Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Technology flexibility and sobriety to address shortage of energy-transition metals

Nature Sustainability (2026)Cite this article

Subjects

Abstract

A successful energy transition is crucial for mitigating climate change but may be hindered by bottlenecks in the availability of critical metals. The energy transition scenarios of the Intergovernmental Panel on Climate Change overlook such risks, proposing energy and transport pathways deemed unrealistic by past studies. Yet by relying on fixed market shares, those studies ignore the market’s ability to shift towards a (sub)technological mix requiring fewer supply-constrained metals. Here, for the most stringent decarbonization scenarios, we show that an optimized technology mix trims the list of metals constrained by mining capacities from 13 to copper, lithium and vanadium only. Key levers include substituting silver and gallium in solar technologies, prioritizing gearbox wind turbines and induction-motor electric vehicles without permanent magnets, and replacing part of the grid’s copper with aluminium. Sixteen other metals remain under pressure, but because over 90% of their demand stems from sectors outside the energy transition, our results underscore the need for economy-wide metallic sobriety.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Global cumulated metal demand from 2020 to 2050 per metal and economic sector aggregates, compared with estimated reserves and resources.
Fig. 2: Global yearly metal demand from 2020 to 2050 by economic sector, compared with mining capacity.
Fig. 3: Comparison of the market-share mix of cumulated installed power capacities required to meet the power-plant demand projected by IMAGE for the SSP1–26 scenario.
Fig. 4: Comparison of the market-share mix of EV motors required to meet the light-duty vehicle demand projected by IMAGE for the SSP1–26 scenario, combined with the estimated share of EVs from the announced pledges IEA scenario.
Fig. 5: Heatmaps comparing metal availability risks under different supply constraints in the initial scenario and the optimized scenario.
Fig. 6: Heatmap comparing metal availability risks under different supply constraints in the initial scenario and the optimized scenario.

Similar content being viewed by others

Data availability

Further information on this study is presented in Supplementary Information and in Supplementary Data 1 and 2. All additional data required to generate the code used in this paper are available via Zenodo (https://doi.org/10.5281/zenodo.15546387)27. The data generated by each IAM under SSP–RCP constraints were retrieved from the IIASA SSP database (https://iiasa.ac.at/models-tools-data/ssp). The IEA data on metal mining capacity and future grid and storage metal demand were extracted from the Critical Minerals Data Explorer (https://www.iea.org/data-and-statistics/data-tools/critical-minerals-data-explorer).

Code availability

IAM data under SSP–RCP constraints from the IIASA SSP database were compiled using the custom algorithm ‘IAM_Download_Data’, available via Zenodo. The subsequent analysis and optimization were performed with the algorithm ‘IAM_Techno_Optimisation’, available in the same Zenodo repository (https://doi.org/10.5281/zenodo.15546387)27. Data processing and analysis were conducted using Python (version 3.11.5), while optimization was carried out with Pyomo (version 6.6.2) using the CPLEX solver (version 12.10.0.0). In addition, an interactive application displaying results for all 110 models studied is publicly available via Streamlit at https://iam-metal-bottlenecks.streamlit.app/.

References

  1. IPCC Climate Change 2023: Synthesis Report (eds Core Writing Team, H. Lee and J. Romero) (IPCC, 2023).

  2. Global Critical Minerals Outlook 2024 (IEA, 2024); https://www.iea.org/reports/global-critical-minerals-outlook-2024

  3. Adoption of the Paris Agreement FCCC/CP/2015/L.9/Rev.1 (UNFCCC, 2015); https://unfccc.int/files/essential_background/convention/application/pdf/english_paris_agreement.pdf

  4. Deetman, S., De Boer, H., Van Engelenburg, M., Van Der Voet, E. & Van Vuuren, D. Projected material requirements for the global electricity infrastructure—generation, transmission and storage. Resour. Conserv. Recycl. 164, 105200 (2021).

    Article  CAS  Google Scholar 

  5. Wang, P. et al. Critical mineral constraints in global renewable scenarios under 1.5 ∘C target. Environ. Res. Lett. 17, 125004 (2022).

    Article  Google Scholar 

  6. Wang, S. et al. Future demand for electricity generation materials under different climate mitigation scenarios. Joule 7, 309–332 (2023).

    Article  CAS  Google Scholar 

  7. Rostami, F., Patrizio, P., Jimenez, L., Pozo, C. & Mac Dowell, N. Assessing the realism of clean energy projections. Energy Environ. Sci. 17, 5241–5259 (2024).

