scholarly journals Road Traffic Noise on the Santa Marta City Tourist Route

2021 ◽  
Vol 11 (16) ◽  
pp. 7196
Author(s):  
Dámaris A. Jiménez-Uribe ◽  
Darwin Daniels ◽  
Zoë L. Fleming ◽  
Andrés M. Vélez-Pereira
Keyword(s):  
Traffic Flow ◽  
Noise Level ◽  
Road Traffic ◽  
Traffic Noise ◽  
Environmental Noise ◽  
Time Of Day ◽  
Road Traffic Noise ◽  
Sampling Point ◽  
Heavy Vehicles ◽  
Noise Levels

The objective of this study was to determine the influence of vehicular traffic on the environmental noise levels of the Santa Marta City tourist route on the Colombian coast. An analysis of vehicle types and frequencies at various times of the day over nearly a year helped to track the main sources of environmental noise pollution. Five sampling points were selected, which were distributed over 12 km, with three classified as peripheral urban and two as suburban. The average traffic flow was 966 vehicles/h and was mainly composed of automobiles, with higher values in the peripheral urban area. The noise level was 103.3 dBA, with background and peak levels of 87.2 and 107.3 dBA, respectively. The noise level was higher during the day; however, there were no differences between weekdays and weekends. The results from the analysis of variance showed that the number of vehicles and the noise levels varied greatly according to the time of day and sampling point location. The peak and mean noise levels were correlated with the number of automobiles, buses and heavy vehicles. The mean noise levels were similar at all sample points despite the traffic flow varying, and the background noise was only correlated for automobiles (which varied much more than the heavy vehicles between day and night).

scholarly journals Influence of Honking on the Road Traffic Noise Generated at Urban Rotaries for Heterogeneous Traffic

2020 ◽  
Vol 24 (1) ◽  
pp. 23-42
Author(s):  
Kamineni Aditya ◽  
Venkaiah Chowdary
Keyword(s):  
Noise Level ◽  
Road Traffic ◽  
Noise Analysis ◽  
Traffic Noise ◽  
Heterogeneous Traffic ◽  
Road Traffic Noise ◽  
Good Precision ◽  
Heavy Vehicles ◽  
Noise Levels ◽  
Noise Data

AbstractThis paper presents a study conducted at major rotaries for quantifying the traffic noise levels by considering the vehicle volume and their respective honking as governing parameters for heterogeneous traffic. Traffic volume and traffic noise data was collected using a digital video camera and a class 1 sound level meter, respectively. The traffic noise data was analysed using noise tools for identifying the noise level variation. The data collected was subjected to statistical analysis for light, medium and heavy vehicles, and their contribution towards noise levels is proven to be effective with the forthright fact that, heavy vehicles and their corresponding honking were majorly affecting the equivalent noise level compared to other vehicular proportion. An equivalent noise level [LAeq (dB)] rise of 2 to 6 dB (A) is solely caused by heavy vehicles, which is an important observation to be considered for traffic noise analysis at the rotaries. Based on the obtained results from one of the rotaries, noise prediction model is developed for estimating the LAeq (dB), which is able to predict the noise levels with good precision when validated with the data collected at second rotary intersection for different vehicle volumes.

scholarly journals Traffic-related Noise at Roadside Schools: Assessment and Prediction in Urban Setting

2021 ◽  
Vol 22 (2) ◽  
pp. 178-189
Author(s):  
Mila Dirgawati ◽  
Gita Nur Apriani ◽  
Astien Arsten Asyari ◽  
R. Triyogo
Keyword(s):  
Noise Level ◽  
Road Traffic ◽  
Traffic Noise ◽  
Urban Setting ◽  
National Standard ◽  
Road Traffic Noise ◽  
Heavy Vehicles ◽  
The Road ◽  
Total Vehicle ◽  
Data Volume

