首页> 外文会议>International Congress and Exposition on Noise Control Engineering >Cities with a Positive Evolution on Noise Action Plans Are Requiring a More Accurate Assessment to Advance Towards New Goals. Two Examples: Donostia-San Sebastián and Vitoria-Gasteiz
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Cities with a Positive Evolution on Noise Action Plans Are Requiring a More Accurate Assessment to Advance Towards New Goals. Two Examples: Donostia-San Sebastián and Vitoria-Gasteiz

机译:在噪声行动计划方面取得积极进展的城市,要求进行更准确的评估以朝着新目标迈进。两个例子:Donostia-SanSebastián和Vitoria-Gasteiz

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This paper shows the positive evolution during the last 15 years of the noise levels and the population noise exposure for two cities: Donostia-San Sebastian and Vitoria-Gasteiz, located in the Basque Country (Spain). Both cities have a long experience on environmental noise assessment, applying comparable and consistent assessment methods based on noise level calculation at real height on building facade, together with effective action plans on traffic management and mobility. This progressive improvement got, in that period, a reduction of 30% of inhabitants exposed over 55 dB(A) for Ln, reaching values that nowadays are recommending to look at new more ambitious aims for the next action plan, starting to assess population exposed to noise levels according with a calm and healthy city. Having the advantage of detailed statistics population exposition for both cities from at least three noise maps during the last 15 years, it is able to analyse the evolution to support new goals on noise management, and to consider how it will affect to the input data and to the working methodology with calculation models, because accuracy will become more relevant to get representative results.
机译:本文显示了位于巴斯克地区(西班牙)的Donostia-San Sebastian和Vitoria-Gasteiz这两个城市在过去15年中的噪声水平和人口噪声暴露的正向变化。这两个城市在环境噪声评估方面都具有丰富的经验,它们基于可比较且一致的评估方法,这些方法基于建筑物立面上实际高度的噪声水平计算,以及有效的交通管理和交通行动计划。在此期间,这种进步得到了改善,使暴露在Ln超过55 dB(A)的居民减少了30%,达到了如今建议针对下一个行动计划研究新的雄心勃勃的目标的价值,从而开始评估暴露的人口达到一个安静健康的城市的噪音水平。在过去15年中,利用至少三个噪声图对两个城市进行详细统计的人口博览会的优势,它能够分析演变以支持噪声管理的新目标,并考虑它将如何影响输入数据和对于具有计算模型的工作方法来说,因为准确性将变得与获取代表性结果更加相关。

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