Geopolitical-related supply risk assessment as a complement to environmental impact assessment: the case of electric vehicles

  • Eskinder D. Gemechu
  • Guido Sonnemann
  • Steven B. Young



Introducing a geopolitical-related supply risk (GeoPolRisk) into the life cycle sustainability assessment (LCSA) framework adds a criticality aspect to the current life cycle assessment (LCA) framework to more meaningfully address direct impacts on Natural Resource AoP. The weakness of resource indicators in LCA has been the topic of discussion within the life cycle community for some time. This paper presents a case study on how to proceed towards the integration of resource criticality assessment into LCA under the LCSA. The paper aims at highlighting the significance of introducing the GeoPolRisk indicator to complement and extend the established environmental LCA impact categories.


A newly developed GeoPolRisk indicator proposed by Gemechu et al., J Ind Ecol (2015) was applied to metals used in the life cycle of an electric vehicle, and the results are compared with an attributional LCA of the same resources. The inventory data is based on the publication by Hawkins et al., J Ind Ecol 17:53–64 (2013), which provides a current, transparent, and detailed life cycle inventory data of a European representative first-generation battery small electric vehicle.

Results and discussion

From the 14 investigated metals, copper, aluminum, and steel are the most dominant elements that pose high environmental impacts. On the other hand, magnesium and neodymium show relatively higher supply risk when geopolitical elements are considered. While, the environmental indicator results all tend to point the same hotspots which arise from the substantial use of resources in the electric vehicle’s life cycle, the GeoPolRisk highlights that there are important elements present in very small amounts but crucial to the overall LCSA. It provides a complementary sustainability dimension that can be added to conventional LCA as an important extension within LCSA.


Resource challenges in a short-term time perspective can be better addressed by including social and geopolitical factors in addition to the conventional indicators which are based on their geological availability. This is more significant for modern technologies such as electronic devices in which critical resources contribute to important components. The case study advances the use of the GeoPolRisk assessment method but does still face certain limitations that need further elaboration; however, directions for future research are promising.


Criticality assessment Electric vehicle Environmental impacts Geopolitical-related supply risk Life cycle assessment Resources 

1 Introduction

Life cycle assessment (LCA) is a systematic tool to quantify environmental impacts associated with the life cycle of products (Guinée et al. 2002; Sonnemann et al. 2003; ISO 2006). A number of studies have been conducted to assess environmental performance of electric vehicles (EV), mainly with the aim of evaluating potential environmental life cycle benefits compared to conventional fossil fuel powered with internal combustion engine vehicles (ICEVs). Two intensive reviews on existing studies have been completed by Hawkins et al. (2012) and Nordelöf et al. (2014). While most literature discusses environmental impacts related to emissions of pollutants, resource issues associated with these technologies are largely overlooked. A few studies discuss the availability issues of specialty metals used in EVs components, such as rare earth elements in NiMH batteries, cobalt in both NiMH and Li-ion batteries, and lithium in lithium-ion batteries (Andersson and Råde 2001; Rydh and Svärd 2003; Gaines and Nelson 2010).

Electric vehicle technologies utilize a wide range of functional materials such as neodymium, dysprosium, cobalt, lithium, and magnesium. These are among resources that have been identified as strategic because of geopolitical issues in the regions where they are sourced, geologically availability is limited to few locations, or their production in only a few countries (European Commission 2010, 2014; Moss et al. 2013b; Graedel et al. 2013). As such, there is risk that supply disruption of these resources could constrain the future deployment of EVs, for example, in materials for lithium-ion battery energy storage systems. The sustainable supply of lithium has become a top priority for different global companies as both the metal reserve and production are controlled by a few countries (USGS 2014). The high price volatility due to limited availability and accessibility of strategic minerals calls for the development of a systematic analytical tool to assess supply risks of resources due to their usage; this is what resource criticality assessment can provide.

Criticality assessment aims at displaying an aggregation of economic, environmental, and social risks of raw materials, and assessing potential consequences of those risks (National Research Council 2008; European Commission 2010, 2014; DOE 2011; Erdmann and Graedel 2011; Graedel et al. 2012; Nassar et al. 2012; Moss et al. 2013a; Zepf et al. 2014). Most criticality assessments to date are based on principles of material flow analysis, and are designed as stand-alone evaluations of raw materials. However, recent interest has been shown from the LCA community towards the combined use of criticality concept in life cycle sustainability assessment (LCSA) in order to meaningfully address the direct impact from the use of natural resources (European Commission 2011). The workshop by the EC Joint Research Center on “Security of supply and scarcity of raw materials: a methodological framework for sustainability assessment,” (European Commission 2012), the 55th LCA discussion forum on abiotic resources from ETH Zurich and recent work from Schneider et al. (2014), Mancini et al. (2015), and Gemechu et al. (2015) are examples.

