Modeling Continuous Descent Approaches for Decarbonizing Aviation through Monte Carlo Analysis of Thrust Inputs

Abstract

Aviation is one of the leading causes of harmful emissions in the transportation industry. Airplanes burn fossil fuels and release contrails during flight, contributing to air pollution and magnifying the greenhouse effect [1]. In this study, a model was developed to analyze one potential solution to reducing aviation’s carbon footprint: continuous descent arrivals (CDA). This model utilized Python to set atmospheric variables and parameters for the airplane as it landed through a CDA, without the steps typically seen in a step-down approach. CDAs are beneficial because they eliminate the need for thrust and the associated emissions when they come in for a step-down approach, because there is no longer the need for the thrust that maintains the altitude at each stage in the descent. This model varied thrust input and input time throughout a simulated CDA in a Monte Carlo simulation. The results show that while CDAs have the potential to greatly reduce aviation’s emissions, they still require some thrust input to ensure the aircraft makes the runway. The timing and magnitude of this thrust input must be adjusted correctly, or there is the risk of missing the airport or landing too fast or too slow. This study found that when thrust of magnitudes anywhere from 70 to 100 kN was input about halfway through the descent, around 1000 seconds into the CDA, it resulted in the most successful landings. Eventually, models like this will allow for the development of CDAs that do not require any thrust input, putting the aviation industry a step in the right direction.