Critical mineral constraints in global renewable scenarios under 1.5 °C target

This study proposes an MEC nexus framework to explore the interaction between metal, energy, and environment systems in figure 1. The climate scenario system is presented by different climate scenarios with different representative concentration pathways (RCPs). Among all available emission pathways, RCP 1.9 is the pathway that follows the goal of the Paris Agreement, which limits global warming to below 1.5 °C above the pre-industrial level. Thus, only RCP 1.9 is selected for this study, given its high preference for our sustainable future (Rogelj et al 2018). The detailed model structure and scenario settings are given in section S3 of supplementary information.

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The energy system is the core of MEC nexus that bridges all systems together. Under different climate targets and SSPs, future renewable growth across the world can be obtained in IAMs. Notably, with rapid shifting from fuels to renewables, the global energy system is gradually changing from carbon-based (e.g. coal, oil, gas) to critical metals-based (e.g. Dy, Nd, In, Cd, Te, Wang et al 2020). This emerging linkage requires a qualitative analysis of the dynamics of renewable infrastructure to metal demand, which is captured with the following stock-driven model:

• (a)  
  For each energy technology infrastructure, its annual inflow required for the addition to in-use stock (or infrastructure capacity) is obtained as follows:

  $$\begin{align} {\text{Inflo}}{{\text{w}}_C}\left( t \right)& = \Delta {\text{Stoc}}{{\text{k}}_C}\left( t \right) - \mathop \sum \limits_{x = 0}^{t - 1} {\text{Inflo}}{{\text{w}}_C}\left( x \right)\nonumber\\& \quad \times {\text{EF}}\left( {\tau ,t - x} \right)\end{align} \tag{ 1 }$$

  where EF is the end-of-life function that determines the possibility of previous inflows with mean lifetime $\tau$ to be phased out at present, which follows various lifetime distribution functions (i.e. Normal, Weibull, etc.) and Weibull distribution function is selected here. The in-use stock can be directly obtained from infrastructure capacity (unit: GW). Meanwhile, the $\Delta {\text{Stoc}}{{\text{k}}_C}\left( t \right)$ is the stock change from last year, and the initial inflow equals the initial stock.
• (b)  
  For each type of studied mineral, its final demand (${\text{FInflo}}{{\text{w}}_M}\left( t \right)$), end-of-life flows (${\text{Outflo}}{{\text{w}}_C}\left( t \right)$), primary mineral demand (${\text{Inflo}}{{\text{w}}_M}\left( t \right)$), and material in-use stocks (${\text{Stoc}}{{\text{k}}_C}$ $\left( t \right)$) are determined as follows, respectively:

  $$\begin{align}{\text{FInflo}}{{\text{w}}_M}\left( t \right) = {\text{Inflo}}{{\text{w}}_C}\left( t \right) \times {\text{M}}{{\text{I}}_M}\left( t \right)\end{align} \tag{ 2 }$$

  $$\begin{align}{\text{Outflo}}{{\text{w}}_C}\left( t \right)& = \mathop \sum \limits_{x = 0}^{t - 1} {\text{Inflo}}{{\text{w}}_C}\left( x \right) \times {\text{M}}{{\text{I}}_M}\left( x \right)\nonumber\\ & \quad \times {\text{EF}}\left( {\tau ,t - x} \right)\end{align} \tag{ 3 }$$

  $$\begin{align}{\text{Inflo}}{{\text{w}}_M}\left( t \right) &= {\text{FInflo}}{{\text{w}}_M}\left( t \right) - {\text{Outflo}}{{\text{w}}_C}\left( t \right) \nonumber\\ &\quad \times {\text{R}}{{\text{R}}_M}\left( t \right)\end{align} \tag{ 4 }$$

  $$\begin{align}{\text{Stoc}}{{\text{k}}_C}\left( t \right) = \mathop \sum \limits_{x = 0}^{t - 1} {\text{FInflo}}{{\text{w}}_M}\left( x \right) - {\text{Outflow}}\left( x \right)\end{align} \tag{ 5 }$$

  where ${\text{M}}{{\text{I}}_M}\left( t \right)$ is the metal intensity of energy infrastructure at time t, ${\text{R}}{{\text{R}}_M}\left( t \right)$ is the end-of-life recycling rate of studied mineral at time t. Notably, the metal cycle system aims to provide the foundation for tracking metal flows and stocks along its entire life cycle from mining, refining, manufacturing, in-use, to end-of-life. The starting points for quantifying metal flows and stocks within the in-use and recycling stage are based on equations (2)–(5).

