Securing the supply of clean energy metals to achieve carbon reduction: a review
0Abstract
Climate change is a major threat to the world. The cause for this global challenge is directly linked to greenhouse gas (GHG) emissions. In order to mitigate climate change, major policies such as reducing GHG emissions are required. Many countries have proposed carbon emission reduction targets at the national strategic level. A crucial issue in achieving the target is low-carbon energy transition, which requires a large amount of clean energy metals as supporting materials. This paper summarizes the latest research results of existing literature on the supply of clean energy metals in achieving the goal of carbon reduction, including the definitions, demand changes, supply capacity assessment, supply risk evolution, supply guarantee and policy system, etc. We point out that further research should be conducted in the following three directions in the future: firstly, strengthen research on the impact of trade and geopolitics on the supply of clean energy metals; secondly, further evaluate the effectiveness of minerals security policies in various countries; finally, broaden the analysis of the clean energy metals supply to encompass the entire industrial chain perspective.
Keywords
INTRODUCTION
With the rapid development of economy and continuous progress of science and technology, human beings now enjoy unprecedented levels of convenience. However, this progress has also brought about a negative impact on climate and environment. Climate change is one of the major challenges of our time. Ongoing climate change has been demonstrated to impact the risk of disasters, human well-being, and terrestrial ecosystems. In the future, how to control GHG emissions will be a key issue in managing climate change. In this context, reducing carbon emissions seems to have become a consensus among countries, with relevant laws, governance plans, strategic plans and so on.
There are slight differences in the understanding of achieving carbon reduction among different countries. China aims to peak its emissions by 2030 and achieve carbon neutrality by 2060. Australia has committed to reducing carbon emissions by at least 26% by 2030. Germany has clearly explicitly outlined plans to incrementally increase the proportion of renewable energy in its total electricity consumption, targeting a level exceeding 80% by 2050. We can see that low-carbon energy transition (Hereafter referred to as energy transition) is the ultimate task for countries to achieve their carbon reduction goals, and each country is willing to reduce carbon emissions to a certain quantitative level at a certain point in time. In order to achieve the goal of carbon reduction, low-carbon energy and low-carbon fossil fuels have become the top priority, and achieving these technologies requires large amounts of metals as the foundation[1]. Therefore, the research objective of this article is to summarize and sort out the supply of clean energy metals within the context of carbon reduction goals, and its latest research results, grasp the current demand, safety situation, and countermeasures of key metals as a whole, and propose effective response suggestions.
Shao and Zhang, Shao et al. defined the metals related to clean energy technology as clean energy metals[2,3]. On the one hand, we sort out the metals related to wind energy, hydropower, solar power generation, electric vehicles and energy storage, nuclear energy, biomass energy, geothermal energy, power grid and hydrogen technology from the perspective of the innovation of low-carbon energy technology. On the other hand, we summarize the metals related to low-carbon traditional energy sources such as natural gas and coal from the perspective of the low-carbon technology of fossil fuels. For coal, measures such as efficient combustion technology, flue gas desulfurization and denitrification, fuel conversion, coal gasification and clean coal technology, carbon capture and storage, and energy efficiency improvement can be used to achieve a low-carbon coal system. We combine the research of Shao and Zhang, Shao et al., and other scholars, comprehensively consider the metals used in low-carbon energy technology and the low-carbon process of fossil energy, and further define clean energy metals[2,3].
Secondly, this paper analyzes the future demand and availability of clean energy metals for achieving carbon reduction. In this section, we analyzed existing literature on methods for predicting the demand for clean energy metals. Due to the high uncertainty in the future demand for clean energy metals, we have divided the existing relevant literature into uncertainty in climate policy and environmental protection, and uncertainty in industry development. We have summarized the scenarios set in the literature for these uncertainties. Corresponding to the future demand for clean energy metals, the supply capacity of clean energy metals in the process of achieving carbon reduction is also very important. This article summarizes the analysis methods for the availability of clean energy metals and the influencing factors of clean energy metals availability from five perspectives: geology, economy, technology, environment, and emergencies.
Thirdly, due to the uneven distribution of metals, domestic supply may not necessarily meet one's own needs. Therefore, when achieving carbon reduction, there are risks in the supply of clean energy metals. Based on this, this paper analyzes relevant literature on the supply risks of clean energy metals and summarizes the evolution of the evaluation system for metals supply risks. In recent years, due to trade protectionism and resource nationalism, the supply of clean energy metals has become increasingly serious due to trade risks and geopolitical risks. Therefore, this article focuses on summarizing the impact of trade and geopolitical risks on supply risks of clean energy metals in the existing literature.
Finally, in order to ensure the stable supply of clean energy metals in each country, a series of policies have been proposed, which are an important cornerstone for ensuring the security of clean energy metals supply. This paper combs the policies of the United States, the European Union, China, Japan and other countries on clean energy metal-related industries, and summarizes the evolution trend of policy content and supply guarantee measures.
This paper has the following contributions: Firstly, as an important support for achieving carbon reduction, we have considered the potential challenges of carbon reduction from the perspectives of clean energy metal supply, demand, and policies. Secondly, we have considered the impact of international trade and geopolitical factors on the supply of clean energy metals, which is an important source of uncertainty in the supply of clean energy metals. Finally, we reviewed the security policies for clean energy metals and found a lack of research on the evaluation of policy effectiveness.
DEFINITION OF CLEAN ENERGY METALS FOR ACHIEVING CARBON REDUCTION
In order to achieve carbon reduction, reducing carbon emissions in the energy industry has become the most important issue. Generally speaking, the energy sector can achieve the goal of reducing carbon emissions through two paths: low-carbon energy technology innovation (Wind energy, Hydro energy, Solar power, Electric vehicles and energy storage, Nuclear energy, Biomass energy, Geothermal energy, Power grid, Hydrogen energy) and low-carbon fossil fuels (Natural gas, Coal). Both low-carbon energy technology innovation and fossil energy low-carbon require a large amount of metals as support[1]. Graedel[4] believes that accompanying metals are becoming increasingly important for many carbon-free energy technologies.
Given the important supporting role of metals in clean energy technology, as shown in Figure 1,
Figure 1. Clean energy technology and their supporting metals. Source: based on IEA[6].
Requirements for clean energy metals to achieve “carbon reduction”
| Type | Sector | Related energy metals |
| Low-carbon energy technology innovation | Wind energy | Cu, REE, Ni, Ge, Zn, Al, V, Mo, Nb, Co |
| Hydro energy | Cu, Ge, Zn, Al | |
| Solar power | Cu, Al, Ga, Se, In, Ge, Te, Ag, Mo, Ge, Zn | |
| Electric vehicles and energy storage | Cu, Cd, Co, La, REE, Li, Ni, Al, Mg, V, Sn | |
| Nuclear energy | Cu, Ni, Cr, Ag, REE, V, Mo, Sn, Nb, Be, Ni, Co, Ge | |
| Biomass energy | Cu, Zn, Al | |
| Geothermal energy | Ni, Cr | |
| Power grid | Cu, Al | |
| Hydrogen energy | Ni, REE, Platinum Group Element, Al | |
| Low-carbon fossil fuels | Natural gas | Fe, Cr, Al, Cu, Ni |
| Coal | Fe, Cr, Al, Cu, Ni |
From Table 1, it can be seen that there is a bidirectional coupling relationship between clean energy metals and energy transition, which is generally characterized by the diversity and similarity of critical metals that low-carbon energy relies on[8,9]. On the one hand, there is a “one to many” demand relationship, which means that the implementation of a low-carbon technology often relies on the use of multiple critical metals. On the other hand, there is a “many to one” consumption relationship, which means that multiple low-carbon technologies may simultaneously rely on the consumption of a critical metal.
