Aviation emissions are not on a trajectory consistent with Paris Climate Agreement goals. We evaluate the extent to which fuel pathways-synthetic fuels from biomass, synthetic fuels from green hydrogen and atmospheric CO 2 , and the direct use of green liquid hydrogen-could lead aviation towards net-zero climate impacts. Together with continued efficiency gains and contrail avoidance, but without offsets, such an energy transition could reduce lifecycle aviation CO 2 emissions by 89-94% compared with year-2019 levels, despite a 2-3-fold growth in demand by 2050. The aviation sector could manage the associated cost increases, with ticket prices rising by no more than 15% compared with a no-intervention baseline leading to demand suppression of less than 14%. These pathways will require discounted investments on the order of US$0.5-2.1 trillion over a 30 yr period. However, our pathways reduce aviation CO 2 -equivalent emissions by only 46-69%; more action is required to mitigate non-CO 2 impacts.

Aviation emissions have been found to cause 5% of global anthropogenic radiative forcing and ∼16 000 premature deaths annually due to impaired air quality. When aiming to reduce these impacts, decision makers often face trade-offs between different emission species or impacts in different times and locations. To inform rational decision-making, this study computes aviation's marginal climate and air quality impacts per tonne of species emitted and accounts for the altitude, location, and chemical composition of emissions. Climate impacts are calculated using a reduced-order climate model, and air quality-related health impacts are quantified using marginal atmospheric sensitivities to emissions from the adjoint of the global chemistry-transport model GEOS-Chem in combination with concentration response functions and the value of statistical life. The results indicate that 90% of the global impacts per unit of fuel burn are attributable to cruise emissions, and that 64% of all damages are the result of air quality impacts. Furthermore, nitrogen oxides (NO x ), carbon dioxide (CO 2 ), and contrails are collectively responsible for 97% of the total impact. Applying our result metrics to an example, we find that a 20% NO x stringency scenario for new aircraft would reduce the net atmospheric impacts by 700 m USD during the first year of operation, even if the NO x emission reductions cause a small increase in CO 2 emissions of 2%. In such a way, the damage metrics can be used to rapidly evaluate the atmospheric impacts of market growth as well as emissions trade-offs of aviation-related policies or technology improvements.

The climate impact of bioenergy is commonly quantified in terms of CO2 equivalents, using a fixed 100‐year global warming potential as an equivalency metric. This method has been criticized for the inability to appropriately address emissions timing and the focus on a single impact metric, which may lead to inaccurate or incomplete quantification of the climate impact of bioenergy production. In this study, we introduce Dynamic Relative Climate Impact (DRCI) curves, a novel approach to visualize and quantify the climate impact of bioenergy systems over time. The DRCI approach offers the flexibility to analyze system performance for different value judgments regarding the impact category (e.g., emissions, radiative forcing, and temperature change), equivalency metric, and analytical time horizon. The DRCI curves constructed for fourteen bioenergy systems illustrate how value judgments affect the merit order of bioenergy systems, because they alter the importance of one‐time (associated with land use change emissions) versus sustained (associated with carbon debt or foregone sequestration) emission fluxes and short‐ versus long‐lived climate forcers. Best practices for bioenergy production (irrespective of value judgments) include high feedstock yields, high conversion efficiencies, and the application of carbon capture and storage. Furthermore, this study provides examples of production contexts in which the risk of land use change emissions, carbon debt, or foregone sequestration can be mitigated. For example, the risk of indirect land use change emissions can be mitigated by accompanying bioenergy production with increasing agricultural yields. Moreover, production contexts in which the counterfactual scenario yields immediate or additional climate impacts can provide significant climate benefits. This paper is accompanied by an Excel‐based calculation tool to reproduce the calculation steps outlined in this paper and construct DRCI curves for bioenergy systems of choice.