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Uncertainty in Emissions Projections for Climate Models

Uncertainty in Emissions Projections for Climate Models. J. Reilly, M. Mayer, M. Webster, C. Wang, M. Babiker, R. Hyman, M. Sarofim MIT Joint Program on the Science and Policy of Global Change American Geophysical Union San Francisco , 14-19 December 2000.

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Uncertainty in Emissions Projections for Climate Models

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  1. Uncertainty in Emissions Projections for Climate Models J. Reilly, M. Mayer, M. Webster, C. Wang, M. Babiker, R. Hyman, M. Sarofim MIT Joint Program on the Science and Policy of Global Change American Geophysical Union San Francisco, 14-19 December 2000

  2. Many climatically important substances (CIS’s) released from many different human activities. IPCC Special Report on Emissions Scenarios (SRES) was a high profile attempt to develop scenarios but had some important limitations: Inconsistency—different models for different gases. No quantification of uncertainty. May not have covered the full range of possibilities. Confusion of policy cases with no policy cases. Motivation

  3. Model of the world economy with all human activities and all CIS’s. GHGs: CO2, CH4, N2O, SF6, PFC, HFC Other air pollutants: NOX, SOX, CO, NMVOC, NH3 and carbonaceous particulates Activities: Energy combustion and production, agriculture and land use, industrial processes, waste disposal (sewage & landfills) EPPA: An Economic/Emissions Model

  4. EPPA: An Economic/Emissions Model

  5. Distributions for 8 key parameters: Labor Productivity Growth (1) Energy Efficiency Improvement Rate (1) GHG and Other Pollutant Emissions Factors (6) Deterministic Equivalent Modeling Method (DEMM) ~1300 model runs to fit 4th order polynomial 10,000 Monte Carlo simulations of polynomial fit to construct distributions. Construct scenarios with known probability characteristics. Simulate these scenarios through the MIT IGSM. Uncertainty Analysis Approach

  6. Probabilistic Scenario Design

  7. Global CO2 Emissions

  8. Global CH4 Emissions

  9. Global N2O Emissions

  10. Global SO2 Emissions

  11. Global NOx Emissions

  12. Global CO2 Emissions in 2100

  13. Global CH4 Emissions in 2100

  14. Global N2O Emissions in 2100

  15. Global HFC Emissions in 2100

  16. Global PFC Emissions in 2100

  17. Global SF6 Emissions in 2100

  18. CO2 Concentration

  19. Aerosol Forcing

  20. CH4 Forcing

  21. N2O Forcing

  22. CO2 Forcing

  23. Total Forcing

  24. Global Average Surface Temperature Change from 1990

  25. SRES CO2 scenarios cover much of the 95% confidence range but.. Biased somewhat toward the low end of emissions: 4 of 6 scenarios are well below 50% level in 2100 No scenario is particularly close to mean/median SRES scenarios for other GHGs are narrow. Fail to consider uncertainty in current emissions when we know current emissions levels very poorly. High bias for some, Low bias for others—evidence of inconsistency SOx in particular are all very low—all SRES scenarios optimistic about control. SRES scenarios are biased somewhat toward high temperatures MIT emissions scenarios will be available at http://web.mit.edu/globalchange Conclusions

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