Modelled exposure to motor vehicle generated noise at schools and early childhood centres.
Motor vehicle generated noise pollution places a significant burden on the health and wellbeing of people in many urban areas and children have been identified as a particularly vulnerable group. Despite this, little is known about the extent of exposure to noise at schools and early childhood centres (ECCs), areas where children spend much of their time. To examine traffic generated noise levels at schools and ECCs, this study used the Common Noise Assessment Methods in Europe and validated the results against volunteered geographic noise measurements, using the Wellington Territorial Authority as a case study area. We examined the relationship of modelled noise values with socio-demographic variables of schools and ECCs. In addition, we assessed the relationship between modelled noise values and land use and proximity to busy roads to assess their use as proxy measures of noise. For the case study area, we found 57.7% of ECCs and 41.0% of schools exceeded the 2018 World Health Organization Environmental Noise Guidelines (53dB) and noise levels at schools and ECCs were higher compared to background levels. Schools with a higher proportion of international students, privately run ECCs, and ECCs located in the central city experienced particularly high noise levels.
Compared to volunteered in situ noise measurements, our model performed reasonably: 81% of model values within 15dB of a volunteered measurement. While we found the proxy noise measurement ‘distance to busy roads’ explained 2% of the modelled noise levels in this study. Compared to proxy measures of noise, the modelled noise levels enhanced our understanding of noise level exposure. Overall, the findings of this research highlight the magnitude and inequalities of traffic generated noise pollution on children, which may be useful for guiding policy to mitigate noise pollution around schools and ECCs, such as location planning and identifying areas where ameliorating noise levels is important.