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Building Emission Inventory for Regional Air Quality Modeling in China

Building Emission Inventory for Regional Air Quality Modeling in China. K. He 1 , Q. Zhang 1 , L. Wang 1 , D. Streets 2 , J. Fu 3 , J.Woo 4. 1 Tsinghua University, Beijing, China 2 Argonne National Laboratory, Chicago, USA 3 Uinversity of Tennessee, Knoxville, USA

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Building Emission Inventory for Regional Air Quality Modeling in China

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  1. Building Emission Inventory for Regional Air Quality Modeling in China K. He1, Q. Zhang1, L. Wang1, D. Streets2, J. Fu3, J.Woo4 1Tsinghua University, Beijing, China 2Argonne National Laboratory, Chicago, USA 3Uinversity of Tennessee, Knoxville, USA 4Northeast States for Coordinated Air Use Management, Boston, USA 2nd ICAP Workshop, Friday Center of Chapel Hill, Oct. 21-22, 2004

  2. Occurrence Frequency of Each Pollutant as Major Pollutant of 42 Key Cities in China 2001-2004.5

  3. Air Pollution Index (API) of SO2 in Beijing: 2000-2002

  4. Air Pollution Index (API) of NO2 in Beijing: 2000-2002

  5. Air Pollution Index (API) of O3 in Beijing: 2000-2002

  6. PM2.5 sampling locations Miyun (MY) Changping (CHP) Tsinghua (THU) Chegongzhuang (ZGC) Tian’anmen Square (TAM)

  7. Weekly Average Concentration of PM2.5 in Beijing: 1999-2003

  8. Two Types of Emission Inventories • Local Inventory • Bottom-up, device based emissions • Exact emission locations • Less uncertainties, but • Only available in limited areas • Regional Inventory • Top-down, sector based emissions • Gridding by allocation factors • More uncertainties, but • Available for large areas

  9. Building Inventory for Regional Air Quality Modeling • Similar methodology with Trace-P inventory • Top-down method, but technical based emissions • More technical splits with sectors • Embed local inventory to regional inventory

  10. Approaches to Activity Data • Statistical yearbook & database • Activity data at sector level: energy balance table, industrial productions, vehicle populations, etc • Technical reports and papers • Technical split within sectors • Energy demand model • Energy consumptions by fuel, by device type

  11. Technical Split for Coal Combustion Devices Good Efficiency Moderate Efficiency Poor Efficiency Lime

  12. Energy Demand Model for Domestic Sector

  13. Share of Energy Use by Device Type in Domestic Sector, Beijing Automatic Boiler HandStoker, Medium Hand Stoker, Small Stove • Well developed distributed heating • Change small coal boilers to natural gas • Decrease of coal use in rural areas

  14. Methodology for Transportation Sector

  15. Approaches to Emission Factors • Chemical balance • Raw gas factors (SO2, Primary PM, Hg) • Technical reports and papers • Fuel characteristics, Operating practice, Control equipments • Field measurement • Final emission factors, Removal efficiency • International EF database • When lack of local measurement data (BC/OC, VOC)

  16. Updated CO Emission Inventory for China 40% higher than Trace-P

  17. Embed Local Inventory to National Inventory

  18. PM10 PM2.5 SO2 NOx CO VOC Difference of Two Inventories: Total Emissions *: CO emission unit: 10t/y Local/Trace-P in Beijing Urban Areas: 3.1 3.9 0.8 1.5 1.6 1.9

  19. Power Plants Power Plants Difference of Two Inventories: Grid Emissions Local Trace-P SO2 Emissions, 4km grid

  20. Beijing Regional Modeling: O3 TRACE-P EMs Trace-P+Beijing EMs (July 4-20, 2001, episode max.) Source: Fu, et.al. 2004

  21. Progress and Future Work • CO • Primary PM: TSP, PM10, PM2.5 • BC/OC • VOC • Field measurement for PM2.5/BC/OC emission factors

  22. Acknowledgment • USEPA and SEPAIES Project • GM and NSFC • Dr. Carey Jiang • Tsinghua University

  23. Thanks!

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