Impact of electric mobility on urban noise levels predicted by time-resolved noise maps

Abstract

The transition from internal combustion engine vehicles (ICEVs) to electric vehicles (EVs) is a key component of urban decarbonization, yet its acoustic implications remain not fully captured by conventional noise assessment. This study presents a timeresolved noise mapping framework which is based on the CNOSSOS-EU guideline and driven by a microscopic traffic simulation, enabling the detailed analysis of transient noise events. The method is applied to the district of Gross Flottbek in Hamburg, Germany, to assess the impact of fleet electrification on noise pollution and human health. To model EV noise emissions, two recently proposed modifications of the CNOSSOS-EU emission model are implemented and compared. Besides the equivalent continuous night-time sound level LNight, the impact on wake-up reactions triggered by isolated pass-by events is studied. The results indicate that the overall impact on sleep quality from the transition to EVs remains moderate. The greatest decrease in wake-up probability occurs along major roads, while reductions of LNight are most pronounced in quieter residential areas. These findings demonstrate that time-resolved noise mapping is a valuable tool for a comprehensive evaluation of noise exposure, as it reveals health-relevant insights, such as the acute impact of transient events, which conventional average-based methods tend to miss.