ABSTRAK Kebisingan lalu lintas adalah salah satu ancaman bagi kesehatan masyarakat perkotaan. Paparan bising memberikan efek kesehatan jangka pendek dan panjang, dan efeknya berpotensi lebih buruk pada anak-anak yang belajar di sekolah pinggir jalan. Penelitian ini bertujuan untuk mengkarakterisasi kebisingan lalu lintas jalan di sekolah-sekolah yang terletak di jalan-jalan utama di Bandung, Indonesia serta memberikan rekomendasi mitigasi dan adaptasi untuk pengendalian kebisingan. Kebisingan lalu lintas diperoleh di dua sekolah pinggir jalan terletak di dua jalan utama (Jalan Suci dan Djuanda), beserta data volume dan komposisi lalu lintas, serta kecepatan kendaraan. Pengukuran dilakukan antara jam sekolah selama satu hari yang mewakili lokasi trotoar jalan, depan sekolah, dan halaman sekolah. Parameter tingkat kebisingan yang penting (Leq, L10, L50, L90) diukur, dan dilakukan analisis korelasi antara masing-masing parameter kebisingan. Model CoRTN digunakan untuk memprediksi kebisingan lalu lintas pada jarak tertentu dari jalan raya. Sepeda motor merupakan jenis kendaraan dominan secara berturut 79,1% dan 67,1% dari total volume kendaraan di ruas jalan Suci dan Djuanda. Kendaraan berat menyumbang <1%. Mayoritas kebisingan lalu lintas yang diukur sebagai Leq, L10, L50, L90 melebihi batas maksimum untuk pinggir jalan dan zona sekolah menurut standar internasional dan nasional <55 dBA). Model tersebut berkinerja lebih baik di ruas jalan Djuanda daripada Suci. Jumlah lokasi dan waktu pengukuran yang lebih banyak dapat memberikan penilaian paparan tingkat kebisingan lalu lintas yang lebih baik dengan menggunakan model CoRTN. Hasil penelitian ini diharapkan dapat menjadi masukan kebijakan berbasis pengetahuan bagi pemerintah kota dan lembaga untuk mengurangi dampak bising bagi anak didik. Kata kunci: kebisingan lalu lintas jalan, tingkat kebisingan, Model CoRTN   ABSTRACT Noise from road traffic is one of the most ubiquitous threats to the public health in urban setting. Its exposures have proven short-and long-term health effects. and potentially worse for vulnerable population such as children studying at roadside schools. This study aimed to characterize the road traffic noise at schools located at major roads in Bandung, Indonesia. Traffic noise were obtained at 2 roadside schools located at two major roads (Suci and Djuanda roads), along with data on traffic volume and composition, and vehicles speed. The measurement was conducted between school hours during one day-time only at locations representative of roadside, front of the schools, and schoolyard. Important noise level parameters such as Leq, L10, L50, L90 were recorded, and correlation analysis between each parameter was conducted. The CoRTN model was then applied to predict the traffic noise at particular distances from the road. Motorcycles were the predominant vehicle type on both road segments: 79.1% and 67.1% of the total vehicle volume on Suci on Djuanda segments, respectively.  Conversely, heavy vehicles accounted <1%. The majority of measured traffic noise determined as Leq, L10, L50, L90 exceeded the maximum limit for roadside and school zone set by the international and national standard (>55 dBA). The model performed better in Djuanda road segment than in Suci segment. More measurement locations and time could provide better assessment of exposure to traffic noise levels at roadside schools using the CoRTN model. Keywords: road traffic noise, noise level, CoRTN model

scholarly journals Theoretical Comparison of the Effects of Different Traffic Conditions on Urban Road Traffic Noise

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad Maghrour Zefreh ◽  
Adam Torok
Keyword(s):  
Traffic Flow ◽  
Noise Level ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Noise ◽  
Urban Traffic ◽  
Road Traffic Noise ◽  
Traffic Lights ◽  
Urban Road ◽  
Traffic Conditions

