High Resolution Urban Air Quality Modeling with an Immersed Boundary Method in WRF

This poster describes the first steps in creating an air quality model capable of representing air pollution concentrations at neighborhood scales to assist with long term exposure studies. Current generation urban air quality models are not capable of providing accurate results at such fine scales due to their simplified representations of flow conditions in time and space. Traditional urban air quality models often do not utilize realistic meteorological input or complex urban geometry, both of which are necessary for comprehensive evaluations of site-specific exposure to atmospheric pollutants. The present study applies an immersed boundary method (IBM) implemented in the Weather Research and Forecasting model (IBM-WRF, Lundquist et al. 2010) to simulate scalar transport and diffusion in an urban environment. The immersed boundary method used in IBM-WRF allows for the evaluation of flow over complex urban geometries including vertical surfaces, sharp corners, and local topographic variations. Lateral boundaries in IBM-WRF are prescribed using output from the standard WRF model, allowing for realistic meteorological input.

IBM-WRF is being used to investigate the transport and trapping of vehicle emissions around a proposed affordable housing development located adjacent to a major freeway. Urban topography is developed using high-resolution airborne LIDAR data to provide building heights that are combined with ground elevation data from the National Elevation Dataset. Meteorological input is created using the WRF model configured to use several nested domains allowing for synoptic scale phenomena to affect the neighborhood scale IBM-WRF domain, which will be run with a horizontal resolution on the order of meters. Results from IBM-WRF will assist planning efforts to reduce local air pollution exposure and minimize related associated adverse health effects.