THE EVOLUTION LAW OF THE DEMAND FOR CLEAN ENERGY METALS TO REALIZE CARBON REDUCTION
Prediction method for clean energy metals demand
The prediction methods for clean energy metals mainly include Dynamic Material Flow Analysis (DMFA), full cycle “S” shape law, departmental analysis prediction method, demand analogy, proportional relationship measurement algorithm, system dynamics method, regression analysis prediction, etc. Among them, DMFA is the most common multi-scenario analysis method. The prediction principles and relevant literature on various prediction methods are shown in Table 2.
Prediction methods for clean energy metals demand
| Prediction methods | Method principle | Refs. |
| DMFA | Quantitative analysis of the dynamic evolution characteristics of various metal processes, calculation of the changes in flow and stock, and then estimation of the future demand for metals | [10-12] |
| Full cycle “S” shaped pattern | According to the “S” shaped correlation between per capita resource consumption and per capita GDP, and the relatively fixed per capita GDP values at the three transition points on the “S” shaped curve. The curve is divided into slow growth zone, fast growth zone, slow growth zone, and zero/negative growth zone. According to this theory, based on the predicted historical resource consumption trajectory of a country, constraint indicators are introduced, transition point parameters are selected, GDP growth plans are set, and the growth trend of per capita resource consumption with per capita GDP is predicted based on the predicted interval resource consumption growth mode. The preliminary prediction results are evaluated by reference indicators, and finally the prediction results are output. | [13-15] |
| SD method | By studying various feedback loops formed by various internal factors within the system, and collecting data and intelligence related to system behavior, computer simulation technology is used to make long-term predictions of large and giant systems | [16,17] |
| Regression analysis prediction | On the basis of analyzing the correlation between metal independent variables and dependent variables, a regression equation between variables is established. And the regression equation is used as a prediction model to predict the relationship between dependent variables based on the changes in the number of independent variables during the prediction period. Most of the relationships between dependent variables are expressed as correlation relationships | [18,19] |
DMFA is mainly suitable for analyzing and modeling material flow processes, and has been widely applied in fields such as environmental regulation, energy conservation and emission reduction. This method comprehensively tracks the production, transportation, use, and disposal of substances in the socio-economic system, analyzing their material flow characteristics and environmental impacts. It requires a large amount of computation and comprehensive analysis and consideration of the interaction of multiple factors. The S-curve method is mainly applied to predict and analyze market demand, technological evolution, new product sales, and other fields. In general, the development process of a product or service is divided into different stages and uses curve-fitting methods to predict its growth trend. This method is suitable for fields with high market saturation and long product lifecycles. The System Dynamics (SD) method is mainly applicable to quantitative analysis and prediction of complex social systems, ecosystems, etc. This method effectively divides the system into multiple subsystems and establishes dynamic models between them, predicting future trends through simulation and other methods. This method is suitable for situations where the system structure is complex and involves the interaction of multiple factors. The regression analysis prediction method is mainly applicable to studying multiple factors that affect a certain indicator and establishing them as mathematical models for prediction. The basic idea is to use statistical methods for regression analysis of data, establish predictive models, and predict future trends. This method is suitable for situations with a wide range of data sources and multiple influencing factors.
Uncertainty in the prediction of clean energy metals
The future demand forecast for clean energy metals mainly faces uncertainty in climate policies and industry development. The uncertainty of climate policy mainly refers to the changes and adjustments in policies, regulations, and goals in the field of environment and energy by the international community and various countries. The formulation and revision of these policies and goals may have an impact on the demand for clean energy metals, such as the environmental protection and emission reduction policies of various governments, the signing and implementation of international agreements, and energy tax policies. The uncertainty usually has various factors such as politics, economy, and technology, and sometimes is also influenced by international situations and geopolitical factors. The uncertainty of industry development mainly refers to the uncertainty related to the clean energy market itself, including technological innovation, market competition, industry capital flow, consumer demand and so on. This uncertainty is closely related to market mechanisms and is more sensitive to market changes and competition. There is a connection between these two types of uncertainties, mainly reflected in: on the one hand, the uncertainty of climate policy will directly affect the demand and pattern of the clean energy metals market, leading to industry changes, technological innovation, and capital flows in the market; on the other hand, the uncertainty of industry development will in turn affect the formulation and revision of climate policies, thereby adjusting policy objectives and measures.
Scholars have set up a series of scenarios to address the uncertainty of climate policy and industry development. From the perspective of the uncertainty of climate policy, early research mainly set scenarios based on GDP, population, urbanization rate, copper intensity, product lifespan, and some conventional government policies[20-23]. In recent years, scholars have paid more attention to the GHG emission and temperature control requirements issued by relevant international organizations for scenario setting. Tokimatsu et al. set scenarios for controlling GHG emissions between 2010 and 2150 through energy and climate policies[24]. Elshkaki and Shen[25] set the IEA current policy scenario, IEA new policy scenario, IEA450 scenario, and National Development and Reform Commission scenario based on government policies, plans, and energy paths. Habib et al. set a baseline scenario, moderate mitigation scenario, and severe mitigation scenario based on the goal of controlling temperature rise at 2 °C[26]. From the perspective of the uncertainty of industry development, Pehlken et al. set up dominant and diverse scenarios from the perspectives of consumer travel habits, public clean energy equipment, company development, and technological level[27]. Hao et al. may have set four scenarios based on the development of the automotive market and found that vehicle electrification in the heavy-duty segment will increase the demand for lithium, cobalt, and nickel[28]. Li et al. set three scenarios: optimistic, neutral, and pessimistic scenarios for China's automotive electrification goals and market share of various types of electric vehicles[29]. Wang et al. have found that regional differences in steel production have a critical impact on its global low-carbon process[30].
Evolution trend of clean energy metals demand
With the proposal of carbon reduction, energy transition has become an unavoidable topic. Scholars set different scenarios based on uncertainty in climate policies and industry development to predict the demand for clean energy metals. The general result is that the potential demand for critical minerals in the future is enormous, and the trend of expanding the supply and demand gap is gradually evident[31,32]. According to the calculations of IEA[6], it is expected that by 2040, the total demand for minerals from global clean energy technologies will double in the benchmark policy scenario (STEPS), quadruple in the sustainable development scenario (SDS), and increase sixfold by 2050. In May 2020, the World Bank released a report on “Minerals for Climate Action: The Mineral Intensity of the Clean Energy Transition”, which showed that in SDS, the overall demand for minerals will increase 30 times from 400,000 tons to
ASSESSMENT OF THE SUPPLY CAPACITY OF CLEAN ENERGY METALS FOR ACHIEVING CARBON REDUCTION
Factors affecting the availability of clean energy metals
Geological factors
Figure 2 shows the five most important factors affecting the availability of clean energy metals. Geological factors are the primary factors affecting metals availability. Among them, mineral resource reserves are an important constraint indicator for availability evaluation, and the fundamental reason is the uneven distribution of minerals in the world, which is the biggest uncertainty factor affecting the availability of metals[41]. At present, the decrease in ore grade or resource quality usually leads to the extraction and processing of more ore in order to produce the same amount of mineral products[42]. When there are multiple economically valuable metals in an ore body, these metals may be reported as equivalent grades of a single metal. As mining intensity increases and ore grade decreases, it will also lead to a significant increase in energy, material, and water demand related to mineral production[43]. Therefore, in traditional availability evaluation, reserves and grade are important geological factors that affect availability. In addition, the mismatch between resource endowment advantages and mineral resource consumption is also an important factor affecting availability. China is the world's largest producer, consumer, and importer of mineral resources. However, due to the mismatch between its resource endowment and consumption, most minerals can only rely on imports to meet domestic demand. The supply of mineral resources has been facing shortages, putting China in a disadvantageous global position[44].
Figure 2. Factors affecting the availability of clean energy metals.
