Annual traffic noise levels estimation based on temporal stratification. (15th January 2018) - Quintero, G.; Balastegui, A.; Romeu, J.
Abstract: This paper proposes a temporal sampling strategy that increases the accuracy of long-term noise level estimation and allows to establish the estimation error according to the number of sampled days. Days of the week are stratified into working days and weekend days. This research shows how to use measurements of L e q on working days to estimate the corresponding values for weekend days. This is possible because working days have higher noise levels and less variability than weekend days. The improvement in accuracy allows for a reduction in the number of required sampled days compared to taking samples randomly, which would help to reduce the uncertainty in environmental noise assessment. As a reference, to obtain a 90% confidence interval of ± 1 dB for L d a y, the proposed sampling strategy reduces the required measurement days by more than 38%. For L D E N, the reduction is close to 18% of the total number of days. The proposed strategy could be adapted to different environments by simply changing a few parameters. Graphical abstract: Image 1 Highlights: Improvement in the estimation of long term noise levels. Two statistically different strata were found partitioning weekends and workdays. Lower variability and higher noise levels on weekdays. Reduction up to 38% of the required measurement days to equal random sampling accuracy. Night period stratification affected by leisure activities.