VISTAS Modeling Overview Jan. 29, 2004

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

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

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?

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

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

Light Extinction on 20% Poorest Visibility Days - IMPROVE 1998 - 2001 50 100 150 200 250 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

Light Extinction on 20% Best Visibility Days - IMPROVE 1998 - 2001 60 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

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

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

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

VISTAS 2002 10-State Emissions Inventory 6 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

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

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

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

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.

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.

VISTAS 36-km and 12-km CMAQ Modeling Domains

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

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

Phase I CMAQ Model Sensitivities CB4 Chemistry SAPRC-99 Chemistry CB4-2002 Chemistry CMAQ - AIM Sectional Approach CAMx performance using similar configuration to best CMAQ

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