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The assessment of the criticality of raw materials allows the identification of the likelihood of a supply disruption of a material and the vulnerability of a system (e.g. a national economy, technology, or company) to this disruption. Inconclusive outcomes of various studies suggest that criticality assessments would benefit from the identification of best practices. To prepare the field for such guidance, this paper aims to clarify the mechanisms that affect methodological choices which influence the results of a study. This is achieved via literature review and round table discussions among international experts. The paper demonstrates that criticality studies are divergent in the system under study, the anticipated risk, the purpose of the study, and material selection. These differences in goal and scope naturally result in different choices regarding indicator selection, the required level of aggregation as well as the subsequent choice of aggregation method, and the need for a threshold value. However, this link is often weak, which suggests a lack of understanding of cause-and-effect mechanisms of indicators and outcomes. Data availability is a key factor that limits the evaluation of criticality. Furthermore, data quality, including both data uncertainty and data representativeness, is rarely addressed in the interpretation and communication of results. Clear guidance in the formulation of goals and scopes of criticality studies, the selection of adequate indicators and aggregation methods, and the interpretation of the outcomes, are important initial steps in improving the quality of criticality assessments.
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Resources, Conservation & Recycling
journal homepage: www.elsevier.com/locate/resconrec
A review of methods and data to determine raw material criticality
Dieuwertje Schrijvers
a,b
, Alessandra Hool
c,
*, Gian Andrea Blengini
d
, Wei-Qiang Chen
e
,
Jo Dewulf
f
, Roderick Eggert
g
, Layla van Ellen
h
, Roland Gauss
i
, James Goddin
j
, Komal Habib
k
,
Christian Hagelüken
l,c
, Atsufumi Hirohata
m
, Margarethe Hofmann-Amtenbrink
n
, Jan Kosmol
o
,
Maïté Le Gleuher
p
, Milan Grohol
q
, Anthony Ku
r
, Min-Ha Lee
s
, Gang Liu
t
, Keisuke Nansai
u
,
Philip Nuss
v
, David Peck
h
, Armin Reller
c,w
, Guido Sonnemann
a,b
, Luis Tercero
c,x
,
Andrea Thorenz
w
, Patrick A. Wäger
c,y
a
Univ. Bordeaux, ISM, UMR 5255, F-33400 Talence, France
b
CNRS, ISM, UMR 5255, F-33400 Talence, France
c
ESM Foundation, Junkerngasse 56, 3011 Bern, Switzerland
d
European Commission, DG JRC – Joint Research Centre, Sustainable Resources Directorate Unit D3 – Land Resources, Via Enrico Fermi 2749 TP270, I-21027 Ispra, Italy
e
Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, 1799 Jimei Road, Xiamen 361021, China
f
Research Group Sustainable Systems Engineering, Department Green Chemistry and Technology, Faculty of Bioscience Engineering, Ghent University, Campus Coupure,
Building B, Coupure Links 653, 9000 Ghent, Belgium
g
Division of Economics & Business, Colorado School of Mines, Golden, CO 80401, USA
h
Delft University of Technology, Faculty of Architecture and the Built Environment, Architectural Engineering and Technology, Building 8, Delft University of Technology
(TU Delft), Julianalaan 134, 2628BL, The Netherlands
i
EIT RawMaterials GmbH, Europa Center, Tauentzienstr. 11, 10789 Berlin, Germany
j
Granta Design/ANSYS, Rustat House, 62 Clifton Road, Cambridge, CB1 7EG, UK
k
Faculty of Environment, University of Waterloo, 200 University Ave West, Waterloo, Ontario, N2L3G1, Canada
l
Umicore AG & Co KG, Rodenbacher Chaussee 4, 63457 Hanau, Germany
m
Department of Electronic Engineering, University of York, Heslington, York YO10 5DD, United Kingdom
n
MatSearch Consulting Hofmann, Chemin Jean Pavillard 14, 1009 Pully, Switzerland
o
German Environment Agency (UBA), Wörlitzer Platz 1, 06844 Dessau-Rosslau, Germany
p
BRGM, 3 avenue C. Guillemin, 45060 Orléans, France
q
European Commission, DG Internal Market, Industry, Entrepreneurship and SMEs, BREY 07/045, 1049 Brussels, Belgium
r
NICE America Research, 2091 Stierlin Ct, Mountain View, CA 94043, USA
s
Korea Institute of Industrial Technology (KITECH), 156 Gaetbeol-ro, Yeonsu-Gu, 21999 Incheon, Republic of Korea
t
SDU Life Cycle Engineering, Department of Chemical Engineering, Biotechnology, and Environmental Technology, University of Southern Denmark, 5230 Odense,
Denmark
u
National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba 305-8506, Japan
v
German Environment Agency (UBA), Unit I1.1 - Fundamental Aspects, Sustainability Strategies and Scenarios, Sustainable Resource Use, Woerlitzer Platz 1, 06844
Dessau-Rosslau, Germany
w
Institute for Materials Resource Management/Resource Lab, Universitätsstr. 1a, University of Augsburg, 86159 Augsburg, Germany
x
Fraunhofer Institute for Systems and Innovation Research ISI. Business Unit Systemic Risks, Breslauer Straße 4, 76139 Karlsruhe, Germany
y
Empa, Swiss Federal Laboratories for Materials Science and Technology, Technology & Society Laboratory, Lerchenfeldstrasse 5, CH-9014 St. Gallen, Switzerland
https://doi.org/10.1016/j.resconrec.2019.104617
Received 27 June 2019; Received in revised form 26 October 2019; Accepted 27 October 2019
Abbreviations: BGS, British Geological Survey; BRGM, Bureau de Recherches Géologiques et Minières; CRM, Critical Raw Materials; EC, European Commission;
Empa, Swiss Federal Laboratories for Materials Science and Technology; EIT, European Institute of Innovation & Technology; EU, European Union; GE, General
Electric; HDI, Human Development Index; HHI, Herfindahl-Hirschman-Index; iCIRCE, Instituto Universitario Investigación CIRCE Universidad Zaragoza; INSEAD,
Institut Européen d'Administration des Affaires; IRTC, International Round Table on Materials Criticality; ISO, International Organization for Standardization;
KIRAM/KITECH, Korea Institute for Rare Metals/Korea Institute of Industrial Technology; LCA, Life Cycle Assessment; NEDO, New Energy and Industrial Technology
Development; NIES, National Institute for Environmental Studies; NRC, National Research Council; NSTC, National Science and Technology Council; OECD,
Organisation for Economic Co-operation and Development; OH, Oakdene Hollins; PGM(s), Platinum Group Metal(s); PPI, Policy Perception Index; REE(s), Rare Earth
Element(s); SDU, University of Southern Denmark; SI, Supplementary Information; UBA, Umweltbundesamt; UNDP, United Nations Development Programme; UNEP
IRP, United Nations Environment Programme International Resource Panel; US DOE, United States Department of Energy; USGS, United States Geological Survey;
VDI, Verein Deutscher Ingenieure; WGI, Worldwide Governance Indicators
Corresponding author.
E-mail address: alessandra.hool@esmfoundation.org (A. Hool).
Resources, Conservation & Recycling 155 (2020) 104617
0921-3449/ © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/BY-NC-ND/4.0/).
T
ARTICLE INFO
Keywords:
Critical raw materials
Material criticality
Critical resources
Strategic raw materials
Criticality assessment
ABSTRACT
The assessment of the criticality of raw materials allows the identification of the likelihood of a supply
disruption of a material and the vulnerability of a system (e.g. a national economy, technology, or company)
to this disruption. Inconclusive outcomes of various studies suggest that criticality assessments would
benefit from the identification of best practices. To prepare the field for such guidance, this paper aims to
clarify the mechanisms that affect methodological choices which influence the results of a study. This is
achieved via literature review and round table discussions among international experts. The paper de-
monstrates that criticality studies are divergent in the system under study, the anticipated risk, the purpose
of the study, and material selection. These differences in goal and scope naturally result in different choices
regarding indicator selection, the required level of aggregation as well as the subsequent choice of ag-
gregation method, and the need for a threshold value. However, this link is often weak, which suggests a lack
of understanding of cause-and-effect mechanisms of indicators and outcomes. Data availability is a key
factor that limits the evaluation of criticality. Furthermore, data quality, including both data uncertainty
and data representativeness, is rarely addressed in the interpretation and communication of results. Clear
guidance in the formulation of goals and scopes of criticality studies, the selection of adequate indicators
and aggregation methods, and the interpretation of the outcomes, are important initial steps in improving
the quality of criticality assessments.
1. Introduction
Raw material criticality is the field of study that evaluates the
economic and technical dependency on a certain material, as well as the
probability of supply disruptions, for a defined stakeholder group
within a certain time frame. Criticality assessments play an indis-
pensable role for industry and policymakers alike, e.g. in material se-
lection, product and process design, investment decisions, trade
agreements, collaboration strategies, as well as in the prioritization of
research projects, policy agendas, and undertakings towards increasing
transparency in value chains (Buijs et al., 2012;Graedel and Reck,
2015).
Criticality assessments are conducted at different levels: for a
specific product (Bach et al., 2016;Cimprich et al., 2017a;Clifton,
2013;Gemechu et al., 2017;Graedel and Nuss, 2014), technology
(Bauer et al., 2010;Gauß et al., 2017;Habib and Wenzel, 2016;
Helbig et al., 2018;Moss et al., 2011,2013b), company (Duclos
et al., 2010), country or region (European Commission, 2017a;
Graedel et al., 2015;Hatayama and Tahara, 2015;Lee, 2014;NRC,
2008), or even at a global level (Graedel et al., 2015;Morley and
Eatherley, 2008). The criticality of a raw material then can be con-
sidered in the short term (e.g. a few years) or in the long term (a few
decades) (Bauer et al., 2010;Buijs et al., 2012;Erdmann and
Graedel, 2011;Ku and Hung, 2014;Riddle et al., 2015). Criticality
methods use a broad selection of indicators to describe various fac-
tors including geological, technological, geopolitical, social, and
environmental factors (Achzet and Helbig, 2013;Dewulf et al., 2016;
Erdmann and Graedel, 2011;Habib and Wenzel, 2016;Kolotzek
et al., 2018). Due to the diverse perspectives and motivations to
carry out such studies, there are considerable variations in the
identification processes of critical raw materials (CRM) and their
outcomes, as assessed by e.g. Erdmann and Graedel (2011);Graedel
and Reck (2015);Dewulf et al. (2016) and illustrated in Fig. 1. One
can say that “Criticality is in the eye of the beholder” (Eggert, 2011);
that is, there is no generic standard approach to conduct a criticality
assessment.
