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Inland waterway traffic noise prediction model: a comparison

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Abstract

Vessel noise pollution in inland waterways can have negative impacts on human health in urban areas. Thus, it is important to evaluate the vessel noise exposure level, in order to take effective measures to protect the urban environment and human health. The aims of this research were (a) to summarize current application tools on modeling and estimating exposure levels for traffic noise pollution in inland waterways; (b) to compare the existing inland waterway traffic noise prediction and evaluation models in terms of their associated strengths and weaknesses, influence factors, simulation accuracy, and application scope. The research reviews the literature with regard to the regression models for estimating traffic noise exposure in inland waterways, including the modified FHWA, RLS 90, Schall 03, CoRTN and Nord 2000 models. The sections providing these models are independent, with establishment principles, fundamental equations, and noise attenuation influencing factors included. The factors that may affect the accuracy of these models—source emission, propagation path, channel characteristics, and other factors are analyzed. Water surface absorption and embankment shielding, especially, are recognized as key factors influencing the attenuation of vessel traffic noise. The simulation accuracy and reliability of the models are then discussed. It was found that all these models produce good agreement with the surveyed results. Special attention is paid to comparing vessel noise prediction and evaluation tools, and to informal alternative schemes for the reduction of the negative influences of inland waterway vessel noise on human beings and the urban environment.

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References

  • Badino A, Borelli D, Gaggero T, Rizzuto E, Schenone C (2012) Noise emitted from ships: impact inside and outside the vessels. Procedia - Soc Behav Sci 48:868–879

    Google Scholar 

  • Badino A, Borelli D, Gaggero T, Rizzuto E, Schenone C (2016) Airborne noise emissions from ships: experimental characterization of the source and propagation over land. Appl Acoust 104:158–171

    Google Scholar 

  • Blair BD, Brindley S, Hughes J, Dinkeloo E, McKenzie LM, Adgate JL (2018) Measuring environmental noise from airports, oil and gas operations, and traffic with smartphone applications: laboratory and field trials. J Expo Sci Env Epid 28:548–558

    Google Scholar 

  • Bolognese M, Fidecaro F, Palazzuoli D, Licitra G (2020) Port noise and complaints in the North Tyrrhenian Sea and framework for remediation. Environments 7:17

    Google Scholar 

  • Breeze H, Li SH, Marotte EC, Thenault JA, Wingfield J, Xu JS (2021) Changes in underwater noise and vessel traffic in the approaches to Halifax Harbor, Nova Scotia Canada. Front Mar Sci 8:674788

    Google Scholar 

  • Brown A (2018) Underwater radiated noise of ships. Int J Acoust Vib 23:422–422

    Google Scholar 

  • Bunn F, Zannin PHT (2016) Assessment of railway noise in an urban setting. Appl Acoust 104:16–23

    Google Scholar 

  • Chang TY, Lin HC, Yang WT, Bao BY, Chan CC (2012) A modified Nordic prediction model of road traffic noise in a Taiwanese city with significant motorcycle traffic. Sci Total Environ 432:375–381

    CAS  Google Scholar 

  • Dai BL, He YL, Mu FH, Xu N, Wu Z (2014) Development of a traffic noise prediction model on inland waterway of China using the FHWA. Sci Total Environ 482–483:480–485

    Google Scholar 

  • Dai BL, He YL, Xu JM, Xu N, Wu Z, Deng YF (2015) Applying the RLS 90 to develop an inland waterway traffic noise prediction model in China that considers water surface influence. J Low Freq Noise V A 34:73–96

    CAS  Google Scholar 

  • 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 13:1235–1244

    Google Scholar 

  • Dai BL, Sheng N, He YL, Mu FH, Xu JM, Zhu AF (2019) Development of an inland waterway traffic noise prediction model considering water surface adsorption and embankment shielding influences. Int J Environ Sci Technol 16:5927–5936

    Google Scholar 

  • Dai BL, Sheng N, Zhao W, Mu FH, He YL (2020) Evaluation of urban inland waterway traffic noise using a modified Nord 2000 prediction model. Environ Res 185:109437

    CAS  Google Scholar 

  • Das A (2011) Shallow ambient noise variability due to distant shipping noise and tide. Appl Acoust 72:660–664

    Google Scholar 

  • de Lisle S (2016) Comparison of road traffic noise prediction models: CoRTN, TNM, NMPB, ASJ RTN. Acoust Aust 44:409–413

    Google Scholar 

  • Delgado-Hidalgo L, Nachtmann H (2020) A heuristic approach to managing inland waterway disruption. Eng Manag J 33:2–14

    Google Scholar 

  • Enguix IF, Egea MS, González AG, Serrano DA (2019) Underwater acoustic impulsive noise monitoring in port facilities: case study of the port of Cartagena. Sensors 19:4672

