Volume 7, Issue 1 (7-2018)                   2018, 7(1): 13-25 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Shayesteh K, Gharibi S. Principal Components Analysis of Main Factors Affecting Noise Pollution in Main Road of Golestan National Park . Iranian Journal of Applied Ecology 2018; 7 (1) :13-25
URL: http://ijae.iut.ac.ir/article-1-822-en.html
Malayer Univ., Malayer, Iran.
Abstract:   (6230 Views)
Traffic noise pollution is a serious threat to wildlife species, resulting in isolating and reducing the population. The Asian Highway of Tehran-Mashhad, from which a 26.51 km long part is located inside Golestan National Park, is the main source of noise disturbance inside the area. The purpose of this study was to determine the most important criteria for noise pollution of this road; in order to achieve this goal, the Principle Components Analysis method was used. To assess the sound emissions and to study the parameters affecting it, desk studies and field visits were used in a 250-meter buffer zone. A total of 16 variables in three different categories of traffic parameters, geometry parameters and environmental parameters were extracted, andthe circular plots were measured at a radius of 25 m  for 15 minutes. The results of PCA showed that six main factors including the speed of light vehicles, the humidity,  the altitude above sea level, the number of light vehicles, the distance from the road and the plot slope could justify a total of 72.396 % of the variance of the data. Based on the results, management measures could  be taken to reduce the noise pollution based on the extracted criteria, and the noise pollution could be managed more efficiently by spending less time and money.
 
 
Full-Text [PDF 686 kb]   (3124 Downloads)    
Type of Study: Research | Subject: General

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Iranian Journal of Applied Ecology

Designed & Developed by : Yektaweb