Preprints
https://doi.org/10.5194/nhess-2022-258
https://doi.org/10.5194/nhess-2022-258
08 Nov 2022
 | 08 Nov 2022
Status: a revised version of this preprint was accepted for the journal NHESS and is expected to appear here in due course.

Seismic Background Noise Levels in Italian Strong Motion Network

Simone Francesco Fornasari, Deniz Ertuncay, and Giovanni Costa

Abstract. Italian strong motion network monitors the seismic activity of Italy and its surrounding with more than 700 stations. Thanks to the upgrade of the stations with continuous data acquisition, it is possible to measure the noise level of the strong motion network. In this study, we used the recorded background noise to estimate the variations in the noise levels of the network. Data recorded in 2019 and 1st of January to 30th of April 2022 are used to understand the noise level of the stations and data from the COVID-19 lockdown period are used to see the effect of the anthropogenic sources on the background noise. To do that, power spectrum density is calculated for the continuous stations. It is found that more than half of the stations exceed the background noise model designed for strong motion stations by Cauzzi and Clinton (2013) in at least one of the calculated periods. Considering the characteristics of the instrumentation at the stations and their deployment often near urban areas, we focused on relatively short periods (≤5 s), interested by anthropic noises. Stations can be noisier during the day, up to 14 decibels and during the weekday, up to 5 decibels in short periods. Noise level differences between day-night decrease with an increasing period as the human-related high-frequency effects of humans are attenuated. As expected, the noisiest stations are located in densely populated areas such as center of Naples, whereas the quietest stations are located far away from cities. The swell, sea, and wind effects, on the other hand, are not observed in stations. During the COVID-19 lockdown, noise levels dropped to 6.5 decibels in daytime and 12.5 decibels on weekdays. Noise levels are reduced by around 2 decibels in 0.1 s, in which cultural noise is predominant. Furthermore, we found that the vehicles have measurable effects on noise levels.

Simone Francesco Fornasari et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2022-258', Anonymous Referee #1, 29 Dec 2022
    • AC1: 'Reply on RC1', Simone Francesco Fornasari, 21 Mar 2023
  • RC2: 'Comment on nhess-2022-258', Anonymous Referee #2, 24 Mar 2023
    • AC2: 'Reply on RC2', Simone Francesco Fornasari, 04 Apr 2023
  • RC3: 'Comment on nhess-2022-258', Anonymous Referee #3, 04 Apr 2023
    • AC3: 'Reply on RC3', Simone Francesco Fornasari, 14 Apr 2023
  • RC4: 'Comment on nhess-2022-258', Anonymous Referee #4, 05 Apr 2023
    • AC4: 'Reply on RC4', Simone Francesco Fornasari, 05 May 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2022-258', Anonymous Referee #1, 29 Dec 2022
    • AC1: 'Reply on RC1', Simone Francesco Fornasari, 21 Mar 2023
  • RC2: 'Comment on nhess-2022-258', Anonymous Referee #2, 24 Mar 2023
    • AC2: 'Reply on RC2', Simone Francesco Fornasari, 04 Apr 2023
  • RC3: 'Comment on nhess-2022-258', Anonymous Referee #3, 04 Apr 2023
    • AC3: 'Reply on RC3', Simone Francesco Fornasari, 14 Apr 2023
  • RC4: 'Comment on nhess-2022-258', Anonymous Referee #4, 05 Apr 2023
    • AC4: 'Reply on RC4', Simone Francesco Fornasari, 05 May 2023

Simone Francesco Fornasari et al.

Simone Francesco Fornasari et al.

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Short summary
We analyzed the background seismic noise for the Italian strong motion network. Several stations located near urban areas are affected by human activities and have high noise levels in the low periods. As such, noise levels show clear daily and weekly patterns and reductions during the COVID-19 lockdown. Moreover, we found slight seasonal variations. Our results provide an overview of the background noise of the network and can be used as a station selection criterion for future research.
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