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Rare earth elements and yttrium in Chinese coals: Distribution and economic significance

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  • Zhu, Wei
  • Shen, Lishan
  • Xu, Na
  • Kong, Jiapei
  • Engle, Mark A.
  • Finkelman, Robert B.
  • Li, Fei
  • Wang, Qingfeng
  • Li, Pengfei
  • Zhang, Shaowei
  • Dai, Shifeng

Abstract

Rare earth elements and yttrium (REY) are essential strategic materials in emerging fields. REY are becoming scarce and expensive as their resources in conventional ores are becoming exhausted. Some previous investigations showed that a number of coals can be considered as a new economic source of REY. However, how many coals can be used as a source of REY recovery is still unknown. This research employed the Kruskal-Wallis H test, Dunn's test, and the self-organizing map algorithm to comprehensively analyze and subsequently predict the REY oxides potential in coals from China, using data from 888 coal samples collected from 64 coal mines across China. The results showed that some Chinese coals hold significant economic value and promise for the recovery of REY, particularly in the Southern and Northern coal-bearing areas. The enrichment of REY exhibits significant variations across different coal-forming periods. The coals from the Carboniferous to Triassic periods show the most promising potential for REY recovery. REY have shown strong associations with Ti, Al, Zr, Hf, Ga, Nb, Ta, and P, which may serve as geochemical indicators for REY enrichment prospection. Owing to the multiple origins of REY enrichment in coal, the coals with a promising REY recovery are characterized by different geochemical compositions. Most coal samples with promising potential for REY recovery yield Class F ash.

Suggested Citation

  • Zhu, Wei & Shen, Lishan & Xu, Na & Kong, Jiapei & Engle, Mark A. & Finkelman, Robert B. & Li, Fei & Wang, Qingfeng & Li, Pengfei & Zhang, Shaowei & Dai, Shifeng, 2025. "Rare earth elements and yttrium in Chinese coals: Distribution and economic significance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 212(C).
    • Handle: RePEc:eee:rensus:v:212:y:2025:i:c:s1364032125000966
    DOI: 10.1016/j.rser.2025.115423
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    References listed on IDEAS

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    1. Wehrens, Ron & Buydens, Lutgarde M. C., 2007. "Self- and Super-organizing Maps in R: The kohonen Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i05).
    2. Tomer Fishman & Rupert J. Myers & Orlando Rios & T.E. Graedel, 2018. "Implications of Emerging Vehicle Technologies on Rare Earth Supply and Demand in the United States," Resources, MDPI, vol. 7(1), pages 1-15, January.
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