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Relationship between green space-related morphology and noise pollution

机译:绿地形态与噪声污染的关系

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Green spaces have been proved to have a positive effect on traffic noise pollution in the local scale; however their effects have not been explored on the urban level. This paper investigates the effects of green space-related parameters from a land cover viewpoint on traffic noise pollution in order to understand to what extent greener cities can also be quieter. A triple level analysis was conducted in the agglomeration, urban and kernel level including various case study cities across Europe. The green space parameters were calculated based on land cover data available in a European scale, while traffic noise data were extracted from online noise maps and configured in noise indices. In the first level 25 agglomerations were investigated, six of which were further analyzed in the urban and kernel levels. It was found that the effect of green spaces on traffic noise pollution varies according to the scale of analysis. In the agglomeration level, there was no significant difference in the cluster of the higher green space index and the percentage of people exposed in the lowest (55-59 dB(A)) or the highest noise band of more than 70 dB(A). In the urban level it was found that lower noise levels can possibly be achieved in cities with a higher extent of porosity and green space coverage. Finally, in the kernel level a Geographically Weighted Regression (GWR) analysis was conducted for the identification of correlations between noise and green. Strong correlations were identified between 60% and 79%, while a further cluster analysis combined with land cover data revealed that lower noise levels were detected in the cluster with higher green space coverage. At last, all cities were ranked according to the calculated noise index. (C) 2016 Elsevier Ltd. All rights reserved.
机译:事实证明,绿色空间对当地的交通噪声污染具有积极作用;但是,尚未在城市一级探讨其影响。本文从土地覆盖的角度研究了与绿色空间相关的参数对交通噪声污染的影响,以了解绿色城市还能在多大程度上安静。在集聚,城市和核心级别(包括整个欧洲的各种案例研究城市)进行了三级分析。绿地参数是根据欧洲规模的可用土地覆盖数据计算得出的,而交通噪声数据则是从在线噪声图提取并在噪声指数中进行配置的。在第一层中,调查了25个集聚区,其中有六个在城市和核心区级中作了进一步分析。结果发现,绿色空间对交通噪声污染的影响随分析规模的变化而变化。在集聚水平上,较高的绿色空间指数集群和处于最低噪声频带(55-59 dB(A))或最高噪声频带超过70 dB(A)的人群所占百分比没有显着差异。 。在城市一级,发现在孔隙度和绿地覆盖率较高的城市中,可以实现较低的噪音水平。最后,在内核级别进行了地理加权回归(GWR)分析,以识别噪声和绿色之间的相关性。在60%和79%之间确定了很强的相关性,而进一步的聚类分析与土地覆盖数据相结合则表明,在具有较高绿地覆盖率的聚类中检测到较低的噪声水平。最后,根据计算出的噪声指数对所有城市进行排名。 (C)2016 Elsevier Ltd.保留所有权利。

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