Scenarios for Demand Growth of Metals in Electricity Generation Technologies, Cars, and Electronic Appliances

Abstract

This study provides scenarios toward 2050 for the demand of five metals in electricity production, cars, and electronic appliances. The metals considered are copper, tantalum, neodymium, cobalt, and lithium. The study shows how highly technology-specific data on products and material flows can be used in integrated assessment models to assess global resource and metal demand. We use the Shared Socio-economic Pathways as implemented by the IMAGE integrated assessment model as a starting point. This allows us to translate information on the use of electronic appliances, cars, and renewable energy technologies into quantitative data on metal flows, through application of metal content estimates in combination with a dynamic stock model. Results show that total demand for copper, neodymium, and tantalum might increase by a factor of roughly 2 to 3.2, mostly as a result of population and GDP growth. The demand for lithium and cobalt is expected to increase much more, by a factor 10 to more than 20, as a result of future (hybrid) electric car purchases. This means that not just demographics, but also climate policies can strongly increase metal demand. This shows the importance of studying the issues of climate change and resource depletion together, in one modeling framework.

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“…The conflicts of goals we derive fit with the results of other studies in terms of indicating a high need for minerals and metals for energy systems with high shares of wind, PV and batteries (e.g., cf. [56][57][58]). Furthermore, investigating the underlying LCI datasets, we observe the shift of impact majorities from the operational to the production phase comparing renewable to fossil energy systems (as described in [14,24]).…”

Documentation of part IV of the RECC model framework: Open Dynamic Material Systems Model for the Resource Efficiency-Climate Change Nexus (ODYM-RECC), v2.2

“…Future metal and material demand has been projected and studied from the perspective of different macro-level scenarios (Deetman et al, 2019(Deetman et al, , 2018Elshkaki et al, 2018Elshkaki et al, , 2016Elshkaki and Graedel, 2013;Hatayama et al, 2010;Schipper et al, 2018;van der Voet et al, 2018;Watari et al, 2019), but those assessments are not linked to resource efficiency, but represent a very important starting point for our work, as we can link our scenarios and data to these studies.…”

“…Finally, there are some recent attempts to link material consumption to economy-wide models more directly. First, by converting sectoral output of CGE models into material flows by applying product material composition and prices (Cao et al, 2018;Winning et al, 2017), and second, by converting end-user demand for new products provided by energy system models into material flows by applying product material composition data (Deetman et al, 2018;Watari et al, 2019). These attempts are a step in the right direction, but the CGE approaches focus on single economic sectors only and do not consider material cycles and the mitigation potentials therein, and the energy system-based approaches only estimate final demand and currently do not consider the material cycle response.…”

“…In the simplest case, this would just mean that the regression model equations are replaced by formatted IAM model output. Such approach has already been lined out for the five materials Cu, Co, Li, Nd, and and Ta, where IMAGE model output for the use phase was converted to material in-use stocks, inflows, and outflows of the use phase (Deetman et al, 2019(Deetman et al, , 2018. Also, the implementation of the material cycle consequences of electricity generation installation from MESSAGE is already under way.…”

Devising Mineral Resource Supply Pathways to a Low-Carbon Electricity Generation by 2100

“…A common approach-focusing on material demand-is to combine data on material usage with development scenarios employing evolution-characteristic parameters such as population growth, monetary flows, energy produced, additional number of products, etc. [5][6][7][8][9][10][11][12][13][14][15]. Data on material usage might only include direct "consumption" by processes or material content in products.…”