Minimising emissions from flights through realistic wind fields with varying aircraft weights

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Wells, C. A. orcid id iconORCID: https://orcid.org/0000-0001-9438-4954, Williams, P. D. orcid id iconORCID: https://orcid.org/0000-0002-9713-9820, Nichols, N. K. orcid id iconORCID: https://orcid.org/0000-0003-1133-5220, Kalise, D. and Poll, I. (2023) Minimising emissions from flights through realistic wind fields with varying aircraft weights. Transportation Research Part D: Transport and Environment, 117. 103660. ISSN 1361-9209 doi: 10.1016/j.trd.2023.103660

Abstract/Summary

The international aviation community has agreed to advance actions to reduce CO emissions. Adopting more fuel-efficient routes will achieve this goal quickly and economically. Full satellite coverage of transatlantic flight routes is now a reality, allowing us to consider moving from the Organised Track Structure to Trajectory-Based Operations. Here, fuel-optimal trajectories through wind fields from a global atmospheric re-analysis dataset are found using dynamic programming. The control variables of aircraft headings and airspeeds are varied to find free-time, fuel-minimal routes. Aircraft fuel consumption is modelled with a new model-specific fuel-burn function, which incorporates aircraft mass reductions as fuel is burned. From 1 December 2019 to 29 February 2020, fuel use from simulated routes is compared with fuel estimates based on recorded flight data. Results demonstrate that an average fuel reduction of 4.2% is possible without significant changes to flight duration. This equates to a reduction of 16.6 million kg of CO emissions. Therefore, free-time, fuel-minimal routes have the potential to offer substantial fuel and emissions savings.

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Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/110952
Identification Number/DOI 10.1016/j.trd.2023.103660
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher Elsevier
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