Traffic Noise Measurements Research Articles

Long-term associations of modeled and self-reported measures of exposure to air pollution and noise at residence on prevalent hypertension and blood pressure

Air pollution, traffic noise and noise annoyance are suggested to be associated with hypertension and blood pressure (BP); however, the evidence remains inconsistent. Our study examined the long-term associations of modeled and self-reported measures of air pollution and traffic noise on prevalent hypertension and BP. We analyzed cross-sectional data from 2552 participants aged 31–72years from the KORA F4 (2006–2008) study conducted in the region of Augsburg, Germany. Land-use regression models were used to estimate residential long-term exposure to particulate matter <2.5μm (PM2.5), soot content of PM2.5 (PM2.5abs) and nitrogen dioxide (NO2). Road traffic noise levels at the facade of the dwellings were estimated for the participants' residences. Participants filled-in a questionnaire on noise annoyance and heavy traffic passing their residence. Linear and logistic regression models adjusting for confounders were used to assess the association between exposure measures and hypertension and BP. An interquartile increase in annual mean PM2.5 (1μg/m3) was significantly associated with 15% higher prevalence of hypertension, without (95% CI: 2.5; 28.0%) and with (95% CI: 0.7; 30.8%) adjustment for traffic noise. Diastolic blood pressure (DBP) was associated with air pollutants and traffic noise with percent increases in mean of 0.7 (95% CI: 0.2; 1.2), 0.6 (95% CI: 0.1; 1.1) and 0.3 (95% CI: 0.0; 0.7) for an interquartile increase in PM2.5 (1μg/m3) and PM2.5abs (0.2∗10−5/m), and 5dB(A) increase in 24-hour road traffic noise, respectively. Associations of PM2.5abs and NO2 with hypertension or DBP were stronger in men and diabetic individuals. No clear associations were seen with systolic BP or noise annoyance. In conclusion, self-reported measures of air pollution or noise did not perform better than the objective measures. Our findings provide further evidence for a link between air pollution, noise and cardiovascular disease and indicate a stronger association for men and diabetic individuals.

Assessment of Uncertainty in Urban Traffic Noise Measurements

This paper presents measurement results recorded by noise and traffic volume monitoring station located in Krakowska Street, Kielce. Poland. The measurements were performed in the period from January to December 2013, twenty-four hours a day and with a sampling time of 1minute. The results were subjected to statistical analysis. A type A uncertainty was evaluated. A new parameter COVL Aeq was proposed for variability assessment of the equivalent sound pressure level.

Relationship of Traffic Noise with High Blood Pressure to Pedicab Drivers Around Purabaya Bus Station Surabaya

Abstract: The existence of bus station can make some problems, one of which is the traffic noise. Traffic noise can induce an increased blood pressure. Therefore, the purpose of this study was to analyzed the relationship between level of traffic noise and increased blood pressure in pedicab drivers around Purabaya bus station. The study was carried out using by cross sectional method. Measurement of traffic noise was carried out around Purabaya bus station Surabaya with Sound Level Meter. Measurement of blood pressure with sphygmomanometer. Sampling method used by simple random sampling with 22 respondents respectively and then total of respondents are 44 respondents. The result of study indicated there was a relationship between the level traffic noise with increased blood pressure (hypertension) (p = 0.034). Another factor related to blood pressure was descendants of the family history (p = 0.002). It was concluded that traffic noise related with increased blood pressure in pedicab drivers. Suggested for the next researcher doing the measurement noise more than a day to get the actual average noise level. In addition, other factors related to the blood pressure should examined to get main factor of hypertension.Keywords: traffic noise, blood pressure, pedicab drivers

Innovative bootstrap approach for the estimation of minimum measurement time interval in road traffic noise evaluation

Abstract It is observed that in order to characterize the environmental noise in a site, during diurnal reference time (6–22 h) or nocturnal reference time (22–6 h), relatively at preset time window, observation period, a single value of the equivalent continuous A-weighted sound pressure level L A,eq is used. This value is determined by integrating and averaging the squared A-weighted sound pressure of fluctuating noise during the measurement time interval, in which there are representative values of acoustic event pressure levels: so it is very important accurately to select the suitable integration time. Such matter are highly relevant to the area of measuring environmental noise and this paper aims to present a statistical method, for determining the minimum measurement time interval for an accurate estimation of L Aeq . The proposed algorithm, based on CPER bootstrap method, has been experimentally verified with real data obtained from road traffic noise measurement and it showed a very good stability. The methodology is suitable for upgrading the level meter firmware in order to have the real time information on the measurand uncertainty estimation and on the minimum measurement time interval.