Economic factors
Economic factors are important factors that affect availability, mainly on both sides of supply and demand. The fluctuation in the availability of mineral resources is partly due to the imbalance between supply and demand of mineral resources. In the case of known reserves, mineral companies need to consider economic factors to develop mining strategies to ensure the economic feasibility of the project. The National Development and Reform Commission (NDRC) and National Energy Administration of China plan to invest approximately $36 billion in the development of renewable energy over the next 5 years and create 130,000 employment opportunities in this field[45]. The increase in labor force can also improve the availability of mineral resources in China from a technical perspective. In addition, economic growth is closely related to environmental impacts, and with economic growth and human understanding of nature, further strategies and implemented policies will deepen or alleviate the pressure on resource availability to a certain extent[46].
Technical factors
The impact of technology on availability is mainly reflected in the development of low-grade minerals and the increase in ultimate recoverable reserves. Exploration technology directly affects the available reserves of mineral resources, and mining technology directly affects the available production of mineral resources. As proposed by Ali and Ghoneim[47], a silica exploration method using remote sensing data can significantly increase the available reserves of resources. Mining and beneficiation technology is an important factor affecting availability, among which beneficiation refers to the process of improving the value or quality of raw materials or minerals through various physical, chemical, or biological methods. Strengthen the research and promotion of new technologies and processes in the mining, selecting and smelting process, and continuously improve the comprehensive utilization level of mineral resources, such as biological beneficiation technology, fine-grained lean ore beneficiation technology, comprehensive utilization technology of polymetallic symbiotic ore, tailings reuse technology and so on. The formation of a group of independent intellectual property rights in catalytic reactions, equipment, process technology, and other aspects, creating one's own core competitive advantage, as well as the formation of core technologies and advanced equipment for comprehensive utilization of resources, are conducive to reducing the consumption of mineral resources and improving resource utilization efficiency.
Environmental factors
Environmental issues have always been an important factor affecting the development and utilization of mineral resources. Mining operations can lead to serious degradation of the land, water, and air environment. In addition to non-standard electricity use, heavy metal pollution, dust air pollution, Noise pollution and other problems will also occur in water sources[48]. Overall, the environmental factors that affect the availability of strategic critical minerals can be divided into two categories: compulsory and restrictive environmental regulations. Compulsory environmental factors refer to environmental policies that require mines to be shut down, such as the withdrawal policy of mining rights within China's ecological red line, which is a national strategy implemented by the Chinese government to protect ecologically sensitive areas and resources, aiming to ensure environmental sustainability, biodiversity conservation, and overall ecosystem well-being. Restrictive environmental factors mean that the speed and intensity of mineral resources development are affected by strict environmental policies, such as mine geology environmental remediation, etc. The introduction of these environmental policies requires enterprises to transform their extensive mining and processing methods, manage and restrict resource exploration and extraction, and thus reduce the availability of resources.
Emergencies
Some strategic critical minerals are often concentrated in individual resource countries and are more susceptible to the impact of unexpected events due to their accompanying small mineral characteristics. On the one hand, international geopolitical factors have a significant impact, such as civil wars in major resource countries or strategic support countries[49,50]. On the other hand, global public health events and other emergencies have a profound impact on it, such as the COVID-19 epidemic[51]. For example, China's mineral resources are mainly imported by sea. The overseas supply chain relies on the South China Sea, Pacific, and land routes, with the value of imports through the South China Sea route accounting for 68%. A single transportation channel can lead to high channel dependence and high safety risks. If sudden factors such as war or other natural disasters block transportation channels, more than half of mineral imports will be blocked and supply will be interrupted. When an emergency occurs, the availability of mineral resources will experience a sharp decrease. As the event continues, the availability will gradually decrease. After the event ends, the availability will gradually increase until it returns to its pre-time level. At the same time, the scale of unexpected events can also affect availability. When an emergency occurs in a resource country, if there are alternative resource countries, the availability of mineral resources is less affected. When some mineral resources are concentrated in a few resource countries, they can obtain new geopolitical leverage by cutting off the supply of critical metals, which poses a significant risk of supply interruption. Therefore, the duration and scale of emergencies have a significant impact on the availability of strategic critical minerals, and are important factors in the availability of strategic critical minerals.
Methods for analyzing the availability of clean energy metals
Based on the meaning of mineral resource availability, scholars have begun to explore analytical methods for mineral resource availability. Scholars estimate the availability of resources according to the reserves and mining output of mineral resources. Initially, academia and industry generally used the storage and extraction ratio of mineral resources to calculate the availability of mineral resources[52,53]. Due to the static characteristics and harsh assumptions of storage production ratio analysis, scholars later proposed the widely used Hubbert model, which draws a Hubbert curve based on resource extraction rate and total exploitable resources to analyze the availability of different mineral resources[54-56]. Recently, some scholars have combined the Hubbert model with other models to analyze the availability problem[57]. Wang et al. analyzed the availability of natural gas using the multi-cycle Hubbert model[56].
In addition to the Hubbert model, the Weng circle model (also known as the Poisson circle model)[41,58], the CAC curve[59-61], SD[17,62], and neural networks[63,64] are also considered effective methods for analyzing resource availability. The details are shown in Table 3.
Availability analysis methods (evaluation results)
| Usage method | Method principle | Refs. |
| Production storage ratio | The ratio between mineral resource reserves and annual production, used to evaluate and predict the sustainable mining capacity of mineral resources | [52,53] |
| Hubbert model | A classic oil resource extraction prediction model that predicts future changes in oil production based on key indicators such as the inflection point (i.e., peak) of the oil production curve and oilfield development speed | [54-56] |
| Hubbert model + Copula function | On the basis of the Hubbert model, the Copula function is introduced to consider the correlation between multiple factors, thereby more accurately predicting changes in oil production | [56,57] |
| Generalized Weng’s model | This model is an extension of the Weng Model and is suitable for various types of mineral resource evaluation and prediction. It can consider multiple factors, including the geological characteristics of the deposit, exploration degree, mining technology, market demand, etc. | [58,65,66] |
| Generalized Herfindahl model | It is mainly used to evaluate and predict the market competition pattern, and judge whether there is monopoly in the market by considering the market share and market concentration ratio of different manufacturers | [67-69] |
| Process for evaluating mine availability in the United States | It is a standard process used by the US government for mineral resource management and development, mainly involving geological exploration, reserve assessment, market demand analysis, and other aspects, in order to develop sustainable mineral resource management policies | [70] |
| Availability Analysis System | It is a sustainable development and management system for mineral resources based on GIS (Geographic Information System) and database technology, which can achieve spatial distribution and availability analysis of mineral resources, thereby better managing and developing these resources | [71,72] |
| Agent model | It is a model based on the interaction and game theory between agents, suitable for studying market competition, investment decision-making, and other issues | [73] |
| CAC curve | The CAC (Cumulative Abundance Curve) curve is used to evaluate the distribution of natural resources in different geographical locations or years, and to describe their details and distribution patterns by calculating the cumulative distribution of biological species or mineral resources | [59-61] |
| SD | It is a system analysis method based on system thinking, which can establish a dynamic equilibrium model of multiple systems, simulate and predict the evolution process of the system, in order to achieve system optimization and sustainable development | [17,62] |
| Nervous system | By utilizing the modeling and prediction capabilities of neural networks, complex data can be quickly processed and highly accurate prediction models can be established, which have wide applications in complex mineral resource mining and market prediction | [63,64] |
Clean energy metals availability
The availability of clean energy metals is an important foundation and guarantee for achieving energy transition and low-carbon economy[74]. As a key material for new energy electric vehicles, the supply and demand of lithium-ion batteries have become a focus of attention[75]. The focus of the battery manufacturing industry has always been on China. For example, although Nevada's super factories are expected to reach 2020 gigawatts of production capacity by the end of 35, China's production capacity may be almost twice that by the same year[76]. However, facing a huge supply and demand gap, there is a higher possibility of lithium supply shortage in 2050 than in 2021[77]. With the support of secondary recovery and nickel-based element production, the supply of cobalt can better meet the demand of 2030[78].