The diversity of raw material criticality assessments, the use of
different indicators, and the complexity of the underlying data
usually makes a comparison of the results generated by different
studies difficult, if not impossible. Authors in the field have pointed
out that there is a need to identify criticality assessment factors and
indicators that provide an improved estimation of the degree of
criticality, as well as suitable data sources for this purpose (Graedel
and Reck, 2015;Speirs et al., 2013). Despite these gaps, an inter-
national forum dedicated to the harmonization of the development of
criticality methods was missing (Dewulf et al., 2016). To begin to
address these challenges, the EIT (European Institute of Innovation &
Technology) Raw Materials project IRTC (“International Round
Table on Materials Criticality”) was established, bringing together
international experts in round table dialogues to tackle the questions
surrounding methodology, application, and future development of
raw material criticality assessments. In the resulting publications, of
which this paper is the first of an ongoing series, the IRTC Con-
sortium integrates the views from a variety of stakeholders world-
wide.
While previous review papers have mostly focused on highlighting
the differences between criticality studies (Achzet and Helbig, 2013;
Erdmann and Graedel, 2011;Helbig et al., 2016c), this paper aims to
clarify the underlying reasons of why criticality method developers have
made different choices that have resulted in the different methodolo-
gies. It focuses especially on how different assessments are framed
(goal, scope) and then on the assessment methods themselves (in-
dicators, aggregation, presentation). This analysis will form the basis to
structure the current discussions around the methodological aspects of
criticality assessments via an international collaborative effort. Under-
standing the status quo, and the directions in which criticality assess-
ment and the debate surrounding it is moving, is vital for identifying
the future needs of different stakeholders and for defining the next steps
on a global level.
2. Methods
The following approach has been applied to identify the underlying
relationships between stakeholder perspectives, methodological
choices, and the outcomes of criticality assessments: firstly, a compre-
hensive overview of the available literature on criticality has been
conducted in the form of a “Criticality Library” (see Supplementary
Information A (SI-A)). Thereafter, methods have been selected for re-
view based on the aim of providing a broad overview of early and more
recent method developments, broad geographical coverage, and the
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
2
inclusion of diverse scopes and stakeholders. Following the approach of
previous review studies (Achzet and Helbig, 2013;Erdmann and
Graedel, 2011;Graedel and Reck, 2015;Habib and Wenzel, 2016),
aspects of the goal and scope and methodological choices were col-
lected and summarized in a “Goal and Scope table” (SI-B). This table
has, as far as possible, been filled in and/or reviewed by the method
developers themselves. This is one of the unique features of the IRTC
project: instead of one group discussing other’s work, the method de-
velopers themselves came to the table. IRTC contacted as many method
developers as possible in order to also integrate approaches that have
146
0 5 10 15 20 25 30
Nomex
Niobium
Nickel
Natural gas
Monazite
Molybdenu…
Mica
Methane
Mercury
Manganese
Magnesium
Magnesite
Lithium
Limestone
Lead
Kyanite
Kevlar
Iron
Iodine
Indium
Helium
Hafnium
Gypsum
Graphite
Gold
Glass ber
Germanium
Gallium
Fluor
Feldspar
Diatomite
Diamond
Cork
Copper
Cobalt
Coal
Clay
Chromium
Chlorine
Carbon ber
Calcium
Caesium
Cadmium
Bromine
Brass
Boron
Bismuth
Beryllium
Bentonite
Bauxite
Baryte
Barium
Asbestos
Arsenic
Anmony
Andalusite
Ammonia
Aluminium
Aggregates
Frequency of appearance a nd assessment of "high", "medium", or "low"
cricality
High Medium Low
0 5 10 15 20 25
Zirconium
Zinc
Wood
Vermiculite
Vanadium
Uranium
Tungsten
Titanium
Tin
Thorium
Thallium
Tellurium
Tantalum
Talc
Sulfur
Stronum
Sodium
Soda ash
Silver
Silicon
Silicomanganese
Silica
Shale gas
Selenium
Rubidium
Rubber
Rhenium
REEs Light
REEs Heavy
REEs
REE Yrium
REE Yerbium
REE Thulium
REE Terbium
REE Scandium
REE Samarium
REE Praseodymium
REE Neodymium
REE Luteum
REE Lanthanum
REE Holmium
REE Gadolinium
REE Europium
REE Erbium
REE Dysprosium
REE Cerium
Quartz ber
Potassium
Phosphorus
PGMs
PGM Ruthenium
PGM Rhodium
PGM Planum
PGM Palladium
PGM Osmium
PGM Iridium
Petroleum
Perlite
Frequency of appearance and assessment of "high", "medium", or
"low" cricality
High Medium Low
Fig. 1. Frequency of appearance in criticality assessments and criticality determination (high, medium, or low) of materials. Included methods (see Table 1.): NRC,
Yale (global and country risk, only the supply risk axis), NSTC (2016 and 2018), EU (2011, 2014a,b, and 2017a,b,c,d), Helbig et al. (2016a,b,cand 2018), Augsburg,
KIRAM/KITECH, NEDO, BRGM, Werner, General Electric, iCIRCE, NIES, GeoPolRisk, SCARCE, Oakdene Hollins, Thomason, Rosenau-Tornow, Öko-Institut, Roelich,
SDU, China, BGS (2011,2012, and 2015), OECD, US DOE (both short term and medium term for 2010 and 2011), Moss et al. (2011 and 2013). Excluded methods are
BIRD, VDI and UBA (no results), Granta Design, ESSENZ and EBP/Empa (unaggregated results and/or company-specific), Angerer (no materials identified as critical).
Multi-stage analyses and multiple forms of the same material are merged (only bottleneck is included), to avoid double counting of appearances. See SI-B for details
on material inclusion and evaluation of methods.
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
3
not been discussed and reviewed in the literature before.
1
Method de-
velopers were contacted based on references in the scientific literature,
and on the consortium representatives’ identification of relevant studies
and authors in their country or field of work. The project consortium
itself was formed by the authors of relevant criticality studies as iden-
tified by the scientific literature (in particular Graedel and Reck, 2015);
further members were included by recommendations of the members of
this initial core group. Advisory Board members representing relevant
stakeholders such as industry representatives and policy-makers were
added based on recommendations from the consortium and under
consideration of country and stakeholder balance.
From the “Goal and Scope table”, key differences were identified
between the assessment methods: this was done first by assessing the
system under study (e.g. national economy, company, product, etc.),
and the related spatial boundaries and the time horizon. Furthermore,
IRTC narrowed into the details of the study on the level of criticality
dimensions (e.g. the probability of a supply disruption and the vul-
nerability to such a disruption), factors (e.g. economic, geological,
political, or environmental), indicators (e.g. the country concentration
of supply, depletion time, etc.), and data sources used. The team as-
sessed how the applied approaches assured the use of reliable input
data for the assessment and which role experts played in this. Other
methodological choices, such as aggregation methods and threshold
values were also discussed. Furthermore, the boundary conditions of
the studies were noted, such as the intended audience and the foreseen
applications of the results, which may justify certain methodological
choices.
In line with the observations of Erdmann and Graedel (2011), sev-
eral aspects of the goal and scope are often not explicitly mentioned in
the evaluated studies, such as the time horizon, material selection cri-
teria, and the intended use of the results. Furthermore, as Achzet and
Helbig (2013);Erdmann and Graedel (2011), and Lloyd et al. (2012)
point out, several studies lack an explicit justification of choices.
Through discussions with IRTC experts during the first IRTC Round
Table in Vancouver (a summary is provided in SI-C), the underlying
motivation of choices in these studies have been clarified in more de-
tail, in order to be able to understand both explicit and implicit factors
that affect the outcome of a criticality study. As this paper has been
developed by many co-authors, a more detailed explanation on the
establishment of the paper is provided in Section S1 of SI-D.
3. Results and discussion
The main mechanisms that were identified via the literature review
which influence the outcomes of criticality assessments are schemati-
cally represented by Fig. 2. These mechanisms are presented in line
with the methodological framework for Life Cycle Assessment (LCA), as
standardized in ISO 14040 (ISO, 2006), which enables the use of the
scheme as a methodology development and evaluation tool. Fig. 2
shows that the goal and scope of a study both directly and indirectly
influence the results of the assessment. The goal and scope influences
indicator selection. Indicator selection is affected by data availability,
which can influence the material coverage of the assessment, and thus
again the goal and scope. The availability and the quality of data finally
influences indicator scoring. In most studies, indicator scores are ag-
gregated to enable the identification of a material as critical or not. The
aggregation method that is used is not determined by the indicator
scoring, but instead by a choice or logic reasoning of the practitioner –
represented by the goal and scope. Finally, the way in which the
practitioner aims to communicate his or her results is solely determined
by the objectives of the assessment itself.
Therefore, the combined factors of goal and scope definition, in-
dicator evaluation, and the chosen aggregation method lead to the
classification of a material as “critical” or “non-critical”. These me-
chanisms are further explained below.
3.1. Goal and scope
In this section, we discuss several key elements of the goal and scope
of criticality methods: the system at risk, the anticipated risk, the ob-
jective of the assessment, and the materials that are evaluated. An
overview of the goals and scopes of methods that are reviewed is pro-
vided in Table 1.
3.1.1. What is at risk?
Throughout the 20
th
century and mainly driven by governmental
reports from the United States and Great Britain, the concept of critical
– or “strategic”, a more frequently used term - raw materials (CRM)
mostly referred to materials used in the field of national security and
defense (Ashby, 2016;Paley, 1952;Tilton, 2003,2001). Typically
governments determined their military material stockpiles as a re-
sponse to anticipated demand surges and potential supply restrictions,
either in preparation for, or during a war situation, with import de-
pendence being a key consideration (Thomason et al., 2010).
