Estimating the impacts of traffic intensity, weather conditions, and airspace structure on fuel consumption and flight time of Brazilian commercial aviation

Abstract

This study employs a statistical modeling approach to commercial aviation fuel consumption and flight time to assess air traffic management (ATM) performance. The study investigates the operational factors that impact ATM efficiency, exploring airport-specific performance. Using datasets from Automatic Dependent Surveillance - Broadcast (ADS-B) surveillance systems, the Brazilian air transport statistical database, and meteorological data, the research develops linear regression models to quantify the effects of traffic intensity, weather conditions, and airspace structure on fuel consumption and flight time. The data covers the Brazilian domestic market from 2018 to 2022, totaling more than 1.3 million flights analyzed. The findings suggest differences in the impacts of traffic intensity and adverse weather conditions among the busiest airports in Brazil. Some airports had better efficiency levels for the same traffic intensity level, while the airspace structure’s impact was somewhat more similar in all major airports. At SBGR, for example, the busiest airport in Brazil, the traffic intensity during arrivals caused about 74 kilograms of extra fuel per flight, while the airspace structure was associated with about 160 kilograms of extra fuel per flight. This research offers insights into quantifying potential savings from ATM improvements by providing a data-driven approach.