Forecasting greenhouse gas emissions performance of the future Australian light vehicle traffic fleet

Ivan Iankov, Michael A.P. Taylor and Derek Scrafton

Transportation Research Part A: Policy and Practice, 2017, vol. 99, issue C, 125-146

Abstract: Knowledge of real-world greenhouse gas emission rates for traffic is necessary for forecasting transport greenhouse gas emissions. This paper presents greenhouse gas emission rates that assist forecasting and modelling greenhouse gas emissions from light vehicles, i.e. private passenger vehicles and light commercial vehicles under realistic traffic conditions. It develops confidence intervals for market shares by categories for fuel or energy efficiency on the Australian market for new light vehicles for the period 2016–2030. The model estimates realistic market scenarios by simulating likely variations of capital and running costs of alternatives for car buyers and by considering buyers’ willingness-to-pay for fuel/energy efficiency. The results suggest that market forces will be insufficient to promote battery electric vehicles and plug-in hybrid electric vehicles in Australia. On average the widths of the 95% confidence intervals for greenhouse emission rates are about 10–15% of the magnitudes of the emission rates, so that analysts can forecast transport greenhouse gas emissions with a reasonable level of certainty. The study suggests that policy interventions to accelerate the uptake of low or zero emitting vehicles may be required.

Keywords: Tank-to-wheel greenhouse gas emission rate; Light vehicle traffic load; Vehicle size; Vehicle year of manufacture; Additional manufacturing cost; Vehicle running cost; Market shares; Willingness-to-pay (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.tra.2017.03.011

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