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1.
公交车已成为当前北京市道路交通噪声的主要束源之一,针对公交车声源模型缺乏而沿用大型车声源模型所致的噪声预测误差问题,在北京市选取了两类常见公交车进行了537辆车的单车通过噪声测试,在无效数据剔除和背景噪声修正后,利用回归分析法获得了北京市公交车声源模型,通过与现有《公路建设项目环境影响评价规范》中大型车声源模型的比较,显示出建立北京市公交车噪声声源模型的必要性。基于《公路建设项目环境影响评价规范》中的道路交通噪声预测方法,提出了符合北京市实际情况的道路交通噪声预测模型。  相似文献   

2.
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   

3.
城市道路交通噪声分布模拟研究   总被引:3,自引:0,他引:3  
通过对梅州市中心城区7条道路的噪声监测,分析了中心城区道路的噪声污染水平。采用道路交通噪声预测模型,以实测交通流数据对中心城区的噪声污染进行模拟和减噪措施评估。结果表明,采用限速措施和安装声屏障措施均有降低噪声污染的效果,为管理部门防治噪声污染提供了参考。  相似文献   

4.
利用噪声自动监测系统中33个道路交通站点的数据,分析了北京市实行黄标车禁行措施后道路交通噪声昼、夜间均值的总体变化趋势.在计算夜间噪声下降量的基础上归纳了噪声降幅大的道路等级,进一步分析了噪声改善最大的时间段,并在结论的基础上为决策者提出了相应的建议.  相似文献   

5.
为科学全面地开展城市道路交通噪声影响评估,更精确地服务道路交通噪声污染治理工作,选取南京市具有代表性的道路交通干线,采用手工监测和自动连续监测的方法,进行不同路段噪声污染程度及其随时间、空间变化规律的研究。结果表明,地面快速路段、高架路段以及衔接路段两侧噪声敏感建筑物受道路交通噪声影响较大,夜间均超标;相邻区域要达到2类声环境功能区昼间标准限值要求,需距离地面快速路慢车道约45 m,距离高架路段慢车道约92 m;要达到2类声环境功能区夜间标准限值要求,需距离地面快速路慢车道约175 m,距离高架路段慢车道约172 m;敏感建筑物所受噪声影响随楼层高度升高而增大,同时噪声影响情况与道路两侧建筑物密度、道路车辆行驶速度有关。建议严格道路及噪声敏感建筑物规划控制,采取阻断传声路径、受声建筑物强化保护等措施控制噪声影响。  相似文献   

6.
高架桥-地面复合型道路交通噪声的分析   总被引:4,自引:0,他引:4  
监测了兰州市马家坡附近一处高架桥-地面复合型交通道路的噪声,分析了这种复合型道路交通噪声的形成及分布,进行了这种立体式交通结构声环境的分析。  相似文献   

7.
公交车站对交通噪声的影响分析   总被引:1,自引:0,他引:1  
首先根据公交车的运行特性提出了公交车在各行驶阶段的噪声计算方法并采用能量叠加的方法建立了公交车站附近交通噪声预测模型.然后对广州市新港西路交通噪声的实测结果与模型计算结果进行了比较,验证了该预测模型的正确性.最后分析了公交车站附近交通噪声的影响因素,通过对公交车站附近的交通噪声和远离公交车站的交通噪声的比较,得到公交车站附近交通噪声明显增大的结论.  相似文献   

8.
高原机场飞机架次较少,机型单一,飞行周期稳定,以及高原特殊的环境特征,有时会导致现场实际噪声监测数据无效。应用综合噪声模型(INM)软件对青海玉树机场飞机噪声进行计算,其结果与监测结果比较显示,计算值和监测值误差在±6 d B的范围以内。探讨提出采用飞机噪声计算模式,可以为高原机场飞机噪声管理提供可靠技术支撑。  相似文献   

9.
浅析新疆城市声环境现状与对策   总被引:1,自引:0,他引:1  
研究了新疆近五年来的城市声环境变化趋势,并对城市噪声污染现状进行综合分析评价,提出相关的治理对策与建议.从区域环境噪声状况看,噪声值呈下降趋势;从声源强度看,对城市声环境冲击最大的是交通噪声源;从道路交通噪声状况看,近五年交通噪声污染呈逐年下降趋势,但全区各年度均有超标路段,全区城市道路交通噪声仍存在污染.因此,整治城市噪声污染应贯彻"预防为主、防治结合"的方针,综合利用科技、法律手段来改善城市声环境.  相似文献   