Resource impacts in LCA are limited to crude methods based on constraints of geological availability of elements. However, the true economic availability of resources cannot be addressed only by considering geological accessibility, as there are also social, geopolitical, legislation, environmental regulations, and other constraints that affect the access and sustainable supply of minerals and resources (Herrington 2013). The established LCA framework fails to address such issues. New frameworks for LCA have emerged under the name of LCSA, as a next-generation of environmental LCA. LCSA has been successful at addressing areas of social concern like labor and gender rights (Kloepffer 2008; Finkbeiner et al. 2010; UNEP 2011; Valdivia et al. 2013). Hence, this paper explores how to add resource criticality concepts into the LCSA framework. The paper aims at addressing the importance of such integration and proposes an initial approach to how it could be done. Thus, this work contributes a new approach for geopolitical-related supply risk criticality assessment under the LCSA framework, and provides an illustrative case of this approach applied to relevant mineral resources required in the production of an EV. In this way, geopolitical-related supply risk complements and extends the established environmental LCA impact categories.

The paper is organized as a typical LCA study, as it is based on an existing published study and augments that with critical analysis. The second section explains the methodological foundation of the approach, examining both the environmental impact assessment and the geopolitically related supply risk. It also describes the goal and scope of the study, functional unit, and system boundary selection. The third section is dedicated to presentation of results and provides detailed discussion around the criticality outcomes. The last section provides the main conclusions and future perspectives, with a focus on strengths and limitations of the criticality approach.

2 Methods

The goal of this study is to show how the scope of conventional LCA can be broadened from only environmental assessment tool to include resource criticality in the tool. In the presented case study, both environmental and criticality concepts are integrated within the LCSA framework with a common understanding of the Natural Resource AoP and the importance of social and economic dimensions as a complementary to the environmental aspects. This is done using a case study to introduce a newly developed geopolitical-related supply risk indicator (Gemechu et al. 2015). The study draws on the structure and inventory data for a European representative first-generation battery small EV published by Hawkins et al. (2013), which provides a current, transparent, and detailed life cycle inventory on this technology.

The inventory data include both material and energy requirements and associated emissions throughout the life cycle of an EV from production, use, and end-of-life including all relevant supply chains. However, in the present study, only the resource requirement in the production phase is considered. Hawkins et al. (2013) showed that electricity consumption during the use phase typically dominates the life cycle of an EV with regard to environmental impact assessment; however, as the focus here is on metal resources, the use phase is not considered. There is high potential for recycling valuable metals from discarded EVs, which points to the relevance of considering its end-of-life phase. It is important to consider recycling while assessing overall supply risk; however, in this specific case, as the main focus is geopolitical-related supply risk of primary resources, recycling is not taken into account. This is a subject for future research.

In line with the inventory data from Hawkins et al. (2013), a functional unit of one EV is considered. Fourteen important metal resources utilized in the production of an EV are included. In terms of mass and volume of ferrous metals (steel and iron), aluminum and copper are the greatest. Steel is used in the base of the vehicle for body and doors, chassis, interior and exterior, and tires and wheels. A small portion of steel and iron is also used in the powertrain. Aluminum is mainly applied in the motor and other powertrain components, but also in the interior and exterior base of the vehicle. Copper is employed in the motor and powertrain for wiring and connectors. Other metals such as lead, magnesium, zinc, platinum group metals, and neodymium are used considerably in smaller amounts. Figure 1 shows the mass content of one vehicle.
Fig. 1

Main material of the EV (own elaboration based on data from Hawkins et al. (2012)

2.1 Environmental impact assessment

Environmental life cycle impact assessment was carried out to explore the contribution of each resource to selected impact categories, consistent with Hawkins et al. (2013), using the ReCiPe midpoint method with Hierarchist perspective: global warming potential (GWP), metal depletion potential (MDP), human toxicity potential (HTP), and freshwater ecotoxicity potential (FETP). According to Hawkins et al. (2013), these categories are mainly caused by the supply chain in the production of the vehicle. Background inventory data from ecoinvent databases (ecoinvent v3.1) and SimaPro LCA software were utilized.