RISK EVOLUTION OF CLEAN ENERGY METALS SUPPLY TO ACHIEVE CARBON REDUCTION
Supply risk assessment system
Due to the limited literature directly targeting the supply security of clean energy metals, and considering the significant similarity of mineral resources in supply security, we also include literature on risk assessment of mineral resources supply other than clean energy metals in this section. In the early stage, evaluation indicators for the supply security of mineral resources were mainly proposed based on resource characteristics and application scope, as shown in Table 4. It mainly includes the stability, external dependence, market concentration ratio of resource countries[81-83], resource stocks, supply and demand, and prices[80,81]. Yao and Chang[91] constructed a 4-As quantitative evaluation framework for energy security from the perspectives of energy resource availability, technological applicability, social acceptance, and affordability. Song et al. constructed a new comprehensive indicator, namely the China Energy Security Index (CESI), based on the energy supply dimension, economic and technological dimension, and environmental dimension of energy security[92].
Evaluation Indicators for Mineral Supply Safety
| Number | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| Proportion of reserves/production in the world | √ | √ | √ | √ | √ | √ | ||||
| Reserve and production ratio | √ | √ | √ | √ | √ | √ | √ | √ | ||
| Externally dependent degree | √ | √ | √ | √ | √ | √ | √ | √ | ||
| Mine industrial capital investment | √ | √ | √ | √ | √ | |||||
| Resource country risk | √ | √ | √ | √ | √ | √ | √ | √ | ||
| Concentration ratio of production/ import | √ | √ | √ | √ | √ | √ | √ | √ | √ | √ |
| Price fluctuations | √ | √ | √ | √ | √ | √ | √ | |||
| Demand growth rate | √ | √ | √ | |||||||
| Recycling potential | √ | √ | √ | √ | √ | √ | √ | √ | ||
| Substitutability | √ | √ | √ | √ | √ | |||||
| Byproduct attributes | √ | √ | √ | |||||||
| Refs. | [80] | [81] | [82,83] | [84] | [85] | [86] | [87] | [88] | [89] | [90] |
In recent years, the game among major countries has become increasingly fierce. Geopolitical events such as “Sino-US trade friction” and “Russia-Ukraine conflict” have caused great negative externality to the stability of global resource supply, and the clean energy metals market closely related to energy transition technology bears the brunt. In addition to supply risks caused by resource characteristics and technological factors, supply risks caused by trade and geopolitical risks have become undeniable factors and have affected the development of clean energy technologies and markets.
In terms of the evaluation methods for the safety of mineral resources supply, the research mainly focuses on qualitative analysis and quantitative analysis, as shown in Table 5. The qualitative analysis method mainly relies on the knowledge and experience of experts to determine the degree of various resource supply risks. Quantitative analysis mostly involves selecting evaluation indicators and then using methods such as analytic hierarchy process, entropy method, and principal component analysis to assign weights to them. Then, the annual scores of a certain mineral are calculated longitudinally according to the time series, which enables the analysis of the magnitude of supply risk for each year. Alternatively, multiple minerals can be assessed horizontally to facilitate a comparison of the magnitude of supply risk among them[80,81].
Comparison of common methods for mineral supply safety assessment
| Method | Advantage | Disadvantage |
| AHP | Complex decision-making problems can be transformed into multi-level, single-objective pairwise comparisons | Expert scoring is required to assist in operation, with strong subjectivity |
| Delphi method | Be able to fully leverage the experience and advantages of experts and gather ideas | There may be a certain degree of subjective one-sidedness, making it difficult to distinguish subtle differences in various indicators |
| Topsis | Method for detecting the distance between the evaluation object and the optimal solution | Highly influenced by the data itself |
| Principal Components | Can intuitively analyze the evaluation indicators that play a decisive role and have a significant impact on the comprehensive evaluation results | There is too much dependence on the main indicators, making it difficult to construct an evaluation index system |
| Entropy weight method | Comply with mathematical laws, have strict mathematical significance, and avoid subjectivity in weight assignment | Neglecting the importance of the indicators themselves may differ significantly from the expected results |
Risks in clean energy metals supply caused by international trade
The global production of clean energy metals is mainly concentrated in several countries. According to IEA[6], DRC and South Africa both produce over 70% of cobalt and platinum, China produces 60% of global rare earth, Australia produces over 50% of lithium, and India, the Philippines, and Russia produce over 50% of global nickel. In addition to different resource endowments, manufacturing developed countries such as China, South Korea, Japan, and the United States will import these metals for industrial processing, ultimately consuming them in densely populated countries or regions such as the United States, the European Union, China, and India. Due to the uneven distribution of global mineral resources, international trade has become an important source of supply for global strategic mineral resources[94,95].
In recent years, some scholars have established international trade network models to study the global trade and competition patterns of different mineral resources, and select quantitative indicators such as degree, intensity, intermediation, and intimacy to study their trade patterns and evolution from different perspectives[96-99]. Other scholars have applied competitive networks to study the national competitive landscape and implicit supply risks of strategic resources, identifying the countries and regions with the most concentrated competitive relationships among minerals, as well as the factors that affect the stability of international mineral resource supply[100-102].
In the existing literature, the supply of clean energy metals triggered by international trade has the following points. First, the export and import concentration ratio is high, some resources are monopolistic, and trade is characterized by a “small world”. The trade is centered on countries with rich resources, and the core countries of trade have strong control over the entire trade network. Secondly, the trade network presents a clear core-edge structure, with a more uneven distribution of trade relations. Core countries trade frequently, while peripheral countries trade sparsely. The number of countries at the core of the trade network is increasing year by year, and the trade volume differences between countries are decreasing. Third, there is the Pareto principle in international trade. A few countries have the majority of trade relations, and about 90% of the competition intensity comes from about 10% of the competition relations. Finally, regional competition has shifted towards global competition, and countries tend to import mineral resources from countries closer to their own countries with a weaker trend. Competition between industry chains is gradually moving towards integration[100,101,103-106].
The impact of geopolitics on the risks of clean energy metals supply
After the “Russia-Ukraine conflict”, the entire mineral resources market and global trade have been seriously impacted, and the geopolitical impact on the clean energy metals market has also received unprecedented attention. The risks caused by geopolitics mainly penetrate into various links of the resource industry chain from aspects such as resources, trade, technology, capital, etc.[93,107,108]. Usually, resource sovereignty parliaments engage in geopolitical competition by restricting resource supply and regulating trade, while high-tech countries engage in technological blockades, enterprise sanctions, and other means. These competition strategies can lead to reduced resource extraction, blocked or even interrupted trade channels, and have an impact on trade relations, resource prices, and capital markets[1,109], as shown in Table 6 below.
The competition behavior of geopolitical actors under geopolitical emergencies
| Geopolitical emergencies | Competition behavior | Specific means and their impact | Refs. |
| Russia-Ukraine conflict | Resource export restrictions; Interruption of trade channels; Technical blockade; Capital controls | Prohibiting the import of oil, natural gas, and coal to Russia, exacerbating the global energy supply and demand conflict; Cancellation of routes to Russia, disrupting shipping activities in the Black Sea region; Restricting technology exports to Russia; Restricting financial market activities in Russia and freeze related assets | [110,111] |
| Sino-US trade friction | Resource export restrictions; Technical blockade | Increase trade tariffs between China and the United States, resulting in a decrease in China’s high-tech product exports; Initiate chain transfer of foreign capital industry, and reduce technology spillover effect | [112,113] |
| Conflict minerals control policy | Resource export restrictions; Capital controls | Prevent enterprises from participating in the trade of conflict minerals; Cut off business dealings with mining enterprises in conflict areas | [114,115] |
| Indonesia’s nickel ore export ban | Resource export restriction | Restricting the export of low-value nickel ore has led to a sharp expansion of global nickel ore smelting capacity and severe price fluctuations | [116,117] |
| The six-day war | Resource extraction restrictions; Interruption of trade channels | Rising risks in oil and gas resource extraction and trade; The Straits of Tiran was closed and the trade channel was blocked | [118] |
The impact of geopolitics on the risk of clean energy metals supply is mainly evaluated from two aspects: first, building a geopolitical risk index and using measurement methods to analyze its impact on resource market prices, capital markets, etc.[119-121]; The second is to use geopolitics as a dimension of comprehensive evaluation to evaluate critical metal supply risks[93,122]. Nassar, Brainard, Gulley, Manley, Matos, Lederer, Bird, Pineault, Alonso, Gambogi, and Fortier[123] studied the geopolitical risks of strategic mineral resources supply security from aspects such as trade relations, sharing mechanisms, and military cooperation, and comprehensively evaluated the supply risks of mineral products in the US manufacturing industry.
