Improving material projections in Integrated Assessment Models: The use of a stock-based versus a flow-based approach for the iron and steel industry

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. (C) 2021 Published by Elsevier Ltd.

Automated summary

The steel industry plays a significant role in industrial energy consumption and greenhouse gas emissions. Existing energy models tend to use a flow-based approach for projecting steel demand, but a stock-based method using historical steel stock results proves to be a better indicator. The two approaches show large differences in steel demand projections for the second half of the 21st century, highlighting the importance of using the right approach to reduce emissions.