dispersionmodeling mld
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Dispersion Modeling
A Brief Introduction
Image from Univ. of Waterloo Environmental Sciences
Mark Daniels, M.S., E.I.T.
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Introduction
Why use dispersion models?Many different types of modelsLimitations & assumptionsMath and science behind modelsTransport phenomenaComputers do Math for youGaussian dispersion modelsScreen3 model information
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Why Use Dispersion Models?
Predict impact from proposed and/or existingdevelopment
NSR- new source review
PSD- prevention of significant deterioration Assess air quality monitoring data
Monitor location
Assess air quality standards or guidelinesCompliance and regulatory
Evaluate AP control strategiesLook for change after implementation
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Types of Models
Gaussian PlumeMathematical approximation of dispersion
Numerical Grid ModelsTransport & diffusional flow fields
StoichasticStatistical or probability based
EmpiricalBased on experimental or field data
PhysicalFlow visualization in wind tunnels, scale mod
els,etc.
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Limitations & Assumptions
Useful tools: right model for your needs Allows quantification of air quality problem
Space – different distances, scale
Time – different time scalesSteady state conditions?
Understand limitationsMathematics-different typesChemistry-reactive or non-reactiveMeteorology-Climatology
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Momentum, Heat & Mass Transport
AdvectionMovement by flow (wind)
ConvectionMovement by heat
Heat island
RadiationDiffusion
Movement from high to low concentrationDispersionTortuous path, spreading out because goes aroundobstacles
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Diffusion & dispersion
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Transport of Air PollutionPlumes tell story
Ambient vs DALR
Models predict airpollutionconcentrationsInput knowledge ofsources and
meteorologyChemical reactionsmay need to beaddressed
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Models allow multiple mechanisms
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Buoyancy =Plume rise
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z
D h
h
H
x
y
D h = plume rise
h = stack heightH = effective stack
heightH = h + D h
C(x,y,z) Downwind at (x,y,z)?
Gaussian Dispersion
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Gaussian DispersionConcentration Solution
C
Q
u
y
z H
z H x y z
y z y
z
z
, , exp
exp
exp
2 2
2
2
2
2
2
2
2
2
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The Gaussian Plume Model
The mathematicalshape of the curveis similar to that of
Gaussian curvehence the model iscalled by thatname.
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Gaussian-BasedDispersion Models
Plume dispersion in lateral & horizontal planescharacterized by a Gaussian distribution
Picture
Pollutant concentrations predicted areestimationsUncertainty of input data values
approximations used in the mathematicsintrinsic variability of dispersion process
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Simple GaussianModel Assumptions
Continuous constant pollutant emissionsConservation of mass in atmosphere
No reactions occurring between pollutants
When pollutants hit ground: reflected, or absorbedSteady-state meteorological conditions
Short term assumption
Concentration profiles are represented byGaussian distribution —bell curve shape
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Gaussian Plume DispersionOne approach: assume each individual plume behavesin Gaussian manner
Results in concentration profile with bell-shaped curve
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Is this clear?
Time averaged concentration profiles aboutplume centerline
Recall limitations
Normal Distribution is used to describe randomprocesses
Recall bell shaped curves in 3-D
Maximum concentration occurs at the center ofthe plume
See up coming model pictures
Dispersion is in 3 directions
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Gaussian Plume
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Graphic Gaussian DispersionGaussian behavior extends in 3 dimensions
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What is a Dispersion Model?
Repetitious solution of dispersion equationsComputer solves over and over againCompare and contrast different conditions
Based on principles of transportComplex mathematical equationsPreviously discussed meteorological conditions
Computer-aided simulation of atmosphere basedon inputs
Best models need good quality and site specific data
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Computer Model Structure
INPUT DATA: Operator experience
METEROLOGY EMISSIONS RECEPTORS
Model Output: Estimates ofConcentrations at Receptors
Model does calculations
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Screen 3 modelUnderstand spatial and temporal relationshipsOne hour concentration estimates
Caveat in program
MeteorologySource type and specific information
Point, flare, area and volume
Receptor distanceDiscrete vs automated
Receptor height
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Meteorological Inputs
Actual pattern of dispersion depends onatmospheric conditions prevailing duringthe release
Appropriate meteorological conditionsWind rose
Speed and direction
Stability classMixing Height
Appropriate time period
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Point SourceSource emission data
Pollutant emission dataRate or emission factors
Stack or source specific dataTemperature in stack
Velocity out of stack
Building dimensionsBuilding location
Release HeightTerrain
More complex scenarios
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Different Stack Scenarios
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Model Inputs Effect Outputs
Height of plume rise calculatedMomentum and buoyancyCan significantly alter dispersion & location of
downwind maximum ground-level concentrationEffects of nearby buildings estimated
Downwash wake effectsCan significantly alter dispersion & location ofdownwind max. ground-level concentration
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Conceptual Effect ofBuildings
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Spatial Relationships
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Gaussian Plume
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Screen3 Area SourceEmission rate
AreaLongest side, shortest sideRelease height
TerrainSimple FlatReflection and absorption
DistancesDiscrete vs automated
Receptor height
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ReviewTransport Phenomena
Meteorology and climatology Add convection, pressure changes
Gaussian = even spreading directionsHighest along axisNot as scary as sounds
Input data quality critical to model quality
Screen 3 limitation for reactive chemicalsNo reactions assumed to create or destroy
Create picture for Screen3 word problems