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Modeling uncertainty in estimation of carbon dioxide abatement costs of energy-saving technologies for passenger cars in China

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  • Peng, Bin-Bin
  • Xu, Jin-Hua
  • Fan, Ying
Abstract
Estimation of carbon dioxide abatement cost is of the essence to promote energy-saving technologies (ESTs) in the passenger car sector, while the existence of various uncertainties of abatement cost may be major barriers for technology promotion. This study establishes the projected marginal abatement cost (MAC) curve of China's passenger car sector over the 2016–2030 period and conducts uncertainty modeling through Monte Carlo simulation. The impacts of uncertainties from oil price, electricity cost, energy-saving potential, incremental investment cost, and emission factor for electricity consumption on emission abatement costs of ESTs are analyzed separately and compared together. Results show that among the five uncertainties, oil price uncertainty has the largest impact on ESTs’ emission abatement cost, but the impact does not differ significantly among different technology bundles. Uncertainties in electricity cost and in electricity emission factor affect significantly the MACs of new-energy paths. Compared with the above two uncertainties, uncertainties in energy-saving potential and in incremental investment cost have larger impacts on the MACs of traditional energy-saving paths. Among different vehicle types, the MACs of ESTs on small-displacement private cars are the least affected by various uncertainties.

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  • Peng, Bin-Bin & Xu, Jin-Hua & Fan, Ying, 2018. "Modeling uncertainty in estimation of carbon dioxide abatement costs of energy-saving technologies for passenger cars in China," Energy Policy, Elsevier, vol. 113(C), pages 306-319.
    • Handle: RePEc:eee:enepol:v:113:y:2018:i:c:p:306-319
    DOI: 10.1016/j.enpol.2017.11.010
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