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

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.

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)

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

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.

Probabilistic Scenario Design

Global CO2 Emissions

Global CH4 Emissions

Global N2O Emissions

Global SO2 Emissions

Global NOx Emissions

Global CO2 Emissions in 2100

Global CH4 Emissions in 2100

Global N2O Emissions in 2100

Global HFC Emissions in 2100

Global PFC Emissions in 2100

Global SF6 Emissions in 2100

CO2 Concentration

Aerosol Forcing

CH4 Forcing

N2O Forcing

CO2 Forcing

Total Forcing

Global Average Surface Temperature Change from 1990

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 http://web.mit.edu/globalchange