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The optimization of aircraft trajectories involves balancing operating costs and climate impact, which are often conflicting objectives. To achieve compromise optimal solutions, higher-level information such as preferences of decision-makers must be taken into account. This paper introduces the SolFinder 1.0 module, a decision-making tool designed to identify eco-efficient aircraft trajectories, which allow to reduce the flights climate impact with limited cost penalties compared to cost-optimal solutions. SolFinder 1.0 offers flexible decision-making options that allow users to select trade-offs between different objective functions, including fuel use, flight time, NOx emissions, contrail distance, and climate impact. The module is included in the AirTraf 3.0 submodel, which optimizes trajectories under atmospheric conditions simulated by the ECHAM/MESSy Atmospheric Chemistry model. This paper focuses on the ability of the module to identify eco-efficient trajectories while solving a bi-objective optimization problem that minimizes climate impact and operating costs. SolFinder 1.0 enables users to explore trajectory properties at varying locations of the Pareto fronts without prior knowledge of the problem results and to identify solutions that limit the cost of reducing the climate impact of a single flight.

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 55 % reduction in climate impact can be achieved at the expense of a 4 % increase in the operating cost.

As aviation's contribution to anthropogenic climate change is increasing, industry aims at reducing the aviation climate effect. However, the large contribution of non-CO2 effects to the total climate effect of aviation and their large variability for each individual flight inhibit finding appropriate guidance. Here, we present a method for the simplified calculation of CO2 equivalent emissions, expressed using the physical climate metrics ATR100 or AGWP100, from CO2 and non-CO2 effects for a given flight, exclusively based on the aircraft seat category as well as the origin and destination airports. The simplified calculation method estimates non-CO2 climate effects of air traffic as precisely as possible, without detailed information on the actual flight route, actual fuel burn, and current weather situation. For this purpose, we evaluate a global data set containing detailed flight trajectories, flight emissions, and climate responses, and derive a set of regression formulas for climate effects, which we call climate effect functions, as well as regression formulas for fuel consumption and NOx emissions. Compared to previous studies, this method is available for a larger number of aircraft types, including most commercial airliners with seat capacities starting from 101 passengers, and delivers more specific results through a clustering approach. The climate effects calculated using the climate effect functions derived in this study exhibit a mean absolute relative error of 15.0 % and a root mean square error of 1.24 nK with respect to results from the climate response model AirClim. The climate effect functions are designed for climate footprint assessments, but would not create an incentive in an emission trading system, for which detailed information on the current weather as well as the actual flight route and profile would be required.

The aviation industry has set an ambitious goal of reducing its climate impacts. Accordingly, airlines must balance their plans according to this goal with financial considerations. We developed a multi-objective framework to facilitate climate-aware network design by incorporating the objective to minimise the flight average temperature response (ATR) when optimising the airline network. We also assessed the operational improvements (OIs) which are introduced to improve sustainability in airline operations. In particular, we considered intermediate stop-overs (ISOs) and lower flight altitudes as OIs in our case studies. We analysed the impact of considering the climate impact in the planning of operations of three different airline types: one main-hub-and-spoke (KLM), one smaller multi-hub airline (TAP), and one low-cost carrier (EasyJet). The results show that airlines could also lower their environmental impact by 10–36% when considering the ATR as an objective. However, this would require an 8–20% reduction in profits. Adopting lower-altitude flying with ISO could mitigate their climate impact by 27–49% while reducing profits by approximately 6%. Our study highlights the importance of considering the airline network as a whole and demonstrates the potential benefits of operational improvements from a network perspective.

Aircraft trajectories are currently flown and optimized to reduce operating costs, keeping engine CO2-emissions from burnt fuel at a minimum by following fuel optimized routes under consideration of wind. However, research has shown that the location and time of non-CO2 emissions such as NOx, water vapor or the formation of contrail cirrus contribute to about two thirds of aviation’s induced climate impact [1]. Consequently, one option to reduce this impact on a short time horizon is operational measures that aim to optimize aircraft trajectories with regard to climate impact by avoiding atmospheric regions that are especially sensitive to non-CO2 emissions from aviation. For this purpose, the effects of individual emission species need to be quantified in order to assess the mitigation potential by climate-optimized routing. For this reason, multi-dimensional algorithmic climate change functions, which allow for the quantification of the climate impact of emissions, based on meteorological parameters which a e available from weather forecast data is used. These algorithmic climate change functions are integrated into the cost functional of a trajectory planning algorithm which is based on an optimal control approach and applied in order to estimate climate optimized aircraft trajectories trading climate impact reduction against cost increase. Since the climate impact and therefore the algorithmic climate change functions are highly dependent on the prevailing atmospheric conditions, particularly the formation of contrail cirrus, weather prediction uncertainties are considered in order to determine robust eco efficient trajectories. Within this study, the methodology and optimization applied to determine such a robust solution are presented and results are analyzed for an exemplary intra-European flight route. Single European Sky ATM Research Programme

Airlines’ fleet assignment heavily affects the economic and ecological performance of the global air transportation system (ATS). Consequently, it is inevitable to include potential changes of the fleet assignment when modeling and assessing future global ATS scenarios. Therefore, this article presents a novel explanatory approach to modeling the fleet assignment in the global ATS. The presented approach is based on formulating and solving an optimization problem, which describes the fleet assignment in the ATS through a suitable combination of objective function and constraints. While the objective function combines both the airline and the passenger perspective on the fleet assignment, the constraints include additional operational and technological aspects. In comparison to the available global fleet assignment models in the literature, which rely on statistical approaches, the advantages of the presented approach via an optimization problem lie in the overall scenario capability and the consideration of explicit aircraft types instead of simplifying seat categories. To calibrate and validate our model, we use 10 years of historic flight schedule data. The results underline the strengths and weaknesses of the presented approach and indicate potential for future improvement.

Neben den Kohlenstoffdioxid-Emissionen tragen sogenannte Nicht-CO2-Effekte erheblich zur anthropogenen Gesamtklimawirkung der Luftfahrt bei. Zu diesen Effekten zählt unter anderem die Bildung von Kondensstreifen, die sich zu Kondensstreifen-Zirren entwickeln können, die die lokale Strahlungsbilanz unter anderem durch Albedo-Effekte beeinflussen. Da technologische Adaptionen zur Reduktion der Klimawirkung nicht kurzfristig implementierbar sind, werden im Rahmen der vorliegenden Arbeit betriebliche Ansätze und deren Umsetzbarkeit untersucht. Mithilfe bereits publizierter Studien zum Thema operationeller Mitigation werden weitere Anforderungen und Ansätze abgeleitet, wodurch Strategien mit gezielten Adaptionen der vierdimensionalen Trajektorien einer Flugmission erarbeitet werden. Hierfür wird der primäre Fokus auf eine vertikale Flughöhenadaption und eine zeitliche Verschiebung der Flugtrajektorie gesetzt. Um die Wirkung der Strategien zu quantifizieren, folgt die Bildung einer Flugverkehrssimulation mit Bezugnahme von meteorologischen Bedingungen und Trajektoriendaten, welches eine Approximation hinsichtlich der Klimawirkung unter Beachtung der Lebensdauer erzeugt. Die Strategien und das zugehörige Reduktionspotenzial werden abschließend im Rahmen einer Verkehrssimulation über dem Nordatlantik untersucht. Die Ergebnisse zeigen, dass wenige Flüge den Großteil der anthropogenen Klimawirkung erzeugen, wodurch mit gezielten Adaptionen weniger Flüge klimawärmende Segmente explizit vermieden werden kann.