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Climate impact of aviation is expected to increase further. Aircraft routings are an important measure for climate impact reductions. To find an effective aircraft routing strategy for reducing the impact, the first version of the submodel AirTraf has been developed; this submodel can simulate global air traffic in the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. This paper describes the updated submodel AirTraf 2.0. Seven new aircraft routing options are introduced, including contrail avoidance, minimum economic costs, and minimum climate impact. Example simulations of the new routing options are presented by using around 100 north-Atlantic flights of an Airbus A330 aircraft for a typical winter day. The results clearly show that the family of optimum flight trajectories (three-dimensional) varies according to the routing options. The comparison of the results for various routing options reveals characteristics of the routing with respect to air traffic performances. The minimum cost option obtains a trade-off solution between the minimum time and the minimum fuel solutions. The aircraft routings for contrail avoidance and minimum climate impact reduce the potential climate impact, which is estimated by using algorithmic Climate Change Functions, whereas these two routings increase flight operating costs. A trade-off between the aircraft operating costs and the climate impact is confirmed. The simulation results are compared with literature data and the consistency of the submodel AirTraf 2.0 is verified. [ABSTRACT FROM AUTHOR]

Mobility is becoming more and more important to society and hence air transportation is expected to grow further over the next decades. Reducing anthropogenic climate impact from aviation emissions and building a climatefriendly air transportation system are required for a sustainable development of commercial aviation. A climate optimized routing, which avoids climate-sensitive regions by rerouting horizontally and vertically, is an important measure for climate impact reduction. The idea includes a number of different routing strategies (routing options) and shows a great potential for the reduction. To evaluate this, the impact of not only CO2 but also non-CO2 emissions must be considered. CO2 is a long-lived gas, while non-CO2 emissions are short-lived and are inhomogeneously distributed. This study introduces AirTraf (version 1.0) that performs global air traffic simulations, including effects of local weather conditions on the emissions. AirTraf was developed as a new submodel of the ECHAM5/MESSy Atmospheric Chemistry (EMAC) model. Air traffic information comprises Eurocontrol's Base of Aircraft Data (BADA Revision 3.9) and International Civil Aviation Organization (ICAO) engine performance data. Fuel use and emissions are calculated by the total energy model based on the BADA methodology and Deutsches Zentrum für Luft- und Raumfahrt (DLR) fuel flow method. The flight trajectory optimization is performed by a genetic algorithm (GA) with respect to a selected routing option. In the model development phase, benchmark tests were performed for the great circle and flight time routing options. The first test showed that the great circle calculations were accurate to -0.004%, compared to those calculated by the Movable Type script. The second test showed that the optimal solution found by the algorithm sufficiently converged to the theoretical true-optimal solution. The difference in flight time between the two solutions is less than 0.01%. The dependence of the optimal solutions on the initial set of solutions (called population) was analyzed and the influence was small (around 0.01%). The trade-off between the accuracy of GA optimizations and computational costs is clarified and the appropriate population and generation (one iteration of GA) sizing is discussed. The results showed that a large reduction in the number of function evaluations of around 90% can be achieved with only a small decrease in the accuracy of less than 0.1%. Finally, AirTraf simulations are demonstrated with the great circle and the flight time routing options for a typical winter day. The 103 trans-Atlantic flight plans were used, assuming an Airbus A330-301 aircraft. The results confirmed that AirTraf simulates the air traffic properly for the two routing options. In addition, the GA successfully found the time-optimal flight trajectories for the 103 airport pairs, taking local weather conditions into account. The consistency check for the AirTraf simulations confirmed that calculated flight time, fuel consumption, NOx emission index and aircraft weights show good agreement with reference data. [ABSTRACT FROM AUTHOR]

Aviation aims to reduce its climate effect by exploiting the potential of identifying alternative climate optimized aircraft trajectories. Such climate-optimized trajectories require a dedicated meteorological service in order to inform on those regions of the atmosphere where aviation emissions have a large effect on climate, for example, by contrail formation or nitrogen-oxide (NOx)-induced ozone formation. With the algorithmic Climate Change Functions (aCCFs) prototypes of a mathematical formulation for the temporal and spatial climate effects of aviation emissions in the atmosphere is provided, which relies solely on numerical weather prediction at the time and location of emissions. Based on the recently published consistent set of aCCF-V1.0, we here introduce newly derived calibration factors for the individual non-CO2 effects of aviation (NOx, water vapour, contrail cirrus) and establish version V1.0A of aCCFs (aCCF-V1.0A). ACCF-V1.0A represents an updated formulation of aCCF while exploring the current level of scientific understanding of individual climate effects of aviation emissions by evaluating quantitative estimates of climate effects with the state-of-the-art climate-response model AirClim. Individual scaling factors (i.e. AirClim calibration factors) are provided for the respective non-CO2 effects comprising contrail cirrus, water vapour and NOx-induced climate effects on ozone and methane, resulting uniformly in lower estimates in aCCF-V1.0A for all species compared to the earlier version aCCF-V1.0. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Aviation aims to reduce its climate impact by adopting trajectories, that avoid those 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 impact 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 here present the open-source Python Library called CLIMaCCF, an easy to use and flexible tool which efficiently calculates both the individual aCCFs (i.e., water vapour, nitrogen oxide (NOx) induced ozone and methane, and contrail-cirrus aCCFs) and the merged non-CO2 aCCFs that combine all these individual contributions. These merged aCCFs can be only constructed with the technical specification of aircraft/engine parameters, i.e., NOx emission indices and flown distance per kg burnt fuel. These aircraft/engine specific values are provided within CLIMaCCF version V1.0 for a set of aggregated aircraft/engine classes (i.e. regional, single-aisle, wide-body). Moreover, CLIMaCCF allows by a user-friendly configuration setting to choose between a set of different 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 by a series of example applications. [ABSTRACT FROM AUTHOR]