Overview THE ATMOSPHERE Constituents Structure ATMOSPHERIC - - PDF document

2/10/2015 1

Anthony J. Sadar, CCM Allegheny County Health Department Air Quality Program

February 11 & 12, 2015 MARAMA Webinar

1

Part 2: Go to Slide 56.

Overview

 THE ATMOSPHERE

Constituents Structure

 ATMOSPHERIC DYNAMICS

Temporal/spatial scale of events

 AIR POLLUTION DISPERSION

SourcesDispersionReceptors

 AIR DISPERSION MODELING

Observation—Theory—Models Receptors = Sources / Dispersion C = Q S / U Empirical research Statistical approach:  = q / ( u y z) …

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Overview (Continued)

 US EPA GUIDELINES

Guideline on Air Quality Models (Revised), Appdx. W Other guidance/clarification

 AERMOD & AERSCREEN

Input requirements Output examples Interpretation of results Comparison between AERMOD and AERSCREEN

 ADDITIONAL MODELS & APPLICATIONS

Requirements for regulatory modeling

3

The Atmosphere

 Constituents  Structure

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Constituents

Permanent Percent

Nitrogen (N2) 78.1 Oxygen (O2) 20.9 Argon (Ar) 0.9 Neon (Ne) 0.002

Variable

Water Vapor (H2O) 0 ‐ 4 Carbon Dioxide (CO2) 0.04 Helium (He) 0.0005 Methane (CH4) 0.0002 Krypton (Kr) 0.0001

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Structure

Not to Scale.

]- ABL

Temperature changes with increasing altitude in atmosphere.

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Atmospheric Boundary Layer (ABL)

 Bottom layer of troposphere starting at earth’s surface

and extending to several km during sunny afternoons.

 Structure and height of ABL varies diurnally, during

fair weather over land:

 From tens of meters on mornings with a strong surface

temperature inversion (when temperature increases with altitude) to several kilometers during sunny afternoons.

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Atmospheric Dynamics

 Temporal/Spatial Scales of Events

Source: A World of Weather: Fundamentals of Meteorology, 4th Edition, by Lee Grenci, Jon Nese, and David Babb, 2008, Figure 1.9.

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Conditions of Note

 Topography

 “Heat Island” Effect (Urban/Rural)  Land/Water (Diurnal “Sea Breeze”/“Land Breeze”)  Mountain/Valley (Diurnal Effects and Channeling)

 Elevation

9

Conditions of Note (Continued)

 Overview

Source: D. Carruthers, Chpt. 10, “Atmospheric Dispersion and Air Pollution Meteorology,” in Handbook of Atmospheric Science: Principles and Applications, C.N. Hewitt and A.V. Jackson, Editors, 2003.

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Conditions of Note (Continued)

 Topography

Source: D. Carruthers, Chpt. 10, “Atmospheric Dispersion and Air Pollution Meteorology,” in Handbook of Atmospheric Science: Principles and Applications, C.N. Hewitt and A.V. Jackson, Editors, 2003.

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Poll Question #1

 The Heat Island Effect occurs in the Atmospheric

Boundary Layer (True/False)

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Poll Question #2

 Turbulence is a meso‐scale temporal event.

(True/False)

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Air Pollution Dispersion

 Transport and Diffusion of Air Pollution  Sources  Dispersion  Receptors

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Air Dispersion Modeling

• What is Modeling?
• Modeling Components:

‐ Source considerations ‐ Dispersion considerations ‐ Receptor considerations

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What Is Modeling?

 A scientific “model” is a tentative representation of an

• bservation based on interpretation of available information;

a tool used to simulate real‐world conditions.

 “Air‐dispersion modeling,” as described by the EPA, “uses

mathematical formulations to characterize atmospheric processes that disperse a pollutant emitted by a source. Based on emissions and meteorological inputs, a dispersion model can be used to predict concentrations at selected downwind receptor locations.”

 Note that “verification of the truth of any model is an

impossible task” (ASTM International, D6589–05, 2010).

 Models contain assumptions and limitations.