State-of-the-Art Review on Sustainable Design and Construction of Quieter Pavements—Part 1: Traffic Noise Measurement and Abatement Techniques

Noise pollution due to highway traffic has drawn the attention of transportation agencies worldwide. Noise pollution is an irritant to residents, especially in urban areas near roads with high traffic volume. In addition to its adverse effects on the quality of life, traffic noise can induce stress that could lead to sleep disturbance and anxiety. Traditionally, noise barrier walls have been used for highways to mitigate traffic noise. However, using barrier walls as a noise abatement measure has proven to be very expensive. In addition to the cost, noise barrier walls are not always effective because they must break the line of sight to work properly, which is not always possible in case of intersections or driveways. Therefore, researchers especially from Europe and USA have been very proactive to reduce the noise at source. A number of research studies show traffic noise can be reduced by using an alternative surface type or changing texture of the pavement while complying with other requirements of sustainability, i.e., safety, structural durability, construction and maintenance costs. This paper presents a comprehensive review of the research conducted on this subject. A review of the tire-pavement noise generation and amplification mechanism, various traffic noise measurement methods and correlation among these methods, in addition to the abatement techniques used by various agencies to reduce pavement noise, is also presented.

Determining environmental noise measurement uncertainty in the context of the Italian legislative framework

Abstract This paper aims to demonstrate the importance of uncertainties in the measurement of environmental noise in the context of Italian legislation on noise pollution focusing the attention on the variability of the measurand as a source of uncertainty and offering a proposal for the evaluation of uncertainty for traffic noise measurement. In particular, drawing on a real traffic noise dataset, firstly outliers are eliminated from the actual noise measurements using an outlier detection algorithm based on K -neighbors distance and then uncertainty range is estimated with the bootstrap- t method. Since the original sequence was Gaussian, this range was compared with the confidence interval of the mean ± standard deviation interval and two intervals were almost coincident.

Methods to improve traffic flow and noise exposure estimation on minor roads

Address-level estimates of exposure to road traffic noise for epidemiological studies are dependent on obtaining data on annual average daily traffic (AADT) flows that is both accurate and with good geographical coverage. National agencies often have reliable traffic count data for major roads, but for residential areas served by minor roads, especially at national scale, such information is often not available or incomplete. Here we present a method to predict AADT at the national scale for minor roads, using a routing algorithm within a geographical information system (GIS) to rank roads by importance based on simulated journeys through the road network. From a training set of known minor road AADT, routing importance is used to predict AADT on all UK minor roads in a regression model along with the road class, urban or rural location and AADT on the nearest major road. Validation with both independent traffic counts and noise measurements show that this method gives a considerable improvement in noise prediction capability when compared to models that do not give adequate consideration to minor road variability (Spearman’s rho. increases from 0.46 to 0.72). This has significance for epidemiological cohort studies attempting to link noise exposure to adverse health outcomes.

Processing and Unification of Environmental Noise Data from Road Traffic with Spatial Dimension Collected through Mobile Phones

Noise measurement using mobile phones is now developed very well. While there are some good applications for the measurement of noise from road traffic, thus on processing of measured data is only paid a very little attention. The data, however, are burdened by specific errors and for further work with them it is necessary to adjust and determine their uncertainty. One of the biggest problems is inaccuracy in position versus the noise source and the shortest length of measurement that can be regarded as representative. Imprecision in terms of location can be determined by calculating the variance of possible distance from the noise source, which for measurement of traffic noise requires a map-matching data points both transverse to the street (sidewalk) network and in the longwise direction. During typical urban measurements, this error can even reach 7 - 10 dB. Three basic types of algorithms for the calculation of uncertainty and positional correction based on the type of input and output data (raster, vector, vector-oriented) were tested. Uncertainty in the variability of the measurement data is necessary to determine from the number of passing vehicles per time unit. The presented solutions are implemented in the Mobile Noise system.

Applicability of models to estimate traffic noise for urban roads.

