Material value chains in a fragmented world: modelling reconfigurations and trade strategies

The global basic material industries (e.g., steel, chemicals) are a crucial bottleneck in the transition towards climate neutrality. Renewable electricity and hydrogen can become a key enabler. However, as the renewable resources are distributed heterogeneously across locations, both the global supply chains and trade will likely reshape in the net-zero transition.^1,2 The resulting global geography of this future climate-neutral production remains uncertain. This uncertainty is further fuelled by an increasingly complex international trade landscape (e.g., geopolitical developments, trade frictions, carbon tariffs, industrial policy). Global shifts in material production in turn determine regional energy and infrastructure demands and associated regional transition bottlenecks.

To derive long-term transition pathways to climate neutrality for the globe, including for basic material industries, Integrated Assessment Models (IAMs) are the methodological standard. While the representation of international trade in IAMs has historically focused on primary energy carriers, more recently some modelling teams have introduced material trade in stylised “pool-trade” form (i.e., without bilateral routing and corridor constraints).³ However, a detailed representation of bilateral material trade flows is required to capture potential reconfigurations of global material supply chains and trade, while accounting for various trade frictions. Hence, there is no modelling framework that analyses the global energy and industry transformation, while accounting for a potential global reconfiguration of material supply chains and trade.

To address this gap, we present a proof-of-concept study for coupling a trade model for materials to an IAM. More concretely, we couple an Armington-CES structural gravity model to the REMIND material flow analysis (REMIND-MFA)⁴ of the IAM REMIND framework⁵. We (i) calibrate the model to historic bilateral trade flows, supply and demand, by adjusting behavioural parameters so that the model reproduces the data, then (ii) take regional supply and demand estimates from the REMIND energy supply system and the REMIND-MFA, respectively, (iii) calculate bilateral trade flows and material prices with the trade model and return them to REMIND. Crucially, transport costs are included as per-unit rates to conserve quantities, as opposed to iceberg costs – the common practice in Comuptable General Equilibrium (CGE modelling. Lastly, (iv) as the trade model enables us to also represent policy changes, geopolitical fragmentation and other modelled shocks, we analyse them and assess their impact on bilateral trade flows in comparison with the previous REMIND-MFA trade. At the conference we present the overall framework and a one-way coupled prototype for steel trade.

Figure: Overview of the linkages between the REMIND-MFA and the trade model

References

¹ Verpoort, P. C. Impact of global heterogeneity of renewable energy supply on heavy industrial production and green value chains. Nature Energy9, 491–503 (2024).

² Eicke, L. & Quitzow, R. Toward a Renewables-Driven Industrial Landscape: Evidence on investment decisions in the Chemical and Steel Sectors. Preprint at https://doi.org/10.21203/rs.3.rs-5519615/v1 (2025).

³ Ünlü, G. et al.MESSAGEix-Materials v1.1.0: representation of material flows and stocks in an integrated assessment model. Geosci. Model Dev.17, 8321–8352 (2024).

⁴ Dürrwächter, J., Hosak, M., Weiss, B. & Ueckerdt, F. Model documentation: REMIND-MFA framework. https://remind-mfa.readthedocs.io/.

⁵ Luderer, G. et al.Impact of declining renewable energy costs on electrification in low-emission scenarios. Nat Energy7, 32–42 (2022).