Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Energy Policyarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Energy Policy
Article . 2017 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
versions View all 1 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

No free ride to zero-emissions: Simulating a region's need to implement its own zero-emissions vehicle (ZEV) mandate to achieve 2050 GHG targets

Authors: Maxwell Sykes; Jonn Axsen;

No free ride to zero-emissions: Simulating a region's need to implement its own zero-emissions vehicle (ZEV) mandate to achieve 2050 GHG targets

Abstract

Abstract The adoption of zero emission vehicles (ZEVs) is limited by a variety of barriers. Some are region-specific (e.g. availability of charging infrastructure) while others are global in nature (e.g. battery prices) where improvements spill over between regions. This study explores regional spillover effects and GHG impacts of strong ZEV-focused policy, specifically the ZEV mandate in place in ten U.S. states (“ZEV States”) which requires automakers to sell a minimum amount of ZEVs each year. We use a dynamic technology adoption model to simulate passenger vehicle sectors in North America, focusing on the case of one small region (British Columbia, covering 0.7% of the market) as potentially free-riding off of ZEV States’ policy (covering 23% of the market). Results indicate that free-ridership is not effective; even with the ZEV mandate driving very high sales in ZEV States, British Columbia cannot achieve significant ZEV adoption without also implementing its own ZEV mandate. Further, for British Columbia to meet its 2050 GHG targets, it may need a ZEV mandate in addition to complementary climate policies—pushing ZEVs to account for 40–93% of new vehicle sales in 2050. In short, regions seeking low-carbon transportation likely need to implement their own stringent policies.

Related Organizations
  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    75
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
75
Top 1%
Top 10%
Top 10%