Annual traffic noise levels estimation based on temporal stratification.

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 me...

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Detalles Bibliográficos
Publicado en:Journal of Environmental Management Vol. 206; pp. 1 - 10
Autores principales: Quintero, G., Balastegui, A., Romeu, J.
Formato: Artículo
Publicado: Academic Press Inc. Jan2018
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jan2018
      vid: 206
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      pub: Academic Press Inc.
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        126805755
        10.1016/j.jenvman.2017.10.008
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        atl: Annual traffic noise levels estimation based on temporal stratification.
      aug:
        au:
          Quintero, G.
          Balastegui, A.
          Romeu, J.
        affil: Laboratory of Acoustics and Mechanical Engineering (LEAM), Polytechnic University of Catalonia, Colom 11, 08222, Terrassa, Spain
      su:
        Differences
        Noise pollution
        Sampling (Process)
        Sampling (Sound)
        Noise measurement
      sug:
        subj:
          Differences
          Noise pollution
          Sampling (Process)
          Sampling (Sound)
          Noise measurement
      keyword:
        Noise assessment
        Noise mapping
        Sampling strategy
        Temporal variability
        Noise assessment
        Noise mapping
        Sampling strategy
        Temporal variability
      ab: 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.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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