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, December 2000

2. Motivation
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.

3. EPPA: An Economic/Emissions Model
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)

4. EPPA: An Economic/Emissions Model
CH4
N2O
HFC,
PFC, SF6
NOx, SOx, CO, VOC, NH3, PM
Fossil Fuel Combustion X
Energy Production
Agriculture and Land Use
Industrial Processes
Sewage and Landfills

5. Uncertainty Analysis Approach
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.

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. Conclusions
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