aermod-basictraining06

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Design by Nancy Ellefson

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Minnesota Air, Water, andMinnesota Air, Water, andWaste Environmental Conf.Waste Environmental Conf.

Air Modeling – Training (8am-noon)

Sheraton Bloomington Hotel, Atrium 7

February 14, 2006

Chris Nelson & Dennis Becker

Minnesota Pollution Control Agency

X:\Old_P_Fox\AQPRJ\TOXTEAM\ModelTraining\

aq-ppt1-05



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Air Modeling (98 Slides) Air Modeling (98 Slides)

AERMOD Status and MPCA “Draft” Data

AERMOD Urban Modeling Developments Metropolitan Statistical Areas and Micropolitan Statistical Areas

New MPCA NAAQS/MAAQS Feature: FAR Data

Break - slide 40

Rochester and Olmsted County SIP Work RPU-Silver Lake Plant Sensitivity Analyses

Break - slide 75

AERA/RASS with supplemental Post-RASS Option

Fugitive PM10 emissions: roads, cooling towers, etc.

VISCREEN (Nearby areas v. Class I areas)

Future Possibilities



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AERMOD AERMOD

AERMOD promulgated Nov. 9, 2005

AERMOD/AERMAP/AERMET (04300) AERSCREEN (early 2006?)

AERSURFACE (mid 2006?)

First PSD Project: RPU (March 2003)

MPCA “Trial” Data (September 2004)

MPCA “Draft” Data (October 2005) http://www.pca.state.mn.us/air/modeling-data2.html

See next 15 slides

http://www.pca.state.mn.us/air/modeling-data2.html




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MPCA “Draft” Data for AERMODMPCA “Draft” Data for AERMOD



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MPCA “Draft” Data for AERMODMPCA “Draft” Data for AERMOD



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AERMAP “Draft” Data AERMAP “Draft” Data

AERMAP (04300) released Dec. 2005

USGS 7.5 minute DEM files (Refined) “Close-in” receptors (within ~10 km)

“Distant” receptors too, if easy to doUSGS 1-degree DEM files (Screening)

Maybe “Distant” receptors (beyond ~10 km)Beware of AERMAP 03107 bugs

Verify! Compare with DRG TOPO maps!



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AERMET “Draft” Data AERMET “Draft” Data

[National Weather Service (NWS)][National Weather Service (NWS)] Standard Meteorological Parameters

Wind speed, wind direction, temperature, etc.

Additional Land Use Land Cover Parameters

Albedo (solar reflection)• Dark soil~0.1; snow cover~0.5

Bowen Ratio (moisture term)

• Lower values for wet conditions• Higher values for dry conditions

Roughness Height (surface roughness)• Grass<0.1m; cropland~0.2m; dense forest~1m; big city~1m



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AERMET “Draft” Data AERMET “Draft” Data

[National Weather Service (NWS)][National Weather Service (NWS)]Nine Surface Stations

Minnesota Sites: INL, HIB, DLH, MSP, RST Adjacent States: FAR, SXF, EAU, LAC

Mostly 1986-1990 (Hibbing: 1972-1976)National Land Cover Data (NLCD)

Draft Values (Albedo, Bowen Ratio, Zo)

Two Upper Air Stations (INL, STC)

Processed each 0.5 degrees lat./long.



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NWS Sites (Yellow Stars) &NWS Sites (Yellow Stars) &

Processed Sites (Red Dots)Processed Sites (Red Dots)

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AERMET “Draft” Surface Data AERMET “Draft” Surface Data

Compare project site vs. NWS sites:

Prevailing winds (annual, season, month?)Land Use Land Cover (LULC)

• Monthly and annual values

• Twelve 30 degree sectors• 3 kilometer radius

Roughness Height (Zo) very important

Albedo and Bowen Ratio less important

Select most representative NWS site



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AERMET AERMET – – Roughness HeightsRoughness Heights