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What Is Modeling? (Continued)

Observation Theory Models

Adapted from: Numerical Weather and Climate Prediction,

• T. T. Warner, 2011, Fig. 1.1, p. 3.

17

Modeling Components

Sources  Dispersion  Receptors

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Whence Highest Concentrations?

 Large Emission Rate  Low Plume Rise  Overlapping Plumes  Stack‐Tip Downwash  Building‐Induced Downwash  Building Cavity

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Whence Highest Conc.? (Continued)

 Proximity to Source(s)  Terrain‐Induced Downwash and Channeling  High Terrain  Short Ground Cover  Stable/Stagnant Atmosphere  Steady Wind Direction from Source(s) to Receptor(s)

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Source Considerations

“Worst‐case” conditions for emissions:

 Maximum particle/gas discharge  Lowest release height  Lowest in‐vent/in‐stack temperature  Lowest exit gas velocity  Shortest distance to property line

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Dispersion Considerations

“Worst‐case” meteorology:

 No precipitation  Light winds from source to critical receptor(s)  Strong ground‐based temperature inversion

(elevated inversion can also cause problems)

Note: Wind Direction is direction from which wind is blowing.

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Receptor Considerations

“Worst‐case” conditions for receptors:

 Closest, highest off‐site location  Plume centerline concentrations  Elevated receptor for malodor investigations

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Simple Relationship

 Sources  Dispersion  Receptors  Receptors = Sources / Dispersion

• r

R = S / D

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Simple Dispersion Formula

C = Q x S

U Where, C is pollutant concentration (g/m3) Q is rate of emissions exiting source (g/s) S is stability of atmosphere (m‐2) U is horizontal wind speed (m/s)

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How Does Emission Rate Affect C?

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How Does Wind Speed Affect C?

27

Poll Question #3

 All else being equal, a pollutant concentration at a

receptor will be higher with a higher stack.(True/False)

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Poll Question #4

 All else being equal, a pollutant concentration at a

receptor will be lower at low wind speed.(True/False)

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How Does Stability Affect C?

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Stability Conditions

 Traditionally, stability of lower atmosphere has been

delineated as:

31

How Does Stability Affect Plumes?

Smokestack emissions that continuously exhaust to the ambient air are referred to as “plumes.” Plumes exhibit particular patterns depending upon atmospheric stability.

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Plume Types

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Simple Dispersion Formula

C = Q x S

U Where, C is pollutant concentration (g/m3) Q is rate of emissions exiting source (g/s) S is stability of atmosphere (m‐2) U is horizontal wind speed (m/s)

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Empirical Research

Field observations suggested that smokestack emissions disperse in a “normal” way; that is, pollutants spread away from a centerline with a typical bell‐shaped or Gaussian frequency distribution.

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Plume Observations

Source: Hanna, et al., 1982

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Statistical Approach

Source: http://scalesstudy.wordpress.com/2012/07/27/my-running-disorder/

Bell-shaped Curve, Normal, or Gaussian Distribution

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Statistical Approach (Continued)

Probability Density Function:

 =

1 .exp[(-0.5 (x-)2)/22]  (2)1/2

Compare with the fundamental Gaussian plume equation:

 =

q .exp[-0.5 (H2/z

2)]

yzu

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Gaussian Plume Model

Source: www.lete.poli.usp.br/Guenther/aula_4/Plumes.pdf 39

Gaussian Distribution

Source: www.lete.poli.usp.br/Guenther/aula_4/Plumes.pdf

The bell‐shaped curves represent a distribution of contaminants across the horizontal (cross‐wind) and vertical axis. Fundamental Gaussian Plume Equation:

 =

q . exp [-0.5 (H2/z

2)]

( u y z)

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Gaussian Distribution (Continued)

Fundamental Gaussian Plume Equation:

 =

q . exp [-0.5 (H2/z

2)]

( u y z)

Where,  = ambient air concentration, q = emission rate, , u = wind speed, y z = dispersion parameters, and H= effective plume height.

