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Session 8, Unit 15 ISC-PRIME and AERMOD

Session 8, Unit 15 ISC-PRIME and AERMOD. ISC-PRIME. General info. PRIME - P lume Ri se M odel E nhancements Purpose - Enhance ISCST3 by addressing ISCST3’s deficiency in building downwash Development work funded by Electric Power Research Institute (EPRI) in 1992

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Session 8, Unit 15 ISC-PRIME and AERMOD

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  1. Session 8, Unit 15ISC-PRIME and AERMOD

  2. ISC-PRIME • General info. • PRIME - Plume Rise Model Enhancements • Purpose - Enhance ISCST3 by addressing ISCST3’s deficiency in building downwash • Development work funded by Electric Power Research Institute (EPRI) in 1992 • Algorithm developed, codified, and incorporated into ISCST3 by Earth Tech, Inc. The combined computer program is called ISC-PRIME

  3. ISC-PRIME • Deficiency of ISC3 model • Reported over predictions under light wind, stable conditions • Discontinuities in the vertical, alongwind, and crosswind directions • Assumption that the source is always collocated with the structure causing down washing • Streamline flow over a structure is not taken into account • Plume rise is not adjusted due to the velocity deficit in the wake or due to vertical wind speed shear • Concentrations in the cavity region are not linked to material capture

  4. ISC-PRIME • The features that ISC-PRIME has and ISCST3 does not: • Stack location with respect to building • Influence of streamline deflection on plume trajectory • Effect of wind angle on wake structure • Effects of plume buoyancy and vertical wind speed shear on plume rise near building • Concentration in near wake (cavity)

  5. ISC-PRIME • PRIME Approach • Trajectory of plume near building is determined by 2 factors: • Descent of the air containing the plume material • Rise of the plume relative to the streamlines due to buoyancy or momentum effects • Mean streamlines near building • Initial ascending upwind of the building • location and maximum height of roof-top recirculation cavity • length of downwind recirculation cavity (near wake) • Building length scale

  6. ISC-PRIME • Running ISC-PRIME • Same way to run ISCST3 with exception of the following three additional keyword in the “SO” pathway: • BUILDLEN - projected length of the building along the flow • XBADJ - along-flow distance from the stack to the center of the upwind face of the projected building • YBADJ - across-flow distance from the stack to the center of the upwind face of the projected building • BPIP is modified (called BPIP-PRIME) to produce these parameters

  7. ISC-PRIME • Independent evaluation by ENSR • Evaluation was based on 14 studies • 8 tracer studies • 3 long-term studies • 3 wind tunnel studies

  8. ISC-PRIME • Evaluation results: • ISC-PRIME is generally unbiased or conservative (overpredicting) • Statistically ISC-PRIME performs better than ISCST3 • Under stable conditions, ISCST3 is too conservative and ISC-PRIME is much better • Under neutral conditions, the two models are comparable and ISC-PRIME is slightly better.

  9. ISC-PRIME • Results of evaluation by EPA • When no building data is included in the models, ISCST3 and ISC-PRIME produce the same results • ISC-PRIME tend to be less conservative than ISCST3, but more conservative than observed values • The results of the two model converge beyond 1 km, and become practically the same after 10 km • Generally agree with ENSR’s evaluation and consider the objectives of PRIME have been met

  10. AERMOD • AERMIC – American Meteorological Society/Environmental Protection Agency Regulatory Model Improvement Committee • AERMOD – AMS/EPA Regulatory Model • Goals of AERMOD – To replace ISC3 (AERMOD has not incorporated the dry and wet deposition features of ISC3) • AERMOD is still a steady-state model, but a more sophisticated one than ISC3

  11. AERMOD • New or improved algorithms: • Dispersion in both the convective and stable boundary layers (separate procedures are used for CBL and SBL) • Plume rise and buoyancy • Plume penetration into elevated inversions • Computation of vertical profiles of wind, turbulence, and temperature • The urban boundary layer • The treatment of receptors on all types of terrain from the surface up to and above the plume height.