2.2 The geopolitical-related supply risk

In addition to the environmental impact, aspects of criticality of metal elements were added as a complementary indicator using a recently developed approach (Gemechu et al. 2015). The significance of integrating criticality assessment into LCA is discussed by Schneider et al. (2014) and Sonnemann et al. (2015). The current method follows broader criticality assessment as described by Graedel et al. (2012), who suggest three broad dimensions: supply risk, vulnerability to supply disruption, and environmental aspect. The geopolitical aspect is the constraint factor that determines potential of supply disruption. Other geological, social, and economic aspects are beyond the scope of this paper.

The geopolitical-related supply risk, hereinafter referred to as “GeoPolRisk,” is calculated using Eq. (1), derived in detail by Gemechu et al. (2015):
$$ {\mathrm{SR}}_{c,i}=\left[\left({\displaystyle \sum_{k=1}^n{s}_k^2}\right)\times \left({\displaystyle \sum_{k=1}^n{g}_k\times {f}_{i,k}}\right)\right] $$
where SRc,i expresses the supply risk of country i for commodity c. sk is the global production share of country k of the commodity c. gk refers to the political instability indicator of country k. It is derived from the Worldwide Governance Indicators (WGI) of the World Bank (World Bank 2014). fi,k is an import share of country k in the supply chain of country i. The GeoPolRisks are then expressed as a socioeconomic risk-oriented midpoint indicator with values between 0 and 1, which can be interpreted as a share of the commodity supply being at risk assuming a linear relation between WGI score and supply disruption probability.

The WGI scores are weighted by the import share so that they can reflect the regional particularities through the consideration of the typical supply chain patterns of each country. This allows attribution of the geopolitical risk depending on the instability of the most relevant import partners in addition to the market concentration. The later rather reflects more the overall market ability to restructure trade flows in order to compensate decreased or disrupted sourcing from more instable countries. It is used as a multiplicative risk mitigation factor as described in the equation (Gemechu et al. 2015). However, in most previous studies, the WGI scores are weighted by average production share (National Research Council 2008; DOE 2011; Erdmann and Graedel 2011; Graedel et al. 2012; Nassar et al. 2012; Zepf et al. 2014).

Three databases are consulted to calculate the GeoPolRisk. The global production distribution data is obtained from US Geological Survey database (USGS 2014). The UN Comtrade database (UN 2014) is used to extract the import data and the World Bank database for WGI (World Bank 2014). The method is applied to the following regions and countries: Australia, Canada, China, EU, France, Germany, Greece, India, Italy, Japan, Norway, UK, and USA. These represent a reasonable diverse set of regions that include primary resource producers, manufacturers of EVs, and end-use economies of EVs.

3 Results

This section presents results from both the GeoPolRisk and environmental impact assessments for selected impact categories. First, the GeoPolRisk results are discussed and followed by the environmental results. The implications of introducing geopolitical considerations are analyzed by comparing with the more established LCA environmental impact assessment results.

3.1 GeoPolRisk assessment

Figure 2 displays results of the relative GeoPolRisks of fourteen metal resources for the thirteen regions. The method differentiates the GeoPolRisk by country due to the consideration of supply chain patterns as a key parameter. The supply risk for each country depends on the instability of important trade partners in addition to the global supply concentration. For example, in the case of neodymium, Canada, India, and Norway show relatively high geopolitical-related supply risk, as they are entirely dependent on neodymium imports from China, which accounts for more than 95 % of supply. However, the neodymium risk for Australia is low since that country imports more than 75 % of its neodymium from the USA, a country with comparatively high political stability. Even though the USA is the second greatest global producer of rare earth elements (REEs), with a global share of 6 %, it also imports from other countries. The high GeoPolRisk for the USA is due to its imports from China, which accounts for 68 % of its total import. Russia and Japan are also important trade partners of the USA for REEs. Here, it is important to note that the GeoPolRisk estimation is exclusively applied to the imported volumes only. The domestically produced and consumed commodities are not taken into account as they are not affected by the geopolitical factors. However, it is important to consider them in assessing the overall supply risk and the potential consequence of supply restriction in a given economy, which is beyond the scope of this study.
Fig. 2

GeoPolRisk assessment of 14 resources which are relevant to EVs

Magnesium and neodymium display the highest geopolitically related supply risk among all the fourteen resources considered in this study. Both metals are among those twenty materials that were identified to be critical from the list of fifty-four candidate materials by the recent EU report on critical materials (European Commission 2014).

