In this work, the impact of the COVID-19 outbreak on the environmental noise generated by the air traffic at the Hannover Airport, Germany, is assessed. For this purpose, a comparative study of the air traffic noise in the years 2019 and 2020 is conducted by means of publicly available measurement data and computational simulations. Based on environmental noise directives defined by the responsible German authorities, the comparative study is conducted in terms of A-weighted equivalent sound pressure level metrics computed for the six months of the forecast years with the largest number of flights. In comparison with the year of 2019, the measurement data indicates that the [Formula: see text], and [Formula: see text] were reduced in average by 2.4, 4.2, and 3.7 dBA, respectively, in the year 2020. Furthermore, the results based on the computational simulations show that the isocontour areas of the [Formula: see text] and [Formula: see text] noise protection zones defined by the German federal government were reduced by [Formula: see text] and [Formula: see text], respectively, in the year of 2020.
The continuous growth of air traffic and increased availability of open source data has enabled the application of data-driven approaches for the prediction of noise contours around airports. Aiming at efficient noise simulations, this contribution proposes a framework for the probabilistic
description of the air traffic around an airport. The methodology is based on using the density-based clustering algorithm OPTICS to cluster flight trajectories. The clustered trajectories serve as a basis for the creation of backbone and dispersion tracks, which, together with a prescribed
number of flight operations per aircraft type, provide a probabilistic description of the air traffic to the noise simulations. A major focus is given to quantitatively assess the sensitivity of the OPTICS algorithm to different hyper-parameters to reduce the dimensionality of the problem.
This framework is demonstrated utilizing a dataset of ADS-B trajectory data associated with flights approaching Hannover airport. Noise simulations based on the ECAC Doc. 29 best-practice method are conducted using SoundPLAN. A good agreement between noise contours is obtained when comparing
simulations performed using the proposed framework and the full dataset while the computational time required decreased. Furthermore, this approach identifies most of the trajectory patterns with the least amount of outliers.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.