Corresponding author:Department of Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran , kianysadr@gmail.com
Abstract: (3227 Views)
Background: Finding the best location for the airport reduces the negative effects of construction and its activity on the environment. This study aimed to evaluate the establishment of the airports (Mehrabad and Imam Khomeini airports) in Tehran province through integration of multi-criteria decision making (MCDM) methods and noise pollution modeling software. Methods: The criteria for zoning the airports were determined using Delphi method, and then, were weighed using analytic network process (ANP). One of the criteria was noise pollution. The computer aided noise abatement (CadnaA) software was used to map the noise level at the airports. The geographic information system (GIS) software and weighted overlay method were used to zone Tehran province for construction of the airports. The percentage of voice annoyance was defined according to the questionnaire provided by the International Commission on the Biological Effects of Noise (ICBEN). Results: Prioritization between the selected criteria using ANP and TOPSIS showed that the most important criteria are the land use (0.069) and the distance from the city (0.0598), respectively. The highest percentage of highly annoyed (%HA) persons was reported at both airports at Lden levels above 70 dB. Conclusion: According to the results of this study, the location of Mehrabad and Imam Khomeini airports is considered 60% and 18% inappropriate, respectively. The results introduce a set of criteria that determines compatibility rate of different activities around the airports based on the noise levels. Finally, it is recommended to study the correlation between aircraft noise pollution indicators in other airports of Iran and design a local model for the whole country.
Kiani Sadr M, Melhosseini Darani K, Golkarian H, Arefian A. Implement of zoning in order to evaluate the establishment of the airports using integrating MCDM methods and noise pollution modeling softwares. Environ. Health Eng. Manag. 2020; 7 (2) :97-105 URL: http://ehemj.com/article-1-623-en.html