Modeling of road traffic noise and traffic flow measures to reduce noise exposure in Antalya metropolitan municipality

  • Mustafa Ece
  • İsmail Tosun
  • Kamil Ekinci
  • Nazlı S. Yalçindağ
Research Article
  • 2 Downloads

Abstract

Background

Road traffic noise influencing directly public health in the modern cities is a growing problem in both developing and developed countries. The objective of this study was to model traffic-induced noise in Antalya province, validate the model with noise emission data, and to run the model for the noise preventive scenarios.

Methods

In this study, modeling of traffic-induced noise was performed using SoundPLAN® software at Gazi Boulevard in the city of Antalya. Calculations were made according to NMPB-Routes 96, which have been accepted by environmental noise legislation of the European Union and Turkey. Fundamental data sets such as geographical, topographical and meteorological data, building information and population, traffic network, traffic volume and vehicle speed, and composition of types of vehicle were utilized for the development of noise prediction model. Eight preventive scenarios to reduce traffic-induced noise levels were simulated using the validated model considering traffic flow measures such as types of vehicles, vehicle speeds, types of road surface, redirecting portion of heavy vehicles to alternative routes and noise barrier usage.

Results

Results showed that increase in heavy vehicle speeds in smooth road surface conditions caused more increase in exposures than that of light vehicle speed. It was highlighted that it would be appropriate to use porous road surface to reduce exposures on population on high-speed roads. Furthermore, the number of people that are exposed to noise is significantly reduced by precautions such as alternative routes for heavy vehicles and speed restriction. These precautions reduced noise exposures by 25.5–63.8%. The results showed that the usage of noise barrier at the alternative routes in case of porous asphalt road reduced population, dwellings, and area exposed to traffic noise which is greater than 75 dB(A) as 63.8, 40.5, and 60.0%, respectively.

Conclusion

It could be concluded that the outcomes of the noise prediction models based on the generated scenarios could be used for the purpose of decision support system and could be helpful for decision-makers on the noise legislations.

Keywords

Road traffic noise Noise mapping Traffic flow measures Noise modeling software 

Notes

Acknowledgements

We wish to thank for the technical assistance of Nesimi Özkurt and Deniz Sarı.

Authors’ contributions

Mustafa Ece, İsmail Tosun and Nazlı S. Yalçindağ conceived and designed the experiments. Mustafa Ece and Nazlı S. Yalçindağ performed the experiments. Kamil Ekinci analyzed the data and reviewed the relevant literature. All authors read and approved the final manuscript.

Compliance with ethical standards

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Environmental Protection and Control DepartmentAntalya Metropolitan MunicipalityAntalyaTurkey
  2. 2.Faculty of Engineering, Department of Environmental EngineeringSuleyman Demirel UniversityIspartaTurkey
  3. 3.Faculty of Agriculture, Department of Agricultural Machinery and Technologies EngineeringSuleyman Demirel UniversityIspartaTurkey

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