    Article  Google Scholar 

  8. Liang, Y., Kleijn, R., Tukker, A. & van der Voet, E. Material requirements for low-carbon energy technologies: a quantitative review. Renew. Sustain. Energy Rev. 161, 112334 (2022).

    Article  CAS  Google Scholar 

  9. Tokimatsu, K. et al. Energy modeling approach to the global energy–mineral nexus: a first look at metal requirements and the 2 ∘C target. Appl. Energy 207, 494–509 (2017).

    Article  Google Scholar 

  10. Watari, T. et al. Total material requirement for the global energy transition to 2050: a focus on transport and electricity. Resour. Conserv. Recycl. 148, 91–103 (2019).

    Article  Google Scholar 

  11. Schulze, K., Kullmann, F., Weinand, J. M. & Stolten, D. Overcoming the challenges of assessing the global raw material demand of future energy systems. Joule 8, 1936–1957 (2024).

    Article  Google Scholar 

  12. O’Neill, B. C. et al. The roads ahead: narratives for Shared Socioeconomic Pathways describing world futures in the 21st century. Glob. Environ. Change 42, 169–180 (2017).

    Article  Google Scholar 

  13. IPCC: Technical Summary. In Towards New Scenarios for Analysis of Emissions, Climate Change, Impacts, and Response Strategies (eds Moss, R. et al.) (IPCC, 2008).

  14. Harmsen, M. et al. Integrated assessment model diagnostics: key indicators and model evolution. Environ. Res. Lett. 16, 054046 (2021).

    Article  Google Scholar 

  15. Bauer, N. et al. Shared Socio-Economic Pathways of the energy sector—quantifying the narratives. Glob. Environ. Change 42, 316–330 (2017).

    Article  Google Scholar 

  16. Gambhir, A., Butnar, I., Li, P.-H., Smith, P. & Strachan, N. A review of criticisms of integrated assessment models and proposed approaches to address these, through the lens of BECCS. Energies 12, 1747 (2019).

    Article  CAS  Google Scholar 

  17. Pauliuk, S., Arvesen, A., Stadler, K. & Hertwich, E. G. Industrial ecology in integrated assessment models. Nat. Clim. Change 7, 13–20 (2017).

    Article  Google Scholar 

  18. Mineral Commodity Summaries 2025 v1.2 (USGS, 2025); https://doi.org/10.3133/mcs2025

  19. Kavlak, G., McNerney, J., Jaffe, R. L. & Trancik, J. E. Metal production requirements for rapid photovoltaics deployment. Energy Environ. Sci. 8, 1651–1659 (2015).

    Article  Google Scholar 

  20. Månberger, A. & Stenqvist, B. Global metal flows in the renewable energy transition: exploring the effects of substitutes, technological mix and development. Energy Policy 119, 226–241 (2018).

    Article  Google Scholar 

  21. Watari, T., McLellan, B., Ogata, S. & Tezuka, T. Analysis of potential for critical metal resource constraints in the International Energy Agency’s long-term low-carbon energy scenarios. Minerals 8, 156 (2018).

    Article  Google Scholar 

  22. Watari, T., Nansai, K. & Nakajima, K. Major metals demand, supply, and environmental impacts to 2100: a critical review. Resour. Conserv. Recycl. 164, 105107 (2021).

    Article  CAS  Google Scholar 

  23. Watari, T., Nansai, K. & Nakajima, K. Review of critical metal dynamics to 2050 for 48 elements. Resour. Conserv. Recycl. 155, 104669 (2020).

    Article  Google Scholar 

  24. Charpentier Poncelet, A. et al. Losses and lifetimes of metals in the economy. Nat. Sustain. 5, 717–726 (2022).

    Article  Google Scholar 

  25. Dong, H. et al. Sub-technology market share strongly affects critical material constraints in power system transitions. Nat. Commun. 16, 1285 (2025).

    Article  CAS  Google Scholar 

  26. Riahi, K. et al. The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Glob. Environ. Change 42, 153–168 (2017).

    Article  Google Scholar 

  27. Bieuville, P. Code - metal bottlenecks along energy transitions call for technology flexibility and sobriety. Zenodo https://doi.org/10.5281/zenodo.15546388 (2025).

  28. Lundaev, V., Solomon, A., Le, T., Lohrmann, A. & Breyer, C. Review of critical materials for the energy transition, an analysis of global resources and production databases and the state of material circularity. Miner. Eng. 203, 108282 (2023).

    Article  CAS  Google Scholar 

  29. Critical Minerals Data Explorer (IEA, accessed 8 October 2024); https://www.iea.org/data-and-statistics/data-tools/critical-minerals-data-explorer

  30. Yao, A., Benson, S. M. & Chueh, W. C. Critically assessing sodium-ion technology roadmaps and scenarios for techno-economic competitiveness against lithium-ion batteries. Nat. Energy 10, 404–416 (2025).