From the mid-20
th
into the early 21
st
century, the industrialized
world experienced a rapid increase in economic growth, driven by
technological developments, against a backdrop of an increasing global
population. The lack of locally sourced material resources for industrial
needs in Europe, as well as the Chinese export restrictions of rare earth
elements (REEs), starting in 2007 and reaching a peak in 2011, caught
the attention of global users of raw materials (Frenzel et al., 2017). This
development had a great impact worldwide, as China has dominated
the global REE market with a 95% market share. Countries with a high
level of industrialization and a high level of dependency on imports of
Fig. 2. How the goal and scope influences which materials are critical.
1
The goal and scope table is an ongoing work in progress and will contain
methods that are not included in this review. If the reader knows about a
method that should be integrated, please contact the corresponding author.
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
4
Table 1
Goals and scopes of reviewed criticality assessment methods (detailed information available in SI-B).
Method Year What is at risk? Geographical scope of
the system at risk
Time horizon Anticipated risk Objective
Oakdene Hollins (OH) (Morley and
Eatherley, 2008)
2008 Economy UK Few decades Insecure material supply, due to high price increases,
shortages of supply, resource nationalism, a high
concentration of supplying companies, or high
environmental impacts can negatively impact economic
sectors.
Inform policy makers, innovation support bodies and
business on the need for resource efficiency strategies.
NRC (NRC, 2008) 2008 Domestic economy USA < 10 years Physical unavailability of materials, high and/or
volatile material prices, disruptions to economic activity
Establish a general conceptual framework for evaluating
material criticality, which specific users can customize
to their own situations
General Electric (GE) (Duclos et al.,
2010)
2008 Company operations Global Not explicit Increased economic growth, increased reliance on raw
materials and sustainability challenges affects the
company’s supply chain.
Identify exposure to supply risks and guide selection of
appropriate mitigation actions
Rosenau-Tornow (Rosenau-Tornow
et al., 2009)
2009 Not specified Not specified 5–15 years Potential supply shortages due to demand growth and
supply from politically instable countries.
Improve decision-making in companies in their
selection of new technologies, anticipate critical market
situations, implement mitigation measures
NEDO (Hatayama and Tahara, 2015;
NEDO, 2009)
2009 Economy Japan Short term Supply, price and demand risk, recycling restrictions on
39 minor metals, and their potential risks related to
environmental aspects
Identify need for the development of substitutes
Öko-Institut (Buchert et al., 2009) 2009 Sustainable energy
technologies
Global NA Combined demand growth, supply risks, and recycling
restrictions result in a limited availability of materials
that are needed in sustainable technologies
Analyse the availability and recycling potential of
critical metals and identify framework conditions that
enhance their recycling
Angerer (Angerer et al., 2009) 2009 Emerging technologies Germany 2030 High volatility of prices of raw materials, of which costs
contribute largely to manufacturing costs, and high
environmental impacts of extraction contribute to
unsustainable material use
Inform market actors about potential peaks in demand
USDOE (Bauer et al., 2010) 2010 Deployment of renewable/
efficient energy
technologies
Global 0–5 years and
5–15 years
Disruptions of supply in the short term of materials that
are important for clean energy technologies
Assess risks and opportunities, inform the public
dialogue, and identify possible program and policy
directions
Thomason (Thomason et al., 2010) 2010 Defense USA 3 years Potential supply shortfalls in case of war Identify needs for stockpiling of materials for the
defense sector
USDOE (U.S. Department of Energy,
2011)
2011 Deployment of renewable/
efficient energy
technologies
Global 0–5 years and
5–15 years
Disruptions of supply in the short term of materials that
are important for clean energy technologies
Assess risks and opportunities, inform the public
dialogue, and identify possible program and policy
directions
Moss (Moss et al., 2011) 2011 Low-carbon energy
technologies for 2020-
2030
European Union Short-medium
term
Shortages of materials due to a rapid growth in demand
and political risks associated with the geographical
concentration of the supply in the short to medium term
(5–10 years) hinder the large-scale deployment of low-
carbon technologies.
Collect data and monitor material supply and demand,
identify potential bottlenecks, and mitigate risks.
EU2011 (European Commission, 2010) 2011 Economy (focus on
manufacturing sector)
European Union 10 years Disruption of supply due to high supply concentration
and poor country governance, mitigated by recycling
and substitutability
Monitor criticality, prioritize needs and actions,
incentivize the European production of CRM, facilitate
the launching of new mining and recycling activities,
negotiating trade agreements, drafting legislation,
challenging trade distortion measures, promoting
research and innovation and inform on options of
supply diversification, with the purpose to increase
competitiveness of the EU economy
BGS (BGS, 2011) 2011 Economy and lifestyle N/A Now and in the
future
Disruption of supply due to resource competition
(demand by emerging economies), geopolitics ("haves"
seeking to influence "have nots"), resource nationalism
(state control of production), strikes, and accidents)
Inform policy-makers, industry, and consumers about
the need to diversify supply, increase recycling, and
decrease resource use
Yale (Graedel et al., 2015,2012) 2012 Future generations Global Few decades Use of elements at a rate that does not permit the next
generation to acquire them to the extent that might be
needed
Policy development of corporations and governments
(continued on next page)
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
5
Table 1 (continued)
Method Year What is at risk? Geographical scope of
the system at risk
Time horizon Anticipated risk Objective
Yale (Graedel et al., 2015,2012) 2012 Domestic economy N/A, applied to USA 5–10 years Unreliable supply of materials that are important for the
economy due to geological, technological, economic,
social, regulatory, and geopolitical restrictions.
Policy development of corporations and governments
Yale (Graedel et al., 2015,2012) 2012 Company operations N/A 1–5 years Unreliable supply of materials that are important for the
company due to geological, technological, economic,
social, regulatory, and geopolitical restrictions.
Policy development of corporations and governments
BGS (BGS, 2012) 2012 Economy and lifestyle N/A Now and in the
future
Disruption of supply due to resource competition
(demand by emerging economies), geopolitics ("haves"
seeking to influence "have nots"), resource nationalism
(state control of production), strikes, and accidents)
Inform policy-makers, industry, and consumers about
the need to diversify supply, increase recycling, and
decrease resource use
Moss (Moss et al., 2013b) 2013 Low-carbon energy
technologies for 2050
European Union Short-medium
term
Shortages of materials due to a rapid growth in demand
and political risks associated with the geographical
concentration of the supply in the short to medium term
(5–10 years) hinder the large-scale deployment of low-
carbon technologies.
Collect data and monitor material supply and demand,
identify potential bottlenecks, and mitigate risks.
Granta Design
a
(Ashby, 2016;Goddin,
2019)
2013 Product Global 1 year - few
decades
Supply disruption from geopolitical activities,
environmental or substances legislation, conflict
mineral regulations – manifesting as increases in price
volatility or possible supply shortages or changes in lead
times. Social impacts from unethical regional practices
manifesting as damage to consumer perception.
Inability to substitute impacted materials with
performant or suitably certified alternative.
Identify sources of risk and possible impact on business,
identify suitable mitigation measures (e.g. substitution,
product design, supply agreements, stockpiling, circular
economy approaches)
Roelich (Roelich et al., 2014) 2014 Wind turbines UK 2014–2048 Constraint on the deployment rate and scale of low-
carbon technologies due to disrupted supply of
materials.
Enable the identification of potential policy responses to
reduce criticality.
OECD (Coulomb et al., 2015) 2014 Economy OECD countries 2012 and 2030 Disruption of supply of minerals that are important for
the economy and that are difficult to substitute and to
recycle, due to reliance on supply from political instable
countries or due to increasing demand from emerging
markets and new technologies
Inform policymakers on recycling efforts and
development of substitutes, stimulate R&D in the OECD.
Formulate policy targets on "required" recycling and
substitution rates. Stimulate data availability on
indicators for supply risk and material use
KIRAM/KITECH (Lee, 2014) 2014 Economy Korea < 10 years Instability of metal supply to the Korean economy due
to high prices and low stocks.
Secure supply of raw materials to SMEs by identifying
needs for stockpiling, new supply routes, substitution,
and recycling
iCIRCE (Calvo et al., 2017;Valero,
2015;Valero et al., 2011)
2014 Availability of resources Global Few decades Resources become too dispersed for efficient extraction
or recovery
Identify needs for substitution and recycling
EU2014 (European Commission,
2014a)
2014 Economy (focus on
manufacturing sector)
European Union 10 years Disruption of supply due to high supply concentration
and poor country governance, mitigated by recycling
and substitutability
Monitor criticality, prioritize needs and actions,
incentivize the European production of CRM, facilitate
the launching of new mining and recycling activities,
negotiating trade agreements, drafting legislation,
challenging trade distortion measures, promoting
research and innovation and inform on options of
supply diversification, with the purpose to increase
competitiveness of the EU economy
NIES Footprint Method (Nansai et al.,
2017,2015)
2015 Economy Japan 2005 Disruptions of supply in the short term of materials that
are important for clean energy technologies
Identify trade-offs against climate mitigation and supply
risks by introduction of new energy technologies
BRGM (BRGM, 2018,2015, 2014) 2015 Economy France Not explicit Supply of metals with strategic importance to the
French economy is affected by geological availability,
recycling, and environmental, social and political
factors.
Support public and private decision-making
BGS (BGS, 2015) 2015 Economy and lifestyle N/A Now and in the
future
Disruption of supply due to resource competition
(demand by emerging economies), geopolitics ("haves"
seeking to influence "have nots"), resource nationalism
(state control of production), strikes, and accidents)
Inform policy-makers, industry, and consumers about
the need to diversify supply, increase recycling, and
decrease resource use
(continued on next page)
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
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Table 1 (continued)
Method Year What is at risk? Geographical scope of
the system at risk
Time horizon Anticipated risk Objective
SDU (Habib and Wenzel, 2016) 2016 Wind turbines Global 2020–2050 Constrained supply of metals for the deployment of
wind turbines due to limiting geological or geopolitical
factors
Support protection against supply constraints by
improved understanding and interpretation of criticality
results
NSTC (Fortier et al., 2018;McCullough
and Nassar, 2017;NSTC, 2018,
2016)
2016 System using a material
(any scale)
Global 5–10 years Decreased availability of a material due to growing
demand, dependency on political instable mining
countries, by-product dependency, or regulatory
constraints
Anticipate potential supply constraints, inform need for
in-depth criticality assessment
Augsburg2016 (Helbig et al., 2016a) 2016 Photovoltaic modules Global Now and in the
future
Disruptions of supply of materials that are important for
Thin-Film Photovolatic modules
Identification of supply risks and guidance of product
selection
GeoPolRisk (Cimprich et al., 2019,
2017a,2017b;Gemechu et al.,
2017,2016;Helbig et al., 2016b)
2016 Product Country < 10 years Supply disruptions of materials that are used in a
product due to political instability of raw material
producing countries
Identify hotspots to inform product design, material
selection, and supply chain management
ESSENZ (Bach et al., 2016) 2016 Product Global < 10 years Restricted availability of resources due to physical as
well as socio-economic factors and societal acceptance,
which compromises the productivity of companies
Identify hotspots to inform product design, material
selection, and supply chain management
China (Ministry of Land and Resources
of the People’s Republic of China,
2016)
2016 National sustainable
development
China < 10 years Limited access to resources per capita and decreasing
investment in exploration hinders the country’s
sustainable development
Secure the supply of strategic resources by investing in
upgrading and structural adjustment of the mining
industry
Werner (Werner et al., 2017) 2017 Availability of resources Global Few decades Depletion of geological availability of resources Inform decision-making by public and private
authorities on resource use and extraction
UBA (Manhart et al., 2018,2017) 2017 Any system using materials Global N/A Environmental impacts from mining and mineral
processing make raw material supply unsustainable and
in this sense decrease raw material availability.