(NNE Sector(NNE Sector – – Monthly Values)Monthly Values)Draft AERMET "SITE_CHAR": Zo(M) for Sector 1 (by Site and Month)

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1 2 3 4 5 6 7 8 9 10 11 12

Z o ( M )

INL

HIB

DLHNSD

MSP

EAU

LAC

RST

SXF

FAR

Month Id. (1=Jan, 2=Feb, 3=Mar, …, 12=Dec)



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(ALL 12 Sectors(ALL 12 Sectors – – Monthly Values)Monthly Values)Draft AERMET "SITE_CHAR": Zo(M) (12 Sectors & 12 Months [144 Values])

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1 13 25 37 49 61 73 85 97 109 121 133

12 Sectors * 12 Months

Z o ( M )

INL

HIB

DLH

NSD

MSP

EAU

LAC

RST

SXF

FAR



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(Northern MN(Northern MN – – All 12 Sectors) All 12 Sectors)Draft AERMET "SITE_CHAR": Zo(M) (12 Sectors & 12 Months [144 Values])

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1 13 25 37 49 61 73 85 97 109 121 133


Z o ( M )

INL

HIB

DLH

NSD



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(Southern MN(Southern MN – – All 12 Sectors) All 12 Sectors)Draft AERMET "SITE_CHAR": Zo(M) (12 Sectors & 12 Months [144 Values])

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1 13 25 37 49 61 73 85 97 109 121 133


Z o ( M ) RST

SXF

FAR



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AERMET “Draft” Upper Air Data AERMET “Draft” Upper Air Data

Generally use INL in northern MN

Generally use STC in southern MNLess important than selecting surface site



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AERMOD Summary AERMOD Summary

MPCA expects AERMOD (04300): State Air Emission Risk Analyses (AERA)

Federal PSD and SIP modeling

Possible Exceptions: Screening

Residual Title V modeling (state requirement)

Miscellaneous non-regulatory applications

Questions?



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AERMOD AERMOD – – Urban ApplicationsUrban Applications

“AERMOD Implementation Guide”

“Urban Determination”• “Selecting population data for AERMOD’s urban mode”

• See Metropolitan Statistical Area (MSA) web sites

– See next slide for examples

U. S. Census Bureau Web site:

http://www.census.gov/population/www/estimates/metrodef.html “OMB Bulletin No. 05-02”

• Metropolitan Statistical Areas (MSA)

– Also includes Micropolitan Statistical Areas

http://www.census.gov/population/www/estimates/metrodef.html




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Some MSA Web SitesSome MSA Web Sites



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AERMOD AERMOD -- Urban ApplicationsUrban Applications

“AERMOD Implementation Guide”

“Urban Determination”• “Selecting population data for AERMOD’s urban mode”

• See Metropolitan Statistical Area (MSA) web sites

U. S. Census Bureau Web site: http://www.census.gov/population/www/estimates/metrodef.html

“OMB Bulletin No. 05-02”• Metropolitan Statistical Areas (MSA)

– Also includes Micropolitan Statistical Areas





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MSA Definitions & InformationMSA Definitions & Information



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OMB Bulletin No. 05OMB Bulletin No. 05--0202



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OMB Bulletin No. 05OMB Bulletin No. 05--02 (Appendix)02 (Appendix)



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Appendix Appendix – – List of Statistical AreasList of Statistical Areas



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Metropolitan Statistical Areas andMetropolitan Statistical Areas and

MicropolitanMicropolitan Statistical Areas in MinnesotaStatistical Areas in Minnesota

Metropolitan Statistical AreasMetropolitan Statistical Areas



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Metropolitan Statistical AreasMetropolitan Statistical Areas

andand MicropolitanMicropolitan Statistical AreasStatistical Areas



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MicropolitanMicropolitan Statistical Areas in Northern MNStatistical Areas in Northern MN



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MicropolitanMicropolitan Statistical Areas in Southern MNStatistical Areas in Southern MN



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Urban GuidanceUrban Guidance – – Stay TunedStay Tuned

More Urban Guidance (Pending)

Just know this out there (for now)Questions?