Road traffic noise is one of the most relevant sources in the environmental noise pollution of the urban areas where dynamics of the traffic flow are much more complicated than uninterrupted traffic flows. It is evident that different traffic conditions would play the role in the urban traffic flow considering the dynamic nature of the traffic flow on one hand and presence of traffic lights, roundabouts, etc. on the other hand. The main aim of the current paper is to investigate the effect of different traffic conditions on urban road traffic noise. To do so, different traffic conditions have been theoretically generated by the Monte Carlo Simulation technique following the distribution of traffic speed in the urban roads. The “ASJ RTN-Model” has been considered as a base road traffic noise prediction model which would deal with different traffic conditions including steady and nonsteady traffic flow that would cover the urban traffic flow conditions properly. Having generated the vehicles speeds in different traffic conditions, the emitted noise (LWA) and subsequently the noise level at receiver (LA) were estimated by “ASJ RTN-Model.” Having estimated LWA and LA for each and every vehicle in each traffic condition and taking the concept of transient noise into account, the single event sound exposure levels (SEL) in different traffic conditions are calculated and compared to each other. The results showed that decelerated traffic flow had the lowest contribution, compared to congestion, accelerated flow, free flow, oversaturated congestion, and undersaturated flow by 16%, 14%, 12%, 12%, and 10%, respectively. Moreover, the distribution of emitted noise and noise level at receiver were compared in different traffic conditions. The results showed that traffic congestion had considerably the maximum peak compared to other traffic conditions which would highlight the importance of the range of generated noise in different traffic conditions.

scholarly journals MODELLING URBAN NOISE IN CITYGML ADE: CASE OF THE NETHERLANDS

2017 ◽  
Vol IV-4/W5 ◽  
pp. 73-81 ◽  
Author(s):  
K. Kumar ◽  
H. Ledoux ◽  
T. J. F. Commandeur ◽  
J. E. Stoter
Keyword(s):  
Urban Areas ◽  
Input Data ◽  
Road Traffic ◽  
Traffic Noise ◽  
Environmental Noise ◽  
Motor Vehicles ◽  
Road Traffic Noise ◽  
Noise Levels ◽  
Noise Mapping ◽  
Urban Noise

Road traffic and industrial noise has become a major source of discomfort and annoyance among the residents in urban areas. More than 44&amp;thinsp;% of the EU population is regularly exposed to road traffic noise levels over 55 dB, which is currently the maximum accepted value prescribed by the Environmental Noise Directive for road traffic noise. With continuously increasing population and number of motor vehicles and industries, it is very unlikely to hope for noise levels to diminish in the near future. Therefore, it is necessary to monitor urban noise, so as to make mitigation plans and to deal with its adverse effects. The 2002/49/EC Environmental Noise Directive aims to determine the exposure of an individual to environmental noise through noise mapping. One of the most important steps in noise mapping is the creation of input data for simulation. At present, it is done semi-automatically (and sometimes even manually) by different companies in different ways and is very time consuming and can lead to errors in the data. In this paper, we present our approach for automatically creating input data for noise simulations. Secondly, we focus on using 3D city models for presenting the results of simulation for the noise arising from road traffic and industrial activities in urban areas. We implemented a few noise modelling standards for industrial and road traffic noise in CityGML by extending the existing Noise ADE with new objects and attributes. This research is a steping stone in the direction of standardising the input and output data for noise studies and for reconstructing the 3D data accordingly.

scholarly journals The “sound of silence” in Granada during the COVID-19 lockdown

Noise Mapping ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 16-31 ◽  
Author(s):  
Jerónimo Vida Manzano ◽  
José Antonio Almagro Pastor ◽  
Rafael García Quesada ◽  
Francesco Aletta ◽  
Tin Oberman ◽  
...  
Keyword(s):  
Human Activity ◽  
Road Traffic ◽  
Traffic Noise ◽  
Environmental Noise ◽  
Road Traffic Noise ◽  
Noise Levels ◽  
Noise Sources ◽  
Comparison Results ◽  
The Impact ◽  
The City

