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Dispersion Modeling 101: ISCST3 vs. AERMOD

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Title: Dispersion Modeling 101: ISCST3 vs. AERMOD


1
Dispersion Modeling 101ISCST3 vs. AERMOD
  • Iowa Chapter AWMA
  • February 14, 2006
  • Mick Durham
  • Stanley Consultants, Inc.

2
What we are going to talk about
  • Brief History of Dispersion Modeling
  • Industrial Source Complex Model
  • AMS/EPA Regulatory Model (AERMOD)
  • Comparisons
  • The IDNR Connection
  • Questions Answers

3
Brief History of Modeling
  • Earliest Studies Simulated the Movement of Air
  • G.I. Taylor, 1915, Eddy Motion in the Atmosphere
  • O.G. Sutton, 1932, A Theory of Eddy Diffusion
  • Dispersion of Pollutants (Mainly Particulate)
    Followed WW II
  • E.W. Hewson, 1945, Meteorological Control of
    Atmospheric Pollutants by Heavy Industry
  • E.W. Hewson, 1955, Stack Heights Required to
    Minimize Ground Level Concentrations
  • Gale, Stewart Crooks, 1958, The Atmospheric
    Diffusion of Gases Discharged from a Chimney

4
Brief History of Modeling
  • Birth of Dispersion Parameters
  • F.A. Gifford, 1960, Atmospheric Dispersion
    Calculations Using the Gaussian Plume Model
  • F. Pasquill, 1961, The Estimation of the
    Dispersion of Windborne Material
  • D. Bruce Turner, 1967, Workbook on Atmospheric
    Dispersion Estimates
  • Briggs, Gary, 1969, Plume Rise

5
Brief History of Modeling
  • Modeling and the Computer Age
  • PTMAX, PTMIN, PTMTP, 1972
  • Air Quality Display Model (AQDM), 1974
  • Single Source (CRSTER) Model, 1977
  • Complex Terrain (VALLEY) Model, 1977
  • Multiple Source (MPTER) Model, 1980
  • Pollutant and Environment Specific Models
  • APRAC, CALINE, HIWAY Carbon Monoxide Models
  • BLP (Bouyant Line and Point Sources) PAL (Point
    Area and Line Source), 1979 TEM (Texas Episode
    for Urban Areas)
  • RPM (Reactive Plume Model) for Ozone, 1980

6
Brief History of Modeling
  • Guideline on Air Quality Models
  • The Guidelines on Air Quality Models, 1978
  • 40 CFR Part 58, Appendix W
  • Refined and More Complex Models
  • Industrial Source Complex (ISC), 1979
  • Industrial Short-Term ST
  • Industrial Long-Term LT
  • Complex Terrain (COMPLEX)
  • Dense Gas (DEGADIS)
  • Urban Airshed Model (UAM)

7
Brief History of Modeling
  • Refined and More Complex Models (cont.)
  • Screening Model (SCREEN)
  • California Line Source (CALINE) and Mobile Source
    Emission Factors (MOBILE)
  • Puff Models (INPUFF)
  • Visibility (VISCREEN)

8
Brief History of Modeling
  • Advanced Models
  • Industrial Source Complex Version 2 (ISC2), 1990
  • Industrial Source Complex Version 3 (ISC3), 1995
  • California Line Source (CAL3QH3)
  • Urban Airshed Model (UAM-V)
  • Complex Terrain Dispersion Model (CTDMPLUS)
  • Offshore and Coastal Dispersion Model (OCD)
  • Bouyant Line and Point Source (BLP)
  • Area Locations of Hazardous Atmospheres (ALOHA)
  • Dense Gas Dispersion Model (DEGADIS 2.1)

9
Brief History of Modeling
  • Todays Models
  • AERMOD
  • Point, Area, Line Sources
  • Simple or Complex Terrain
  • Transport distance up to 50 km
  • CALPUFF
  • Transport from 50 to hundreds of kilometers
  • Visibility, Regional Haze
  • Dispersion in Complex Terrain
  • Complex Dispersion Model Plus Algorithms for
    Unstable Conditions (CTDMPLUSS)
  • Dispersion in Complex Terrain

10
Brief History of Modeling
  • Todays Models (Continued)
  • Caline3 or CAL3QHC, MOBILE6
  • Highway Line sources
  • Simple Terrain
  • Carbon Monoxide
  • Buoyant Line and Point Source (BLP)
  • Aluminum Reduction plants with buoyant line and
    point sources
  • Rural location
  • Simple Terrain
  • Community Multi-scale Air Quality Model (CMAQ)
  • Ozone

