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.

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Aviation aims to reduce its climate effect by adopting trajectories that avoid regions of the atmosphere where aviation emissions have a large impact. To that end, prototype algorithmic climate change functions (aCCFs) can be used, which provide spatially and temporally resolved information on aviation's climate effect in terms of future near-surface temperature change. These aCCFs can be calculated with meteorological input data obtained from, e.g., numerical weather prediction models. We present here the open-source Python library called CLIMaCCF, an easy-to-use and flexible tool which efficiently calculates both the individual aCCFs (i.e., aCCF of water vapor, nitrogen oxide (NOx)-induced ozone production and methane depletion, and contrail cirrus) and the merged non-CO2 aCCFs that combine all these individual contributions. To construct merged aCCFs all individual aCCFs are converted to the same physical unit. This unit conversion needs the technical specification of aircraft and engine parameters, i.e., NOx emission indices and flown distance per kilogram of burned fuel. These aircraft- and engine-specific values are provided within CLIMaCCF version V1.0 for a set of aggregated aircraft and engine classes (i.e., regional, single-aisle, wide-body). Moreover, CLIMaCCF allows the user to choose from a range of physical climate metrics (i.e., average temperature response for pulse or future scenario emissions over the time horizons of 20, 50, or 100 years). Finally, we demonstrate the abilities of CLIMaCCF through a series of example applications.@en

The aircraft’s environmental performance on fleet level is so far completely decoupled from the design process. The climate impact from aviation arising from non-CO2 effects are largely independent from CO2 emissions, but rather depend on the atmospheric state. Previously complex climate-chemistry models were used to evaluate the non-CO2 emissions impact on climate. This is far too computationally demanding for a multidisciplinary design optimisation (MDO) process, requiring a multitude of climate impact evaluations. The question then is, how to efficiently design the next generation climate optimal aircraft? In this paper, a new concept for designing aircraft with minimum climate impact using Climate Functions for Aircraft Design (CFAD) is presented. The content of this paper provides an overview of the development of these innovative CFAD and demonstrates the ability to be integrated in an existing MDO framework. The mitigation potential by optimising aircraft design using CFAD is analysed with respect to different cruise conditions and by minimizing the overall climate impact. To validate the CFAD, a higher fidelity assessment is carried out. Finally, the key performance indicators, i.e. fuel consumption, flight time and operating cost, of the optimised aircraft design are compared to that of the reference aircraft.@en

Aviation ensures mobility for both passengers and goods. It is important as a transport sector for connections on and between continents. Nevertheless, aviation also contributes to anthropogenic climate change. The effects are usually divided in CO2 and non-CO2 effects and therefore not only CO2 emissions but also other emissions (e.g., NOx , water vapour or soot) and contrails are covered. To reduce the effects of aviation’s climate impact, several mitigation options are applied. One approach are climate change functions, which will be addressed here. The concept of climate change functions was used in previous projects, e.g. REACT4C, WeCare, ATM4E. The goal of these functions was to optimize the aircraft routes regarding the calculated climate impact. Climate change functions measure the climate impact per unit emission for a specific day, which considers the current meteorological conditions. Climate change functions were previously used to optimize the aircraft routings. The concept should now be applied for the optimization of the aircraft design as well since the promising concept is currently missing for the application of aircraft design optimization. The climate functions for aircraft design will connect the aircraft design with the climate impact of various emission in order to be able to optimize the aircraft design. For the calculation of the functions, it is necessary to define a specific application. This application results from a combination of aircraft design parameters. Aircraft design parameters can be for example flight altitude, climb rate, speed or range. Based on a resulting emission inventory, the temperature response can be calculated with the model “AirClim”. This model calculates with the input, first, the radiative forcing and based on that the temperature change. The final development step is the verification of the climate functions.@en

