Modeling and characterizing urban infrasonic and low-frequency noise in the Las Vegas, NV regiona).

Empirical models of ambient infrasound noise are valuable tools for assessing the detection capabilities of infrasound networks on local to global scales. Models that characterize noise in unpopulated, quiet environments are well established, and there is a detailed understanding of the sources that contribute to rural noise profiles. However, there is a research gap for infrasound and low-frequency noise in urban environments, based on the assumption that high noise levels generated by human activity will render signals of interest, such as earthquakes and explosions, undetectable. In this study, 11 infrasound sensors deployed across Las Vegas, NV, USA from 2019 to 2021 are used to create a long-term noise profile for infrasound and low-frequency noise in the city. The resulting empirical model is used to determine whether this network deployed in an urban area is capable of recording signals of interest or if noise from anthropogenic activity dominates detections to a prohibitive degree. The Las Vegas model presented here has noise levels that sit within the bounds of established global noise models, and the network records multiple signals of interest during the study period, indicating that this and similar urban networks are more capable of reliably detecting signals of interest than previously thought.

Monitoring changes in human activity during the COVID-19 shutdown in Las Vegas using infrasound microbarometers.

While studies of urban acoustics are typically restricted to the audio range, anthropogenic activity also generates infrasound (<20 Hz, roughly at the lower end of the range of human hearing). Shutdowns related to the COVID-19 pandemic unintentionally created ideal conditions for the study of urban infrasound and low frequency audio (20-500 Hz), as closures reduced human-generated ambient noise, while natural signals remained relatively unaffected. An array of infrasound sensors deployed in Las Vegas, NV, provides data for a case study in monitoring human activity during the pandemic through urban acoustics. The array records a sharp decline in acoustic power following the temporary shutdown of businesses deemed nonessential by the state of Nevada. This decline varies spatially across the array, with stations close to McCarran International Airport generally recording the greatest declines in acoustic power. Further, declines in acoustic power fluctuate with the time of day. As only signals associated with anthropogenic activity are expected to decline, this gives a rough indication of periodicities in urban acoustics throughout Las Vegas. The results of this study reflect the city's response to the pandemic and suggest spatiotemporal trends in acoustics outside of shutdowns.

Evaluating factors influencing infrasonic signal detection and automatic processing performance utilizing a regional network.

Physical and deployment factors that influence infrasound signal detection and assess automatic detection performance for a regional infrasound network of arrays in the Western U.S. are explored using signatures of ground truth (GT) explosions (yields). Despite these repeated known sources, published infrasound event bulletins contain few GT events. Arrays are primarily distributed toward the south-southeast and south-southwest at distances between 84 and 458 km of the source with one array offering azimuthal resolution toward the northeast. Events occurred throughout the spring, summer, and fall of 2012 with the majority occurring during the summer months. Depending upon the array, automatic detection, which utilizes the adaptive F-detector successfully, identifies between 14% and 80% of the GT events, whereas a subsequent analyst review increases successful detection to 24%-90%. Combined background noise quantification, atmospheric propagation analyses, and comparison of spectral amplitudes determine the mechanisms that contribute to missed detections across the network. This analysis provides an estimate of detector performance across the network, as well as a qualitative assessment of conditions that impact infrasound monitoring capabilities. The mechanisms that lead to missed detections at individual arrays contribute to network-level estimates of detection capabilities and provide a basis for deployment decisions for regional infrasound arrays in areas of interest.