Technological Advancements Within the Canadian Electric Vehicle Industry

Vice, Michael; Mikolášik, Marián

doi:10.1007/978-3-030-77916-0_18

Cited by 1 publication

(1 citation statement)

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“…The GHG reduction efficiency of this policy suggests that the provincial government should lead by example and switch over as many government vehicles as possible. In addition to being cost saving, this action can provide confidence in the technology for private consumer in which range anxiety is still a prominent barrier for slowing adoption [71].…”

Section: Discussion On Policy Implementationmentioning

confidence: 99%

Electric Mobility Emission Reduction Policies: A Multi-Objective Optimization Assessment Approach

2022

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The passenger transportation sector is notoriously sticky to decarbonize because it is interlinked with urban form, individual choice, and economic growth. As the urgency to respond to climate change increases and the transport sector disproportionally increases its contributions to global GHG emissions, there is a need for a more meaningful and transparent application of tools to cost GHG emission reduction. This study presents a multi-objective integer optimization (MIO) model to support the costing and GHG reduction estimation of electric mobility road passenger transportation policies. The model considers both cost and GHG emission minimization under resource constraints and background changes in policy interventions within interval ranges for the province of Ontario’s (Canada) in year 2030. All Pareto optimal solutions are included but results that indicate the optimal policy allocation for two discrete targets are discussed in detail; one scenario where $3 billion spending over ten years is the target and another scenario where the target is 40% GHG reduction in year 2030 (relative to 2005 levels). The MIO approach offers an out-of-the-box solution to support the GHG-reducing decision-making process at all levels of government by implementing optimal policy combinations to achieve GHG emission reductions under a target GHG emission reduction target and/or budget.

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Section: Discussion On Policy Implementationmentioning

confidence: 99%