共查询到17条相似文献,搜索用时 109 毫秒
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高速公路交通噪声经验预测模式探讨 总被引:1,自引:0,他引:1
通过对浙江省内各高速公路交通噪声实测数据的分析,总结和探讨较为简便的高速公路交通噪声经验预测模式,主要讨论车流量、受声点离公路距离和噪声等效声级的相关性,为高速公路交通噪声环境影响预测与评价提供参考。 相似文献
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噪声不仅干扰人们的正常生活,严重时可以危害人的身心健康.随着交通事业的快速发展,一大批高速公路迅速建成,交通噪声污染不容忽视.对西宝高速公路沿线交通噪声进行了实地昼夜监测,结果表明交通噪声夜间超标较为严重,干扰了沿线居民的正常生活.分析了污染现状和原因,并提出了降低道路交通噪声的一些简单措施. 相似文献
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禁鸣交通嗽叭是改善交通噪声的重要措施。道路噪声测试结果表明效能噪声与鸣笛次数成正相关。交通喇叭的鸣响次数之差与鸣响前后的等效声级Leq差值的回归方程为△Leq=0.08308+0.08877A。禁鸣喇叭对降低交通噪声的显著程度随道路路面的好坏和车辆类型的不同而有一定差异。 相似文献
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公路噪声模式存在的问题与处理 总被引:1,自引:0,他引:1
采用《公路建设项目环境影响评价规范》(试行)中推荐的环境噪声影响预测模式(规范模式)和以“城市道路交通噪声预测统计模型”为基础的综合模式分别对高速公路交通噪声进行了计算,并利用实测资料对两种模式进行了检验和比较分析。指出规范模式存在着对低车流量噪声预测值偏大(约4-5dB)等问题,而综合模式可以部分弥补这些缺陷,使预测能力明显提高。 相似文献
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开封市交通噪声环境质量二级模糊综合评价 总被引:1,自引:1,他引:0
在开封市2005年交通噪声实地监测数据的基础上,运用二级模糊综合评价法,对市区交通噪声环境质量进行现状评价,评价结果为开封市交通噪声环境质量总体上昼间属于轻污染,夜间属于重度污染,夜间交通噪声环境质量明显劣于昼间。其结论符合开封市的实际情况,不仅能较好地描述开封市交通噪声环境污染的连续、渐变、模糊的特点,而且还弥补了一级模糊综合评价难以反映出小范围路段对整体环境质量贡献的不足。 相似文献
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Wang He yong 《中国环境监测》1997,(3)
新增交通干线噪声对总体交通干线噪声的影响,取决于新增交通干线在总体交通干线中的权重P及其噪声平均值与原有交通干线噪声平均值的差值ΔLx。用公式可表示为Lx=Lx原+P·ΔLx。在新增交通干线长度的权重P≤0.3的情况下,新增交通干线噪声对总体交通干线噪声影响不大,原有交通干线噪声水平基本上可以反映新增交通干线后的总体交通干线噪声水平。 相似文献
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Development of Noise Simulation Model for Stationary and Mobile Sources: A GIS-Based Approach 总被引:1,自引:0,他引:1
Asheesh Sharma Ritesh Vijay Veena K. Sardar R. A. Sohony Apurba Gupta 《Environmental Modeling and Assessment》2010,15(3):189-197
In the rapidly urbanizing country like India, the transportation sector is growing rapidly, which lead to overcrowded roads
producing air and noise pollution. Noise of a particular region is influenced by the volume of traffic on the highway, in
addition to other causative factors like existing infrastructure and industrial setup etc. In the present paper, a geographical
information system (GIS)-based noise simulation model has been developed to generate noise levels in Versova region of Mumbai,
India. The study area comprises effect of infrastructure, road network, traffic volume, and various mechanical components
like sewage pumping station and wastewater treatment facility. Various meteorological parameters and effect of land use and
land cover on noise attenuation are also considered in the model. In this way, commutative noise prediction for point as well
as mobile sources has been presented in the study. GIS-based noise simulation has been calibrated with observed noise levels
during day and night time with correlation of 0.84 and 0.74, respectively. 相似文献
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基于L-M神经网络的道路交通噪声预测研究 总被引:1,自引:1,他引:0
神经网络具有很强的预测功能.根据石家庄公路交通噪声的实测数据,利用L-M优化算法的多层神经网络预测模型进行道路交通噪声的预测,经检验,计算值与实测值接近,预测精度令人满意. 相似文献
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This paper elucidates the basic approach of determining the path coefficients and its significance in the road traffic noise
annoyance. Path model not only outline the direct effect of the traffic noise on the nearby residents but also indicate the
indirect effect via other variables. In this study seven variables were considered for determining road traffic noise annoyance.
However the same would be equally applicable for other situations like aircraft noise, rail noise, and industry noise with
the different variables. At the outset a priori path model was designed and then on the basis of the partial regression coefficient
values for the different paths, the revised path model was developed. The standardized partial regression coefficients known
as path coefficients, determine the strength of the linkage among variables. Some of the paths in the model were not statistically
significant. Revised path models were developed by deleting the insignificant paths whose values were found above 5% level.
In the revised path model, thus the direct and indirect effect due to a particular variable causing the road traffic noise
annoyance could be observed. 相似文献
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On the basis of the continuous traffic noise data observed at 142 sites distributed in 52 roads from 1989 to 2003, the characteristics of traffic noise and effect factors were analyzed through traffic noise indices, such as Lep, L10, L50, L90, TNI, and Pn. Our findings allow us to reach a number of conclusions as follows: Firstly, traffic noise pollution was serious, and its fluctuant characteristic was obvious, resulting in a great intrusion to public in Lanzhou City during last 15 years. Secondly, traffic noise made a distinction between trunk lines and secondary lines, west-east direction roads and north-south direction roads. Thirdly, spatial character and time rule of traffic noise were obvious. In addition, traffic volume, traffic composition, road condition, and traffic management were identified as the key factors influencing traffic noise in this city. 相似文献