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- W4200537172 abstract "Although numerous studies investigate the impacts of policy on zero-emissions vehicle (ZEV) sales, few address the impacts of a ZEV sales mandate and its particular design features. We use the AUtomaker-consumer Model (AUM) to simulate varying designs of a ZEV mandate in Canada's light-duty vehicle sector, requiring 30% ZEV sales by 2030. Design features include: different penalties for non-compliance, different allocations of credits per ZEV type, and the allowance of banking credits across years. For each policy design, we consider impacts on ZEV adoption, GHG emissions, consumer surplus, automaker profits, and overall policy cost-effectiveness. Results demonstrate trade-offs among the policy designs. Generally, ZEV mandate designs that are more effective at increasing ZEV adoption and decreasing GHG emissions also induce larger reductions in consumer surplus and automaker profits. To achieve the ZEV sales goal, simulations show that a higher non-compliance penalty (CDN$ 10k per credit) is needed. ZEV adoption and GHG reductions are also improved by a “One credit per ZEV” scheme, rather than a “California-style” scheme that gives multiple credits per battery-electric vehicle. Further, allowing automakers to bank credits softens the policy impact on profit and increases automaker compliance in initial years. Across these different design combinations, we find that the most cost-effective design ($CDN/tonne mitigated, including consumer surplus and automaker profits impacts) utilizes a $10k non-compliance penalty and “One credit per ZEV” system that allows banking. Our analysis demonstrates the importance of various ZEV mandate design features, and the complex trade-offs involved among various policy goals." @default.
- W4200537172 created "2021-12-31" @default.
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- W4200537172 date "2022-03-01" @default.
- W4200537172 modified "2023-09-27" @default.
- W4200537172 title "How to design a zero-emissions vehicle mandate? Simulating impacts on sales, GHG emissions and cost-effectiveness using the AUtomaker-Consumer Model (AUM)" @default.
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- W4200537172 doi "https://doi.org/10.1016/j.tranpol.2021.12.012" @default.
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