Exploring the Rebound in Passenger Aviation

Abstract

Attention for the aviation industry's impact on climate change has increased significantly in recent years, as it is one of the fastest growing industries worldwide. Aviation contributes around 2.4% to the global emissions of CO₂ and an average of 3.5% to climate change because of fossil fuel consumption. If aviation continues its current trajectory of increasing traffic volumes, the sector will increasingly conflict with global decarbonization targets. Although aviation's emissions targets align with the overall goals of the Paris Agreement, it is unlikely that the sector will meet these goals. While efficiency measures are being implemented, concerns are growing over the short-term feasibility of current development scenarios. Given that radical engine innovations and large-scale deployment of Sustainable Aviation Fuels (SAF) are unlikely to become technically and commercially viable before 2040, improving fuel efficiency remains the most immediate and effective strategy for reducing emissions. The key short-term measures available to airlines under the four-pillar strategy proposed by the International Air Transport Association (IATA) can be summarized as follows:

- Invest in new generation, more fuel-efficient aircraft to increase average fuel efficiency;
- Implement strategies to increase passenger load factors;
- Optimize flight operations such as route planning to reduce flight distances.

As advancements in operational and aircraft fuel efficiency also enhance cost-effectiveness, airlines have the potential to significantly reduce fuel costs and pass these savings on to consumers, leading to lower ticket fares. This could further stimulate passenger demand, amplifying the existing upward trend in air travel. This feedback might result in a fuel efficiency rebound effect, partially or fully offsetting the intended emission reductions. Projections for future demand, fuel efficiency and the associated emission reduction in the literature often overlook the fuel efficiency rebound effect, leading to systematic overestimation of actual emission reductions. 

The research addresses this critical knowledge gap by conceptualizing and quantifying how future fuel efficiency rebound effects may affect projected emission reductions in passenger aviation. Previous research identified rebound effects in aviation of 49%* between 1986 and 1999, and 18.8% between 2000 and 2013, based on retrospective analysis of empirical data. A forward-looking analysis of how fuel efficiency rebound effects may influence future emission projections is currently missing. The research estimates the fuel efficiency rebound effect over a 15-year time horizon, up to 2040. Indirect rebound effects fall outside the scope of this analysis. With the aim of contributing to the integration of rebound dynamics into policy evaluation models and supporting robust policy design, the research adopts an exploratory approach by combining quantitative System Dynamics (SD) modeling with Scenario Analysis. 

The research contributes to future predictive studies on rebound effects and broader emission reduction efforts in aviation. First, it conceptualizes the key drivers and feedback mechanisms of the rebound effect using a systems thinking approach. Second, it captures these dynamics in a compact System Dynamics model, that operates without relying on extensive empirical data. Third, it estimates the rebound effect and its implications within a reference scenario, and explores a range of plausible scenario outcomes. Fourth, it analyzes these outcomes to identify influential combinations of market-specific uncertain parameters. Finally, the research highlights critical market-specific empirical data gaps that must be addressed to narrow the plausible range of model results.

The model results indicate an emission reduction potential of 14% compared to a scenario without any efficiency improvements. Within a reference scenario, a rebound effect of 91.3% was estimated over the 2025-2040 period, offsetting the majority of this potential and resulting in an actual net reduction of only 1.3%. The magnitude of the rebound and its impact on emissions is influenced by market-specific uncertainties, including airline pricing strategies, fare elasticity of demand, and the market shares of different haul segments. To capture a range of plausible outcomes, 1000 scenario runs were conducted, incorporating varying combinations of these uncertainties. The findings suggest that in the majority of scenarios, the rebound effect approaches or exceeds 100%.

Using the Patient Rule Induction Method (PRIM) algorithm, outcomes of interest were evaluated based on a rebound effect threshold, defined as any scenario in which a larger share of the emission reduction potential is offset relative to the reference scenario. The extent to which fuel cost savings are passed on to consumers appeared to be less influential, as the analysis revealed that even at its minimum value, a substantial rebound effect can occur. However, a higher average pass-through rate remains undesirable, as it is associated with an even greater magnitude of the rebound effect. The magnitude of the rebound effect exceeds the 91.3% observed in the reference scenario, under the following conditions:

- Consumers exhibit a high sensitivity to fare price reductions per passenger-kilometer;
- Relatively high market shares of longer haul segments compared to that of short-haul segments;
- Airlines can fully capitalize on demand growth, i.e. the potential amount of flights is unrestricted.

The rebound effect estimated in the research is significantly higher than the rebound effects of 49% and 18.8% reported in previous research. This discrepancy can be attributed to key methodological differences, including the use of a ceteris paribus approach that isolates behavioral feedback effects, and the exclusive focus on passenger aviation, whereas previous research also included cargo operations. The results indicate that the rebound effect in passenger aviation can offset a substantial portion of the emission reduction potential in the reference scenario. In most other scenarios, the effect is even more pronounced, with projected outcomes showing a complete offset or even an additional increase in emissions. These findings highlight a significant risk that the sector's contribution to global emission reduction targets is being overestimated, as the effectiveness of the key short-term measures under the four-pillar strategy proposed by the IATA is substantially diminished by the rebound effect.

*The rebound effect is typically expressed as the ratio of the lost savings to the expected savings, representing the share of the emission reduction potential offset by the rebound of efficiency improvements.