Simulation and characteristic analysis of urban environmental noise in daytime and nighttime in Guangzhou

Accurate understanding of the temporal and spatial distribution characteristics of urban noise is crucial for the prevention and control of noise and the reduction of adverse health consequences related to noise exposure. Most of the previous studies focused on the spatial distribution of noise and neglected their temporal variation. Based on the urban environmental noise monitoring data from 2011 to 2019, this paper simulated and analyzed the spatial and temporal distribution of environmental noise in 8 districts of Guangzhou by random forest method. The results showed that there is no obvious annual and quarterly variation of day and night noise in Guangzhou, but obvious diurnal fluctuation characteristics with the residents’ activities. The simulated values of day and night noise were 52.92-63.20 dB and 37.21-55.33 dB, respectively. It’s obvious heterogeneity of the noise spatial distribution. During daytime, the high-noise were mainly concentrated in areas with dense road networks, along both sides of expressways and urban main roads, as well as the overpasses and crossroads. At night, the areas with high noise levels were mainly distributed in the old urban districts, as well as the areas surrounded by some expressways and the intersections of major urban roads. Overall, the noise level in the central urban area was high, especially around major urban traffic arteries, followed by the areas around industrial parks and commercial centers. The main sources of daytime noise were road traffic, dense population and their activities, while the main sources of nighttime noise were road traffic, human activities and activities related to industrial production and medical services. The simulation and analysis framework of environmental noise distribution can provide theoretical support for the assessment of environmental noise exposure risk and health impact of residents, as well as for the formulation of targeted urban noise prevention and control measures.