5 results
Now showing1 - 5 of 5
- Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Operational improvements to reduce the climate impact of aviation - A comparative study from EU project ClimOP(Multidisciplinary Digital Publishing Institute (MDPI), 2023-08-09); ; 51 98 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , A Python library for computing individual and merged non-CO2 algorithmic climate change functions: CLIMaCCF V1.0(Copernicus Publications, 2023-08-02); ; ; ; 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.Publicationtype: Journal ArticleScopus© Citations 7 31 67 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Robust 4D climate-optimal flight planning in structured airspace using parallelized simulation on GPUs: ROOST V1.0(2023-07-06); ; ; ; 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.Publicationtype: Journal ArticleScopus© Citations 5 29 48 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Mitigation of aviation’s climate impact through robust climate optimized trajectories in intra-european airspace(ICAS, 2022-09); ; ; ; 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.Publicationtype: Conference PaperScopus© Citations 1 116 205 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Seasonal variability of aircraft trajectories reducing NOx-climate impacts under a multitude of weather patterns(SESAR Joint Undertaking, 2021); ; ; ; Air traffic contributes to global warming through CO2 and non-CO2 effects, including the impact of NOx emissions on atmospheric ozone and methane, formation of contrails, and changes in the amount of stratospheric water vapour. The climate impact of non-CO2 effects is highly dependent on the background atmospheric conditions at the time and location of emission. Therefore, there is the potential of mitigating the climate impact of aviation by optimizing the aircraft trajectories. In the present paper, we focus on the properties of alternative trajectories which have the potential to minimize the climate impact of NOx emissions, under a multitude of weather patterns. This study aims at enhancing the understanding of the relation between NOx-climate impacts and routing strategies, by employing the European Center Hamburg general circulation model (ECHAM) and the Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model. To this end, we conduct 1-year simulations with the air traffic submodel AirTraf 2.0, coupled to the EMAC model. We optimize 85 European flights, considering the atmospheric conditions at the time and location of the flight, to calculate the expected climate impact from the emitted species through a set of prototype algorithmic Climate Change Functions (aCCFs). The mean flight altitudes of NOx-climate optimal trajectories showed seasonal and latitudinal dependencies. We found that the potential of reducing ozone effects from aviation NOx is subjected to a strong seasonal cycle, reaching a minimum in summer.Publicationtype: Conference Paper6