With the European Union targeting a 55% reduction in greenhouse gas (GHG) emissions by 2030, the shift to renewable energy sources like offshore wind is crucial. Another consequence of the 55% reduction goal is the new upcoming registration and levy on carbon emissions. Since there is a noticeable lack of research on the emissions from the installation offshore wind farms, and marine contractors will have to pay for those emissions in the near future, there is a need for a framework to predict those emissions prior to the installation process. This thesis aims to develop such a framework to predict GHG emissions during the installation process using Wind Turbine Installation Vessels (WTIVs).

The study starts with a review of current methods for calculating maritime GHG emissions, following the EU Emissions Trading System (ETS) guidelines. It then looks at the steps and technology involved in offshore wind farm installations, pinpointing the main energy consumers. Using a physics-based approach, the model estimates fuel consumption and the the GHG emissions for the installation of wind turbines for an offshore wind farm.

For the complete installation of 50 wind turbines, the model predicts a total effective energy requirement of approximately 408,000 kWh, leading to GHG emissions of around 312,533 kg CO2.
The results highlight the significant impact of activities like vessel transit and auxiliaries on total emissions. The sensitivity analysis performed identifies critical parameters influencing the model's accuracy, such as vessel speed, jack-up height, and crane efficiency. The model's validation through a real-world case study for the crane part of the developed model shows its accuracy in predicting emissions.

The thesis ends with suggestions for improving the model and finding ways to reduce emissions in offshore wind installations. This involves the validation of the other aspects of the model, technology upgrades, and checking if feedering might me an interesting solution to reduce the impact on the environment even more.

Overall the developed model for the prediction of greenhouse gas emissions proves to be a stable framework that could be used in the future by marine contractors when negotiating contracts and installation costs, including the predicted costs of the carbon levy.