Uncertainty in Emissions Projections for Climate Models

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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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Motivation

• Many climatically important substances (CISs)
  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
• Inconsistencydifferent 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.

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EPPA An Economic/Emissions Model

• Model of the world economy with all human
  activities and all CISs.
• 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)

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EPPA An Economic/Emissions Model
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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.

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Probabilistic Scenario Design
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Global CO2 Emissions
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Global CH4 Emissions
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Global N2O Emissions
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Global SO2 Emissions
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Global NOx Emissions
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Global CO2 Emissions in 2100
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Global CH4 Emissions in 2100
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Global N2O Emissions in 2100
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Global HFC Emissions in 2100
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Global PFC Emissions in 2100
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Global SF6 Emissions in 2100
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CO2 Concentration
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Aerosol Forcing
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CH4 Forcing
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N2O Forcing
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CO2 Forcing
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Total Forcing
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Global Average Surface Temperature Change from
1990
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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 othersevidence
  of inconsistency
• SOx in particular are all very lowall 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