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Abstract
Abstract. Noise pollution is one of the most influential factors in the degradation of the quality of life in cities. The problem is that in recent years, the level of urban noise impact on the environment and public health has increased by almost 25% globally. Traffic plays a dominant role in urban noise generation. Natural vegetation, provided it is large enough and dense enough, is an effective means of combating traffic noise. That is, among the other benefits – ecosystem services (ES) – that urban residents receive from green areas, reducing road noise levels is one of the leading ones. However, there is currently a lack of methods and technologies that are easy to use and easy to determine the volume of ES. Thus, the development of a methodology for assessing ecosystem services to reduce traffic noise is the main purpose of this paper. The materials used for the study were open cartographic data on: green areas and roads extracted from the OpenStreetMap database; vegetation of the study area and its redistribution within green areas extracted from ESA WorldCover and Copernicus Land Cover products.
The paper develops a methodology for assessing ecosystem services to reduce the level of traffic noise, based on determining the efficiency of the relevant function. A geodatabase (DB) has been created to correspond to the defined indicators. The calculated parameters were the average noise levels (Рemission), distance (D) from motorways and noise reduction coefficient (Inoise_reduction). In the process of GIS modelling, were determined: characteristics of the primary pollution field (Cont_noise), the «residual» noise level in the green zone (Noise) and its effectiveness in function (Еnoise_reduction). Efficiency indicators, based on the Harrington’s desirability function, allowed to calculate the volume of provision of the ES for reducing motorway noise (ESnoise_reduction). According to this algorithm, all green areas that are able to reduce the initial noise levels to safe or close to safe levels are provided with the maximum volumes of ES.
The assessment carried out using this methodology can be a useful tool in urban planning decisions, as it allows to identify green areas that need priority action to improve their ability to reduce road noise.
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