On Enhancing Air Quality Model Predictions of Particulate Matter From Aircraft Emissions
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Woody, Matthew. On Enhancing Air Quality Model Predictions of Particulate Matter From Aircraft Emissions. Chapel Hill, NC: University of North Carolina at Chapel Hill Graduate School, 2014. https://doi.org/10.17615/kzj7-y977APA
Woody, M. (2014). On Enhancing Air Quality Model Predictions of Particulate Matter From Aircraft Emissions. Chapel Hill, NC: University of North Carolina at Chapel Hill Graduate School. https://doi.org/10.17615/kzj7-y977Chicago
Woody, Matthew. 2014. On Enhancing Air Quality Model Predictions of Particulate Matter From Aircraft Emissions. Chapel Hill, NC: University of North Carolina at Chapel Hill Graduate School. https://doi.org/10.17615/kzj7-y977- Last Modified
- March 19, 2019
- Creator
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Woody, Matthew
- Affiliation: Gillings School of Global Public Health, Department of Environmental Sciences and Engineering
- Abstract
- Aviation is an important mode of transportation and usage is expected to continually grow. However, aircraft emit numerous pollutants that adversely impact air quality. The goal of this work is to provide additional certainty in air quality estimates of one of those pollutants, aircraft-attributable PM<sub>2.5</sub>, during landing and takeoff cycles using the Community Air Quality (CMAQ) Model and its enhancements. First, CMAQ's response to secondary organic aerosol (SOA) concentrations, a component of PM<sub>2.5</sub>, formed from aircraft emissions was examined. It was determined that at coarser model resolutions (36-km and 12-km), aircraft NO<sub>x</sub> emissions lowered free radical concentrations and thereby reduced SOA precursor oxidation. This directly resulted in the reduction of SOA concentrations, primarily biogenic SOA. At a finer grid resolution (4-km), aircraft primary organic aerosol (POA) emissions provided additional mass for SOA to partition onto, promoting semi-volatile organic carbon species to partition from the particle phase to the gas phase, increasing SOA concentrations. Secondly, a new formation pathway for modeled PM<sub>2.5</sub> (based on recent sampling and smog chamber data) was incorporated into CMAQ to account for non-traditional SOA (NTSOA), SOA formed from aircraft emissions of semi and intermediate volatile organic compounds. This new pathway added 1.7% in January and 7.4% in July to aircraft-attributable PM<sub>2.5</sub> at the Hartsfield-Jackson Atlanta International Airport. Downwind of the Atlanta airport, NTSOA averaged 4.6-17.9% of aircraft- attributable PM<sub>2.5</sub>. These contributions were generally low compared to smog chamber results due to considerably lower ambient organic aerosol concentrations in CMAQ versus those in the smog chamber experiments. Thirdly, alternative aircraft PM emission estimates based on a 1-D plume model were coupled with a plume in grid (PinG) treatment for aircraft in CMAQ. This treatment increased grid-based monthly and contiguous U.S. average aircraft-attributable PM<sub>2.5</sub> by 40% (from 1.9 ng m<super>-3</super> to 2.7 ng m<super>-3</super>) in a winter month and 12% (from 2.4 ng m<super>-3</super> to 2.6 ng m<super>-3</super>) in a summer month. Maximum modeled hourly subgrid scale aircraft-attributable PM<sub>2.5</sub> concentrations were 23.7 µg m<super>-3</super> in a winter month and 59.3 µg m<super>-3</super> in a summer month, considerably higher than typical grid-based aircraft contributions (~0.1 µg m<super>-3</super>).
- Date of publication
- December 2014
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- Rights statement
- In Copyright
- Advisor
- West, J. Jason
- Napelenok, Sergey
- Arunachalam, Saravanan
- Vizuete, William
- Surratt, Jason
- Degree
- Doctor of Philosophy
- Degree granting institution
- University of North Carolina at Chapel Hill Graduate School
- Graduation year
- 2014
- Language
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- Place of publication
- Chapel Hill, NC
- Access right
- There are no restrictions to this item.
- Date uploaded
- April 23, 2015
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