Aviation can reduce its climate impact by controlling its CO2-emission and non-CO2 effects, e.g. aviation-induced contrail-cirrus and ozone caused by nitrogen oxide emissions. One option is the implementation of operational measures which aim to avoid those atmospheric regions that are in particular sensitive to non-CO2 aviation effects, e.g. where persistent contrails form. Quantitative estimates of mitigation potentials of such climate-optimized aircraft trajectories are required, when working towards sustainable aviation. Results are presented from a comprehensive modelling approach which is working towards identifying such climate-optimized aircraft trajectories. The overall concept relies on a multi-dimensional environmental change function concept, which is capable of providing environmental impact information to air traffic management (ATM) and which in principal could include the noise and air quality impacts. A one-day case study with a weather situation containing regions with high contrail impacts for European air traffic estimated an overall climate impact reduction of about 30% for an increase of costs of 0.5%, relying on best estimate for climate impact information. The climate impact reduction and mitigation potential varies strongly with individual routes. By using a range of different climate metrics, the robustness of proposed mitigation trajectories is assessed. Sustainable ATM needs to integrate comprehensive environmental impacts and associated forecast uncertainties into route optimisation in order to identify robust eco-efficient trajectories. @en

Air traffic contributes to anthropogenic global warming by about 5% due to CO2 emissions (about 1/3) and non-CO2 effects (about 2/3) primarily caused by emissions of NOx and water vapour as well as the formation of contrails. Since aviation is expected to maintain its trend to grow over the next decades, mitigation measures are required counteracting its negative effects upon the environment. One of the promising operational mitigation measures which has been subject of the EU project ATM4E, is climate-optimized flight planning using algorithmic climate change functions describing the climate sensitivity as a function of emission location and time. The methodology developed for the use of algorithmic climate change functions in trajectory optimization is described and results of its application to the planning of about 13,000 intra-European flights on one specific day are presented. The optimization problem is formulated as bi-objective continuous optimal control problem with climate impact and fuel burn being the two objectives. Results on individual flight basis indicate that there are three major classes of different routes which are characterized by different shapes of the corresponding Pareto-fronts. For the investigated scenario, results show a climate impact mitigation potential of about 73% which is related with a fuel penalty of 14.5%. However, a climate impact reduction of 50% can already be achieved with 0.75% additional fuel burn. @en

Air traffic management as currently under development by the Single European Sky ATM Research program has an important role to play in reducing environmental impact of aviation by operational means, in addition to the improvements to be derived from improved aircraft and engine technologies. Information on environmental and climate impact of aviation emissions are required during the flight planning process, in order to assess environmental impact of aircraft operations for an environmental optimization of aircraft trajectories. Modelling capabilities linking such environmental impact information with the air traffic management (ATM) are required to allow a multi-dimensional environmental impact assessment during the flight planning process. For this purpose, this study presents a concept for an advanced MET Service which enables to determine aviation emission climate impacts for carbon dioxide, nitrogen oxides, contrails, and water vapour, on a daily basis. This concept has been developed within the Exploratory Research Project ATM4E (Air Traffic Management for Environment, SESAR2020). It relies on so-called algorithmic environmental change functions (aECFs) which provide expected environmental impact of a local emission and which can be directly integrated in aircraft trajectory optimisation tools, based on weather forecast data. We present how to transform environmental impact of aviation emissions calculated with state-of-the-art climate-chemistry-models into environmental change functions, and further on relating them to synoptical forecast information to generate aECFs. We present ideas on future implementation of such advanced meteorological services required for climate-optimization into air traffic management in a case study for Europe using prototype ECFs. We show that regions sensitive to aviation emissions can be avoided with only small changes in flight time and at low costs. Environmental performance parameters, e.g. overall climate impact given as average temperature change over a specific period, demonstrates environmental benefit of such routing options. Assuming market-based measures were in place, which include these non-CO2 effects, climate optimal routing of aircraft would even be beneficial for airline operators. Having available such kind of comprehensive assessment framework in ATM integrating aECFs as advanced MET Service would allow studying and characterising changes in traffic flows due to environmental optimisation, as well as studying trade-offs between distinct strategic measures. The current study has been supported by ATM4E project, which has received funding from the SESAR Joint Undertaking under grant agreement No 699395 under European Union’s Horizon 2020 research and innovation program. High-performance computing simulations with the chemistry-climate model EMAC were performed at the Deutsches Klima-Rechenzentrum (DKRZ), Hamburg. @en