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Gaussian Plume Cross Section

Source: Hanna, et al., 1982

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Poll Question #5

 If a plume concentration is distributed normally

pollutant concentration will be highest along the centerline.(True/False)

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Dispersion Parameters (y and z)

Source: Turner, 1970

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Good Engineering Practice Stack Height (HGEP)

HGEP is the greater of:

• 65 meters
• For stacks built before 1/12/1979:

HGEP = 2.5 H, where H is height of nearby structure(s)

• For all other stacks:

HGEP = H + 1.5L, where L is lesser of H or projected width of nearby structure(s).

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Flow Around Buildings

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Flow Around Buildings (Continued)

Source: Saskatchewan Air Quality Modeling Guideline, March 2012

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Plume Rise

Plume rise is also important to pollution

• dispersal. Plume rise is primarily a function of

exit gas temperature and momentum. Generally,

• Higher temperature = higher plume rise.
• Higher momentum = higher plume rise.
• Higher plumes = lower ground‐level

pollutant concentrations.

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Poll Question #6

 Buildings can cause plume downwash.(True/False)

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Types of Mathematical Air Quality Models

• Lagrangian models simulate

dispersion or reactions in parcels of air that move along with the wind trajectory.

• Eulerian approaches divide

the problem domain into fixed grid cells. Various methods are then used to solve equations over the full domain.

Slide adapted from: Julie McDill, MARAMA

2/10/2015 26

Which Models Use Which Math?

 Lagrangian models

 Dispersion models (e.g.,

AERMOD)

 Trajectory models (e.g.,

HYSPLIT)

 Eulerian

 Photochemical grid models

(e.g., CAMx)

Slide adapted from: Julie McDill, MARAMA

Summary

 THE ATMOSPHERE

Constituents Structure

 ATMOSPHERIC DYNAMICS

Temporal/spatial scale of events

 AIR POLLUTION DISPERSION

SourcesDispersionReceptors

 AIR DISPERSION MODELING

Observation—Theory—Models Receptors = Sources/Dispersion C = QS/U Empirical research Statistical approach: =q/(uyz)…

52

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References

53

Links to Resources

 Meteorology and Atomic Energy 1968:

http://www.orau.org/ptp/PTP%20Library/library/Subject/Mete

• rology/meteorology%20and%20atomic%20energy.pdf

http://www.orau.org/ptp/PTP%20Library/library/Subject/Meteorology/meteorology%20and%20atomic%20energy.pdf

 Workbook of Atmospheric Dispersion Estimates, 1970:

http://gate1.baaqmd.gov/pdf/1691_Workbook_Atmospheric_Dispersion_Esti mates_1971.pdf

http://gate1.baaqmd.gov/pdf/1691_Workbook_Atmospheric_Dispersion_Estimates_1971.pdf

 Handbook on Atmospheric Diffusion, 1982:

http://www.wmo.int/pages/prog/www/DPFSERA/documents/workbook.pdf

http://www.wmo.int/pages/prog/www/DPFSERA/documents/workbook.pdf

 Handbook of Atmospheric Science: Principles and Applications,

2003: http://www.dvfu.ru/meteo/book/HandbookAtm.pdf

http://www.dvfu.ru/meteo/book/HandbookAtm.pdf

 EPA’s Support Center for Regulatory Atmospheric Modeling

(SCRAM) Website: http://www.epa.gov/scram001/ http://www.epa.gov/scram001/

 “Guideline on Air Quality Models (Revised)” (40 CFR 51):

http://www.epa.gov/scram001/guidance/guide/appw_05.pdf

http://www.epa.gov/scram001/guidance/guide/appw_05.pdf

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55

Anthony J. Sadar, CCM Allegheny County Health Department Air Quality Program

December 4, 2014 MARAMA Webinar

2/10/2015 29

Review

 THE ATMOSPHERE

Constituents Structure

 ATMOSPHERIC DYNAMICS

Temporal/spatial scale of events

 AIR POLLUTION DISPERSION

SourcesDispersionReceptors

 AIR DISPERSION MODELING

Observation—Theory—Models Receptors = Sources/Dispersion C = QS/U Empirical research Statistical approach: =q/(uyz)…

