GreenTraC: Green Transition Policy Centre

The Green Transition Policy Centre (GreenTraC) is dedicated to developing a comprehensive theory of green transition policy, focusing on how policies can address the complexity and urgency of the advanced phase of the energy transition.

GreenTraC aims to uncover the causal relationships between key factors—such as political, institutional, and technological conditions—and their effects on green transition processes.

Rather than concentrating on single policy instruments, GreenTraC examines comprehensive packages of policy tools, known as policy mixes, which are applied to specific sectors. This approach acknowledges that addressing systemic changes—across technologies, infrastructure, behavior, and business models—requires coordinated and multifaceted efforts.

Our research focuses on policy mixes designed to decarbonize three key sectors where progress has been slow and rapid acceleration is critical: the agrifood sector, energy-intensive industries (e.g., cement and chemicals), and maritime transport across Denmark, Norway, and Sweden.

By analyzing these sectors, GreenTraC seeks to identify how well-designed policy mixes can facilitate faster emission reductions and promote sustainable practices in areas with high environmental impact

GreenTraC uses a mixed-method approach, combining in-depth qualitative case studies with advanced data science techniques to investigate green transition policies in Denmark, Sweden, and Norway.

By comparing policy mixes, we aim to identify patterns linking policy effectiveness to successful sustainability transitions. This includes examining how political, institutional, economic, and technological factors shape the adoption and success of these policies.

We also consider non-policy factors, such as market conditions, and use detailed case analysis to reveal mechanisms connecting these factors to effective policy adoption.

To support our findings, we employ data science techniques to track transition processes over time. A multi-source database will compile scientific, technological, industrial, and policy data from European sources, analyzed using natural language processing (NLP) and network analysis to map relationships and reconfigurations among key actors. This helps us quantify findings, isolate causal effects, and develop indicators for measuring green transitions across contexts.

• Ina Drejer, Professor (AAU)
• Christian Richter Østergaard, Professor (AAU)
• Roman Jurowetzki, Associate Professor (AAU)
• Christian Nielsen, Research Assistant (AAU)
• Daniel Hain, Associate Professor (AAU)
• Irene Ramos-Vielba, Residential Academic Fellow (DTU)
• Maria-Theresa Norn, Associate Professor (DTU)