Mapping Noise Pollution Using Modelled and Crowdsourced Urban Noise Data

ABSTRACT Transport‐generated noise pollution significantly burdens population health. Quantifying noise distribution and identifying areas with elevated noise levels is crucial for designing effective policy measures. We apply the CNOSSOS‐EU numerical transport noise model to Pōneke Wellington, mapping traffic‐induced noise exposure with good spatial coverage from public data. Crowdsourced noise data (CND) maps all noise sources and we spatially compare results. While unsuitable as a standalone method, CND highlights the impact of missing noise sources and offers a limited but promising validation tool for modelled data when alternatives are lacking.