1 / 19

Evaluation of an Advanced Reactive Puff Model using Aircraft-based Plume Measurements

Evaluation of an Advanced Reactive Puff Model using Aircraft-based Plume Measurements. Krish Vijayaraghavan, Prakash Karamchandani, Bart Brashers, Shu-Yun Chen, Greg Yarwood, Sue Kemball-Cook ENVIRON International Corporation, Novato, CA Biswanath Chowdhury - Sage Management, Princeton, NJ

thad
Download Presentation

Evaluation of an Advanced Reactive Puff Model using Aircraft-based Plume Measurements

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Evaluation of an Advanced Reactive Puff Model using Aircraft-based PlumeMeasurements Krish Vijayaraghavan, Prakash Karamchandani, Bart Brashers, Shu-Yun Chen, Greg Yarwood, Sue Kemball-Cook ENVIRON International Corporation, Novato, CA Biswanath Chowdhury - Sage Management, Princeton, NJ Eladio Knipping - EPRI, Washington, DC 9th Annual CMAS Conference, October 11-13, 2010 Chapel Hill, North Carolina

  2. Outline • Model Description • Objective • Model Inputs and Application • Aircraft Traverses and Model Receptors • Performance Evaluation • Conclusions and Recommendations

  3. Model Description - SCICHEM • Second-order Closure Integrated Puff model with Chemistry • Three dimensional Lagrangian puff model • Plume is represented as a superposition of a series of 3-D Gaussian puffs • Uses second-order turbulence closure • Dynamic plume-rise calculation based on conservation of energy and momentum • Puff-splitting algorithm allows accurate treatment of wind shear • Puff merging minimizes number of puffs • Efficient adaptive time-step algorithm

  4. Model Description - SCICHEM • Detailed gas-phase photochemistry based on CB-IV • RADM aqueous-phase chemistry scheme • Inorganic aerosol thermodynamics (ISORROPIA) • Secondary Organic Aerosols (SOA) treatment • Sectional PM size distribution with two sections • Optional modal PM size distribution • SCICHEM can use either routine observations of meteorology and concentrations or modeled 3-D fields.

  5. Objective • Evaluate SCICHEM using aircraft observations of the plume from the Dolet Hills power plant in NW Louisiana conducted during the Northeast Texas Air Care (NETAC) 2005 Air Quality Study Source: Baylor University Report

  6. Model Inputs and Application • Simulation performed for 8 September 2005 • Hourly emissions of SO2 and NOx from CAMD • Surface and upper-air meteorology from Shreveport, from NOAA Integrated Surface Hourly Observations DVD (ds3505) and the NOAA ESRL radiosonde database • Fixed wind direction to best match observed plume direction • Constant background chemical environment specified using domain-averages from previous CAMx simulations as well as aircraft data • Stack parameters for Dolet Hills Power Plant (in NW Louisiana near the Texas border) • Height = 160 m • Diameter = 7.6 m • Exit Temperature = 70 C • Exit Velocity = 26 m/s

  7. Aircraft Traverses and Model Receptors

  8. Comparison with Aircraft Measurements

  9. Comparison with Aircraft Measurements

  10. Comparison with Aircraft Measurements

  11. Comparison with Aircraft Measurements

  12. Performance Statistics Ozone

  13. Performance Statistics NOx

  14. Performance Statistics NOy

  15. Performance Statistics SO2

  16. SCICHEM Evaluation in a Prior Application Comparison with helicopter measurements of Cumberland power plant plume Source: Karamchandani et al. 2000. Environ. Sci. Technol., 34, 870-880.

  17. Conclusions and Recommendations • Aircraft observations of plumes provide another dimension to evaluating air quality models • SCICHEM was evaluated using aircraft measurements of a power plant plume along the Louisiana/Texas border • Model performance statistics are good near the stack and generally reasonable farther away. • Model application used readily available data • Need to investigate the effects of meteorology and background pollutant concentrations on predicted peak concentrations: can model performance be improved by using 3-D meteorology and concentration fields?

  18. Acknowledgments This work was conducted under EPRI sponsorship

  19. Questions?

More Related