Inform policy-making and industry in the potential
environmental impacts of raw material from mining
SCARCE (Bach et al., 2017b) 2017 Economy Germany Not explicit Restricted availability of resources to a country due to
physical as well as socio-economic factors and social
acceptance
Identify relative criticality for a country compared to
global average and identify hotspots
EU2017 (Gian Andrea Blengini et al.,
2017a;European Commission,
2017b)
2017 Economy (focus on
manufacturing sector)
European Union 10 years Disruption of supply due to high supply concentration,
poor country governance, trade distortions, and import
dependency, mitigated by recycling and existing
substitutes
Monitor criticality, prioritize needs and actions,
incentivize the European production of CRM, facilitate
the launching of new mining and recycling activities,
negotiating trade agreements, drafting legislation,
challenging trade distortion measures, promoting
research and innovation, with the purpose to increase
competitiveness of the EU economy
EBP/Empa (Spörri et al., 2017;
Swissmem, 2015)
2017 Company operations Global Not explicit Supply risks related to metals relevant for the company's
products, company vulnerability to metal supply
restrictions, environmental and social impacts related to
the supply of metals relevant for the company's products
("reputational risks")
Identify risks related to metals relevant for the
company's products and provide measures to counter
these risks
BIRD (Bach et al., 2017a) 2017 Company operations Global Not explicit The availability of biotic materials to product systems
could become restricted, which could affect the
productivity or continuity of companies, which in turn
affects society
Provide information about the global criticality of raw
materials in product systems over the supply chain
VDI (Kosmol et al., 2017;VDI, 2018) 2018 N/A N/A < 10 years Difficult raw material situations that can impair the
system of interest caused by geological, technical,
geopolitical, or economic factors
Provide guidance on resource efficiency to industry
stakeholders, consultancies, researchers, governments,
and public administration
Augsburg2018 (Helbig et al., 2018) 2018 Lithium-Ion batteries Global Now and in the
future
Disruptions of supply of materials that are crucial for
advanced battery technologies
Identification of supply risks and guidance of
technology selection
Augsburg (Kolotzek et al., 2018) 2018 Company operations Global Now and in the
future
Decreased competitiveness due to unsustainable use of
raw materials
Inform sustainable decision-making by the corporate
management
a
The products of Granta Design are only commercially available.
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
7
raw materials, such as Japan, Korea, the USA, and the European
countries, started to systematically assess the security of their raw
material supply chains (Frenzel et al., 2017). Over this period, the USA
and the European Union developed and published criticality methods,
which were mainly influenced by economic and geopolitical factors.
Such methods are designed to identify potential supply risks of mate-
rials that are important to sustain contemporary lifestyles, and for the
development and growth of national or regional economies (BGS,
2011). National defense considerations have also remained a factor.
The methods that are reviewed in this paper (Table 1) have been
published from this time onwards, starting in 2008.
Methods continued to be developed in order to assess the criticality
of raw materials for specific industrial sectors, such as low-carbon en-
ergy technologies (Bauer et al., 2010;Buchert et al., 2009;Helbig et al.,
2018;Moss et al., 2011) and other emerging technologies. Criticality
assessments also found increased application in companies who began
to approach the topic from their own specific perspectives (Duclos
et al., 2010;Goddin et al., 2013;Kolotzek et al., 2018;Marsden et al.,
2013). As a subset of these approaches, methods have been designed
that assess whether potential supply risks could affect the raw or in-
termediate materials supply for a specific product (Bach et al., 2016;
Cimprich et al., 2017b;Gemechu et al., 2017;Helbig et al., 2016a).
Finally, some methods assess the potential supply shortage of raw
materials for future generations (Calvo et al., 2017;Graedel et al.,
2012).
Table 1 shows that studies do not always specify a geographical
scope, except for most criticality assessments for national or regional
economies. Regarding the time horizon, most studies evaluate criti-
cality for the status quo. A few studies make future projections, e.g.
KIRAM/KITECH for the Korean economy in the year 2020, US DOE
(2010 and 2011) for clean energy materials in 2011–2016 and
2016–2026, OECD (Organisation for Economic Co-operation and De-
velopment) for the OECD economies in the year 2030 (Coulomb et al.,
2015), Habib and Wenzel for the deployment of wind energy up to the
year 2050 (Habib and Wenzel, 2016), Moss et al. for low-carbon energy
technologies up to 2050 (Moss et al., 2013a,b) and Oakdene Hollins for
global use up to the year 2050 (Morley and Eatherley, 2008). Studies
classified as “dynamic criticality studies” investigate the development
of criticality indicators in the past, with the purpose of identifying
trends of increasing or decreasing criticality (Goddin, 2019;Habib
et al., 2016;Habib and Wenzel, 2016;McCullough and Nassar, 2017;
Roelich et al., 2014)).
3.1.2. What type of risk is anticipated?
Changes in the demand and supply of materials have led, at least
locally, to periods of material scarcity and shortage (Ashby, 2016,
2013;Johnson et al., 2007;Tilton, 2003). Relevant changes in supply
can have the form of supply disruptions (short-term) or declines (long-
term – for a distinction see Sprecher et al., 2015). Changes in demand
can be relevant both in positive and negative terms. A positive change
in demand refers to a (frequently sudden) increase in demand in a
possibly relatively short period of time, e.g. by the rapid dissemination
of a new technology. A negative change in demand describes a demand
drop, for example when a technology becomes superfluous (Langkau
and Tercero Espinoza, 2018), which can be a risk for the company or
(regional) economy relying on the adoption of this technology. Most
criticality assessments evaluate either the probability of a decrease in
supply, the probability of an increase in demand, or a combination of
both, which can be generalized by the risk of price increase (Frenzel
et al., 2017), or price fluctuations (Lee et al., 2019). Table 1 shows an
overview of the anticipated risk of the reviewed methods, which illus-
trates that supply and demand changes can be intertwined, such as in
the case of decreased availability of a material due to a growing de-
mand (e.g. NSTC). Several studies only consider supply and demand
changes as a risk when the system at risk is vulnerable to these (e.g.
USDOE and OECD). Vulnerability is frequently marked by a lack of
available substitutes or a lack of options to adapt supply or demand to
the anticipated change, leading to, for example, decreased competi-
tiveness when supply is disrupted. Even if vulnerability is not always
mentioned in the anticipated risk, as summarized in Table 1 it is often
implicitly considered in criticality assessments via the selection of
vulnerability indicators (see Section 3.2.1.2).
3.1.3. What is the objective of the assessment?
Three main objectives could be distinguished that were addressed in
the reviewed criticality methods of Table 1. Firstly, criticality studies
are generally performed to raise the attention of decision makers in
government and industry towards issues related to raw materials supply
and demand. There is no apparent or reasonable interest on the side of
the funders or performers of such studies to either create panic or in-
stigate tension among countries or companies. On the contrary: for
example, Sprecher et al. (2015) show that the stockpiling activity of
Japan amid the REE crisis raised prices even further. Also, a 10-fold
increase in the price of iridium (one of the Platinum Group Metals
(PGMs)) over the last 15 years has motivated industrial users, such as
the magnetic storage sector, to develop their own stockpiles, which
further stimulated speculation by investors (European Commission,
2016). Calm, stable raw materials markets are at the core of effectively
facing the challenges related to the secure supply of raw materials for
industries worldwide.
Secondly, studies often aim to provide information to policymakers,
industry, and/or consumers on mitigating criticality. Mitigation mea-
sures could be focused on decreasing criticality in the short term, such
as pointing out the need for stockpiling of raw materials or challenging
trade-distortive measures. Also, mitigation measures on the medium to
long term could be proposed, such as by diversifying supply, for ex-
ample by increasing recycling, launching new mining activities, finding
substitution alternatives, developing new technologies, or negotiating
trade agreements. For most economies, different mitigation strategies
may be considered in parallel, such as the exploration of new mining
sites, increased recycling, finding substitutes, and increased invest-
ments in material processing (see also Lee et al., 2019).
Thirdly, generic criticality assessments could be used as “pre-
screenings” for in-depth studies with a more specific focus (e.g. NSTC).
Screening studies help to prioritize the type of information that needs to
be gathered for more detailed criticality studies. Dynamic criticality
studies could be considered as a subset of screening studies in which
materials are followed over multiple years considering a limited
number of indicators.
3.1.4. Which materials are evaluated?
Fig. 1 provides an overview of the frequency with which materials
are included in a selection of the reviewed criticality assessments. Most
recent criticality assessments only included non-energy minerals, as the
supply of fossil fuels has been widely covered in earlier analyses (Angerer
et al., 2009;European Commission, 2010). Some studies only included
metals (e.g. Graedel et al., 2015), or only biotic materials (Bach et al.,
2017a), while others were very comprehensive and included all elements
of the periodic table and/or other types of materials, such as industrial
minerals or biotic materials (European Commission, 2017b). A few stu-
dies focus only on one specific material or element (e.g. Rosenau-Tornow
et al., 2009). Materials that are most frequently included are indium,
gallium, cobalt, lithium, nickel, tellurium, copper, the PGMs and the
REEs (see Fig. 1). Materials that are only included in a single study are,
among others, aggregates, ammonia, cork, carbon fiber, and a few
branded products (e.g. Nomex®and Kevlar®).
