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Title: The role of technical improvements in decarbonising passenger transport
Author: Craglia, Matteo Alexander McConnochie
ISNI:       0000 0004 9353 8693
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2020
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Passenger vehicles are a leading driver of anthropogenic greenhouse gas (GHG) emissions. The majority of efforts to reduce vehicle GHG emissions focus on technical improvements, due to difficulties in reducing travel demand and shifting to alternative modes of travel. However, the rate at which technical improvements can be deployed is highly uncertain. Furthermore, the benefits of technical efficiency improvements may be offset by consumer trends towards larger and more powerful vehicles, filled with a greater number of accessories. Similarly, efficiency improvements can lower running costs, which may stimulate drivers to travel more. These consumer trends create further uncertainty about the impact of technical improvements. The aim of this thesis is to estimate the extent to which future technical improvements might be offset by consumer trends, and the risks they pose to reducing CO2 emissions. Firstly, technical efficiency improvements in vehicles over the past two decades are quantified, using driver-reported data for the first time. This is important as vehicle fuel consumption reported by drivers on the road is found to be ≈35% higher than official tested values in 2017-18. The analysis shows that technical improvements had the potential to reduce fuel consumption by 1.8 L/100km between 2001 and 2018. However, two thirds of this potential was offset by the increasing size and power of vehicles. Finally, the introduction of new EU vehicle efficiency regulations in 2008/09 is found to have had little effect at stimulating the rate of real technical efficiency improvements in British vehicles. If efficiency improvements stimulate drivers to travel more, due to lower running costs, potential emissions reductions from technical improvements may be further offset. Past estimates of the magnitude of this effect, known as the Rebound Effect, have varied widely, partly due to data constraints and a reliance upon highly aggregated government statistics. The analysis of this thesis instead uses a novel dataset of over 275 million vehicle road-worthiness tests. Results show that the Rebound Effect in Great Britain is small, with magnitude 4.6%, meaning efficiency improvements are unlikely to greatly stimulate increased mileage. Having quantified the extent to which technical efficiency improvements in vehicles have been offset by consumer trends in the recent past, the analysis then explores their future role. A range of technology and policy actions can be put in place to reduce carbon emissions, this thesis aims to prioritise between them, based upon their likely impact and uncertainty. Formal sensitivity analysis techniques are used for the first time to determine the relative importance of factors affecting future emissions from passenger vehicles. The findings show that over 80% of the uncertainty in future cumulative CO2 emissions can be attributed to uncertainty in electric vehicle uptake and vehicle size and power. These variables are therefore of primary importance for transport policy makers. The analysis also highlights variables of comparatively low importance; these include the carbon intensity of the electricity grid, the share of hybrid electric vehicles, the magnitude of the Rebound Effect and the rate of incremental improvements within powertrain technologies. The core contribution of this thesis is to compare efforts to improve the technical efficiency of vehicles, with the impacts of consumer trends and factors affecting future transport emissions. The majority of potential emissions savings from engineering improvements in the past two decades have been lost, strong policy action is required to avoid this trend continuing in future.
Supervisor: Cullen, Jonathan M. Sponsor: EPSRC
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
Keywords: Transport ; CO2 emissions ; sensitivity analysis ; decomposition analysis ; rebound effect ; energy efficiency ; fuel consumption