Advertisement

Development of an inland waterway traffic noise prediction model considering water surface adsorption and embankment shielding influences

  • B. L. Dai
  • N. Sheng
  • Y. L. He
  • F. H. Mu
  • J. M. Xu
  • A. F. Zhu
Original Paper
  • 8 Downloads

Abstract

This paper proposed an improved prediction method of inland waterway vessel noise considering the effects of water surface adsorption and embankment shielding. The method was established on the basis of the UK Calculation of Road Traffic Noise (CoRTN) method, and the effects of water surface adsorption and embankment shielding were integrated into the governing equations. The developed method was validated using the data measured at the 40 monitoring points along Da Yunhe Channel in China. The results showed that the improved method had a higher accuracy and precision than that of the unmodified CoRTN method. The predicted noise exposure level by the unmodified CoRTN method correlated with the measured values with an R2 of 0.74569, which was enhanced to 0.86457 by the improved method. The current research is the prime to forecast river vessel noise level on the basis of the CoRTN method considering water surface adsorption and embankment shielding influences in China. It is expected that the modified method could be a new tool for estimating vessel noise effect on the inhabitant around the urban inland waterways.

Keywords

Vessel noise Water surface Embankment Inland waterway 

Notes

Acknowledgements

This research was supported by the Natural Science Foundation of Jiangsu Province of China (BK20160430), the Project Funded by China Postdoctoral Science Foundation (2016M591757), the Jiangsu Planned Projects for Postdoctoral Research Funds of China (1601179C), and Huaian Key Research and Development (Social Development) Program of China (HAS201601).

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.