CLEAN ENERGY METALS SUPPLY GUARANTEE AND POLICY SYSTEM FOR ACHIEVING CARBON REDUCTION
Policy review
The achievement of carbon reduction and the development of low-carbon energy technologies cannot be achieved without a stable and sustainable supply of clean energy metals. In response to the increasing demand for clean energy metals and rising supply risks, different countries have proposed a large number of supportive policies.
The United States has long been at the top of the resource interest chain. Relying on its enormous advantages in industry standard setting, technological level, funding, and international political relations in the clean energy industry, the United States has formulated a series of policies that are conducive to the security of resources and industry development. Due to China's vast industrial system, it requires a large amount of metal resources as support. However, China’s own resource reserves are not sufficient to fully support current industrial activities. Therefore, on the one hand, China's policies improve strategic reserve policies, and on the other hand, enhance the resilience of the mineral resources supply chain to ensure that these resources are less affected by unexpected events. Due to the scarcity of domestic resources, Japan tends to propose policies to increase domestic reserves and recycle resources. As Australia and Canada are countries with rich resources, they will establish resource diplomacy through their own resource advantages and propose policies that are conducive to foreign investment.
Supply guarantee measures
In order to ensure the smooth transition of the energy system from fuel intensive to material intensive, countries and regions such as the United States, Australia, the European Union, Japan, and Canada have successively introduced more comprehensive mineral resource strategies, as shown in Table 7. Overall, firstly, from the perspective of safety level testing, in order to improve the security of metal mineral supply, these countries have proposed policies related to the productivity, technological level, competitiveness, and maintenance of domestic resource security and stability of clean energy metals from multiple dimensions. Secondly, from the perspective of resource recovery and substitution, countries focus on developing new technologies to improve the recycling and processing capabilities of resources and enhance their substitutability. Thirdly, from the perspective of sustainable development, countries adopt energy-saving and emission reduction measures, pay attention to circular development, advocate environmental protection, and improve sustainability. Fourthly, from the perspective of increasing domestic supply, countries have proposed policies to enhance the exploration and mining capabilities of critical minerals, develop alternative technologies, and enhance recycling and resource recycling technologies. Fifth, from the perspective of the diversification of international supply, policies of various countries tend to increase overseas investment, establish resource diplomacy, and strengthen the global supply chain of important mineral resources in their own countries.
Measures for ensuring clean energy metals supply in various countries
| Country | Strategic objectives/tasks | |
| America | Safety level monitoring | Strengthen the monitoring and evaluation capabilities of global strategic materials, do well in intelligence collection work, solve the problem of funds required for domestic production and processing, and establish national defense reserves |
| Resource recycling and substitution | Emphasize the development of mineral recycling and reprocessing technologies, as well as promoting mineral technology alternatives; Provide tax incentives to enterprises that mine, recycle, or recycle critical minerals and metals within the United States | |
| Sustainable development | Develop sustainability standards for critical minerals and develop a “Sustainable Development Plan for Critical Minerals” | |
| Increase domestic supply | Enhance the exploration and mining capabilities of critical minerals, expand access to important resources, increase research and development investment and technological innovation, and improve production capacity | |
| Diversified international supply | Increase overseas investment; Establishing an international supply chain alliance | |
| China | Safety level monitoring | Deepen the reform of “streamlining management and serving”, further improve mineral resource management, and promote the reform of mineral resource management, grasp digital security technology accurately |
| Resource recycling and substitution | Develop and utilize advanced technology, turn “waste” into “treasure”, and improve the utilization level of renewable resources; Further research and development of resource substitution technologies | |
| Sustainable development | Comprehensive investigation and evaluation of resources and green exploration; Promote green and low-carbon development in the national industrial sector; Reduce carbon emissions from the non-ferrous metal industry; Deepening industrial structure, energy conservation, emission reduction, and technological upgrading | |
| Increase domestic supply | Introduce incentive policies to enhance domestic exploration and development capabilities; Establish mineral resource reserves; Increase research and development efforts | |
| Diversified international supply | Develop a “going global” policy to increase foreign direct investment; Strengthen export controls; Introduce foreign capital; Diversify supply | |
| European Union | Safety level monitoring | Organize and strengthen data collection and management across Europe |
| Resource recycling and substitution | Waste recycling management; Innovating technology to improve the substitutability of traditional energy sources | |
| Sustainable development | Promote the effective utilization and recycling of critical minerals, making circular economy a priority area for the EU; Focus on circular economy and sustainable procurement | |
| Increase domestic supply | Research and innovation of raw materials; Improve skills and focus research on innovative exploration and mining technologies, recycling, raw material substitution, and resource efficiency | |
| Diversified international supply | Establish strategic partnerships with resource-rich countries covering mining, processing, and refining; Optimize the overseas supply chain of resources | |
| Australia | Safety level monitoring | Conduct technological innovation; Enhance the security, productivity, and competitiveness of the resource sector |
| Sustainable development | Produce sustainable resource products through rich environmental and labor practices | |
| Increase domestic supply | Increase investment in domestic resource projects to ensure investment, financing, and market access for important mineral projects; Expand the scope and capacity of resource exploration | |
| Diversified international supply | Promote and strengthen cooperation with relevant departments and international supply chains; Resource diplomacy | |
| Japan | Safety level monitoring | Build a global cooperation network for overseas geological surveys; Strengthen overseas resource survey evaluation and information services |
| Resource recycling and substitution | Promote recycling and research and development of recycling technologies; Actively develop alternative industries and implement resource substitution strategies | |
| Sustainable development | Build a resource-saving society and improve sustainability | |
| Increase domestic supply | Promote the development of alternative materials; Improve the reserve mechanism system and strengthen the reserve of critical raw materials | |
| Diversified international supply | Carry out extensive resource diplomacy to ensure the security of overseas resources and achieve diversified supply; Establish specialized agencies to organize and implement overseas geological survey strategies, and vigorously support overseas operations of Japanese mining companies; Adopt diversified overseas geological survey cooperation methods according to local conditions | |
| Canada | Safety level monitoring | A complete and clear mining management system ensures transparency and predictability in mining development; Financial policies share survey risks |
| Resource recycling and substitution | Maintain resource recycling and minimize waste; Retain the inherent characteristics of metals throughout the entire recycling process; Reuse and maintain their quality and functionality | |
| Sustainable development | Reduce waste emissions and enhance sustainable development capabilities; Build future “low carbon footprint” mines, and manage the heritage of past mining activities; Protect the natural environment | |
| Increase domestic supply | Improve the processing technology for critical minerals; Cultivate a highly skilled workforce with professional knowledge in fields such as mining technology, geological and biological sciences, artificial intelligence, and space science | |
| Diversified international supply | Strengthen competitive advantage and enhance global leadership in mining industry | |
CONCLUSION
This paper starts with the process of carbon reduction, defines the connotation of clean energy metals, and considers the analysis methods for predicting the future demand for clean energy metals in the existing literature and the uncertainties faced in the future. At the same time, the analysis methods and influencing factors of the future availability of clean energy metals are analyzed. Furthermore, we analyze the significant impact of international trade and geopolitical factors on the risk of clean energy metal supply. Finally, ensuring the supply of clean energy metals during the process of achieving carbon reduction requires policy support. This article summarizes the policy measures proposed by major countries around the world.