While most studies look at material supply at the mining stage (e.g.
BGS (2012)), several studies evaluate criticality at different points in
the supply chain of a material (e.g. European Commission (2017c);
Granta Design (2019);NSTC (2016)). For example, the EU study
identifies the bottleneck in the supply chain and quantifies supply risks
at that point. Cimprich et al. (2019) apply a life cycle perspective and
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
8
aim to include all the resources extracted from nature, as well as all the
intermediate products (including ancilliary products) that are required
to produce the product under study. Achzet and Helbig (2013) stress
the differences in the supply chains of materials in different forms,
which are used in different applications, such as high-grade lithium for
batteries and low-grade lithium for lubricants. Thomason et al. (2010)
differentiate five types of carbon fiber for use in national defense
technologies, of which only one is identified as being critical. Also,
among five different forms of manganese (battery-grade manganese
dioxide (natural and synthetic), ferromanganese, metallurgical-grade
manganese ore, and electrolytic manganese metal), only electrolytic
manganese metal was evaluated as being critical (Thomason et al.,
2010). Such precision is not provided in most other studies.
Erdmann and Graedel (2011) already noticed that the reasons to
include or exclude materials in criticality assessments are not always
explained. Material selection can be based on a first identification of
materials that are vulnerable to a supply disruption (compare, e.g.,
Kolotzek et al. (2018)). BGS excludes elements with little or no com-
mercial use, synthetic elements, and elements naturally occurring in a
gaseous state (BGS, 2011). Initial material selection is very relevant, as
materials that are not included in the assessment cannot be identified as
being critical. If data on specific materials are not available, these
materials are sometimes excluded from the assessment as well, which
reinforces the influence that data availability exerts on the goal and
scope. This strategy is, for example, applied in the BGS studies: due to a
lack of available data, the studies exclude boron, bromine, calcium,
carbon (coal), chlorine, helium, phosphorous, potassium, sodium,
Fig. 3. Classical criticality assessment, combining a supply risk dimension and
an importance/vulnerability dimension (NRC, 2008).
Fig. 4. Indicators for the probability of a supply disruption and/or the vulnerability to a supply disruption, their frequency of use, and the scope in which they are
used. Detailed tables with background information are provided in Section S2 and S3 of SI-D.
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
9
sulphur, and iodine (BGS, 2015,2012). NSTC exclude hafnium and
osmium due to unavailable data (NSTC, 2016). For some materials,
available data are very scarce for a large range of indicators – such as
calcium, helium, barium, boron, magnesia, wood, graphite, and clay –
or data are limited on specific material grades or material forms, such
as coking coal (European Commission, 2017d). The REEs and PGMs
suffer from a lack of differentiation between the individual elements
belonging to these groups, although they can have very different uses
and supply situations (e.g. the REE cerium is mostly used in catalysts
and produced in surplus, while the REE neodymium is mostly used in
magnets and the market is comparatively tight (European Commission,
2014b)). Besides lacking data on specific materials, there are large data
gaps concerning the intermediate products of critical materials and
their indirect trade in intermediate and final products, which hinders a
full understanding of the criticality challenges for different countries or
regions and at different life cycle stages (like in a trade-linked global
value chain (Liu and Müller, 2013a)). This can explain the fact that
most studies focus on materials at an element level.
3.1.5. Data requirements
Several aspects of the goal and scope of a criticality assessment
determine the type of data that can be used, i.e. data requirements.
Studies should be defendable, especially if the results are used to decide
on public expenditure. This is relevant for government assessments
(e.g., EC, NSTC, BGS) and studies conducted by academics. Public
studies have a general preference for quantitative data, as they are
perceived as being more objective (Coulomb et al., 2015). Furthermore,
these data should be, ideally, publicly available, which contributes to
the transparency and reproducibility of the study. Relying on such data
is defendable against potential criticism that qualitative assessments
reflect the biases of the researchers – a criticism that is especially im-
portant to avoid for government assessments. The EU method has been
slightly revised for the 2017 assessment (European Commission, 2017a)
to decrease the influence of expert judgement, e.g. by a more precise
calculation of substitution or economic importance and establishing the
priority of data to be used. Companies also must be able to defend their
results, although mostly internally. Therefore, for these, it will be easier
to use confidential data. On the other hand, Kolotzek et al. (2018)
eliminate expert judgment in order to keep indicators more quantita-
tive, which they consider to better serve decision-making. Also, Granta
aims with their proprietary software at quantifying multi-faceted
parameters such as substitutability (Granta Design, 2014).
As stated in Section 3.1.4, data availability has a direct influence on
the materials and life cycle stages included in a criticality assessment.
Constraints in the availability of resources (time, money, and per-
sonnel) can put a limit on the type of assessment that can be done.
Especially public entities do not have the time or the staff to invest in
data collection before conducting a criticality assessment, and they
usually are missing the deep market insights which are necessary to
understand especially the markets for specialty metals, limiting there-
fore the assessment factors to data that are readily available (Coulomb
et al., 2015). Readily available data is also a requirement for assess-
ments that have to be repeated regularly or that assess the evolvement
of criticality over time. The use of quantitative or readily available data
might compromise the quality of the data regarding the representa-
tiveness of the available data for the specific material, technology,
geographical area, and time frame under study. The requirements for
the quality of the data should therefore be anticipated by the study
commissioners.
3.2. Indicator evaluation
Fig. 2 shows that the evaluation of indicators is a key parameter
which affects the outcome of a criticality study. Indicator evaluation is
based on two components: indicator selection and indicator scoring. As
there is no adequate database specifically created for criticality studies,
criticality evaluators have to resort to idealized constructs more or less
fitting their situation, and relate these to available indicators and data
sources (Buijs et al., 2012;Graedel et al., 2012).
3.2.1. Indicator selection
Many of today’s criticality methods have emerged from the ap-
proach developed by the US National Research Council in 2008 (NRC,
2008), which was the very first systematic take on measuring criticality.
As part of the NRC methodology, the criticality matrix was introduced
containing axes for supply risk (later often referred to as “probability/
likelihood of a supply disruption”) and impact of supply restriction
(Fig. 3) – also referred to as “vulnerability to a supply disruption”.
Starting from there, new approaches have developed, taking parts of
established methods as well as adding new aspects. Thus, there are
certain similarities as well as significant differences between the ap-
proaches. This section discusses indicator selection for these two criti-
cality axes, illustrated by the examples of substitutability and en-
vironmental and social factors.
3.2.1.1. Supply disruption. An overview of indicators for the probability
of a supply disruption that are used in different criticality methods with
different scopes is provided in
Fig. 4 and Section S2 of SI-D.
Fig. 4 shows that the most widely used indicator is the diversity of
producing or supplying countries, measured by the Herfindahl-
Hirschman-Index (HHI), often in combination with the political stabi-
lity of this country, measured by one or more sub-indicators of the
Worldwide Governance Indicators (WGI) (Achzet and Helbig, 2013;
Frenzel et al., 2017). These indicators aim to capture the probability of
a supply disruption within current or future supply structures, either
from the perspective of global supply or the country-specific import
mix. Other frequently used indicators are depletion time, recycling
rates, environmental and social regulations, and by-product de-
pendency.
Some indicators reflect potential supply disruptions only for certain
time horizons. For example, it is unlikely that physical scarcity will
limit the accessibility to any material in the foreseeable future, which is
why depletion is not considered a relevant factor in several criticality
studies (e.g. Coulomb et al. (2015)). In others, the indicators depletion
time is calculated using different sub-indicators that represent different
time horizons. For example, the Yale approach considers depletion time
based on reserves for the short/medium term and based on the reserve
base for the long term. Also the indicator “Diversity of supply” can on
one hand be based on current production or import structures, and on
the other on the geological distribution of the material, reflecting the
flexibility to change supply routes either on the short/medium term or
on the long term, respectively (Roelich et al., 2014). Furthermore, it is
not always clear in what time horizon supply or demand changes are
anticipated, which is sometimes illustrated by the parallel inclusion of
indicators that are relevant in the short term (e.g. import shares, cur-
rent production rates) as well as indicators that provide information
about resource availability in the long term (e.g. reserve base, crustal
content). Evaluation on an indicator level – i.e. without aggregation –
would provide valuable information on, for example, in what time
horizon a supply might be disrupted (e.g. as applied by Öko-Institut
(Buchert et al., 2009)), or which risk mitigation options might be of
interest for the specific material.
It is noteworthy that, despite the different scopes of the different
studies, frequently the same or similar indicators are selected for the
evaluation of the probability of a supply disruption.
Fig. 4 shows that the indicators most frequently used in studies
focusing on a national economy are also often chosen in studies with a
technology, company, or product focus. A few indicators are indirectly
reflected by other, more frequently used indicators (such as market
price, price increase, or elasticity of supply that could be represented by
price volatility or by-product dependency). Some indicators are mainly
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
10
used by methods which aim to provide a holistic sustainability ap-
proach, or which consider technical limitations, including environ-
mental impacts, geological properties, or natural disasters. Only a few
studies include indicators that reflect potential bottlenecks in the
supply chain downstream from the mining activity, such as restrictions
regarding storage and transport and material processing capacity. Fi-
nally, a few indicators refer to mitigation measures (e.g. stockpiling,
exploration, or resource efficiency). A key difference between methods
seems to be the consideration of demand growth. Not all the studies
focusing on a national economy consider demand growth, which is
however more often included in technology-oriented methods. This
implies that the criticality of material use for an economy is often
considered only in the context of the current economic situation, dis-
regarding the future development of the economy. Indicator selection is
sometimes dependent on only a few aspects of the goal and scope. For
example, Kolotzek et al. (2018) select indicators based on their per-
ceived relevance by company actors, established via a survey. Hence,
indicator selection implicitly depends on the experience and anticipated
risks of the individual stakeholders that filled in the survey.
It also happens that studies with a similar scope use different in-
dicators (Frenzel et al., 2017), for example illustrated by the evolve-
ment of the methods applied by the EC and BGS over the years, which is
further specified in Section S2.2 in SI-D. This demonstrates that, over
time, the relevance of indicators can be perceived differently, which
can be influenced by discussions in the scientific arena on indicator
selection, as well as by indicator choices of newly published studies
with similar scopes.