References

  1. Ambrosio L, Iglesias L, Pascual V, Pedrero A, Rodriguez M, Diaz C, Gimenez MD (2014) A nonlinear mixed model for the assessment of traffic noise levels in urban areas. Stoch Environ Res Risk Assess 28:1085–1098Google Scholar
  2. Birk M, Ivina O, Klot S, Babisch W, Heinrich J (2011) Road traffic noise: self-reported noise annoyance versus GIS modelled road traffic noise exposure. J Environ Monitor 13:3237–3245CrossRefGoogle Scholar
  3. Bluhm G, Lindqvist M, Rosenlund M (2003) Road traffic noise exposure and myocardial infarction—a novel approach. In: The 9th international conference on urban transport and the environment in the 21st century, Iraklion, pp 385–392Google Scholar
  4. Charlotte C, Katarina P (2018) WHO environmental noise guidelines for the European region: a systematic review on environmental noise and quality of life, wellbeing and mental health. Int J Environ Res Public Health 15:2400CrossRefGoogle Scholar
  5. Dai BL, Sheng N, He YL, Xu JM, Zhu AF (2016) An inland waterway traffic noise prediction model for environmental assessment in China. Int J Environ Sci Technol 13:1235–1244CrossRefGoogle Scholar
  6. de Simon L (2016) Comparison of road traffic noise prediction models: CoRTN, TNM, NMPB, ASJ RTN. Acoust Aust 44:409–413CrossRefGoogle Scholar
  7. Dintrans A, Préndez M (2013) A method of assessing measures to reduce road traffic noise: a case study in Santiago, Chile. Appl Acoust 74:1486–1491CrossRefGoogle Scholar
  8. Givargis S, Mahmoodi M (2008) Converting the UK calculation of road traffic noise (CORTN) to a model capable of calculating L Aeq,1h for the Tehran’s roads. Appl Acoust 69:1108–1113CrossRefGoogle Scholar
  9. Golebiewski R, Makarewicz R, Nowak M, Preis A (2003) Traffic noise reduction due to the porous road surface. Appl Acoust 64:481–494CrossRefGoogle Scholar
  10. Guarnaccia C, Quartieri J, Barrios JM, Rodrigues ER (2014) Modeling environmental noise exceedances using non-homogeneous Poisson processes. J Acoust Soc Am 136:1631–1639CrossRefGoogle Scholar
  11. Iannone G, Guarnaccia C, Quartieri J (2013) Speed distribution influence in road traffic noise prediction. Environ Eng Manag J 12:493–501CrossRefGoogle Scholar
  12. Jakovjevic B, Paunovic K, Belojevic G (2009) Road—traffic noise and factors influencing noise annoyance in an urban population. Environ Int 35:552–556CrossRefGoogle Scholar
  13. Khan J, Ketzel M, Kakosimos K, Sorensen M, Jensen SS (2018) Road traffic air and noise pollution exposure assessment—a review of tools and techniques. Sci Total Environ 634:661–671CrossRefGoogle Scholar
  14. Li BG, Tao S, Dawson RW (2002) Evaluation and analysis of traffic noise from the main urban roads in Beijing. Appl Acoust 63:1137–1142CrossRefGoogle Scholar
  15. Liu Y, Xia B, Cui CY, Skitmore M (2017) Community response to construction noise in three central cities of Zhejiang province, China. Environ Pollut 230:1009–1017CrossRefGoogle Scholar
  16. Lui WK, Li KM, Ng PL, Frommer GH (2006) A comparative study of different numerical models for predicting train noise in high-rise cities. Appl Acoust 67:432–449CrossRefGoogle Scholar
  17. Mak CM, Leung WK, Jiang GS (2010) Measurement and prediction of road traffic noise at different building floor levels in Hong Kong. Build Serv Eng Res T 31:131–139CrossRefGoogle Scholar
  18. Morley DW, Gulliver J (2016) Methods to improve traffic flow and noise exposure estimation on minor roads. Environ Pollut 216:746–754CrossRefGoogle Scholar
  19. Naish D (2010) A method of developing regional road traffic noise management strategies. Appl Acoust 71:640–652CrossRefGoogle Scholar
  20. Nassiri P, Abbaspour M, Mahmoodi M, Givargis Sh (2007) A rail noise prediction model for the Tehran–Karaj commuter train. Appl Acoust 68:326–333CrossRefGoogle Scholar
  21. O’Malley V, King E, Kenny L, Dilworth C (2009) Assessing methodologies for calculating road traffic noise levels in Ireland—converting CRTN indicators to the EU indicators (L den, L night). Appl Acoust 70:284–296CrossRefGoogle Scholar
  22. Pamanikabud P, Tansatcha M, Brown AL (2008) Development of a highway noise prediction model using an Leq20s measure of basic vehicular noise. J Sound Vib 316:317–330CrossRefGoogle Scholar
  23. Sheng N, Zhou X, Zhou Y (2016) Environmental impact of electric motorcycles: evidence from traffic noise assessment by a building-based data mining technique. Sci Total Environ 554–555:73–82CrossRefGoogle Scholar
  24. Skarlatos D, Zakinthinos T (2007) A simplified model for urban traffic noise prediction. Noise Control Eng J 55:266–274CrossRefGoogle Scholar
  25. Tarrero AI, Martín MA, González J, Machimbarrena M, Jacobsen F (2008) Sound propagation in forests: a comparison of experimental results and values predicted by the Nord 2000 model. Appl Acoust 69:662–671CrossRefGoogle Scholar
  26. Tetsuya H, Yano T, Murakami Y (2017) Annoyance due to railway noise before and after the opening of the Kyushu Shinkansen Line. Appl Acoust 115:173–180CrossRefGoogle Scholar

Copyright information

© Islamic Azad University (IAU) 2019

Authors and Affiliations

  1. 1.Jiangsu Engineering Laboratory for Environment Functional Materials, Jiangsu Collaborative Innovation Center of Regional Modern Agriculture and Environmental Protection, School of Chemistry and Chemical EngineeringHuaiyin Normal UniversityHuaianPeople’s Republic of China
  2. 2.Department of Decision SciencesMacau University of Science and TechnologyTaipaPeople’s Republic of China
  3. 3.Faculty of Geosciences and Environmental EngineeringSouthwest Jiaotong UniversityChengduPeople’s Republic of China

Personalised recommendations