Scenario Results

Several policy scenarios are simulated using the numerical optimization methods presented, these are summarized in Table 8.

Tip

Every scenario in this section can be reproduced with the scripts of the optimization examples gallery: the run_*.py scripts re-run each optimization, and the plot_compare_*.py scripts regenerate the comparison figures from the pre-computed optima shipped with the repository.

Table 8 Overview of simulated scenarios and their assumptions regarding: the background scenario, personal demand saturation, presence of traffic aversion policies, optimization objective, energy carriers included, the share of global energy production allocated to aviation, and the technology scenarios. In case multiple background scenarios, the objective is the mean among realizations. The demand saturation indicates storyline-specific assumptions on the stabilization level of per-capita demand. In presence of extra price-based traffic aversion, the objective is the minimization of relative ticket price increase. The energy carriers included are subject to variable Entry-Into-Service, and are limited to a fixed share of global production of biomass and electricity. Finally, the technology scenarios are determinant of the aircraft technology parameters, impacting the performance of new aircraft designs, driving the choice of which architectures to deploy.

Scenario name	Background scenario	Demand saturation	Traffic aversion	Policy objective (min)	Energy carriers		Tech scenarios
Baseline SSP1	SSP1-1.9	Trend -10%		Cumulative CO2	Jet-A (fossil)		Lower, Mid, Upper
Baseline SSP2	SSP2-2.6	Trend		Cumulative CO2	Jet-A (fossil)		Lower, Mid, Upper
Baseline SSP5	SSP5-4.5	Trend +50%		Cumulative CO2	Jet-A (fossil)		Lower, Mid, Upper
Drop-in trend	SSP2-2.6	Trend		Cumulative CO2	Jet-A (fossil+SAF)	5.0	Lower, Mid, Upper
Drop-in availability	SSP2-2.6	Trend		Cumulative CO2	Jet-A (fossil+SAF)	8.6	Lower, Mid, Upper
Drop-in low-demand	SSP2-2.6	Trend	✓	Rel. price increase	Jet-A (fossil+SAF)	5.0	Lower, Mid, Upper
Breakthrough trend	SSP2-2.6	Trend		Cumulative CO2	Jet-A (fossil+SAF), LH2, Battery	5.0	Lower, Mid, Upper
Breakthrough availability	SSP2-2.6	Trend		Cumulative CO2	Jet-A (fossil+SAF), LH2, Battery	8.6	Lower, Mid, Upper
Breakthrough low-demand	SSP2-2.6	Trend	✓	Rel. price increase	Jet-A (fossil+SAF), LH2, Battery	5.0	Lower, Mid, Upper
Scenario-robust trend	SSP2-1.9, 2.6, and 3.4	Trend		Mean cumulative CO2	Jet-A (fossil+SAF), LH2, Battery	5.0	Mid
Scenario-robust low-demand	SSP2-1.9, 2.6, and 3.4	Trend	✓	Min rel. price increase	Jet-A (fossil+SAF), LH2, Battery	5.0	Mid

We start with the baseline no-policy scenarios (SSP1, 2, and 5), where two new generations of conventional aircraft are launched, and their entry-into-service and deployment is optimized to minimize cumulative emissions, while consuming only fossil kerosene. The sensibility to maturing aircraft technology is also explored with 3 technology scenarios affecting: energy consumption of current aircraft, fleet replacement lifetimes, and energy consumption of new aircraft (Fig. 11).

Then the mitigation scenarios are explored using SSP2 as the baseline. The Drop-in trend mitigation scenarios also introduce incorporation of biofuel and electrofuel (SAF) in the Jet-A blend, and constraint the sectoral consumption of electricity and biomass to 5.0 % of the global supply. The Drop-in availability mitigation scenario increases the sectoral consumption to 8.6 %. And the Drop-in low-demand mitigation scenario keeps trend consumption, but avoids traffic in order to fulfill an additional constraint on the total cumulative emissions. As the baseline scenarios, these are also explored with 3 technology scenarios.

The Breakthrough mitigation scenario increments the Drop-in by introducing new alternative aircraft concepts (Battery-Electric, LH2 Fuel-Cell, and LH2 Gas Turbine), and is also divided into a trend, availability, and low-demand variant, each sweeping the 3 technology scenarios.

Finally, the scenario-robust mitigation scenarios keep all mitigation measures (SAF and deployment of alternative aircraft), but the objective is now to optimize the mean among 3 different background scenarios: SSP2-1.9, 2.6, and 3.4. These scenarios keep the trend assumption of 5.0 % global energy production allocated to aviation, and are divided into a trend and low-demand variant. For simplification purposes, these are only explored with the Mid aircraft technology.

Energy production sankey diagrams. Comparison of energy production sankey diagram for global aviation by 2045 for SSP2 scenarios: (a) Baseline, (b) Drop-in, and (c) Breakthrough. These also assume extra energy availability, and Mid aircraft technology.

(a) Baseline:

(b) Drop-in:

(c) Breakthrough:

Fig. 17 Comparison of scenario trends (traffic, annual and cumulative emissions, carbon and energy intensity) for the Baseline scenarios. The sensibility to aircraft technology is displayed with 3 aircraft technology scenarios: Lower (continuous line), Mid (dotted line), and Upper technology (shadowed region).

Fig. 18 Comparison of scenario trends for the Drop-in scenarios (legend as in Fig. 17).

Fig. 19 Comparison of scenario trends for the Breakthrough scenarios (legend as in Fig. 17).

The overall scenario results are presented and analyzed here; the full fleet and energy results are presented at the end of each scenario section.