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The impact of Chinese airport infrastructure on airline pollutant emissions: A hybrid stochastic-neural network approach based on utility functions
Cui, Q. Antunes, J. Wanke, P. Tan, Yong Roubaud, D. Jabbour, C.J.C.
Cui, Q.
Antunes, J.
Wanke, P.
Tan, Yong
Roubaud, D.
Jabbour, C.J.C.
Publication Date
2024-02
End of Embargo
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© 2024 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.
Peer-Reviewed
Yes
Open Access status
openAccess
Accepted for publication
12/01/2024
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Department
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Abstract
With China being the world’s largest emitter of greenhouse gases and its aviation sector burgeoning, the environmental performance of Chinese airlines has global significance. Amidst rising demands for eco-friendly
practices from both customers and regulators, the interplay between airport infrastructure and environmental
performance becomes pivotal. This research offers an innovative methodology to gauge the environmental
performance of Chinese airlines, emphasizing the distance traveled between airports using weighted additive
utility functions. Leveraging neural networks, the study investigates the impact of various airport infrastructural
characteristics on environmental performance. Noteworthy findings indicate that ground control measures,
automatic information services at origin airports, surface concrete on runways at both ends, and a centerline
lighting system in destination airports positively influence environmental performance. In contrast, longer and
wider runways at origin airports, increased distances to control towers, and asphalt runways at destination
airports adversely affect it. These insights not only underscore the importance of strategic infrastructure enhancements for reducing carbon footprints but also hold profound policy implications. As global climate change
remains at the forefront, fostering sustainable airport infrastructure in China can significantly contribute to
worldwide mitigation efforts.
Version
Accepted manuscript
Citation
Cui Q, Antunes J, Wanke P et al (2024) The impact of Chinese airport infrastructure on airline pollutant emissions: A hybrid stochastic-neural network approach based on utility functions. Journal of Environmental Management. 352: 120117.
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Article