Mine to Table: Technology and Policy Strategies for Sustainable Mineral Supply Chains in the Low-Carbon Energy Transition
Author(s)
Ryter, John
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Advisor
Olivetti, Elsa
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With rapidly increasing demand due to the low-carbon energy transition, the metals and mineral extraction industry has seen a flurry of new policy over the last several years looking to direct or capitalize on new investment. This rapidly increasing demand is coupled with a need for industry decarbonization, prompting availability, price, and environmental concerns simultaneously. To identify mechanisms to address these concerns, this work models material and economic relationships between the mining, refining, manufacturing, and recycling components of mineral supply chains. We consider unit processes and environmental impacts to establish the material processing improvements and policy mechanisms most capable of supplying the low-carbon energy transition and limiting environmental impacts. There are three main lines of inquiry.
First, we assess the environmental benefits of recycling and its reduction of mine production by developing a dynamic, economically-informed simulation model for the copper supply chain. The primary environmental benefit of recycling is its implied reduction of mine production. However, we find that increases in recycling only displace, on average, $\sim$0.5 tons of mine production per ton increase in scrap supply, due to slow mine response rates and interim increases in demand owing to excess commodity supply. We find supply chain evolution pathways maximizing displacement of mine production, such as the inclusion of recyclables on major futures exchanges. However, even in best-case scrap supply scenarios, CO\textsubscript{2}e emissions from the copper supply chain increase 25\% by 2040 relative to 2018. With simultaneous global adoption of current best practices, 2040 CO\textsubscript{2}e emissions 10\% below 2018 are possible, though still well short of 2°C emissions targets.
Second, we assess the impacts that regional supply chain variations and disruptions have on future supply chain behavior and emissions. We expand the copper supply chain model to enable regional, alloy-level consumption, and scrap grade-level consumption granularity, investigating each copper supply chain actor’s response to China’s solid waste import ban and the COVID-19 pandemic. We demonstrate that the economic changes associated with China’s solid waste import ban increase primary refining within China, offsetting the policy's intended environmental benefits of decreased copper scrap refining, and instead generate a cumulative increase in CO\textsubscript{2}-equivalent emissions of up to 13 Mt by 2040. Increasing China’s refined copper imports reverses this trend, decreasing CO\textsubscript{2}e emissions in China (up to 180 Mt by 2040) and globally (up to 20 Mt). We test sensitivity to supply chain disruptions using GDP, mining, and refining shocks associated with the COVID-19 pandemic, showing the results translate onto disruption effects, and that slow mine response rates make them more resilient to perturbations than recycling streams.
Finally, we attempt to quantify the market-based and technological mechanisms available for mitigating supply and price risks, particularly for byproduct/coproduct commodities. Here we introduce GLOMBO (GLObal Materials modeling using Bayesian Optimization), a generalized economics-informed material flow model that captures the dynamics of key mineral commodities with minimal training data inputs. Building upon established material flow and economic modeling techniques, we apply Bayesian optimization to fit global historical demand, supply, and price. We developed individual material-specific economics-informed MFA models for commodities covering the vast majority of annual mineral consumption. These also act as host metals to the bulk of the minor metals, and we develop an ancillary model to assess their byproduct commodities. We then use these models to demonstrate methods for supply risk assessment that rely wholly on empirical data, and work to understand the key drivers of price risk. Given the volatility of the resulting byproduct model, we conclude with a mine-level case study on the mechanisms and rates at which byproduct commodity prices impact mine operation, using net present value optimization methods.
Date issued
2023-06Department
Massachusetts Institute of Technology. Department of Materials Science and EngineeringPublisher
Massachusetts Institute of Technology