Blog
About

  • Record: found
  • Abstract: found
  • Article: not found

A modified Nordic prediction model of road traffic noise in a Taiwanese city with significant motorcycle traffic.

Read this article at

ScienceOpenPublisherPubMed
Bookmark
      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

      Abstract

      A prediction model was developed to map road traffic noise in an area with significant motorcycle traffic in Taichung City, Taiwan. This model was modified from the Nordic prediction method by adding three types of traffic flow rates, including heavy vehicles, light vehicles, and motorcycles, as well as local traffic speeds and road characteristics to the calculating equations. The parameters that were input into the equations include traffic flow, vehicle speed, distance from the center of the road, height of the road surface, position and height of the barriers, thickness of the barriers, location of the receiver relative to the surrounding road surface or barriers, reflecting vertical surfaces, type of ground, and height of the buildings. The model was validated by comparing the measured noise levels at 42 sampling sites close to main roads with the predicted values. A significant correlation was found between the predicted and measured noise levels (Pearson correlation coefficient=0.75, p<0.001). The deviation between the predicted and measured noise levels within the range of ±3.5 A-weighted decibel (dB(A)) was 90.5%. The mean difference between the predicted and measured noise levels was 0.9±2.1 dB(A). The modified Nordic prediction model is therefore applicable to estimate the noise exposure in this urban environment in Taiwan.

      Related collections

      Author and article information

      Affiliations
      [1 ] Department of Occupational Safety and Health, College of Public Health, China Medical University, Taichung, Taiwan, ROC.
      Journal
      Sci. Total Environ.
      The Science of the total environment
      Elsevier BV
      1879-1026
      0048-9697
      Aug 15 2012
      : 432
      22750184
      S0048-9697(12)00831-5
      10.1016/j.scitotenv.2012.06.016

      Comments

      Comment on this article