dispersion modeling 101

Dispersion Modeling 101:Dispersion Modeling 101:ISCST3 vs. AERMODISCST3 vs. AERMOD

Iowa Chapter AWMAIowa Chapter AWMAFebruary 14, 2006February 14, 2006

Mick DurhamMick Durham

Stanley Consultants, IncStanley Consultants, Inc..

What we are going to talk aboutWhat we are going to talk about

Brief History of Dispersion ModelingBrief History of Dispersion Modeling Industrial Source Complex ModelIndustrial Source Complex Model AMS/EPA Regulatory Model (AERMOD)AMS/EPA Regulatory Model (AERMOD) ComparisonsComparisons The IDNR ConnectionThe IDNR Connection Questions & AnswersQuestions & Answers

Brief History of ModelingBrief History of Modeling

Earliest Studies Simulated the Movement of AirEarliest Studies Simulated the Movement of Air– G.I. Taylor, 1915, Eddy Motion in the AtmosphereG.I. Taylor, 1915, Eddy Motion in the Atmosphere

– O.G. Sutton, 1932, A Theory of Eddy DiffusionO.G. Sutton, 1932, A Theory of Eddy Diffusion

Dispersion of Pollutants (Mainly Particulate) Dispersion of Pollutants (Mainly Particulate) Followed WW IIFollowed WW II– E.W. Hewson, 1945, Meteorological Control of E.W. Hewson, 1945, Meteorological Control of

Atmospheric Pollutants by Heavy IndustryAtmospheric Pollutants by Heavy Industry

– E.W. Hewson, 1955, Stack Heights Required to Minimize E.W. Hewson, 1955, Stack Heights Required to Minimize Ground Level ConcentrationsGround Level Concentrations

– Gale, Stewart & Crooks, 1958, The Atmospheric Diffusion Gale, Stewart & Crooks, 1958, The Atmospheric Diffusion of Gases Discharged from a Chimneyof Gases Discharged from a Chimney


Birth of Dispersion ParametersBirth of Dispersion Parameters– F.A. Gifford, 1960, Atmospheric Dispersion Calculations F.A. Gifford, 1960, Atmospheric Dispersion Calculations

Using the Gaussian Plume ModelUsing the Gaussian Plume Model– F. Pasquill, 1961, The Estimation of the Dispersion of F. Pasquill, 1961, The Estimation of the Dispersion of

Windborne MaterialWindborne Material– D. Bruce Turner, 1967, Workbook on Atmospheric D. Bruce Turner, 1967, Workbook on Atmospheric

Dispersion EstimatesDispersion Estimates– Briggs, Gary, 1969, Plume RiseBriggs, Gary, 1969, Plume Rise

Brief History of ModelingBrief History of Modeling Modeling and the Computer AgeModeling and the Computer Age

– PTMAX, PTMIN, PTMTP, 1972PTMAX, PTMIN, PTMTP, 1972– Air Quality Display Model (AQDM), 1974Air Quality Display Model (AQDM), 1974– Single Source (CRSTER) Model, 1977Single Source (CRSTER) Model, 1977– Complex Terrain (VALLEY) Model, 1977Complex Terrain (VALLEY) Model, 1977– Multiple Source (MPTER) Model, 1980Multiple Source (MPTER) Model, 1980

Pollutant and Environment Specific ModelsPollutant and Environment Specific Models– APRAC, CALINE, HIWAY Carbon Monoxide ModelsAPRAC, CALINE, HIWAY Carbon Monoxide Models– BLP (Bouyant Line and Point Sources); PAL (Point Area and BLP (Bouyant Line and Point Sources); PAL (Point Area and

Line Source), 1979; TEM (Texas Episode for Urban Areas)Line Source), 1979; TEM (Texas Episode for Urban Areas)– RPM (Reactive Plume Model) for Ozone, 1980RPM (Reactive Plume Model) for Ozone, 1980


Guideline on Air Quality ModelsGuideline on Air Quality Models– The Guidelines on Air Quality Models, 1978The Guidelines on Air Quality Models, 1978– 40 CFR Part 58, Appendix W40 CFR Part 58, Appendix W

Refined and More Complex ModelsRefined and More Complex Models– Industrial Source Complex (ISC), 1979Industrial Source Complex (ISC), 1979

Industrial Short-Term STIndustrial Short-Term ST Industrial Long-Term LTIndustrial Long-Term LT

– Complex Terrain (COMPLEX)Complex Terrain (COMPLEX)– Dense Gas (DEGADIS)Dense Gas (DEGADIS)– Urban Airshed Model (UAM)Urban Airshed Model (UAM)


