Evaluation of Traffic Noise Pollution in Amman, Jordan

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.     

城市道路交通噪声分布模拟研究

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。     

北京市公交车噪声测试与分析

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。     

测点高度对道路交通噪声监测数据的影响

通过在4城市对132条道路进行了道路交通噪声测点高度试验,系统分析了测点高度从手工监测的1.2 m向自动监测的4.5 m转化后,在不同道路情况对道路交通噪声监测数据的影响。结果表明,测点高度提高后监测结果变化在±3 dB(A)以内。待测道路的车道数和测点与机动车道的距离是其主要影响因素。对两测点高度进行对比,4.5 m高度噪声值随水平距离增加衰减较小,测量结果更稳定。     

基于异质人群响应特征的交通噪声暴露评估研究

考虑异质人群不同声功能需求和时空分布,对异质人群交通噪声暴露特征进行评估。通过集记人口高斯分解和噪声预测,获取特征人群分布数据和交通噪声数据;基于特征人群年龄和声功能需求,标定各年龄段人群噪声响应函数并进行归一化处理,构建异质人群噪声响应曲线;构建交通噪声暴露评估模型,结合获取数据及噪声响应曲线进行噪声暴露评估。结果表明,3类声功能区中人群噪声暴露与年龄变量均呈现类抛物线趋势,40岁左右人群暴露影响较儿童和老人低59.9%左右。人均噪声暴露在夜间明显偏高,尤其在声功能需求较高的第1类声功能区,其人均噪声超标值比昼间高7 d B。特征人群的空间分布对噪声暴露影响显著,工作时段学校区域适学人群集中,其总噪声暴露风险为同等状况住宅区的1.2倍。综合考虑人群特征和时空分布等因素,可更科学地进行区域交通噪声污染评估。     

Development of Noise Simulation Model for Stationary and Mobile Sources: A GIS-Based Approach

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.     

高速公路交通噪声经验预测模式探讨

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。     

英国CRTN道路交通噪声预测模型在中国的适用性研究

基于道路交通噪声990 h监测数据,对英国CRTN模型中源强计算模型在中国的适用性进行了验证。试验结果表明,理论计算与实测结果之间平均仅相差0.57 dB（A）,CRTN源强预测模型在中国可以可靠地预测道路交通噪声。     

应用GIS技术研究车流量与交通噪声相关性

对无锡建成区交通噪声等效声级(L_(eq))与车流量进行监测,应用GIS技术分析交通噪声与车流量的空间分布,为交通噪声污染防治工作提供科学参考。结果表明:噪声L_(eq)峰值及车流量峰值均集中在高速公路出入口必经路段,此区域为噪声污染防治重点区域。同时发现,噪声L_(eq)与车流量在空间分布上并非成正比关系,在时间趋势上车流量上升但噪声值下降,说明在机动车保有量不断攀升的背景下,采取多种防治措施可以有效缓解甚至改善交通噪声污染。     

Air pollution exposure monitoring and estimation. Part V. Traffic exposure in adults

In Oslo, traffic has been one of the dominating sources of air pollution in the last decade. In one part of the city where most traffic collects, two tunnels were built. A series of before and after studies was carried out in connection with the tunnels in use. Dispersion models were used as a basis for estimating exposure to nitrogen dioxide and particulate matter in two fractions. Exposure estimates were based on the results of the dispersion model providing estimates of outdoor pollutant concentrations on an hourly basis. The estimates represent concentrations in receptor points and in a square kilometre grid. The estimates were used to assess development of air pollution load in the area, compliance with air quality guidelines, and to provide a basis for quantifying exposure-effect relationships in epidemiological studies. After both tunnels were taken in use, the pollution levels in the study area were lower than when the traffic was on the surface (a drop from 50 to 40 micrograms m-3). Compliance with air quality guidelines and other prescribed values has improved, even if high exposures still exist. The most important residential areas are now much less exposed, while areas around tunnel openings can be in periods exposed to high pollutant concentrations. The daily pattern of exposure shows smaller differences between peak and minimum concentrations than prior to the traffic changes. Exposures at home (in the investigation area) were reduced most, while exposures in other locations than at home showed only a small decrease. Highest hourly exposures are encountered in traffic.     

基于L-M神经网络的道路交通噪声预测研究

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.     

Determination of Path Coefficients and Its Application in Road Traffic Noise Annoyance – a Theoretical Approach

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.     

城市快速路交通噪声影响分析——以深圳市罗湖区罗沙路为例

城市快速路是城市交通运输网的重要组成部分,其产生的交通噪声相当严重。评价城市快速路交通噪声对其两侧交通噪声敏感点的污染状况是目前面临的一个难题。文章以深圳市罗湖区罗沙路为例,对其周边的交通噪声敏感点进行现状调查,利用SoundPLAN软件模拟噪声污染状况,并对安装声屏障前后的降噪效果进行评价,为城市快速路交通噪声污染防治措施的制定提供基础数据和建议。     

Evolution of building façade road traffic noise levels in Flanders

The evolution of daytime fa?ade noise levels by road traffic at 250 dwellings in Flanders is assessed. Three identical man-operated measurement campaigns have been conducted in the years 1996, 2001 and 2009, during fall. A practical methodology has been developed, based on short time noise measurements and context observations at these locations. The uncertainty introduced by short-term sampling has been quantified as a function of the noise level. Furthermore, a correction is proposed for measuring at a random moment during daytime. Analysis of the data showed that road traffic noise levels hardly changed globally over this period of 13 years. The distribution of changes in noise level at corresponding measurement locations is nevertheless rather wide-all improvements are equally compensated by increases in noise levels at other locations. The percentage of the dwelling fa?ades exposed to daytime noise levels above 65 dBA has increased slightly between 1996 and 2001, but seems to stagnate in 2009. In spite of the increased interest and actions of policy makers during the past decades, noise exposure caused by road traffic at dwelling fa?ades is a persistent problem.     

