Editing IPCC:AR6/WGIII/Chapter-10 (section)

=== 10.7.7 Insights from the Modelling Literature ===

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This section provides an updated, detailed assessment of future transport scenarios from IAM, GTEMs, and NTEMs given a wide range of assumptions and under a set of policy targets and conditions. The scenario modelling tools are necessary to aggregate individual options and understand how they fit into mitigation pathways from a systems perspective. The scenarios suggest that 43% (30–63% for the interquartile ranges) reductions in CO 2 emissions from transport (below modelled 2020 levels) by 2050 would be compatible with warming levels of 1.5°C (C1–C2 group). While the global scenarios suggest emissions reductions in energy supply sectors at large precede those in the demand sectors ( [[IPCC:Wg3:Chapter:Chapter-3#3.4.1|Section 3.4.1]] ), a subset of the scenarios also demonstrate that more stringent emission reductions in the transport sector are feasible. For example, the illustrative mitigation pathways IMP-REN and IMP-LD suggest emissions reductions of 80% and 90% respectively are feasible by 2050 ''en route'' to warming levels of 1.5°C with low or no overshoot by the end of the century.

The scenarios from the different models project continued growth in demand for freight and passenger services, particularly in developing countries. The potential for demand reductions is evident, but the specifics of demand-reduction measures remain less explored by the scenario literature. This limitation notwithstanding, the IAM and GTEMs suggest that interventions that reduce the energy and fuel carbon intensity of transport are likely crucial to successful mitigation strategies.

The scenario literature suggests that serious attempts at carbon mitigation in the transport sector must examine the uptake of alternative fuels. The scenarios described in the IAMs and GTEMs literature decarbonise through a combination of fuels. Across the scenarios, electrification plays a key role, complemented by biofuels and hydrogen. In general terms, electrification tends to play the key role in passenger transport while biofuels and hydrogen are more prominent in the freight segment. The three illustrative mitigation pathways described in Box 10.4 exemplify different ways these technologies may be combined and still be compatible with warming levels of 1.5°C with low or no overshoot. Shifts towards alternative fuels must occur alongside shifts towards clean technologies in other sectors, as all alternative fuels have upstream impacts. Without considering other sectors, fuel shifts would not yield their full mitigation potentials. These collective efforts are particularly important for the electrification of transport, as the transformative mitigation potential is strongly dependent on the decarbonisation of the power sector. In this regard, the scenario literature is well aligned with the LCA literature reviewed in [[#10.4|Section 10.4]] .

The models reviewed in this section would all generally be considered to have a good representation of fuels, technologies, and costs, but they often better represent land transport modes than shipping and aviation. While these models have their strengths in some areas, they have some limitations in other areas, like behavioural aspects. These models are also limited in their ability to account for unexpected technological innovation, such as a breakthrough in heavy vehicle fuels, artificial intelligence, autonomy and big data, even the extent of digital communications replacing travel ( [[#10.2|Section 10.2]] ). As a result of these limitations, the models cannot yet provide an exhaustive set of options for decarbonising the transport sectors. These limitations notwithstanding, the models can find solutions encompassing the transport sector and its interactions with other sectors that are compatible with stringent emissions mitigation efforts. The solutions space of transportation technology trajectories is therefore wider than explored by the models, so there is still a need to better understand how all options in combination may support the transformative mitigation targets.

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