Abstract Exceptional circumstances in the city of Granada due to the COVID-19 lockdown have provided the opportunity to characterise the impact of humans on its urban acoustic climate. Traditional environmental noise management and urban sound planning usually take into account noise sources in the city, such as industrial activities or road traffic noise, in model estimations, as well as in empirical research. But trying to isolate human impact by itself, human activity including social activity, walking, talking or just going around the city, has always been a difficult or even impossible task. The COVID-19 lockdown measures have provided the opportunity to study urban climate as never before, affected just by natural or animal noise sources. Previous soundscape research at some iconic sites in the city of Granada carried out in 2019 before the lockdown and a special measuring campaign carried out at the same locations during the lockdown in 2020 offered valuable information on sound levels and local characteristics in order to carry out this comparison. Results show a great change in environmental noise levels that is interesting not only because of its magnitude, but also for its implications, especially at those sites where social human activity was an identifying characteristic. Natural or animal sounds became surprisingly evident at some study sites, especially where road traffic noise dramatically decreased, leading to significantly lower background noise levels. Important spectral changes are observed before and during the lockdown, suggesting a shift from anthropic to animal sources in the acoustic environment.

scholarly journals LONG-TERM NOISE MEASUREMENTS AND HARMONICA INDEX AS A WAY OF RAISING PUBLIC AWARENESS ABOUT TRAFFIC NOISE IN THE CITY OF NIŠ

2017 ◽  
pp. 041 ◽  
Author(s):  
Momir Praščević ◽  
Darko Mihajlov ◽  
Dragan Cvetkovic ◽  
Aleksandar Gajicki
Keyword(s):  
Noise Level ◽  
Road Traffic ◽  
Traffic Noise ◽  
Environmental Noise ◽  
Road Traffic Noise ◽  
Short Term ◽  
Noise Measurements ◽  
The City ◽  
Level Monitoring

Environmental noise level monitoring in Serbia is performed in several cities and it is pursuant to the Law on Environmental Noise Protection and the accompanying regulations. Although these regulations are in accordance with the national standards, the methodology of noise monitoring varies in different cities. The issues which differ include the following: the number of measurement spots, the number of daily, weekly, and monthly measurement intervals, the duration of measurement intervals, measurement parameters and noise indicators used for noise evaluation. Different measurement procedures are the consequence of diverse city configurations, traffic structure, traffic flow, locations of noise-sensitive objects, as well as diverse contribution of noise sources. The road traffic noise level monitoring in the City of Nis has been organized from 1995 until today based on short-term measurements. The values of noise indicators are calculated based on these short-term measurements. The two newly purchased noise monitoring terminals by the Noise and Vibration Laboratory of the Faculty of Occupational Safety in Nis, enabled the long-term noise measurements. The procedure of permanent and semi-permanent road traffic noise measurements at eight locations in the City of Nis has been carried out since January 1, 2014. The results of long-term road traffic noise measurements at the main streets of Niš city are presented in this paper as well as the possibility of their presentation in the sense of the Harmonica index.

Prediction of L10 and Leq Noise Levels Due to Vehicular Traffic in Urban Area Using ANN and Adaptive Neuro-Fuzzy Interface System (ANFIS) Approach

2019 ◽  
Vol 15 (2) ◽  
pp. 92-105
Author(s):  
Vilas K Patil ◽  
P.P. Nagarale
Keyword(s):  
Noise Level ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Vehicular Traffic ◽  
Noise Levels ◽  
Anfis Model ◽  
Neuro Fuzzy ◽  
Interface System

Recently in urban areas, road traffic noise is one of the primary sources of noise pollution. Variation in noise level is impacted by the synthesis of traffic and the percentage of heavy vehicles. Presentation to high noise levels may cause serious impact on the health of an individual or community residing near the roadside. Thus, predicting the vehicular traffic noise level is important. The present study aims at the formulation of regression, an artificial neural network (ANN) and an adaptive neuro-fuzzy interface system (ANFIS) model using the data of observed noise levels, traffic volume, and average speed of vehicles for the prediction of L10 and Leq. Measured noise levels are compared to the noise levels predicted by the experimental model. It is observed that the ANFIS approach is more superior when compared to output given by regression and an ANN model. Also, there exists a positive correlation between measured and predicted noise levels. The proposed ANFIS model can be utilized as a tool for traffic direction and planning of new roads in zones of similar land use pattern.

scholarly journals Aggregate Impact of Anomalous Noise Events on the WASN-Based Computation of Road Traffic Noise Levels in Urban and Suburban Environments

