How physical modelling can improve Life Cycle Inventory accuracy and allow predictive LCA: an application to the steel industry

摘要

Assessing traditional iron and steelmaking processes from an environmental point of view and developing breakthrough eco-effieient processes for the future are major challenges for the steel industry today. In the framework of the challenging European project ULCOS, which stands for Ultra Low CO_2 Steelmaking, Life Cycle Assessment (LCA) was chosen to assess breakthrough processes that could be port of the future iron and steel making landscape and to compare them to the reference classical integrated steelmill. To carry out such a study we propose a new methodological concept which combines LCA thinking with physicochemical process modelling. Physicochemical models were developed for each processes of the classical integrated steelmaking route in order to generate the data required to draw the Life Cycle Inventory of the route. Such a method bypasses the traditional data collection and brings accuracy to the inventory by introducing rigorous mass and energy balances into the methodology. In addition it was shown that such an approach allows testing and assessing different operational practices of the processes in order to optimise the use of energy and the CO_2 emissions, which shewed that it can be used as a powerful tool for eco-conception of processes.