Streamlined approach for assessing embedded consumption of lithium and cobalt in the United States
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Abstract
In today's complex global supply chains, time and data intensive analyses are required to understand global flows of mineral commodities from mine to consumer, particularly for mineral commodities in products (electronics, automobiles, etc.) that contain multiple parts with many mineral commodities. National and regional analyses require additional time and data to incorporate international trade flows. However, data limitations and time constraints often prohibit global and national material flow analyses for minor metals. Here we present a methodological approach to circumvent these constraints by utilizing readily available industry-level global data from the United Nations Statistics Division and national industrial data to estimate total requirements for a mineral commodity. We apply this approach to lithium and cobalt use in the United States for the year 2018 and distinguish between apparent raw material consumption versus inferred embedded consumption of lithium and cobalt materials in all forms. The results show that more than half of the United States’ total requirements for both lithium and cobalt is in parts and products that were manufactured outside the United States. In large part, this is due to limited US manufacturing capability for lithium-ion battery materials and cells and the United States’ high import reliance for electronics that use those batteries.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Streamlined approach for assessing embedded consumption of lithium and cobalt in the United States |
| Series title | Journal of Industrial Ecology |
| DOI | 10.1111/jiec.13337 |
| Volume | 27 |
| Issue | 1 |
| Year Published | 2023 |
| Language | English |
| Publisher | Wiley |
| Contributing office(s) | National Minerals Information Center |
| Description | 10 p. |
| First page | 33 |
| Last page | 42 |
| Country | United States |
| Google Analytic Metrics | Metrics page |