1. VISTAS Modeling Overview
Jan. 29, 2004

2. Shining Rock Wilderness Area, NC
VISTAS is evaluating visibility and sources of
fine particulate mass in the Southeastern US
Cold Mountain in
Shining Rock Wilderness Area, NC

3. There are 18 Class 1 areas within VISTAS region, IMPROVE operates monitors at 15 of the 18 Class I areas.

4. Inter-RPO Modeling Cooperation
Model performance evaluation/comparison
differences Southeast vs West
criteria vary as function of speciated PM2.5 mass
Implications for calculating relative reduction factors
If under predict high concentrations, under estimate rrf?

5. VISTAS Science Supports Regulatory Decisions
Air Quality
Air Quality
Responses
to Emission
Controls
gases
particles
deposition
visibility
Atmospheric
Model:
Chemistry
Transport
Deposition
Meteorology
topography
Policy
Interpretation
Emissions
anthropogenic
biogenic

6. 2001 Annual Average Light Extinction
Looking at visibility, the worst conditions in the country in 2001 were in the VISTAS region. Hot, humid, also highest occurrence of air stagnation in this region.
(would like to get slide to support above statement from Mike A.)
Mm-1
From VIEWS website

7. Light Extinction on 20% Poorest Visibility Days - IMPROVE 1998 - 200150
100
150
200
250
Coarse
Soil
Organics EC
NH3NO3
(NH4)2SO4
Rayleigh
Extinction (Mm-1)
(GO through these slides fairly fast because your audience knows their equivalent data.)
Sulfate is the largest contributor to light extinction at IMPROVE sites in the VISTAS region.
Higher extinction at Southern Appalachian sites than coastal sites. Higher extinction attributable to sulfate.
Organic carbon second highest contributor. Contribution less variable across region.
Organic carbon also fairly constant across seasons. From source apportionment analyses we are learning that in winter, organic carbon likely from primary sources such as gasoline, diesel, and wood smoke. In summer, higher fraction of organic carbon likely from secondary formation. VISTAS is
Nitrate, elemental carbon, soils, and coarse mass are small fractions of total extinction on poor visibility days.
Rayleigh (in turquoise) is scattering due to molecules in ambient air
Sipsey, AL
Dolly Sods, WV
Shenandoah, VA
Okefenokee, GA
Everglades, FL
Mammoth Cave, KY
Shining Rock, NC
Linville Gorge, NC
Swan Quarter, NC
Cape Romain, SC
Chassahowitzka, FL
James Rvier Face, VA
Great Smoky Mtns, TN

8. Light Extinction on 20% Best Visibility Days - IMPROVE 1998 - 200160 50
Coarse
Soil
Organics EC
NH3NO3
(NH4)2SO4
Rayleigh 40
Extinction (Mm-1) 30 20 10
In contrast, on the best visibility days, sulfate is a less dominant component of light extinction and nitrate is a somewhat larger component.
The clearer days in the Southeast are likely to be winter days. Nitrate doesn’t remain in particle phase at warmer temperatures, so nitrate is more likely to be formed in the winter than summer.
Sipsey, AL
Dolly Sods, WV
Shenandoah, VA
Cape Romain, SC
Okefenokee, GA
Everglades, FL
Mammoth Cave, KY
Shining Rock, NC
Linville Gorge, NC
Swan Quarter, NC
Chassahowitzka, FL
James Rvier Face, VA
Great Smoky Mtns, TN

9. Light extinction on 20% Haziest Days - IMPROVE (1998-2001)50
100
150
200
250
Coarse
Soil
Organics EC
NH4NO3
(NH4)2SO4
Rayleigh
Extinction (Mm-1)
Acadia, ME
Big Bend, TX *
Yosemite, CA
Lye Brooke, NH
Cape Romain, SC
Grand Canyon, AZ *
Boundary Waters, MN *
Great Smoky, Mtns, TN
* missing data 1-2 yrs

10. State Regulatory Activities
Emissions, Meteorological, Air Quality Modeling Deliverables
Draft 1/16/04
Jan-Mar 2004
Define inv growth and control assumptions
Jan-Jun 2004
Define BART sources
Jun 2004
Identify BART controls
June 2005
Economic Analyses
Jan 2004
Revised 2002 VISTAS Em Inv
Feb 2004
Em Modeling
QA + Fill Gaps
Apr 2004
Draft “2018”
National Inv
Sep 2004
Revised 2002
National Inv
Sep 2004
“Typical” 2002
Modeling Inv
Oct 2004:
Revised “2018”
Em Inv
Oct-Dec 2004:
Control Strategy
Inventories
Jan 2004
Met modeling
protocol
Feb 2004
MM5 Met runs
6 mo 2002
Sept 2004
MM5 Met
Final Report
Dec 2004
Revised 2002
Base Run (model performance)
Dec 2004
“Typical”
2002 Run
(compare to
“2018” runs)
Dec 04 ?
“2018” Base
Run
Jan-Jun 2005
“2018” Control Strategy Runs
Jan 2004
AQ Phase I
wrapup
Feb 2004
AQ modeling
protocol
Mar-Sep 2004
Annual 2002 CMAQ model
performance
Jan 2005
Phase II “2018”
Sensitivity Runs
EPA- approved
Modeling
Protocol
July-Dec 2005:
Observations
Conclusions
Recommendations
Apr 2004:
DDM in
CMAQ
May-Oct 2004
“2018” Emissions
Sensitivity Runs
Apr 2004
CART:select
episodes
Aug 2004
Natural Background and Reasonable Progress Goals
State Regulatory Activities
Dec 2004
Interim Future Year Inventories
Jan 2005
Interim Future Year Model Runs