Neodymium is the most widely used type of rare earth metals. It is alloyed with iron and boron and used in permanent magnets (Nd2Fe14B tetragonal crystalline structure) in electric motors in EVs. A neodymium-based permanent magnet provides higher performance of magnetic properties—high permanent magnetic strength with less weight and size—making it very attractive for modern high technology applications where strong permanent magnets are essential. It is also widely used in electronic devices such as computers, headphones, loudspeakers, wind turbine, and magnetic resonance imaging (MRI) equipment.

Rare earth elements, unlike their name suggests, are geologically widely distributed in the world and are relatively abundant in the earth’s crust, occurring in deposits containing copper, lead, molybdenum, nickel tungsten, tin, zinc, etc. (Long et al. 2012). However, most rare earth elements are found in low concentrations in extractable ore deposits, thus their extraction is associated with large amount of wastes, including radioactive compounds that dictate environmental regulations and thus result in higher costs. A number of mines in the world were shutdown due to high environmental and regulation costs, leaving China as the leading global producer. Relatively cheap labor, low regulatory cost, and the abundances of rare earths in relatively extractable concentration are among the factors for high dominance of China over rare earths global supply. China holds around 86 % of the estimated world production market for rare earth elements (USGS 2015). There is a growing concern over the availability of neodymium, which is largely driven by its high demand from the automotive sector and geopolitical concerns as a result of production concentration. Geopolitical conflict already arose between China and important trade partners in 2009, when China introduced export quotas on rare earth exports. The EU, USA, and Japan formally complained to the World Trade Organization (WTO) to challenge China’s restriction on export of rare earth elements. They accused China of increasing the price of rare earth for international manufacturers while holding it down to its domestic firms to force international firms to move their operation to China. The WTO appellate body confirmed that China’s export duties and quotas imposed on rare earth, tungsten, and molybdenum were illegal under the WTO (WTO 2014), and subsequently withdrew restrictions.

Magnesium is used in the interior of the vehicle instrument panel where both strength and light weight are very essential. Magnesium alloys are known for their high specific strength (strength-to-weight ratio) that makes them a very crucial resource in the automotive and aerospace industries. Recently, interest has increased to adapt its use for new application in the vehicle industry, to produce thin-walled vehicle doors with the aim of decreasing the total weight and the associated energy consumption. For example, substituting steel-based inner panels with magnesium could reduce the car door’s weight by 60 %, which could reduce the total fuel consumption and CO2 emissions (USGS 2013).

Magnesium reserves appear to be sufficient to satisfy current and future demands (USGS 2013). But the high GeoPolRisk comes from its large market concentration, again dominated by China, which accounts for around 86 % of the global production (USGS 2013; European Commission 2014). China imposed certain measures that affect the exportation of a list of resources including magnesium. The USA, EU, and Mexico challenged China with respect to these export restraints imposed on the resources: export duties, export quotas, minimum export price requirements, and export licensing requirements, which they claimed that such export restraints broke the WTO’s rules. In response to the allegation, the WTO panel issued a report. It highlights that China’s export duties imposed on a number of resources including magnesium are inconsistent with its commitments with the WTO, and China’s export quota and minimum export price violate the provision that prohibits quantitative trade restriction (WTO 2013).

Other resources, such as Fe, Al, and Cu constitute the largest quantity of metals by mass, but do not exhibit supply risks. This is because their production is relatively widely distributed around the globe, and includes numerous low-risk country sources as measured by the WGI.

3.2 Environmental impact results

Figure 3 shows the selected environmental impact indicators and geopolitical-related supply risk per functional unit for the production of a European standard small EV. The results are presented only for the production phase, without taking into account the environmental burden from the use and end-of-life phases, which are available in the original study by Hawkins et al. (2013).
Fig. 3

Environmental impacts and geopolitical-related supply risk per functional unit (production of one EV)

Environmental impacts associated with metals primary productions are mainly associated with mining, extraction, and refining processes. This is well established, given that metals production has high energy intensity and emissions (Althaus and Classen 2005; Norgate et al. 2007). Copper, aluminum, and steel are the dominant elements with relatively high environmental impacts per functional unit, as can be seen in Fig. 3, across different impact categories. For example, in the case of the MDP indicator, copper and steel are the most important elements in the EV. Human toxicity and freshwater ecotoxicity are to a great extent dominated by copper, though steel and aluminum also have contributions. Aluminum and steel are the most relevant metals contributing to the climate change impact indicator. Steel appears to be the most relevant element when considered only on a total mass basis, but its relative contribution to the selected impact categories is not so high compared with copper and aluminum, which have one fourth and one seventh mass contribution than steel, respectively.