Neither dissipation nor rebound effects have been considered as
potential risk indicators. This could be due to the difficulty of quanti-
fying such effects, or, regarding rebound effects, due to the delay of
occurrence: they are often an unforeseen, unintended, but relevant side
effect after the implementation of an innovative functional material or
process. Frenzel et al. (2017) state that, in many studies, the choice of
indicators is rather dependent on subjective opinions (or a “gut feeling”
of the method authors) than on empirical evidence. Also Erdmann and
Graedel (2011) mention the lack of description of the foreseen dy-
namics of supply disruptions, adaptation measures, and impacts. This
could partly explain the weak link between the anticipated risk and the
selected indicators. For example, the risk factors that were suggested by
BGS are not fully reflected in the final set of indicators. Furthermore,
while political stability is considered as an indicator of supply risk in
many studies, the possibility of active trade policy is less often included
– although China’s industrial policy on rare earth production in the late
2000’s and early 2010’s is considered to be an important factor in the
rare earth supply crisis during that period (Wübbeke, 2013). A potential
solution to establish this link is by the description of cause-and-effect
mechanisms – such as commonly used in environmental Life Cycle
Impact Assessment (Frischknecht and Jolliet, 2016) and demonstrated
for criticality methods by Cimprich et al. (2019) for the methods Geo-
PolRisk, Economic Scarcity Potential (ESP), and ESSENZ. Such a de-
scription of cause-and-effect mechanisms aids in identifying methodo-
logical differences and deciding whether an approach is compatible
with the goal and scope of the study.
3.2.1.2. Vulnerability. Besides the indicators for risk of supply
disruption, Fig. 4 also presents the indicators that are used to
evaluate the vulnerability to a supply disruption for different study
scopes. The indicator that is included in most criticality studies is
substitutability. Regarding the other indicators, there is little overlap
between the indicators that are used to evaluate the vulnerability for a
company and for technologies – showing the scope-dependency of
vulnerability indicators. A few indicators (demand growth, internal
demand, and use in emerging technologies) are used both for methods
focusing on technologies and economies.
Indicators could be divided into three groups:
1. Indicators that reflect that the material is used by the system under
study (e.g. internal demand, sectors using the material, population
using the material, and apparent consumption) – indicating that the
more a material is used, the more vulnerable the system is to a
supply disruption.
2. Indicators that reflect the relative use of the material compared to
other users (e.g. globally), or the relative importance of the material
compared to other materials that are used by the same system (e.g.
via the price of the material or the revenue or GDP that is impacted
by a supply disruption).
3. “Other indicators”, which are also used (by other methods) to
evaluate supply risks: substitutability (further discussed in the next
section), demand growth, import dependency, trade restrictions,
price volatility, stockpiles, and resource efficiency.
The first and second group of indicators are useful to rank materials
considering their relative importance for a system. For the indicators of
the third group, the establishment of cause-and-effect mechanisms as
discussed in the previous section would be helpful to evaluate whether
they better reflect the anticipated risk as an indicator for the probability
of a supply disruption or as an indicator for the vulnerability to such a
disruption, and whether they provide useful information to fulfil the
objective of the study.
3.2.1.3. Substitutability. As mentioned before, substitutability is
included in most criticality assessments, either as an indicator for
supply disruptions or as an indicator for vulnerability. In the EU method
(European Commission, 2017a) the substitution parameter affects both
the economic importance in terms of technical and cost performance of
the available substitutes for individual applications, and the supply risk
in terms of physical availability of a substitute, its criticality and the
way it is produced, e.g. as a main product or a by- or co-product. The
GE method (Duclos et al., 2010) integrates a measure of substitutability
both in the evaluation of supply risk and of importance: high
substitutability in the market decreases the probability for a supply
disruption, while a low substitutability of a material in the technology
that is important for the system under study makes the system highly
vulnerable for a supply disruption. There does not seem to be
agreement on whether the inclusion of substitutability in two
criticality factors leads to double counting of this attribute – a risk
that could be minimized if scoring would be communicated at an
indicator level and results were not further aggregated.
Not all studies include substitutability in the initial assessment.
Some (e.g. NEDO) aim to identify elements for which substitutes need
to be found, which make substitution a potential mitigation strategy
based on the outcome of the study. The EU explicitly distinguishes
between currently available substitutes and potential substitution, and
only includes the former in the study – recommending the latter for
future research needs. This differentiation clearly marks the short-to-
medium-term time frame in which supply risks are assessed in the EU
method.
3.2.1.4. Environmental and social factors. Many of the criticality
methods shown in Table 1 include environmental and/or social
factors in their analysis. While there is overlap in the type of
indicators that are used (such as human health, ecosystem quality,
and biodiversity as assessed by the Life Cycle Impact Assessment
method ReCiPe (Bach et al., 2017b;Graedel et al., 2012;Kolotzek
et al., 2018)), the indicators seem to reflect different perspectives
regarding the anticipated risks that may or may not be correlated to one
another. The following perspectives have been identified in the
reviewed methodologies:
-Perspective 1: Environmental/social impacts as a source of supply risk
(e.g. European Commission, 2010): Environmental impacts cause a
high or low probability of a supply disruption of a material due to
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
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potential regulations
-Perspective 2: Vulnerability of the environment/social values to material
use (e.g. Graedel et al., 2012): The use of a material has a high or
low impact on the environment
-Perspective 3: Environmental/social risk (e.g. proposed by Frenzel
et al. (2017)): The disrupted availability of a material has a high or
low impact on the environment or on social values
-Perspective 4: Reputational risk (e.g. ESSENZ): The use of a material
with a high environmental or social impact affects the reputation of
the company.
A discussion is provided in Section S4 of SI-D as to how these dif-
ferent perspectives are considered within the reviewed criticality as-
sessments. Several method developers (e.g. EU and KIRAM/KITECH)
highlight environmental and social issues as future research needs. An
evaluation of the appropriate perspective(s) can be helpful for a po-
tential integration of environmental and social factors into existing
methods. As long as clear cause-and-effect mechanisms are not yet
formulated on the influence of environmental and social implications
on criticality, it is recommended to present environmental and social
implications as a separate dimension for the identification and resolu-
tion of possible trade-offs.
3.2.1.5. The resilience concept. The previous sections demonstrate that a
clear-cut separation of supply risk indicators, vulnerability indicators,
or suggested mitigation options is not always applied nor
straightforward in criticality evaluations. Dewulf et al. (2016) point
out that most criticality assessments are backward-looking and that a
more forward-looking approach could be a promising new perspective
in criticality research, investigating how economies could respond to
potential supply disruptions by responsive actions to improve supply
chain resilience (see e.g. Mancheeri et al. (2018) and Sprecher et al.
(2017)) – or, in other words, to decrease the supply chain vulnerability
to supply disruptions. Recent studies have discussed barriers and
enablers for mitigation strategies to enhance supply chain resilience
on the company level (Gardner and Colwill, 2018;Griffin et al., 2019;
Bustamante et al., 2017); some of them with an emphasis of circular
economy strategies (Gaustad et al., 2018;Lapko et al., 2018). Further
exploration of the resilience concept could provide more understanding
in the cause-and-effect mechanisms between supply risks, vulnerability,
and potential mitigation options and whether it is indeed useful to
distinguish these three types of indicators.
3.2.2. Data availability
Fig. 2 illustrates that data availability influences the outcomes of
materials criticality assessments in at least three different ways: by af-
fecting the goal and scope of the assessment, the selection of the in-
dicators, and the evaluation of the selected indicators. Whereas the first
relationship was covered in Section 3.1.4, the latter relationships are
further discussed in sections 3.2.2.2 and 3.2.2.3, following a review on
data sources and their limitations.
3.2.2.1. Data sources and their limitations. Criticality methods use a
wide range of data sources to identify and quantify the level of specific
risks associated with their production or consumption, such as mining
and smelting/refining statistics, indicators related to country-level
sociopolitical factors, life-cycle inventory data to assess the
environmental impacts of materials provisioning, recycling rates,
industry reports, and expert judgment. Fig. 5 visualizes the data
sources used in the criticality methods of Table 1.
According to Fig. 5, the major data providers are geological surveys
(USGS, BGS, BRGM, BGR, etc.), the World Bank providing the World-
wide Governance Indicators (WGI), the Fraser Institute Annual Survey
of Mining Companies reporting the Policy Perception Index (PPI)
(Fraser Institute, 2019), scientific literature (i.e., peer-reviewed pub-
lications and technical reports), UNEP IRP data on recycling rates
(UNEP, 2011), UNDP’s Human Development Index (HDI), ecoinvent for
environmental data, as well as a wide range of industry reports (e.g.,
Roskill) and expert opinions. Furthermore, each method uses unique
data sources not widely shared among methods. For example, the Yale
criticality method developed for corporations uses INSEAD’s Global
Innovation Index, while the Augsburg method uses the Social Hotspot
Database and Granta’s method uses material property data from Ma-
terial Universe as well as company-specific information. Further ex-
amples can be deducted directly from Fig. 5.
Ideally, the criticality assessor has complete awareness of material
Fig. 5. Network visualization of data sources
used by the 39 criticality methods examined in
this study (China is excluded as data sources
are unspecified). Blue nodes represent data
sources, their size is shown proportional to the
number of times a data source is being used.
Red nodes represent the criticality methods
assessed. More details are available in SI-B.
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
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flows and added economic value at each link in the supply chain of all
materials that are used within the system under study. However, data
availability and data quality can vary significantly by raw material.
Production and consumption data for major metals such as iron and
aluminum tend to be widely researched and complete (Cullen et al.,
2012;Liu et al., 2013;Liu and Müller, 2013b;Pauliuk et al., 2013),
whereas data for many minor metals (e.g., germanium, indium, tell-
urium, europium, and scandium) are more difficult to obtain and more
prone to variation and error. These data may exist but kept proprietary
by industry. Examples include actual pricing and materials usage data –
particularly for materials that are not traded on large open exchanges,
but rather through direct contracts between the producer and the user –
and materials embedded in products, such as rare earth magnets that
might be incorporated into motor components that downstream users
may not even recognize. Moreover, the proprietary data may also be
dispersed among many different entities, so that no single entity has
access to all the data. Hence, public data can be unavailable for specific
indicators, specific materials or material grades, and specific points in a
materials’ supply chain.
