeciated organics (i.e., unresolved complex mixture) are a very important class of precursors and that multigenerational processing of both gases and particles is important at longer time scales. The chemical evolution of the organic aerosol inside the PAM reactor appears to be similar to that observed in the atmosphere. The mass spectrum of the unoxidized primary organic aerosol closely resembles ambient hydrocarbon-like organic aerosol (HOA). After aging the exhaust equivalent to a few hours of atmospheric oxidation, the organic aerosol most closely resembles semivolatile oxygenated organic aerosol (SV-OOA) and then low-volatility organic aerosol (LV-OOA) at higher OH exposures. Scaling the data suggests that mobile sources contribute ∼ 2.9 ± 1.6 Tg SOA yr(-1) in the United States, which is a factor of 6 greater than all mobile source particulate matter emissions reported by the National Emissions Inventory. This highlights the important contribution of SOA formation from vehicle exhaust to ambient particulate matter concentrations in urban areas.

BACKGROUND:Most epidemiological studies address health effects of atmospheric particulate matter (PM) using mass-based measurements as exposure surrogates. However, this approach ignores many critical physiochemical properties of individual atmospheric particles. These properties control the deposition of particles in the human lung and likely their toxicity; in addition, they likely have larger spatial variability than PM mass. OBJECTIVES:This study was designed to quantify the spatial variability in number, size, source, and chemical mixing state of individual particles in a populous urban area. We quantified the population exposure to these detailed particle properties and compared them to mass-based exposures. METHODS:We performed mobile sampling using an advanced single-particle mass spectrometer to measure the spatial variability of number concentration of source-resolved 50-1,000 nm particles and particle mixing state in Pittsburgh, Pennsylvania. We built land-use regression (LUR) models to estimate their spatial patterns and coupled them with demographic data to estimate population exposure. RESULTS:Particle number concentration had a much larger spatial variability than mass concentration within the city. Freshly emitted particles from traffic and cooking drive the variability in particle number, but mass concentrations are dominated by aged background particles composed of secondary materials. In addition, people exposed to elevated number concentrations of atmospheric particles are also exposed to more externally mixed particles. CONCLUSIONS:Our advanced measurement technique provides a new exposure picture that resolves the large intra-city spatial heterogeneity in traffic and cooking particle number concentrations in the populous urban area. Our results provide a complementary and more detailed perspective compared with bulk measurements of composition. In addition, given the influence of particle mixing state on properties such as particle deposition in the lung, the large spatial gradients of chemical mixing state may significantly influence the health effects of fine PM. https://doi.org/10.1289/EHP5311.

Biomass burning (BB) is a major source of atmospheric pollutants. Field and laboratory studies indicate that secondary organic aerosol (SOA) formation from BB emissions is highly variable. We investigated sources of this variability using a novel dual-smog-chamber method that directly compares the SOA formation from the same BB emissions under two different atmospheric conditions. During each experiment, we filled two identical Teflon smog chambers simultaneously with BB emissions from the same fire. We then perturbed the smoke with UV lights, UV lights plus nitrous acid (HONO), or dark ozone in one or both chambers. These perturbations caused SOA formation in nearly every experiment with an average organic aerosol (OA) mass enhancement ratio of 1.78 ± 0.91 (mean ± 1σ). However, the effects of the perturbations were highly variable ranging with OA mass enhancement ratios ranging from 0.7 (30% loss of OA mass) to 4.4 across the set of perturbation experiments. There was no apparent relationship between OA enhancement and perturbation type, fuel type, and modified combustion efficiency. To better isolate the effects of different perturbations, we report dual-chamber enhancement (DUCE), which is the quantity of the effects of a perturbation relative to a reference condition. DUCE values were also highly variable, even for the same perturbation and fuel type. Gas measurements indicate substantial burn-to-burn variability in the magnitude and composition of SOA precursor emissions, even in repeated burns of the same fuel under nominally identical conditions. Therefore, the effects of different atmospheric perturbations on SOA formation from BB emissions appear to be less important than burn-to-burn variability.