3.3 Comparison of environmental impact vs. GeoPolRisk

In addition to the usual LCA environmental impacts, the last column in Fig. 3 displays the GeoPolRisk as an additional indicator. Unlike other indicators, which evaluate the absolute value per functional unit, the GeoPolRisk attempts to provide a relative criticalness among multiple resources through assessing them at a time. For the comparison purpose, Fig. 3 provides only the GeoPolRisk for the EU-27 region. As it can be seen, there is a clear difference between the GeoPolRisk and environmental impacts for different resources. While the global impacts per the functional unit are dominated by copper, aluminum, and steel, magnesium and neodymium are most relevant to the geopolitical-related supply risk. The relatively low environmental impact contributions of magnesium and neodymium correspond to their low mass requirement (they are utilized in very small amounts, 240 and 2 kg, respectively). More importantly, their contributions to resource impact are very low compared with others elements. The resource impact assessment in most existing life cycle impact assessment methods is based on the geological availability. Particularly in the ReCiPe method, the metal depletion at midpoint level is estimated as a marginal lower grade of a deposit which resulted from a marginal increase in yield, caused by an extraction of the deposit. The metal depletion at endpoint, which is a damage measure on Natural Resource AoP, is defined as the additional costs society has to pay as a result of extraction (Goedkoop et al. 2013). The cost increase results from the need of additional effort to extract a certain amount of a resource in the future due to a reduction in its ore grade. The midpoint metal depletion results in Fig. 3 (4th column), which is a traditional LCA indicator, shows that copper and steel have the highest impact per functional unit. Metal depletion in the LCA also seems to follow mass, like the environmental measures; however, looking outside LCA, the global resource concerns are dominated by PGMs, gold and rhodium—and these do not appear in the LCA results due to their low mass contribution. This is because resource availability is not entirely determined by the geological parameters, but also by other factors such as socioeconomic, political, environmental regulation, and others. The GeoPolRisk results (6th column) reflect the importance of considering such other factors to meaningfully address the issue of resource accessibility. The metal depletion results are based on the global availability and attempt to assess resource scarcity for mid- and long-term time perspective without regarding the short-term availability (accessibility). The dominancy of neodymium and magnesium in the GeoPolRisk indicator, on the other hand, points to the higher criticality of these resources with regard to their accessibility compared with other resources.

4 Discussion

An important contribution of the GeoPolRisk indicator is to give broader social dimension that is added to conventional environmental LCA. In the case study considered here, the environmental indicator results all tend to point to the same hotspots that arise from the substantial use of several materials in the vehicle. The GeoPolRisk indicator, on the other hand, suggests that there are important elements present in very small quantities in the vehicle that may be crucial to the overall LCSA. This fuller analysis supports the emerging and broader challenges of assessment that are needed as society shifts towards more complex and sophisticated technologies, like electric vehicles. Part of the issue of materials criticality that has been highlighted shows there is the importance of certain scarce minor elements, used in green technologies for renewable energy (Graedel et al. 2012). Metals such as rare earth elements, magnesium, and PGMs provide special functions but are utilized in small amounts so that they are usually left out in the traditional LCA assessment due to their low environmental significance. Presenting the GeoPolRisk indicator side-by-side with the environmental results can support more informed decision-making for both business and policy-makers providing fuller life cycle sustainability assessment framework leading to better product development and material management.

The conventional metals depletion indicator, for example, as employed by ReCiPe, has significant weaknesses that are partially addressed by the GeoPolRisk approach. A metals depletion factor based on mineral reserves is inherently flawed, partly because the concept of reserves is actually economic in character, not biophysical: reserves of a metal tend to stay approximately the same over decades, regardless of societal consumption of the resource. Companies simply expand their reserves by either more intensive geological exploration or enhanced technological extraction methods. The GeoPolRisk indicator, on the other hand, more directly addresses the real problem of access to raw materials. This too may change over time in its characterization factors, as geopolitical circumstances and trade patterns shift overtime. But for companies making decisions in the short- and medium-term, say less than 10 years, the GeoPolRisk value has greater meaning for sustainable supply chain management than “metal depletion.”