In order to achieve carbon reduction targets, we suggest that further research on clean energy metals should also be carried out in the following aspects. First, due to the uneven global distribution of clean energy metals and the frequent occurrence of geopolitical events such as trade protectionism and resource nationalism, it is necessary to focus on how clean energy metals are affected by trade and geopolitics, the impact mechanism, and how to address the impact of trade and geopolitical factors. Secondly, effective policy guarantee measures are crucial for countries to achieve their carbon reduction goals. There are many current policies, but there is little research on the effectiveness of policies. Future research also needs to evaluate the effectiveness of policies more to provide a basis for their continued implementation. Finally, existing literature lacks a comprehensive exploration of the sustainable supply of clean energy metals from the perspective of the entire industry chain. Future research should extend the global governance of clean energy metals from the original resource governance to the governance of the industry chain supply chain, and explore the mechanism innovation of countries participating in the global governance of clean energy metals.
DECLARATIONS
AcknowledgmentsWe are grateful to the editor and the anonymous referees for their helpful comments and suggestions.
Authors’ contributionsSupervision, Project Management, Validation, Conceptualization: Shao L
Conceptualization, Investigation, Writing-original Draft Preparation: Zhang H
Literature collection, Validation, Writing-original Draft Preparation: Zhang T
Writing-original Draft Preparation: Cao S
Validation, Conceptualization: Lan T
Availability of data and materialsNot applicable.
Financial support and sponsorshipThe authors wish to express their gratitude for the support provided by the National Social Science Fund of China (Grant No. 22&ZD098), the National Natural Science Foundation of China (Grant No. 71974208), and the National Social Science Fund of China (Grant No. 21&ZD103).
Conflicts of interestAll authors declared that there are no conflicts of interest.
Ethical approval and consent to participateNot applicable.
Consent for publicationNot applicable.
Copyright© The Author(s) 2023.
REFERENCES
1. Ali S, Giurco D, Arndt N, et al. Mineral supply for sustainable development requires resource governance. Nature 2017;543:367-72.
2. Shao L, Zhang H. The impact of oil price on the clean energy metal prices: a multi-scale perspective. Resour Policy 2020;68:101730.
3. Shao L, Zhang H, Chen J, Zhu X. Effect of oil price uncertainty on clean energy metal stocks in China: evidence from a nonparametric causality-in-quantiles approach. Int Rev Econ Finance 2021;73:407-19.
5. Grandell L, Lehtilä A, Kivinen M, Koljonen T, Kihlman S, Lauri LS. Role of critical metals in the future markets of clean energy technologies. Renew Energy 2016;95:53-62.
6. IEA. An energy sector roadmap to carbon neutrality in China 2021. Available from: https://www.oecd-ilibrary.org/energy/an-energy-sector-roadmap-to-carbon-neutrality-in-china_5f517ddb-en [Last accessed on 10 August 2023].
7. Zhang L, Chen Z, Yang C, Xu Z. Global supply risk assessment of the metals used in clean energy technologies. J Clean Prod 2022;331:129602.
8. Wang P, Chen L, Ge J, Cai W, Chen W. Incorporating critical material cycles into metal-energy nexus of China’s 2050 renewable transition. Appl Energy 2019;253:113612.
9. Wang P, Wang H, Chen W, Pauliuk S. Carbon neutrality needs a circular metal-energy nexus. Fundam Res 2022;2:392-5.
10. Ren K, Tang X, Wang P, Willerström J, Höök M. Bridging energy and metal sustainability: insights from China’s wind power development up to 2050. Energy 2021;227:120524.
11. Tang C, Sprecher B, Tukker A, Mogollón JM. The impact of climate policy implementation on lithium, cobalt and nickel demand: the case of the Dutch automotive sector up to 2040. Resour Policy 2021;74:102351.
12. Nassar NT, Wilburn DR, Goonan TG. Byproduct metal requirements for U.S. wind and solar photovoltaic electricity generation up to the year 2040 under various clean power plan scenarios. Appl Energy 2016;183:1209-26.
13. Wu J, Yang J, Ma L, Li Z, Shen X. A system analysis of the development strategy of iron ore in China. Resour Policy 2016;48:32-40.
14. Liu QY, Wang AJ, Chen QS. Analysis for the global demand of energy in the next 20 years. Adv Mater Res 2013;734-7:1719-23.
15. Li Y, Wang AJ, Chen QS, Liu QY. Influencing factors of chinese aluminium resources demand in the next 20 years. Adv Mater Res 2013;734-7:122-8.
16. Mermer C, Şengül H. Addressing potential resource scarcity for boron mineral: a system dynamics perspective. J Clean Prod 2020;270:122192.
17. Sverdrup HU, Ragnarsdottir KV. A system dynamics model for platinum group metal supply, market price, depletion of extractable amounts, ore grade, recycling and stocks-in-use. Resour Conserv Recycl 2016;114:130-52.
18. Ciacci L, Fishman T, Elshkaki A, Graedel T, Vassura I, Passarini F. Exploring future copper demand, recycling and associated greenhouse gas emissions in the EU-28. Glob Environ Chang 2020;63:102093.
19. Schipper BW, Lin H, Meloni MA, Wansleeben K, Heijungs R, van der Voet E. Estimating global copper demand until 2100 with regression and stock dynamics. Resour Conserv Recycl 2018;132:28-36.
20. Elshkaki A, Graedel T. Dysprosium, the balance problem, and wind power technology. Appl Energy 2014;136:548-59.
21. Dong D, Tukker A, Van der Voet E. Modeling copper demand in China up to 2050: a business-as-usual scenario based on dynamic stock and flow analysis. J Ind Ecol 2019;23:1363-80.
22. Krausmann F, Wiedenhofer D, Lauk C, et al. Global socioeconomic material stocks rise 23-fold over the 20th century and require half of annual resource use. Proc Natl Acad Sci USA 2017;114:1880-5.
23. Wiedenhofer D, Steinberger JK, Eisenmenger N, Haas W. Maintenance and expansion: modeling material stocks and flows for residential buildings and transportation networks in the EU25. J Ind Ecol 2015;19:538-51.
24. Tokimatsu K, Wachtmeister H, Mclellan B, et al. Energy modeling approach to the global energy-mineral nexus: a first look at metal requirements and the 2 °C target. Appl Energy 2017;207:494-509.
25. Elshkaki A, Shen L. Energy-material nexus: the impacts of national and international energy scenarios on critical metals use in China up to 2050 and their global implications. Energy 2019;180:903-17.
26. Habib K, Hansdóttir ST, Habib H. Critical metals for electromobility: global demand scenarios for passenger vehicles, 2015-2050. Resour Conserv Recycl 2020;154:104603.
27. Pehlken A, Albach S, Vogt T. Is there a resource constraint related to lithium ion batteries in cars? Int J Life Cycle Assess 2017;22:40-53.
28. Hao H, Geng Y, Tate JE, et al. Impact of transport electrification on critical metal sustainability with a focus on the heavy-duty segment. Nat Commun 2019;10:5398.
29. Li X, Ge J, Chen W, Wang P. Scenarios of rare earth elements demand driven by automotive electrification in China: 2018-2030. Resour Conserv Recycl 2019;145:322-31.
30. Wang P, Zhao S, Dai T, et al. Regional disparities in steel production and restrictions to progress on global decarbonization: a cross-national analysis. Renew Sustain Energy Rev 2022;161:112367.
31. Tong X, Dai H, Lu P, Zhang A, Ma T. Saving global platinum demand while achieving carbon neutrality in the passenger transport sector: linking material flow analysis with integrated assessment model. Resour Conserv Recycl 2022;179:106110.
32. Yang J, Yu Y, Ma T, Zhang C, Wang Q. Evolution of energy and metal demand driven by industrial revolutions and its trend analysis. Chin J Popul Resour Environ 2021;19:256-64.
33. Watari T, Nansai K, Nakajima K. Major metals demand, supply, and environmental impacts to 2100: a critical review. Resour Conserv Recycl 2021;164:105107.
