Assessing the performance of the sonAIR aircraft noise model in predicting noise levels at Schiphol Airport

Abstract

Aircraft noise is a significant problem for communities surrounding airports. Accurate prediction models are needed to estimate noise levels from aircraft operations. In this research, the accuracy of the sonAIR aircraft noise model in predicting noise levels from departures around Schiphol airport is evaluated by comparison to measurement data from NOMOS and the current best-practice modelling approach Doc29. Results show a significant but consistent underestimation of noise levels by sonAIR, mainly due to a generalisation of emission models. The standard deviation of differences between model results and measurements is lower for sonAIR than for Doc29 by up to 1 dB. Differences between measurement and model results were found in the relation between N1 and noise levels, and for maximum noise levels. The results demonstrate that sonAIR provides more reliable predictions of noise levels on the single flight event level than Doc29. Additionally, this study shows agreement with results from a previous validation study in Zürich, thereby demonstrating the applicability of sonAIR to another airport. This research contributes to better aircraft noise predictions, which will have implications that ultimately lead to a better quality of life for communities affected by aircraft noise.