Development of a Fast Method to Analyze Patterns in Airport Noise

Abstract

Traditional airport noise modeling is limited in its ability to analyze large quantities of flight tracks due to high computation time. As a result, yearly noise reports are often limited to modeling flights from a single “representative day,” which lacks detail arising from the natural dispersion of flight tracks and variety in airport operations occurring throughout an entire year of operations.

A framework for processing actual flight data and applying an existing, fast noise approximation is presented. Tens of thousands of flights can be analyzed in a matter of hours, allowing for a data-comprehensive approach to calculating noise metrics. Method results are cross-validated against the Aviation Environmental Design Tool (AEDT) on a single-event basis and an existing aggregate result on a multi-event basis.

Results for a variety of metrics are presented based on data sourced from Boston Logan International Airport in 2016. Day-Night-Level (DNL) is calculated on a yearly, daily, and hourly basis, highlighting the variability in noise patterns depending on evolving airport runway configuration. N60 is calculated as a supplemental metric on a daily basis.