Transcript Types of models 6-03.ppt

Types of Models
Marti Blad
Northern Arizona University
College of Engineering & Technology
Models
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Meteorological
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Diagnostic
Prognostic
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Emissions
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Type of chemicals
Rates of release
Sources
Building impacts
Surface
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Viewing
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Terrain complexity
Air turbulence
GUI to see pictures
Receptor
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Human
Ecological impact
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EPA MODELS—Screening
CTSCREEN
COMPLEX1
LONGZ
RTDM32
SCREEN3
RVD2
CTSCREEN
VISCREEN
TSCREEN
VALLEY
SHORTZ
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EPA MODELS—Regulatory
MPTER
ISC3
OCD
EKMA
CRSTER
UAM
CDM2
CALINE3
CAL3QHC
RAM
CTDMPLUS
BLP
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EPA Models—Other
MESOPUFF
TOXST
COMPDEP
FDM
CMB7
PLUVUE2
RPM-IV
SDM
MOBILE5
DEGADIS
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Models = Representations
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Simplified representation of complex
system
Used to study & understand the complex
Numerical
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Set of equations
Describe = quantify
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Box Model Concept
Time= t
t, x
t, x, y
t, x, y, z
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1-D and 2-D Models
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3-Dimensional Models
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Types of Air Quality Models
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Dispersion models
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Solves turbulent dispersion of
unreactive species based on Gaussian
distributions
Chemical Tracer Models (CTMs)
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Lagrangian (trajectory) models
Eulerian (grid) models
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Lagrangian Air Quality Models
From “INTERNATIONAL AIR QUALITY ADVISORY BOARD 1997-1999 PRIORITIES
REPORT, the HYSPLIT Model”
(http://www.ijc.org/boards/iaqab/pr9799/project.html)
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Lagrangian Model Strengths
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Easy to code, run and analyze
Explicit mechanisms easily modified
Evaluate chemical effects
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Isolate from the meteorology
Facilitates evaluation of source-receptor
Numerically efficient
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Eulerian Air Quality Models
Figure from http://irina.colorado.edu/lectures/Lec29.htm
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Eulerian Models (cont.)
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Plume in Grid (P in G)
Simulates atmospheric chemistry
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Transport
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Gas phase & reactions
photolysis
Advection & diffusion
Deposition
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Particle modeling & visibility
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Eulerian Model Strengths
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Contain detailed 4-D descriptions
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Predicts species concentrations
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Meteorological and transport processes
Defined geographical and temporal domain
Simulates multi-day scenarios
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What is a dispersion model?
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Repetitious solution of dispersion equations
Based on principles of transport, diffusion
Computer-aided simulation of atmospheric
dispersion from emission
Allows assessment of air quality problem in
spatial, temporal terms (i.e., space & time)
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Gaussian-Based Dispersion Models
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Plume dispersion in lateral &
horizontal planes characterized by a
Gaussian distribution
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See picture next slide
Pollutant concentrations predicted are
estimations
Uncertainty of input data values
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approximations used in the
mathematics
intrinsic variability of dispersion
process
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Gaussian Dispersion
z

Dh = plume rise
h = stack height
Dh
H = effective stack
height
H = h + Dh
H
h
x
C(x,y,z) Downwind at (x,y,z) ?
y
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Gaussian Dispersion
Concentration

  z  H 2  
exp 

2
2 z



2

 y  
Q
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Cx , y ,z  

exp   2   

2 u y z 
 2 y   
2 



z

H


exp 


2

2

z

 

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Simple Gaussian Model Assumptions
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Continuous pollutant emissions
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Conservation of mass in atmosphere
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Steady-state meteorological conditions
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Concentration profiles represented by
Gaussian distribution – bell curve shape
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Model Considerations
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Actual pattern of dispersion depends on
atmospheric conditions prevailing during
release
Major meteorological factors that influence
dispersion of pollutants
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Atmospheric stability (& temperature)
Mixing height
Wind speed & direction
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Maximum Mixing Depth
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Review Atmospheric Effects
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Computer Model Input
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Appropriate meteorological conditions
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Stack or source emission data
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Appropriate for the location
Appropriate for the averaging time period
Pollutant emission data
Stack or source specific data
Receptor data
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Model Considerations (cont.)
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Height of plume rise calculated
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Momentum and buoyancy
Can significantly alter dispersion & location
of downwind maximum ground-level
concentration
Effects of nearby buildings estimated
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Downwash wake effects
Can significantly alter dispersion & location
of downwind max. ground-level
concentration
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Computer Model Input (cont.)
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Plume data
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Source type
Velocity of release
Temperature of release
BPIP recommended
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Models downwash
Multiple stacks and buildings
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Maximum Mixing Height (MMD)
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Coastal or Large Water Bodies
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Coastal Complexity
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Complex Terrain
Different math for flat or elevated terrain
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Types of Dispersion Models
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Gaussian Plume
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Numerical or CFDs
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Transport & diffusional flow fields
Statistical & Empirical
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Analytical approximation of dispersion
Based on experimental or field data
Physical
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Flow visualization in wind tunnels, etc.
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Models
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Useful tools: right model for your needs
Allows assessment of air quality problem
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Space – different distances
Time – different times of day
Situations – change weather
Understand limitations
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Assumptions in science speak
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