Refined and More Complex Models (cont.)Refined and More Complex Models (cont.)– Screening Model (SCREEN)Screening Model (SCREEN)– California Line Source (CALINE) and Mobile California Line Source (CALINE) and Mobile

Source Emission Factors (MOBILE)Source Emission Factors (MOBILE)– Puff Models (INPUFF)Puff Models (INPUFF)– Visibility (VISCREEN)Visibility (VISCREEN)


Advanced ModelsAdvanced Models– Industrial Source Complex Version 2 (ISC2), 1990Industrial Source Complex Version 2 (ISC2), 1990– Industrial Source Complex Version 3 (ISC3), 1995Industrial Source Complex Version 3 (ISC3), 1995– California Line Source (CAL3QH3)California Line Source (CAL3QH3)– Urban Airshed Model (UAM-V)Urban Airshed Model (UAM-V)– Complex Terrain Dispersion Model (CTDMPLUS)Complex Terrain Dispersion Model (CTDMPLUS)– Offshore and Coastal Dispersion Model (OCD)Offshore and Coastal Dispersion Model (OCD)– Bouyant Line and Point Source (BLP)Bouyant Line and Point Source (BLP)– Area Locations of Hazardous Atmospheres (ALOHA)Area Locations of Hazardous Atmospheres (ALOHA)– Dense Gas Dispersion Model (DEGADIS 2.1)Dense Gas Dispersion Model (DEGADIS 2.1)


Today’s Models:Today’s Models:– AERMODAERMOD

Point, Area, Line Sources Point, Area, Line Sources Simple or Complex TerrainSimple or Complex Terrain Transport distance up to 50 kmTransport distance up to 50 km

– CALPUFFCALPUFF Transport from 50 to hundreds of kilometersTransport from 50 to hundreds of kilometers Visibility, Regional HazeVisibility, Regional Haze Dispersion in Complex TerrainDispersion in Complex Terrain

– Complex Dispersion Model Plus Algorithms for Unstable Complex Dispersion Model Plus Algorithms for Unstable Conditions (CTDMPLUSS)Conditions (CTDMPLUSS) Dispersion in Complex TerrainDispersion in Complex Terrain


Today’s Models Today’s Models (Continued):(Continued):

– Caline3 or CAL3QHC, MOBILE6Caline3 or CAL3QHC, MOBILE6 Highway Line sourcesHighway Line sources Simple TerrainSimple Terrain Carbon MonoxideCarbon Monoxide

– Buoyant Line and Point Source (BLP)Buoyant Line and Point Source (BLP) Aluminum Reduction plants with buoyant line and point sourcesAluminum Reduction plants with buoyant line and point sources Rural locationRural location Simple TerrainSimple Terrain

– Community Multi-scale Air Quality Model (CMAQ)Community Multi-scale Air Quality Model (CMAQ) OzoneOzone

Industrial Source Complex ModelIndustrial Source Complex Model

Introduced in 1979Introduced in 1979 First adopted as Preferred Model in 1983First adopted as Preferred Model in 1983 Major Revisions 4 times in 27 year history Major Revisions 4 times in 27 year history Can remain acceptable as a preferred Can remain acceptable as a preferred

model until November 9, 2006model until November 9, 2006


Gaussian Plume ModelGaussian Plume Model Building DownwashBuilding Downwash Particulate DepositionParticulate Deposition Point, Area, and Line SourcesPoint, Area, and Line Sources Complex TerrainComplex Terrain Simple Meteorological Data InputSimple Meteorological Data Input


Has been primary model in Iowa for 27 Has been primary model in Iowa for 27 yearsyears

Over 100 facilities have modeled Over 100 facilities have modeled compliance with ISCcompliance with ISC

Generally the short-term standards have Generally the short-term standards have caused greatest predicted non-compliance caused greatest predicted non-compliance


Problems with ISCST3:– Modeling of Plume Dispersion is Crude– Only 6 possible states (Stability Classes)– No variation in most meteorological variables with height– No use of observed turbulence data– No information about surface characteristics– Erroneous depiction of dispersion in convective

conditions– Substantial overprediction in complex terrain– Crude building downwash algorithm

AERMODAERMOD

AERMODAERMOD stands for stands for AAmerican merican Meteorological Society/ Meteorological Society/ EEnvironmental nvironmental Protection Agency Protection Agency RRegulatory egulatory ModModelel

Formally Proposed as replacement for ISC Formally Proposed as replacement for ISC in 2000in 2000

