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

Authors :
Cui, Qiang
Antunes, Jorge
Wanke, Peter
Tan, Yong
Roubaud, David
Jabbour, Charbel Jose Chiappetta
Source :
Journal of Environmental Management. Feb2024, Vol. 352, pN.PAG-N.PAG. 1p.
Publication Year :
2024

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. • We propose a novel approach to estimating an overall environmental performance index for airline pollutant emissions. • It is based on weighted additive utility functions, given the distance traveled between airports. • Neural networks are used to predict the impact of infrastructure characteristics of the origin and destination airports. • Ground control, automatic information service, surface concrete, centerline lighting system have positive impacts. • Runway length and width, longer distances to the control tower in origin airports, and asphalt runway have negative impacts. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03014797
Volume :
352
Database :
Academic Search Index
Journal :
Journal of Environmental Management
Publication Type :
Academic Journal
Accession number :
175136941
Full Text :
https://doi.org/10.1016/j.jenvman.2024.120117