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G_(den): An indicator for European noise maps comparison and to support action plans

机译:G_(den):欧洲噪声图比较和支持行动计划的指标

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Ten years after the approval of the Environmental Noise Directive 2002/49/EC (END) a large experience have been acquired to develop noise maps and action plans: the Noise Observation and Information Service for Europe maintained by the European Environment Agency (EEA) on behalf of the European Commission contains all data delivered in accordance with the END by Members States within the first round of implementation of the END. This large database should be useful to evaluate the pollution of Europe and to guide policy makers to establish best practices. However, local procedures and national methods do not permit a direct comparison of data reported. A comparison within agglomerations in EU is here carried out in order to find suitable indicators to identify most polluted cities despite different methods used. Critical and quiet areas have been assessed in action plans, but national laws and requirements are various, as different indicators used for their identification. The analysis was performed on noise exposure classes distribution, grouping them together using G_(den) and G_(night) indicators to offer a new tool for presenting noise maps of the cities to the public permitting their comparison and for drawing detailed action plans. Strong relationship between these indicators and highly annoyed and highly sleep-disturbed people percentages are obtained. Furthermore, a comparison between G_(den) and Qcity Noise Scoring for local hot spot identification is carried out for the agglomeration of Pisa, where different transportation noise sources are present. The final goal is to define faster methods for suitable indicators calculation in hot spot identifications.
机译:在环境噪声指令2002/49 / EC(END)批准十年后,已经积累了丰富的经验来制定噪声图和行动计划:欧洲环境署(EEA)维护的欧洲噪声观测和信息服务中心代表欧洲委员会的国家/地区包含在END实施的第一轮中成员国根据END提交的所有数据。这个庞大的数据库应有助于评估欧洲的污染状况,并指导政策制定者建立最佳实践。但是,当地程序和国家方法不允许直接比较报告的数据。为了找到合适的指标来识别大多数受污染的城市,尽管使用了不同的方法,此处在欧盟内部进行了比较。行动计划已经评估了关键和安静地区,但是国家法律和要求各不相同,因为用于识别它们的指标不同。对噪声暴露等级分布进行了分析,并使用G_(den)和G_(night)指标将它们分组在一起,从而提供了一种新工具,可向公众展示城市的噪声图,以进行比较并制定详细的行动计划。这些指标与高度烦恼和高度睡眠困扰的人之间的关系密切。此外,对比萨的集聚进行了G_(den)和Qcity噪声评分之间的比较,以进行局部热点识别,其中存在不同的运输噪声源。最终目标是为热点识别中的合适指标计算定义更快的方法。

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