Adopted as Preferred Model November 9, Adopted as Preferred Model November 9, 20052005

AERMODAERMOD 3 COMPONENTS3 COMPONENTS

– AERMETAERMET – THE METEOROLOGICAL PREPROCESOR – THE METEOROLOGICAL PREPROCESOR

– AERMAPAERMAP – THE TERRAIN DATA PREPROCESSOR – THE TERRAIN DATA PREPROCESSOR

– AERMODAERMOD – THE DISPERSION MODEL – THE DISPERSION MODEL

2 SUPPORT TOOLS2 SUPPORT TOOLS

– AERSURFACEAERSURFACE – PROCESSES SURFACE CHARACTERISTICS DATA – PROCESSES SURFACE CHARACTERISTICS DATA

– AERSCREENAERSCREEN – PROVIDES A SCREENING TOOL – PROVIDES A SCREENING TOOL

AERMODAERMOD

AERMOD IS SIMILAR TO ISC IN SETUPAERMOD IS SIMILAR TO ISC IN SETUP

– THE CONTROL FILE STRUCTURE IS THE THE CONTROL FILE STRUCTURE IS THE SAMESAME

– VIRTUALLY ALL THE CONTROL KEYWORDS VIRTUALLY ALL THE CONTROL KEYWORDS AND OPTIONS ARE THE SAMEAND OPTIONS ARE THE SAME

AERMODAERMOD

AERMOD IS DIFFERENT FROM ISCAERMOD IS DIFFERENT FROM ISC

– REQUIRES SURFACE CHARACTERISTICS (ALBEDO, REQUIRES SURFACE CHARACTERISTICS (ALBEDO, BOWEN RATIO, SURFACE ROUGHNESS) IN BOWEN RATIO, SURFACE ROUGHNESS) IN AERMETAERMET

– HAS PRIME FOR BUILDING DOWNWASH AND THE HAS PRIME FOR BUILDING DOWNWASH AND THE BUILDING PARAMETERS ARE MORE EXTENSIVEBUILDING PARAMETERS ARE MORE EXTENSIVE

– REQUIRES LONGER COMPUTER RUN TIMES (up to REQUIRES LONGER COMPUTER RUN TIMES (up to 5 times longer!)5 times longer!)

Comparison of Dispersion Model Features:Meteorological Data Input

– ISCST3:• One level of data accepted

– AERMOD:• An arbitrarily large number of data levels can be

accommodated

Comparison of Dispersion Model Features:Plume Dispersion and Plume Growth Rates

ISCST3:• Based upon six discrete stability classes only• Dispersion curves are Pasquill-Gifford• Choice of rural or urban surfaces only

AERMOD:• Uses profiles of vertical and horizontal turbulence

variable with height• Uses continuous growth function• Uses many variations of surface characteristics

Comparison of Dispersion Model Features:Complex Terrain Modeling

ISCST3:

• Elevation of each receptor point input

• Predictions are very conservative in complex terrain

AERMOD:

• Controlling hill elevation and point elevation at each receptor are input

• Predictions are nearly unbiased in complex terrain

Comparisons ISC Vs AERMODComparisons ISC Vs AERMOD

CONSEQUENCE ANALYSIS - ratios of AERMOD predicted high concentrations to ISCST3 predicted high concentrations:

flat and simple terrain point, volume and area sources.

1hour 3hour 24hour annual

average 1.04 1.09 1.14 1.33 high 4.25 2.82 3.15 3.89low 0.32 0.26 0.24 0.30

Total 48 48 48 48

– AN OVERVIEW FOR THE 8AN OVERVIEW FOR THE 8THTH MODELING CONFERENCE SEPTEMBER 22, 2005 MODELING CONFERENCE SEPTEMBER 22, 2005

Comparisons ISC Vs AERMODComparisons ISC Vs AERMODCONSEQUENCE ANALYSIS - ratios of AERMOD predicted high concentrations to ISCST3

(and PRIME) predicted high concentrations:

flat terrain point sources with significant bldg downwash

ANNUAL 24 H2H 3 H2H

AER/ISC3 AER/ISCP AER/ISC3 AER/ISCP AER/ISC3 AER/ISCP ave 1.08 1.05 1.25 1.01 0.71 1.05 max 1.35 1.29 1.87 1.14 1.20 1.17 min 0.69 0.79 0.69 0.84 0.38 0.93No cases 6 6 6

– AN OVERVIEW FOR THE 8AN OVERVIEW FOR THE 8THTH MODELING CONFERENCE SEPTEMBER 22, 2005 MODELING CONFERENCE SEPTEMBER 22, 2005


