DispersionModeling MLD

8/13/2019 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



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



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



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



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

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