Improving material projections in Integrated Assessment Models: The use of a stock-based versus a flow-based approach for the iron and steel industry. (15th January 2022)

• Record Type: Journal Article
• Authors: Kermeli, Katerina; Edelenbosch, Oreane Y.; Crijns-Graus, Wina; van Ruijven, Bas J.; van Vuuren, Detlef P.; Worrell, Ernst
• Is Part Of: Energy. Volume 239:Part E(2022)
• Publication Date: 2022-01-15
• Subjects: Integrated assessment models -- Long-term energy models -- Steel industry -- Steel demand -- Steel stocks; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2021.122434
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The steel industry is responsible for a large share of the industrial energy consumption and greenhouse gas emissions and several long-term energy models have some representation of this sub-sector. It is found that models, commonly use a flow-based approach for projecting steel demand neglecting that in-use steel stocks serve as a better demand indicator than steel consumption. A stock-based method that uses the historical steel stock results from detailed material flow analysis is developed for making steel demand projections and implemented in the IMAGE Integrated Assessment Model. Large differences between the two approaches arise. For the first half of the 21st century, global steel demand increases with both approaches and at a similar rate to reach 2300 Mt/yr by 2050. For the second half of the 21st century, however, the developments differ drastically. With the stock-based approach, global steel demand decreases by 0.8%/a to reach 1600 Mt/yr, while with the flow-based approach it increases by 0.3%/a to reach 2600 Mt/yr in 2100. Given that steel production levels have a profound contribution to greenhouse gas emissions, using the right approach is crucial. This means that long-term energy models may currently overestimate the industrial emissions in the last half of the century. Highlights: Energy models do not use the true steel demand driver for making steel projections. Energy models can profit from material flow analysis on steel stocks to improve their material projections. Steel demand in 2100 is 75% lower when a stock-based instead of a flow-based approach is used.