search
for
 About Bioline  All Journals  Testimonials  Membership  News


International Journal of Environment Science and Technology
Center for Environment and Energy Research and Studies (CEERS)
ISSN: 1735-1472
EISSN: 1735-1472
Vol. 13, No. 5, 2016, pp. 1235-1244
Bioline Code: st16117
Full paper language: English
Document type: Research Article
Document available free of charge

International Journal of Environment Science and Technology, Vol. 13, No. 5, 2016, pp. 1235-1244

 en An inland waterway traffic noise prediction model for environmental assessment in China
Dai, B. L.; Sheng, N.; He, Y. L.; Xu, J. M. & Zhu, A. F.

Abstract

This paper aimed at proposing an inland waterway traffic noise prediction model for environmental assessment in China. The study was the first to predict inland waterway traffic noise levels considering water surface condition and absorption influence in China. The analysis results indicated that the inland waterway traffic noise exposure levels can be influenced by water surface. The model was developed based on the Germany Schall 03 model by adding the water surface condition and absorption correction terms to the governing equations. Results showed that the predicted noise levels by the developed model correlated well with the measurements. In addition, the developed model had higher precision compared with the existing models such as the Schall 03 model, the modified US Federal Highway Administration (FHWA) model and the modified Germany Richtlinien für den Lärmschutz an Straßen (RLS 90) model. The proposed model can be utilized to assess inland waterway traffic noise exposure in China.

Keywords
Inland waterway; Schall 03 model; Vessel traffic noise; Water surface influence

 
© Copyright 2016 - Islamic Azad University (IAU)
Alternative site location: http://www.ijest.org

Home Faq Resources Email Bioline
© Bioline International, 1989 - 2024, Site last up-dated on 01-Sep-2022.
Site created and maintained by the Reference Center on Environmental Information, CRIA, Brazil
System hosted by the Google Cloud Platform, GCP, Brazil