For the first time, the algorithmic Climate Change Functions (aCCFs) for ozone, methane, water vapor, and persistent contrails have been developed within the ATM4E project to provide information on the climate sensitive regions, which can be conveniently implemented for the climate based flight routing. These aCCFs need to be verified before they are implemented. In this paper, we focus on the verification of the ozone aCCFs to enable the prediction of the short-term NOx effects from aviation en-route. The verification is conducted from two aspects. Firstly, the climatology of the ozone aCCFs is calculated based on a one-year simulation and verified by the existing literature. Secondly, the effectiveness of the ozone aCCFs for optimizing aircraft trajectories concerning the climate impact is verified by the comprehensive climate-chemistry model calculation. @en

Besides CO2, the climate impact of commercial aviation is strongly influenced by non-CO2 effects, which are highly sensitive to meteorological conditions and their spatial variations. To assess the cost-benefit potential (climate impact mitigation vs. cost increase) of climate and weather optimized flight trajectories in the North Atlantic flight corridor, optimal control techniques are applied. However, the execution of multi-criteria route optimizations for an intercontinental route network and various weather patterns is computationally highly intensive. Since computational resources are limited, a reduced surrogate route network is generated and evaluated first with regard to the computational effort, the coverage in terms of available seat kilometers, as well as the accuracy of reproducing the original route network with regard to climate impact. The proposed reduced route network consists of 40 routes (original network: 1,359) and is able to reproduce the climate impact of the original route network with reasonable climate impact deviations of 2.5%. The evaluation of climate and weather optimized trajectories is performed for the top route of the surrogate network. The maximum climate impact reduction potential is differing strongly from 9% up to 60% for varying North Atlantic weather patterns. Averaged over the weather patterns, a maximum climate impact mitigation potential of about 32%, going along with a cost increase of about 8% has been estimated. However, at a cost penalty of 1%, a potential climate impact reduction of 24% has been observed @en

Within this study, the lack of incentivizing airlines to internalize their climate costs is tried to be closed by the introduction of climate-charged airspaces, as non-CO2 emissions have locationand time-dependent effects upon the climate. In order to create an incentive for airlines to minimize flight time and emissions in highly climatesensitive regions, a climate charge is imposed for airlines when operating in these areas. Costminimizing airlines are expected to re-route their flights to reduce their climate charges and hence cash operating costs. Accordingly, this leads to the desired outcome of incentivizing climate mitigation and even of driving technological innovation towards cleaner technologies. The evaluation of the climate impact mitigation potential of climate-charged airspaces is performed based on optimal control techniques. Climate sensitivities are expressed by climate change functions characterizing the climate impact caused by an emission at a certain location and time. The cost-benefit potential (climate impact mitigation vs. rise in operating costs) is investigated for a Transatlantic route and benchmarked against climate-optimized trajectories. @en

Comprehensive assessment of the environmental aspects of flight movements is of increasing interest to the aviation sector as a potential input for developing sustainable aviation strategies that consider climate impact, air quality and noise issues simultaneously. However, comprehensive assessments of all three environmental aspects do not yet exist and are in particular not yet operational practice in flight planning. The purpose of this study is to present a methodology which allows to establish a multi-criteria environmental impact assessment directly in the flight planning process. The method expands a concept developed for climate optimisation of aircraft trajectories, by representing additionally air quality and noise impacts as additional criteria or dimensions, together with climate impact of aircraft trajectory. We present the mathematical framework for environmental assessment and optimisation of aircraft trajectories. In that context we present ideas on future implementation of such advanced meteorological services into air traffic management and trajectory planning by relying on environmental change functions (ECFs). These ECFs represent environmental impact due to changes in air quality, noise and climate impact. In a case study for Europe prototype ECFs are implemented and a performance assessment of aircraft trajectories is performed for a one-day traffic sample. For a single flight fuel-optimal versus climate-optimized trajectory solution is evaluated using prototypic ECFs and identifying mitigation potential. The ultimate goal of such a concept is to make available a comprehensive assessment framework for environmental performance of aircraft operations, by providing key performance indicators on climate impact, air quality and noise, as well as a tool for environmental optimisation of aircraft trajectories. This framework would allow studying and characterising changes in traffic flows due to environmental optimisation, as well as studying trade-offs between distinct strategic measures@en