Climate impact reduction has for a long time focused on carbon dioxide (CO2) released into the atmosphere, but recent assessments show non-CO2 climate effects to be equally, if not more, harmful. Dr Sigrun Matthes coordinates aviation climate change research at Germany’s DLR research centre: “The climate effect of aviation is composed of CO2 and non-CO2 effects - which include contrail-cirrus, NOx induced changes on ozone and methane, water vapour effects and aerosol indirect effects.” The radiative effects caused by these non-CO2 emissions can be positive or negative, equivalent to warming and cooling climate effects, depending upon the weather, flight path, and climatic conditions representing the physical state of the atmosphere. The net radiative effect of non-CO2 emissions is positive and thus has a warming effect on climate. According to a report (1) published by the European Aviation Safety Agency in 2020, non-CO2 emissions account for more than half of aviation’s total climate effect.
Under Dr Matthes’ leadership, the SESAR FlyATM4E project investigated climate optimised aircraft trajectories that mitigate the impact of non-CO2 emissions based on analysis of flight data during different meteorological conditions, vertical, and horizontal flight paths. There are still many uncertainties surrounding the radiative effects of non-CO2 emissions, however, project partners identified a potential 20-50% reduction in climate effect as a result of minor flight detours, estimated to less than 4% of the direct operating costs.
FlyATM4E explored a concept on how to describe the spatially and temporally varying climate effect of non-CO2 emissions, e.g. where warming contrail can form, based on atmospheric weather prediction together with numerical modelling to provide quantitative estimates of aviation climate effects. Project partners developed a prototype algorithm combining climate change functions with meteorological forecast information to enable identification of an optimised route for a particular flight which can be used by flight dispatch during the planning phase. The prototype provides functions for different non-CO2 emissions night and day which can be merged into one climate change function to show how much an emission released would modify the global surface temperature over e.g. the next 20 years. Universidad Carlos III de Madrid, Director PhD Program Aerospace Engineering, Manuel Soler explains: “We are optimising trajectories to take climate change into account as part of the business objective. We can find win-win solutions by weighting climate effect against cost to pick solutions that are more eco-efficient.” He acknowledges 20-50% uncertainty is high, and expects further research to help refine the algorithms.
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The prototype algorithmic climate change functions can be plugged into existing flight planning systems today, with the potential to also support planning decisions at network management level and by navigation service providers. Accessed via an application programming interface (API), the solution could be used to provide polygons, graphs, and maps at different flight levels showing areas most likely to produce a large climate effect in terms of the global surface temperature over the next 20 years. “This is a SESAR success story because for the first time we’ve been able to encapsulate climate change information into an open-source library, available for anyone to access,” says Sigrun Matthes concerning the DLR lead research paper (Dietmüller et al., 2022). “It offers a preliminary meteorological service related to climate change to support industrialisation and the development of future standards.”
- EASA Analysis of the non-CO2 climate impacts of aviation https://drive.google.com/file/d/1u4_fSu232_8gO5_TUf8GTZKZ6mZcxggG/view
- Dietmüller, S., Matthes, S., Dahlmann, K., Yamashita, H., Simorgh, A., Soler, M., Linke, F., Lührs, B., Meuser, M. M., Weder, C., Grewe, V., Yin, F., and Castino, F.: A python library for computing individual and merged non-CO2 algorithmic climate change functions: CLIMaCCF V1.0, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2022-203, in review, 2022. https://gmd.copernicus.org/preprints/gmd-2022-203/