Air traffic assignment based on daily population mobility to reduce aircraft noise effects and fuel consumption

Journal Article (2019)
Authors

V. Ho Huu (Air Transport & Operations)

E. Ganic (University of Belgrade)

Sander Hartjes (Air Transport & Operations)

Obrad Babić (University of Belgrade)

R Curran (Air Transport & Operations)

Research Group
Air Transport & Operations
Copyright
© 2019 V. Ho-Huu, Emir Ganić, S. Hartjes, Obrad Babić, R. Curran
To reference this document use:
https://doi.org/10.1016/j.trd.2019.04.007
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 V. Ho-Huu, Emir Ganić, S. Hartjes, Obrad Babić, R. Curran
Research Group
Air Transport & Operations
Volume number
72
Pages (from-to)
127-147
DOI:
https://doi.org/10.1016/j.trd.2019.04.007
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Abstract


The paper first investigates the influence of daily mobility of population on evaluation of aircraft noise effects. Then, a new air traffic assignment model that considers this activity is proposed. The main objective is to reduce the number of people affected by noise via lowering as much as possible the noise exposure level L
den
of individuals or groups of people who commute to the same locations during the day. It is hereby intended to reduce the noise impact upon individuals rather than to reduce the impact in particular – typically densely populated – areas. However, sending aircraft farther away from populated regions to reduce noise impact may increase fuel burn, thus affecting airline costs and sustainability. Therefore, a multi-objective optimization approach is utilized to obtain reasonable solutions that comply with overall air transport sustainability. The method aims at generating a set of solutions that provide proper balance between noise annoyance and fuel consumption. The reliability and applicability of the proposed method are validated through a real case study at Belgrade airport in Serbia. The investigation shows that there is a difference between the number of people annoyed (NPA) evaluated based on the census data and the NPA evaluated based on the mobility data. In addition, these numbers differ significantly across residential locations. The optimal results show that the proposed model can offer a considerable reduction in the NPA, and in some cases, it can gain up to 77%, while maintaining the same level of fuel consumption compared with the reference case.

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