Cost-Effective Climate-Friendly Aircraft Flight Planning

The aviation-induced non-CO₂ climate effects, being responsible for two-thirds of aviation radiative forcing [1], have a direct dependency on atmospheric location and time of emissions. This implies that their associated impacts can be mitigated by planning climate-aware trajectories to avoid areas of airspace with large climate effects [2]. However, for the efficiency of such a mitigation strategy, one needs to consider various sources of uncertainty. In fact, if not accounted for within flight planning a priori, the rather immature scientific understanding of aviation-induced climate effects and uncertainty associated with emissions calculation and meteorological conditions can lead to inefficient aircraft trajectories. In addition, the mitigation potential achieved by the climate-optimal routing option increases the operating costs as the aircraft flies longer by re-routing climate-sensitive areas. In this respect, there is a need to plan robust climate-optimal aircraft trajectories having a minimum cost increase compared to the Business-as-usual (BAU) scenario.

In the current study, we present robust climate optimal aircraft trajectory planning, considering meteorological uncertainties. The airspace is assumed to be fully free routing. The information on the spatio-temporal dependency of aviation-induced climate effects is based on the latest version of the prototype algorithmic climate change functions (aCCF V1.1) [3]. An ensemble prediction weather forecast is used to characterize meteorological uncertainty. The flight planning objective is to find an efficient balance between the increased operating costs and the mitigated climate effects with acceptable ranges of uncertainty. The general approach for decision-making between conflicting objectives relies on building a Pareto-frontier by running the optimization many times, each corresponding to a weighting parameter in the objective function (see e.g., [4]). In this study, by proposing a more efficient modeling scheme in the definition of the aircraft trajectory optimization within the context of optimal control theory, we provide an ability to determine the highest possible mitigation potential with a user-specified limit on the increased operating cost and vice versa only in two iterations. In this approach, we define the “Lagrangian” term of the performance index (used to represents climate effects in the objective function) as an additional state variable, enabling to impose path and boundary constraints on the climate effect and its dispersion.

The effectiveness of the proposed approach is illustrated by considering the optimization of 10 flights on June 13, 2018, 0000UTC. Due to the strong variability among different members of relative humidity within the EPS weather forecast, the climate impact of contrails is highly uncertain. This in turn leads to high uncertainty in quantifying the net climate effects due to the dominant impact of contrails compared to the remaining species. For the considered case studies, it is shown that by employing the proposed trajectory optimizer, it is possible to minimize the climate effects while respecting the specified available extra operating cost in US dollars. In addition, the uncertainty on the quantified climate effects lies within the user-defined range, implying that the sensitivity of climate impact to the uncertainty in the forecasted weather conditions can be controlled.