Regional sources of airborne ultrafine particle number and mass concentrations in California

Abstract

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).

Predicted ultrafine particulate matter source contribution across the continental United States during summertime air pollution events

“…Performance for PM 2.5 and O 3 predictions met or exceeded the criteria typically used for regional air quality model applications, building confidence in the emissions inputs and meteorological fields used to drive the calculations. Similar model exercises carried out for episodes in California in 2015 and 2016 find good agreement between predicted PM 0.1 source contributions and receptor-based PM 0.1 source contributions calculated using measured concentrations of molecular markers (Yu et al, 2019). In the current study, predicted regional PM 0.1 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.…”

“…Good agreement was found between predictions for PM 0.1 concentrations associated with gasoline engines, diesel engines, cooking, wood burning, and "other sources" from these two independent techniques. Further details on this comparison are provided by Yu et al (2019). This evaluation of the modeling procedures builds confidence in the PM 0.1 source predictions across the US in the current study, but new measurements would be helpful to fully evaluate model predictions in the future.…”

“…A tunable nucleation parameter equal to 10 −5 was used based on results from previous studies across California for the year 2012 (Yu et al, 2019). Yu et al (2019) found good agreement between predicted and measured concentrations of daily-averaged PM 0.1 and N 7 source contributions in California. The current study expands these nucleation calculations to investigate new particle formation across all major US cities, but the data needed to evaluate the accuracy of these calculations are generally not available outside California, and particle number concentrations will not be a focal point of this work.…”

“…Model performance statistics for PM 2.5 predictions are summarized in Table S6. PM 0.1 measurements are not available for model evaluation in the 39 cities across the US in 2010 at the core of the current study, but measurements are available in California in the years 2015 and 2016 that can be used to evaluate similar modeling procedures. Yu et al (2019) compared PM 0.1 concentrations in Los Angeles, Fresno, East Oakland, and San Pablo, California, predicted using the UCD-CIT air quality model to receptor-based source apportionment calculations based on measured concentrations of molecular markers in the ultrafine particle size fraction (Xue et al, 2018). Good agreement was found between predictions for PM 0.1 concentrations associated with gasoline engines, diesel engines, cooking, wood burning, and "other sources" from these two independent techniques.…”

“…Nucleation was included in the model using the ternary nucleation (TN) mechanism involving H 2 SO 4 -H 2 O-NH 3 (Napari et al, 2002). A tunable nucleation parameter equal to 10 −5 was used based on results from previous studies across California for the year 2012 (Yu et al, 2019). Yu et al (2019) found good agreement between predicted and measured concentrations of daily-averaged PM 0.1 and N 7 source contributions in California.…”