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NAAQS AnalysesNAAQS Analyses -- FAR IdeasFAR Ideas

First-Approximation Run (FAR) Approach

First-Approximation Regional (FAR) Sources EPA 1999 AirData (PM10, SO2, NOx)

893 facilities: 1 volume source per facility

1 regional/county area source [AREACIRC]

Lower Background Concentrations

Process (Tentative) 5-year runs find design receptors w/key FAR sources

Event runs find design values with all FAR sources

EPA Facility “EPA Facility “AirDataAirData” (1999)” (1999)



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EPA Facility EPA Facility AirData AirData (1999) (1999)

MPCA “FAR” SourcesMPCA “FAR” Sources



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MPCA FAR SourcesMPCA FAR Sources



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NAAQS AnalysesNAAQS Analyses -- FAR IdeasFAR Ideas

First-Approximation Run (FAR) Approach

893 Facilities (1 volume source/facility) Release Height depends on SO2

Sigma-Y (~20m) and Sigma-Z (~10m)

EMISFACT scalars for facilities < 50km

• Re-computed for each project location!!! No EMISFACT scalars for facilities > 50km

1 regional/county area source [AREACIRC] Release Height (~10m)

Radius (50,000m)

Sigma-Z (0m)

No EMISFACT scalars

FAR Release HeightsFAR Release Heights



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FAR Release HeightsFAR Release Heights

200m for SO2 greater than 20000 tpy

150m for SO2 from 10000 to 20000 tpy






10m for SO2 less than 10 tpy



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FAR EMISFACT ScalarsFAR EMISFACT Scalars

Facilities within 50km of project site EMISFACT varies by averaging time & distance (<50km)

Surrogate for maximum allowable emissions Simple, fast, easy (and still under construction)

Site-Specific: re-computed for each project site!

Beware of close-in facilities – see EMISFACT warning messages

(less important to most important):• “** SPOT CHK”

• “** FULL CHK”

• “** REFINE: ”

Facilities beyond 50km of project site No EMISFACT scalars



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Goal: Estimate maximum allowable emissions

Download actual annual average emissions from EPA web site

Apply EMISFACT scalar for FAR sources within 50km of project site• Vary by averaging time (1, 3, 24-hour, and annual)

• Vary by distance within 50 kilometers

No EMISFACT scalar beyond 50km of project site. Rationale:• Various atmospheric removal processes (chemical transformation,

deposition, gravitational settling)

• Various anticipated emission reductions (cleaner fuels, BART, CAIR, MERP)

• General guidance in GAQM Table 9-1 – “Other Sources” with reduced operating levels and reduced operating factors

Calculate distance (km) between project site and each FAR facility



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Calculate DISTKM (distance [km] to each FAR facility)

Calculate EMISFACT

EF01HOUR = 1000.00 / DISTKM

EF03HOUR = 1000.00 / DISTKM

EF24HOUR = 500.00 / DISTKM EFANNUAL = 100.00 / DISTKM

Annual Examples: EMISFACT = 2.00 at 50.0 km

EMISFACT = 20.0 at 5.00 km

EMISFACT = 200 at 0.50 km

R S



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FAR SummaryFAR Summary

Relatively simple, fast, easy Still under construction (work-in-progress)

Re-compute for each project location EMISFACT scalars

Possible Improvements: Post 1999 data

More pollutants (e.g., CO, Lead, H2S)

More release heights Refined scalars (e.g. by industry sector?)

Questions?

