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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 (<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.

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.

Photoelectron resonance capture ionization (PERCI) is demonstrated as a sensitive ionization technique involving minimal fragmentation of organic molecules. PERCI has been used successfully to softly and efficiently ionize both strongly UV absorbing and non-absorbing molecules. Tunable low energy (<1 eV) electrons are generated by focusing a pulsed UV laser on an aluminum photocathode in the presence of gas phase analyte. Negative ions are formed through a resonance electron capture process. Mass analysis is done using a reflectron time-of-flight mass spectrometer. PERCI is demonstrated for a number of gas phase compounds and simple mixtures, including sulfur hexafluoride, nitrobenzene, nitrophenol, 2-pentanone, hexanal, heptanal, and octanal. In all cases the molecular ion (or [M − H] −) was observed to be the dominant peak. The 1σ limit of detection was estimated to be on the order of 10 6 molecules in the ionization region.

Mobile-platform measurements provide new opportunities for characterizing spatial variations in air pollution within urban areas, identifying emission sources, and enhancing knowledge of atmospheric processes. The Aclima, Inc., mobile measurement and data acquisition platform was used to equip four Google Street View cars with research-grade instruments, two of which were available for the duration of this study. On-road measurements of air quality were made during a series of sampling campaigns between May 2016 and September 2017 at high (i.e., 1 s) temporal and spatial resolution at several California locations: Los Angeles, San Francisco, and the northern San Joaquin Valley (including nonurban roads and the cities of Tracy, Stockton, Manteca, Merced, Modesto, and Turlock). The results demonstrate that the approach is effective for quantifying spatial variations in air pollutant concentrations over measurement periods as short as 2 weeks. Measurement accuracy and precision are evaluated using results of weekly performance checks and periodic audits conducted through the sampler inlets, which show that research instruments located within stationary vehicles are capable of reliably measuring nitric oxide (NO), nitrogen dioxide (NO2), ozone (O3), methane (CH4), black carbon (BC), and particle number (PN) concentration, with bias and precision ranging from < 10 % for gases to < 25 % for BC and PN at 1 s time resolution. The quality of the mobile measurements in the ambient environment is examined by comparisons with data from an adjacent (< 9 m) stationary regulatory air quality monitoring site and by paired collocated vehicle comparisons, both stationary and driving. The mobile measurements indicate that United States Environmental Protection Agency (US EPA) classifications of two Los Angeles stationary regulatory monitors' scales of representation are appropriate. Paired time-synchronous mobile measurements are used to characterize the spatial scales of concentration variations when vehicles were separated by < 1 to 10 km. A data analysis approach is developed to characterize spatial variations while limiting the confounding influence of diurnal variability. The approach is illustrated using data from San Francisco, revealing 1 km scale differences in mean NO2 and O3 concentrations up to 117 % and 46 %, respectively, of mean values during a 2-week sampling period. In San Francisco and Los Angeles, spatial variations up to factors of 6 to 8 occur at sampling scales of 100–300 m, corresponding to 1 min averages.

Photoelectron resonance capture ionization (PERCI) is demonstrated as a sensitive ionization technique involving minimal fragmentation of organic molecules. PERCI has been used successfully to softly and efficiently ionize both strongly UV absorbing and non-absorbing molecules. Tunable low energy (<1 eV) electrons are generated by focusing a pulsed UV laser on an aluminum photocathode in the presence of gas phase analyte. Negative ions are formed through a resonance electron capture process. Mass analysis is done using a reflectron time-of-flight mass spectrometer. PERCI is demonstrated for a number of gas phase compounds and simple mixtures, including sulfur hexafluoride, nitrobenzene, nitrophenol, 2-pentanone, hexanal, heptanal, and octanal. In all cases the molecular ion (or [M - H](-)) was observed to be the dominant peak. The 1sigma limit of detection was estimated to be on the order of 10(6) molecules in the ionization region.

Patients with heterotaxy syndrome (HS) have a range of anomalies and outcomes. There are limited data on perinatal outcomes after prenatal diagnosis. To determine the factors influencing perinatal and infant outcomes, we analyzed prenatal and postnatal variables in fetuses with HS from 1995 to 2011. Of 154 fetuses with HS, 61 (40%) had asplenia syndrome (ASP) and 93 (60%) had polysplenia syndrome (PSP). In the ASP group, 22 (36%) patients were elected for termination of pregnancy, 4 (10%) had fetal death, and 35 of 39 (90%) continued pregnancies were live born. In the PSP group, 12 (13%) patients were elected for termination of pregnancy, 5 (6%) had fetal death (4 with bradyarrhythmia), and 76 of 81 (94%) continued pregnancies were live born. Bradyarrhythmia was the only predictor of fetal death. In the live-born ASP group, 43% (15 of 35) died, 7 because of pulmonary vein stenosis, 4 postoperatively, and 4 because of noncardiac causes. In the live-born PSP group, 13% (10 of 76) died, 5 postoperatively, 2 from bradyarrhythmia, 1 from a cardiac event, and 2 from noncardiac causes. Pulmonary vein stenosis and noncardiac anomalies were independent risk factors for postnatal death. Only 8% of ASP patients achieved biventricular circulation, compared with 65% of PSP patients. In the live-born cohort, the 5-year survival rate was 53% for ASP and 86% for PSP. In conclusion, most PSP patients are currently alive with biventricular circulation in contrast with few ASP patients. Bradyarrhythmia was the only predictor of fetal death. Pulmonary vein stenosis and noncardiac anomalies were predictors of postnatal death.

Communism may have been ousted or on its last legs around the world, but nearly 2 billion people from Moscow to Beijing still struggle daily with a Marxist legacy that demonized private ownership of land and has left much property in state hands. Private ownership is becoming a benchmark for progress in more than two dozen former and present Communist nations. In the coming decade, it will help show how much these nations accept market reform and may also indicate their prospects for political stability. Karl Marx, the 19th-century philosopher who laid out the principles of communism, saw private property as a tool controlled by the rich to keep the working class poor. Whenever communists gained power, they seized private property from individuals - in theory to distribute it more equitably among the people. But the question of land ownership still serves as a valuable propaganda weapon. Cuban leaders use it to play on popular concern about US legislation, now under consideration, that would entitle Americans who owned property in Cuba before the revolution to regain their confiscated land and other possessions.