Dynamic Material Flow Analysis of steel in Europe
Résumé
The growth of industrial activities, mass production, material consumption and re-source exhaustion is questioning the sustainability of our industrial system, consider-ing economic, environmental and social consequences. Study of anthropogenic metal flows contributes to better resource management, economic development and emission reduction. The study of metal stock accumulated in the society contributes to better resource management since the metal will be a part of end-of-life treatment in some time. In order to estimate the stock in use and future scrap availability dynamic approach of Material Flow Analysis (MFA) is used. It shows the evolution of the system through the time. The flow of obsolete products, issued from the stock in use, depends on the lifetime of products. This paper discusses about the first steps toward a complete DMFA model for any materials, in the EU 27 area, from 1945 to 2014. These first steps are presented con-sidering only steel. Steel has been chosen in a first place because its lifecycle is well known. It is assumed that numerous data are available regarding all the stages of its lifecycle. First, an overview of the steel lifecycle is made in order to define the different flows and the associated data that are needed to implement the model. From iron ore (mining in Europe and imported/exported) to scrap collection (in Europe and import-ed/exported), considering iron making, steel making, steel products making, goods manufacturing … the model needs a lot of data in terms of metric tones of steel be-tween the different stages of this lifecycle. Considering iron making, the model con-siders blast furnace and direct reduction. For steel making, the model considers oxy-gen blown converter, electric arc furnace and open-hearth furnace. Steel making in-cludes production of two categories: (1) casting of ingots, billets, blooms and slabs and (2) finished steel products that include coated sheets, cold rolled sheets, wire rods, hot rolled strips, merchant bars, quarto plates, reinforcing bars, heavy section bars and others. Then, manufacturing of goods stage includes construction, automo-tive industry, other transportations, mechanical engineering, domestic electrical equipment, tubes, metal goods and other. Then, once these data are identified, some values are determined thanks to statis-tical databases of European Steel Association Eurofer and WorldSteel Associations. Other data have to be estimated. Finally, a first implementation of the model is proposed for the period 1980-2013.