3.2.2.2. Influence of data availability on indicator selection. Criticality is
mostly considered to be a relative concept: one material is more or less
critical than another. Therefore, ideally only materials and indicators
are included in the assessment for which the same type and quality of
data are available. This becomes a limiting factor in criticality
assessments with very large scopes, such as the OECD study that
includes 51 materials and assesses their economic importance for all
countries within the OECD (Coulomb et al., 2015). In studies evaluating
criticality over time, only materials and indicators are included of
which data is available in time series. Data availability was explicitly
considered for the operationalization of indicators in the studies of
OECD, BGS, and the most recent assessment of the European Union.
Examples of indicators for which data are lacking are provided in
Section S5 in SI-D.
If data on a certain indicator are missing, a proxy indicator might be
used, such as import data instead of production data (BGS, 2011). The
probability of supply disruption and economic importance are based on
very complex mechanisms that are difficult to measure. Instead of
identifying and measuring all contributing factors, often an indicator is
chosen that is directly related to economic impact (Frenzel et al., 2017).
Examples of proxy indicators for substitutability and availability of
reserves and by-product dependency are expected demand growth and
price elasticities of supply, respectively (Moss et al., 2011). Several
indicators could also be combined to more accurately represent the
aspect of interest. For example, due to lacking available data for a large
range of materials to accurately represent the supply of raw materials to
the EU, the revised EU method uses a new indicator that combines
global supply and actual supply to the EU (i.e. the mix of domestic
production plus import) (Blengini et al., 2017a,b;European
Commission, 2017c).
Proxies can also be useful to estimate future indicator values. The
OECD study conducts the same assessment on two different points in
time. For their assessment of 2015, the country concentration of pro-
duction in 2030 is assessed by the estimation of global reserves using
data from 2014. Hence, “global reserves” are used as a proxy for “global
production in 2030”. Habib and Wenzel (2016) use a similar approach
to assess the country concentration of raw materials production in
2050. Ioannidou et al. (2019) recommend using more concrete in-
dicators, such as estimations of population and material intensity, in-
stead of a generic estimation of future demand, for dynamic assess-
ments with respect to future trends and scenarios.
3.2.2.3. Influence of data availability on indicator scoring. The data that
are available should be interpreted with care. Data collection and
reporting of the physical stocks and flows of critical materials are often
not done with the criticality context in mind. Data quality is affected by
an inherent uncertainty, and routinely updated data contain frequently
inherent errors resulting from the primary data reporting. Global
production data e.g. differ between the USGS and BGS; thus the
selection of the source or combining these sources will result in
different risk evaluations. Many studies convert data ranges into a
mean value, resulting in a loss of information on uncertainty on the
way. Using data ranges for the criticality calculations also provides a
range of criticality determinations. Such ranges can be calculated if the
original data sources present uncertainty ranges as well. These are
provided by, among others, the World Bank for the WGI. However, for
most indicators, such uncertainty ranges are not provided, implying
that the data point is an absolute, true value. This is overcome by
Graedel et al. by calculating their own uncertainty ranges (Graedel
et al., 2012).
Besides the inherent uncertainty of data, data should be evaluated
regarding their representativeness for the technology, the specific ma-
terial, the geographical area, and the time frame formulated in the goal
and scope of the study. Data often represent current or historic situa-
tions, and should be updated regularly. Data from different sources,
such as production and trade nomenclature, are usually not harmo-
nized. This leads to inconsistencies that weaken the robustness of the
monitoring of the physical material flows and the evaluation of raw
material criticality. Extremely difficult to assess are trade statistics.
Fig. 4 shows that such statistics (e.g. UN Stats and Eurostat) are used as
input data for several assessments. The accuracy and reliability of these
data directly impact the outcome of these studies. For example, most
reports group minor producers into an ‘Other’ category. Treating this as
one source, or a collection of many sources, will materially impact the
degree of monopoly of supply that is indicated in the assessment. Fur-
thermore, criticality of raw materials can vary for materials with dif-
ferent purity grades (e.g. pure metals, ingots, etc.), making it important
that data sources differentiate between different material forms. For the
trade of metal concentrates, it is challenging to find numbers about
metal content and associated elements. The trade of complex products
is even more difficult, and results of “objective, statistics-based” CRM
assessments should be cross-checked by (industry) experts. However,
even for experts, trade data are a complex puzzle that require much
additional information and market knowledge. If the experts articulate
serious doubts on how to interpret the data, the “objective” assessment
should be carefully revised.
More examples on the evaluation of data uncertainty and re-
presentativeness are provided in section S5.2 of SI-D. Section S5.2 also
presents how studies have dealt with lacking data, for example by at-
tributing arbitrary scoring, using proxy data, or by additional data
collection. In most reviewed criticality studies, data quality is not ad-
dressed in an explicit or quantitative manner. This could be further
improved by adopting practices that have been implemented in other
domains, such as LCA, where data quality indicators have been devel-
oped which can be used to calculate uncertainty ranges (Weidema
et al., 2013;Weidema and Wesnæs, 1996).
3.3. Aggregation
In order to reach a final criticality outcome, different aggregation
tasks can be performed: a) the aggregation of sub-indicators to com-
posite single score indicators (e.g. the WGI, which contains 6 sub-in-
dicators), b) the aggregation of various indicators (e.g. HHI and WGI) to
a single score for a specific dimension (e.g. the probability of a supply
disruption), c) the aggregation of different dimensions (e.g. probability
of a supply disruption and vulnerability) to a raw-material-specific
single-score criticality index, and d) the assessment of a single-score
criticality index for a whole technology, consisting of multiple raw
materials, which is performed by a few studies (Goddin, 2019;Helbig
et al., 2018,2016a). In Section S6 of SI-D it is discussed how criticality
assessments apply different scaling and aggregation methods on each of
these levels. Aggregation is necessarily related to loss of information
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
13
and includes normative decisions. Therefore, it is recommended to
display the disaggregated data and perform a sensitivity analysis.
3.4. Interpretation and communication of the results
Once the indicator scores are calculated and the required aggrega-
tion steps are done, the results must be interpreted and communicated.
Firstly, the results should always be interpreted with the context of the
study in mind. The results will only reflect the criticality of the eval-
uated materials for the specified system under study, and only the in-
dicators that are included in the assessments will determine the criti-
cality of the materials, which explains the dependency of the
interpretation of the results – besides on the indicator scoring and ag-
gregation – on the goal and scope in Fig. 2. Secondly, not only the
method is tailored to capture and combine the elements of major in-
terest, but also the way in which the results are communicated can be
very stakeholder-specific, which influences further interpretation of the
results by the intended audience. Further elaboration is made here on
two main aspects of the communication of the results that is divergent
in the reviewed studies: the level of aggregation and the use of a
threshold value. Furthermore, it is discussed how the interpretation and
communication of the results could merit from uncertainty and sensi-
tivity analyses.
3.4.1. Level of aggregation
A main difference in the presentation of the results of different
studies is the number of aggregation steps that are applied.
Communication of criticality scoring per indicator provides the most
detailed information and enables understanding of the sources of cri-
ticality (Hatayama and Tahara, 2015). Hotspot analyses on a material
level might provide more information than the ranking of materials due
to a low data availability and high data uncertainty (Speirs et al., 2013).
Furthermore, understanding of the sources of risk enables to identify
suitable mitigation strategies. Scoring of materials per indicator is
provided by, among others, the EC in their background reports, by
BRGM, Granta, Moss, and Yale. Furthermore, dynamic criticality stu-
dies can provide more detail on an indicator level by providing scores
for different points in time (McCullough and Nassar, 2017). The pre-
sentation of indicator scores might be cumbersome if a lot of indicators
are included in the assessment, or if a lot of materials are evaluated.
However, it provides flexibility to the user to conduct tailored studies
with the inclusion or exclusion of certain indicators, or with alternative
weighting factors of the indicators.
Many studies present their results on the level of scoring per criti-
cality dimension. Materials are often plotted in a 2D or 3D matrix in
which the axes represent the probability of supply disruption, the vul-
nerability to this disruption (or importance of the material), and poten-
tially a third axis, such as environmental importance in the Yale method.
Several methods end up with a single criticality parameter. This is
the case for, among others, NEDO with the aggregated score (Hatayama
and Tahara, 2015) and NSTC with a criticality potential score. Although
the EC also presents a list of critical materials, no final numerical ag-
gregation of the criticality dimensions is done in their study. The CRM
are presented in rigorous alphabetical order to eliminate any references
to relative criticality levels, which is a specific policy need (Blengini
et al., 2017a,b). Frenzel et al. (2017) argue that, following classical risk
theory, a single score could be obtained by multiplying an axis of
“probability for supply disruption” with an axis of “vulnerability”. In
practice, however, most methods are not designed with this perspective
in mind, making such a multiplication potentially erroneous.
Different forms of communication can be used by different audi-
ences, i.e. reflecting different assessment objectives. Lists are practical
for policymakers that oversee targeting public funding to mitigation
programs. Lists can also be useful in early-warning screenings. For ex-
ample, NSTC produced a list of potentially critical minerals for the US,
to be followed by a second stage in-depth analysis. Hence, the initial list
aids in prioritizing the materials that require further study. Studies that
aim to inform different types of audiences can chose to communicate
the results in different forms. For example, the EC provide single raw
materials factsheets, with structured and detailed information and data,
as a complement of the 2011, 2014 and 2017 lists of CRM for the EU.
Raw materials factsheets show the data used in the assessment and
bring further information and data that third parties might want to use
in their ad hoc criticality studies. Detailed information is relevant for
both suppliers and users of individual raw materials, as such informa-
tion can be used to better assess individual risks.
3.4.2. Use of a threshold value
An important element in the presentation of criticality results is the
concept of a “critical” vs a “non-critical” raw material, based on which a
list of CRM can be drawn (European Commission, 2017a,2014b,2010;
US Department of Interior, 2018). The scientific community is generally
less favorable to the adoption of a sharp criticality threshold value and
more inclined to qualitative or quantitative levels of criticality (ideally
with the recognition of uncertainty ranges) (Graedel et al., 2012;
Hatayama and Tahara, 2015;Kolotzek et al., 2018;NRC, 2008), as this
highlights that criticality is not an absolute status, but rather a relative
condition. In contrast, policymakers have historically shown a pre-
ference for sharp and simpler communication solutions (European
Commission, 2017a,2014b,2010;Lee, 2014), which are easier to un-
derstand for non-experts and more practical to translate into effective
policy actions at large scale. The determination of the threshold value is
not a scientific exercise but can be motivated politically, such as com-
parability with previous studies or the designation of a specific number
or share of the evaluated materials as “critical”.
