Developing an improved metric to better predict aircraft noise annoyance based on number of flights and complaints data
Predicting the impact that aircraft noise will have on the community around an airport is a challenging problem. A human being experiences sound based on more than just the sound pressure (dB), and annoyance can increase even though measured dB levels do not. With the currently used metric Lden, a 3 dB reduction in engine noise during testing allows for 2x the number of flights to be flown in the same time, without the metric being affected. This 3 dB reduction is barely noticeable by the human ear on the ground, so the annoyance increases, which is reflected in complaints and survey data. In my project I will develop a new metric that incorporates the number of flights more explicitly, aiming to better predict the annoyance caused than the current Lden metric. This will be achieved by analyzing flight tracks, number of flights and peak levels and comparing them to the complaint data obtained from Bewoners Aanspreekpunt Schiphol. Together with this data analysis, listening experiments will be conducted at the TU Delft that test the effect of a higher number of marginally quieter flyovers on experienced annoyance, which will help to substantiate or reject the developed metric.