    Article  Google Scholar 

  31. Ayat, S., Wrobel, R., Baker, J. & Drury, D. A comparative study between aluminium and copper windings for a modular-wound IPM electric machine. In Proc. IEEE International Electric Machines and Drives Conference (IEMDC) 1–8 (IEEE, 2017).

  32. Grandell, L. & Thorenz, A. Silver supply risk analysis for the solar sector. Renew. Energy 69, 157–165 (2014).

    Article  CAS  Google Scholar 

  33. Grosjean, A., Soum-Glaude, A. & Thomas, L. Replacing silver by aluminum in solar mirrors by improving solar reflectance with dielectric top layers. Sustain. Mater. Technol. 29, e00307 (2021).

    CAS  Google Scholar 

  34. Pavel, C. C. et al. Substitution strategies for reducing the use of rare earths in wind turbines. Resour. Policy 52, 349–357 (2017).

    Article  Google Scholar 

  35. Nikkhah, H. et al. Challenges and opportunities of recovering lithium from seawater, produced water, geothermal brines, and salt lakes using conventional and emerging technologies. Chem. Eng. J. 498, 155349 (2024).

    Article  CAS  Google Scholar 

  36. Data Download and API: MineralsUK—Statistics (British Geological Survey, accessed 17 June 2021); https://www.bgs.ac.uk/mineralsuk/statistics/world-mineral-statistics/world-mineral-statistics-data-download/

  37. Commodity Statistics and Information (USGS, accessed 17 June 2021); https://www.usgs.gov/centers/nmic/commodity-statistics-and-information

  38. Wang, P. et al. Regional rare-earth element supply and demand balanced with circular economy strategies. Nat. Geosci. 17, 94–102 (2024).

    Article  Google Scholar 

  39. Roskill Information Services Rare Earths Outlook to 2030 20th edn (Roskill Information Services, 2021).

  40. Gómez, M., Li, J. & Zeng, X. Niobium: the unseen element—A comprehensive examination of its evolution, global dynamics, and outlook. Resour. Conserv. Recycl. 209, 107744 (2024).

    Article  Google Scholar 

  41. Sverdrup, H. U., Ragnarsdottir, K. V. & Koca, D. Aluminium for the future: modelling the global production, market supply, demand, price and long term development of the global reserves. Resour. Conserv. Recycl. 103, 139–154 (2015).

    Article  Google Scholar 

  42. Mohr, S., Giurco, D., Retamal, M., Mason, L. & Mudd, G. Global projection of lead–zinc supply from known resources. Resources 7, 17 (2018).

    Article  Google Scholar 

  43. Nassar, N. T., Graedel, T. E. & Harper, E. M. By-product metals are technologically essential but have problematic supply. Sci. Adv. 1, e1400180 (2015).

    Article  CAS  Google Scholar 

  44. Nassar, N. T., Lederer, G. W., Brainard, J. L., Padilla, A. J. & Lessard, J. D. Rock-to-metal ratio: a foundational metric for understanding mine wastes. Environ. Sci. Technol. 56, 6710–6721 (2022).

    Article  CAS  Google Scholar 

  45. European Commission: Raw materials demand for wind and solar PV technologies in the transition towards a decarbonised energy system. Joint Research Centre (2020).

  46. Magdalena, R., Valero, A. & Calvo, G. Limit of recovery: how future evolution of ore grades could influence energy consumption and prices for nickel, cobalt, and PGMs. Miner. Eng. 200, 108150 (2023).

    Article  CAS  Google Scholar 

  47. Seck, G. S., Hache, E. & Barnet, C. Potential bottleneck in the energy transition: the case of cobalt in an accelerating electro-mobility world. Resour. Policy 75, 102516 (2022).

    Article  Google Scholar 

  48. Edelenbosch, O. Y. et al. Decomposing passenger transport futures: comparing results of global integrated assessment models. Transp. Res. D 55, 281–293 (2017).

    Article  Google Scholar 

  49. Habib, K., Hansdóttir, S. T. & Habib, H. Critical metals for electromobility: global demand scenarios for passenger vehicles, 2015–2050. Resour. Conserv. Recycl. 154, 104603 (2020).

    Article  Google Scholar 

  50. Edmondson, J., Siddiqi, S. & Takahashi, M. Electric Motors for Electric vehicles 2025–2035: Technologies, Materials, Markets, and Forecasts (IDTechEx, 2024).

