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Climatic Change

, Volume 136, Issue 2, pp 203–216 | Cite as

How climate metrics affect global mitigation strategies and costs: a multi-model study

  • Mathijs J. H. M. HarmsenEmail author
  • Maarten van den Berg
  • Volker Krey
  • Gunnar Luderer
  • Adriana Marcucci
  • Jessica Strefler
  • Detlef P. Van Vuuren
Article

Abstract

In climate policy, substitutions metrics are used to determine exchange ratios for different greenhouse gases as part of a multi-gas strategy. The suitability of the metric depends on the policy goals and considerations regarding its practical use. Here, we present a multi-model comparison study to look at the impact of different metrics on the mitigation strategies and global climate policy costs. The study looks into different Global Warming Potentials (GWP) and the Global Temperature change Potential (GTP). The study shows that for all the models, varying between GWPs - from different IPCC reports, with different integration periods: 20 or 100 years - has a relatively small influence on policy costs (< 2.2 % spread across scenarios with a 2.8 W/m2 target) and climate outcomes. Metrics with a constant low substitution value for methane (effectively reducing its abatement), in contrast, lead to higher-cost mitigation pathways (with an average cost increase of 32.8 % in a 2.8 W/m2 scenario). If implemented efficiently, a time-varying GTP leads to a limited cost reduction compared to GWP. However, under imperfect foresight in combination with inertia of CH4 abatement options, or if implemented sub-optimally, time-varying GTP can result in higher costs than a 100-year GWP. At the same time, given a long-term radiative forcing target, a time-varying GTP results in slightly higher maximum global temperature change rates.

Keywords

Emission Reduction Methane Emission Climate Policy Global Warming Potential Marginal Abatement Cost 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The research leading to these results has received funding from the European Union’s Seventh Framework Programme FP7/2010 under grant agreement n°265139 (AMPERE) and under grant agreement n° 282846 (LIMITS)

Supplementary material

10584_2016_1603_MOESM1_ESM.docx (1.6 mb)
ESM 1 (DOCX 1.58 mb)

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Mathijs J. H. M. Harmsen
    • 1
    • 2
    Email author
  • Maarten van den Berg
    • 2
  • Volker Krey
    • 3
  • Gunnar Luderer
    • 4
  • Adriana Marcucci
    • 5
  • Jessica Strefler
    • 4
  • Detlef P. Van Vuuren
    • 1
    • 2
  1. 1.Copernicus Institute of Sustainable DevelopmentUtrecht UniversityUtrechtThe Netherlands
  2. 2.PBL Netherlands Environmental Assessment AgencyBilthovenThe Netherlands
  3. 3.International Institute for Applied Systems Analysis (IIASA)ViennaAustria
  4. 4.Potsdam Institute for Climate Impact Research (PIK)PotsdamGermany
  5. 5.Center of Economic ResearchETHZurichSwitzerland

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