B k



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BreakBreak

Back in 15 Minutes

ROCSIPMA P j tROCSIPMA P j t



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ROCSIPMA ProjectROCSIPMA Project

Rochester and Olmsted County SIPs

PM10 and SO2 Maintenance AreasSeveral Rochester Facilities

Regional Sources (e.g., mobile sources)

• US Highways: 14, 52, and 63• IBM onsite (public) roads

Distant Sources via FAR data

Zero Sources (50km radius, county outline)

ROCSIPMA Summary – Next 32 Slides

ROCSIPMA T kROCSIPMA T k



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ROCSIPMA TasksROCSIPMA Tasks

Data Collection

Work Orders for Key Facilities

Literature values for roads and other sources

• Paved Roads and Highways; Unpaved Roads

• Other Sources (e.g., cooling towers)

“Actual” emissions for distant “FAR” sources

Computational Challenges

Many sources and many receptors “Key” sources for slow, 5-year runs

“ALL” sources for fast, event runs

R h t Hi h A tiR h t Hi h A ti



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Rochester Highway AssumptionsRochester Highway Assumptions

Average Daily Traffic (ADT) Rates

US Highway 14 at 25,000



Fleet-average vehicle weight of 5 Tons Paved road silt loading at 0.03 grams/m2

Receptors at 10, 20, 50, 100, 200 meters

Urban Dispersion

“CO URBANOPT 100000 Rochester 0.4”

Mi t T ffi C t D tMi t T ffi C t D t



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Minnesota Traffic Count DataMinnesota Traffic Count Data

R h t ADT (2004 D t )R h t ADT (2004 D t )



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Rochester ADT (2004 Data)Rochester ADT (2004 Data)

R h t Hi h (14 52 63)Rochester Highways (14 52 63)



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Rochester Highways (14,52,63)Rochester Highways (14,52,63)

Rochester Highway 52 ResultsRochester Highway 52 Results



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Rochester Highway 52 ResultsRochester Highway 52 Results

(1986 H1H 24(1986 H1H 24--Hour PM10 = 74 ug/m3)Hour PM10 = 74 ug/m3)

Rochester Highway PM10 TestsRochester Highway PM10 Tests



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g yg y

(ISCST3, ISC(ISCST3, ISC--PRIME, AERMOD)PRIME, AERMOD)

Rochester Public UtilitiesRochester Public Utilities – – Silver Lake PlantSilver Lake Plant

Sensitivity AnalysesSensitivity Analyses



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Sensitivity AnalysesSensitivity Analyses

Receptor Grid 360 polar receptors (36 directions and 10 downwind distances)

94 discrete receptors (property line)

6 Stacks: 4 Boilers and 2 Cooling Towers Group 1: SV03 (SH~90m) minimal building downwash

Group 2: SV01 (SH~61m) moderate building downwash

Group 3: SV02 (SH~61m) moderate building downwash Group 4: SV04 (SH~27m) extreme building downwash

Group 5: CT03 (SH~19m) cooling tower

Group 6: CT02 (SH~14m) cooling tower

7 Fugitive Sources (groups 7-13, respectively)

“ALL” Source Group (group 14)

Site Layout (2D View)Site Layout (2D View)



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3D View3D View Looking NorthLooking North



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3D View3D View – – Looking NorthLooking North



Polar ReceptorsPolar Receptors



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Polar ReceptorsPolar Receptors

Discrete ReceptorsDiscrete Receptors



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Discrete ReceptorsDiscrete Receptors

Base Case vs 84 “ABZ” TestsBase Case vs 84 “ABZ” Tests



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Base Case vs. 84 ABZ TestsBase Case vs. 84 ABZ Tests

AERMOD/AERMET/AERMAP (02222) First 100 Days of 1990 (Meteorology)

Base Case: RPU-SLP 24-Hour PM10 Modeling All “urban” LULC [Zo=1m]

84 “ABZ” Combinations [3*4*7=84] 3 Albedos (A=0.1, 0.3, and 0.5) [dark to light]

