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ZENODO
Dataset . 2018
License: CC 0
Data sources: ZENODO
DRYAD
Dataset . 2018
License: CC 0
Data sources: Datacite
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Data from: Modelling of ships as a source of underwater noise

Authors: Jalkanen, Jukka-Pekka; Johansson, Lasse; Liefvendahl, Mattias; Bensow, Rickard; Sigray, Peter; Östberg, Martin; Karasalo, Ilkka; +3 Authors

Data from: Modelling of ships as a source of underwater noise

Abstract

In this paper, a methodology is presented for modelling underwater noise emissions from ships based on realistic vessel activity in the Baltic Sea region. This paper combines the Wittekind noise source model with the Ship Traffic Emission Assessment Model (STEAM) in order to produce regular updates for underwater noise from ships. This approach allows the construction of noise source maps, but requires parameters which are not commonly available from commercial ship technical databases. For this reason, alternative methods were necessary to fill in the required information. Most of the parameters needed contain information that is available during the STEAM model runs, but features describing propeller cavitation are not easily recovered for the world fleet. Baltic Sea ship activity data were used to generate noise source maps for commercial shipping. Container ships were recognized as the most significant source of underwater noise, and the significant potential for an increase in their contribution to future noise emissions was identified.

Underwater noise energy emissions from the Baltic Sea fleet during 2015A methodology was developed for describing the underwater noise emissions from ships. These files contain noise source maps in netcdf format, which contain daily emissions of underwater noise in three frequency bands (63, 125 and 2000 Hz)Jalkanen_et_al_Ocean_Science_14_2018_1_Noisemaps.zip

Keywords

Shipping, Baltic Sea, AIS, emissions, Ship Traffic Emission Assessment Model, Underwater noise, Full year 2015

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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