Evaluation of road traffic noise exposure based on high-resolution population distribution and grid-level noise data

The primary objective of this study is to propose a method for assessing population exposure to road traffic noise based on high-resolution population and grid-level noise data. First, after meshing the study region and setting the receivers at the nodes, the noise values of all receivers are calculated by regarding roads as linear sound sources, and these values are rendered as the traffic noise distribution. Next, a population distribution model is trained with point of interest (POI) sample data, population sample data, and the random forests algorithm. Then, the statistics of the POIs in the grids are input to the trained model as the noise distribution; the grid-level population data are obtained and used to depict the population distribution. Then, to facilitate the assessment, the grid-level traffic noise distribution data and population distribution data are combined according to the ID or location of the nodes of grids. Finally, evaluation indexes considering the traffic noise and population distribution are used to assess the population exposure to traffic noise. The proposed method is applied to three types of regions in Guangzhou: a residential area, a commercial area and an industrial area. The noise pollution levels of all study regions are ‘Mild’, but the pollution of road traffic noise is most severe in the residential area with 12.00% of the population and 7.60% of the area affected due to the denser road network and stricter standards. These results indicate that people in residential areas are more sensitive to road traffic noise. [Display omitted] •A method for assessing the micro-scale the population exposure to road traffic noise is developed.•High-resolution traffic noise and population distributions are used.•Block-level population data are disaggregated into grid-level distribution data.•Spatial distribution of population exposure to road traffic noise is mapped.•Evaluation indexes that consider the traffic noise and population distribution are developed.