Anemoi

Investigation of chemical emissions from offshore wind farms

Direction Prof. Dr.-Ing. habil. Nils Goseberg Team Dr. Christian Windt   Niklas Czerner, M.Sc. Funding Interreg North Sea Duration 02/2023 - 01/2027 Project Partners Flanders Research Institute for Agriculture, Fisheries and Food (ILVO)   University of Antwerp   Royal Belgian Institute of Natural Sciences (RBINS)   SINTEF Ocean   Royal Netherlands Institute for Sea Research (NIOZ)   Bundesamt für Seeschifffahrt und Hydrographie (BSH)   French Research Institute for Exploitation of the Sea (Ifremer)   POM West-Vlaanderen   Helmholtz-Zentrum Hereon   Technical University of Denmark (DTU)

Brief descritpion

The Anemoi project studies the chemical emissions from offshore wind farms (OWFs) and their impact on ecosystems and aquaculture. Along with the expansion of OWFs in the North Sea, the environmental impact of OWFs is routinely monitored by assessing the effect of novel habitat introduction, the exclusion of fisheries or the introduction of energy.  However, the possible contamination of the marine environment by dissolved and particulate pollutants, e.g. due to corrosion protection systems, is largely overlooked.

As such, Anemoi aims to:

1. identify relevant chemical emissions from OWFs,

2. assess the effect on ecosystem and aquaculture activities,

3. propose solutions and opportunities to reduce chemical emissions from OWFs.

To assess the chemical emissions associated with OWFs, sediment, water and biota samples will be taken at and near OWFs. The impact of chemical contaminants detected on site will be evaluated and current knowledge gaps will be addressed. In consultation with stakeholders, approaches to reduce chemical emissions will be proposed. Current gaps in the legislation will be addressed on an international level. At the Leichtweiß- Institute, the distribution of particulate emissions in the vicinity of offshore wind structures will be investigated in the wave-current flume. Additionally, the distribution of chemical contaminants on a regional scale will be modelled with the help of numerical models.