快速高架复合道路近场交通噪声垂向分布

采用Cadna/A环境噪声模拟软件建立了高架复合道路的基本模型,根据6种基本模拟情况进行了声场模拟,并把模拟结果与实测结果进行对比分析。结果表明,高架道路结构本身对地面道路、高架道路分别形成的声场有明显的遮挡作用,但对高架复合道路所形成的声场遮挡作用不明显;对于高架复合道路垂向声场,在低层段地面道路的影响大于高架道路,而在高层段高架道路的影响起决定作用;高架复合道路较地面道路的垂向声场最大值增加2.5 dB(A),位置上移6m;在高架道路上设置声屏障有一定降噪效果,但在高架复合道路的上层设置声屏障降噪效果不理想。     

城市天然气加气站噪声影响分析及噪声控制技术简

城市天然气加气站位于城市道路和居民区周边。由于加气站地理位置特殊，声源复杂，与周边道路对环境的影响叠加，还要考虑通风散热等问题，噪声治理难度大。目前，国内关于城市天然气加气站的噪声控制研究的报道较少。本研究以合肥市长江西路天然气加气站为例，根据城市天然气加气站加气工艺噪声源及邻近交通噪声对周围环境进行叠加影响预测，根据预测结果和通风散热等工艺要求设计冷却塔安装进风、出风消声器和隔声罩，压缩机安装局部通风隔声罩及压缩机房东墙内安装隔声墙及通风隔声窗等措施。经检验，研究结果好于《工业企业厂界噪声排放标准（GB12348-2008）》中的2类标准的夜间50 dB（A）的标准。该研究设计技术工艺、参数先进合理，费用低且实际简单，为国内天然气加气站噪声预测及治理提供较好的示范作用。     

城市天然气加气站噪声影响分析及噪声控制技术

城市天然气加气站位于城市道路和居民区周边。由于加气站地理位置特殊,声源复杂,与周边道路对环境的影响叠加,还要考虑通风散热等问题,噪声治理难度大。目前,国内关于城市天然气加气站的噪声控制研究的报道较少。本研究以合肥市长江西路天然气加气站为例,根据城市天然气加气站加气工艺噪声源及邻近交通噪声对周围环境进行叠加影响预测,根据预测结果和通风散热等工艺要求设计冷却塔安装进风、出风消声器和隔声罩,压缩机安装局部通风隔声罩及压缩机房东墙内安装隔声墙及通风隔声窗等措施。经检验,研究结果好于《工业企业厂界噪声排放标准(GB12348-2008)》中的2类标准的夜间50 dB(A)的标准。该研究设计技术工艺、参数先进合理,费用低且实际简单,为国内天然气加气站噪声预测及治理提供较好的示范作用。     

不同声学元件在公路声屏障中的应用

通过对公路声屏障不同声学元件声学性能的比较研究,阐明了两种声学元件在治理交通噪声中的差别,指出吸声共振型声学元件将是未来公路声屏蔽的发展方向,这对于开展公路声障声学设计有较为重要的参考价值。     

变电站吸隔声屏体的研制及工程实践

低频噪声污染是输变电工程建设重点关注的环境问题。基于对南通地区变电站噪声样本的频谱特性分析,研发了对低频噪声具有良好吸隔声性能的复合声屏障屏体,并应用于110 k V变电站噪声治理工程实践。声学仿真和验收监测结果表明,声屏障降噪效果明显,周围敏感建筑的声环境质量可满足相关环保标准要求。     

环境噪声控制技术的进展

噪声控制技术是五十年代发展起来的一门技术科学。它是古老的声学理论与飞速发展的现代电子技术结合的产物。随着环境科学的发展,噪声控制也越出企业内部噪声治理的范围,“环境声学”一词已经在1974年第八届国际声学会议文件中出现。     

