The non-CO₂ climate impact of aviation strongly relies on the atmospheric conditions at the time and location of emissions. Therefore, it is possible to mitigate their associated climate impact by planning trajectories to re-route airspace areas with significant climate effects. Identifying such climate-sensitive regions requires specific weather variables. Inevitably uncertain weather forecasts can lead to inefficient aircraft trajectories if not accounted for within flight planning. The current study addresses the problem of generating robust climate-friendly flight plans under meteorological uncertainty characterized using the ensemble prediction system. We introduce a framework based on the concept of robust tracking optimal control theory to formulate and solve the proposed flight planning problem. Meteorological uncertainty effects on aircraft performance variables are captured using the formulated ensemble aircraft dynamical model and controlled by penalizing the performance index variance. Case studies show that the proposed approach can generate climate-optimized trajectories with minimal sensitivity to weather uncertainty.

The spatiotemporal dependency of aviation-induced non-CO₂ climate effects can be incorporated into flight planning tools to generate climate-friendly flight plans. However, estimating climate impact is challenging and associated with high uncertainty. To ensure the effectiveness of such an operational measure, sources that induce uncertainty need to be identified and considered when planning climate-aware trajectories. The mismatch between different assessments of climate impact is an important indicator of uncertainty. This study introduces a concept aimed at planning robust climate-optimized aircraft trajectories under multiple climate impact estimates. The objective is to generate climate-optimal trajectories that achieve mitigation potential consistent with all available assessments. Case studies show that, even when there is a significant discrepancy between input models in specific regions, the proposed approach can effectively generate trajectories to mitigate the climate impact with a high level of confidence.

The climate impact of non-CO2 emissions, which are responsible for two-thirds of aviation radiative forcing, highly depends on the atmospheric chemistry and weather conditions. Hence, by planning aircraft trajectories to reroute areas where the non-CO2 climate impacts are strongly enhanced, called climate-sensitive regions, there is a potential to reduce aviation-induced non-CO2 climate effects. Weather forecast is inevitably uncertain, which can lead to unreliable determination of climate-sensitive regions and aircraft dynamical behavior and, consequently, inefficient trajectories. In this study, we propose robust climate-optimal aircraft trajectory planning within the currently structured airspace considering uncertainties in standard weather forecasts. The ensemble prediction system is employed to characterize uncertainty in the weather forecast, and climate-sensitive regions are quantified using the prototype algorithmic climate change functions. As the optimization problem is constrained by the structure of airspace, it is associated with hybrid decision spaces. To account for discrete and continuous decision variables in an integrated and more efficient manner, the optimization is conducted on the space of probability distributions defined over flight plans instead of directly searching for the optimal profile. A heuristic algorithm based on the augmented random search is employed and implemented on graphics processing units to solve the proposed stochastic optimization computationally fast. An open-source Python library called ROOST (V1.0) is developed based on the aircraft trajectory optimization technique. The effectiveness of our proposed strategy to plan robust climate-optimal trajectories within the structured airspace is analyzed through two scenarios: a scenario with a large contrail climate impact and a scenario with no formation of persistent contrails. It is shown that, for a nighttime flight from Frankfurt to Kyiv, a 55ĝ€¯% reduction in climate impact can be achieved at the expense of a 4ĝ€¯% increase in the operating cost.

The strong growth rate of the aviation industry in recent years has created significant challenges in terms of environmental impact. Air traffic contributes to climate change through the emission of carbon dioxide (CO₂) and other non-CO₂ effects, and the associated climate impact is expected to soar further. The mitigation of CO₂ contributions to the net climate impact can be achieved using novel propulsion, jet fuels, and continuous improvements of aircraft efficiency, whose solutions lack in immediacy. On the other hand, the climate impact associated with non-CO₂ emissions, being responsible for two-thirds of aviation radiative forcing, varies highly with geographic location, altitude, and time of the emission. Consequently, these effects can be reduced by planning proper climate-aware trajectories. To investigate these possibilities, this paper presents a survey on operational strategies proposed in the literature to mitigate aviation’s climate impact. These approaches are classified based on their methodology, climate metrics, reliability, and applicability. Drawing upon this analysis, future lines of research on this topic are delineated.