4 Bowen Ratios (B=0.1, 0.5, 0.9, and 4.0) [wet to dry]

7 Roughness Heights (Zo=0.01, 0.2, 0.4, 0.6, 0.8, 1.0,and 1.2 meters) [smooth to rough]

Results: “Percent of Base Case”

Group 1 (SV03)Group 1 (SV03) RuralRural ResultsResults



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Group 1 (SV03)Group 1 (SV03) UrbanUrban ResultsResults



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Group 1 (SV03)Group 1 (SV03) UrbanUrban ResultsResults

Groups 1Groups 1--66 RuralRural ResultsResults



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(SV03,SV01,SV02,SV04,CT03,CT02)(SV03,SV01,SV02,SV04,CT03,CT02)

Groups 1Groups 1--66 UrbanUrban ResultsResults

(SV03 SV01 SV02 SV04 CT03 CT02)



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(V i F iti S )



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(Various Fugitive Sources)(Various Fugitive Sources)


(Vario s F giti e So rces)



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All 14 Groups (6 Stacks, 7 Fugitives, ALL) All 14 Groups (6 Stacks, 7 Fugitives, ALL)

(Urban on Left; Rural on Right)(Urban on Left; Rural on Right)



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““100 Day Test” Summary100 Day Test” Summary



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y yy y

Tall (~GEP) Stacks Roughness Height is most important

Albedo & Bowen Ratio are less important Intermediate Stacks

Roughness Height is still most important

Albedo & Bowen Ratio are less important

Stub Stacks Roughness Height is not very important

Albedo & Bowen Ratio are not important

Fugitive Sources Roughness Height is most important

Albedo & Bowen Ratio are less important

DISPERSE TestsDISPERSE Tests



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DISPERSE Categories

Cultivated land (Zo~0.01m to 0.2m)50/50 mix (Zo~0.3m to 0.8m)

Deciduous forest (Zo~0.5m to 1.3m)

1986-1990 MSP/STC Meteorology

Rural vs. Urban (pop. 100,000; Zo=1m)

Results in Micrograms per Cubic Meter

DISPERSE ComparisonsDISPERSE Comparisons



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pp

Display Format (Group N; Modeling Method M) N.1 denotes ISCST3

N.2 denotes ISC-PRIME N.3 denotes AERMOD with 100% “urban” LULC

(RPU-Silver Lake [PSD] Project)

N.4 denotes AERMOD with DISPERSE LULC1(cultivated land)

N.5 denotes AERMOD with DISPERSE LULC2

(50/50 mix of cultivated land and deciduous forest) N.6 denotes AERMOD with DISPERSE LULC3

(deciduous forest)




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p ( )p ( )




(SV03 SV01 SV02 SV04 CT03 CT02)(SV03 SV01 SV02 SV04 CT03 CT02)



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(SV03 SV01 SV02 SV04 CT03 CT02)(SV03 SV01 SV02 SV04 CT03 CT02)



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All 14 Groups (6 Stacks, 7 Fugitives, ALL) All 14 Groups (6 Stacks, 7 Fugitives, ALL)




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(Urban on Left; Rural on Right)(U ba o e t; u a o g t)

DISPERSE SummaryDISPERSE Summary



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Significant changes from ISC to AERMOD

DISPERSE cases are (surprisingly) similar

Recall: AERMOD and 3 LULC cases

Significant seasonal variability seems to yield

the surprisingly similar results

BreakBreak



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Back in 15 Minutes

AERA/RASS with Q/CHI Sums AERA/RASS with Q/CHI Sums



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AERA option - computationally efficient

Eliminates conservative unpaired events

Input is “Q / CHI” instead of “Q”Output is “Risk” instead of “Concentration”

AERA/RASS with Q/CHI Sums AERA/RASS with Q/CHI Sums



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Input is “Q / CHI” instead of “Q”

Critical Health Index (CHI “concentration standard”)

Past approaches:

Unit emission rates (Q=1 gram/second) Other (MCES) approaches

Equivalent Risk Emission Rate (proposed by Mr.

