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Overview of Other RPO Modeling Work

Ralph Morris ENVIRON International Corporation Joint Modeling Forum and Attribution of Haze Workgroup Meeting San Diego, California November 2, 2006. Overview of Other RPO Modeling Work. CENRAP ENVIRON and UCR MRPO LADCO w/ assistance from contractors VISTAS ENVIRON, UCR and Alpine

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Overview of Other RPO Modeling Work

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  1. Ralph Morris ENVIRON International Corporation Joint Modeling Forum and Attribution of Haze Workgroup Meeting San Diego, California November 2, 2006 Overview of Other RPO Modeling Work

  2. CENRAP ENVIRON and UCR MRPO LADCO w/ assistance from contractors VISTAS ENVIRON, UCR and Alpine MANE-VU NESCAUM, OTC, MARAMA, States Other RPO Modeling

  3. 2002 Actual Base Case MPE CMAQ and CAMx @ 36 km 2002 Typical Base Case (Base F latest) 2018 Base E2 Emissions and CMAQ Working on 2018 Base F Preliminary 2018 CAMx/PSAT runs Identify contributions of International Transport How to work into Reasonable Progress 2018 Base E2 Visibility Projections Comparisons with WRAP, MRPO and VISTAS 2018 Base F visibility projections ongoing Ready in about 4 weeks CENRAP Update

  4. Treatment of International Transport • Modeled Uniform Rate of Progress (URP) test compares against 2018 Goal from Glide Slope 2000-2004 Baseline to 2064 Natural Conditions • Modeled 2018 visibility projection includes contributions from International Transport and Natural Sources that are not completely accounted for in 2064 Natural Conditions • Regional Haze Rule goal is no man-made visibility impairment in 2064 • For demonstrating Reasonable Progress does this just apply to US man-made (controllable) sources? • CENRAP Visibility Projections found Class I areas on US international border fail to meet URP goal • How to treat International Transport in modeled URP test?

  5. How to Treat International Transport in Reasonable Progress • Approach 1: Include International Transport with the 2064 Natural Conditions Goal • Can use different estimates of International Transport (GEOS-CHEM, PSAT, etc.) • Simple to implement • Keeps Glide Slope in deciview • Inconsistent with Regional Haze Rule 2064 Natural Conditions goal? • Not liked by FLMs

  6. How to Treat International Transport in Reasonable Progress • Approach 2: Define 2064 goal as Elimination of U.S. Anthropogenic Emissions Contribution to Visibility Impairment • Interpretation of the “no man-made impairment” as U.S. man-made impairment • Need approach to track U.S. anthropogenic contribution • 2064 goal is zero • Must use Extinction (Mm-1) to calculate

  7. Intl Transport & Reasonable Progress • Approach 3: Adjust modeled 2018 visibility projection to account for International Transport (FLM suggestion) • Consistent with Regional Haze Rule • How and what to do? • (3A) Assume International Transport component is reduced same amount as U.S. anthropogenic emissions component • If International Transport is above and beyond Natural Conditions then this seems reasonable • Can keep deciview • Promotes fairness across States with Class I areas in center versus border of U.S. • (3B) Other???

  8. CENRAP PM Source Apportionment • PM Source Apportionment Technology (PSAT) • 2018 Base D CAMx Database • State Level Geographic Regions • CENRAP and Adjacent States • Track Three Families • SO4; NO3 & Primary PM [No SOA or Hg] • Use standard model output to split SOA into anthropogenic and biogenic SOA (SOA_A & SOA_B) • No geographic source apportionment for SOA

  9. 22 Separate States; rest of West and East US; Canada; Mexico GulfMex ; IC; & BC

  10. Geographic PSAT • 2018 Base D Emissions Scenario • Class I areas for W20% Days • Convert to Extinction (Bext) and determine State’s contribution to Visibility Impairment on Worst 20% • Can also partition by RPO and split International vs. U.S. Sources • Only geographic Source Apportionment at this time • Can not Separate Natural from Anthropogenic U.S. (except for SOA_B)

  11. Wichita Mountains, Oklahoma Visibility Extinction (Mm-1) Source Apportionment for the Worst 20% Days 70  SOA_B & SOA_A All Sources  BCs (Global Transport)  Mexico  VISTAS + MANE-VU  CENRAP

