Statistical Modeling for Traffic Noise: The Case of Kirkuk City

Abstract

The auditory system can suffer from exposure to loud noise and human health can be affected. Traffic noise is a primary contributor to noise pollution. To measure the noise levels, 3 variables were examined at 25 locations. It was found that the main factors that determine the increase in noise level are traffic volume, vehicle speed, and road functional class. The data have been taken during three different periods per day so that they represent and cover the traffic noise of the city during heavy traffic flow conditions. Analysis of traffic noise prediction was conducted using a simple linear regression model to accurately predict the equivalent continuous sound level. The difference between the predicted and the measured noise shows that the model's accuracy is 93.93%. The results show the effectiveness of the suggested method and confirm its applicability in developing mitigation plans for both existing and future roadways. To test the effectiveness of the suggested method, the selected location of different road functional classifications of Kirkuk city in Iraq was studied. It was noticed that in all the selected sites, the noise level was observed to be above the permissible noise standard of the World Health Organization (WHO).