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Energy scenarios project future possibilities based on a variety of assumptions, yet do not fully account for inherent friction in the energy transition, particularly over the near term. A new study shows how machine learning can complement existing scenario tools by incorporating lessons from the past into projections for the future.

In the version of ‘Supplementary Data 1’ originally published with this Article, the units for the ‘Capacity|Electricity|*’ variables in the ‘Non_Investment_Annual’ tab were incorrectly given as EJ/yr; they should have read GW. This has now been corrected. Also, some of the variables listed in the ‘Non_Investment_Variable_Defs’ were not required and have therefore been removed.

Low-carbon investments are necessary for driving the energy system transformation that is called for by both the Paris Agreement and Sustainable Development Goals. Improving understanding of the scale and nature of these investments under diverging technology and policy futures is therefore of great importance to decision makers. Here, using six global modelling frameworks, we show that the pronounced reallocation of the investment portfolio required to transform the energy system will not be initiated by the current suite of countries’ Nationally Determined Contributions. Charting a course toward ‘well below 2 °C’ instead sees low-carbon investments overtaking fossil investments globally by around 2025 or before and growing thereafter. Pursuing the 1.5 °C target demands a marked upscaling in low-carbon capital beyond that of a 2 °C-consistent future. Actions consistent with an energy transformation would increase the costs of achieving the goals of energy access and food security, but reduce the costs of achieving air-quality goals. The scale and nature of energy investments under diverging technology and policy futures is of great importance to decision makers. Here, a multi-model study projects investment needs under countries’ nationally determined contributions and in pathways consistent with achieving the 2 °C and 1.5 °C targets as well as certain SDGs.

Oil prices have fluctuated remarkably in recent years. Previous studies have analysed the impacts of future oil prices on the energy system and greenhouse gas emissions, but none have quantitatively assessed how the broader, energy-system-wide impacts of diverging oil price futures depend on a suite of critical uncertainties. Here we use the MESSAGE integrated assessment model to study several factors potentially influencing this interaction, thereby shedding light on which future unknowns hold the most importance. We find that sustained low or high oil prices could have a major impact on the global energy system over the next several decades; and depending on how the fuel substitution dynamics play out, the carbon dioxide consequences could be significant (for example, between 5 and 20% of the budget for staying below the internationally agreed 2 ∘C target). Whether or not oil and gas prices decouple going forward is found to be the biggest uncertainty. The recent drop in oil prices is having a profound impact on global energy markets, raising questions about how these markets might evolve over the long term. This study uses scenarios to assess the energy and emissions impacts of diverging oil price futures and which uncertainties they depend upon.