Overview of Topics for Today

 US EPA GUIDELINES

Guideline on Air Quality Models (Revised), Appdx. W Preferred and Recommended Dispersion Models Examples of Other Models (CAMx and WRF)

 AERMOD & AERSCREEN

Input requirements Output examples Comparison between AERMOD and AERSCREEN

 AERSCREEN Operation  MODELING GUIDANCE AND SUPPORT

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U.S. EPA Guidelines

Guideline on Air Quality Models (Revised) “Appendix W” – 40 CFR 51, Nov. 9, 2005

‐ AERMOD Established as Preferred Dispersion Model Out to 50 km

http://www.epa.gov/scram001/guidance/guide/appw_05.pdf

EPA’s Support Center for Regulatory Atmospheric Modeling (SCRAM) Website

http://www.epa.gov/scram001/

EPA “Approved” Models

 AERMOD

 AMS/EPA Regulatory Model

 CAMx

 Comprehensive Air quality Model with extensions

 CMAQ

 Community Multiscale Air Quality model

 CALPUFF

 Originally sponsored by CA Air Resources Board

2/10/2015 31

Types of Mathematical Air Quality Models

• Lagrangian models simulate

dispersion or reactions in parcels of air that move along with the wind trajectory.

• Eulerian approaches divide

the problem domain into fixed grid cells. Various methods are then used to solve equations over the full domain.

Slide adapted from: Julie McDill, MARAMA

Which Models Use Which Math?

 Lagrangian models

 Dispersion models (e.g.,

AERMOD)

 Trajectory models (e.g.,

HYSPLIT)

 Eulerian

 Photochemical grid models

(e.g., CAMx)

Slide adapted from: Julie McDill, MARAMA

2/10/2015 32

CAMx Dispersion Model

Uses nested three‐dimensional grids Accounts for average species concentration

changes over time within each grid cell volume via:

 Horizontal advection  Vertical transport  Sub‐grid scale turbulent diffusion  Dry deposition and wet scavenging  Chemical/photochemical reactions  Secondary aerosol formation/partitioning

CAMx Nested Grids

Example of Horizontal Grid Nesting (Fig. 2-2, pg. 2-5)

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CAMx Horizontal Grid Nesting

Source: ENVIRON 120 240 360 480 600 720 840 960 1080 1200 1320 1440 1560 1680 1800 1920 2040 2160

• 480
• 360
• 240
• 120

120 240 360 480 600 720 840 ACHD Proposed CAMx Domain 36 km 148 x 112 (-2736, -2088) to (2592, 1944) 12 km 174 x 117 ( 72, -540) to (2160, 864) 04 km 54 x 60 ( 1296, 48) to (1512, 288) 0.8 km 75 x 60 ( 1392, 144) to (1452, 192) 12 km 04 km 0.8 km

Weather Research and Forecasting (WRF) Model

 State‐of‐the‐science mesoscale numerical weather

prediction system developed by NCAR, NOAA, et al.

 Used worldwide for both operational forecasting

and atmospheric research

 “Community model” that undergoes continuous

evaluation and frequent updates

 Operates like CAMx, using 3‐D grid cells

2/10/2015 34

AERMOD vs. CAMx

AERMOD CAMx Gaussian, straight line dispersion Concentrations within 3‐D box Generally non‐reactive plume Chemical/photochemical reactions Impact distance limited to 50 km Practically unlimited distance Models impact from individual sources to specific receptor points Generally does not model direct impact

• f point sources to nearby receptors

Simple construction, direct and quick

• peration

Complex construction and more sophisticated, time‐consuming operation

Poll Question #7

 CAMx is used for permit modeling of stationary

industrial sources.(True/False)

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What is Dispersion Modeling?