  12.  SOA_B & SOA_A All Sources  BCs (Global Transport) ~60% of visibility extinction on average of Worst 20% Days due to international transport  Mexico  CENRAP States (Texas largest) Big Bend National Park, Texas Visibility Extinction Apportionment Worst 20% Days

  13. 22% due to non-US Anthro Sources Wichita Mtns Oklahoma Bext

  14. 24% due to non-US Sources BSO4

  15. 13% due to non-US Sources BNO3

  16. International Transport Methods • Use PM Source Apportionment Technology (PSAT) to separately track contributions due to International Transport • Initial results for 2018 Base D • Zero-Out GEOS-CHEM global chemistry model (eliminate U.S. sources or eliminate International sources) • Initial results from EPRI study with Harvard • Two “independent” approaches for estimating contributions of International Transport to PM concentrations at Class I areas. • How do PSAT and GEOS-CHEM results compare?

  17. CAMx/PSAT Sulfate (SO4) Annual Average International Transport by CAMx/PSAT and GEOS-CHEM models Excellent to Good Agreement of Two Methods Not truly “independent” evaluation since CAMx/PSAT runs used GEOS-CHEM BCs, but results encouraging GEOS-CHEM

  18. CAMx/PSAT Organic Carbon Mass (OCM) Annual Average International Transport by CAMx/PSAT and GEOS-CHEM models Reasonably Good Agreement of Two Methods, As much as a Factor of Two Different (LYBR), but most fairly close Larger differences in OCM. CAMx/PSAT includes OCM from Biogenic Sources so expected to be higher, but frequently lower? GEOS-CHEM

  19. CAMx/PSAT Elemental Carbon (EC) Annual Average International Transport by CAMx/PSAT and GEOS-CHEM models Differences in fires may be affecting results. Large Quebec fires in 2002 affect CAMx/PSAT. Mex fires in GEOS-CHEM? GEOS-CHEM

  20. Accounting for International Transport • Run PSAT for 2002 and 2018 separating controllable and uncontrollable (or US vs. International Transport) components • Approach 1: Add “International Transport” component to Natural Conditions for 2064 goal and redefine 2018 URP goal from 2000-2004 Baseline to new 2064 goal (in deciviews) • Approach 2: Redefine URP goal based on Controllable haze only. 2064 endpoint would be zero (no man-made impairment) • Examples of these approaches using current 2018 PSAT run follows • International Transport = Uncontrollable = Mex+Can+BCs+SOA_B

  21. Big Bend: Standard URP Calculation = 31% of URP goal

  22. Big Bend: Approach 1 IntlTrans in 2064 Natural Conditions = 62%

  23. Big Bend: Approach 2 URP Based on Controllable Haze = 31%

  24. Big Bend Example • Standard URP = 31% • Intl Trans in 2064 = 62% • Controllable URP = 31% (???) • Could not do this correctly since only had geographic PSAT for 2018 and natural emissions were included in US portion • Also need 2002 source apportionment • CENRAP intends to correct this with Base F modeling

  25. CENRAP PSAT Next Steps • International Transport and Natural Conditions Analysis combined with Control Strategy Design Analysis • Source Regions: CENRAP States and Nearby WRAP, MRPO and VISTAS States • Source Categories: EGU, Non-EGU Point, On-Road Mobile; Off-Road Mobile; Natural Emissions (Biogenics, Wildfires, Non-Ag WBD); Remaining Anthropogenic (e.g., area, Ag WBD) • 2002 and 2018 Base Case emissions

  26. CENRAP PSAT Source Regions

  27. MM5 Meteorology 2001, 2002, 2003 36-km for regional haze & PM2.5 2002 12-km for 8-hour ozone EMS Emissions (Base K) Starting to Migrate to CONCEPT CAMx Air Quality Model CMAQ may be used for corroborative analysis Update model for SOA treatment Using PSAT and OSAT Aggressive Movement to 2005 Modeling Year Driven by 8-hour ozone and PM25 issues Midwest RPO Modeling

  28. Update Biogenic Emissions Model to MEGAN and Generate all SOA precursor Species E.g., sesquiterpenes Update CAMx SOA Module Treat new SOA precursors Separate emissions for SOA species from gas-phase chemistry species Slightly different than VISTAS SOAmods update that is plug and play with current biogenic emissions Considering directly emit Condensable Gases (CG) from mobile sources Midwest RPO SOA Updates

