Single Source Ozone and PM Mod

Ralph Morris 

ENVIRON International Corporation

rmorris@environcorp.com

EPA’s 9th Conference on Air Quality Modeli

Non-Guideline Applications

October 10, 2008
EPA Guidelines/Guidance 

Quality Modeling Assessm

 AERMOD for near-source (< 50 km) air qu

impacts of primary pollutants (EPA, 2005)

 CALPUFF for far-field (> 50 km) air quality 

of primary pollutants (EPA, 2003)

– CALPUFF adopted for SO2 and primary PM PS

increments and NAAQSs, not AQRV analysis

 Photochemical Grid Models (PGMs) recom

for ozone and secondary components of PSO4 & NO3) (EPA, 2007)

– Lagrangian models (e.g., AERMOD and CALPU

suitable for primary components
New Ozone and PM2.5 N

 New 0.075 ppm 8-hour and 35 μg/m

3 24-hr PM

NAAQSs will bring many more areas into nona

– PM2.5 NAAQS increases importance of secondary P

 Capability needed to obtain individual contribu

ozone and PM2.5 concentrations, deposition an

 Current guideline models have no (AERMOD) 

simplified (CALPUFF) representation of chemi

 Photochemical Grid Models (PGMs) have cap

correctly treat chemistry 

– But how can they resolve and correctly simulate nea

plume chemistry and dispersion?
Why PGMs Have Not Been Use

Address “Single Source” Impa

 PGMs can only resolve impacts to the gri

resolution

– Fine grid size needed near the source to reso

source plume chemistry and dispersion

Need many grid cells to assess downwind impactsHigh computer resource requirements

 Must account for all emission sources

Needed to correctly simulate chemistry

 Databases more costly to develop

MM5/WRF applicationsSMOKE or other emissions model

 More expertise needed in their applicatio
Recent Developments for “

Source” Modeling using P

 Two-way interactive grid nesting

– Allows fine grid over sources with coarser grid downwind 

when plumes are larger

 Flexi-nesting

– Can specify fine grid to resolve point source plume chem

and dispersion without providing met and emission input

 Full Chemistry Plume-in-Grid Modules

– Treats unique near-source chemistry of point source plu

 PM and Ozone Source Apportionment

– Allows individual source(s) assessments

 Computational advances Availability of PGM Databases and model set ups

– RPOs, AIRPACT, SIPs, etc.
Advanced Grid Nesting

 Two-way interactive grid nesting

– Allows specification of high resolution grid ove

with coarser grids downwind where plumes a

 Flexi-Nesting

– Interpolate meteorology, emissions and/or oth

for nested fine grid from coarse grid data

– Allows fine grid treatment of point source plum

Available within the CAMx model (just specify whe

domains are desired in job script)

Have developed tool to generate flexi-nest fine gri

CMAQ (for EPA/OAQPS)
Full Chemistry Plume-in

 Incremental chemistry approach allows fu

phase, aqueous-phase and aerosol chemwithin Plume-in-Grid modules

– CAMx Incremental Reactions for Organics an

(IRON) Plume-in-Grid (PiG) treatment

– CMAQ Advanced Plume Treatment (APT)

• Calculate chemical kinetic reaction rates using 

concentrations (PiG + Grid)

• Apply chemical rates to incremental concentra

puffs (PiG alone)

• When size of plume is commensurate with grid 

release incremental PiG concentrations to grid m
Full Chemistry Plume-in

 Important to simulate 

proper chemistry in early evolution of point source plumes

 Very little if any ozone 

and secondary PM2.5formed under Stage 1 and 2 plume chemistry conditions for large NOx sources

Stack
PM and Ozone Source 

Apportionment

 PM and Ozone Source Apportionment Te

(OSAT/PSAT) available in CAMx

– Uses reactive tracers that operate in parallel t

model and tracks ozone and PM formation baemission source regions and categories

– PSAT has five families of tracers: SO4; NO3/N

Primary PM; SOA; and Hg

 Similar approaches in CMAQ (TSSA and  Allows for identification of the ozone and 

impacts from several individual sources oof sources in single run
Example “Single Source” P

Applications

 Texas “Group BART” application

– CAMx 36/12 km with PiG and PSAT

 Estimation of individual contributions of 3

sources to annual PM2.5 in the eastern U.

