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Hierarchal Assessment of Noise Pollution in Urban Areas - a Case Study Publisher



Abbaspour M1 ; Karimi E2 ; Nassiri P3 ; Monazzam MR4 ; Taghavi L2
Authors
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Authors Affiliations
  1. 1. School of Mechanical Engineering, Sharif University of Technology, P. O. Box 11155-8639, Tehran, Iran
  2. 2. Department of Environment and Energy, Science and Research Branch, Islamic Azad University, Tehran, Iran
  3. 3. Department of Occupational Health School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Department of Occupational Hygiene, School of Public Health and Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran

Source: Transportation Research Part D: Transport and Environment Published:2015


Abstract

Noise pollution in urban areas has many harmful effects on the citizens. There are varieties of noise generation sources of which the traffic noise could be a major source. The point which is perhaps less noticed is that sound level is not the only parameter to indicate the extent and intensity of noise pollution. Situation of urban land uses, distribution of population centers and types of passages can deeply affect the concern on this environmental issue but not with a similar ratio. This article presents an overlaying technique to define noise prone areas using all different factors involved. A case study was carried out in the District 14 of Tehran Metropolitan City where there are busy streets and highways. For this purpose, the share of each criterion in noise pollution intensity was determined using Analytical Hierarchy Process (AHP). Afterwards, the map layers were overlaid based upon the relative importance of the criteria to get the final map on which the noise prone areas are specified. The developed method could be used as a tool for indirect estimation of noise pollution by which instead of direct measurement of the equivalent sound level, it would be possible to predict noise susceptible areas considering the most important influential factors. © 2014.
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