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Climatic Change

, Volume 118, Issue 3–4, pp 595–608 | Cite as

Climate impact of transportation A model comparison

  • Bastien GirodEmail author
  • Detlef P. van Vuuren
  • Maria Grahn
  • Alban Kitous
  • Son H Kim
  • Page Kyle
Article

Abstract

Transportation contributes to a significant and rising share of global energy use and GHG emissions. Therefore modeling future travel demand, its fuel use, and resulting CO2 emission is highly relevant for climate change mitigation. In this study we compare the baseline projections for global service demand (passenger-kilometers, ton-kilometers), fuel use, and CO2 emissions of five different global transport models using harmonized input assumptions on income and population. For four models we also evaluate the impact of a carbon tax. All models project a steep increase in service demand over the century. Technology change is important for limiting energy consumption and CO2 emissions, the study also shows that in order to stabilise or even decrease emissions radical changes would be required. While all models project liquid fossil fuels dominating up to 2050, they differ regarding the use of alternative fuels (natural gas, hydrogen, biofuels, and electricity), because of different fuel price projections. The carbon tax of 200 USD/tCO2 in 2050 stabilizes or reverses global emission growth in all models. Besides common findings many differences in the model assumptions and projections indicate room for further understanding long-term trends and uncertainty in future transport systems.

Keywords

Emission Factor Energy Intensity Fuel Price Travel Demand Carbon Intensity 
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

Acknowledgements

Bastien Girod’s contribution to this article has been funded by the Swiss National Science Foundation. We acknowledge Lew Fulton and the IEA ETP Transport Unit for running the IEA Transport model (MoMo) with the harmonized population and income projections and providing resulting output data.

Supplementary material

10584_2012_663_MOESM1_ESM.pdf (287 kb)
ESM 1 (DOCX 286 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Bastien Girod
    • 1
    • 2
    Email author
  • Detlef P. van Vuuren
    • 2
    • 3
  • Maria Grahn
    • 4
  • Alban Kitous
    • 5
  • Son H Kim
    • 6
  • Page Kyle
    • 6
  1. 1.Swiss Federal Institute of Technology Zurich (ETH Zurich), Department of Management, Technology, and Economics, Chair of Sustainability and TechnologyZurichSwitzerland
  2. 2.Department of GeosciencesUtrecht UniversityUtrechtThe Netherlands
  3. 3.PBL-Netherlands Environment Assessment AgencyBilthovenThe Netherlands
  4. 4.Department of Energy and Environment, Physical Resource TheoryChalmers University of TechnologyGoeteborgSweden
  5. 5.European Commission, JRC-IPTSSevilleSpain
  6. 6.Joint Global Change Research Institute, Pacific Northwest National Laboratory5825 University Research CtCollege ParkUSA

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