– Individual point source contributions to 2009 a

PM2.5 concentrations

– Visibility Improvements for States and Tribal A

of the Southeast (VISTAS) and Association foIntegrated Planning of the Southeast (ASIP)

 Annual PM2.5 SIP modeling for St. Louis

– Effects of local sources on PM2.5 nonattainme
Texas Group BART Ana

 CENRAP 2002 36 km modeling CAMx databa

– Add 12 km flexi-nest grid covering Texas and nearby C– Use IRON PiG for Texas BART Source– Use PSAT to obtain PM2.5 contributions of groups of T

sources for comparison with 0.5 deciview threshold

-2736 -1872 -1008 -144 

-2088-1656-1224

-792-360

72

504936

13681800

TCEQ Task J

km

km

-936 -816 -696 -576 -456 -336 -216 -96 24 144 264 384

-1620-1500-1380-1260-1140-1020

-900-780-660-540-420

km

km
VISTAS/ASIP 36/12 km Dom

 2002 Annual Run

– 4 Quarters w/ ~15 – MPI w/ 6 CPUs

 36 km: 148 x 112  12 km: 168 x 177  19 Vertical Layer CMAQ V4.51 w/ 

– M3Dry– CBM-IV/AE4/SOR– SOAmods: In 2005 

enhanced CMAQ tSOA from sesquiteisoprene (Morris e
ASIP PM2.5 Point Source Contr

 Some ASIP/VISTAS states wanted to know individual con

several point sources to 2009 PM2.5 levels – 31 individual point sources in 6 states identified – Contributions due to SO2 and primary PM emissions request

 CALPUFF considered for assessment – Not consistent with CMAQ full-science chemistry – Provide inconsistent source contributions with 2009 PM2.5 SI ASIP 36/12 km database inappropriate for individual point 

modeling – 12 km grid cell size too coarse to treat chemistry and dispers

source plumes – Use of high enough resolution to resolve point source plume computationally prohibitive – Would need to perform base case and 31 zero-out runs to gesource contributions

 Elected to develop a new CAMx 2002 database: – 12/4 km domain with two-way nested grids – Plume-in-Grid to address near-source chemistry and dispers

– PM Source Apportionment Technology (PSAT) to obtain indi

contributions
 CAMx 12/4 km domain 

nested within ASIP 12 km CMAQ domain (one-way nesting)

 CAMx 12/4 modeling 

using two-way interactive grid nesting

 2002 base case using 

standard model

 2009 base case with 

PSAT PM2.5 source 

apportionment for 31 point sources

120 240 360 480 600 720 840 960 1080 1200 1320 

-1560-1440-1320-1200-1080

-960-840-720-600-480-360-240-120

0

120240360480

VISTAS CMAQ 12 km: 168 x 177 (108, -16

CAMx 12km: 54 x 71 (828, -6

CAMx 12km
900 1000 1100 12

-600-500-400-300-200-100

0

100200

CAMx 12km: 54 x 71 (8CAMx 04km (includes buffer cells):Steubenville/Wierton 26 x 35 (1Charleston 50 x 38 (1Louisville 17 x 26 ( Chattanooga/Knoxville 47 x 44 (1

4km Ch

4 km Loui

 CAMx 12/4 Domains Four 4 km domains: – Charleston-Huntington, 

KY/OH/WV – Wheeling-Weirton, OH/PA/WV – Louisville, IN/KY – Knoxville-Chattanooga, GA/KY/NC

 PSAT to obtain individual 

PM2.5 contributions from 

31 point sources

 Plume-in-Grid for 31 plus 

other large point sources
Huntington-Ashland and Charleston 4 

Map with FRM sites & Source Location

1180 1200 1220 1240 1260 1280 1300 1320 1340 13

-140-120-100

-80-60-40-20

0

Marathon Ashland Pet LLC

Ak Steel Corp

E I Dupont Inc

Kentucky Power Co Big Sandy Plant

Ohio Valley Electric Corp. Kyger Creek

Gavin Power Plant

Swva, Inc.