    Google Scholar 

  • Franěk M, Režný L, Šefara D, Cabal J (2018) Effect of traffic noise and relaxations sounds on pedestrian walking speed. Int J Environ Res Publ Health 15:752

    Google Scholar 

  • Fredianelli L, Nastasi M, Bernardini M, Fidecaro F, Licitra G (2020) Pass-by characterization of noise emitted by different categories of seagoing ships in ports. Sustainability 12:12051740

    Google Scholar 

  • Garg N, Maji S (2014) A critical review of principal traffic noise models: strategies and implications. Environ Impact Assess Rev 46:68–81

    Google Scholar 

  • Garg N, Mangal SK, Saini PK, Dhiman P, Maji S (2015) Comparison of ANN and analytical models in traffic noise modeling and predictions. Acoust Aust 43:179–189

    Google Scholar 

  • Givargis SH, Mahmoodi M (2008) Converting the UK calculation of road traffic noise (CORTN) to a model capable of calculating LAeq, 1h for the Tehran’s roads. Appl Acoust 69:1108–1113

    Google Scholar 

  • Gozalo GR, Escobar VG (2021) Uncertainty evaluation of road traffic noise models in two Ibero-American cities. Appl Acoust 180:108134

    Google Scholar 

  • Heitmeyer RM, Wales SC, Pflug LA (2003) Shipping noise predictions: capabilities and limitations. Mar Technol Soc J 37:54–65

    Google Scholar 

  • Khan J, Ketzel M, Kakosimos K, Sørensen M, Jensen SS (2018) Road traffic air and noise pollution exposure assessment—A review of tools and techniques. Sci Total Environ 634:661–676

    CAS  Google Scholar 

  • King EA, Murphy E, McNabola A (2009) Reducing pedestrian exposure to environmental pollutants: a combined noise exposure and air quality analysis approach. Transport Res D: Tr E 14:309–316

    Google Scholar 

  • Kumar P (2021) Traffic noise prediction and optimization using response surface method (RSM). Arab J Geosci 14:2181

    Google Scholar 

  • Lam WHK, Tam ML (1998) Reliability analysis of traffic noise estimates in Hong Kong. Transport Res D: Tr E 3:239–248

    Google Scholar 

  • Lan YL, Roberts H, Kwan MP, Helbich M (2020) Transportation noise exposure and anxiety: a systematic review and meta-analysis. Environ Res 191:110118

    CAS  Google Scholar 

  • Leeuwen ven HJA (2000) Railway noise prediction models: a comparison. J Sound Vib 231:975–987

    Google Scholar 

  • Li T, Burdisso R, Sandu C (2018) Literature review of models on tire-pavement interaction noise. J Sound Vib 420:357–445

    Google Scholar 

  • Licitra G, Fredianelli L, Petri D, Vigotti MA (2016) Annoyance evaluation due to overall railway noise and vibration in Pisa urban areas. Sci Total Environ 568:1315–1325

    CAS  Google Scholar 

  • Ligtelijn D, Nojiri T, Walsh R, Wittekind D (2014) A review of practical methods for reducing underwater noise pollution from large commercial vessels. Int J Marit Eng 156:203–206

    Google Scholar 

  • 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 67:432–449

    Google Scholar 

  • Mansourkhaki A, Haghiri M, Berangi M (2021) A modified noise-prediction model for highways with significant motorcycle traffic. P I Civil Eng-Transp 174:239–247

    Google Scholar 

  • Marquis-Favre C, Gille L-A, Breton L (2021) Combined road traffic, railway and aircraft noise sources: Total noise annoyance model appraisal from field data. Appl Acoust 180:108127

    Google Scholar 

  • Morel J, Marquis-Favre C, Gille L-A (2016) Noise annoyance assessment of various urban road vehicle pass-by noises in isolation and combined with industrial noise: a laboratory study. Appl Acoust 101:47–57

    Google Scholar 

  • Morillas JMB, Gozalo GR, Montes-Gonzalez D, Vilchez-Gomez R, Escobar VG (2021) Variability of traffic noise pollution levels as a function of city size variables. Environ Res 199:111303

    Google Scholar 

  • Morley DW, de Hoogh K, Fecht D, Fabbri F, Bell M, Goodman PS, Elliott P, Hodgson S, Hansell AL, Gulliver J (2015) International scale implementation of the CNOSSOS-EU road traffic noise prediction model for epidemiological studies. Environ Pollut 206:332–341

    CAS  Google Scholar 

  • Murphy E, King EA (2014) An assessment of residential exposure to environmental noise at a shipping port. Environ Int 63:207–215