BackgroundTraffic noise is a highly relevant environmental impact in cities. Models to estimate traffic noise, in turn, can be useful tools to guide mitigation measures. In this paper, the applicability of models to estimate noise levels produced by a continuous flow of vehicles on urban roads is investigated. The aim is to identify which models are more appropriate to estimate traffic noise in urban areas since several models available were conceived to estimate noise from highway traffic.ResultsFirst, measurements of traffic noise, vehicle count and speed were carried out in five arterial urban roads of a brazilian city. Together with geometric measurements of width of lanes and distance from noise meter to lanes, these data were input in several models to estimate traffic noise. The predicted noise levels were then compared to the respective measured counterparts for each road investigated. In addition, a chart showing mean differences in noise between estimations and measurements is presented, to evaluate the overall performance of the models. Measured Leq values varied from 69 to 79 dB(A) for traffic flows varying from 1618 to 5220 vehicles/h. Mean noise level differences between estimations and measurements for all urban roads investigated ranged from −3.5 to 5.5 dB(A).ConclusionsAccording to the results, deficiencies of some models are discussed while other models are identified as applicable to noise estimations on urban roads in a condition of continuous flow. Key issues to apply such models to urban roads are highlighted.

Benefits and limitations toward a sustainable road environment during the years of economic recession

The prolonged economic crisis in Greece in the last 5 years resulted in a dramatic road traffic volume reduc tion and as a consequence in environmental road traffic noise diminution. This article analyses this issue with comparisons of measurements of noise, traffic volume and speed, at certain points along the capital’s ring motorway, for a 9-year period. Data and comparisons concern measurements taken at 42 locations in Athens ring road during the last 9 years. According to the results, since 2009 – the year with the highest ring road traffic volume – there is a downward trend in both road traffic and environmental noise measurements recorded every year. It is also interesting to point out that until 2009, at locations where there is high traffic volume and many hours of congestion during the day, there is some minor reduction or even an increase in noise level due to the increase of the average speed. On the other hand, night measurements show that, for economy reasons, driver’s speed has dropped to lower levels and thus lower noise level measurements are recorded.

HEDONIC ANALYSIS OVER TIME AND SPACE: THE CASE OF HOUSE PRICES AND TRAFFIC NOISE

ABSTRACTOne consequence of the expanding road network and its associated traffic is increased levels of traffic noise. While the hedonic literature has consistently found a negative relationship between real estate prices and noise levels, research in the United States has typically relied on crude measures of traffic noise. Here, we reduce the measurement error of traffic noise exposure through a detailed model of noise propagation over the landscape. We then estimate the hedonic relationship between noise and single family house prices using over 40,000 transactions throughout the St. Paul, Minnesota, urban area from 2005 to 2010. We implement spatially and temporally flexible local regression techniques and find significant nonstationarity in the hedonic function over time and space.

Applicability of a noise-based model to estimate in-traffic exposure to black carbon and particle number concentrations in different cultures

Several studies show that a significant portion of daily air pollution exposure, in particular black carbon (BC), occurs during transport. In a previous work, a model for the in-traffic exposure of bicyclists to BC was proposed based on spectral evaluation of mobile noise measurements and validated with BC measurements in Ghent, Belgium. In this paper, applicability of this model in a different cultural context with a totally different traffic and mobility situation is presented. In addition, a similar modeling approach is tested for particle number (PN) concentration.Indirectly assessing BC and PN exposure through a model based on noise measurements is advantageous because of the availability of very affordable noise monitoring devices. Our previous work showed that a model including specific spectral components of the noise that relate to engine and rolling emission and basic meteorological data, could be quite accurate. Moreover, including a background concentration adjustment improved the model considerably. To explore whether this model could also be used in a different context, with or without tuning of the model parameters, a study was conducted in Bangalore, India. Noise measurement equipment, data storage, data processing, continent, country, measurement operators, vehicle fleet, driving behavior, biking facilities, background concentration, and meteorology are all very different from the first measurement campaign in Belgium. More than 24h of combined in-traffic noise, BC, and PN measurements were collected. It was shown that the noise-based BC exposure model gives good predictions in Bangalore and that the same approach is also successful for PN. Cross validation of the model parameters was used to compare factors that impact exposure across study sites. A pooled model (combining the measurements of the two locations) results in a correlation of 0.84 when fitting the total trip exposure in Bangalore. Estimating particulate matter exposure with traffic noise measurements was thus shown to be a valid approach across countries and cultures.