34. Qiao D, Wang G, Gao T, Wen B, Dai T. Potential impact of the end-of-life batteries recycling of electric vehicles on lithium demand in China: 2010-2050. Sci Total Environ 2021;764:142835.
35. Mo J, Jeon W. The impact of electric vehicle demand and battery recycling on price dynamics of lithium-ion battery cathode materials: a vector error correction model (VECM) analysis. Sustainability 2018;10:2870.
36. Shao L, Kou W, Zhang H. The evolution of the global cobalt and lithium trade pattern and the impacts of the low-cobalt technology of lithium batteries based on multiplex network. Resour Policy 2022;76:102550.
37. Shao L, Wang Z, Lan T. Formation mechanism and countermeasures of China’s new energy vehicle industry shakeouts. Resour Sci 2022;44:1316-30.
38. Jones B, Elliott RJR, Nguyen-Tien V. The EV revolution: the road ahead for critical raw materials demand. Appl Energy 2020;280:115072.
39. Xu C, Dai Q, Gaines L, Hu M, Tukker A, Steubing B. Future material demand for automotive lithium-based batteries. Commun Mater 2020;1:99.
40. Maisel F, Neef C, Marscheider-weidemann F, Nissen NF. A forecast on future raw material demand and recycling potential of lithium-ion batteries in electric vehicles. Resour Conserv Recycl 2023;192:106920.
41. Northey SA, Mudd GM, Werner TT. Unresolved complexity in assessments of mineral resource depletion and availability. Nat Resour Res 2018;27:241-55.
42. West J. Decreasing metal ore grades: are they really being driven by the depletion of high-grade deposits? J Ind Ecol 2011;15:165-8.
43. Northey S, Mohr S, Mudd G, Weng Z, Giurco D. Modelling future copper ore grade decline based on a detailed assessment of copper resources and mining. Resour Conserv Recycl 2014;83:190-201.
44. Luo X, Pan L, Yang J. Mineral resource constraints for China’s clean energy development under carbon peaking and carbon neutrality targets: quantitative evaluation and scenario analysis. Energies 2022;15:7029.
45. Zahoor Z, Khan I, Hou F. Clean energy investment and financial development as determinants of environment and sustainable economic growth: evidence from China. Environ Sci Pollut Res Int 2022;29:16006-16.
47. Ali HF, Ghoneim SM. Satellite-based silica mapping as an essential mineral for clean energy transition: Remote sensing mineral exploration as a climate change adaptation approach. J Afr Earth Sci 2022;196:104683.
48. Burchart-Korol D, Fugiel A, Czaplicka-Kolarz K, Turek M. Model of environmental life cycle assessment for coal mining operations. Sci Total Environ 2016;562:61-72.
49. Habib K, Hamelin L, Wenzel H. A dynamic perspective of the geopolitical supply risk of metals. J Clean Prod 2016;133:850-8.
50. Dogan E, Majeed MT, Luni T. Analyzing the impacts of geopolitical risk and economic uncertainty on natural resources rents. Resour Policy 2021;72:102056.
51. Sarkis J, Cohen MJ, Dewick P, Schröder P. A brave new world: lessons from the COVID-19 pandemic for transitioning to sustainable supply and production. Resour Conserv Recycl 2020;159:104894.
52. Barnhart CJ, Benson SM. On the importance of reducing the energetic and material demands of electrical energy storage. Energy Environ Sci 2013;6:1083-92.
53. Bartlett AA. A depletion protocol for non-renewable natural resources: Australia as an example. Nat Resour Res 2007;15:151-64.
54. Valero A, Valero A. Physical geonomics: combining the exergy and hubbert peak analysis for predicting mineral resources depletion. Resour Conserv Recycl 2010;54:1074-83.
55. Scholz RW, Ulrich AE, Eilittä M, Roy A. Sustainable use of phosphorus: a finite resource. Sci Total Environ 2013;461-2:799-803.
56. Wang J, Jiang H, Zhou Q, Wu J, Qin S. China’s natural gas production and consumption analysis based on the multicycle Hubbert model and rolling Grey model. Renew Sustain Energy Rev 2016;53:1149-67.
57. Xu D, Zhu Y. A copula-hubbert model for Co(By)-product minerals. Nat Resour Res 2020;29:3069-78.
58. Wang J, Ju Y, Wang M, Li X. Scenario analysis of the recycled copper supply in China considering the recycling efficiency rate and waste import regulations. Resour Conserv Recycl 2019;146:580-9.
59. Castillo E, Eggert R. Reconciling diverging views on mineral depletion: a modified cumulative availability curve applied to copper resources. Resour Conserv Recycl 2020;161:104896.
60. Jordan BW, Eggert RG, Dixon BW, Carlsen BW. Thorium: crustal abundance, joint production, and economic availability. Resour Policy 2015;44:81-93.
61. Yaksic A, Tilton JE. Using the cumulative availability curve to assess the threat of mineral depletion: the case of lithium. Resour Policy 2009;34:185-94.
62. Bustamante ML, Gaustad G. Challenges in assessment of clean energy supply-chains based on byproduct minerals: a case study of tellurium use in thin film photovoltaics. Appl Energy 2014;123:397-414.
63. Chen F, Tiwari S, Mohammed KS, Huo W, Jamróz P. Minerals resource rent responses to economic performance, greener energy, and environmental policy in China: combination of ML and ANN outputs. Resour Policy 2023;81:103307.
64. Jiang L, Jiang H. Analysis of predictions considering mineral prices, residential energy, and environmental risk: Evidence from the USA in COP 26 perspective. Resour Policy 2023;82:103431.
65. Islam M, Saidur R, Rahim N. Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function. Energy 2011;36:985-92.
66. Wang X, Lei Y, Ge J, Wu S. Production forecast of China’s rare earths based on the Generalized Weng model and policy recommendations. Resour Policy 2015;43:11-8.
67. Ioannidis A, Chalvatzis KJ, Li X, Notton G, Stephanides P. The case for islands’ energy vulnerability: electricity supply diversity in 44 global islands. Renew Energy 2019;143:440-52.
68. Geissler B, Mew MC, Steiner G. Phosphate supply security for importing countries: developments and the current situation. Sci Total Environ 2019;677:511-23.
69. Mohsin M, Zhou P, Iqbal N, Shah S. Assessing oil supply security of South Asia. Energy 2018;155:438-47.
70. Yuwei L. The principle and methodology of mineral availability analysis. Nat Res Econ China 2015;28:8-13.
71. Werner T, Bebbington A, Gregory G. Assessing impacts of mining: recent contributions from GIS and remote sensing. Extr Ind Soc 2019;6:993-1012.
72. Cui C, Wang B, Zhao Y, Wang Q, Sun Z. China’s regional sustainability assessment on mineral resources: results from an improved analytic hierarchy process-based normal cloud model. J Clean Prod 2019;210:105-20.
73. Riddle M, Macal CM, Conzelmann G, Combs TE, Bauer D, Fields F. Global critical materials markets: an agent-based modeling approach. Res Policy 2015;45:307-21.
74. Shao L, Lan T. Review of the by- product critical minerals resource security research and prospects. Resour Sci 2020;42:1452-63.
75. Shao L, Jin S. Resilience assessment of the lithium supply chain in China under impact of new energy vehicles and supply interruption. J Clean Prod 2020;252:119624.
76. Olivetti EA, Ceder G, Gaustad GG, Fu X. Lithium-ion battery supply chain considerations: analysis of potential bottlenecks in critical metals. Joule 2017;1:229-43.
77. Calisaya-azpilcueta D, Herrera-leon S, Lucay FA, Cisternas LA. Assessment of the supply chain under uncertainty: the case of lithium. Minerals 2020;10:604.
78. Fu XK, Beatty DN, Gaustad GG, et al. Perspectives on cobalt supply through 2030 in the face of changing demand. Environ Sci Technol 2020;54:2985-93.
79. Elshkaki A, Graedel T, Ciacci L, Reck BK. Copper demand, supply, and associated energy use to 2050. Glob Environ Chang 2016;39:305-15.
