Data-Driven Methodology Characterizing CO2 Emission Discrepancies Between Actual and Optimum Operations

This paper presents a data-driven methodology for estimating and comparing fuel consumption inefficiencies and [Formula: see text] emissions in the aviation sector, with a focus on improving environmental sustainability from the Air Navigation Service Provider (ANSP) perspective and contributing to decarbonization goals by emphasizing the establishment of new performance indicators for assessing the environmental impact of ANSPs. The methodology involves predicting the fuel consumption of actual flight trajectories from publicly available historical surveillance and weather data and comparing it to that of each flight’s respective performance-optimal trajectory using a multivariate regression factor weighting analysis. A case study of Airbus A320 flights between LAX and SFO is used to demonstrate the methodology’s effectiveness, including the development of a representative performance indicator for this aircraft type and flight route. The results show a significant relationship between predictor variables such as differences in altitude, distance, time, and wind between actual and optimal trajectories, with differences in distance, which ANSPs can control, being identified as the most influential factor. The methodology has the potential to enhance aviation efficiency and reduce [Formula: see text] emissions by providing a framework for evaluating the impact of ANSPs on environmental performance and offering insights for optimizing operational trajectories.