Application of Land Use Regression Modelling to Assess the Spatial Distribution of Road Traffic Noise in Three European Cities

Noise prediction models and noise maps are used to estimate the exposure to road traffic noise, but their availability and the quality of the noise estimates is sometimes limited. This paper explores the application of land use regression (LUR) modelling to assess the long-term intraurban spatial variability of road traffic noise in three European cities. Short-term measurements of road traffic noise taken in Basel, Switzerland (n=60), Girona, Spain (n=40), and Grenoble, France (n=41), were used to develop two LUR models: (a) a “GIS-only” model, which considered only predictor variables derived with Geographic Information Systems; and (b) a “Best” model, which in addition considered the variables collected while visiting the measurement sites. Both noise measurements and noise estimates from LUR models were compared with noise estimates from standard noise models developed for each city by the local authorities. Model performance (adjusted R2) was 0.66–0.87 for “GIS-only” models, and 0.70–0.89 for “Best” models. Short-term noise measurements showed a high correlation (r=0.62–0.78) with noise estimates from the standard noise models. LUR noise estimates did not show any systematic differences in the spatial patterns when compared with those from standard noise models. LUR modelling with accurate GIS source data can be a promising tool for noise exposure assessment with applications in epidemiological studies.

Research of the Spread and Measurement of Urban Traffic Noise

Study of the traffic noise has important role in the improvement of urban living environment. The source of the noise of road vehicle and the spectral features of urban traffic noise are analysed in the paper. Through the investigation and monitoring on two typical roads, the distribution law of traffic noise along both sides of the road is analysed and a theoretical basis for the control of traffic noise is provided.

Application of land use regression modelling to assess the spatial distribution of road traffic noise in three European cities

Noise prediction models and noise maps are used to estimate the exposure to road traffic noise, but their availability and the quality of the noise estimates is sometimes limited. This paper explores the application of land use regression (LUR) modelling to assess the long-term intraurban spatial variability of road traffic noise in three European cities. Short-term measurements of road traffic noise taken in Basel, Switzerland (n=60), Girona, Spain (n=40), and Grenoble, France (n=41), were used to develop two LUR models: (a) a "GIS-only" model, which considered only predictor variables derived with Geographic Information Systems; and (b) a "Best" model, which in addition considered the variables collected while visiting the measurement sites. Both noise measurements and noise estimates from LUR models were compared with noise estimates from standard noise models developed for each city by the local authorities. Model performance (adjusted R(2)) was 0.66-0.87 for "GIS-only" models, and 0.70-0.89 for "Best" models. Short-term noise measurements showed a high correlation (r=0.62-0.78) with noise estimates from the standard noise models. LUR noise estimates did not show any systematic differences in the spatial patterns when compared with those from standard noise models. LUR modelling with accurate GIS source data can be a promising tool for noise exposure assessment with applications in epidemiological studies.

Designing a Traffic Noise Prediction Model for Highways in Iranian Megacities (Case study: Ahvaz City)

One of the important factors in urban construction designs is noise prevention. According toresults of this study (2011-2012), a suggested model is presented for traffic noise compatible to conditions in Ahvaz. Data was colleted to design a model from totally 112 measuring stations, 4 weekdays and 2 intervals as rush hours, yielding to a total number of 1344 traffic noise measurements (Leq) and the effective factors from traffic load, speed of vehicles, environmental and dimensional factors of roads. In the next step, based on desired overall structure, using analytical and experimental modeling strategies, several Regression multivariables were tested on data in order to design a model. The model designed for Ahvaz consists of 9 inputs with high clarification coefficient (R2=0.92) and correlation coefficient (R= 0.95). Due to precision and minuteness of designing as well as the number of inputs, the model can be a suitable one to define half – hour equal level for traffic noise and estimation of noise pollution in Ahvaz.

Temporal and spatial variability of traffic-related noise in the City of Toronto, Canada

The majority of studies that assessed population-level exposure to traffic-related noise were conducted in European countries and less is known about the exposure to traffic noise in North America, particularly in Canadian cities. This study explored the temporal and spatial variability of traffic noise in the City of Toronto, the largest city in Canada. We conducted two cycles of intensive field measurement campaign to collect real-time measurements of traffic noise at 554 locations across Toronto between June 2012 and January 2013. At each site, we collected measurements for a period of 30min during daytime. Repeated measurements were made in cycle two at 62 locations randomly selected from cycle one, which exhibited high correlation (Pearson's correlation coefficient (r): 0.79). In addition, continuous measurements of noise were recorded for seven days at ten sites. We observed that noise variability was predominantly spatial in nature, rather than temporal: spatial variability accounted for 60% of the total observed variations in traffic noise. Traffic volume, length of arterial road, and industrial area were three most important variables, explaining the majority of the spatial variability of noise (R2=0.68 to 0.74, depending on the cycle). In comparison to the 16-h equivalent sound level guideline for outdoor locations set out by the Ministry of the Environment of the Province of Ontario, 80% of our sampled locations exceeded this guideline (i.e. 55 dBA,16h). These findings suggested ubiquitous traffic noise exposure across Toronto and that noise variability was explained mostly by spatial characteristics.

