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Starting climate policies early in order to reach long-term climate targets is... as cumbersome yet as neccessary ...as getting out of bed early enough to climb a mountain. following C. Schär (2003). Where do we want to go?. Malti-gas emission profiles to mitigate dangerous climate change. - PowerPoint PPT Presentation
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Starting climate policies early
in order to reach long-term climate targets is...
as cumbersome
yet as neccessary
...as getting out of bed early enough to climb a mountain
following C. Schär (2003)
Malti-gas emission profiles to mitigate dangerous climate change.
Malte Meinshausen, [email protected], 17. February 2004, RIVM Photo courtesy Leila Mead, IISD.ca;
Where do we want to go?
1. Introduction
2. Methods
3. Limitations
4. Results
Introduction
A work-in-progress report
Objective: Multi-gas emission profiles to limit global mean temperatures, radiative forcing, CO2 concentrations etc.
Possible methods for non-CO2: ‚one size fits all‘ scaling to (fossil) CO2 source-specific reduction potentials for all gases
(IMAGE) cost-optimisations (TIMER/FAIR) and ...
The ‘multi-gas meta approach’ motivation: ‘Peaking’ and ‘temperature’ related profiles Dealing ‘consistently’ with non-CO2 gases Building on pluralism of existing work to derive a
continuous set of mitigation profiles
Methods I: World per-capita emissions
Methods II: The ‚distribution of possible emission levels‘
Methods III: Going along equal percentiles
Methods IV: Overview
Limitations
1. Throwing garbage in a blender? Underestimation of non-CO2 /
landuse reduction potentials?
Limitations
1. Throwing garbage in a blender? Underestimation of non-CO2 /
landuse reduction potentials? Comparison with IMAGE EMF21
profiles shows rough consistency for non-CO2 gases – despite lack of fully elaborated scenarios in the underlying pool of scenarios.
2. Or blending everything into garbage? Not respecting anti-correlations in
scenarios? Ranking correlation analysis
Limitations II: Ranking Correlations
~0 ~0>0 >0 >0 >0 >0
Limitations
1. Throwing garbage in a blender?
2. Or blending everything into garbage? Not respecting anti-correlations in
scenarios? Ranking correlation analysis
3. Does the methodology assume a certain probability of the underlying SRES scenarios? Yes, but robust to different probabilities.
Results / ‚Found again‘
Multi-gas CO2 scenarios have substantially less overall forcing. Comparison CO2-only WRE450 and multi-gas S450C.
Results / ‚Found again‘
Multi-gas CO2 scenarios have substantially less overall forcing. Comparison CO2-only WRE450 and multi-gas S450C.
Under default assumptions, to stay below 2°C requires, atmospheric concentrations to peak below 420 ppmv CO2 or 490 ppmv CO2 equivalence
Results II: Comparison to long-term pledges
Results II: Comparison to long-term pledges
Results II: Comparison to long-term pledges
Results II: Comparison to long-term pledges
Results II: Comparison to long-term pledges
Results II: Comparison to long-term pledges
Results II: Comparison to long-term pledges
Results II: Comparison to long-term pledges
Results II: Comparison to long-term pledges
Results II: Comparison to long-term pledges
Results II: Comparison to long-term pledges
Results II: Comparison to long-term pledges
Results II: Comparison to long-term pledges
Results / ‚Found again‘
Multi-gas CO2 scenarios have substantially less overall forcing. Comparison CO2-only WRE450 and multi-gas S450C.
Under default assumptions, to stay below 2°C requires, atmospheric concentrations to peak below 420 ppmv CO2 or 490 ppmv CO2 equivalence
Long-term pledges of EU countries roughly consistent with derived emission reduction necessities for Annex I countries (Sweden/UK pledges for 2050 on the higher end, though)
Looking forward to another 3 ½ months here... Thanks!