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Case Studies in Air Dispersion Modeling for Young Professionals

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Background on:
-origin of air quality regulations
-Gaussian models
-AERMOD
-Case study for an Aluminum Manufacturing Facilty

Published in: Engineering
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Case Studies in Air Dispersion Modeling for Young Professionals

  1. 1. Sergio Guerra, PhD | GHD A&WMA’s 112th Annual Conference & Exhibition Quebec City, Canada June 26, 2019 Case Studies in Air Dispersion Modeling for Young Professionals
  2. 2. Why do we regulate the air? • In December 1930, 63 people died in Belgium's Meuse Valley during a five-day fog; most of the deaths occurring on the fourth and fifth days. • In October 1948, a thick cloud of air pollution formed above the industrial town of Donora, Pennsylvania. The cloud which lingered for five days, killed 20 people and caused sickness in 6,000 of the town's 14,000 people. • In 1952, over 3,000 people died in what became known as London's "Killer Fog." The smog was so thick that buses could not run without guides walking ahead of them carrying lanterns.
  3. 3. Why do we regulate the air?
  4. 4. Dispersion Modeling • A series of equations that mathematically describe pollutant behavior in the atmosphere • Can be simple or complex depending on the assumptions and mathematical equations used • Is a tool used in air permitting to ensure that the air quality will not be compromised • Based on best available science • Performance is evaluated for specific scenarios • Like any other numerical tool it has its limitations
  5. 5. What are the Reasons to Model? • Regulatory purposes • Design purposes • Health • Ecology
  6. 6. AERMOD “A steady-state plume model that incorporates air dispersion based on planetary boundary layer turbulence structure and scaling concepts, including treatment of both surface and elevated sources, and both simple and complex terrain.” SCRAM web site: www.epa.gov/scram001/dispersion_prefrec.htm
  7. 7. Gaussian Distribution ⋅                 −= 2 2 1 exp y y Value σ1.0 0.5
  8. 8. Plume Rise Example Result INPUTS Hb = 40 m Hs = 90 m Ve = 5 m/s Ts = 430K Ta = 279K d = 2.1 m Neutral stability
  9. 9. Horizontal and Vertical Dispersion x y z σz hs+hr σy /σz vary with: - Downwind distance - Surface roughness - Ambient turbulence levels - Atmospheric stability - Urban or rural - Building downwash
  10. 10. Inputs BPIPBuilding Geometry Meteorological Data Terrain Data AERMET AERMAP Operating ParametersOperating Parameters AERMOD
  11. 11. Source Types Point source Volume source Area source Line source Open pit
  12. 12. Case Study: Aluminum Manufacturing Facility • Existing melting furnace exists with a baghouse: BH1 • Adding 2 new melting furnaces: MELT1 and MELT2 • Evaluating PM2.5 24-hr standard • NAAQS is 35 ug/m3 YP Panel on Dispersion Modeling Emission Unit PM2.5 Emission Rate BH1 0.7 lb/hr MELT1 1.5 lb/hr MELT2 1.5 lb/hr
  13. 13. Cases Evaluated Case Description 1 Base case 2 MELT1 and MELT2 routed to BG with 95% control efficiency 3 MELT1 and MELT2 w/o BH and Relocated to North Building 4 Same as #3 but with restricted access road YP Panel on Dispersion Modeling
  14. 14. Definition of Ambient Air “that portion of the atmosphere, external to buildings, to which the general public has access.” 40 CFR § 50.1(e) YP Panel on Dispersion Modeling
  15. 15. Base Case Max Rec is 35.9 ug/m3 YP Panel on Dispersion Modeling
  16. 16. Add new Bag Houses to MELT1 and MELT2 Max Rec is 4.6 ug/m3 YP Panel on Dispersion Modeling
  17. 17. Relocate MELT1 and MELT2 (no Baghouse) Max Rec is 21.3 ug/m3 YP Panel on Dispersion Modeling
  18. 18. Relocate MELT1 and MELT2 and add guard shack Max Rec is 17.5 ug/m3 YP Panel on Dispersion Modeling
  19. 19. Results Modeled Conc (ug/m3) Background (ug/m3) Total (ug/m3) Percent of 24-hr NAAQS Case 1 35.9 17 52.9 151% Case 2 4.6 21.6 62% Case 3 21.3 38.3 109% Case 4 17.5 34.5 99% YP Panel on Dispersion Modeling
  20. 20. Sergio A. Guerra, PhD sergio.guerra@ghd.com Office: 720 974 0935 Questions YP Panel on Dispersion Modeling
  21. 21. www.ghd.com YP Panel on Dispersion Modeling

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