中德工业产品声学设计技术交流会在沪举行

由上汽——同济噪声与振动工程中心和北京朗德科技有限公司共同主持的中德工业产品声学设计技术交流会于 2 0 0 1年 7月在同济大学举行。参加北京《第二届中德声学创新技术研讨会》的德国 5位专家以及华东地区有关声学单位 30余人出席了会议。本次技术交流内容丰富 ,其中包括噪声和声品质的基本概念、车内噪声模拟及声质量和舒适度的理论、互动式分析在故障诊断方面的应用、噪声传输路径分析及传输路径合成、汽车通过噪声的模拟、发动机台架噪声测试分析、非破坏性整车噪声模拟以及汽车工业用消声室设计新概念等。同时展示了德国等多通道噪…     

噪声对人体健康影响的分析

从全国的城市噪声调查角度出发，得出中国环境噪声的危害程度，并就噪声对人体健康的危害、对工作的影响，作了详细的综述，最后指出中国城市噪声研究存在的问题，并针对这些问题提出了今后研究的发展方向。     

试油测试燃烧器噪声场的计算

在试油测试期间,燃烧器喷射和燃烧产生的噪声会对人员和坏境造成较大的危害,故有必要对燃烧过程中噪声预测展开研究,其结果对于评估平台燃烧噪声危害、优化作业设计及进一步采取降噪措施有重要意义。结合测试燃烧器实际情况提出相应声学计算模式。基于经典燃烧噪声理论及流体动力学噪声的Lighthill理论,通过相似准则的量纲分析方法推导出喷射及燃烧噪声计算公式,并通过声波叠加原理得到声源噪声。同时考虑指向性、扩散衰减、空气吸收、水喷淋消音等减噪因素建立测试燃烧器的噪声计算模型。结合测试燃烧器高压喷射的湍流及多相流特点开展CFD数值模拟计算,数值模拟计算噪声声压级结果与噪音模型计算结果吻合较好。通过该噪声模型计算结果与现场实测数据及某西方公司软件计算结果比较,表明该计算模型可以较好的应用于测试燃烧器噪声预测。     

运用灰色系统理论对城市环境噪声分析与预测

利用灰色系统理论的灰色关联度分析法,对影响佛山市禅城区区域环境噪声的影响因子进行定量分析,结果表明,影响佛山市禅城区区域环境噪声的第一位因素是机动车辆密度;同时建立了城市区域环境噪声的灰色GM(1,1)预测模型,短期预测精度很高,未来5年禅城区区域环境噪声呈平稳下降趋势.为规划防治城市区域环境噪声提供科学依据.     

基于GIS城市道路交通噪声环境管理系统的构架与实现

详细介绍了基于GIS技术开发城市道路交通噪声环境管理系统的构架与实现.该系统的开发工作主要包括:噪声数据库设计、噪声数据管理、交通噪声的模拟和交通噪声影响统计.系统采用了数据库技术、GIS技术和交通噪声预测模型,综合考虑实际情况,对城市噪声环境进行管理和模拟.从实例结果分析可见,模拟结果能达到实际使用的要求.该系统能为城市规划、城市环境评价提供信息和技术支持.     

道路交通噪声预测的研究进展

为评价道路交通噪声影响情况,以美国联邦公路管理局(FHWA)噪声预测模型为主,各国相继开发了基于当地实际情况的道路交通噪声预测模型,中国也以导则和规范等形式相继发布了各种交通噪声预测模型。中国进行噪声环境影响评价中,用得较多的主要有《环境影响评价技术导则声环境》(HJ 2.4—2009)、《公路建设项目环境影响评价规范》(JTG B03—2006)推荐的噪声预测模型,此外也有部分评价工作采用了德国的Cadna A软件。通过对比分析,HJ 2.4—2009的衰减及修正因素在综合考虑FH-WA噪声预测模型及JTG B03—2006基础上更加全面,而JTG B03—2006和Cadna A软件在源强和车速确定方面则均较成熟。有必要根据区域道路特点,选择适合特征区域的道路交通噪声预测模型,并结合实际情况对模型参数进行合理修正,最终形成一些可供区域参考的统一的模型修正参数,积极推动中国的声环境评价工作的发展。     

Prediction of Traffic Noise: A Screening Technique

Abstract

Traffic noise is ubiquitous in many communities and is an important environmental concern, especially for persons located near major roadways. Several different methods are available to estimate noise levels resulting from roadway traffic. These include computational, graphical, and computer modeling techniques.

