Noise pollution is a widespread environmental problem in cities, with significant adverse effects on public health. In the city of Mashhad, which with 29 million visitors a year is the greatest hub of religious tourism in Iran, the extremely high noise pollution is turning into a health risk factor for citizens as well as visitors. Since the existing standard models cannot provide an accurate forecast of noise pollution in the central part of Mashhad because of its unique traffic conditions, this study first developed a model for predicting noise pollution in arterial roads around the city’s centrally-located main attraction, i.e. Imam Reza Shrine, and then created a noise map of the area. For this purpose, a sound level meter was used to collect noise pollution data from streets and the measurements were used to obtain the equivalent 10-minute sound pressure level. During these measurements, spatial-traffic data including the number of light vehicles, motorcycles, buses, and trucks, average traffic speed, road width, distance, temperature, etc. were also collected. The collected data were then used to develop a noise pollution model using the multiple linear regression method. The results showed that, as the existing standard models predict, noise pollution decreases with the distance from the source and increases with the increase in the number of vehicles, road width, and percentage of heavy vehicles. It was also found that noise pollution increases as traffic speed decreases because vehicles moving slowly in queues brake and accelerate more frequently. The modeling results showed that noise pollution is most greatly affected by distance (with 42% relative importance) and average traffic speed (with 26% relative importance). The developed model was then used to draw a noise pollution map of the study area based on the traffic data related to the morning peak hour (7–8 am). The noise mapping results showed that the average noise pollution of the area during the morning peak hour is 14 dB higher than the level recommended in the regulations and falls in a range that makes it a health risk factor.

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