Analysis of Aircraft Routing Strategies for North Atlantic Flights by Using AirTraf 2.0
Climate-optimized routing is an operational measure to effectively reduce the climate impact of aviation with a slight increase in aircraft operating costs. This study examined variations in the flight characteristics among five aircraft routing strategies and discusses several characteristics of th...
Published in: | Aerospace |
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Main Authors: | , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
MDPI AG
2021
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Subjects: | |
Online Access: | https://doi.org/10.3390/aerospace8020033 https://doaj.org/article/04df246c7b0541fcbdcde178f60cc4f9 |
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author | Hiroshi Yamashita Feijia Yin Volker Grewe Patrick Jöckel Sigrun Matthes Bastian Kern Katrin Dahlmann Christine Frömming |
author_facet | Hiroshi Yamashita Feijia Yin Volker Grewe Patrick Jöckel Sigrun Matthes Bastian Kern Katrin Dahlmann Christine Frömming |
author_sort | Hiroshi Yamashita |
collection | Directory of Open Access Journals: DOAJ Articles |
container_issue | 2 |
container_start_page | 33 |
container_title | Aerospace |
container_volume | 8 |
description | Climate-optimized routing is an operational measure to effectively reduce the climate impact of aviation with a slight increase in aircraft operating costs. This study examined variations in the flight characteristics among five aircraft routing strategies and discusses several characteristics of those routing strategies concerning typical weather conditions over the North Atlantic. The daily variability in the North Atlantic weather patterns was analyzed by using the European Center Hamburg general circulation model (ECHAM) and the Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model in the specified dynamics mode from December 2008 to August 2018. All days of the ten complete winters and summers in the simulations were classified into five weather types for winter and into three types for summer. The obtained frequency for each of the weather types was in good agreement with the literature data; and then representative days for each weather type were selected. Moreover, a total of 103 North Atlantic flights of an Airbus A330 aircraft were simulated with five aircraft routing strategies for each representative day by using the EMAC model with the air traffic simulation submodel AirTraf. For every weather type, climate-optimized routing shows the lowest climate impact, at which a trade-off exists between the operating costs and the climate impact. Cost-optimized routing lies between the time- and fuel-optimized routings and achieves the lowest operating costs by taking the best compromise between flight time and fuel use. The aircraft routing for contrail avoidance shows the second lowest climate impact; however, this routing causes extra operating costs. Our methodology could be extended to statistical analysis based on long-term simulations to clarify the relationship between the aircraft routing characteristics and weather conditions. |
format | Article in Journal/Newspaper |
genre | North Atlantic |
genre_facet | North Atlantic |
id | ftdoajarticles:oai:doaj.org/article:04df246c7b0541fcbdcde178f60cc4f9 |
institution | Open Polar |
language | English |
op_collection_id | ftdoajarticles |
op_doi | https://doi.org/10.3390/aerospace8020033 |
op_relation | https://www.mdpi.com/2226-4310/8/2/33 https://doaj.org/toc/2226-4310 doi:10.3390/aerospace8020033 2226-4310 https://doaj.org/article/04df246c7b0541fcbdcde178f60cc4f9 |
op_source | Aerospace, Vol 8, Iss 2, p 33 (2021) |
publishDate | 2021 |
publisher | MDPI AG |
record_format | openpolar |
spelling | ftdoajarticles:oai:doaj.org/article:04df246c7b0541fcbdcde178f60cc4f9 2025-01-16T23:32:47+00:00 Analysis of Aircraft Routing Strategies for North Atlantic Flights by Using AirTraf 2.0 Hiroshi Yamashita Feijia Yin Volker Grewe Patrick Jöckel Sigrun Matthes Bastian Kern Katrin Dahlmann Christine Frömming 2021-01-01T00:00:00Z https://doi.org/10.3390/aerospace8020033 https://doaj.org/article/04df246c7b0541fcbdcde178f60cc4f9 EN eng MDPI AG https://www.mdpi.com/2226-4310/8/2/33 https://doaj.org/toc/2226-4310 doi:10.3390/aerospace8020033 2226-4310 https://doaj.org/article/04df246c7b0541fcbdcde178f60cc4f9 Aerospace, Vol 8, Iss 2, p 33 (2021) climate impact mitigation air traffic management flight trajectory optimization climate-optimized routing contrail avoidance North Atlantic weather patterns Motor vehicles. Aeronautics. Astronautics TL1-4050 article 2021 ftdoajarticles https://doi.org/10.3390/aerospace8020033 2023-12-10T01:42:30Z Climate-optimized routing is an operational measure to effectively reduce the climate impact of aviation with a slight increase in aircraft operating costs. This study examined variations in the flight characteristics among five aircraft routing strategies and discusses several characteristics of those routing strategies concerning typical weather conditions over the North Atlantic. The daily variability in the North Atlantic weather patterns was analyzed by using the European Center Hamburg general circulation model (ECHAM) and the Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model in the specified dynamics mode from December 2008 to August 2018. All days of the ten complete winters and summers in the simulations were classified into five weather types for winter and into three types for summer. The obtained frequency for each of the weather types was in good agreement with the literature data; and then representative days for each weather type were selected. Moreover, a total of 103 North Atlantic flights of an Airbus A330 aircraft were simulated with five aircraft routing strategies for each representative day by using the EMAC model with the air traffic simulation submodel AirTraf. For every weather type, climate-optimized routing shows the lowest climate impact, at which a trade-off exists between the operating costs and the climate impact. Cost-optimized routing lies between the time- and fuel-optimized routings and achieves the lowest operating costs by taking the best compromise between flight time and fuel use. The aircraft routing for contrail avoidance shows the second lowest climate impact; however, this routing causes extra operating costs. Our methodology could be extended to statistical analysis based on long-term simulations to clarify the relationship between the aircraft routing characteristics and weather conditions. Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Aerospace 8 2 33 |
spellingShingle | climate impact mitigation air traffic management flight trajectory optimization climate-optimized routing contrail avoidance North Atlantic weather patterns Motor vehicles. Aeronautics. Astronautics TL1-4050 Hiroshi Yamashita Feijia Yin Volker Grewe Patrick Jöckel Sigrun Matthes Bastian Kern Katrin Dahlmann Christine Frömming Analysis of Aircraft Routing Strategies for North Atlantic Flights by Using AirTraf 2.0 |
title | Analysis of Aircraft Routing Strategies for North Atlantic Flights by Using AirTraf 2.0 |
title_full | Analysis of Aircraft Routing Strategies for North Atlantic Flights by Using AirTraf 2.0 |
title_fullStr | Analysis of Aircraft Routing Strategies for North Atlantic Flights by Using AirTraf 2.0 |
title_full_unstemmed | Analysis of Aircraft Routing Strategies for North Atlantic Flights by Using AirTraf 2.0 |
title_short | Analysis of Aircraft Routing Strategies for North Atlantic Flights by Using AirTraf 2.0 |
title_sort | analysis of aircraft routing strategies for north atlantic flights by using airtraf 2.0 |
topic | climate impact mitigation air traffic management flight trajectory optimization climate-optimized routing contrail avoidance North Atlantic weather patterns Motor vehicles. Aeronautics. Astronautics TL1-4050 |
topic_facet | climate impact mitigation air traffic management flight trajectory optimization climate-optimized routing contrail avoidance North Atlantic weather patterns Motor vehicles. Aeronautics. Astronautics TL1-4050 |
url | https://doi.org/10.3390/aerospace8020033 https://doaj.org/article/04df246c7b0541fcbdcde178f60cc4f9 |