The prediction methodology presented here is a simplified technique that can be used for estimating noise resulting from traffic and for screening traffic noise impacts. This Traffic Noise Screening (TNS) approach consists of a series of traffic noise level prediction graphs developed for different roadway configurations. The graphs are based on the results from using the Federal Highway Administration (FHWA) STAMINA2.0 computerized noise prediction model for various scenarios. Data inputs to the TNS approach include roadway geometries, traffic volumes, vehicle travel speed, and centerline distance to the receptors.

The TNS graphs allow easy estimation of traffic noise levels for use in predicting traffic-related noise impacts. This TNS approach is not intended as a substitute for detailed modeling, such as with STAMINA2.0, but as a screening tool to aid in determining when detailed modeling may be necessary. If screening results indicate that noise estimates are significant, or if the scenario is rather complex, then additional, more detailed modeling can be performed.     

公路交通噪声预测模型FHWA与RLS90的比较

为了了解我国长期以来使用的两种公路交通噪声预测模型,即美国联邦公路局(FHWA)模型和德国RLS90模型的预测精确性,通过理论分析,比较了RLS90分段模型、RLS90长直线模型、FHWA模型的差异,并通过实际测量值对3种模型的计算结果进行了验证,表明RLS90模型在高速公路交通噪声预测中略优于FHWA模型。     

道路交通噪声预测模式预测结果的比较

为了分析实际环境影响评价中常用的各种公路交通噪声预测模型预测结果之间存在的差异,并验证各预测方式与实测值之间的相符性,通过对选取的高速公路和市政快速公路采用各种预测模型计算比较,并用实际监测值对各模型预测结果进行验证,结果发现,不同的预测方式会造成预测结果之间昼间4～9 dB、夜间5～10 dB的差异,采用2006版规范计算车速和单车噪声源强,距离衰减考虑车流量大小的预测方式得到的预测结果与实测值最为接近。     

Assessment of noise level due to vehicular traffic at Warangal city, India

In the light of the rapid growth of vehicles and the ill effects due to noise pollution, there is a need to study noise pollution from the transportation point of view. In this study, an attempt has been made to study noise pollution due to vehicular traffic in Warangal city, India. It was observed that noise levels are increasing with increased traffic volume. Studies also revealed that 3-wheelers have a major influence on noise levels. It was found that the noise levels at all the locations studied exceeded the Indian standard ambient noise levels.     

Modeling vehicle interior noise exposure dose on freeways: Considering weaving segment designs and engine operation

Vehicle interior noise functions at the dominant frequencies of 500 Hz below and around 800 Hz, which fall into the bands that may impair hearing. Recent studies demonstrated that freeway commuters are chronically exposed to vehicle interior noise, bearing the risk of hearing impairment. The interior noise evaluation process is mostly conducted in a laboratory environment. The test results and the developed noise models may underestimate or ignore the noise effects from dynamic traffic and road conditions and configuration. However, the interior noise is highly associated with vehicle maneuvering. The vehicle maneuvering on a freeway weaving segment is more complex because of its nature of conflicting areas. This research is intended to explore the risk of the interior noise exposure on freeway weaving segments for freeway commuters and to improve the interior noise estimation by constructing a decision tree learning–based noise exposure dose (NED) model, considering weaving segment designs and engine operation. On-road driving tests were conducted on 12 subjects on State Highway 288 in Houston, Texas. On-board Diagnosis (OBD) II, a smartphone-based roughness app, and a digital sound meter were used to collect vehicle maneuvering and engine information, International Roughness Index, and interior noise levels, respectively. Eleven variables were obtainable from the driving tests, including the length and type of a weaving segment, serving as predictors. The importance of the predictors was estimated by their out-of-bag–permuted predictor delta errors. The hazardous exposure level of the interior noise on weaving segments was quantified to hazard quotient, NED, and daily noise exposure level, respectively. Results showed that the risk of hearing impairment on freeway is acceptable; the interior noise level is the most sensitive to the pavement roughness and is subject to freeway configuration and traffic conditions. The constructed NED model shows high predictive power (R = 0.93, normalized root-mean-square error [NRMSE] < 6.7%).

