Ugo Igere

AI-Driven Decision Support for Environmental Impact Assessment: Enhancing Scoping, Baseline Synthesis, and Consultation Analysis in UK Offshore Wind farms

The aim of my research is to explore the potential role and effectiveness of AI-driven tools to enhance the efficiency of Environmental Impact Assessment (EIA) processes for consenting offshore wind energy projects in the UK, with my areas of focus being Scoping, Baseline Synthesis and Consultation Analysis.

The United Kingdom is one of the world’s largest offshore wind markets, with more than twelve gigawatts of installed capacity and further rapid expansion underway.

Currently, there is no widely adopted AI system capable of synthesising baseline datasets, retrieving insights from past EIAs, or summarising public comments for UK offshore wind projects.

This PhD aims to fill this gap by contributing to digital transformation of EIA and supporting more efficient, consistent, and transparent offshore wind planning.

Names of Supervisors:

  • 1st Supervisor: Dr Enrico Tommarchi
  • 2nd Supervisor: Dr Sandra Costa Santos
Ugo Igere