11. Inter-RPO Modeling Cooperation
Emissions inventory consistency/compatibility
Data exchange protocol: common format
Common data repository? (not EPA)
Improvements for fire:
How temporally and spatially allocate emissions from fire activity data?
“Typical” base year or future year fire emissions
Other emissions improvements, e.g. NH3
Common/comparable future year assumptions
BART control technologies and costs of controls

12. VISTAS 2002 10-State Emissions Inventory6 5 4
Nonroad
Million tons/year
On-Road 3
Area
Industry 2
Utility 1
SO2
NOx
VOC
PM10
PM2.5
NH3
Aug 2003 draft, based on state/local inventory data or 1999 NEI v2, grown to 2002

13. SO2 Point Sources >5,000 Tons per year
1999 National Emissions Inventory v 2
This map illustrates concentration of sources in the region surrounding Shenandoah National Park.
This map also points to another desirable graphic capability: defining emissions sources in interactive Geographic Information System (GIS) data base.
Annual SO2 emissions
250,000
125,000
25,000

14. Wildfire PM2.5 Emissions for 8 VISTAS States*
2002 Emissions Calculated from State and Federal Fire Data
8,000
6,000
PM2.5 (Tons per year)
4,000
2,000
Jan Feb Mar Apr May Jun July Aug Sept Oct Nov Dec
* AL, GA, KY, NC, SC, TN, VA, WV. FL wildfire data to be added; MS wildfire data not available

15. VISTAS Inventory Next Steps
Revised 2002 inventory incorporating 2nd state review: delivered end Jan 04
Define “typical” base year fire and utility emissions: due Sept 04
Project emissions to future years, including BART controls: 1st draft due Apr 04, revised due Sep 04
2009/2010 interim year; 2015/2016/2018 future year
Cooperate with EPA, other RPOs for common protocols, growth and control assumptions

16. VISTAS Air Quality Modeling
Objectives:
Accurately represent meteorology, emissions, and air quality
MM5, SMOKE, CMAQ
Model base year to support both regional haze and PM2.5 regulatory requirements
Model future year and control strategies for regional haze
states responsible for PM2.5 attainment demonstrations
The most recent contract awarded was for meteorological modeling. This contract was awarded to Baron Advanced Meteorological Systems. They have recommended performance evaluation methods, delivered a review of meteorological sensitivities and recommended VISTAS sensitivity runs. They will run meteorological sensitivities for 3 episodes recommend protocol for annual run by Fall of 2003 and complete meteorological runs by December 2004.

17. VISTAS Air Quality Modeling
Phase I: Evaluate different model configurations for 3 episodes: Jan 02, July 99, July 01
Recommend annual modeling protocol Jan 04
Phase Ib: Evaluate emissions sensitivities
Decoupled Direct Method (DDM) to support design of emissions control strategies - initial results Sept 04
Phase II: Annual regional modeling
Base year modeling begins Feb 04
Future year control strategy runs completed 2005
The next contract to be awarded will be for emissions modeling and an integrated, one atmosphere, photochemical model for fine particulate matter to support regional planning for the VISTAS states & tribes.
3 bids from qualified contractors were received by January 31.
Plans are for a contractor selection by the end of February and for work to begin in March/April.
Work will include:
Emissions and Air Quality sensitivities runs for 3 episodes; a recommendation for protocol for annual modeling by Fall; base year and future sensitivities in 2004; and future year and control strategies in 2005.

18. VISTAS 36-km and 12-km CMAQ Modeling Domains

19. Inter-RPO Modeling Cooperation
Model sensitivities
Initial/Boundary Conditions
Chemistry: CB4, SAPRC, CB4-2002, AIMS sectional, CAMx4+
36 vs 12 km grid
Source Apportionment Techniques
2002 vs future year
Tracers vs sensitivity analyses

20. Phase I CMAQ Model Sensitivities
Fugitive dust transport factor
19 vs 34 vertical layers
Ammonia: seasonal and daily profile
Vertical diffusivity (affects mixing)
Height of planetary boundary layer
Boundary Conditions (BC)
CMAQ default vs GEOS-CHEM global model outputs
Alternative meteorology model configuration
Aerosol mass conservation: S, N
36 vs 12 km grid

21. Phase I CMAQ Model Sensitivities
CB4 Chemistry
SAPRC-99 Chemistry
CB Chemistry
CMAQ - AIM Sectional Approach
CAMx performance using similar configuration to best CMAQ

22. Annual SO4 Fine Particles Response to 10% Reduction in
SO2 Emissions from 2010 A2 strategy
SO4 Fine Particle Response (%)
-8.0
-6.0
-4.0
-2.0
0.0
Sipsey, AL
Cohutta, GA
Joyce Kilmer, NC
Great Smoky
Mtn, TN
Shining
Rock, NC
Gorge, NC
Linville
James River
Face, VA
Shenanhoah, VA
Otter Creek,
Dolly Sods, WV
Non-SAMI states
SAMI states
From SAMI Final Report, 2002