A Methodology for Evaluating UAM Noise and Visual Pollution

This paper proposes an innovative methodology to evaluate the noise and visual pollution generated by UAM activities, with a particular focus on how these impacts vary across different population segments (e.g., differentiating by age and gender). We present the outcomes of a novel simulation toolset that models drone-generated noise and visual pollution, integrating these data with dynamic population distribution maps derived from the combination of mobile network data and GPS data from personal mobile devices. The analysis focuses on three case studies in the city of Madrid: the impact of a drone flying over residential and downtown areas during the cruise phase; the effects of take-off in a residential neighbourhood; and the cumulative effects of multiple flights. These results offer valuable insights into the local environmental impacts of UAM and are expected to contribute to the development of more targeted U-space regulations and social acceptance strategies.