Implications: Vehicle interior noise is usually ignored in the public, and its modeling and evaluation are generally conducted in a laboratory environment, regardless of the interior noise effects from dynamic traffic, road conditions, and road configuration. This study quantified the interior exposure dose on freeway weaving segments, which provides freeway commuters with a sense of interior noise exposure risk. In addition, a bagged decision tree–based interior noise exposure dose model was constructed, considering vehicle maneuvering, vehicle engine operational information, pavement roughness, and weaving segment configuration. The constructed model could significantly improve the interior noise estimation for road engineers and vehicle manufactures.     

Traffic noise exposure of high-rise residential buildings in urban area

Noise pollution is a major factor of environmental complaints in many cities, which has significant impacts on human health. As a dominating source of environmental noise, the impact of road traffic noise is increasing. Residents living in high-rise buildings along the main road are severely affected by traffic noise. In order to assess the noise level of urban area along the main road in Guangzhou, three buildings were selected to conduct traffic noise measurements, and the questionnaire about traffic noise impact on human being was completed. Through the questionnaire, around 70% of participants consider the traffic noise has negative effect, and about 60% of participants consider the noise has moderate or much higher impact on physical comfort. Around 65% of participants consider the noise had moderately or much higher impact on their psychological comfort. By analyzing the measured data, all of the measured noise levels in three buildings exceed the recommended limit of 55 dB (A) in the daytime and 45 dB (A) in the night for residence, and the exceeded value can be up to 16 dB (A). By comparing the fitting curve of noise level transfer function on each floor relative to the reference floor, the quadratic polynomial was selected to plot the transfer function rather than cubic polynomial.

     

A simple model for the dispersion of pollutants from a road tunnel portal

The dispersion of pollutants from a roadway tunnel portal is mainly determined by the interaction between the ambient wind and the jet stream from the tunnel portal. In principal, Eulerian microscale models by solving the conservation equations for mass, momentum, and energy, are thus able to simulate effects such as buoyancy etc. properly. However, for engineering applications such models need too much CPU time, and are not easy to handle by non-scientific personnel. Only a few dispersion models, applicable for regulatory purposes, have so far appeared in the literature. These models are either empirical models not always applicable for different sites, or they do not capture important physical effects like buoyancy phenomena. Here, a rather simple model is presented, which takes into account most of the important processes considered to govern the dispersion of a jet stream from portals. These are the exit velocity, the buoyancy, the influence of ambient wind direction fluctuations on the position of the jet stream, and traffic induced turbulence. Although the model contains some heuristic elements, it was successfully tested against tracer experiments taken near a motorway tunnel portal in Austria. The model requires relatively little CPU time. Current limitations of the model include the neglect of terrain, building, and vehicle effects on the dispersion, and the neglect of the horizontal dispersion arising from entrainment of ambient air in the jet stream. The latter could lead to an underestimation of plume spreads for higher wind speeds. The validation of the model will be the focus of future research. The experimental data set is also available for the scientific community.     

Spatio-temporal covariation of urban particle number concentration and ambient noise

Mobile measurements of ambient noise and particle number concentrations were carried out within an urban residential area in Essen, Germany, during summer 2008. A busy major road with a traffic intensity of about 44,000 vehicles per day was situated within the study area. The spatio-temporal distribution of noise and particles was closely coupled to road traffic on the major road. Total particle number concentrations in proximity to the main road were on average between 25,000 cm^?3 and 35,000 cm^?3 while sound levels reached 70–78 dB(A). These estimates were more than double-fold (factor 2.4) in comparison to the urban residential background. At a 50 m distance off the road particle number concentrations were decaying to about 50% of the initial value. The measurements were characterised by close spatial correlation between total particle number concentration and ambient noise with correlation coefficients of up to r = 0.74. However, during one measurement day coupling between both quantities was weak due to higher turbulent mixing within the canopy layer and a change in ambient wind directions. Enhanced dilution of particle emission from road traffic by turbulent mixing and ‘decoupling’ from the influence of road traffic are believed to be responsible.