Ozone reactivity scales play an important role in selecting which chemical compounds are used in products ranging from gasoline to pesticides to hairspray in California, across the United States and around the world. The California Statewide Air Pollution Research Center (SAPRC) box model that calculates ozone reactivity uses a representative urban atmosphere to predict how much additional ozone forms for each kilogram of compound emission. This representative urban atmosphere has remained constant since 1988, even though more than 25 years of emissions controls have greatly reduced ambient ozone concentrations across the United States during this time period. Here we explore the effects of updating the representative urban atmosphere used for ozone reactivity calculations from 1988 to 2010 conditions by updating the meteorology, emission rates, concentration of initial conditions, concentration of background species, and composition of volatile organic compound (VOC) profiles. Box model scenarios are explored for 39 cities across the United States to calculate the Maximum Incremental Reactivity (MIR) scale for 1,233 individual compounds and compound-mixtures. Median MIR values across the cities decreased by approximately 20.3% when model conditions were updated. The decrease is primarily due to changes in atmospheric composition ultimately attributable to emissions control programs between 1998 and 2010. Further effects were caused by changes in meteorological variables stemming from shifting seasons for peak ozone events (summer versus early fall). Lumped model species with the highest MIR values in 1988 experienced the greatest decrease in MIR values when conditions were updated to 2010. Despite the reduction in the absolute reactivity in the updated 2010 atmosphere, the relative ranking of the VOCs according to their reactivity did not change strongly compared to the original 1988 atmosphere. These findings indicate that past decisions about ozone control programs remain valid today, and the ozone reactivity scale continues to provide relevant guidance for future policy decisions even as new products are developed. Implications: Updating the representative urban atmosphere used for the Maximum Incremental Reactivity (MIR) scale from 1988 to 2010 conditions caused the reactivity of 1223 individual compounds and combined mixtures to decrease by an average of 20.3% but the relative ranking of the VOCs was not strongly affected. This means that previous guidance about preferred chemical formulations to reduce ozone formation in cities across the United States remain valid today, and the MIR scale continues to provide relevant guidance for future policy decisions even as new products are developed.

Abstract. Regional concentrations and source contributions are calculated for airborne particle number concentration (Nx) and ultrafine particle mass concentration (PM0.1) in the San Francisco Bay Area (SFBA) and the South Coast Air Basin (SoCAB) surrounding Los Angeles with 4 km spatial resolution and daily time resolution for selected months in the years 2012, 2015, and 2016. Performance statistics for daily predictions of N10 concentrations meet the goals typically used for modeling of PM2.5 (mean fractional bias (MFB) < ±0.5 and mean fractional error (MFE) < 0.75). The relative ranking and concentration range of source contributions to PM0.1 predicted by regional calculations agree with results from receptor-based studies that use molecular markers for source apportionment at four locations in California. Different sources dominated regional concentrations of N10 and PM0.1 because of the different emitted particle size distributions and different choices for heating fuels. Nucleation (24 %–57 %) made the largest single contribution to N10 concentrations at the 10 regional monitoring locations, followed by natural gas combustion (28 %–45 %), aircraft (2 %–10 %), mobile sources (1 %–5 %), food cooking (1 %–2 %), and wood smoke (0 %–1 %). In contrast, natural gas combustion (22 %–52 %) was the largest source of PM0.1 followed by mobile sources (15 %–42 %), food cooking (4 %–14 %), wood combustion (1 %–12 %), and aircraft (2 %–6 %). The study region encompassed in this project is home to more than 25 million residents, which should provide sufficient power for future epidemiological studies on the health effects of airborne ultrafine particles. All of the PM0.1 and N10 outdoor exposure fields produced in the current study are available free of charge at http://webwolf.engr.ucdavis.edu/data/soa_v3/hourly_avg/ (last access: 20 November 2019).

Abstract. The regional concentrations of airborne ultrafine particulate matter mass (Dp<0.1 µm; PM0.1) were predicted in 39 cities across the United States (US) during summertime air pollution episodes. Calculations were performed using a regional source-oriented chemical transport model with 4 km spatial resolution operating on the National Emissions Inventory created by the U.S. Environmental Protection Agency (EPA). Measured source profiles for particle size and composition between 0.01 and 10 µm were used to translate PM total mass to PM0.1. Predicted PM0.1 concentrations exceeded 2 µg m−3 during summer pollution episodes in major urban regions across the US including Los Angeles, the San Francisco Bay Area, Houston, Miami, and New York. PM0.1 spatial gradients were sharper than PM2.5 spatial gradients due to the dominance of primary aerosol in PM0.1. Artificial source tags were used to track contributions to primary PM0.1 and PM2.5 from 15 source categories. On-road gasoline and diesel vehicles made significant contributions to regional PM0.1 in all 39 cities even though peak contributions within 0.3 km of the roadway were not resolved by the 4 km grid cells. Cooking also made significant contributions to PM0.1 in all cities but biomass combustion was only important in locations impacted by summer wildfires. Aviation was a significant source of PM0.1 in cities that had airports within their urban footprints. Industrial sources, including cement manufacturing, process heating, steel foundries, and paper and pulp processing, impacted their immediate vicinity but did not significantly contribute to PM0.1 concentrations in any of the target 39 cities. Natural gas combustion made significant contributions to PM0.1 concentrations due to the widespread use of this fuel for electricity generation, industrial applications, residential use, and commercial use. The major sources of primary PM0.1 and PM2.5 were notably different in many cities. Future epidemiological studies may be able to differentiate PM0.1 and PM2.5 health effects by contrasting cities with different ratios of PM0.1∕PM2.5. In the current study, cities with higher PM0.1∕PM2.5 ratios (ratio greater than 0.10) include Houston, TX, Los Angeles, CA, Bakersfield, CA, Salt Lake City, UT, and Cleveland, OH. Cities with lower PM0.1 to PM2.5 ratios (ratio lower than 0.05) include Lake Charles, LA, Baton Rouge, LA, St. Louis, MO, Baltimore, MD, and Washington, D.C.

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