The strategy categories in the tables encompass consideration of various specific strategies to reduce material demand. These include the following:

optimising buildings design to reduce material needs

switching to composite frame buildings

reducing over-engineering/overestimation

optimising the structure

post-tensioning

using fabric formwork

choosing lateral load-resisting systems

using hollow-core concrete

optimising steel fibres in concrete

using cold-formed/light-gauge steel framing

using correct exposure class for concrete

employing additive manufacturing

enhancing material properties

improving concrete packing, including by using admixtures

using high-strength cement

using high-strength steel

promoting best construction practices

reducing waste

improving value chain management

prefabricating/precasting

extending buildings lifetimes

in-depth retrofitting

repositioning

repurposing

handling end of life of buildings elements

reuse

recycling.

Vehicles value chain assumptions and modelling methodology

Estimates of the material intensity were incorporated into the IEA Mobility Model (MoMo), a transport energy database and simulation model with full stock accounting. The reassessment of historical material trends in passenger light-duty vehicles (PLDVs) drew upon recent updates of the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Transportation) modelling tool (Argonne National Laboratory, 2017)32 and validation against detailed material composition tracking of light-duty vehicles sold in the United States (Dai, Kelly and Elgowainy, 2016). Due to data limitations, material composition trends for other global regions were assumed to be the same as in the United States. However, sales-weighted average kerb weights

32 GREET material composition by vehicle part is decreased in resolution in the MoMo to the basic vehicle systems level (i.e. body, powertrain and battery).

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and powertrain shares differed based on the resolution available in the IEA historical vehicle database.

Historical estimates of the material composition of light commercial vehicles (LCVs) and heavyduty vehicles (HDVs) (medium and heavy-freight trucks, buses and minibuses) were estimated based on underlying data provided from a study for the Directorate-General Clima of the European Commission by Ricardo-AEA (Hill et al., 2015).

Keeping forward-looking transport carbon dioxide (CO2) emissions consistent with the RTS would require that vehicle efficiency improvements occur over a sustained time period in vehicle design. Rates of vehicle efficiency progress in light-duty sales would need to match the ambition of historical best performance, even in countries where initial standards are being formulated or follow-up standards will soon be drafted. The global trend of increasing vehicle size (Global Fuel Economy Initiative, n.d.) would have to stop in the coming one to two decades, as well as the trend of compensating savings from lightweighting by adding more safety, performance and other amenities. Heavy-duty vehicle efficiency standards should be designed to promote/capture the impact of lightweighting (so that these are incentivised alongside other improvements to operational efficiency); testing regimes like those used by the People’s Republic of China (“China”) that simulate vehicles at maximum load provide no such incentive.

The policy stringency required in the CTS scenario is even greater. The success of emissions reduction targets in this scenario is predicated not only on fuel economy standards and vehicle purchase and usage pricing, but also by policies across the energy system, notably in electricity generation. The CTS incorporates a rapid shift to electric powertrains across all road vehicle categories, at rates intermediate between those detailed in the 2018 Global Electric Vehicle Outlook EV30@30 scenario and this publication’s RTS (IEA, 2018).

Lightweighting was assumed to be a key strategy to achieve fuel efficiency improvements in the scenarios. Lightweighting assumptions were informed by a combination of: studies conducted by the National Highway Traffic Safety Administration and by the Environmental Protection Agency to inform the US 2017-25 fuel economy standards (EPA, 2012; Singh, 2012); literature assessments of the technical and economic potential for lightweighting (Dai, Kelly and Elgowainy, 2016; Ducker Worldwide, 2017; Kelly et al., 2015; Kelly et al., 2014; Luk et al., 2017; Modaresi et al., 2014); and consultation with experts. Following expert review of initial assumptions on the potential for maximum lightweighting in each scenario by 2030 and 2060, final assumptions were made for the maximum kerb weight reductions possible in the salesweighted average new sales of conventional internal combustion engine (ICE) PLDVs. These “benchmark weight reductions” were assigned to the region with the highest ambition. For LCVs and HDVs, benchmark weight reductions for the RTS were set based on the lightweighting assumptions in Hill et al. (2015), which is broadly in line with the RTS scenario definition. Given the lack of studies outlining lightweighting potential in LCVs and HDVs under more ambitious policy conditions, the CTS and MEF benchmark weight reductions were set proportional to the incremental weight reduction potential relative to the RTS in PLDVs. The resulting total maximum assumed weight reductions for each vehicle category for ICEs are shown in Table 10.