The geopolitical risk approach, however, does have important weaknesses and limitations—which present opportunities for future research. First, at this time, data needed to calculate the GeoPolRisk do not support sufficiently high resolution examination of individual metal elements, where for example, production numbers of the platinum group of metals and the rare earth elements are commonly lumped together. Second, the assessment of geopolitical stress is limited to a country-level understanding of political conditions and mineral production. Conditions may differ significantly within a nation, and this level of resolution is not easily captured. Moreover, unlike the approach used here that relied on the UN Comtrade database, the commerce of minerals and metals does not precisely correspond to trade between countries. The current GeoPolRisk indicator implicitly assumes that all production stages of a metal occur in one country, and then captures the trade of direct exports to the country of manufacture. Supply chains actually occur from firm to firm, which may have unique or tightly managed supply chains depending on the specific company. Thus, one company in Europe could have very different supply risk to a neighboring company that uses the same metal and makes the same product.

Third, the current approach simplifies all mineral production processes as aggregated into one life cycle stage, which the GeoPolRisk assesses as the mining of raw material. Other stages in the life cycle of the metal, like mineral processing, smelting, and refining, are ignored in the current calculation. This is of concern for most metals, and more so for certain metals like aluminum, which is known to be mined in countries that tend to be equatorial and have surface reserves of bauxite but tend to have lower WGI values (e.g., Brazil, China, Guinea, Jamaica, Guyana), but is smelted in countries with abundant low-cost electrical energy, like hydropower, which tend to be in the north and have higher WGI values (like Canada, USA, Norway). This simplification in the GeoPolRisk approach needs to be addressed in a future work. Fourth, the sourcing of raw materials is not totally reliant on primary production but also includes recycled sources. These too are not captured in the current GeoPolRisk indicator.

These challenges confront methodological challenges and concern data availability across mineral and metal life cycles; however, such concerns regarding regional (and temporal) limitations are not new to LCA. Some advances are being made, specifically towards better mapping and resolution of critical material flows and product supply chains. Conceptually, it is important to distinguish tracking, which follows a unit of material downstream (e.g., from mine to final-product) from tracing, which provides information on materials in the other direction (e.g., from final-product back to original source) (Young and Dias 2011). Moran et al. (2014) have used a multiregional input-output hybrid LCA methodology to trace sourcing of metals in global supply chains; however, this approach is limited by availability of spatially disaggregated supply chain data. To address this, a possible research direction is to use data created for other purposes that identify production locations and feedstock profiles at metal smelters and refineries potentially differentiating primary and recycled sources in activities that certify more sustainable production of metals (Young 2015) or to identify responsible sourcing of so-called “conflict minerals” (Young et al. 2014).

5 Conclusions

In this paper, we introduced a new geopolitical-related supply risk indicator, GeoPolRisk, and it was applied to a case study to show the possible integration of traditional environmental LCA with some concepts of resource criticality under the LCSA framework. Introduction of the GeoPolRisk allows the conventional LCA to evolve from being used as only environmental assessment tool to resource risk assessment through allowing it to emphasize on different issues.

Impact assessments based on only geological availability overlook the significance of critical resources that are the basic components of modern technology such as advanced electronic devices, electric vehicles. and high-tech applications. The GeoPolRisk indicator can play a vital role in managing the supply chain of critical resources used in future products as it highlights their potential supply constraints.

There are still issues that are not addressed in this paper. These are for example, the geopolitical supply risk is aggregated for a number of platinum group metals or rare earth elements but not examined at each individual metal elements; the risk is not differentiated by the metal production stages rather it is based on the assumption that all production stages of the metal occur in one country; no differentiation was made between the primary and recycled sources in the assessment. The future perspectives will be to address the aforementioned limitations of the approach and develop midpoint and endpoint characterization factors through establishing a cause and effect chain.



We would like to thank Christoph Helbig for helping to develop the Geopolitical Supply Risk method. The authors also acknowledge the financial support of the Region of Aquitaine for the Chair on Life Cycle Assessment (CyVi) at the University of Bordeaux to carry out this work.


