Alternative Model Simulations: CAMx vs' CMAQ and PSAT vs' TSSA

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Alternative Model Simulations CAMx vs. CMAQ and
PSAT vs. TSSA
Ralph Morris, Greg Yarwood, Bonyoung Koo, Steven
Lau and Abby Hoats ENVIRON International
Corporation, Novato, CA Gail Tonnesen, Chao-Jung
Chien and Zion Wang University of California,
Riverside
WRAP Modeling Forum Meeting, San Francisco, CA
March 8-9 18, 2005
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Content

• Purpose
• Approach
• CAMx/CMAQ Model Performance Evaluation
• PM Source Apportionment Technology (PSAT)
• Formulation and Testing
• WRAP Application
• Comparisons with CMAQ TSSA
• Conclusions on Alternative Models and PM Source
  Apportionment

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Purpose

• Compare CMAQ and CAMx model performance for
  February and July 2002 using latest 2002
  databases
• Compared CMAQ Tagged Species Source Apportionment
  (TSSA) and CAMx PM Source Apportionment
  Technology (PSAT)
• ? Should we run alternative models for key
  2002 simulations in 2005-2006?

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Approach (1)

• Develop CAMx modeling databases for February and
  July 2002 and the 36km Continental US Inter-RPO
  Domain
• 15 day spin-up period (45 day simulations)
• MM5CAMx to process latest 2002 36 km MM5 data
• Used CMAQ Kv vertical diffusivity option
• CMAQ-to-CAMx Processors
• IC/BC and Emissions
• Develop other CAMx inputs
• Photolysis rates (TUV), landuse and terrain,
  Albedo/Haze/Ozone column, etc.

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Approach (2)

• Perform February and July 2002 36 km CAMx Base D
  (pre02d) Base Case simulations
• Model performance evaluation and comparison
  against CMAQ Base D (pre02d) Base Case
• Set up CAMx PSAT PM Source Apportionment using
  same source regions and categories as CMAQ TSSA
• Run for Sulfate and Nitrate source apportionment
  and compare with CMAQ TSSA

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Approach (3)

• Extract PSAT SO4 and NO3 Source Apportionment
  results at Class I areas
• Generate 24-hour average Model performance
  evaluation and comparison against CMAQ Base D
  (pre02d) Base Case
• Set up CAMx PSAT PM Source Apportionment using
  same source regions and categories as CMAQ TSSA
• Run for Sulfate and Nitrate source apportionment
  and compare with CMAQ TSSA for 24-hour impacts at
  Class I areas

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Model Evaluation CAMx/CMAQ

• Continental US 36 km Inter-RPO Domain
• 6 Subregions All US, WRAP, CENRAP, MRPO, VISTAS
  and MANE-VU States
• Three Networks IMPROVE, CASTNet, STN
• PM Species Components
• SO4, NO3, EC, OC, Soil, CM and TCM
• CAMx V4.20beta Base D (pre02d) vs. CMAQ V4.4 Base
  D (pre03d)