This study collected the future scenario settings on the global social-economic system and energy system based on six commonly available IAMs, including AIM, GCAM, IMAGE, MESSAGE, REMIND, and WITCH (Rogelj et al 2018). Those IAMs follow five different SSPs (i.e. SSP 1–5). Not all the IAMs run or have feasible solutions for every combination of SSPs and RCPs under the 1.5 °C target (with a radiative forcing of 1.9 W m⁻²), the available results are summarized in table 1.

The SSPs are recently established as a critical part of new climate scenario framework to facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation, and mitigation (Riahi et al 2017). Five narratives are designed in the absence of explicit additional climate policies, including sustainable development, regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development (Neill et al 2017). One contribution of this work aims to extend SSPs with different mineral supply scenarios that may relate to climate change, which is missing in the current SSPs settings.

In our analysis, SSP1 represents a sustainable development pathway, calling for a higher installed capacity of low-carbon technology and lower resource intensity to mitigate climate change, so it adopts the optimistic parament, with a higher technology mix of low-carbon technologies, an advanced material intensity reduction, a higher circularity, and an ideal extension of lifetime. However, using more advanced technologies (e.g. direct-drive and hybrid-drive wind turbines) may increase the material intensity compared to the normal ones (Wolfram and Hertwich 2019). In the SSP3, a resurgent nationalism with concerns about competitiveness and security may help raise the recycling to secure national resource security. However, the lack of international cooperation may defer technology improvement. The SSP5 may express neutral technology improvement with medium material intensity and lifetime extension. All factors in the SSP4 are assumed to be business as usual, while those in SSP2 are in the middle of SSP1 and SSP4. The detailed settings of each SSP are given in table 2 and section S3 of supplementary information.

Given the scope of this work mainly lies in the introduction of MEC framework and its application, this study only focused on six representative types of critical minerals (i.e. Nd, Dy, Cd, Te, Se, In) given their relatively high technical importance and supply risks (Liang et al 2022). The temporal boundary is set to be from 2000 to 2050 with a focus on the global level.

Wind (onshore and offshore) and solar (cell PV) are typical power technologies constrained by minerals, and their magnitude of total installed capacity, newly added capacity, and end-of-service are presented in figure 2. As the proxy of material requirements, the future infrastructure stocks of all three studied technologies grow substantially, with large disparities among SSPs and models. Compared to the stock in 2017, the total installed capacity of onshore and offshore wind and solar PV in 2050 increases by orders of magnitude ranged 24–173, 40–289 and 142–1183, respectively. The future infrastructure stocks are highest in a sustainability pathway (SSP1) since less reliance would be placed on alternative low-carbon power supply technologies such as fossil fuel with CCS and nuclear based on the SSPs narratives.

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The newly added capacity from 2000 to 2050 shows rapid and steady growing trends with decadal fluctuations for all three studied technologies. The cumulative newly added capacities from 2000 to 2050 reach 1400–9419, 169–1111 and 473–5361 GW for onshore wind, offshore wind, and solar PV, respectively, while roughly 75% to 85% of installations occur after 2030. The infrastructures would gradually become obsolete when approaching their lifetime, and the embodied materials would enter the end-of-life stage for further treatment. As shown in figure 2(C), the end-of-service wind and solar devices soar after 2030 in all scenarios due to large cumulative installed capacities and increasing operating years. In 2050, additional installations of 13.2–82.2, 3.7–15.6, and 2.2–42.1 GW for onshore wind, offshore wind, and solar PV would be needed to replace the retired devices.

Climate mitigation is expected to boost the critical mineral demand significantly. The mineral required for the world to achieve 1.5 targets are presented in figure 3. On average, the deployment of wind power will require around 33.8 Kt of Dy and 413 Kt of Nd in total from 2000 to 2050, respectively. For the scale-up of photovoltaic (PV) technology, around 145 kt of Cd, 136 kt of Te, 41 Kt of Se, and 45 Kt of In will be required, respectively. Clearly, more stringent climate targets call for higher mineral demand. Compared to the results of 'beyond 2 degree' (B2D) scenario from IEA (2015), it is found our mineral demand estimates for 1.5 °C target are around 2–3 times (and six times) higher for wind-related (and solar-related) critical minerals, respectively. This indicates that expanding solar power for higher climate mitigation may bring severer pressure on the mineral supply of Cd, Te, Se, and In.