  1. Althaus H-J, Classen M (2005) Life cycle inventories of metals and methodological aspects of inventorying material resources in ecoinvent. Int J Life Cycle Assess 10:43–49CrossRefGoogle Scholar
  2. Andersson BA, Råde I (2001) Metal resource constraints for electric-vehicle batteries. Transp Res Part D: Transp Environ 6:297–324(28)CrossRefGoogle Scholar
  3. DOE (2011) Critical materials strategy. US Department of Energy, WashingtonGoogle Scholar
  4. Erdmann L, Graedel TE (2011) Criticality of non-fuel minerals: a review of major approaches and analyses. Environ Sci Technol 45:7620–7630CrossRefGoogle Scholar
  5. European Commission (2010) Critical raw materials for the EU, Report of the Ad-hoc Working Group on defining critical raw materials. Eucom 39:1–84Google Scholar
  6. European Commission (2011) International Reference Life Cycle Data System (ILCD) Handbook : Recommendations for Life Cycle Impact Assessment in the European context. EUR 24571 EN. Eur Comm 159. doi: 10.278/33030Google Scholar
  7. European Commission (2012) Security of supply and scarcity of raw materials: towards a methodological framework for sustainability assessment. Joint European Centre–Institute for Environment and SustainabilityGoogle Scholar
  8. European Commission (2014) Report on critical raw materials for the EU: report of the Ad-Hoc Working Group on Defining Critical Raw Materials. Brussels, BelgiumGoogle Scholar
  9. Finkbeiner M, Schau EM, Lehmann A, Traverso M (2010) Towards life cycle sustainability assessment. Sustainability 2:3309–3322CrossRefGoogle Scholar
  10. Gaines L, Nelson P (2010) Lithium-ion batteries: examining material demand and recycling issues. Proc. 2010 TMS Annu Meet Exhib Sustain Mater Process Prod SympGoogle Scholar
  11. Gemechu ED, Helbig C, Sonnemann G et al (2015) Import-based indicator for the geopolitical supply risk of raw materials in life cycle sustainability assessments. J Ind Ecol. doi:10.1111/jiec.12279
  12. Goedkoop M, Heijungs R, Huijbregts M et al. (2013) ReCiPe 2008: A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level - Report I: CharacterisationGoogle Scholar
  13. Graedel TE, Barr R, Chandler C et al (2012) Methodology of metal criticality determination. Environ Sci Technol 46:1063–1070CrossRefGoogle Scholar
  14. Graedel TE, Harper EM, Nassar NT, Reck BK (2013) On the materials basis of modern society. Proc Natl Acad Sci. doi:10.1073/pnas.1312752110 Google Scholar
  15. Guinée JB, Gorrée M, Heijungs R et al (2002) Handbook on life cycle assessment: operational guide to the ISO standards. Kluwer Academic Publishers, DordrechtGoogle Scholar
  16. Hawkins TR, Gausen OM, Strømman AH (2012) Environmental impacts of hybrid and electric vehicles—a review. Int J Life Cycle Assess 17:997–1014CrossRefGoogle Scholar
  17. Hawkins TR, Singh B, Majeau-Bettez G, Strømman AH (2013) Comparative environmental life cycle assessment of conventional and electric vehicles. J Ind Ecol 17:53–64CrossRefGoogle Scholar
  18. Herrington R (2013) Road map to mineral supply. Nat Geosci 6:892–894CrossRefGoogle Scholar
  19. ISO (2006) ISO 14040 International Standard. In: Environmental management—life cycle assessment—requirements and guidelinesGoogle Scholar
  20. Kloepffer W (2008) Life cycle sustainability assessment of products. Int J Life Cycle Assess 13:89–95CrossRefGoogle Scholar
  21. Long K, Van Gosen B, Foley N, Cordier D (2012) The principal rare earth elements deposits of the United States: a summary of domestic deposits and a global perspective. In: Sinding-Larsen R, Wellmer F-W (eds) Non-Renewable Resour. Issues SE - 7. Springer, Netherlands, pp 131–155CrossRefGoogle Scholar
  22. Mancini L, Sala S, Recchioni M et al (2015) Potential of life cycle assessment for supporting the management of critical raw materials. Int J Life Cycle Assess 20:100–116CrossRefGoogle Scholar
  23. Moran D, McBain D, Kanemoto K et al (2014) Global supply chains of coltan. J Ind Ecol. doi:10.1111/jiec.12206 Google Scholar
