Session 8, Unit 15 ISC-PRIME and AERMOD

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

• General info.
• PRIME - Plume Rise Model Enhancements
• Purpose - Enhance ISCST3 by addressing ISCST3s
  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

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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

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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)

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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

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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

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ISC-PRIME

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

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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.

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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 ENSRs evaluation and
  consider the objectives of PRIME have been met

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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

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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.

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AERMOD

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

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AERMOD

• Data flow in AERMOD system

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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

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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

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AERMOD

• AERMAP

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AERMOD

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

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AERMOD
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AERMOD
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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.

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AERMOD

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

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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

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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)

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Session 8, Unit 16CALPUFF
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CALPUFF

• ISC3, AERMOD
• Steady-sate
• Plume
• Local-scale

• CALPUFF
• Non-steady-state
• Puff
• Long-range (up to hundreds of kilometers)
• Can simulate ISC3

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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

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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
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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

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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.)

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CALPUFF

• Example CALMET wind field

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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 lt1-2 ?. 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)

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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)

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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

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CALPUFF

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