This paper aims to demonstrate the importance of uncertainties in the measurement of environmental noise in the context of Italian legislation on noise pollution focusing the attention on the variability of the measurand as a source of uncertainty and offering a proposal for the evaluation of uncertainty for traffic noise measurement. In particular, drawing on a real traffic noise dataset, firstly outliers are eliminated from the actual noise measurements using an outlier detection algorithm based on K-neighbors distance and then uncertainty range is estimated with the bootstrap-t method. Since the original sequence was Gaussian, this range was compared with the confidence interval of the mean ± standard deviation interval and two intervals were almost coincident.
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