    Google Scholar 

  • Pang FZ, Wu C, Miao XH, Song HB (2015) Transferred boundary similarity method and application to the prediction of ship vibration and radiated noise. Noise Control Eng J 63:318–330

    Google Scholar 

  • Paschalidou AK, Kassomenos P, Chonianaki F (2019) Strategic noise maps and action plans for the reduction of population exposure in a Mediterranean port city. Sci Total Environ 654:144–153

    CAS  Google Scholar 

  • Rodríguez-Díaz A, Adenso-Díaz B, González-Torre PL (2017) A review of the impact of noise restrictions at airports. Transport Res D: Tr E 50:144–153

    Google Scholar 

  • Ross D (2005) Ship sources of ambient noise. IEEE J Oceanic Eng 30:257–261

    Google Scholar 

  • Sezen S, Atlar M, Fitzsimmons P, Sasaki N, Tani G, Yilmaz N, Aktas B (2020) Numerical cavitation noise prediction of a benchmark research vessel propeller. Ocean Eng 211:107549

    Google Scholar 

  • Singh D, Nigam SP, Agrawal VP, Kumar M (2016) Vehicular traffic noise prediction using soft computing approach. J Environ Manage 183:59–66

    Google Scholar 

  • Singh D, Nigam SP, Agrawal VP, Kumar M (2018) Modelling of urban traffic noise using a systems approach. P. I. Civil Eng-Transp 171:235–244

    Google Scholar 

  • Tao YH, Kou LR, Chai YW, Kwan M-P (2021) Associations of co-exposures to air pollution and noise with psychological stress in space and time: a case study in Beijing. China Environ Res 196:110399

    CAS  Google Scholar 

  • Thompson R, Smith RB, Karim YB, Shen C, Drummond K, Teng C, Toledano MB (2022) Noise pollution and human cognition: an updated systematic review and meta-analysis of recent evidence. Environ Int 158:106905

    Google Scholar 

  • Veber T, Tamm T, Rundva M, Kriit HK, Pyko A, Orru H (2022) Health impact assessment of transportation noise in two Estonian cities. Environ Res 204:112319

    CAS  Google Scholar 

  • Weryk M, Kozaczka E, Grelowska G (2015) Study of noise propagation for small vessels. Arch Acoust 40:267–272

    Google Scholar 

  • Yan XW, Song H, Peng ZL, Kong HM, Cheng YP, Han LJ (2021) Review of research results concerning the modelling of shipping noise. Pol Marit Res 28:102–115

    Google Scholar 

  • Yang WJ, Cai M, Luo P (2020) The calculation of road traffic noise spectrum based on the noise spectral characteristics of single vehicles. Appl Acoust 160:107128

    Google Scholar 

  • Zhao N, Prieur JF, Liu Y, Kneeshaw D, Lapointe EM, Paquette A, Zinszer K, Dupras J, Villeneuve PJ, Rainham DG, Lavigne E, Chen H, van den Bosch M, Oiamo T, Smargiassi A (2021) Tree characteristics and environmental noise in complex urban settings—A case study from Montreal Canada. Environ Res 202:111887

    CAS  Google Scholar 

  • Zheng Y, Jiang B, Yang G (2020) Simulation of dynamic ship radiated noise signal. The 15th IEEE International Conference on Signal Processing (ICSP), Beijing, China, pp. 636–639

  • ZoBell VM, Frasier KE, Morten JA, Hastings SP, Reeves LEP, Wiggins SM, Hildebrand JA (2021) Underwater noise mitigation in the Santa Barbara Channel through incentive-based vessel speed reduction. Sci Rep 11:18391

    CAS  Google Scholar 

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Acknowledgements

This work was supported by the Jiangsu Key Research and Development (R&D) Projects (Social Development, BE2020772), Huaian Natural Science Research Program (HAB202157) and Natural Science Major Foundation of the Jiangsu Higher Education Institutions of China (22KJA610002).

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Authors and Affiliations

  1. Jiangsu Key Laboratory for Chemistry of Low-Dimensional Materials, School of Chemistry and Chemical Engineering, Huaiyin Normal University, Huaian, 223300, People’s Republic of China

    B. L. Dai, J. Huang, F. H. Mu, X. Chen, T. Li & J. M. Xu

  2. Department of Decision Sciences, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, 999078, People’s Republic of China

    N. Sheng

  3. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 610031, People’s Republic of China

    Y. L. He

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  1. B. L. Dai
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Dai, B.L., Sheng, N., Huang, J. et al. Inland waterway traffic noise prediction model: a comparison. Int. J. Environ. Sci. Technol. 21, 2007–2016 (2024). https://doi.org/10.1007/s13762-023-05009-1

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