Volume 20, Issue 3 (2020)                   MCEJ 2020, 20(3): 69-78 | Back to browse issues page

XML Persian Abstract Print


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

Eskandari R, Rassafi A A, Behnood H R. Modelling noise in an urban intersection (A case study). MCEJ 2020; 20 (3) :69-78
URL: http://mcej.modares.ac.ir/article-16-35615-en.html
1- Imam Khomeini International University
2- Imam Khomeini International University , rasafi@eng.ikiu.ac.ir
Abstract:   (1868 Views)
The development of technology along with the development of facilities for modern and comfortable life brings some disadvantages as well as environmental problems, it consists of five categories of air pollution, water, soil, heat and noise pollution. In the meantime, the issue of noise pollution in cities is a global problem in most countries, In most developing countries, they are also striving for rapid industrial development to improve the country's economic and social conditions. Of course, In the absence of proper control, this growth along with improving the quality of life in these countries will lead to environmental pollution, including the most important of which is noise pollution, in the absence of proper control. Noise pollution is of particular importance due to the potential for physiological and psychological effects on humans. There has been significant growth in noise pollution from man-made sources over the past 100 years, which now doubles every 10 years. Therefore, evaluation of problem and functional planning to control noise pollution and its harmful effects is an essential issue for the community. Noise pollution that is different from other types of pollution due to its source and emission characteristics. Sources of noise pollution in urban areas can be divided into two groups: Fixed sources and moving sources. Fixed sources include: industrial, construction and demolition, commercial, local and recreational. Moving resources include ground and air transportation. In urban areas, the engine and exhaust system of cars, light trucks, buses and motorcycles is an important source of noise pollution, that have major environmental impacts. Traffic noise pollution is the most important source of environmental noise pollution in cities. The main objective of the paper is to find the relationships between noise and traffic characteristics, and also to examine the impact of each one separately, so that we can find out the importance of each variable in noise pollution we will find suitable solutions to reduce the noise pollution. In this study, which was carried out at one of the important intersections of Qazvin, data including equivalent sound level, the volume of vehicles by type, traffic light timing at picked up time, distance from picked up point to intersection center, number of beeps at the time of picked up which is heard, that data was estimated at 94 points, Points were located at 10 m distance on the edge of the street and If there was an open space, points were expanded, and there were two picked up for each point .The results of modeling showed that the most important variables affecting the sound equivalent level includes the volume of vehicles, especially heavy and semi-heavy vehicles (with the impacts of 0.025, 0.125, 0.526, 0.489 for cars, motors, semi-heavy vehicles and trucks, respectively,) the green time of the approach 1 and the number horns honked in this period (with the impact of 0.05 dB per second, and .08 dB per honk, respectively), are the variables that influence the equivalent sound level at this intersection.
Full-Text [PDF 483 kb]   (1160 Downloads)    
Article Type: Original Research | Subject: Transportation Management
Received: 2019/08/12 | Accepted: 2020/06/10 | Published: 2020/10/31

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.