11
Industrial Source Complex Model
  • Introduced in 1979
  • First adopted as Preferred Model in 1983
  • Major Revisions 4 times in 27 year history
  • Can remain acceptable as a preferred model until
    November 9, 2006

12
Industrial Source Complex Model
  • Gaussian Plume Model
  • Building Downwash
  • Particulate Deposition
  • Point, Area, and Line Sources
  • Complex Terrain
  • Simple Meteorological Data Input

13
Industrial Source Complex Model
  • Has been primary model in Iowa for 27 years
  • Over 100 facilities have modeled compliance with
    ISC
  • Generally the short-term standards have caused
    greatest predicted non-compliance

14
Industrial Source Complex Model
  • 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

15
AERMOD
  • AERMOD stands for American Meteorological
    Society/ Environmental Protection Agency
    Regulatory Model
  • Formally Proposed as replacement for ISC in 2000
  • Adopted as Preferred Model November 9, 2005

16
AERMOD
  • 3 COMPONENTS
  • AERMET THE METEOROLOGICAL PREPROCESOR
  • AERMAP THE TERRAIN DATA PREPROCESSOR
  • AERMOD THE DISPERSION MODEL
  • 2 SUPPORT TOOLS
  • AERSURFACE PROCESSES SURFACE CHARACTERISTICS
    DATA
  • AERSCREEN PROVIDES A SCREENING TOOL

17
AERMOD
  • AERMOD IS SIMILAR TO ISC IN SETUP
  • THE CONTROL FILE STRUCTURE IS THE SAME
  • VIRTUALLY ALL THE CONTROL KEYWORDS AND OPTIONS
    ARE THE SAME

18
AERMOD
  • AERMOD IS DIFFERENT FROM ISC
  • REQUIRES SURFACE CHARACTERISTICS (ALBEDO, BOWEN
    RATIO, SURFACE ROUGHNESS) IN AERMET
  • HAS PRIME FOR BUILDING DOWNWASH AND THE BUILDING
    PARAMETERS ARE MORE EXTENSIVE
  • REQUIRES LONGER COMPUTER RUN TIMES (up to 5 times
    longer!)

19
Comparison of Dispersion Model FeaturesMeteorolo
gical Data Input
  • ISCST3
  • One level of data accepted
  • AERMOD
  • An arbitrarily large number of data levels can
    be accommodated

20
Comparison of Dispersion Model FeaturesPlume
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

21
Comparison of Dispersion Model FeaturesComplex
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

22
Comparisons 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 3.89
  • low 0.32 0.26 0.24 0.30
  • Total 48 48 48 48
  • AN OVERVIEW FOR THE 8TH MODELING CONFERENCE
    SEPTEMBER 22, 2005

23
Comparisons ISC Vs AERMOD
  • CONSEQUENCE 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 0.93
  • No cases 6 6
    6
  • AN OVERVIEW FOR THE 8TH MODELING CONFERENCE
    SEPTEMBER 22, 2005

24
Comparisons ISC Vs AERMOD
  • Duane Arnold Energy Center Data (Palo, IA)
  • Ratio of Modeled Conc to Observed
  • AERMOD 0.69 (1-hr avg 46m release)
  • ISC-Prime 0.76 (1-hr avg 46m release)
  • AERMOD 0.25 (1-hr avg 24m release)
  • ISC-Prime 0.29 (1-hr avg 24m release)
  • AERMOD 0.51 (1-hr avg 1m release)
  • ISC-Prime 0.38 (1-hr avg 1m release)

25
Comparisons ISC Vs AERMOD
  • Presentation at EUEC conference by Bob Paine,
    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

26
Comparisons ISC Vs AERMOD
  • Our Recent Experience
  • Annual concentrations higher with AERMOD by
    10-15
  • Short term concentrations similar without
    downwash
  • Short-term concentrations generally lower with
    building downwash by 20

27
The IDNR Connection
  • IDNR will allow use of either ISCST3 or AERMOD
    until November 9, 2006
  • Meteorological Data will be provided by IDNR for
    eight stations
  • Compliance with ISCST3 and non-compliance by
    AERMOD must be addressed

28
Questions Answers
29
(No Transcript)
30
AERMOD
31
AERMOD
32
AERMOD
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