개선된 럼블스트립의 현장적용에 따른 사후 소음특성 평가

PURPOSES : This research investigates traffic noise characteristics as change the transverse rumble strips shape from rectangular to cylinder at toll plaza of highway. METHODS : The traffic noise was investigated at two different places at toll plaza of highway. One is modified grooving, another is employed cylinder shape of TRS instead of rectangular shape of TRS. A measurement of traffic noise was conducted at same location and time period. The traffic volume information was gotten from office of highway office and vehicle speed was measured by speed measuring device. The traffic noise measurement was conducted from 13:00 to 23:00 and by pass-by method. Also, the traffic noise was measured behind noise barrier. Various distance from noise barrier(7.5m, 30m, 50m) and different heights(1.2m, 3m, and 5m) were parameter for measurement of traffic noise in this study. RESULTS : The class 1 vehicle was contributed from traffic volume which was increased 1,500. However, the distribution of traffic speed didn`t change compare to previous investigated period. From this study, It was found that the external traffic noise was changed as function of geometric shape of TRS. The external noise from modified grooving was less than 1.2dB(A) of the current TRS. A difference of traffic noise was 20dB(A) before and after barrier. It came from a noise barrier effect as reduction of traffic noise. According to investigate a traffic noise distribution near barrier, there is similar noise characteristic as function of height at 7.5m distance from noise barrier. Also, There is no different traffic noise between 30m and 50m from source of the noise of sound barrier. CONCLUSIONS : Based on this traffic noise investigation result, there is a clear characteristic difference as changed TRS shape. The traffic noise was reduced by changed TRS shape. Specially, traffic noise was decreased although the traffic volume was increase for same investigation time and period. It is implied that cylinder type of TRS significantly reduces the traffic noise. The specification of various TRS will be studied in the future.

Exploratory traffic noise measurements at five main streets of Thessaloniki, Greece

Although noise is a very common nuisance in Greek cities, information on actual noise levels in streets is sparse. Here, noise measurements at five main streets of Thessaloniki, Greece for about five weeks are presented. Ten minute, one hour and daily average noise levels were calculated. Traffic noise levels were significant in every examined street during the study. In all streets, the diurnal variation of noise levels and traffic volume exhibited significant correlation, with r2 up to 0.92. Noise measurements at two heights in one street showed a difference of around 14 db between the 1st and the 8th floor. The noise levels difference between working days and weekends was around 1-2 dB during daytime, but it changed sign during the late night hours. The latter can be attributed to night-life recreational traffic during weekends. Noise levels from 7:00 to 24:00 were around 63-66 dB in the 1st and 2nd floors of all four streets where measurements were made at these floors. In these cases, the quietest period was between 4:00 and 6:00, but even then, in three out of four cases noise levels were above 60 dB. Although no exceedances have been observed, the mean daily values, i.e. Leq(08:00-20:00), are close to the national limit of 67 dB(A). This exploratory measurements show that Thessaloniki has a traffic noise problem, which is likely to become more acute, if the 6% annual increase in traffic volume experienced during the previous decade is to continue.

Parameter Estimation for Traffic Noise Models Using a Harmony Search Algorithm

A technique has been developed for predicting road traffic noise for environmental assessment, taking into account traffic volume as well as road surface conditions. The ASJ model (ASJ Prediction Model for Road Traffic Noise, 1999), which is based on the sound power level of the noise emitted by the interaction between the road surface and tires, employs regression models for two road surface types: dense-graded asphalt (DGA) and permeable asphalt (PA). However, these models are not applicable to other types of road surfaces. Accordingly, this paper introduces a parameter estimation procedure for ASJ-based noise prediction models, utilizing a harmony search (HS) algorithm. Traffic noise measurement data for four different vehicle types were used in the algorithm to determine the regression parameters for several road surface types. The parameters of the traffic noise prediction models were evaluated using another measurement set, and good agreement was observed between the predicted and measured sound power levels.