Role of technology learning in the decarbonization of the iron and steel sector

The iron and steel sector is one of the most impacting for greenhouse gases emissions on a global level (from 7 to 9% yearly) and is also one of the hard-to-abate end-use sectors.

This activity aims at analyzing the impact that future investments in decarbonization-friendly technologies may have on their technological development, taking into account the uncertainty intrinsic to their correlation (called technology learning), and consequently, on the decarbonisation of the sector, combined with the presence of policies for the reduction of emissions on a global scale.

Using the EUROFusion TIMES Model (ETM) and a learning model based on the Wright curve, and having supposed different levels of learning, a series of ETM simulations are run. The results showed that a significant impact can be played by  such  phenomenon in the long term, as the decarbonization results particularly enhanced when the levels of learning are maximized for electrolysis and hydrogen-based processes, while CCS-based processes play only a marginal role in the short term.  Therefore, long-term investments on the former technologies are recommended, while further, policy-centered studies should be performed to understand the impact the latter can have in the short term.