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SO4 July 2002 USA CMAQ vs. CAMx Base D
SO4 CASTNet
SO4 IMPROVE
IMPROVE
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SO4 2002 USA CMAQ vs. CAMx Base D
Jan SO4 IMPROVE
Jul SO4 STN
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SO4 Jan 2002 USA CMAQ vs. CAMx Base D
SO4 Jan STN
SO4 Jan CASTnet
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NO3 July 2002 USA CMAQ vs. CAMx Base D
NO3 IMPROVE
NO3 CASTNet
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NO3 July 2002 USA CMAQ vs. CAMx Base D
NO3 STN
HNO3 CASTNet
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NO3 January 2002 USA CMAQ vs. CAMx Base D
NO3 IMPROVE
NO3 CASTNet
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NO3 Jan 2002 USA CMAQ vs. CAMx Base D
NO3 STN
HNO3 CASTNet
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Carbon July 2002 USA CMAQ vs. CAMx Base D
OC IMPROVE
TCM STN
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Carbon Jan 2002 USA CMAQ vs. CAMx Base D
OC IMPROVE
TCM STN
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EC IMPROVE USA CMAQ vs. CAMx Base D
July EC
January EC
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Hourly TCM July 2002 at SEARCH Yorkville Observed,
CMAQ and CAMx
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SOIL IMPROVE USA CMAQ vs. CAMx Base D
July SOIL
January SOIL
Note that Crustal emissions were not modeled
separately as normally done in CAMx due to use of
CMAQ2CAMx processor
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CM IMPROVE USA CMAQ vs. CAMx Base D
July Coarse Mass
January Coarse Mass
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SO4 IMPROVE WRAP CMAQ vs. CAMx Base D
July SO4 WRAP
January SO4 WRAP
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NO3 IMPROVE WRAP CMAQ vs. CAMx Base D
July NO3 WRAP
January NO3 WRAP
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OC IMPROVE WRAP CMAQ vs. CAMx Base D
July OC WRAP
January OC WRAP
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EC IMPROVE WRAP CMAQ vs. CAMx Base D
July EC WRAP
January EC WRAP
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SOIL IMPROVE WRAP CMAQ vs. CAMx BaseD
July SOIL WRAP
January SOIL WRAP
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CM IMPROVE WRAP CMAQ vs. CAMx Base D
July Coarse Mass WRAP
January Coarse Mass WRAP
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Conclusions CMAQ vs. CAMx Performance

• Both models exhibit very similar good model
  performance for SO4 in summer
• Slight SO4 overestimation in winter, CAMx
  overestimation greater than CMAQ
• Both models poor NO3 performance
• Summer underestimation (CMAQ worse than CAMx)
• Winter overestimation (CAMx worse than CMAQ)
• OC, EC, TCM, Soil and CM performance mixed
• Further analysis needed

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Source Apportionment Approaches

• CALPUFF chemistry highly simplified, incorrect
  and over 20 years old (1983)
• SCICHEM needs 3-D concentrations fields,
  currently computationally demanding
• Photochemical Grid Models
• Zero-Out Runs (actually sensitivity approach)
• Reactive Tracer PSAT/TSSA approaches shows
  promise for source apportionment modeling

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PM Source Apportionment Technology (PSAT)

• Reactive tracer approach that operates in
  parallel to the host model to track PM precursor
  emissions and formation
• Set up to operate with families of tracers that
  can operate separately or together for
• Sulfate, Nitrate, Ammonium, Mercury, Primary PM
  (EC, POA, crustal and other)

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PSAT Conceptual Approach

• Modify CAMx to include families of tracers
  (tagged species) for user selected source
  groups
• Source group source category and/or geographic
  area
• Build on CAMx ozone apportionment schemes (OSAT,
  APCA)
• Tag primary species as they enter the model
• SO2i , NOi , VOCi , primary PM (crustal, EC,
  etc.)
• When secondary species form, tag them according
  to their parent primary species
• SO4i , NO3i , SOAi

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Zero-Out Comparisons for Sulfate

• Use Eastern US/Canada modeling domain
• Add four hypothetical point sources to base
  emissions
• Test large and small emission rates to
  investigate signal/noise
• Large SOx 850 TPD
• Small SOx 0.85 TPD

X
X
X
X
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MRPO Large Source Episode Maximum SO4 PSAT
versus Zero Out
PSAT
Zero-Out
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MRPO Large Source Episode Average SO4 PSAT
versus Zero Out
PSAT
Zero-Out
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Oxidant Limiting Sulfate Example
PSAT
Zero-Out

• PSAT attributes 50 of SO4 to source A (and 50
  to B)
• Zero-out attributes zero SO4 to source A (no
  source is culpable)
• Zero-out result (sensitivity) is not a reasonable
  apportionment for this example

