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      Annoyance from transportation noise: relationships with exposure metrics DNL and DENL and their confidence intervals.

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      Environmental Health Perspectives

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          Abstract

          We present a model of the distribution of noise annoyance with the mean varying as a function of the noise exposure. Day-night level (DNL) and day-evening-night level (DENL) were used as noise descriptors. Because the entire annoyance distribution has been modeled, any annoyance measure that summarizes this distribution can be calculated from the model. We fitted the model to data from noise annoyance studies for aircraft, road traffic, and railways separately. Polynomial approximations of relationships implied by the model for the combinations of the following exposure and annoyance measures are presented: DNL or DENL, and percentage "highly annoyed" (cutoff at 72 on a scale of 0-100), percentage "annoyed" (cutoff at 50 on a scale of 0-100), or percentage (at least) "a little annoyed" (cutoff at 28 on a scale of 0-100). These approximations are very good, and they are easier to use for practical calculations than the model itself, because the model involves a normal distribution. Our results are based on the same data set that was used earlier to establish relationships between DNL and percentage highly annoyed. In this paper we provide better estimates of the confidence intervals due to the improved model of the relationship between annoyance and noise exposure. Moreover, relationships using descriptors other than DNL and percentage highly annoyed, which are presented here, have not been established earlier on the basis of a large dataset.

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          Author and article information

          Journal
          Environ Health Perspect
          Environmental Health Perspectives
          0091-6765
          April 2001
          : 109
          : 4
          : 409-416
          Affiliations
          TNO-PG, Leiden, The Netherlands. hme.miedema@pg.tno.nl
          Article
          sc271_5_1835
          10.1289/ehp.01109409
          1240282
          11335190
          8cdbcc8a-9ab7-4cf0-b5eb-5b05f04d24e4
          History
          Categories
          Research Article

          Public health
          Public health

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