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The impact of Chinese airport infrastructure on airline pollutant emissions: A hybrid stochastic-neural network approach based on utility functions

Yes / 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. / The full-text of this article will be released for public view at the end of the publisher embargo on 18 Jan 2025.

Identiferoai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/19783
Date18 January 2024
CreatorsCui, Q., Antunes, J., Wanke, P., Tan, Yong, Roubaud, D., Jabbour, C.J.C.
Source SetsBradford Scholars
LanguageEnglish
Detected LanguageEnglish
TypeArticle, Accepted manuscript
Rights© 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., CC-BY-NC-ND

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