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PSAT Sulfate Evaluation

• Good agreement for extent and magnitude of
  sulfate impacts between PSAT and zero-out
• Comparing the outer plume edge is a stringent
  test
• Zero-out impacts can be smaller or larger due to
  oxidant limited sulfate formation and changes in
  oxidant levels.
• Run times look very good
• PSAT obtains 50 SO4 source contributions in time
  needed for 1 zero-out assessment

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PSAT Chemical Scheme for NOy Gasses

• PSAT tracks 4 groups of NOy gasses
• RGN
• TPN
• HN3
• NTR
• Conversion of RGN to HN3 and NTR is slowly
  reversible
• Conversion of RGN to TPN is reversible rapidly
  or slowly

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PSAT Partitioning of NOy Gasses
CAMx box model run with 20 ppb initial NO and 100
ppb NO emissions at a constant rate. Looks
reasonable, is it correct?
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Independent Check for NOy SOEM

• SOEM Source Oriented External Mixture
• We only use part of the SOEM concept here
• Duplicate all NOy reactions in the chemical
  mechanism
• blue NOy and red NOy
• affects NO, NO2, PAN, HNO3, etc.
• difficulty for self-reactions, e.g., NO NO --gt
  2 NO2
• forms red, blue and purple NO2
• SOEM may change the base result
• Model initial conditions (ICs) as blue NOy
• Model emissions as red NOy
• Implemented in CAMx, run for 1-D case (box model)

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Comparing SOEM and PSAT for NOy

• The independent SOEM method agrees well with PSAT

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Testing Secondary Organics (SOA)

• CAMx SOA scheme
• VOC -- OH, O3, NO3 --gt Condensable Gas (CG) ltgt
  SOA
• CGs partition to an SOA solution phase
• PSAT implementation straightforward, but many
  terms
• Three types of VOC precursor
• alkanes, aromatics, terpenes
• Five pairs of CG/SOA
• four anthropogenic, one biogenic
• low/high volatility products
• PSAT tracers for VOC, CG and SOA species
• Test implementation using another SOEM method
• duplicate red/blue reactions and species,
  similar to NOy testing

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PSAT apportionment of SOA to ICs and Emissions
Biogenic emissions
Biogenic ICs
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PSAT SOA Apportionment for Emissions

• Excellent 11 correspondence between SOEM and
  PSAT results

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PSAT SOA Apportionment for Ics

• 11 correspondence for ICs as well as for
  Emissions (last slide)
• Conclusion PSAT implementation for SOA is
  accurate

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Full-Scale Application Testing by MRPO

• 13 Source Regions
• 6 Emission Categories
• Boundary Conditions
• Initial Conditions
• Source apportionment to 90 groups for SO4, NO3,
  NH4, SOA and 6 primary species
• Results courtesy of Kirk Baker, LADCO/MRPO

Canada
WRAP
MANE-VU
MRPO
CENRAP
VISTAS
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Episode Average On-Road PNO3 for January 2002
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Episode Average Point Source PSO4 for June 2002
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Episode Average Biogenic SOA for June 2002
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WRAP PSAT Source Categories

• Sulfate Family (2)
• SO2 (SO2)
• PS4 (SO4)
• Nitrate Family (5)
• RGN (NOxNO3HONON2O5)
• TPN (PANPNA)
• NTR (RNO3)
• HN3 (HNO3)
• PN3 (PM NO3 )
• Ammonium Family (2)
• NH3 (NH3)
• PN4 (NH4)
• SOA (14), Hg (3) and Primary PM (6) Not Run

• 15 Source Regions
• 5 Source Categories
• Biogenic
• On-Road Mobile
• Points
• Fires
• AreaNon-Road
• Initial Concentrations
• Boundary Conditions
• 77 Source Groups (7715 x 5 2)

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PSAT/TSSA Source Region Map CA, NV, OR, WA, ID,
UT, AZ, NM, CO, WY, MT, ND, SD, Eastern States
and Mex/Can/Ocean
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PSAT vs. TSSA

• 24-hour Sulfate contributions ay Class I areas in
  the WRAP States
• February and July 2002
• Bar charts of Sulfate contributions by source
  group Category_Area
• Category Bio, Mob, Pts, Fir, ANR
• Area CA, NV, OR, WA, , SD, EST, Mex
• Pts_NM Point sources from New Mexico
• ANR_AZ AreaNon-Road sources from Arizona
• Some differences in TSSA/PSAT Categories
• TSSA mv on-road non-road fires??? BCs???