  12. AERMOD • AERMOD is a modeling system consisting of: • AERMOD - AERMIC Dispersion Model • AERMAP – AERMOD Terrain Preprocessor • AERMET - AERMOD Meteorological Preprocessor

  13. AERMOD • Data flow in AERMOD system

  14. AERMOD • AERMET • Use met measurements to compute PBL parameters • Monin-Obukhov Length, L • Surface friction velocity, u* • Surface roughness length, z0 • Surface heat flux, H • Convective scaling velocity, w* • Convective and mechanical mixed layer heights, zic and zim, respectively

  15. AERMOD • Met interface • Compute vertical profiles of: • Wind direction • Wind speed • Temperature • Vertical potential temperature gradient • Vertical turbulence (w) • Horizontal turbulence (v) • Unlike ISC3, both w and v have more than 1 component • Express inhomogeneous parameters in PBL as effective homogeneous values

  16. AERMOD • AERMAP

  17. AERMOD • Treatment of terrain • No distinction between simple terrain and complex terrain • Plume either impacts the terrain or/and follows the flow

  18. AERMOD

  19. AERMOD

  20. AERMOD • Calculation of concentrations • Simulate 5 plume types • Direct (real source at the stack) • Indirect (imaginary source above CBL to account for slow downward dispersion) • Penetrated (the portion of the plume that has penetrated into the stable layer) • Injected • Stable.

  21. AERMOD • For CBL, contributions from 3 types of plume • For SBL, similar to ISC3

  22. AERMOD • Dispersion coefficients • Contributed by three factors: • ambient turbulence • Turbulence induced by a plume buoyancy • Enhancements from building wake effects • Plume rise • Source characterization • Added feature – irregularly shaped area sources • Adjustment for urban boundary layer • For nighttime only

  23. AERMOD • Evaluation • Scientifically AERMOD has an advantage over ISC3 • Performance evaluation: • Data: • 4 short-term tracer study • 6 conventional long-term monitoring • Results (after minor revisions): • Nearly unbiased • Generally better than ISCST3 • Recommended for regulatory applications (rule proposed)

  24. Session 8, Unit 16CALPUFF

  25. ISC3, AERMOD Steady-sate Plume Local-scale CALPUFF Non-steady-state Puff Long-range (up to hundreds of kilometers) Can simulate ISC3 CALPUFF

  26. CALPUFF • Recommended by IWAQM • IWAQM – Interagency Workgroup on Air Quality Modeling • EPA • U.S. Forest Service • National Park Service • U.S. Fish and Wildlife Service

  27. CALPUFF • CALPUFF System Prepare meteorological fields. It generates hourly wind and temperature fields on a 3-D gridded modeling domain. CALMET A Gaussian puff dispersion model with chemical removal, wet & dry deposition, complex terrain algorithm, building downwash, plume fumigation, and other effects CALPUFF Postprocessing programs for the output fields of met data, concentrations, deposition fluxes, and visibility data CALPOST

  28. CALPUFF • CALMET process • Step 1 – Initial guess wind field is adjusted for kinematic effects of terrain, slope flows, terrain blocking effects • Step 2 – Introduce observational data into Step 1 wind field to produce final wind field

  29. CALPUFF • CALMET data requirements • Surface met data (wind, temp, precipitation, etc.) • Upper air data (e.g., observed vertical profiles of wind, temp, etc.) • Overwater observed data (optional) • Geophysical data (e.g., terrain, land use, etc.)

  30. CALPUFF • Example CALMET wind field

  31. CALPUFF • CALPUFF concept and solutions • Plume is treated as series of puffs • Snapshot approach • Sampling time – time interval between snapshots • Concentrations at receptors are determined at the snapshot time. One receptors may receive contributions from more than 1 puff • Puffs may move and evolve in size between snapshots • Separation between puffs: <1-2 . Otherwise, results are not accurate • Problems – too many puffs (e.g., thousands puffs/hr) • Solutions • 1. Radially symmetric puffs, OR • 2. Non-circular puff (slug)

  32. CALPUFF • Other CALPUFF features • Dispersion (dispersion coefficients, buoyancy-induced dispersion, puff splitting, etc.) • Building downwash • Plume rise • Overwater and coastal dispersion • Complex terrain • Dry and wet deposition • Chemical reaction • Visibility modeling • Odor modeling • Graphic User Interface (GUI)

  33. CALPUFF • CALPUFF data and computer requirements • Up to 16 input files (control, met, geophysical, source, etc.) • Up to 9 output files • Computer requirements: • Memory: typical case – 32 MB; more for more sources • Computing time: for a 500 MHz PC, 218 sources and 425 receptors • 9 hours for CALMET • 95 hours for CALPUFF

  34. CALPUFF • Summary • Primarily for long range modeling, but can be used for local modeling • A puff model • Non-steady state • Very sophisticated • Resource intensive

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