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 609 ◽  
Author(s):  
Francesc Alías ◽  
Ferran Orga ◽  
Rosa Ma Alsina-Pagès ◽  
Joan Claudi Socoró
Keyword(s):  
Sensor Networks ◽  
Road Traffic ◽  
Traffic Noise ◽  
Noise Pollution ◽  
Environmental Noise ◽  
Integration Time ◽  
Road Traffic Noise ◽  
Noise Levels ◽  
Noise Mapping ◽  
Acoustic Data

Environmental noise can be defined as the accumulation of noise pollution caused by sounds generated by outdoor human activities, Road Traffic Noise (RTN) being the main source in urban and suburban areas. To address the negative effects of environmental noise on public health, the European Environmental Noise Directive requires EU member states to tailor noise maps and define the corresponding action plans every five years for major agglomerations and key infrastructures. Noise maps have been hitherto created from expert-based measurements, after cleaning the recorded acoustic data of undesired acoustic events, or Anomalous Noise Events (ANEs). In recent years, Wireless Acoustic Sensor Networks (WASNs) have become an alternative. However, most of the proposals focus on measuring global noise levels without taking into account the presence of ANEs. The LIFE DYNAMAP project has developed a WASN-based dynamic noise mapping system to analyze the acoustic impact of road infrastructures in real time based solely on RTN levels. After studying the bias caused by individual ANEs on the computation of the A-weighted equivalent noise levels through an expert-based dataset obtained before installing the sensor networks, this work evaluates the aggregate impact of the ANEs on the RTN measurements in a real-operation environment. To that effect, 304 h and 20 min of labeled acoustic data collected through the two WASNs deployed in both pilot areas have been analyzed, computing the individual and aggregate impacts of ANEs for each sensor location and impact range (low, medium and high) for a 5 min integration time. The study shows the regular occurrence of ANEs when monitoring RTN levels in both acoustic environments, which are especially common in the urban area. Moreover, the results reveal that the aggregate contribution of low- and medium-impact ANEs can become as critical as the presence of high-impact individual ANEs, thus highlighting the importance of their automatic removal to obtain reliable WASN-based RTN maps in real-operation environments.

Road Traffic Noise Levels at Different Types of Residential Areas in Nibong Tebal, Penang

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Herni Halim ◽  
◽  
Nur Fatin Najiyah Hamid ◽  
Mohamad Firdaus Mahamad Yusob ◽  
Nur Atiqah Mohamad Nor ◽  
...  
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Residential Areas ◽  
Noise Levels ◽  
Different Types

INFLUENCE OF TRUCK TRAFFIC ON ACOUSTIC POLLUTION IN KAUNAS DISTRICTS CROSSED BY HIGHWAYS/KROVININIO AUTOTRANSPORTO ĮTAKA AKUSTINEI TARŠAI RESPUBLIKINĖS REIKŠMĖS MAGISTRALIŲ KERTAMUOSE KAUNO MIKRORAJONUOSE/ ВЛИЯНИЕ ГРУЗОВОГО АВТОТРАНСПОРТА НА АКУСТИЧЕСКОЕ ЗАГРЯЗНЕНИЕ В МИКРОРАЙОНАX ГОРОДА KАУНАСА С ТРАССАМИ ГОСУДАРСТВЕННОГО ЗНАЧЕНИЯ

2009 ◽  
Vol 17 (4) ◽  
pp. 198-204 ◽  
Author(s):  
Regina Gražulevičienė ◽  
Inga Bendokienė
Keyword(s):  
Data Analysis ◽  
Traffic Flow ◽  
Noise Level ◽  
Traffic Noise ◽  
Heavy Vehicles ◽  
Truck Traffic ◽  
Statistical Software ◽  
Study Results ◽  
Noise Measurements ◽  
Main Streets

