IDEAS home Printed from https://ideas.repec.org/a/spr/minecn/v30y2017i3d10.1007_s13563-017-0119-6.html
   My bibliography  Save this article

Assessment of critical minerals: updated application of an early-warning screening methodology

Author

Listed:
  • Erin McCullough

    (National Mineral Information Center, U.S. Geological Survey)

  • Nedal T. Nassar

    (National Mineral Information Center, U.S. Geological Survey)

Abstract

Increasing reliance on non-renewable mineral resources reinforces the need for identifying potential supply constraints before they occur. The US National Science and Technology Council recently released a report that outlines a methodology for screening potentially critical minerals based on three indicators: supply risk (R), production growth (G), and market dynamics (M). This early-warning screening was initially applied to 78 minerals across the years 1996 to 2013 and identified a subset of minerals as “potentially critical” based on the geometric average of these indicators—designated as criticality potential (C). In this study, the screening methodology has been updated to include data for 2014, as well as to incorporate revisions and modifications to the data, where applicable. Overall, C declined in 2014 for the majority of minerals examined largely due to decreases in production concentration and price volatility. However, the results vary considerably across minerals, with some minerals, such as gallium, recording increases for all three indicators. In addition to assessing magnitudinal changes, this analysis also examines the significance of the change relative to historical variation for each mineral. For example, although mined nickel’s R declined modestly in 2014 in comparison to that of other minerals, it was by far the largest annual change recorded for mined nickel across all years examined and is attributable to Indonesia’s ban on the export of unprocessed minerals. Based on the 2014 results, 20 minerals with the highest C values have been identified for further study including the rare earths, gallium, germanium, rhodium, tantalum, and tungsten.

