Future scenarios of greenhouse gas emissions from electric and conventional vehicles in Australia

The results have two implications for the manufacture of EVs with life-cycle GHG emissions benefits. First, given that EVs have a use-stage benefit, automakers may still include some GHG-intensive processes and components, such as batteries, during manufacture. Second, given that the benefit declines with later models, automakers should plan to improve or replace such processes and components. Batteries offer great potential because their expected increase in energy density might decrease the GHG intensity of manufacture as well as decrease the GHG intensity of use through mass reduction.

Compared with the use-stage GHG emissions calculated in other Australian studies (Crossin & Doherty 2016; Sharma et al. 2013), the 2010 results of the present study are 17% lower for the CV and 16% lower for the EV. The differences are mainly due to the lower energy consumption of the smaller vehicles and partly due to the exclusion of maintenance materials in the present study. Australian studies report relatively high use-stage emissions for EVs due to 73% of electricity being generated in coal-fired power stations (Acil Allen Consulting 2013).

The method of the study can be applied to LCA studies that assume constant emission intensities of electricity generation. The results can directly replace the use-stage data of some LCA studies of EVs used in Australia. The method can also be applied to the modelling of the production and end-of-life stages, but the extra complication of addressing multiple material supply chains might outweigh the benefits, especially since the LCA technique is intended to simplify environmental impact estimation.

Interpretation of the results should consider the wider system beyond the scope of the study. A mandatory target can help to decrease tailpipe GHG emissions from CVs, as estimated by Reedman & Graham (2013). Dynamic LCA studies, however, suggest long delays before significant benefits emerge in the light vehicle fleet, even in the studies that assume that low-emission vehicles attain 100% of the market share within 20 years (Stasinopoulos et al., 2012b). This is one of many ways that parameter values could change over time, as explained by Laurenti et al. (2014).

The present study has limitations that could be addressed in future work. The long useful lifetime leads to uncertainty in many parameters. The GHG intensity is assumed to be unaffected by wear, but it actually increases. The GHG intensity is assumed to be constant for a CV manufactured in a particular year, but it might change as the quality of available raw material and well-to-tank GHG intensity change over time (Dale et al. 2011; Hall et al. 2014; Heun & de Wit 2012). Furthermore, the future driving intensity is uncertain. It might decrease with not only age but increasing traffic congestion, increasing urbanisation, and decreasing car ownership; but it might increase with urban expansion (Stasinopoulos et al. 2012a).

The present study quantified and compared the GHG emissions of two functionally-similar cars, a CV and an EV, used in Australia under multiple scenarios of energy supply, vehicle efficiency, driving intensity, and useful lifetime. The method was based on the time-resolved LCA technique, but analysed only the GHG emissions of driving. The results suggest that an EV will have fewer GHG emissions than a CV from driving but that the benefit declines steadily with later models. Therefore, to maintain the net life-cycle GHG emissions benefits of EVs, EV automakers may still include some GHG-intensive processes and components during manufacture, but they should plan to improve or replace such processes and components. A detailed model that accounts for further variations in influential parameters would help to increase the accuracy of the calculations.

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