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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 (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.

The effects of liquefied natural gas (LNG) on pollutant emission inventories and air quality in the South Coast Air Basin (SoCAB) of California are evaluated using recent appliance emissions measurements by Lawrence Berkeley National Laboratory and the Southern California Gas Company (SoCalGas), and use of a state-of-the-art air quality model. Pollutant emissions can be impacted by LNG operation because of differences in composition and physical properties including the Wobbe index, a measure of energy delivery rate. Various LNG distribution scenarios are evaluated to determine the potential impacts of LNG. Projected penetration of LNG in the SoCalGas pipeline network in SoCAB is expected to be limited, which could cause increases in overall (area-wide) emissions of nitrogen oxides that are smaller than 0.05%. Based on the photochemical state of the South Coast Air Basin of California, any increase in NOx is expected to cause an increase in the highest local ozone concentrations, which is observed in model results. However, the magnitude of NOx emissions increases due to LNG use is determined to be within the uncertainty range of natural gas combustion sources and would not be discernible with the existing monitoring network.

Effective exhaust hoods can mitigate the indoor air quality impacts of pollutant emissions from residential cooking. This study reports capture efficiencies (CE) measured for cooking generated particles for scripted cooking procedures in a 121-m3 chamber with kitchenette. CEs also were measured for burner produced CO2 during cooking and separately for pots and pans containing water. The study used four exhaust hoods previously tested by Delp and Singer (Environ. Sci. Technol., 2012, 46, 6167-6173). For pan-frying a hamburger over medium heat on the back burner, CEs for particles were similar to those for burner produced CO2 and mostly above 80percent. For stir-frying green beans in a wok (high heat, front burner), CEs for burner CO2 during cooking varied by hood and airflow: CEs were 34-38percent for low (51?68 L s-1) and 54?72percent for high (109?138 L s-1) settings. CEs for 0.3?2.0 ?m particles during front burner stir-frying were 3?11percent on low and 16?70percent on high settings. Results indicate that CEs measured for burner CO2 are not predictive of CEs of cooking-generated particles under all conditions, but they may be suitable to identify devices with CEs above 80percent both for burner combustion products and for cooking-related particles.

Air pollution monitoring using mobile ground-based measurement platforms can provide high-quality spatiotemporal air pollution information. As mobile air quality monitoring campaigns extend to entire fleets of vehicles and integrate smaller-scale air quality sensors, it is important to address the need to assess these measurements in a scalable manner. We explore the collocation-based evaluation of air quality measurements in a mobile platform using fixed regulatory sites as a reference. We compare two approaches: a standard collocation assessment technique, in which the mobile platform is parked near the fixed regulatory site for a period of time, and an expanded approach, which uses measurements while the mobile platform is in motion in the general vicinity of the fixed regulatory site. Based on the availability of fixed-reference-site data, we focus on three pollutants (ozone, nitrogen dioxide, and nitric oxide) with distinct atmospheric lifetimes and behaviors. We compare measurements from a mobile laboratory with regulatory site measurements in Denver, CO, USA, and in the San Francisco Bay Area, CA, USA. Our 1-month Denver dataset includes both parked collocation periods near the fixed regulatory sites and general driving patterns around the sites, allowing a direct comparison of the parked and mobile collocation techniques on the same dataset. We show that the mobile collocation approach produces similar performance statistics, including coefficients of determination and mean bias errors, to the standard parked collocation technique. This is particularly true when the comparisons are restricted to specific road types, with residential streets showing the closest agreement and highways showing the largest differences. We extend our analysis to a larger (yearlong) dataset in California, where we explore the relationships between the mobile measurements and the fixed reference sites on a larger scale. We show that using a 40 h running median converges to within ± 4 ppbv of the fixed reference site for nitrogen dioxide and ozone and up to about 8 ppbv for nitric oxide. We propose that this agreement can be leveraged to assess instrument performance over time during large-scale mobile monitoring campaigns. We demonstrate an example of how such relationships can be employed during large-scale monitoring campaigns using small sensors to identify potential measurement biases. [ABSTRACT FROM AUTHOR]

Air pollution monitoring using mobile ground-based measurement platforms can provide high quality spatiotemporal air pollution information. As mobile air quality monitoring campaigns extend to entire fleets of vehicles and integrate smaller scale air quality sensors, it is important to address the quality assurance needs for validating these measurements. We explore collocation-based evaluation of air quality instruments in a mobile platform against fixed regulatory sites, both when the mobile platform is parked at the fixed regulatory site and when moving at distances of meters to kilometers from the site. We demonstrate agreement within 4 ppbv (for NO2 and O3+NO2) to 10 ppbv (for NO) when using a running median of 40 hourly differences between the moving mobile platform measurements and stationary site measurements. The comparability is strong when only measurements from residential roads are used but are only slightly diminished when all roads except highways are included in the analysis. We present a method for assessing mobile measurements of ozone (O3), nitrogen dioxide (NO2), and odd oxygen (OX = O3 + NO2) on an ongoing basis through comparisons with fixed regulatory sites. [ABSTRACT FROM AUTHOR]