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Estimating electric car’s emissions in Germany: an analysis through a pivotal marginal method and comparison with other methods


  • Jérome Massiani
  • Jens Weinmann


In this paper, we estimate the emissions resulting from electric vehicles in Germany. We make use of EMOB, a comprehensive simulation model that provides a forecast and evaluation of the diffusion of alternative fuel vehicles in the next decades. Our method to compute emissions differs from existing ones by a "pivotal marginal" or "hourly marginal" calculation that takes into account the predicted time pattern of EV reloading and can offer a parsimonious alternative to resource intensive micro simulation models. Our approach results in EV emissions of 87 g/km in 2012 and 82 g/km in 2020. These estimates are much higher than those provided by simplified approaches (marginal and average emission) in the short run and get close to marginal emissions after 2035. Co-ordinated charging may reduce the emissions only marginally (usually less than 4 %). Generally, our findings cast doubts on the general claim that electric cars could be fuelled by renewable energy in general, and with fluctuating excess supply of renewables (wind, solar) in particular. This conclusion persists even in the presence of realistic coordination schemes.

Suggested Citation

  • Jérome Massiani & Jens Weinmann, 2012. "Estimating electric car’s emissions in Germany: an analysis through a pivotal marginal method and comparison with other methods," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2012(2), pages 131-155.
  • Handle: RePEc:fan:efeefe:v:html10.3280/efe2012-002007

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    Cited by:

    1. Rusich, Andrea & Danielis, Romeo, 2015. "Total cost of ownership, social lifecycle cost and energy consumption of various automotive technologies in Italy," Research in Transportation Economics, Elsevier, vol. 50(C), pages 3-16.
    2. Massiani, Jérôme, 2015. "Cost-Benefit Analysis of policies for the development of electric vehicles in Germany: Methods and results," Transport Policy, Elsevier, vol. 38(C), pages 19-26.
    3. Hirte, Georg & Tscharaktschiew, Stefan, 2013. "The optimal subsidy on electric vehicles in German metropolitan areas: A spatial general equilibrium analysis," Energy Economics, Elsevier, vol. 40(C), pages 515-528.

    More about this item

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning


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