AAAR 32nd Annual Conference
September 30 - October 4, 2013
Oregon Convention Center
Portland, Oregon, USA
Abstract View
Implementation of a High-Resolution Source-Oriented WRF-Chem Model Using Large Eddy Simulation at the Port of Oakland
David Joe, Steven DeNero, Hongliang Zhang, Hsiang-He Lee, Shu-Hua Chen, MICHAEL KLEEMAN, UC Davis
Abstract Number: 222 Working Group: Source Apportionment
Abstract A version of the Source-Oriented WRF-Chem (SOWC) model with Large Eddy Simulation (SOWC-LES) was developed and implemented to perform high resolution simulations over the community of Oakland, California, during March 2010. A multiscale set of nested domains was used to predict contributions to elemental carbon (EC) concentrations from ships, trains, and on-road diesel trucks at 250 m spatial resolution. Results of the nested LES model were compared model results using a parameterization scheme and no nested LES (1 km resolution). Model predictions were compared to speciated particulate matter (PM) measurements and source contributions calculated using Positive Matrix Factorization (PMF). The PMF analysis found that on-road diesel traffic was a major EC contributor, a result consistent with previous studies for Oakland.
The average EC concentration predicted by the SOWC-LES model was 0.42 µg m-3, with source contributions of 0.22 µg/m3 from on-road diesel, 0.05 µg/m3 from ships, 0.08 µg/m3 from trains, and 0.09 µg/m3 from other sources. The nested LES and non-LES simulations produced similar EC predictions at the monitoring site, but predictions at other locations showed substantial differences. The LES model predicted higher period-averaged and hourly-averaged EC source contributions. The greatest increase was seen in the maximum hourly EC from the on-road diesel source, which increased by nearly a factor of 2 (3.74 µg/m3 to 6.69 µg/m3).
Population-weighted calculations showed that the SOWC-LES model predicted greater community EC exposure from all sources. The increase in period-averaged EC exposure from each source ranged from +1% to +17%, while the increase in maximum hourly EC exposure was even greater, ranging from +9% to +32%. This evaluation shows that resolving neighborhood scales through the representation of local mixing phenomena can significantly impact pollutant concentration predictions, especially when examining extreme exposures in a densely populated area with many sources and complex terrain.