– Duane Arnold Energy Center Data (Palo, IA)Duane Arnold Energy Center Data (Palo, IA)– Ratio of Modeled Conc to Observed:Ratio of Modeled Conc to Observed:

AERMOD: 0.69 (1-hr avg 46m release)AERMOD: 0.69 (1-hr avg 46m release) ISC-Prime: 0.76 (1-hr avg 46m release)ISC-Prime: 0.76 (1-hr avg 46m release)




Presentation at EUEC conference by Bob Paine, Presentation at EUEC conference by Bob Paine, TRC:TRC:

AERMOD consistently showed better or comparable performance with ISCST3

In flat terrain, AERMOD and ISCST3 predictions are comparable, but AERMOD has higher annual averages

In complex terrain, AERMOD predictions are markedly lower

Building downwash predictions will often be lower, especially for stacks located some distance from controlling buildings

Overall, more confidence in accuracy of AERMOD results


Our Recent Experience:Our Recent Experience:– Annual concentrations higher with AERMOD by Annual concentrations higher with AERMOD by

10-15%10-15%– Short term concentrations similar without Short term concentrations similar without

downwashdownwash– Short-term concentrations generally lower with Short-term concentrations generally lower with

building downwash by 20%building downwash by 20%

The IDNR ConnectionThe IDNR Connection

IDNR will allow use of either ISCST3 or IDNR will allow use of either ISCST3 or AERMOD until November 9, 2006AERMOD until November 9, 2006

Meteorological Data will be provided by Meteorological Data will be provided by IDNR for eight stationsIDNR for eight stations

Compliance with ISCST3 and non-Compliance with ISCST3 and non-compliance by AERMOD must be compliance by AERMOD must be addressedaddressed

Questions & AnswersQuestions & Answers

AERMODAERMODFeature ISCST3 AERMOD Comments Types of Sources

Point, Area, Volume Point, Area, Volume Models are Comparable

Plume Rise Uses Briggs equations with Stack-top wind speed and vertical temp gradient

In stable use Briggs In convective uses random convective velocities

AERMOD superior in accounting for convective updrafts and downdrafts

Met Data Input One level of data accepted

An arbitrarily large number of data levels can be accommodated

AERMOD can adapt multiple levels of data to various stack and plume heights

Profiling Met Data

Only wind speed is profiled

Creates profiles for wind, temperature and turbulence

More accurate portrayal of actual conditions

Plume Dispersion

Gaussian treatment in horizontal and vertical

Same for stable only; non-Gaussian probability density in vertical for unstable conditions

More accurate portrayal of actual conditions

Urban Treatment

Urban option either on or off

Population is specified so treatment can consider a variety of urban conditions; sources can individually be modeled urban or rural

More options to depicts urban characteristics

AERMODAERMODFeature ISCST3 AERMOD Comments Surface Characteristics

Choice of rural of urban

Selection by direction and month of roughness length, albedo, and Bowen ratio

Provide significantly more options in selecting sfc characteristics

Boundary Layer

Wind speed, mixing height, and stability class

Five update methodologies for improved boundary layer interpretation

Provides parameters for use with up-to-date planetary boundary layer parameterization

Mixed layer Height

Holzworth, based on afternoon mixing ht

Has convective and mechanical mixing layer ht based upon sensible heat flux

Provides more realistic sequence of the diurnal mixing height changes

Terrain Depiction

Elevation at each receptor point

Controlling hill elevation and point elevation at each receptor using DEM data

Uses digital data for terrain heights and preprocessor (AERMAP) advanced streamline algorithms

AERMODAERMODFeature ISCST3 AERMOD Comments Plume Growth Rates

Pasquill-Gifford dispersion curves and 6 stability classes

Uses profiles of vertical and horizontal turbulence; variable with height;

Turbulence- based plume growth with height superior to 6 classes

Plume Interaction with Mixing Lid - Convective

If plume is above lid zero concentration on ground

Three plume components: updrafts, downdrafts, and stable layer dispersion

Avoids potential under-prediction due to all of nothing approach

Plume Interaction with Mixing Lid - Stable

Mechanical lid is ignored; assumed infinitely high

Mechanical mixing layer near surface; plume reflection from elevated lid

Advancement over simplistic ISC approach

Building Downwash

Combination Huber-Snyder and Scire-Schulman algorithms; many discontinuities

New PRIME downwash algorithms

AERMOD benefits from tech advances of PRIME

dispersion modeling 101

Documents

arbitrarily

air quality

urban airshed

modeling todays

dispersion

plume dispersion

data levels

complex terrain