 Lagrangian Model  Purpose: Estimate effect of

 local sources  near‐field receptors  local atmosphere  pollutants not affected by

chemical transformation  Example: AERMOD

Slide adapted from: Julie McDill, MARAMA

Source: U.S.EPA

2/10/2015 36

AERMOD Modeling System/Inputs

Source: U.S.EPA

AERMOD System Inputs/Outputs

Source: U.S.EPA

2/10/2015 37

AERMODModelingSystemAlgorithms

 Dispersion in Convective and Stable ABLs  Plume Rise and Buoyancy  PlumeIncursionIntoElevatedInversionsandRe‐entrainment  ComputationofVerticalProfilesofTemp.,Wind,andTurbulence  Site‐specific meteorology beneficial

AERMODSystemAlgorithms (Continued)

 Urban Nighttime Boundary Layer  Receptor Considerations On All Types of Terrain  Building Wake Effects  Improvement in Characterizing Basic ABL Parameters  Treatment of Plume Meander

2/10/2015 38

Poll Question #8

 AERMOD is used for permit modeling of

stationary industrial sources.(True/False)

75

Poll Question #9

 Site specific meteorology is preferred if

available.(True/False)

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AERMOD Run Example

 How Is AERMOD Used In Regulatory Work, Such As

SIP Preparation?

Allegheny County Nonattainment Area

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AERMOD Example Output

Slide adapted from: ACHD’s AWMA Presentation, 2014

N Modeling Results for 2011 (Contours every 100 g/m3)

“Q‐Q Plot” of Results

Source: ACHD’s AWMA Presentation, 2014

2/10/2015 41

Source: U.S.EPA

AERMOD & AERSCREEN

 Comparison between AERMOD and AERSCREEN

2/10/2015 42

AERMOD vs. AERSCREEN Input

Bla nkr rr

Output examples

 AERMOD

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Output examples

 AERSCREEN

AERSCREEN Operation

 What is AERSCREEN?  Model Run Demonstration

86

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What Is AERSCREEN?

 Screening model based on AERMOD  Estimates "worst‐case" 1‐hour concentrations from a

single source

 Does not need hourly meteorological data (MAKEMET)  Includes conversion factors to estimate "worst‐case" 3‐

hour, 8‐hour, 24‐hour, and annual concentrations

(Note: These conversion factors are conservative!)  Estimated concentration = or > than AERMOD  Degree of conservatism depends on application

What’s So Good About AERSCREEN?

 EPA approved (replaced SCREEN3)  Provides more realistic, yet conservative values

 more‐sophisticated treatment of building wake effects  handles winds at 0.5 m/s, et al.  incorporates terrain impacts

 Familiar operation  Quick and easy to run  But, plug & chug can be GI/GO

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AERSCREEN vs. SCREEN3

 Building Wake Effects Modeled With BPIPPRM  Incorporates More Detailed Meteorology

 Albedo, Bowen Ratio, Surface Roughness

 More‐Realistic/Site‐Specific Terrain Impacts Modeled

Poll Question #10

AERSCREEN is more conservative than AERMOD (T/F)

2/10/2015 46

AERMOD & AERSCREEN Comparison

 AERMOD simulates numerous sources simultaneously

while AERSCREEN is limited to a single source

 Both models:

 Vertical or horizontal stack, capped stack, rectangular or

circular area, flare stack, volume release

 Building downwash option

 AERSCREEN results typically more conservative than

AERMOD results

Operation Of AERSCREEN

 Interactive command‐prompt application that runs via

interfaces with: site‐specific matrix of meteorology, terrain and building input, and AERMOD

 Release conditions: Vertical uncapped or capped stack,

horizontal stack, rectangular or circular area, flare, or volume source

 Models NOx to NO2 conversion

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

 Default values  When in doubt… follow the instructions  “The Usual Suspects” (typical pitfalls)  Does the answer make sense?

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Default Values

 Model Mode = Rural (+ try Urban)  Min/Max Temperatures = 250.0 K / 310.0 K  Stack Temperature = “0,” for ambient temperature  Minimum Wind Speed = 0.5 m/s  Anemometer Height = 10.0 m  Surface Characteristics = “2,” AERMET seasonal tables  Dominant Surface Profile = “6,” grassland (+ try others)  Dominant Climate Type = “1,” Average Moisture  Others

“The Usual Suspects”

 Mistyping  Misconstruing instructions  Mixed or incorrect units  Mis‐assigning file names or extensions  Misunderstanding “wind direction”  Others

Don’t Forget to Ask Yourself: Does the answer make sense?

