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J. Woo, S. He, P. Amar NESCAUM E. Tagaris, K. Liao, K. Manomaiphiboon, A. G. Russell

Development of Year 2050 Anthropogenic Emissions Inventory in Support of Future Regional Air Quality Modeling. J. Woo, S. He, P. Amar NESCAUM E. Tagaris, K. Liao, K. Manomaiphiboon, A. G. Russell Georgia Institute of Technology. CMAS Conference, Oct, 2006, Chapel Hill, NC.

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J. Woo, S. He, P. Amar NESCAUM E. Tagaris, K. Liao, K. Manomaiphiboon, A. G. Russell

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  1. Development of Year 2050 Anthropogenic Emissions Inventory in Support of Future Regional Air Quality Modeling J. Woo, S. He, P. Amar NESCAUM E. Tagaris, K. Liao, K. Manomaiphiboon, A. G. Russell Georgia Institute of Technology CMAS Conference, Oct, 2006, Chapel Hill, NC

  2. Background and Objectives * A part of “Global Climate Change Impacts on Regional Air Quaility over North America” modeling work - In support of air quality modeling (GISS/MM5 and CMAQ-DDM) - Did not create new future energy/emissions scenarios * Develop 2050 EI - Target year : Year 2050, Annual - Format : SMOKE-ready - Sector : Anthropogenic only - Geographical domain : US/CAN/MEX

  3. IPCC SRES Scenarios(Global CO2 & SO2) 2050 2050 Source : IPCC

  4. Basic Strategy Future-year EI development • Obtain the best available future EI data possible • Fill-up gaps from near/certain future to distant/uncertain future Example : Use EPA projection until 2020 and use IPCC scenario from 2020-2050

  5. Comparison of existing “future-EI” development approaches • RIVM : Netherlands’s National Institute for Public Health and the Environment • IMAGE : Integrated Model to Assess the Global Environment

  6. Projecting emissions - US - • Step #1 : Obtain national projection data available for the near future - Use EPA CAIR Modeling EI (Point/Area/Nonroad, from Y2001 to Y2020) - Use RPO SIP Modeling EI (Mobile, from Y2002 to Y2018) • Step #2 : Obtain growth data for the distant future and develop cross-reference - Use IMAGE model (IPCC SRES, A1B) - From Y2020 (Y2018 for mobile activity) to Y2050 - X-Ref : Sectors/Fuels combination to SCCs • Step #3 : Apply growth factors using cross-reference

  7. Projecting emissions - CANADA/MEXICO - • Step #1 : Obtain national projection data available for the near futureor update base year inventory - Use Y2020 Environmental Canada Future EI (Area/Mobile) - Use Y2002 Point source inventory (NYS DEC) scaled with Y2000 by-state point source summary from Environment Canada - Update base year Mexico inventory using Mexico NEI for 6 US-Mexico Border states • Step #2 : Obtain simple growth data for the distant future and apply them - Use IMAGE model (IPCC SRES, A1B) - From Y2020 to Y2050 (CAN, Area/Mobile) - From Y2000 to Y2050 (CAN, Point) - From Y1999 to Y2050 (MEX, All)

  8. Developing cross-references (CAIR and IMAGE) 5159 SCCs

  9. Dots : Annual emissions in Tg/Yr Stacked-Bar : % fraction of emissions by fuels andby sectors SO2(as S) Years Countries NOx(as N) Growth (IMAGE – A1B)

  10. Pie Chart : State-level emissions fraction by source types 2001 2020 Bkgrnd Map : State-level annual emissions 2050 Spatial Distribution of US Emissions (SO2)

  11. Spatial Distribution of US Emissions (NOx) 2020 2001 2050

  12. Future Emissions (CANADA) 2050 2000

  13. Future Emissions (Mexico) 2050 1999

  14. Summary • US emissions in the future (Y2050) are estimated to decrease by 50%+ for SO2 and NOx • Canadian EI shows decrease of gaseous pollutants • For Mexico, emissions of NOx, SO2, NH3, and VOC are estimated to increase

  15. On-going work & Acknowledgement • Air quality modeling using CMAQ-DDM for three cases - Base year emissions with base year meteorology - Base year emissions with future year (2050) meteorology - future year (2050) emissions with future year (2050) meteorology • Dr. Efthimios Tagaris will present AQM effort tomorrow • This study has been financially supported by the US EPA under Grant No. R830960

  16. Near Future EI (EPA CAIR) • Base Case - Current controls except CAIR • Control Case (Clean Air Interstate Rule)* - The same as base case except for EGUs • Available for Y2001, Y2010, Y2015, Y2020 • Based on 1999 NEI • Pollutants : NOx, CO, NMVOC, SO2, NH3, PM10, PM2.5 • Available in SMOKE/IDA format * CAIR region : AL, AR, CT, DE, DC, FL,GA, IL, IN, IA, KY, LA, MD, MA, MI, MN, MS, MO, NJ, NY, NC, OH, PA, SC, TN, TX,VA, WV, WI

  17. RIVM IMAGE IMAGE : A dynamic integrated assessment modeling framework for global change WorldScan(economy model), and PHOENIX (population model) feed the basic information on economic and demographic developments for 17 world regions into three linked subsystems (EIS, TES, and AOS*) * EIS(Energy-Industry System), TES(Terrestrial Environment System), AOS (Atmospheric Ocean System)

  18. Growth (IMAGE – A1B) CO(as C) NMVOC

  19. Growth (IMAGE – A1B) Surrogates for PM species BC+EC -Streets et al. (2004) Agricultural Production Surrogates for NH3 for OTH sector

  20. Spatial Distribution of US Emissions (NMVOC) 2001 2020 2050

  21. Spatial Distribution of US Emissions (PM2.5) 2001 2020 2050

  22. Mobile source (VMT vs. Emission) Three SMOKE/M6 runs(2002/2018/2050) for MANE-VU states VMT increases (about 1%/year) for the future years (Y2050 = Y2018 yet) In spite of VMT increase, emission (CO) decrease dramatically because of controls for the future years. Much less effect of controls after 2018.

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