Introduction to the ISC Model

Marti BladNAU College of Engineering

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Model Overview The Industrial Source Complex (ISC)

model version 3--key regulatory model developed by EPA Gaussian plume model appropriate for

complex mixture of sources Chemical reactions can only be treated in

rudimentary way, thus… Model best applied to non-reactive pollutants

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Model Overview Short-term and long-term versions of ISC3 model

Differ in averaging times available for data output Short-term model also has more sophisticated capabilities for

estimating effects of terrain and deposition

ISC-PRIME Plume Rise Model Enhancements

ISC-AERMOD Based on more-sophisticated treatment of boundary layer

dynamics than possible with Gaussian plume model

GUI Courtesy of Lakes Environmental

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Applications

ISCST3 Model widely used by EPA, state and local environmental agencies

Models effects of various pollution sources Model can calculate average concentrations over

time periods of an hour to a year Appropriate modeling uses include

Demonstrating sufficiency of proposed State Implementation Plans (SIPs) for criteria air pollutants

Predicting air quality impact of new regulated sources Supporting assessment of health impacts of air toxics

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History

Several revisions to model, each adding new capabilities (without changing Gaussian plume assumptions at heart of model) ISCST3 has new

Algorithms for wet and dry deposition Way of simulating area sources Method for simulating complex terrain

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How To Get the Model

Primary source for most up-to-date model is EPA’s Support Center for Regulatory Air Quality Models (SCRAM) website www.epa.gov/ttn/scram

Site includes compiled, executable version of model for running on Microsoft Windows operating system

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How to Get the Model (cont.) EPA version not particularly user-friendly No graphical interface--everything done

with input/output files More user-friendly interfaces designed by

several private vendors To locate, Web search “ISCST3”

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ISC Model outline Screens with multiple tabs for multiple inputs

Control Pathway Source Pathway Receptor Pathway Meteorology Pathway Terrain Grid Pathway Output Pathway

See each piece now in detail

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Pathways in detail Control Pathway

Dispersion options, specify pollutant, averaging times, terrain height options

Source characteristics Source type: point, volume, open pit source release parameters Variable emission rate: season, month, hour Variables for deposition, settling & removal Variable source groups: single, combined

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Pathways in detail (cont.) Receptor Pathway

Network of gridded receptors Cartesian & polar

Where to calculate concentrations Specify discrete receptor location

Flagpole Elevated receptors: terrain above stack base

Plant boundary distances

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Pathways in detail (cont.)

Meteorology Specify met data input files

Station location and other indicators

Anemometer height Wind speed categories Wind profile exponents Vertical temperature gradients Data time period to process

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Pathways in detail (cont.) Terrain Grid

Used to calculate dry depletion in elevated or complex terrain

Output Pathway Summary of high values by receptor

For each averaging period and source group Overall maximum values Find all occurrences over threshold value Plot files

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Site Maps for Modeling One degree DEMs

http://edcwww.cr.usgs.gov/glis/hyper/guide/1_dgr_dem

7.5 degree DEMs http://edcwww.cr.usgs.gov

Format notation DXF. = autoCAD DLG. = USGS digital line graph LULC.= USGS land use and land coverage BMP.= Bitmap images SHP. = ArcView shapefiles

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Dispersion Coefficients

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Met Data Needed for the ISCST3

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Surface Roughness

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Noontime Albedo

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Albedo Values for Model Inputs

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Daytime Bowen Ratios by Land Use

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Parameters not Frequently Seen

Anthropogenic heat flux Surface heating caused by humans Rural = 0.0 Watts/m2

Urban (large) = 20 Watts/m2

Rammet View has many inside program Fraction of net radiation absorbed @ ground

Rural = 0.15 Urban = 0.27

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Other Dispersion Models

Models-3 CMAQ Will provide more advanced chemistry for reactive

pollutants Plume within grid to more realistically simulate

dispersion at multiple scales