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In this chapter, we estimate the effect of surface metering technology deployed at Charlotte Douglas International Airport (CLT) by the National Aeronautics and Space Administration (NASA) and the Federal Aviation Administration (FAA) on fuel consumption and CO₂ emissions. We employed a difference-in-differences strategy, covariate-balancing methods, and a fixed-effects model. Furthermore, we used a doubly robust strategy that combines matching with parametric regression, using datasets constructed through data-driven approaches to minimize discretion in selecting comparison units. Our estimates, based on a daily panel of U.S. carriers from November 2015 to November 2019, suggest that about 39.156 kg of fuel (95% confidence interval [CI]: 13.436–64.017) and 120.599 kg of CO₂ (CI: 41.382–197.174 kg) could be saved per flight—even when the single-engine taxiing rate was as high as 75% during the entire deployment phase. At the same time, our results suggest a concerning pattern: the taxi-out time savings generated by the technology diminished over time.

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Estimating Tactical Surface Metering Management’s Effect on Aircraft Fuel Savings at Airport

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  • 发表日期：

    2025年

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  • Hideki Fukui

摘要

In this chapter, we estimate the effect of surface metering technology deployed at Charlotte Douglas International Airport (CLT) by the National Aeronautics and Space Administration (NASA) and the Federal Aviation Administration (FAA) on fuel consumption and CO₂ emissions. We employed a difference-in-differences strategy, covariate-balancing methods, and a fixed-effects model. Furthermore, we used a doubly robust strategy that combines matching with parametric regression, using datasets constructed through data-driven approaches to minimize discretion in selecting comparison units. Our estimates, based on a daily panel of U.S. carriers from November 2015 to November 2019, suggest that about 39.156 kg of fuel (95% confidence interval [CI]: 13.436–64.017) and 120.599 kg of CO₂ (CI: 41.382–197.174 kg) could be saved per flight—even when the single-engine taxiing rate was as high as 75% during the entire deployment phase. At the same time, our results suggest a concerning pattern: the taxi-out time savings generated by the technology diminished over time.