Automated simulation for household road traffic noise exposure: Application and field evaluation in a high-density city

Abstract

Road traffic noise is a major nuisance and a risk factor of poor health for urban dwellers. A household's exposure to road traffic noise, especially in a high-density city, can be easily modified by the surrounding built environment, i.e., roads, traffic, buildings, and the topography. This leads to high variation in noise exposure between neighboring households. Existing simulation-based studies were limited in accounting for the variation of noise exposure at the household level, which restricted their applications in public health research involving large numbers of participants. This paper describes a novel simulation-based workflow to assess household traffic noise exposure, which consists of 1) a source model to assess road traffic noise levels, 2) a propagation model to simulate noise propagation in complex three-dimensional urban areas, 3) an automation algorithm to process large quantity of simulation runs and data. The workflow has been evaluated using field studies conducted in Sham Shui Po District, Hong Kong, with reasonably good agreements between simulated and measured data. It was then used to assess road traffic noise exposure for a sample of 6158 households enrolled in the FAMILY Cohort, representing Hong Kong's population dwelling in the dense urban areas. Results showed that 83% of sampled households have been exposed to excessive road traffic noise above the World Health Organization (WHO) standard, or 30% above the local standard. The estimated burden of disease is over 45,000 disability-adjusted life-years (DALYs) from both high annoyance and sleep disturbance for households in Hong Kong. The study has contributed to the methodologies and datasets in evaluating noise exposure in high-density cities, which can further support urban noise mitigation policies and planning and population-based health studies in the next steps.