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Notably, more sustainable SSP will induce a higher demand for critical mineral (in figure 3). For instance, the wind-related mineral requirement for most SSP 1 (i.e. sustainability pathway) are highest among all scenarios (e.g. around twice that in REMIND model) even with most optimistic life cycle strategies. This is mainly because more renewables, especially wind power, will be required for sustainability pathways that induce higher mineral demand. However, given the mineral are harder to obtain, the feasibility of achieving sustainability pathways should be assessed on the mineral availability. On the other hand, the mineral demand in the next two decades (till 2030) is expected to account for less than 20% of total demand. Meanwhile, a faster growth is expected for the demand for all minerals after 2030.

This study explored the annual mineral demand from 2000 to 2050 in line with 1.5 °C targets under various SSPs. The shortage of minerals to meet their demand is assessed by comparing total cumulative mineral demand to the present mineral production capacity. Our results, together with de Koning et al (2018), indicate the mineral of Te, Se, and Dy in nearly all scenarios may face physical shortage based on present mineral reserve, i.e. the cumulative Dy demand during 2021–2050 reached 9–58 kt, equals to running out 3%–18% of the global economic reserve (314 kt), highlighting the potential constraints in the further development of wind and solar to meet the 1.5 °C target. Further exploration and attention on efficient production for those three minerals should be given.

Despite adequate mineral reserve, the mineral production may face scalability constraints due to the long period of preparation (5–15 years) (Prior et al 2012) for capacity expansion and limitation in host metals (critical minerals as by-products), which is measured by the average mineral demand to the present total production capacity in figures 4 and 5. It is found only Cd, Se and Nd can be supplied with current production capacity. However, the rest three minerals (i.e. Dy, In, and Te) should expand their production capacities quickly for wind and solar power growth worldwide. There are two specific concerns that desire further notice: the future deployment of wind power may be constrained by the rare earth production capacity limitation in China and the shortage of Dy in the global minerals (Lee and Wen 2018), thus mines outside China and the substitution of Dy in wind turbine is very important for 1.5 °C targets. While solar power faces severer constraints from the physical shortage of Te and Se as well as the limited scalability in In production, suggesting the innovation of novel solar cells without those critical minerals in meeting energy needs as well as climate targets is very urgent.

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There are several previous studies (e.g. Stamp et al 2014, Månberger and Stenqvist 2018, Takuma et al 2018) has projected the demand for energy-related materials. On the basis of those work, this study introduced more detailed analysis related to the changes of mineral supply chain along its life cycle in different SSPs with key parameters like lifetime, recycling rate, material intensity and technology mix (i.e. share of PM wind turbines and thin-film PVs). We performed a sensitivity analysis to capture the impacts of those parameters, in which AIM/CGE-SSP2 scenario was selected as a proxy with the development of around 11 'sensitivity analysis' scenarios in the section S5 of the support information. As figure S7 shows, for Nd, compared with the base case, a 5% lifetime extension can result in a 0.68% reduction in metal demand from virgin ores, a 1.42% reduction in total demand, and a 16.53% reduction in metal recycling. As for the recycling rate, a 5% improvement can cause a 0.24% reduction in metal demand from virgin ores and cause a 5.01% increase in recycling. Thus, it is found that material intensity and technology mix are two key paraments, i.e. a 5% increase in material intensity and new energy infrastructure (PM wind turbines and thin-film solar PVs) market share will result in a 5% increase in metal direct demand and metals from virgin ores, indicating the importance of the innovation in material substitution and energy technologies in future low-carbon transition. Meanwhile, further cautions should be paid for the application of future critical metal demand results, particularly on the assumptions of material intensity and technology mix. Meanwhile, we further compare our results with those publications to validate our results in section S6 of the supporting information. As shown in table S9 of the supporting information, it is found our estimation is in line with most studies with acceptable differences.

Given the importance of prediction of long-term climate change pathways, the IAMs have emerged as a modeling backbone of the IPCC reports (IPCC 2022) and other fundamental studies (Bednar et al 2021) due to their great potential in exploring inter-linkages between climate, energy, land-use, and economic development (Pauliuk et al 2017). Our study has recognized that mineral resources have been key constraints on low-carbon energy development and further the achievability of climate targets. However, our analysis through the applications of six widely-used IAMs is mainly limited to the direct link to demand projection of various critical minerals, while the analysis of mineral price changes and their interactions with low-carbon technologies competitiveness is yet conducted.

