Iranian Journal of

Background and Objective: The aim of  noise control in a community is to improve its management in the community, because the traffic noise can affect neighboring residential areas. Well-planned noise management can eliminate this major and harmful component issue, which is one of the stresses of urban life on human health. However, before planning to decrease urban noise, it is necessary to determine the very noisy areas in a given city. Therefore, the objective of this study was to measure the main noise indices at the noisy areas of Zanjan City, Iran.

Materials and Methods: This study was performed in the central area of Zanjan City, with heavy traffic. For this purpose, the equivalent sound level (L_eq), the day-night sound level (L_dn), the day-evening-night sound level (L_den), the noise pollution level (NP) and the traffic noise index (TNI) were measured in 19 stations in the first half (winter and spring) of 2012. The measurements were conducted in the main streets of this area as recommended by EPA guidelines and finally the results obtained were mapped using the ArcGIS (Ver. 10.2) software. 

Results: the noise maps in GIS showed clearly the variations of L_eq, L_dn, and L_den indices in the study field area. Moreover, it was found that the hourly variations of L_eq, L_dn and L_den in stations are completely function of population movements and therefore traffic loads in the Zanjan city center. In addition, the extent of violation of traffic noise level from the ambient noise standard was estimated by L_den at 100% stations (greater than 55 dB). The TNI values at 67  and 100% stations  were more than 74 dB (A), but  in the evenings the TNI values at  100% of stations  were more than 74 dB (A). The NP values at 78% sampling stations were more than 80 dB  implying  traffic noise was annoying in the most stations and times.

Conclusion: Using noise maps, NP and TNI indices can help intelligent traffic control planning, because the noise maps can be used to represent the movement of people in different times and parts of a city.