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.
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