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LOWNOISER

LOWering underwater NOISE Radiation from waterborne transport
Funder: European CommissionProject code: 101192302 Call for proposal: HORIZON-CL5-2024-D5-01
Funded under: HE | HORIZON-IA Overall Budget: 7,318,500 EURFunder Contribution: 6,330,920 EUR

LOWNOISER

Description

Underwater radiated noise (URN) by ships is one of main anthropogenic sources of noise in the marine environment. Transport by ship has been hailed as a green mean of transportation, at the same time, trapped under the water surface, the noise has been overlooked when considering the impact and the effects of human activities on marine species. On 11 March 24, a notice from the EC has been issued on the threshold values for the Marine Strategy Framework Directive 2008/56/EC. For continuous URN, the threshold for the habitat size of target species exceeding the Level of onset of Biologically adverse Effects (LOBE) has been set to 20%. While this notice does not set a specific limit for ship noise levels, it requires member states to evaluate the state of conservation of waters and take actions as needed. Many projects have brought to light that the marine environment is influenced by marine traffic to a level and in ways that were not obvious to predict. E.g. AQUO project has drawn attention to the effects on different marine species. SONIC looked into the noise generated by cavitating propeller. Both projects led to the development of a series of criteria to quantify the harmfulness of URN and measures to reduce it, though without demonstrating the measures in full scale. These projects were followed by PIAQUO and SATURN that have moved the focus towards regulating the noise emission of ships and implementing solutions for its reduction. The LOWNOISER project aims to bring the effort towards quieter ocean closer to reality than previous projects by showing the effectiveness of noise reduction solutions, i.e. technologies, measures and management strategies, that have a high TRL with full/large scale demonstrators. Also, the project is developing better tools for predicting URN, showing that noise reduction solutions are environmentally friendly in the sense of GHG emissions while being economically viable and safe.

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