10.
环境噪声监测自动化是环境噪声监测发展的必然趋势。该文探讨了道路交通噪声自动监测系统的组成以及在相应的环保宣传方面的应用。  相似文献   

11.
The City of Amman, Jordan, has been subjected to persistent increase in road traffic due to overall increase in prosperity, fast development and expansion of economy, travel and tourism. This study investigates traffic noise pollution in Amman. Road traffic noise index L 10(1 h) was measured at 28 locations that cover most of the City of Amman. Noise measurements were carried out at these 28 locations two times a day for a period of one hour during the early morning and early evening rush hours, in the presence and absence of a barrier. The Calculation of Road Traffic Noise (CRTN) prediction model was employed to predict noise levels at the locations chosen for the study. Data required for the model include traffic volume, speed, percentage of heavy vehicles, road surface, gradient, obstructions, distance, noise path, intervening ground, effect of shielding, and angle of view. The results of the investigation showed that the minimum and the maximum noise levels are 46 dB(A) and 81 dB(A) during day-time and 58 dB(A) and 71 dB(A) during night-time. The measured noise level exceeded the 62 dB(A) acceptable limit at most of the locations. The CTRN prediction model was successful in predicting noise levels at most of the locations chosen for this investigation, with more accurate predictions for night-time measurements.  相似文献   

12.
Roads may act as barriers, negatively influencing the movement of animals, thereby causing disruption in landscapes. Roads cause habitat loss and fragmentation not only through their physical occupation, but also through traffic noise. The aim of this study is to provide a method to quantify the habitat degradation including habitat loss and fragmentation due to road traffic noise and to compare it with those of road land-take. Two types of fragmentation effects are determined: structural fragmentation (based on road land-take only), and functional fragmentation (noise effect zone fragmentation, buffer using a threshold of 40 dB). Noise propagation for roads with a traffic volume of more than 1000 vehicles per day was simulated by Calculation of Road Traffic Noise (CRTN) model. Habitat loss and fragmentation through land-take and noise effect zone were calculated and compared in Zagros Mountains in western Iran. The study area is characterized by three main habitat types (oak forest, scattered woodland and temperate grassland) which host endangered and protected wildlife species. Due to topographic conditions, land cover type, and the traffic volume in the region, the noise effect zone ranged from 50 to 2000 m which covers 18.3% (i.e. 516,929.95 ha) of the total study area. The results showed that the habitat loss due to noise effect zone is dramatically higher than that due to road land-take only (35% versus 1.04% of the total area). Temperate grasslands lost the highest proportion of the original area by both land-take and noise effect zone, but most area was lost in scattered woodland as compared to the other two habitat types. The results showed that considering the noise effect zone for habitat fragmentation resulted in an increase of 25.8% of the area affected (316,810 ha) as compared to using the land-take only (555,874 ha vs. 239,064 ha, respectively). The results revealed that the degree of habitat fragmentation is increasing by considering the noise effect zone. We conclude that, although the roads are breaking apart the patches by land-take, road noise not only dissects habitat patches but takes much larger proportions of or even functionally eliminates entire patches.  相似文献   

13.
平原高速公路交通噪声对两侧敏感区域影响的探讨   总被引:1,自引:0,他引:1  
针对目前平原高速公路交通噪声影响两侧敏感区域的状况,环评预测结果偏差过大的问题,应用声学传播理论,对交通噪声的衰减结果进行计算,并用实测数据进行验证。其结果对平原高速公路交通噪声的管理与治理提供相应的参考。  相似文献   

14.
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   

15.
铁路专用线验收噪声监测方法探讨   总被引:1,自引:0,他引:1  
铁路专用线与国铁线路相比,具有流量低、分布不均的特点,《声环境质量标准》(GB3096—2008)中交通干线两侧的铁路不包括铁路专用线,铁路专用线两侧的噪声敏感点应该执行相应功能区噪声标准,与铁路边界的距离无关,以火车通过时最大噪声值与背景值比较,评价对其噪声敏感点的影响。本文通过实测数据对铁路专用线噪声监测方法提出看...  相似文献   

16.
The objective of this study is to develop an empirical traffic noise prediction model under interrupted traffic flow conditions using two analytical the approaches, the first being the acceleration lane approach and second being the deceleration approach. The urban road network of Bangalore city has been selected as the study area. Sixteen locations are chosen in major traffic junctions of the study area. The traffic noise data collected from the study locations were analyzed separately for both acceleration and deceleration lanes when vehicles leave an intersection on a green traffic light and come to a stop on red traffic light. Based on the study, a regression noise prediction model has been developed for both acceleration and deceleration lanes.  相似文献   

17.
日本道路交通噪声监测体系与借鉴   总被引:1,自引:1,他引:0  
系统介绍了日本环保部门每年在全国范围内开展的道路交通噪声普查性监测工作及评价体系,分析了中日两国监测与评价方法的异同和优缺点,提出在点位布设、评价方法、信息公开等方面的改进建议,以推进中国道路交通噪声监测工作向科学化、精细化、定量化转变。  相似文献   

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