This work, as one preliminary and explorative study, demonstrate the potential impacts of critical minerals on future climate mitigation pathways. Among various IAMs, the MEDEAS (Capellán-Pérez et al 2020) has tried to incorporate the mineral system into the IAM framework, highlighting a large amount of interrelated energetic, material, and economic investments will be required to build, operate and interconnect energy infrastructures. Meanwhile, other studies (Deetman et al 2018, Boubault and Maïzi 2019, Kalt et al 2022) also introduced IAMs into such analysis. Still, all those studies mentioned above can help to provide the trends of future critical mineral demand under different climate and energy scenarios but fail to capture more dynamics related to the interdependence between material, energy, and climate systems.

Our analysis highlighted the resource availability and production capacity of critical minerals would become a major constraint of the global low-carbon transition. Indeed, critical minerals are a finite, non-renewable resource found in the Earth's crust (Ober 2017). Some consider depletion to be unavoidable given the fixed resource stock and continuous demand (Cohen 2007, Gordon et al 2007, Ragnarsdóttir 2008). For some energy-related minerals such as cobalt, nickel, and cadmium, geological scarcity might be a major concern. However, new technologies and innovation can offset the cost-increasing effects of depletion (Tilton and Lagos 2007, Turner 2008), which are not captured in this work. Thus, the technical factors and their impacts on physical scarcity should be further studied.

Aside from resource perspective, the production of critical minerals is also energy-intensive and carbon-intensive, the factors of which should also be valued and captured by IAMs. For example, researchers have assembled extensive information on the cradle-to-gate environmental burdens of 63 minerals and found that the major industrial metals (e.g. iron, manganese) are at the lower end of the environmental impacts scale (Nuss and Eckelman 2014). Other work has warned that producing a kilogram of nickel requires more energy and causes more GHG emissions than copper, iron, and aluminum (Van der Voet et al 2019). Meanwhile, mining critical minerals will cause a series of local environmental threats (Holland et al 2019), which is absent from our analysis. For example, rare earths extraction may result in chemical pollution and radioactive waste that threatens rural groundwater aquifers as well as rivers and streams (Sovacool et al 2020). The tantalum and nickel mining in Brazil drives extensive deforestation in Amazon (Sonter et al 2017), and the mining of cobalt in DR Congo causes the heavy metal contamination of air, waste, and soil, which has further led to severe health impacts for miners (Farjana et al 2019). This would be considered negative feedback to achieve sustainable development goals. In this way, the mineral constraints for climate mitigation will become severer than our results indicated. This calls for a regional-specific analysis of mineral production as well as holistic assessment of the corresponding economic, environmental, and social impacts on those local suppliers.

How can we mitigate such pressing metal constraints on the global energy system transition? From a systematic perspective, our work has clarified this challenge and its corresponding metal-related strategies, as shown in table 2. From the mineral supply side, we urge to expand geological exploration to increase the resource base, and improve their mining and processing technologies to harvest more metal resources. However, it is worth pointing out that this set of strategies may cause severe environmental impacts associated with metal extraction and production. To overcome the resulting environmental inequality, cooperative mechanisms are needed to actively share the burden between both the production and the consumption sides.

To identify the key strategies and their priorities, this work further performed the sensitivity analysis of key parameters and details can be found in section S5 of SI. In our model, material intensity and market share of new technology can directly impulse the mineral demand, indicating that material reduction will play an important role in mitigating mineral constraints. This also indicates that the end-of-life options (i.e. recycling rate improvement) will have limited impacts on reducing mineral demand, compared to other demand-side options. Thus, combing material efficiency strategies (Allwood et al 2011, Ciacci et al 2016) into MEC nexus is key demand-side measure to alleviate the contradiction between supply and demand of critical metals. CE aims to decouple growth from the consumption of finite resources, including various strategies, such as recycling, remanufacturing, and reuse, to ensure the high value of products, components, and materials throughout the whole lifecycle. Meanwhile, strategies to reduce the amount of material required by energy technologies during the in-use stage, call for technical innovations and the design for material efficiency. These can help to deliver more renewable services and prolong the lifetime and efficiency of renewable energy technologies during the in-use stage. Consequently, less new infrastructure would be required, and critical materials could be saved, which calls for more research and development efforts.