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

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.

[1]  Chris Manzie,et al.  Conventional, hybrid and electric vehicles for Australian driving conditions – Part 1: Technical and financial analysis , 2012 .

[2]  Mark J. Koetse,et al.  A choice experiment on alternative fuel vehicle preferences of private car owners in the Netherlands , 2014 .

[3]  Yu Zhou,et al.  Real-world fuel consumption and CO2 (carbon dioxide) emissions by driving conditions for light-duty passenger vehicles in China , 2014 .

[4]  J King,et al.  The King Review of low-carbon cars: part I: the potential for CO2 reduction , 2007 .

[5]  Ye Wu,et al.  Modeling real-world fuel consumption and carbon dioxide emissions with high resolution for light-duty passenger vehicles in a traffic populated city , 2016 .

[6]  André Faaij,et al.  Energy use, cost and CO 2 emissions of electric cars , 2011 .

[7]  Michael G. McNally,et al.  The Four Step Model , 2007 .

[8]  N. H. Ravindranath,et al.  2006 IPCC Guidelines for National Greenhouse Gas Inventories , 2006 .

[9]  A. Rousseau,et al.  Light-Duty Vehicle Fuel Consumption Displacement Potential up to 2045 , 2016 .

[10]  David L. Greene,et al.  Uncertainty, loss aversion, and markets for energy efficiency , 2011 .

[11]  Meryl P. Gardner,et al.  Willingness to pay for electric vehicles and their attributes , 2011 .

[12]  Sujit Das,et al.  Status of advanced light-duty transportation technologies in the US , 2012 .

[13]  Hui Xiong,et al.  Access to Destinations: Travel Time Estimation on Arterials , 2007 .

[14]  H Minken,et al.  A SUSTAINABILITY OBJECTIVE FUNCTION FOR LOCAL TRANSPORT POLICY EVALUATION , 1999 .

[15]  André Faaij,et al.  Performance of batteries for electric vehicles on short and longer term , 2012 .

[16]  Yizao Liu,et al.  Household demand and willingness to pay for hybrid vehicles , 2014 .

[17]  Aaron Hula,et al.  Light-Duty Automotive Technology, Carbon Dioxide Emissions, and Fuel Economy Trends: 1975 Through 2015 , 2015 .

[18]  Geoffrey P. Hammond,et al.  Indicative energy technology assessment of advanced rechargeable batteries , 2015 .

[19]  Leonidas Ntziachristos,et al.  COPERT Australia: a new software to estimate vehicle emissions in Australia , 2013 .

[20]  John M. Rose,et al.  Environmental attitudes and emissions charging: An example of policy implications for vehicle choice , 2013 .

[21]  D. Greene,et al.  Survey evidence on the willingness of U.S. consumers to pay for automotive fuel economy , 2013 .

[22]  Florian Zettelmeyer,et al.  Are Consumers Myopic? Evidence from New and Used Car Purchases , 2013 .

[23]  Aie.  World Energy Outlook 2015 , 2015 .

[24]  Charalampos Saridakis,et al.  An empirical investigation of the impact of behavioural and psychographic consumer characteristics on car preferences: An integrated model of car type choice , 2013 .

[25]  T. Tran,et al.  Lithium Production Processes , 2015 .

[26]  David Gargett.  Traffic growth: modelling a global phenomenon , 2012 .

[27]  K. Kurani,et al.  Car buyers and fuel economy , 2007 .

[28]  J. Dargay,et al.  Vehicle Ownership and Income Growth, Worldwide: 1960-2030 , 2007 .

[29]  Christian A. Klöckner,et al.  Influences of car type class and carbon dioxide emission levels on purchases of new cars: A retrospective analysis of car purchases in Norway , 2013 .

[30]  Youngguk Seo,et al.  Estimation of greenhouse gas emissions from road traffic: A case study in Korea , 2013 .

[31]  J. Eom,et al.  Trends in passenger transport energy use in South Korea , 2010 .

[32]  A. McKinnon,et al.  Forecasting the carbon footprint of road freight transport in 2020 , 2010 .