Ambient Noise Level in Eastern North China from ChinArray and Its Response to COVID-19

Abstract

High-frequency (>1 Hz) ambient noise is usually closely related to anthropogenic activities. During the outbreak and spread of the COVID-19, as various anthropogenic activities are restricted, high-frequency ambient noise level has been observed to be reduced on a worldwide scale. The continuous waveform data at dense broadband seismic stations from ChinArray in eastern North China provides a good opportunity to study the temporal and spatial patterns of the ambient noise level in the region, and to further study the influencing factors, such as the topography and the population density. In this study, we calculated the average power spectral density of ambient noise at each station ±90 days around the Spring Festival in 2019 and in 2020, analyzed the noise level at different stations through normal times, Spring Festivals, epidemic control period, and recovery period, and studied the influencing factors of the noise level. We found that normally high-frequency (1–10 Hz) ambient noise correlates well with the surrounding sedimentary thickness: The noise level is higher when the surrounding sedimentary layer is thicker and vice versa. It correlates moderately with local population density and is time-varying due to anthropogenic activities. During the Spring Festival in 2019 and in 2020, and the epidemic control period after the Spring Festival in 2020, the reduction extent of the noise level correlates moderately with both the sedimentary thickness and population density; the ambient noise level reduces more significantly to the south of 40° N than to the north of it in the study region. Considering that the sedimentary thickness beneath each station is not time-varying, the variation in ambient noise level due to anthropogenic activities is clearly amplified by the sedimentary layer.

Sensing Human Activity of the Guangdong–Hong Kong–Macao Greater Bay Area by Ambient Seismic Noise

“…These intricate signals are generally stronger during the day than at night, less intense on weekends than on weekdays, and more pronounced in urban areas than in rural areas [13,61,62]. Moreover, human activities can be influenced by inclement weather or traditional festivals [64,68,69]. As mentioned previously, the dominant frequency of cultural seismic noise ranges from 2 to 20 Hz in the GBA.…”

“…Previous studies have shown that cultural seismic noise levels are closely related to regional population density and economic development [44,63,64]. Consequently, we analyzed the correlation between cultural seismic noise and population density [65] as well as gross domestic product (GDP) [66,67] in the GBA (Figures 5 and 6).…”

“…Previous studies have shown that cultural seismic noise changes significantly during traditional festivals such as the Chinese Spring Festival [44,64], Christmas [13,69], and others. In our dataset, 120 stations recorded cultural seismic noise during the New Year's Days, a three-day holiday for Chinese citizens.…”

CSES Satellite Observations of 50 Hz Power Line Radiation Over Mainland China and Its Response to COVID‐19

“…At the end of 2019, novel coronavirus cases were diagnosed in Wuhan, China, and the virus was named COVID‐19 in February 2020 by the World Health Organization (Zhou et al., 2020). As the COVID‐19 epidemic escalated, different regions in China successively imposed epidemic control measures, such as restrictions on rallies, suspension of industrial production, management of floating populations, and health quarantine (W. Wang et al., 2021). On 23 January, China raised national public health response to the highest state of emergency‐ Level 1 of 4 levels of severity in the Chinese Emergency System (Tian et al., 2020).…”

Big Data Seismology

“…Finally, the data set was large enough to challenge researchers to employ considerable computational resources to devise and perform novel large‐scale data‐hungry analyses, some of which have derived from the exploration seismology community (Burdick et al., 2014; Lin et al., 2011; Long et al., 2014). The success of well‐behaved data sets like USArray to drive innovation is evident in like‐spirited deployments that have followed it: IberArray in the Iberian Peninsula (Díaz et al., 2008), AlpArray in the Alps (Hetényi et al., 2018), and ChinArray in China (K. Wang et al., 2020; W. Wang et al., 2021; Zeng et al., 2020). Through these efforts and others, the continued growth of data volumes, computing availability, and the appetites of our algorithms is expanding the scope of seismic inquiry into emerging areas.…”