Estimating economy-wide mineral commodity consumption using hybrid input-output modeling: a case study of fluorspar

Understanding economy-wide material flows is of increasing importance as industries and governments seek to develop secure supply chains for critical minerals while mitigating negative social and environmental impacts. To advance research merging economy-wide material flow accounting with economic impact analysis, we adapt the integrated hybrid input-output analysis framework to build a mixed-unit model of mineral commodity processing in the United States. As a test case we apply the approach to fluorspar and derived fluorine-based chemicals, presenting one of a few models of fluorspar's domestic supply chain. We then estimate demand for this critical mineral that would be induced by projected sales of two emerging technologies, semiconductors and lithium-ion batteries, which are expected to contribute substantially to increasing demand. We find that near-term U.S. demand for fluorspar and its derivatives for use in semiconductors but not for use in lithium-ion batteries may surpass recent economy-wide domestic consumption of these materials. Modeling an increase in U.S. production of advanced chips in line with expressed targets results in 1% to 5% more fluorspar demand per year compared to the baseline. Global sensitivity analysis demonstrates an approach to factor prioritization applied to physical input-output table (PIOT) construction. We find the two major sources of physical flow data uncertainty, the ratios used to allocate national use to industries and the assumption used to partition exports into their domestic and foreign components, contribute about equally to uncertainty in the output. However, we also find the uncertainty in choice between several approaches to compiling the allocation ratios leads to most uncertainty in total physical output.