Dustin Hamari, NRG)• Goal: incorporate into RASS spreadsheet

Q/CHI SumsQ/CHI Sums – – The MathThe Math



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Q/CHI for Source (i) = SUM (Qi,j / Ti)

Q(i,j) denotes source (i) and pollutant (j)

T(j) denotes Toxicity of pollutant (j)

Example: 1 source with M chemicals

Q1/T1 + Q2/T2 + Q3/T3 + … + Qm/Tm

Example: N sources with M chemicals SV001 = SUM (Q1m / Tm) for m=1 to M.

SV002 = SUM (Q2m / Tm) for m=1 to M.

SV003 = SUM (Q3m / Tm) for m=1 to M.

SV00N = SUM (Qnm / Tm) for m=1 to M.

Q/CHI Sums Advantages vs. RASSQ/CHI Sums Advantages vs. RASS



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Less conservative than DISPERSE

Reason: events are paired in time & space

Run many sources (RASS = 10 stacks)

Run all AERMOD source types

Point and Volume

Area (AREA, AREACIRC, AREAPOLY)

Needs no PLOTFILE or POSTFILE files

use PLOTFILE for plots & culpability tables

Q/CHI SumsQ/CHI Sums – – “Disadvantages”“Disadvantages”



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Need separate runs for each risk type 4 runs for total inhalation pathway risks

• Acute, sub-chronic, chronic, cancer

4 runs for total indirect pathway risks

• Farmer non-cancer and cancer

• Resident non-cancer and cancer

4 runs for total multi-pathway risks• Farmer non-cancer and cancer

• Resident non-cancer and cancer

Large AERMOD run times 20 hours for 4 risks with 15 sources & 1140 receptors

Internal calculations-less transparent than RASS Post-RASS software???



Paved RoadsPaved Roads



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EPA AP42 and EPA Mobile 6.2

MPCA Dual Adjustment (Optional) Includes speed adjustment: (S/30)0.5

• S = Speed in MPH

• Similar to unpaved road speed adjustment

Includes Mobile 6.2 tailpipe emissions• Onsite traffic (cars, trucks, etc.)

• Idling HDDV (heavy duty diesel vehicles)

• Generally small compared to re-entrainment

Dispersion based on Gilles et. Al. Atmospheric Environment (2005), p.2341-2347

Unpaved RoadsUnpaved Roads



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EPA AP42 Guidance

MPCA Guidance (same as EPA?)

Same dispersion as paved roads

Atmos. Environment (2005), p.2341-2347

Road DispersionRoad Dispersion -- Volume SourcesVolume Sources



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Volume Source Parameters (Rochester roads) TOP = 1.7 * Vehicle Height

Release Height = TOP / 2.0 Initial Sigma-Z = TOP / 2.15

Initial Sigma-Y = Spacing / 2.15

• Rochester Examples:• Spacing ~10m for roads with 1 lane each way

• Spacing ~20m for roads with 2 lanes each way

• Spacing ~25m for roads with 3 lanes each way

Reference: Gilles et. al. Atmospheric Environment (2005), p. 2341-2347

AP42 Silt Loading (grams/m2) AP42 Silt Loading (grams/m2)

Section 13.2.1 – Paved Roads



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Section 13.2.1 – Paved Roads AP42 Range for ”Public” Roads (Table 13.2.1-3)

Non-winter Conditions

• 0.6 for ADT<500

• 0.2 for ADT 500-5000

• 0.06 for ADT 5000-10000

• 0.03 for ADT>10000 Winter Conditions

• 2.4 for ADT<500

• 0.6 for ADT 500-5000• 0.12 for ADT 5000-10000

• 0.03 for ADT>10000



Measured Silt Loading ValuesMeasured Silt Loading Values



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Measured Values in Minnesota (Summer) OSB Manufacturers (Ainsworth [formerly Potlatch] –