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Material efficiency in clean energy transitions General annexes

Notes: PLDVs are split in the IEA MoMo into passenger cars and light trucks based on country-specific data availability. Kerb weights of heavy vans (Isenstadt et al., 2016) were scaled at the ratio of 3.5/5 based on the ratio of maximum gross vehicle weight to estimate material composition of LCVs.

Sources: * Argonne National Laboratory (2017b), GREET; + Hill, N. et al. (2015), Light weighting as a means of improving Heavy-duty Vehicles’ energy efficiency and overall CO2 emissions, https://ec.europa.eu/clima/sites/clima/files/transport/vehicles/heavy/docs/hdv_lightweighting_en.pdf.

For vehicles with electric motors and batteries (hybrid electric vehicles, plug-in hybrid electric vehicles and battery-electric vehicles [BEVs]), the body and powertrains were assumed to be lightweighted more aggressively than in ICEs, given that lightweighting can allow for reduced batteries sizes or increased range with the same battery size. The financial incentive for more lightweighting was assumed to be stronger earlier on, and then to decline over time as battery costs fall. Thus, the analysis assumed that the combined weight reduction in the electric vehicle (EV) body and powertrain (not including the battery) is 20-25% greater than the ICE weight reduction in 2030 (depending on the scenario) and 10% greater in 2060. Battery weight was assumed to remain relatively constant over time. While battery developments after 2030 are highly uncertain, this analysis assumed that in the 2030-40 time frame, a shift from nickel- manganese-cobalt to lithium-sulphur or lithium-air chemistries will be successfully translated from the laboratory to commercial automotive applications. This will enable considerable improvements in battery density. However, the density improvements were assumed to be offset by increases in capacity, as consumers continue to value greater range, thus resulting in a relatively constant battery weight over time. In the CTS and MEF, lightweighting beyond the RTS enables a reduction in battery capacity while achieving the same range, resulting in somewhat lighter batteries.

In the MEF, all regions pursue equally ambitious material efficiency strategies and thus all achieve the maximum weight reduction. In the RTS and CTS, the benchmark region was set as the region with the strongest fuel economy and lightweighting regulations in that scenario. For PLDVs, the benchmark region was China. For LCVs and HDVs, the benchmark region was North America, where heavy-duty fuel economy regulations and testing procedures explicitly incentive lightweighting as a strategy for vehicle efficiency improvements. Weight reductions in other regions were set based on the relative ambition of their fuel economy and lightweighting regulations. To illustrate, Table 11 shows the weight reductions by region in the RTS and CTS for PLDVs.

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Material efficiency in clean energy transitions General annexes

Notes: The figures show the percentage reduction in vehicle kerb weight of new vehicle sales relative to 2015. They apply to conventional ICE PLDVs. OECD = Organisation for Economic Co-operation and Development.

Weight reductions were assumed to be achieved through a combination of part downsizing and optimisation, material substitution, and secondary weight reduction. The mass composition assumptions for the benchmark ICE passenger car were chosen based on the range of mass compositions found in the literature and to achieve the targeted weight reduction. The mass compositions for other vehicle types were set to achieve approximately the same proportion of weight reduction from each lightweighting strategy, while taking into account differences in the original mass composition of the vehicle.

Figure 60. Estimates of the MSR in vehicles

Notes: Range of MSRs of different lightweight materials reported by the US Department of Energy (EERE, 2013) and error bars representing theoretical limits as calculated by Kelly et al. (2015), as presented in Luk, J. et al. (2017). Due to data limitations, the IEA assumed a single value for high-strength steel and advanced high-strength steel. Due to uncertainty on the potential for plastics and composites, the IEA similarly assumed a single value across these options (which are introduced into vehicles from 2030 onwards in all scenarios). MSRs adopted in this study were: steel to high-strength and advanced high-strength steel: 0.80; steel to aluminium: 0.55; and steel to plastics and composites: 0.40.

Sources: Adapted with permission from Luk, J. et al., (2017), “Review of fuel saving, life cycle GHG emission, and ownership cost impacts of lightweighting vehicles with different powertrains’’, http://doi.org/10.1021/acs.est.7b00909. Copyright 2017 American Chemical Society. Estimates of the MSR of plastics and composites are from Kelly et al. (2015), "Impacts of vehicle weight reduction via material substitution on life-cycle greenhouse gas emissions", https://doi.org/10.1021/acs.est.5b03192.

There is considerable variability in MSR estimates found in literature.

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