scholarly journals Assessment of the masking effects of birdsong on the road traffic noise environment

2016 ◽  
Vol 140 (2) ◽  
pp. 978-987 ◽  
Author(s):  
Yiying Hao ◽  
Jian Kang ◽  
Heinrich Wörtche
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Noise Environment ◽  
The Road ◽  
On The Road

Social survey on the road traffic noise effect on the quality of life in Moroccan cities

2008 ◽  
Vol 123 (5) ◽  
pp. 3811-3811
Author(s):  
Weam Kharbaoui ◽  
Mohammed Garoum ◽  
Abdelaziz Bahoussa ◽  
Mohammed Rhachi
Keyword(s):  
Quality Of Life ◽  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
Social Survey ◽  
Noise Effect ◽  
The Road ◽  
On The Road

scholarly journals REVIEW ON THE ROAD TRAFFIC NOISE ASSESSMENT

2016 ◽  
Vol 22 (1) ◽  
Author(s):  
PETROVICI ALINA ◽  
TOMOZEI CLAUDIA ◽  
NEDEFF FLORIN ◽  
IRIMIA OANA ◽  
PANAINTE-LEHADUS MIRELA
Keyword(s):  
Urban Areas ◽  
Road Traffic ◽  
Traffic Noise ◽  
Legal Aspects ◽  
Urban Traffic ◽  
Road Traffic Noise ◽  
Action Plans ◽  
Noise Mapping ◽  
The Road ◽  
On The Road

<p>This paper presents a synthesis of current state of the assessment of road traffic noise in urban areas considering economic, social and legal aspects. Therefore, there were described several prediction methods of the urban traffic noise. These methods are useful in calculating the exposure of the population at noise levels which exceed the permissible limits. Mapping is one of the most common methods used for the assessment of noise. Whether it is industrial, airport, rail or road traffic noise, noise mapping provides accurate data needed later in developing action plans against noise. The road traffic noise assessments are performed periodically, and a representative picture of the noise in the analysed areas is obtained. Then, the action plans can be developed in order to reduce road traffic noise, where it is necessary.</p>

Windows Sound Insulation Research with Different Glass

2014 ◽  
Vol 584-586 ◽  
pp. 1868-1871
Author(s):  
Xiao Dong Lu ◽  
Jin Hong Wang ◽  
Wei Ling Wang
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Sound Insulation ◽  
Road Traffic Noise ◽  
Laminated Glass ◽  
Sound Sources ◽  
The Road ◽  
Insulation Effect ◽  
On The Road ◽  
Better Than

As the weak area of the residence envelope’s, window’s sound insulation is very important in the way of indoor quiet assurance. Base on the road traffic noise as sound sources, the sound insulation comparative studies is made between the insulating laminated glass and double insulated glass. The article choose two similar rooms near the Gaoerji road in Dalian assembled with the different windows, one room’s window was assembled with the insulating laminated glasses, and the other was assembled with double insulated glasses. Research shows that sound insulation effect of the wall with insulating laminated glass is better than the wall with double insulated glass 4dB.

scholarly journals The Psychological Effect of Visual and Auditory Stimuli on the Road Traffic Noise Perception

2008 ◽  
Vol 11 (1) ◽  
pp. 19-25 ◽  
Author(s):  
Gil-Soo Jang ◽  
Hoon Shin ◽  
Min-Jeong Song ◽  
Chan Kook
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Psychological Effect ◽  
Auditory Stimuli ◽  
Road Traffic Noise ◽  
The Road ◽  
On The Road

scholarly journals Dataset on the road traffic noise measurements in the municipality of Thessaloniki, Greece

Data in Brief ◽  
2020 ◽  
Vol 29 ◽  
pp. 105214 ◽  
Author(s):  
Paraskevi Begou ◽  
Pavlos Kassomenos ◽  
Apostolos Kelessis
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Road Traffic Noise ◽  
The Road ◽  
Noise Measurements ◽  
On The Road

scholarly journals REVIEW ON THE ROAD TRAFFIC NOISE ASSESSMENT

2016 ◽  
Vol 22 (1) ◽  
pp. 81-89
Author(s):  
ALINA PETROVICI ◽  
CLAUDIA TOMOZEI ◽  
FLORIN NEDEFF ◽  
OANA IRIMIA ◽  
MIRELA PANAINTE-LEHADUS
Keyword(s):  
Urban Areas ◽  
Road Traffic ◽  
Traffic Noise ◽  
Legal Aspects ◽  
Urban Traffic ◽  
Road Traffic Noise ◽  
Action Plans ◽  
Noise Mapping ◽  
The Road ◽  
On The Road

This paper presents a synthesis of current state of the assessment of road traffic noise in urban areas considering economic, social and legal aspects. Therefore, there were described several prediction methods of the urban traffic noise. These methods are useful in calculating the exposure of the population at noise levels which exceed the permissible limits. Mapping is one of the most common methods used for the assessment of noise. Whether it is industrial, airport, rail or road traffic noise, noise mapping provides accurate data needed later in developing action plans against noise. The road traffic noise assessments are performed periodically, and a representative picture of the noise in the analysed areas is obtained. Then, the action plans can be developed in order to reduce road traffic noise, where it is necessary.

scholarly journals Rapid Modeling Method for Road Traffic Noise Sources: A case study in Beijing

Noise Mapping ◽  
2015 ◽  
Vol 2 (1) ◽  
Author(s):  
L. Zhu ◽  
X. Li ◽  
C. Jiang ◽  
L. Liu ◽  
R. Wu ◽  
...  
Keyword(s):  
Road Traffic ◽  
Traffic Noise ◽  
Modeling Method ◽  
Model Parameters ◽  
Road Traffic Noise ◽  
Emission Model ◽  
Noise Sources ◽  
The Road ◽  
The Mean ◽  
Rapid Modeling

AbstractBased on the local road traffic conditions in Beijing, China, this contribution proposes a rapid modeling method for road traffic noise sources. Since establishing the standardized experiment fields are expensive, real roads are used to determine the road traffic noise emission model in the method. Due to the similarity in the urban structures in China and Japan, this paper uses the ASJ- 2013 model as a template and replaces its model parameters with the ones output by an optimization program which minimizes the sum of absolute errors between the predicted and the measured LAeq. Real road experiments are conducted to verify the effectiveness and feasibility of the modeling method. The mean error of the model deduced by the method and the ASJ-2013 model is respectively 0.4 dB and 2.6 dB, and the mean absolute error of the two models is respectively 1.1 dB and 2.6 dB. The results of the real road experiments show that the road traffic noise sources deduced by the method are more accurate to conduct local noise prediction than those of other models.

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