Dupont - Belle

Bayer Cropscience

Appalachian Power - Mountaineer Plant

Flexsys - Nitro Plant

Appalachian Power - John E Amos Plant

KY-Boyd-0017

KY-Carter-0500

OH-Lawrence-0010

OH-Scioto-0013

WV-Cabell-0006

WV-Kanawha-1005 WV-Kanawha-00

Appalachian Power - Kanaw

Appalachian Power - Philip Sporn Plant

Huntington Alloys

Union Carbide (Dow) So. Charleston Plan

Fmc Corporation - Steam Plant Clearon Corp.
Huntington-Ashland-Charleston: 4 

All Sources and SO4+Prim-PM

ASIP 2009 Q1 Projected SO4+EC+POC

0123456789

10

KY-Boyd-0017

KY-Carter-0500

OH-Lawrence-0010

OH-Scioto-0013

WV-Cabell-0006

WV-Kanawha-0010

WV-Kanawha-1005

Sources

SO4+EC+POC ug/m3

BCICOt

A

Fle

AA

OOPpClBa

A

UnFmDuIsg Sw HuBoE.Pa WWCaGaOR.KeE 

A

MaPs
ASIP 2009 Annual Projected SO4+EC+POC

0

0.5

1

1.5

2

2.5

3

KY-Boyd-0017 KY-Carter-0500

OH-Lawrence-0010 OH-Scioto-0013 WV-Cabell-0006 WV-Kanawha-0010 WV-Kanawha-1005

Sources

SO4+EC+POC ug/m3

Appalac

Flexsys 

AppalacAppalac

Ohio Pow Ohio Pow Ppg InduClearon Bayer Cr

Appalac

Union CaFmc CorDupont - Isg WeirtSw va, InHuntingtoBow ater E.U.Du PPa Pow eW.H. SamWheelingCardinal Gavin PoOhio ValR.E. BurgKentucky E I Dupon

Ak Steel 

Marathon Psi Energ

Huntington-Ashland and Charl4 km Grid; 31 Facilities

 Ak Steel Corp

 Swva Inc.

(12.9)

(10.3)

(13.7)

(15.0)

(14.5)

(13.3) (15.0)

(CAMx 4 km 2009 PM2.5 DVs)
ASIP 2009 Annual Projected PSO4

0

0.20.40.60.8

1

1.21.4

KY-Boyd-0017 KY-Carter-0500 OH-Lawrence-0010 OH-Scioto-0013 WV-Cabell-0006 WV-Kanawha-0010 WV-Kanawha-1005

Sources

PSO4 ug/m3

Huntington- Ashland and CharlestoFacilities; SO4 (left) and Primary PM 

ASIP 2009 Annual Projected PEC+P

0.000.200.400.600.801.001.201.40

KY-Boyd-0017 KY-Carter-0500 OH-Lawrence-0010 OH-Scioto-0013 WV-Cabell-0006 WV

Sources

PEC+POA ug/m3

SO4 Primary PM
Wheeling 4 km 

Domain Map with FRM sites and Source Locations

1320 1340 1360 1380 1

80

100120140160180200220

R.E. Burger Plant 

Cardinal Power Plant (Cardinal Operating

Wheeling-Pittsburgh Steel Corp

W.H. Sammis Plant

Pa Power Co/Bruce Mansfield Plt

Isg Weirton

Ppg Industries, Inc.

Ohio Power - Mitchell Plant Ohio Power - Kammer Plant

WV-Brooke-0005

WV-Hancock-0011

WV-Hancock-100

WV-Marshall-1002

WV-Ohio-0010

CAMx 04km (includes buffer cells):Steubenville/Wierton 26 x 35 (1316, 80) to (
ASIP 2009 Annual Projected SO4+EC+POC

0

0.5

1

1.5

2

2.5

WV-Brooke-0005WV-Hancock-0011WV-Hancock-1004WV-Marshall-1002 WV-Ohio-0010

Sources

SO4+EC+POC ug/m3

A

Fle

AA

OOPpClBa

A

UnFmDuIsg Sw HuBoE.Pa WWCaGaOR.KeE 

A

MaPs

Wheeling and Steubenville-Wekm Grid; 31 Facilities and SO4

(13.3)

(12.5)

(13.6)

(13.5) (12.8)

