Abstract
Transport generates a large and growing component of global greenhouse gas emissions contributing to climate change. Effective transport emissions reduction policies are needed in order to reach a climate target well below 2 ∘C. Representations of technology evolution in current integrated assessment models (IAM) make use of systems optimisations that may not always provide sufficient insight on consumer response to realistic policy packages for extensive use in policy-making. Here, we introduce FTT: transport, an evolutionary technology diffusion simulation model for road transport technology, as an IAM sub-component, which features sufficiently realistic features of consumers and of existing technological trajectories that enables to simulate the impact of detailed climate policies in private passenger road transport. Integrated to the simulation-based macroeconometric IAM E3ME-FTT, a plausible scenario of transport decarbonisation is given, defined by a detailed transport policy package, that reaches sufficient emissions reductions to achieve the 2 ∘C target of the Paris Agreement.
Highlights
Road transport emits 17% of global greenhouse gas (GHG) emissions, a flow of carbon that has grown historically by 2–3% every year over the past 20 years (IEA 2015a)
The optimisation methodology used in integrated assessment models (IAM) is useful from a normative perspective as it helps map out feasible space and determine what are desirable configurations from a societal point of view
Many IAMs are employed using typically one single policy lever for decarbonisation: the carbon price, which is applied to all emitting sectors including road transport
Summary
Road transport emits 17% of global greenhouse gas (GHG) emissions, a flow of carbon that has grown historically by 2–3% every year over the past 20 years (IEA 2015a). IAMs with high detail in energy end-use technologies have been based on system cost-optimisation or maximisation of the utility of the representative agent.. Optimisations interpreted as positive descriptions may not be reliable for use for impact assessments of policy scenarios, if the modelled behaviour of agents is not sufficiently well informed. There are two major issues with current optimisation-based IAMs (Wilson et al 2015; McCollum et al 2016; Pettifor et al 2017b; Mercure et al 2016): Many IAMs are employed using typically one single policy lever for decarbonisation: the carbon price (through assumed emissions trading), which is applied to all emitting sectors including road transport. FTT models the diffusion of innovations calibrated on recent diffusion data and observed cost-distributions as a representation of consumer heterogeneity It offers a highly detailed set of possible policy packages.
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