  24. Moss R, Tzimas E, Willis P et al. (2013a) Critical metals in the path towards the decarbonisation of the EU energy sector—assessing rare metals as supply-chain bottlenecks in low-carbon energy technologies. Publication Office of the European Union, LuxembourgGoogle Scholar
  25. Moss RL, Tzimas E, Kara H et al (2013b) The potential risks from metals bottlenecks to the deployment of strategic energy technologies. Energy Policy 55:556–564CrossRefGoogle Scholar
  26. Nassar NT, Barr R, Browning M et al (2012) Criticality of the geological copper family. Environ Sci Technol 46:1071–1078CrossRefGoogle Scholar
  27. National Research Council (2008) Minerals, critical minerals, and the U.S. economy. The National Academies Press, WashingtonGoogle Scholar
  28. Nordelöf A, Messagie M, Tillman AM et al (2014) Environmental impacts of hybrid, plug-in hybrid, and battery electric vehicles—what can we learn from life cycle assessment? Int J Life Cycle Assess 19:1866–1890CrossRefGoogle Scholar
  29. Norgate TE, Jahanshahi S, Rankin WJ (2007) Assessing the environmental impact of metal production processes. J Clean Prod 15:838–848CrossRefGoogle Scholar
  30. Rydh CJ, Svärd B (2003) Impact on global metal flows arising from the use of portable rechargeable batteries. Sci Total Environ 302:167–184CrossRefGoogle Scholar
  31. Schneider L, Berger M, Schüler-Hainsch E et al (2014) The economic resource scarcity potential (ESP) for evaluating resource use based on life cycle assessment. Int J Life Cycle Assess 19:601–610CrossRefGoogle Scholar
  32. Sonnemann G, Castells F, Schuhmacher M (2003) Integrated life-cycle and risk assessment for industrial processes. Lewish Publishers, Boca RatonCrossRefGoogle Scholar
  33. Sonnemann G, Gemechu ED, Adibi N et al (2015) From a critical review to a conceptual framework for integrating the criticality of resources into life cycle sustainability assessment. J Clean Prod 94:20–24CrossRefGoogle Scholar
  34. UN (2014) United Nations Commodity Trade Statistics Database. In: United Nations Stat. Div.
  35. UNEP (2011) Towards a life cycle sustainability assessment: making informed choices on products. UNEP/SETAC, ParisGoogle Scholar
  36. USGS (2013) Mineral commodity summaries 2013. U.S. Geological Survey, WashingtonGoogle Scholar
  37. USGS (2014) Mineral commodity summaries 2014. U.S. Geological Survey, WashingtonGoogle Scholar
  38. USGS (2015) Mineral commodity summaries 2015. U.S. Geological Survey, WashingtonGoogle Scholar
  39. Valdivia S, Ugaya CML, Hildenbrand J et al (2013) A UNEP/SETAC aproach towards a life cycle sustainability assessment—our contribution to Rio + 20. Int J Life Cycle Assess 18:1673–1685CrossRefGoogle Scholar
  40. World Bank (2014) Worldwide Governance Indicators.
  41. WTO (2013) China—measures related to the exportation of various raw materials—reports of the Appellate Body. Geneva, SwitzerlandGoogle Scholar
  42. WTO (2014) China—measures related to the exportation of rare earths, tungsten and molybdenum—reports of the Appellate Body. Geneva, SwitzerlandGoogle Scholar
  43. Young SB (2015) Responsible sourcing of metals: certification approaches for conflict minerals and conflict-free metalsGoogle Scholar
  44. Young SB, Dias G (2011) LCM of metals supply to electronics: tracking and tracing “Conflict Minerals.” Towar. Life Cycle Sustain. Manag.-Aug 29–31. Berlin, Germany, p 12Google Scholar
  45. Young SB, Yuan Z, Dias G (2014) Prospects for sustainability certification of metals. Metal Res Technol 111:131–135CrossRefGoogle Scholar
  46. Zepf V, Reller A, Rennie C et al. (2014) Materials critical to the energy industry. An introduction, 2nd edn. London, United KingdomGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Eskinder D. Gemechu
    • 1
    • 2
  • Guido Sonnemann
    • 1
    • 2
  • Steven B. Young
    • 3
  1. 1.University of Bordeaux, ISM, UMR 5255TalenceFrance
  2. 2.CNRS, ISM, UMR 5255TalenceFrance
  3. 3.School of Environment, Enterprise and Development (SEED)University of WaterlooWaterlooCanada

Personalised recommendations