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城市铁路环境噪声评估的几种方法。

Selected Approaches to the Assessment of Environmental Noise from Railways in Urban Areas.

机构信息

Department of Physics, Electrical Engineering and Applied Mechanics, Faculty of Wood Sciences and Technology, Technical University in Zvolen, T.G. Masaryka 24, 96001 Zvolen, Slovakia.

Forest Research Institute, National Forest Centre, T.G. Masaryka 22, 96001 Zvolen, Slovakia.

出版信息

Int J Environ Res Public Health. 2021 Jul 2;18(13):7086. doi: 10.3390/ijerph18137086.

DOI:10.3390/ijerph18137086
PMID:34281024
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8297324/
Abstract

Rail transport is the second most important way of transporting people and freights by land in the European Union. Rail noise affects around 12 million people in the European Union during the day and around 9 million at night. There are two possible ways to assess environmental noise: noise measurement in situ and prediction using mathematical models. The aim of the work is based on the performed measurements and selected noise predictions to evaluate the accuracy of the prediction models and assess their sensitivity to various aspects. Two measuring points in the Banská Bystrica Self-Governing Region, within Slovakia, were selected for measurement, which is characterized by increased mobility of the population. For prediction, the two methodologies were selected (Schall 03 and Methodical instructions for the calculation of sound pressure level from transport). The results show that the Schall 03 method is sensitive to the measurement location (the value reaches half of the significance level) and to the location-period interaction. The second prediction method is sensitive to systematic error (absolute term) and, such as Schall 03, to the location-period interaction. This method systematically overestimates the results. Results showed greater accuracy of both prediction models compared to the measured noise values than the results of the authors in other countries and conditions.

摘要

铁路运输是欧盟内陆地第二大人流和货运的重要运输方式。铁路噪音在白天影响着欧盟约 1200 万人,晚上则影响约 900 万人。评估环境噪声有两种可能的方法:现场噪声测量和使用数学模型进行预测。这项工作的目的是基于所进行的测量和选定的噪声预测,评估预测模型的准确性,并评估其对各种方面的敏感性。在斯洛伐克的班斯卡·比斯特里察自治地区选择了两个测量点进行测量,该地区的人口流动性较大。对于预测,选择了两种方法(Schall 03 和交通噪声声压级计算方法说明)。结果表明,Schall 03 方法对测量位置(数值达到显著性水平的一半)和位置-时间交互作用敏感。第二种预测方法对系统误差(绝对值)敏感,并且与 Schall 03 一样,对位置-时间交互作用敏感。该方法系统地高估了结果。与其他国家和条件下的作者的结果相比,这两种预测模型的结果都显示出了更高的准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/b50b00dabe06/ijerph-18-07086-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/67c5aef442c2/ijerph-18-07086-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/c175c5235861/ijerph-18-07086-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/fab814c0deda/ijerph-18-07086-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/f3bedb5ad5c9/ijerph-18-07086-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/bc6da61b5f16/ijerph-18-07086-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/678cf1a9f543/ijerph-18-07086-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/36f22792f331/ijerph-18-07086-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/752dd208f3b5/ijerph-18-07086-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/e1b40d167079/ijerph-18-07086-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/b50b00dabe06/ijerph-18-07086-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/67c5aef442c2/ijerph-18-07086-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/c175c5235861/ijerph-18-07086-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/fab814c0deda/ijerph-18-07086-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/f3bedb5ad5c9/ijerph-18-07086-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/bc6da61b5f16/ijerph-18-07086-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/678cf1a9f543/ijerph-18-07086-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/36f22792f331/ijerph-18-07086-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/752dd208f3b5/ijerph-18-07086-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/e1b40d167079/ijerph-18-07086-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1acd/8297324/b50b00dabe06/ijerph-18-07086-g010.jpg

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Framework to manage railway noise exposure in Brazil based on field measurements and strategic noise mapping at the local level.
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