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Alan H Huber Physical Scientist; PhD, QEP NOAA, ASMD, in partnership with the US EPA, National Exposure Research Laboratory, RTP, NC, USA THE 5TH ANNUAL.

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Presentation on theme: "Alan H Huber Physical Scientist; PhD, QEP NOAA, ASMD, in partnership with the US EPA, National Exposure Research Laboratory, RTP, NC, USA THE 5TH ANNUAL."— Presentation transcript:

1 Alan H Huber Physical Scientist; PhD, QEP NOAA, ASMD, in partnership with the US EPA, National Exposure Research Laboratory, RTP, NC, USA THE 5TH ANNUAL CMAS CONFERENCE, Chapel Hill, NC October 18, 2006 A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

2 What is Computational Fluid Dynamics (CFD)? Computational (having to do with mathematics & computation) Fluid Dynamics (the dynamics of things that flow) CFD is built upon fundamental physics equations: equations of motion and conservation. CFD applications range from numerical weather prediction to vehicular aerodynamics design. CFD applications are linked with advances in computing software and hardware. CFD software is characterized by the physical models in the software. Fine-scale CFD applications closely match the true geometry of the physical objects and processes being modeled.

3 Brief Background – before electronic computers Philosophical Interests in Fluid Flow Newton’s Physical Equations (1686) Navier-Stokes Equations (1823) V. Bjerknes – Notions of Numerical Weather Prediction (1904) L.F. Richardson – First Numerical Weather Prediction (1922)

4 Brief Background – with electronic computers :Progression to Air Quality Modeling First Electronic Computers (1940’s) J. Charney – First Computer Numerical Weather Prediction (April 1950) Numerical Modeling of Air Quality Promoted by US EPA in 1970’s and 1980’s CMAQ Evolves in the 1990’s to Present CMAQ Continues to Evolve with Advancing Computation Hardware and Software

5 Challenge to Relate to Human Exposure Assessment – Four Questions Modeling Should Help Answer How many people are exposed ? What is the level of each person’s exposure? What are the causes of exposure? How can exposures be altered efficiently?

6 Total Exposure Concentrations = Local Sources + Regional Background

7 Urban Exposures: Beyond the Lamp Post

8 Roadway Exposures: Within the Roadway or Neighborhood Microenvironments

9 Human Exposure A human is only exposed to what can possibly contact his body. Air quality concentrations need to be linked to temporal and spatial scales associated with profiles of human exposure relevant to supporting health risk assessments

10 Making Fine-Scale CFD Application Routine Computational resources. Today, industrial complexes can be practically modeled by most workstations, while complex urban areas can only be modeled by the cluster systems. Develop best-practice methods. CFD codes have many options. Develop user-friendly interfaces for general application. Air quality modelers should be able to run routine applications. Interface CFD software with other models.

11 Support/Collaborators Wei Tang: National Research Council Post Doc with EPA, 2003-2005 (2.5 years) Matt Freeman, Richard Spencer: EPA Scientific Visualization Center under EPA contract with Lockheed-Martin Karl Kuehlert, Brian Bell, Walter Schwarz: EPA Cooperative Research and Development Agreement with Fluent, Inc Michael Lazaro: EPA Memorandum of Cooperation with Argonne National Laboratory Department of Homeland Security: New York City Urban Dispersion Program Army Research Laboratory MSRC Visualization and Supercomputing Facility

12 Application of Fine-scale CFD Models Develop databases to complement the dearth of exposure measurements. Support the development of Human Exposure Factors. Support the development of subgrid parameterization for CMAQ. Interface with CMAQ

13 Present CMAQ Multi-scale Multi-pollutant Various Chemical and Physical Processes Common Linkage of Meteorology, Emissions, and Air Quality Regional Applications > 10 km grid Urban Applications > 1 km grid

14 Potential for Interfacing CMAQ CFD with Fine-scale CFD Models Increasing computational capacities make it possible to extend CMAQ to spatially fine-scales. Finer temporal scale may be more difficult. Interface CMAQ when needed with a separate fine-scale (subgrid) model. Pass information between separate CMAQ and fine-scale model.

15 Example Fine-scale CFD “Think Inside the Box” A few example solutions follow: While the example cases do not involve thermal heating, methods have been developed for adding heat fluxes to any grid face or volume. Motion of objects can be added. Particle physics can be added. Chemistry can be added.

16 Fine-scale CFD Modeling of Urban Neighborhoods

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19 Example Wind Field What is the direction of the freestream winds?

20 Example: Winds from Southwest

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23 Surface Winds and with Plume Concentration within Building Arrays

24 Plume Initiated from Different Point Locations - but within an Identical Wind Field.

25 Horizontal Planes - Vertical Velocity

26 Area-averaged * Winds – Urban Canopy Parameterization Wind speed Wind direction * Area-averaged over same horizontal slice-plane shown in the previous slide. Upstream Inlet: Blue

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29 Automobile Microenvironments

30 Modeling Urban Roadways - Including the Vehicle Effects TKEGrid Resolution

31 Modeling Urban Roadways - Including the Vehicle Effects Concentration Wind Velocity

32 SUMMARY STATEMENT CMAQ-like air quality modeling systems may evolve to support the critical needs for modeling human exposures to air pollutants. Continued advances in computing hardware and software make it possible and increasingly more practical to consider extending present CMAQ air quality models to increasingly finer scales. Fine-scale CFD should be interfaced with CMAQ Fine-scale CFD should support CMAQ parameterizations Fine-scale CFD models can also be applied independent of larger scale grid models to support the development of human exposure factors and the human exposure profiles that are dominated by local source emissions.

33 Disclaimer The research presented here was performed under the Memorandum of Understanding between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Commerce's National Oceanic and Atmospheric Administration (NOAA) and under agreement number DW13921548. This work constitutes a contribution to the NOAA Air Quality Program. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their policies or views


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