  51. Critical Materials: Batteries for Electric Vehicles (IRENA, 2024).

  52. Pedneault, J., Majeau-Bettez, G., Pauliuk, S. & Margni, M. Sector-specific scenarios for future stocks and flows of aluminum: an analysis based on Shared Socioeconomic Pathways. J. Ind. Ecol. 26, 1728–1746 (2022).

    Article  Google Scholar 

  53. Kermeli, K. et al. Improving material projections in Integrated Assessment Models: the use of a stock-based versus a flow-based approach for the iron and steel industry. Energy 239, 122434 (2022).

    Article  Google Scholar 

  54. Rostek, L., Pirard, E. & Loibl, A. The future availability of zinc: potential contributions from recycling and necessary ones from mining. Resour. Conserv. Recycl. Adv. 19, 200166 (2023).

    Google Scholar 

  55. Halada, K., Shimada, M. & Ijima, K. Decoupling status of metal consumption from economic growth. J. Jpn. Inst. Met. 71, 823–830 (2007).

    Article  CAS  Google Scholar 

  56. Global Material Resources Outlook to 2060: Economic Drivers and Environmental Consequences (OECD, 2019).

  57. García-Olivares, A. Substituting silver in solar photovoltaics is feasible and allows for decentralization in smart regional grids. Environ. Innov. Soc. Transit. 17, 15–21 (2015).

    Article  Google Scholar 

  58. Clean Energy Is Boosting Economic Growth (IEA, 2024); https://www.iea.org/commentaries/clean-energy-is-boosting-economic-growth

Download references

Acknowledgements

To support the mandate of Canada’s Net-Zero Advisory Body related to research, this project was undertaken with the financial support of the Government of Canada. Funding was provided through the Environmental Damages Funds’ Climate Action and Awareness Fund, administered by Environment and Climate Change Canada (grant NO. FDE-CA-2022g010). This research was also supported by the Collaborative Research and Training Experience in Sustainable Electronics and Eco-Design (CREATE SEED) programme at Polytechnique Montréal (P.B.). We express our gratitude to A. Immas (University of California, Berkeley) for his time and valuable insights regarding North American wind turbine technologies; to H. De Wachter (Polytechnique Montréal) for assistance with the optimization programming; and to T. Greffe (Université du Québec à Montréal) for sharing relevant resources on energy projections and mining production. This work is derived by P.B. from IEA material. P.B. is solely liable and responsible for this derived work. The derived work is not endorsed by the IEA in any manner.

Author information

Author notes

  1. These authors contributed equally: Guillaume Majeau-Bettez, Anne de Bortoli.

Authors and Affiliations

  1. CIRAIG, Department of Chemical Engineering, Polytechnique Montréal, Montreal, Québec, Canada

    Pénélope Bieuville, Guillaume Majeau-Bettez & Anne de Bortoli

  2. LVMT, École Nationale des Ponts et Chaussées, Institut Polytechnique de Paris, Champs-sur-Marne, France

    Anne de Bortoli

  3. Department of Strategy, Social and Environmental Responsibility, Université du Québec à Montréal (UQAM), Montreal, Québec, Canada

    Anne de Bortoli

Authors
  1. Pénélope Bieuville
    View author publications

    Search author on:PubMed Google Scholar

  2. Guillaume Majeau-Bettez
    View author publications

    Search author on:PubMed Google Scholar

  3. Anne de Bortoli
    View author publications

    Search author on:PubMed Google Scholar

Contributions

P.B., G.M.-B. and A.d.B. designed the research and interpreted the results. P.B. realized the data collection, developed the optimization code, calculated and visualized the results and wrote the paper, with inputs from G.M.-B. and A.d.B.

Corresponding author

Correspondence to Pénélope Bieuville.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Sustainability thanks Stephen Northey, Ester van der Voet and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Results 1.1–1.8, Discussion 2.1 and Methods 3.1–3.8.

Reporting summary

Supplementary Data 1

All data necessary to calculate metal demand, including metal demand from grid, storage and the rest of the economy; market shares and metal intensities of electric vehicles and energy sources; charging factors and energy source availability limitation.

Supplementary Data 2

All data necessary to calculate metal constraints, including mining capacity, recycling rate, reserves, resources and recovery rates, along with the full datasets underlying the figures in the article.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bieuville, P., Majeau-Bettez, G. & de Bortoli, A. Technology flexibility and sobriety to address shortage of energy-transition metals. Nat Sustain (2026). https://doi.org/10.1038/s41893-025-01762-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • DOI: https://doi.org/10.1038/s41893-025-01762-y

Search

Advanced search

Quick links

Nature Briefing Anthropocene

Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing: Anthropocene