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Modeling Issues

 Malodors  Air toxics  “Guideline on Air Quality Models,” 40 CFR Part 51,

Appendix W

 Others

Modeling Demo

Before using AERSCREEN, users must have the latest

AERMOD executable (09292 or later) AERMAP terrain preprocessor BPIPPRIME executables.

These can be downloaded from the AERMOD Modeling System section. [Source: SCRAM Website.]

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Nominal Industrial Source Example Input File (AERSCREEN 11126)

Note that the most recent version of the model is AERSCREEN 14147.

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AERSCREEN Modeling Results (Without and With Building) Building Downwash

Figure 11. Stack and building orientation for a building oriented 90 degrees to north and stack oriented 45 degrees to north. (Source: AERSCREEN User’s Guide, U.S.EPA, 3/2011, p. 20)

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Plane View of Building and Stack Orientation for Example AERSCREEN Run

(Source: AERSCREEN User’s Guide, U.S. EPA, 3/2011, Figure 35, pg. 56)

AERMET Guidance: Albedo

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AERMET Guidance: Bowen Ratio AERMET Guidance: RoughnessLength

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AERSCREEN Results “Better ingredients …”

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Modeling Guidance and Support

Guideline on Air Quality Models (Revised) “Appendix W” – 40 CFR 51, Nov. 9, 2005 EPA’s Support Center for Regulatory Atmospheric Modeling (SCRAM) Website

 Model formulation documents, user guides; addendums  Model Change Bulletins  Clarification memos (Ex., September 30, 2014 memo)

http://www.epa.gov/ttn/scram/guidance/clarification/NO2_Clarification_Memo‐20140930.pdf

Model Clearinghouse State and Local Modeling Guidance

Summary

 THE ATMOSPHERE

Constituents Structure

 ATMOSPHERIC DYNAMICS

Temporal/spatial scale of events

 AIR POLLUTION DISPERSION

SourcesDispersionReceptors

 AIR DISPERSION MODELING

Observation—Theory—Models Receptors = Sources/Dispersion C = QS/U Empirical research Statistical approach: =q/(uyz)…

2/10/2015 55

Summary (Continued)

 US EPA GUIDELINES

Guideline on Air Quality Models (Revised), Appdx. W Other guidance/clarification

 AERMOD & AERSCREEN

Input requirements Output examples Interpretation of results Comparison between AERMOD and AERSCREEN

 ADDITIONAL MODELS & APPLICATIONS

Requirements for regulatory modeling

References

2/10/2015 56

Links to Resources

 Meteorology and Atomic Energy 1968:

http://www.orau.org/ptp/PTP%20Library/library/Subject/Mete

• rology/meteorology%20and%20atomic%20energy.pdf

http://www.orau.org/ptp/PTP%20Library/library/Subject/Meteorology/meteorology%20and%20atomic%20energy.pdf

 Workbook of Atmospheric Dispersion Estimates, 1970:

http://gate1.baaqmd.gov/pdf/1691_Workbook_Atmospheric_Dispersion_Esti mates_1971.pdf

http://gate1.baaqmd.gov/pdf/1691_Workbook_Atmospheric_Dispersion_Estimates_1971.pdf

 Handbook on Atmospheric Diffusion, 1982:

http://www.wmo.int/pages/prog/www/DPFSERA/documents/workbook.pdf

http://www.wmo.int/pages/prog/www/DPFSERA/documents/workbook.pdf

 Handbook of Atmospheric Science: Principles and Applications,

2003: http://www.dvfu.ru/meteo/book/HandbookAtm.pdf

http://www.dvfu.ru/meteo/book/HandbookAtm.pdf

 EPA’s Support Center for Regulatory Atmospheric Modeling

(SCRAM) Website: http://www.epa.gov/scram001/ http://www.epa.gov/scram001/

 “Guideline on Air Quality Models (Revised)” (40 CFR 51):

http://www.epa.gov/scram001/guidance/guide/appw_05.pdf

http://www.epa.gov/scram001/guidance/guide/appw_05.pdf