The increasing demand for mineral-based resources that face supply risks calls for managing the supply chains for these resources at the regional level. Cobalt is a widely used cathode material in lithium-ion batteries, which form the major portion of batteries used for renewable energy storage - a necessary technology for electrifying mobility and overcoming the challenge of intermittency, thus making renewable energy more reliable and energy generation more sustainable. This necessitates understanding cobalt's supply risks and for the Untied States, identifying sources of cobalt available for future use via recycling or mining. These needs are addressed in this work using single and multiregional input-output (MRIO) analysis in combination with graph theory. An MRIO-based approach is developed to obtain the trade network of cobalt and offer a more expedient way to identify potential critical material sources embodied in commodities made domestically. Commodities containing cobalt were disaggregated from two input-output (IO) models and the trade structure of cobalt at the national and state level was observed and compared. The significance of identified key sectors is measured according to several criteria and differences in sectors highlighted in the national versus subnational networks suggests that analysis at the two regional aggregation levels provides alternative insights. Results from mining the IO networks for cobalt highlight the geographical distribution of its use and industries to further investigate as potential sources for secondary feedstock.
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/15164721 |
| Date | 13 August 2021 |
| Creators | Miriam Chrisandra Stevens (11272506) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY-NC-SA 4.0 |
| Relation | https://figshare.com/articles/thesis/A_framework_for_domestic_supply_chain_analysis_of_critical_materials_in_the_United_States_an_economic_input-output-based_approach/15164721 |
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