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

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.