80. Ma Y, Sha J, Yan J, et al. Safety assessment and countermeasures of nickel resource supply in China. Resour Sci 2019;41:1317-28.
81. Yihao S. Supply security evaluation and security strategy study of cobalt resources in China. 2019.
83. Wang D, Wang W, Chen W. Supply security of strategic metal ores in China. Res Ind 2019;21:22-30.
85. Achzet B, Helbig C. How to evaluate raw material supply risks - an overview. Resour Policy 2013;38:435-47.
86. Jasiński D, Cinelli M, Dias LC, Meredith J, Kirwan K. Assessing supply risks for non-fossil mineral resources via multi-criteria decision analysis. Resour Policy 2018;58:150-8.
87. Zhang L, Bai W, Yu J, et al. Critical mineral security in china: an evaluation based on hybrid MCDM methods. Sustainability 2018;10:4114.
88. Zhou Y, Li J, Wang G, Chen S, Xing W, Li T. Assessing the short-to medium-term supply risks of clean energy minerals for China. J Clean Prod 2019;215:217-25.
89. Zhou N, Wu Q, Hu X, Zhu Y, Su H, Xue S. Synthesized indicator for evaluating security of strategic minerals in China: a case study of lithium. Resour Policy 2020;69:101915.
90. Yu S, Duan H, Cheng J. An evaluation of the supply risk for China’s strategic metallic mineral resources. Resour Policy 2021;70:101891.
91. Yao L, Chang Y. Energy security in China: a quantitative analysis and policy implications. Energy Policy 2014;67:595-604.
92. Song Y, Zhang M, Sun R. Using a new aggregated indicator to evaluate China’s energy security. Energy Policy 2019;132:167-74.
93. Liao Q, Sun M. Security evaluation of lithium resources supply in china under the background of “anti-globalization”. Mining 2022;42:179-86.
94. Klimek P, Obersteiner M, Thurner S. Systemic trade risk of critical resources. Sci Adv 2015;1:e1500522.
95. Hao H, Geng Y, Tate JE, et al. Securing platinum-group metals for transport low-carbon transition. One Earth 2019;1:117-25.
96. Chen G, Kong R, Wang Y. Research on the evolution of lithium trade communities based on the complex network. Physica A 2020;540:123002.
97. Wang C, Huang X, Lim MK, Tseng M, Ghadimi P. Mapping the structural evolution in the global scrap copper trade network. J Clean Prod 2020;275:122934.
98. Zhao Y, Gao X, An H, Xi X, Sun Q, Jiang M. The effect of the mined cobalt trade dependence network’s structure on trade price. Resour Policy 2020;65:101589.
99. Ge J, Wang X, Guan Q, Li W, Zhu H, Yao M. World rare earths trade network: patterns, relations and role characteristics. Resour Policy 2016;50:119-30.
100. Shao L, Hu J, Zhang H. Evolution of global lithium competition network pattern and its influence factors. Resour Policy 2021;74:102353.
101. Huang J, Ding Q, Wang Y, Hong H, Zhang H. The evolution and influencing factors of international tungsten competition from the industrial chain perspective. Resour Policy 2021;73:102185.
102. Gulley AL, Nassar NT, Xun S. China, the United States, and competition for resources that enable emerging technologies. Proc Natl Acad Sci USA 2018;115:4111-5.
103. Liu D, Liu JC, Huang H, Sun K. Analysis of the international polysilicon trade network. Resour Conserv Rec 2019;142:122-30.
104. Yu G, Xiong C, Xiao J, He D, Peng G. Evolutionary analysis of the global rare earth trade networks. Appl Math Comput 2022;430:127249.
105. Wang X, Li H, Yao H, Zhu D, Liu N. Simulation analysis of the spread of a supply crisis based on the global natural graphite trade network. Resour Policy 2018;59:200-9.
106. Sun X, Shi Q, Hao X. Supply crisis propagation in the global cobalt trade network. Resour Conserv Rec 2022;179:106035.
108. Galos K, Lewicka E, Burkowicz A, et al. Approach to identification and classification of the key, strategic and critical minerals important for the mineral security of Poland. Resour Policy 2021;70:101900.
109. Gulley AL, Mccullough EA, Shedd KB. China’s domestic and foreign influence in the global cobalt supply chain. Resour Policy 2019;62:317-23.
110. Umar Z, Polat O, Choi S, Teplova T. The impact of the Russia-Ukraine conflict on the connectedness of financial markets. Finance Res Lett 2022;48:102976.
111. European Commission. Press statement by President von der Leyen on a new package of restrictive measures against Russia 2022. Available from: https://www.eeas.europa.eu/delegations/ukraine/press-statement-president-von-der-leyen-new-package-restrictive-measures_en?s=232 [Last accessed on 10 August 2023].
112. Li Y, Chen B, Li C, Li Z, Chen G. Energy perspective of Sino-US trade imbalance in global supply chains. Energy Econ 2020;92:104959.
113. Chen T, Lin C, Shao X. Globalization and U.S. corporate tax policies: evidence from import competition. SSRN J 2021.
114. Hanai K. Conflict minerals regulation and mechanism changes in the DR Congo. Resour Policy 2021;74:102394.
115. Koch D, Burlyuk O. Bounded policy learning? EU efforts to anticipate unintended consequences in conflict minerals legislation. J Eur Public Policy 2020;27:1441-62.
116. Camba A. The unintended consequences of national regulations: large-scale-small-scale relations in Philippine and Indonesian nickel mining. Resour Policy 2021;74:102213.
117. Dong X, An F, Dong Z, et al. Optimization of the international nickel ore trade network. Resour Policy 2021;70:101978.
118. Shalom Z. Israel’s Foreign minister eban meets president de gaulle and prime minister wilson on the eve of the six day war. Isr Aff 2008;14:277-87.
119. Wang B, Wang L, Zhong S, Xiang N, Qu Q. Assessing the supply risk of geopolitics on critical minerals for energy storage technology in China. Front Energy Res 2023;10:1032000.
120. Sweidan OD. The geopolitical risk effect on the US renewable energy deployment. J Clean Prod 2021;293:126189.
121. Flouros F, Pistikou V, Plakandaras V. Geopolitical risk as a determinant of renewable energy investments. Energies 2022;15:1498.
122. Liu W, Li X, Liu C, Wang M, Liu L. Resilience assessment of the cobalt supply chain in China under the impact of electric vehicles and geopolitical supply risks. Resour Policy 2023;80:103183.
Cite This Article
Export citation file: BibTeX | RIS
OAE Style
Shao L, Zhang H, Zhang T, Cao S, Lan T. Securing the supply of clean energy metals to achieve carbon reduction: a review. Carbon Footprints 2023;2:16. http://dx.doi.org/10.20517/cf.2023.33
AMA Style
Shao L, Zhang H, Zhang T, Cao S, Lan T. Securing the supply of clean energy metals to achieve carbon reduction: a review. Carbon Footprints. 2023; 2(3): 16. http://dx.doi.org/10.20517/cf.2023.33
Chicago/Turabian Style
Shao, Liuguo, Hua Zhang, Ting Zhang, Saisha Cao, Tingting Lan. 2023. "Securing the supply of clean energy metals to achieve carbon reduction: a review" Carbon Footprints. 2, no.3: 16. http://dx.doi.org/10.20517/cf.2023.33
ACS Style
Shao, L.; Zhang H.; Zhang T.; Cao S.; Lan T. Securing the supply of clean energy metals to achieve carbon reduction: a review. Carbon. Footprints. 2023, 2, 16. http://dx.doi.org/10.20517/cf.2023.33
About This Article
Copyright
Data & Comments
Data
0
Cite This Article 9 clicks
Like This Article 13
likes
Comments
Comments must be written in English. Spam, offensive content, impersonation, and private information will not be permitted. If any comment is reported and identified as inappropriate content by OAE staff, the comment will be removed without notice. If you have any queries or need any help, please contact us at support@oaepublish.com.