Understanding the association between urban noise and nighttime light in China

Abstract

Nighttime light data partially reflects the process of urban modernization and its reaction to urban scale, but its correlation with noise remains unclear, especially over a long-term time series, remains unclear. To address this gap, we examine 31 provincial capital cities and municipalities in China as the study area, utilizing noise monitoring data and nighttime light data to explore their relationship in urban areas from 2012 to 2021. The results show that: (1) During the study period, the regional environmental noise and night light index of 31 major cities exhibited a consistent upward trend, with the average equivalent sound level of environmental noise in most urban areas fluctuating between 50.1 dB (A) and 60.0 dB (A). The overall quality evaluation was average, indicating that the effectiveness of noise pollution prevention and control was difficult to sustain in the long term. (2) The driving factor affecting the change in environmental noise quality in urban areas is population density. (3) There is a significant correlation between different types of noise proportion and urban construction and development, with the closest correlation observed with the urban economy, urban built-up area, and urban construction land area. Cities with high levels of urbanization tend to have more vulnerable acoustic environments. (4) Industrial noise percentage of urban environmental noise has a significant positive impact on nighttime light data. This study provides valuable insights for promoting the coordinated development between urbanization and acoustic environment optimization, as well as fostering a healthy and sustainable living environment.

Keywords: Correlation research; Influencing factors; Nighttime light data; Temporal and spatial variation; Urban environmental noise.

Fig. 1

Overview of the study area: (a) location of the provincial capital city, (b) geographical division.

Fig. 2

Flow chart of correlation research based on urban regional environmental noise and nighttime light data.

Fig. 3.

Time series changes of major cities from 2012 to 2021: (a) urban environmental noise, (b) night light index.

Figure. 4.

The standard deviation ellipse and its gravity center migration trajectory of major cities from 2012 to 2021: (a) Urban environmental noise, (b) Night light intensity. Based on the standard map with review number GS(2019)1822 downloaded from the standard map service website of the Ministry of Natural Resources, with no modification to the base map.

Fig. 5

Time series changes of various noise source proportion in major urban areas: (a) provincial capital city, (b) national.

Fig. 6

Spearman correlation matrix diagram: (a) urban environmental noise, (b) traffic noise percentage of urban environmental noise, (c) industrial noise percentage of urban environmental noise, (d) construction noise percentage of urban environmental noise, (e) the noise of social activities percentage of urban environmental noise, (f): nighttime light data, (g): urban GDP, (h) urban area, (i) urban built-up area green rate, (j) urban built-up area, (k) urban construction land area, (l): urban population density, (m): total retail sales of consumer goods (*p < 0.05 **p < 0.01).