How to make environmental noise monitoring more robust? "The answer, my friend, is blowing in the wind"

Wind-induced noise is a major challenge in environmental noise monitoring, as it can interfere with accurate measurements and generate false noise events. This effect occurs when wind interacts with the measurement microphone, introducing unwanted fluctuations that compromise data quality. To mitigate this issue, windscreens are commonly used; however, their effectiveness varies based on design, size and wind speed. Previous studies have attempted to address wind-induced noise by setting fixed noise limits, optimizing microphone placement, or developing models for wind-induced noise. While these approaches have had some success, they do not fully eliminate the need for post-processing and manual review of measurement data. In this work, we propose a method that utilizes measurement values to characterize commonly used windscreens. By analyzing these values in conjunction with recorded wind speed, we develop a predictive model for estimating wind-induced noise. This approach allows us to classify noise events as either real or wind-induced, enabling noise consultants to focus on genuine noise sources and significantly streamlining the analysis process. By improving the accuracy and efficiency of noise monitoring, our findings contribute to more reliable environmental assessments and enhanced decision-making in noise management.