Geospatial Data and Deep Learning Expose ESG Risks to Critical Raw Materials Supply: The Case of Lithium

Geospatial Data and Deep Learning Expose ESG Risks to Critical Raw Materials Supply: The Case of Lithium

Disruptions to the global supply chains of critical raw materials (CRM) have the potential to delay or increase the cost of the renewable energy transition. However, for some CRM, the primary drivers of these supply chain disruptions are likely to be issues related to environmental, social, and gove...

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Bibliographic Details
Main Authors: Christopher J. M. Lawley, Marcus Haynes, Bijal Chudasama, Kathryn Goodenough, Toni Eerola, Artem Golev, Steven E. Zhang, Junhyeok Park, Eleonore Lèbre
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Earth Science, Systems and Society
Subjects:
machine learning
sustainability
critical mineral
sustainable development
mineral potential
geoscience
Online Access:https://www.lyellcollection.org/doi/10.3389/esss.2024.10109

Internet

https://www.lyellcollection.org/doi/10.3389/esss.2024.10109

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