  29. Need to address 8-hr ozone and PM2.5 as well as regional haze BART for non-EGUs Beyond CAIR scenario for EGUs Fuel scenarios for urban ozone/PM2.5 Combined with Northeast to look at regional diesel retrofit controls Midwest RPO Controls

  30. 2002 36/12 km MM5 SMOKE 36/12 km CMAQ 2002 36/12 km Looked at CAMx early on but dropped due to resource and time constraints Led to addition of biogenic SOA treatment Just finished Base G (final) Modeling 2009 8-hour ozone and PM25 projections under ASIP Visibility projections 36-km vs. 12-km similar Using both 36 km and 12 km grid for 2009 and 2018 projections VISTAS Modeling

  31. 2018 Base G Visibility Projections • 2018 36/12 km Base G OTB Base Case • With CAIR but Without BART • New and Old IMPROVE equation • New Natural Conditions for New IMPROVE from VIEWS • Previously presented preliminary 2018 36 km Base G visibility projections • Data substitution updates since then

  32. Data Substitution Updates • New data substitution database received from ARS on October 19, 2006 • Add one more site (CADI1) to New IMPROVE equation database • Old IMPROVE still not supporting CADI1 • Update MING1 with latest data from UC Davis • Other minor updates (BRET1, etc.) • Always use newest data when available • Still using old substitution data for CHAS1 as missing data in 2003 & 2004 not in new database • Display using “DotPlots”, percentage of achieving 2018 URP goal

  33. CMAQ 2018g1a/Typ02g Method 1 predictions for VISTAS+ sites 200% CMAQ New IMPROVE Algorithm 12km CMAQ Old IMPROVE Algorithm 12km 180% CMAQ New IMPROVE Algorithm 36km CMAQ Old IMPROVE Algorithm 36km 160% 140% 120% Percent of target reduction achieved 100% 80% 60% 40% 20% 0% JARI1 SIPS1 LIGO1 CADI1 BRIG1 MING1 BRET1 OKEF1 HEGL1 EVER1 SHEN1 CHAS1 UPBU1 CACR1 SAMA1 SHRO1 MACA1 DOSO1 COHU1 GRSM1 ROMA1 SWAN1 VISTAS non-VISTAS

  34. Comparison of VISTAS 2018 36/12 km Base G New/Old IMPROVE projections with CENRAP 36 km New/Old and MRPO 36 km Old IMPROVE projections CMAQ Method 1 predictions for VISTAS+ sites Across RPOs VISTAS New Algo 12km (baseG) 200% VISTAS Old Algo 12km (baseG) VISTAS New Algo 36km (baseG) 180% VISTAS Old Algo 36km (baseG) CENRAP New Algo 36km (18e2 SOA) CENRAP Old Algo 36km (18e2 SOA) 160% MwRPO Old Algo 36km (R4s1a) 140% 120% Percent of target reduction achieved 100% 80% 60% CENRAP/MRPO Visibility Projections Now Much More Consistent with VISTAS 40% 20% 0% JARI1 LIGO1 CADI1 SIPS1 CACR1 HEGL1 OKEF1 COHU1 SHRO1 DOSO1 CHAS1 EVER1 SHEN1 MACA1 GRSM1 ROMA1 SAMA1 SWAN1 BRIG1 MING1 BRET1 UPBU1

  35. Likely to meet(>110%) May meet (90-110%) Likely not meet (<90%) VISTAS 2018 Base G Uniform Rate of Progress Assessment Using New IMPROVE equation to calculate visibility . . Hercules Glade, MO . . . . .

  36. QA/QC of 2009 and 2018 projections Area of Influence (AOI) analysis Identify sources within AOI BART control definitions 2018 strategy runs and projections States perform local PM2.5 and 8-hour ozone modeling VISTAS Next Steps

  37. NESCAUM, OTC, MARAMA, UMD, States mainly in-house analysis Contribution Report – look at various methods for where PM came from Back Trajectories -- Residence Time PMF Receptor Modeling REMSAD Tagged Species CMAQ Joint study with MRPO on regional diesel retrofit controls MANE-VU Modeling

  38. 2018 visibility projections across RPOs starting to converge WRAP may want to consider processing existing WRAP 2002/2018 PSAT results to look at International Transport/Natural Emissions issues at WRAP Class I areas CENRAP 2018 visibility projections consistent with WRAP Potential Effects on WRAP

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