The aim of the study was to assess the influence of truck traffic on acoustic pollution in two Kaunas districts crossed by highways‐ Eiguliai and Šilainiai. Composition of traffic flow and noise measurements were conducted near the main streets and national highways that cross the districts. GIS and statistical software SPSS 12.01 were used for the data analysis. The study results showed that mean noise level near the main streets was 70 dB(A) in the daytime,‐ 68.6 dB(A) in the evening and at night it was 61.1 dB(A) in Eiguliai, and in Šilainiai it was 67 dB(A), 65 dB(A) and 58 dB(A), correspondingly. On the highways, crossing the districts, heavy vehicles compose about 3 times higher part of total traffic flow during the day and about 2 times in the evening compared to other main streets. The noise level depended on the traffic flow and correlation coefficient fluctuated from 0.77 to 0.85. The modelling of traffic flow showed, that the increase of trucks proportion by 2 percent would increase the traffic noise by 1.1 dB(A) in the streets with traffic flow of 300 veh./hour or more, and by 1.8 dB(A) with traffic flow of 200 veh./hour or less. Our findings suggest that the influence of heavy vehicles on acoustic pollution is higher in the districts with lower traffic flow. Santrauka Tyrimo tikslas – nustatyti krovininio autotransporto įtaką akustinei taršai Kauno mikrorajonuose, kuriuos kerta respublikinės reikšmės magistralės – Islandijos plentas ir vakarinis lankstas. Aplinkos triukšmo lygis ir transporto srautų intensyvumas Eigulių ir Šilainių seniūnijoje buvo matuotas 34 taškuose – dieną, vakare ir naktį. Duomenims apdoroti taikyta geografinių informacinių (GIS) sistemų technologijos, SPSS 12.0.1 ir Statistica 15 statistinės analizės paketai. Tyrimų rezultatai: vidutinis ekvivalentinis triukšmo lygis Eigulių seniūnijoje dieną prie pagrindinių gatvių siekė 70 dBA, vakare – 68,6 dBA, o naktį – 61,1 dBA ir iš esmės nesiskyrė nuo Šilainių seniūnijos, atitinkamai 67 dBA, 65 dBA ir 58 dBA. Magistraliniuose keliuose, kertančiuose Eigulių ir Šilainių seniūnijas, vidutinis transporto srautų intensyvumas dieną ir vakare buvo 5 kartus, naktį 6 kartus didesnis nei vidutinis srautų intensyvumas pagrindinėse gatvėse tuo pačiu metu, o krovininio autotransporto dalis dieną 3 kartus, o vakare 2 kartus viršijo vidutinius pagrindinių gatvių srautus. Nustatyta sąsaja tarp transporto srautų intensyvumo ir triukšmo lygio: Eigulių seniūnijos dienos koreliacijos koeficientas buvo 0,85, vakaro ir nakties – 0,83, o Šilainių seniūnijos – atitinkamai 0,78, 0,77 ir 0,80. Transporto srautų sudėties modeliavimo duomenimis, padidėjus krovininio transporto proporcijai 2 %, gatvėse, kuriose transporto srautas didesnis nei 300 aut./val., triukšmo lygis padidėtų 1,1 dBA, o kur transporto srautas mažesnis nei 200 aut./val., triukšmo lygis padidėtų 1,8 dBA (koreliacijos koeficientas – 0,63). Krovininio transporto įtaka akustinei taršai didesnė mikrorajonuose, kuriuose transporto srautai nedideli. Резюме Целью данной работы было изучить влияние грузового автотранспорта на акустическое загрязнение в микрорайонах города Каунаса, которые пересекают трассы государственного значения. Это шоссе Исландиос и объезд Вакаринис. Состав транспортного потока определялся и уровень шума измерялся около главных улиц микрорайонов. Результаты исследования показали, что средний уровень шума днем был 70 dBA, вечером – 68,6 dBA, ночью – 61,1 dBA. На трассах государственного значения, пересекающих микрорайоны, по сравнению с другими улицами потоки грузовых автомобилей были в 3 раза больше днем и 2 раза больше вечером. Установлена зaвисимость между величиной транспортного потока и шума (r = 0,77–0,85). Моделирование состава транспортного потока показало, что при увеличении на улицах грузового транспорта на 2% с 300 авт./час и больше шум увеличивается на 1,1 dBA, а при количестве грузового транспорта, составляющем 200 авт./час и меньше, шум возрастает на 1,8 dBA. Влияние грузового автотранспорта на акустическое загрязнение больше в микрорайонах с небольшим транспортным потоком.

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