# Traffic Noise Reduction Strategy in a Large City and an Analysis of Its Effect
###### Abstract
Moreover, the flight altitude also showed a noticeable influence on the property prices. [PERSON] et al. [22] used the hedonic method to find the correlations between house prices and traffic noise in St. Paul, Minnesota, United States. They commented that the impact of traffic noise on house prices was obvious, and a precise estimation of the impact of traffic noise could be helpful for the cost of efficient mitigation projects. Similar research was conducted by [PERSON] et al. [23]. They investigated the impact of aircraft noise on property prices from a database that included the transaction prices for 1328 apartments and 438 single-family houses from 2010 to 2015 in Poznan, Poland. They also found that the property prices were negatively related to the aircraft noise level. The depreciations of the index value due to noise were 0.87% and 0.57% for single-family houses and apartments, respectively. In order to assess the levels of noise emitted in an urban area, noise mapping is widely accepted as one of the most meaningful and popular approaches in the research community [24; 25; 26; 27; 28]. A precise noise mapping can provide the detailed spatial noise level distribution of a certain area with multiple noise sources and temporal intervals. With these advantages, noise mapping can be applied as the first step toward the calculation of populations exposed to the noise levels in a specific area; then, some applicable noise mitigation strategies, such as noise barriers, vegetation, and landscing, can be proposed to reduce the impact of noise. Over recent years, numerous efforts were made to develop traffic noise maps through numerical modeling based on traffic flow parameters and a geographic information system (GIS) [25]. [PERSON] et al. [29] proposed a method for three-dimensional (3D) road traffic noise mapping with unstructured surface meshes of buildings and roads. This method enabled 3D noise mapping with realistic buildings, road models, and traffic information. [PERSON] [30] compared the accuracy of the noise maps created via the radial basis function (RBF), ordinary kriging (OK), and inverse distance weighting (IDW) methods. The RBF method was found to be the most accurate among the tested methods. [PERSON] [31] produced a noise map of selected sections of the Egnatia motorway together with an extended traffic noise measurement campaign, and the population under noise exposure was then calculated according to the noise map. A large population was found to live under relatively high noise levels, indicating the necessity of traffic noise monitoring in residential areas. [PERSON] and [PERSON] [32] assessed the noise pollution conditions in Surat city, India through noise mapping by using two inbuilt noise propagation models of SoundPLAN. Similarly, [PERSON] et al. [33] constructed noise maps near the main roads that passed through densely populated residential areas in North India using the SoundPLAN and MapInfo Professional software, and a comparison between the 2D and 3D models was reported and analyzed. [PERSON] and [PERSON] [34] evaluated the railway noise in a municipality of Brazil based on noise measurements and strategic noise mapping (SNM). The results showed that one-quarter of the population in the study area was exposed to noise that exceeded the level of the limit recommended by the WorldHealth Organization (WHO). Strategies for managing exposure to rail noise, including noise barriers, were proposed according to their analysis. As mentioned before, it has been acknowledged that there are still large populations living in unhealthy sound environments in urban areas all over the world. The impact of noise has not only undermined the health of individuals, but has also lead to the depreciation of values of the affected private properties. Therefore, it is essential to take traffic noise issues into account in urban planning, particularly for urban renewal plans in old cities, which usually have high densities in terms of population and residential buildings.