Evaluation of traffic noise pollution using geographic information system and descriptive statistical method: a case study in Mashhad, Iran

Environ Sci Pollut Res Int. 2022 Jan 15:1-14. doi: 10.1007/s11356-022-18532-4. Online ahead of print.

Abstract

Environmental consequences and the epidemiologic results of noise pollution have chronic effects leading to widespread complications in the long run. As far as we know, there are a few studies for pollution monitoring and control systems in comparison with other environmental pollutants. One of the largest metropolitan cities located in Iran is Mashhad city as known as one of the biggest religious cities in the world. Different properties of this city including historical, industrial, and religious draw thousands of visitors to Mashhad, yearly. This fact motivates us to contribute to the concept of noise pollution in streets and sidewalks around the Holy Shrine, namely, Imam Reza. In this regard, different measurements using geographic information system (GIS) and descriptive statistical methods were conducted for our case study in Mashhad, Iran. All measurements and records were done during the peak of morning crowd (10-12 AM) and evening crowd (4-6 PM) on both sidewalks of each street around the Holy Shrine. This study showed that the pollution in the evening time span (4-6 PM) has the maximum level of noise. Among all streets in our case study in Mashhad, Iran, Tabarsi street has the most amount of noise pollution with a mean of 78 dB(A) for the mean intensity for each point, and Imam Reza street has the minimum amount of pollution with a mean of 72.75 dB(A). Our findings from the temporal perspective analysis confirm that the noise pollution peaks in the evening, when weather conditions are favorable. From the spatial perspective analysis, the most intensive noise pollution was observed around residential and accommodation land uses, which have the highest number of arterial routes towards the Holy Shrine.

Keywords: Geographic information system; Noise pollution; Statistical analysis; Traffic.