Ambient noise characteristics at seismic stations in Huangshi City
Using continuous seismic waveform data from the vertical component collected at three seismic stations in Huangshi City,Hubei Province,from January 2018 to March 2020,the power spectral density and probability density function of noise acceleration were calculated for the three stations before the COVID-19 pandemic(from January 2018 to December 2019)and during the pandemic(from January to March 2020).This study focused on the spatiotemporal variation of high-frequency(1-10 Hz)seismic ambient noise.Results are as follows:(1)During the COV-ID-19 pandemic prevention period,an overall decrease in the acceleration power spectral density of high-frequency noise was observed.Notably,during the Spring Festival in 2018 and 2019,the amplitudes of short-period(approximately 1 s)noises decreased,with a rapid recovery after the holiday.However,during the COVID-19 pandemic prevention in 2020,noise amplitudes substan-tially dropped and remained at low levels.(2)Changes in diurnal pattern were observed.Before the pandemic,the power spectral density of earthquake background noise in the daytime(6:00-20:00)was notably higher than that in the nighttime(20:00-6:00).At approximately 12:00,the power spectral density decreased for a short time,and the lowest value appeared at approxi-mately 2:00.This change is consistent with the pattern of human work and rest.However,dur-ing the COVID-19 epidemic prevention and control,the noise amplitudes decreased,and the diur-nal variation became less pronounced,indicating a reduction in human activities,which in turn led to changes in the high-frequency noise amplitude.(3)Additionally,population density and economic development were found to affect the ambient noise level.Regions with higher popula-tion density and greater economic development exhibited higher noise levels,indicating a correla-tion between urban human activities and economic conditions with seismic ambient noise.These results offer substantial reference value for urban planning,public administration,and environ-mental protection,providing valuable insights for monitoring urban human activities and impro-ving public governance.
seismic ambient noiseHuangshi Citypower spectral densityprobability density functionhuman activity
万方数据
维普