灰色理论及其模型在北京典型城市区域声环境研究中的应用

以北京市某典型区域作为研究对象，在收集大量相关资料与实测历史噪声数据的基础上，对研究区域内的声环境质量影响因素进行灰色关联度分析，并运用灰色理论建立GM（1,1）模型进行预测。结果表明，影响城市区域声环境质量因素从大到小的排序依次为：机动车辆﹥常住人口数量﹥平均车流量﹥地区生产总值﹥城市道路桥梁﹥基础设施投资﹥治理噪声环保投资；以研究区域内噪声污染实测历史数据建立的GM（1,1）模型精度符合要求标准，根据GM（1,1）模型预测北京市“十二五”期间声环境质量达标且有轻微下降趋势。     

Integrated Traffic and Emission Simulation: a Model Calibration Approach Using Aggregate Information

Environmental impacts of road traffic have attracted increasing attention in project-level traffic planning and management. The conventional approach considers emission impact analysis as a separate process in addition to traffic modeling. This paper first introduces our research effort to integrate traffic, emission, and dispersion processes into a common distributed computational framework, which makes it efficient to quantify and analyze correlations among dynamic traffic conditions, emission impacts, and air quality consequences. A model calibration approach is particularly proposed when on-road or in-lab instantaneous emission measurements are not directly available. Microscopic traffic simulation is applied to generate dynamic vehicle states at the second-by-second level. Using aggregate emission estimation as standard reference, a numerical optimization scheme on the basis of a stochastic gradient approximation algorithm is applied to find optimal parameters for the dynamic emission model. The calibrated model has been validated on several road networks with traffic states generated by the same simulation model. The results show that with proper formulation of the optimization objective function, the estimated dynamic emission model can capture the trends of aggregate emission patterns of traffic fleets and predict local emission and air quality at higher temporal and spatial resolutions.     

公交车站对交通噪声的影响分析

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.     

Modelling the Size Separated Particulate Matter (SSPM10) from Vehicular Exhaust at Traffic Intersections in Mumbai

The study was carried out to predict the size separated particulate matter below 10 microm size (SSPM10) from vehicular exhausts at traffic intersections using modified general finite line source model (GFLSM). Two air quality control regions (AQCRs) were selected in Mumbai City for this study. One was industrial area (AQCR1) containing the busy intersection, i.e. Marol link road, with the heavy inflow of two-three wheelers. And, the other was commercial busy district area (AQCR2) containing the busy intersection, i.e. Dadar circle, with a heavy traffic flow especially cars. The model was applied at both the traffic intersections. The data were collected for modelling study for three winter months in 1995 using cascade impactor of nine size ranges. The prediction results revealed that modified GFLSM underpredicted the SSPM10 concentrations for all the size ranges. However, showed considerable correlation between observed and predicted values for the size range below 4.7 microm at both the intersections. The relative high concentrations observed in the coarser range of 10-4.7 microm are attributed to the resuspension of the roadside particulate matter. Hence, the amount of underprediction was more for this range, which was due to the characteristics of model that does not take into account the factor for resuspension of roadside particulate matter caused by traffic movements. The model was also applied to predict the total particulate matter for downwind distances from the road intersection. The statistical evaluation of model was done, which indicated that the model's performance was good for the finer range of particles (below 4.7 microm) with r-square values of 0.49 and 0.57 found at both the intersections in AQCR1 and AQCR2, respectively. However, it is not unusual that the model uncertainty is likely to exist due to data input errors and stochastic fluctuations irrespective of the models accurateness. The statistical distribution model was therefore identified using Kolmogorov-Smirnov test. At both the intersections, SSPM10 concentration data were found lognormally distributed.     

高速公路交通噪声的多普勒效应

通过对高速公路交通噪声现场测定与研究分析,结果表明,由于高速公路上行驶的车辆速度很快,致使在高速公路两侧近距离接收点上,当车辆迎面驶来到背离驶去时,交通噪声出现明显的频率漂移和A声级的显著差异,即出现高速公路交通噪声的多普勒效应。     

2Loud?: Community mapping of exposure to traffic noise with mobile phones

Despite ample medical evidence of the adverse impacts of traffic noise on health, most policies for traffic noise management are arbitrary or incomplete, resulting in serious social and economic impacts. Surprisingly, there is limited information about citizen’s exposure to traffic noise worldwide. This paper presents the 2Loud? mobile phone application, developed and tested as a methodology to monitor, assess and map the level of exposure to traffic noise of citizens with focus on the night period and indoor locations, since sleep disturbance is one of the major triggers for ill health related to traffic noise. Based on a community participation experiment using the 2Loud? mobile phone application in a region close to freeways in Australia, the results of this research indicates a good level of accuracy for the noise monitoring by mobile phones and also demonstrates significant levels of indoor night exposure to traffic noise in the study area. The proposed methodology, through the data produced and the participatory process involved, can potentially assist in planning and management towards healthier urban environments.