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TSSA/PSAT results for selected sites ARCH, FLAT,
FOPE, GRCA, LOPE, LYND, MEAD, NOPL, ORPI, RMHQ,
SAAN, SALM, SCOV, SEQI, SOLA, STPE, THBA
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Grand Canyon, Arizona Day 182 (07/01/02) 2nd
Worst Visibility Day in 2002 NV Points
Highest AZ Points (5xsmall) Mex Points TSSA
Units??? TSSA Other???
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Grand Canyon, Arizona Day 188 (07/07/02) 15th
Worst Visibility Day in 2002 Some differences
TSSA and PSAT Pts_Mex, Other, BC
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Grand Canyon, Arizona Day 194 (07/13/02) 7th
Worst Visibility Day in 2002 Pts_NV by far
largest contributor for both TSSA and PSAT
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Grand Canyon, Arizona Day 32 (02/01/02) 8th Best
Visibility Day in 2002 PSAT UT_Points BC
AZ_Points UT_NonRoad NM_Points TSSA UT_Points
Other OR_Points WA_Points ID_Points
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FOPE, Fort Peck, Montana Day 185 (07/04/05) 6th
Worst Day during 2002 Generally good agreement
between PSAT and TSSA
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Rocky Mtn. NP, Colorado Day 182 (07/01/05) Worst
Day of 2002 PSAT UT_Fires CO_Pts NV_Pts
CO_Fires UT_Pts. TSSA Other CO_Pts UT_Pts
NV_Pts If Fires in Other then fairly good
agreement
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Rocky Mtn. NP, Colorado Day 185 (07/04/05) 14th
Worst Day of 2002 PSAT CO_Pts CO_NonRoad
UT_Fires, East_Pts TSSA CO_Pts CO_Mobile
Other East_Pts
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Rocky Mtn. NP, Colorado Day 191 (07/04/05) 11th
Worst Day of 2002
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SALM, Idaho Day 182 (07/01/05) With exception of
Other (TSSA) and BC (PSAT) agree on top
contributors
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Conclusions Alternative Model

• Alternative Model to CMAQ (CAMx)
• Addresses some model uncertainty using
  corroborative model (EPA, 2001)
• Uses alternative science algorithms
• Powerful diagnostic tool
• Small additional work to operate as can use same
  MM5 (MM5CAMx) and SMOKE (CMAQ-to-CAMx) output

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Conclusions PM Source Apportionment

• PM Source Apportionment Technology (PSAT) results
  mostly consistent with TSSA
• Some differences, TSSA Other category makes it
  hard to interpret
• Powerful diagnostic tool that can be used for
  source culpability (e.g., BART) and to design
  optimally effective control PM/visibility control
  strategies
• Explains 100 of the PM sulfate and nitrate,
  doesnt suffer Other unexplained portion of PM
  like TSSA

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BART Modeling using Grid Models

• Midwest RPO (MRPO)
• Use combination of photochemical grid and CALPUFF
  modeling in the BART analysis
• Comprehensive Air-quality Model with extensions
  (CAMx) PM Source Apportionment Technology (PSAT)

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CALPUFF estimates higher visibility impacts than
CAMx/PSAT and consequently generally more days
and larger spatial extent of dV gt 0.5 deciview
PSAT
CALPUFF
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July 19, 2002 24-Hour SO4 Concentrations IN
Source (isgburn) CALPUFF much higher
concentrations away from source. Why secondary
CALPUFF SO4 peak over Cape Cod?
CAMx PSAT
CALPUFF