Session 8, Unit 15

ISC-PRIME and AERMOD

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

ISC-PRIMEDeficiency 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

ISC-PRIMEThe 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)

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

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

ISC-PRIME

Independent evaluation by ENSR Evaluation was based on 14 studies

8 tracer studies 3 long-term studies 3 wind tunnel studies

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.

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

AERMOD

AERMIC – American Meteorological Society/Environmental Protection Agency Regulatory Model Improvement CommitteeAERMOD – AMS/EPA Regulatory ModelGoals 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

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.

AERMOD

AERMOD is a modeling system consisting of: AERMOD - AERMIC Dispersion Model AERMAP – AERMOD Terrain

Preprocessor AERMET - AERMOD Meteorological

Preprocessor

AERMOD

Data flow in AERMOD system

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

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

AERMOD

AERMAP

AERMOD

Treatment of terrain No distinction between simple terrain

and complex terrain Plume either impacts the terrain

or/and follows the flow

AERMOD

AERMOD

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.

AERMOD For CBL, contributions from 3 types of plume

For SBL, similar to ISC3

AERMOD

Dispersion coefficients Contributed by three factors:

ambient turbulence Turbulence induced by a plume buoyancy Enhancements from building wake effects

Plume riseSource characterization Added feature – irregularly shaped area

sources

Adjustment for urban boundary layer For nighttime only

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)

Session 8, Unit 16

CALPUFF

CALPUFF

ISC3, AERMOD Steady-sate Plume Local-scale

CALPUFF Non-steady-state Puff Long-range (up to

hundreds of kilometers)

Can simulate ISC3

CALPUFF

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

CALPUFF

CALPUFF System

CALMET

CALPUFF

CALPOST

Prepare meteorological fields. It generates hourly wind and temperature fields on a 3-D gridded modeling domain.

A Gaussian puff dispersion model with chemical removal, wet & dry deposition, complex terrain algorithm, building downwash, plume fumigation, and other effects

Postprocessing programs for the output fields of met data, concentrations, deposition fluxes, and visibility data

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

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.)

CALPUFF

Example CALMET wind field

400 420 440 460 480 500 520 540 560 580

U T M E astin g (k m )

4 ,1 30

4 ,1 50

4 ,1 70

4 ,1 90

4 ,2 10

4 ,2 30

UT

M N

orth

ing

(km

)

CALPUFFCALPUFF 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)

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)

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

CALPUFF

Summary Primarily for long range modeling, but

can be used for local modeling A puff model Non-steady state Very sophisticated Resource intensive