Grand Rapids, Bemidji): GR=0.39, B=1.19 g/m2

• Similar facilities

• Both use natural gas and wood

• Silt loadings differ by factor of 3

Cereal Production (N. Gas) (Malt-O-Meal -Northfield): 0.5 g/m2

Soybean Processing (N. Gas, Diesel) (Minnesota

Soybean Processors - Brewster): 0.11 g/m2

Coal-Fired Public Utility (Virginia Public Utilities): 0.67to 9.3 g/m2



SCAQMD Rule 1186 CertifiedSCAQMD Rule 1186 Certified



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Exposure Profiling MethodExposure Profiling Method



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Exposure Profiling MethodExposure Profiling Method



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MPCA ExpectationsMPCA Expectations -- Silt LoadingSilt Loading



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MPCA Expectations Good documentation for proposed silt loading values

Companies will do some (extensive) on-site testing/cleaning, or use

• AP42 Table 13.2.1-4 (Industrial Facilities)

Permit Requirements Cleaning: sweeping, vacuuming, washing

Frequency: daily, weekly, monthly, annual

Testing: silt loading and/or exposure profiling

Other possible solutions Speed limits

Salt applications only – no sanding EMISFACT scalars (e.g., SHRDOW7)

Silt ContentSilt Content – – Unpaved RoadsUnpaved Roads



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MPCA Title V Default: 10%

EPA AP-42 Range for Industrial SitesMean Silt Content: 4.3 – 24%

Range of Values: 0.2 – 29%

No recent testing in Minnesota

Usual control: paving or watering or

chemical dust suppression

Cooling TowersCooling Towers



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EPA Guidance: AP42 Emission Factors

MPCA Emission Guidance (EPA or below)Reisman and Frisbie

“Calculating Realistic PM10 Emissions from

Cooling Towers”

MPCA Leads Meeting (Jan. 2002)

Model as point sources or volume sources

Fugitive PM10 SummaryFugitive PM10 Summary



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MPCA recommends that proposed silt values be part of themodeling protocol

Silt loading values from Table 13.2.1-3 will be less scrutinized forpublic areas and campus-like cases Public roads/highways (city, county, state, and federal)

Very light industry/manufacturing (e.g., IBM-Rochester)• Often minor or synthetic minor sources

Schools, universities, hospitals, R&D sites, etc.• Unpaved areas/shoulders are red flags (track-out)

Good Behavior: ISO14001, approved EMS, aggressive testing, etc.

Silt loading values from Table 13.2.1-3 will be closely scrutinized forindustrial facilities – examples (often major or PSD sources): Moderate industry (e.g., agriculture, ethanol)

Heavy industry (e.g., refinery, paper mill, mining)

VISCREENVISCREEN



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EPA model for visibility screening

Class I Areas

Class II (Near Field) Visibility Analysis

EPA Region V Requests

Citizen Complaints Does not address some issues (e.g., steam plumes)

What should be the criteria for “passing”?

• 1.0 * Class I values?• 2.0 * Class I values??

• 3.0 * Class I values???

Future PossibilitiesFuture Possibilities



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AERMOD Accelerator AERMOD.KEY (for slow 5-YEAR runs)

AERMOD.ALL (for fast EVENTFIL runs) FAR Improvements

Post-1999 data

More pollutants

RASS with ERER (by NRG)

Post-RASS via AERMOD with Q/CHI sums

Electronic Modeling Protocol/Checklist

Newer AERMET Data (e.g. 2001-2005)

Questions?Questions?



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Contact:

Chris Nelson at (651) 296-7750

Dennis Becker at (651) 297-7364

MPCA Web Site

http://www.pca.state.mn.us/

MPCA Air Dispersion Modeling web page

http://www.pca.state.mn.us/air/modeling.html

MPCA “Draft” AERMOD Data (Oct. 2005) http://www.pca.state.mn.us/air/modeling-data2.html







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