Isg Weirton

W.H. Sammis

Wheeling 

Pittsburgh Steel
Wheeling-Weirton: 31 Facilitie

(left) and Primary PM (right)

ASIP 2009 Annual Projected PSO4

0

0.30.60.91.21.5

WV-Brooke-0005

WV-Hancock-0011

WV-Hancock-1004

WV-Marshall-1002

WV-Ohio-0010

Sources

PSO4 ug/m3ASIP 2009 Annual Projected PEC+POA

0.000.300.600.901.201.50

WV-Brooke-0005

WV-Hancock-0011

WV-Hancock-1004

WV-Marshall-1002

Sources

PEC+POA ug/m3

SO4

Primary PM
St. Louis 2003-2005 Annua

Design Values
-500 0 500 1000 1500

-1500-1000

-500

0

500

Domain 1 (68x68)

Domain 2 (128x149)

Domain 3 (92x113)

St. 

Regio

km 

CM

SO

Projecte

2012 P

Values 

City a

Louis st

annu

N
Evidence that local sources contribute 

nonattainment at Granite City Monitor Washington St. Monitor (A)
Hybrid CAMx 2002 12/4/1 km 

Modeling with PiG for Local 

 BCs for from CM

km regional mod

 12/4/1 km two-w

interactive grid n

– Allows for recircu

pollutants within 

 Plume-in-Grid a

used for local so

– Subgrid-scale sa

use to sample pureleased to grid

– Ability for near-so

300 350 400 450 500 550 600 650 700 750 800 line” impacts 

-400-350-300-250-200-150-100

-50

0

50

100
Preliminary Results for To

PSAT_PIG - P25

05

10152025

Q1

Q2

Q3

Q4

ANN

Q1

Q2

Q3

Q4

ANN

Q1

Q2

Q3

Q4

ANN

Q1

Q2

Q3

Q4

ANN

Q1

Q2

Q3

Q4

ANN

Q1

Q2

Q3

Q4

ANN

Q1

Q2

Q3

Q4

Washington Ave. Granite City East St. Louis Ferguson Blair St. Margaretta 2nd & Mou

Concentration

Local Sources contributing ~7 and ~3.4 μg/m

3 to annual average 

PM2.5 at Washington Street and Granite City monitoring sites
St. Louis Conceptual M

 Turner and co-workers (2007a,

developed a Conceptual Model exceedances in the St. Louis a

– They found that local sources co

μg/m

3 to PM2.5 at the Granite City 

average

– The CAMx 12/4/1 km PiG model

3.4 μg/m

3 to local sources at Gra

– Turner, J.R. and J.L. Garlock. 2007a. A Concep

Fine Particulate Matter over the St. Louis Area. RWashington University, St. Louis, MO. October.

– Turner, J., J. Garlock, S. Raffuse, J. Rubin, S. Br

G. Norris. 2007b. Task#5 Transport Regimes AnTechnical Memorandum. Washington University, October.

– Turner, J.R., J. Garlock, J. Jaeckels and J. Schau

Fine Particulate Matter Carbon Apportionment, VUniversity, St. Louis, MO. October.

– Turner, J. and J. Garlock. 2007d. Task#4 Urban

and Intraurban Variability, Version 1. Washington MO. October.

W a sh in g to n A ve .

G ra n ite C ity

E a st S t. L o u is

Fe rg u so n

B la ir S t.

M a rg a re tta

2 n d & M o u n d

ANN

BCICSurface sourcesOther PointSourcesSource#1Source#2Live Puff

05

10152025

W a sh in g to n A ve .

C o n c e n tra tio n
Conclusions

 Recent advances in PGMs make them more sui

assessing “single source” contributions to ozone

visibility and deposition – Fine resolution grids, two-way grid nesting, and flexi-ne

– Full chemistry Plume-in-Grid modules – Ozone and PM source apportionment – Full gas-phase and aqueous-phase chemistry and aero

thermodynamic modules

 The use PGM modeling to assess “single source

quality, visibility and deposition issues has becoroutine: – ASIP point source PM2.5 assessment – Oil and gas AQ and AQRV assessments as part of NE

– Texas and Arkansas BART assessment – PM2.5 SIP modeling