Suggested Citation

  • Erin McCullough & Nedal T. Nassar, 2017. "Assessment of critical minerals: updated application of an early-warning screening methodology," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 30(3), pages 257-272, October.
  • Handle: RePEc:spr:minecn:v:30:y:2017:i:3:d:10.1007_s13563-017-0119-6
    DOI: 10.1007/s13563-017-0119-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13563-017-0119-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13563-017-0119-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Roelich, Katy & Dawson, David A. & Purnell, Phil & Knoeri, Christof & Revell, Ruairi & Busch, Jonathan & Steinberger, Julia K., 2014. "Assessing the dynamic material criticality of infrastructure transitions: A case of low carbon electricity," Applied Energy, Elsevier, vol. 123(C), pages 378-386.
    2. Rosenau-Tornow, Dirk & Buchholz, Peter & Riemann, Axel & Wagner, Markus, 2009. "Assessing the long-term supply risks for mineral raw materials--a combined evaluation of past and future trends," Resources Policy, Elsevier, vol. 34(4), pages 161-175, December.
    3. Renaud Coulomb & Simon Dietz & Maria Godunova & Thomas Bligaard Nielsen, 2015. "Critical Minerals Today and in 2030: An Analysis for OECD Countries," OECD Environment Working Papers 91, OECD Publishing.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Brown, Teresa, 2018. "Measurement of mineral supply diversity and its importance in assessing risk and criticality," Resources Policy, Elsevier, vol. 58(C), pages 202-218.
    2. Schnebele, Emily & Jaiswal, Kishor & Luco, Nicolas & Nassar, Nedal T., 2019. "Natural hazards and mineral commodity supply: Quantifying risk of earthquake disruption to South American copper supply," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    3. Kim, Juhan & Lee, Jungbae & Kim, BumChoong & Kim, Jinsoo, 2019. "Raw material criticality assessment with weighted indicators: An application of fuzzy analytic hierarchy process," Resources Policy, Elsevier, vol. 60(C), pages 225-233.
    4. Hayes, Sarah M. & McCullough, Erin A., 2018. "Critical minerals: A review of elemental trends in comprehensive criticality studies," Resources Policy, Elsevier, vol. 59(C), pages 192-199.
    5. Vidal, Rosario & Alberola-Borràs, Jaume-Adrià & Mora-Seró, Iván, 2020. "Abiotic depletion and the potential risk to the supply of cesium," Resources Policy, Elsevier, vol. 68(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dewulf, Jo & Blengini, Gian Andrea & Pennington, David & Nuss, Philip & Nassar, Nedal T., 2016. "Criticality on the international scene: Quo vadis?," Resources Policy, Elsevier, vol. 50(C), pages 169-176.
    2. Hache, Emmanuel & Seck, Gondia Sokhna & Simoen, Marine & Bonnet, Clément & Carcanague, Samuel, 2019. "Critical raw materials and transportation sector electrification: A detailed bottom-up analysis in world transport," Applied Energy, Elsevier, vol. 240(C), pages 6-25.
    3. Elshkaki, Ayman & Graedel, T.E., 2014. "Dysprosium, the balance problem, and wind power technology," Applied Energy, Elsevier, vol. 136(C), pages 548-559.
    4. Glöser, Simon & Tercero Espinoza, Luis & Gandenberger, Carsten & Faulstich, Martin, 2015. "Raw material criticality in the context of classical risk assessment," Resources Policy, Elsevier, vol. 44(C), pages 35-46.
    5. Helbig, Christoph & Bradshaw, Alex M. & Kolotzek, Christoph & Thorenz, Andrea & Tuma, Axel, 2016. "Supply risks associated with CdTe and CIGS thin-film photovoltaics," Applied Energy, Elsevier, vol. 178(C), pages 422-433.
    6. Blengini, Gian Andrea & Nuss, Philip & Dewulf, Jo & Nita, Viorel & Peirò, Laura Talens & Vidal-Legaz, Beatriz & Latunussa, Cynthia & Mancini, Lucia & Blagoeva, Darina & Pennington, David & Pellegrini,, 2017. "EU methodology for critical raw materials assessment: Policy needs and proposed solutions for incremental improvements," Resources Policy, Elsevier, vol. 53(C), pages 12-19.
    7. Zuo, Zhili & Cheng, Jinhua & Guo, Haixiang & McLellan, Benjamin Craig, 2021. "Catastrophe progression method - path (CPM-PATH) early warning analysis of Chinese rare earths industry security," Resources Policy, Elsevier, vol. 73(C).
    8. A. Mateus & C. Lopes & L. Martins & J. Carvalho, 2017. "Towards a multi-dimensional methodology supporting a safeguarding decision on the future access to mineral resources," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 30(3), pages 229-255, October.
    9. Marc Wentker & Matthew Greenwood & Jens Leker, 2019. "A Bottom-Up Approach to Lithium-Ion Battery Cost Modeling with a Focus on Cathode Active Materials," Energies, MDPI, Open Access Journal, vol. 12(3), pages 1-18, February.
    10. Ren, Kaipeng & Tang, Xu & Wang, Peng & Willerström, Jakob & Höök, Mikael, 2021. "Bridging energy and metal sustainability: Insights from China’s wind power development up to 2050," Energy, Elsevier, vol. 227(C).
    11. Brown, Teresa, 2018. "Measurement of mineral supply diversity and its importance in assessing risk and criticality," Resources Policy, Elsevier, vol. 58(C), pages 202-218.
    12. Alexandre Tisserant & Stefan Pauliuk, 2016. "Matching global cobalt demand under different scenarios for co-production and mining attractiveness," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 5(1), pages 1-19, December.
    13. Lapko, Yulia & Trucco, Paolo, 2018. "Influence of power regimes on identification and mitigation of material criticality: The case of platinum group metals in the automotive sector," Resources Policy, Elsevier, vol. 59(C), pages 360-370.
    14. Alexandre Tisserant & Stefan Pauliuk, 2016. "Matching global cobalt demand under different scenarios for co-production and mining attractiveness," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 5(1), pages 1-19, December.
    15. SIPOS Csanád & MÁTÉ Domicián, 2020. "Industrial Environment Selection By Sourcing Strategy In The Case Of North African Countries," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 395-404, July.
    16. Stepanek, Christian & Walter, Matthias & Rathgeber, Andreas, 2013. "Is the convenience yield a good indicator of a commodity's supply risk?," Resources Policy, Elsevier, vol. 38(3), pages 395-405.
    17. Henrik Florén & Johan Frishammar & Anton Löf & Magnus Ericsson, 2019. "Raw materials management in iron and steelmaking firms," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 32(1), pages 39-47, April.
    18. Tapia, Carlos & Coulton, Jeff & Saydam, Serkan, 2020. "Using entropy to assess dynamic behaviour of long-term copper price," Resources Policy, Elsevier, vol. 66(C).
    19. Elaine Garcia de Lima & Cécile Bulle & Cássia Maria Lie Ugaya, 2018. "A Functionality Based Wood Substitutability Index," Sustainability, MDPI, Open Access Journal, vol. 10(6), pages 1-28, May.
    20. Shule Li & Jingjing Yan & Qiuming Pei & Jinghua Sha & Siyu Mou & Yong Xiao, 2019. "Risk Identification and Evaluation of the Long-term Supply of Manganese Mines in China Based on the VW-BGR Method," Sustainability, MDPI, Open Access Journal, vol. 11(9), pages 1-23, May.

    More about this item

    Keywords

    Criticality potential; Risk analysis; Mineral supply chains; Production concentration; Price volatility;
    All these keywords.

    JEL classification:

    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:minecn:v:30:y:2017:i:3:d:10.1007_s13563-017-0119-6. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.springer.com .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.