Quantifying low-frequency acoustic fields in urban environments

Abstract

Summary Infrasound data contain contributions from incoherent noise, coherent noise, and signals of interest. The design of an infrasound array to target sources of interest requires a quantification of array response, individual sensor response, propagation effects (topography and meteorological conditions), signal spectrum, and the noise environment. The Comprehensive Nuclear-Test-Ban Treaty community has spent significant effort in quantifying the acoustic field in rural environments for frequencies up to 7 Hz. Given that the nuclear monitoring and tactical infrasound community have growing interests in monitoring sources in or near populated regions, there is an emergent need to measure and understand acoustic fields in these environments as well. This paper focuses on quantification of the acoustic field in three different urban environments: (1) arrays installed within Dallas, TX, a metropolitan area, (2) an array installed at the rural-suburban interface near San Diego, CA, and (3) an array installed in Vicksburg, MS, a small city with multiple major transportation corridors. A minimum of five months of data was recorded and used for each site characterization. The analysis focuses on frequencies from 0.1–45 Hz. The quantification of the data from these three sites is accomplished with statistical noise models that capture the total ambient acoustic field, separation of the coherent portion of the field, and trend analysis to link temporal and seasonal variations to wind speed and anthropogenic activities. The resulting physical interpretation of the data demonstrates that the total acoustic field in urban regions is overall higher and inversely related to the number of coherent detections observed by an array. Furthermore, this study presents an analysis framework for characterizing additional urban arrays and provides a basis for future array site selection and installation.

Methodological Aspects of Industrial and Transport Noise Monitoring

“…The physical features of infrasound include a long wavelength and low absorption in the atmosphere and the resulting ability of infrasound to propagate over long distances from the source without significant loss of energy. It should be kept in mind that sound propagates spherically and the decrease in sound pressure is inversely proportional to the square of the distance from the source [13,14].…”

Local Infrasound Monitoring of Lava Eruptions at Nyiragongo Volcano (D.R. Congo) Using Urban and Near‐Source Stations

“…Near‐source infrasound stations (i.e., flank and summit) already provided insights into the eruptive dynamics of Nyiragongo (Barrière et al., 2018; Valade et al., 2018). However, operating an infrasound station like GOM in a dense urban area is challenging (McComas et al., 2022) and has not been adequately tested or explored worldwide. If an infrasound station deployed in a city detects a coherent and meaningful signal, it could reduce the need for a dangerous geophysical deployment, overcoming possible accessibility, security and/or budgetary issues.…”

“…Path effects due to the topography can be significant at local scale, altering the waveform (Lacanna & Ripepe, 2013) and resulting in biased source locations if straight‐line propagation is assumed (Fee et al., 2021). In case of a dense urban area nearby, human activity can also be an issue, since the anthropogenic acoustic noise at infrasound frequencies can reduce the detectability of other signals (McComas et al., 2022). Finally, microbaroms generated over the oceans are a dominant source of ambient noise recorded worldwide around 0.1–0.4 Hz (Bowman et al., 2005) and can contaminate volcanic signals (Fee et al., 2010; Rosenblatt et al., 2022).…”

“…Near-source infrasound stations (i.e., flank and summit) already provided insights into the eruptive dynamics of Nyiragongo (Barrière et al, 2018;Valade et al, 2018). However, operating an infrasound station like GOM in a dense urban area is challenging (McComas et al, 2022) and has (Berens, 2009).…”

Updated Global Reference Models of Broadband Coherent Infrasound Signals for Atmospheric Studies and Civilian Applications

“…Previous works have provided measures of the incoherent noise (Bowman et al., 2005; Brown et al., 2012; Marty et al., 2021) and measures of the ambient coherent infrasound (Matoza et al., 2013), both globally and at each station. There have also been other studies, which use different techniques for identifying the coherent signals, such as the Fisher statistic (Evers & Haak, 2001; Park et al., 2016) or a frequency–wavenumber (FK) array processing algorithm (McComas et al., 2022; Rost & Thomas, 2002); however, these studies focused on a small number of non‐IMS stations. The goal of this work is to provide an update of the previous ambient coherent infrasound signals at each station.…”