3.4.3. Uncertainty and sensitivity analyses
As shown in the previous sections, criticality assessments are un-
avoidably affected by many uncertainties and methodological choices,
e.g. regarding the acceptable quality of the data, the selection of ma-
terials, the choice of data sources, and the choice of aggregation
methods. The robustness of the criticality results is strongly dependent
on the transparent communication of (the effect of) uncertainties and
assumptions. For example, Helbig et al. (2016a) evaluate the influence
of aggregation methods on the final outcomes via a sensitivity analysis
and conduct uncertainty analyses. Graedel et al. (2015) present the
relative criticality of each material in the form of a “criticality cloud”
that accounts for uncertainty ranges. As very few methods report un-
certainty ranges of the criticality results, it is not known whether the
assignment of materials as “critical” is generally robust, especially in
studies that apply criticality threshold values.
4. Conclusions and perspectives
After more than a decade of 21
st
century raw material criticality
assessments, conducted by scientists and governmental institutes, the
question “Which materials are critical?” has not provided an un-
ambiguous response, even if one has a specific nation or industry in
mind. Materials such as chromium, cobalt, gallium, lithium, mo-
lybdenum, tantalum, tellurium, and vanadium have very diverging
criticality determinations: in some studies they appear to be highly
critical, while in other studies they are considered to be not critical at
all. This paper seeks to clarify which contextual factors and choices
affect the outcomes of criticality assessments. The IRTC team demon-
strated that there are diverging views on what criticality is about. Some
studies are concerned with the criticality of raw materials for national
defense or a national economy, while others focus on specific tech-
nologies, companies, or products. Most studies anticipate a disruption
in the supply of raw materials, either due to unstable supply routes, or
due to sudden increases in demand, for example caused by the re-
levance of a material for emerging technologies. The assessments often
aim to provide recommendations regarding criticality mitigation or the
D. Schrijvers, et al. Resources, Conservation & Recycling 155 (2020) 104617
14
need for a better understanding of the supply chains of prioritized
materials. Studies mostly cover a large range of materials in their as-
sessment: including most metals or as many elements from the periodic
table as possible – however focusing often solely at the mining stage.
These differences in goal and scope of criticality studies can partly
explain the different outcomes – but not entirely. Some indicators ap-
pear very frequently to assess the probability of supply disruption or the
vulnerability to supply disruption, such as the country concentration of
production, political stability of supplying countries, by-product de-
pendency, and the use of a material in a technology that contributes to a
company’s revenue or a country’s economy. Studies with seemingly
similar goals and scopes do not, however, always select the same in-
dicators. This is largely dependent on the anticipated events that could
affect raw material supply. A clear mechanism between the selected
indicators and a resulting supply risk, for example in the form of a
cause-and-effect diagram, is often missing, resulting in diverging se-
lections of (proxy) indicators.
Data availability is also a key factor that influences the design of
criticality methods. Study composers do not necessarily have access to
the same data sources, as this is influenced by, among others, the re-
quired transparency, the perception of objectivity, and ease of access,
which are often limiting factors in governmental assessments. Data
availability influences the selection of indicators and the inclusion of
materials in the assessment, as well as the accuracy of the results. There
are important data gaps on specialty elements and materials that are
frequently produced as by-products. Data sources often do not differ-
entiate between different material grades or forms, although these can
have important differences in supply. Also, data on intermediate pro-
ducts is lacking, which explains why most studies evaluate material
supply primarily at the level of mines. Remaining differences in criti-
cality determinations could be ascribed to different aggregation pro-
cedures and the formulation of a criticality threshold value, which is
especially useful in the communication of the results to policymakers.
During the course of the IRTC expert discussion, the potential value
of criticality concepts taking a more holistic approach on sustainable
development throughout the whole material value chain came up re-
peatedly. These reflections go beyond the scope of this review paper but
will be investigated in more detail in upcoming publications of the
project.
From this paper we can extract several lessons that could contribute
to the future development and implementation of criticality assess-
ments. A clear description of the goal and scope, including a description
of the anticipated risks that are considered within the study will help
the readers of a study to evaluate whether a study fits their perception
on criticality and to identify which studies are comparable. Researchers
should develop an increased understanding of the cause-and-effect
mechanisms that link anticipated risk factors to concrete indicators,
possibly with the application of the resilience concept. This could also
aid in developing aggregation methods that contribute to a meaningful
determination of risk. Furthermore, it would be interesting to evaluate
whether risk scenarios exist that are currently underrepresented by
criticality assessments, such as the risks of negative demand changes
(i.e. demand drops). Communication on critical raw materials should be
more transparent regarding the used methodology, data sources, and
uncertainty ranges, especially when criticality determinations have
consequences on public decision-making.
Increased understanding on the relevance of indicators for different
goals and scopes can stimulate more efficient data collection. With ju-
dicious assumptions, it might for some cases be possible to establish
order-of-magnitude estimates. While this is not as rigorous as a vali-
dated model with full data access, these types of analyses can be used in
an initial round of screening to create the basis for further investigation.
The results of our study also highlight the value of expert judgment
both as a source of data as well as in interpreting publicly available data
sources. Further efforts should be put in the identification of best
practices regarding data sources, (proxy) indicator selection,
aggregation methods, and presentation and communication formats. In
this regard, the rise of machine learning and big data offers an inter-
esting opportunity, as this information might allow criticality assess-
ments to become more dynamic and comprehensive. Recent advances
in data science may also offer new ways to collect data, e.g. the concept
of differential privacy is gaining traction among business users to share
information while maintaining a degree of privacy. This area merits
further exploration for the enhancement of criticality assessments.
Stakeholders interested in the evaluation of raw material criticality
would further benefit from the availability of clear guidance in the
formulation of their goals and scopes, the selection of potentially useful
indicators and aggregation methods, and the interpretation of the
outcomes. Such guidance could be a first step in improving the quality
of criticality assessments, and fostering more standardized approaches.
Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influ-
ence the work reported in this paper.
Acknowledgements
The IRTC project has received funding from the EIT RawMaterials,
supported by the Institute of Innovation and Technology (EIT), a body
of the European Union, under the Horizon 2020, the EU Framework
Programme for Research and Innovation. The authors would like to
thank Vanessa Bach, Ton Bastein, Britta Bookhagen, Hiroki Hatayama,
Alan Hurd, Risto Krebs, Gavin Mudd, Nedal Nassar, Tanya Tsui, and
Alicia Valero for contributing to the Criticality Library (SI-A) and the
Goal and Scope table (SI-B). Furthermore, we thank René Kleijn, Ester
van der Voet, and Steven Young for their contributions to the initial
scoping of the paper, Ton Bastein, Julian Hilton, Dominique Guyonnet,
and the two anonymous reviewers for their comments, and Tom
Graedel for his contributions to the discussion.
Appendix A. Supplementary data
Supplementary material related to this article can be found, in the
online version, at https://doi.org/10.1016/j.resconrec.2019.104617.
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... vulnerability and probability of supply disruption), consider different aspects (e.g. geopolitical, economic, social, environmental) and use different indicators (e.g. a country's concentration of mines and manufacturing) [9]. In the European policy context, the identification of CRMs is part of the strategies from the EU Raw Materials Initiative [10] to tackle the issue of sufficient access to raw materials. ...
... Where there was no immediate link to LC(S)A, the search performed by mid-March 2021 yielded 33 journal articles, reviews and reports. Three other publications could be identified from the review by Schrijvers et al. [9]. So, 36 documents were considered further. ...
... There is no scientific consensus on best practice how to 4 noting that a distinction at inventory level is also possible, as e.g. suggested evaluate criticality neither in general nor from a product life cycle perspective [9]. There is, however, a general agreement that material criticality is not part of environmental LCA. ...
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The beginning of the 21st century is marked by the fourth industrial revolution, which could be a great opportunity for a sustainable technological transformation. The key role of these technologies in the development of a more sustainable future implies the need for the evaluation and monitoring of both supply risks as well as environmental and social impacts of a number of raw materials in the supply chain. These raw materials that are important to the economy and might be under supply risk are referred to as Critical Raw Materials (CRMs) in the EU. The integration of Life Cycle Sustainability Assessment (LCSA) - well established for sustainability evaluation - and Criticality Assessment (CA) – increasingly used as governance tool - is therefore consequent to support decision-making regarding efficient use those natural resources. Based on a critical review of CA methods within and outside the framework of an LCSA, this research aimed to investigate the compatibility of CA methods with the life-cycle approach. The methods range from specific CA methodologies (e.g., NRC (USA) and EC-CA (EU)) to the existing methods integrating CA and LCSA (e.g., ESSENZ and GeoPolRisk). The evaluation of the methods was based on a set of criteria (e.g., acceptance and credibility) and further analysis of compatibility with frameworks from ISO 14040-44 and UNEP-SETAC. The current challenges for integration in the field are identified, namely: interpretation of criticality within the three pillars of sustainability (social, economic or environmental); the incompatibility among inventories and the characterization of material’s criticality; arbitrariness in the interpretation of what is “critical”; and the uncertainty intrinsic to CA models. Potential solutions towards the operationalization of criticality indicators in a product-oriented LCSA include the definition of the impact pathway of criticality in LCSA, the linkage of criticality indicators to product/technological flows, the use of intermediate indicators (supply risk and economic importance), the characterization of criticality at the normalization and weighting step, and addressing uncertainties in an LCSA. Further works of this research will explore the solutions proposed.
... To have a broader perspective on this important role of raw materials, several studies have been devoted to developing and utilizing the assessment of the criticality of raw materials to mitigate the risk, as well as the concern, of the source of materials [19]. Prior studies [20][21][22][23] have been conducted to measure the effects of critical raw materials on a specific product. ...
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With the evolution of today's economy, supply chain management for raw materials is a complex task, but it can be simplified with the appropriate strategies. Thus, relationships between firms and suppliers have become critical for enterprise success and country development. This study investigates the effects of raw materials sources, including domestic and international ones, on small and medium enterprises (SMEs) performance. Supporting this research, all the regression models are conducted on Stata version 16.0 software with the dataset of 3485 manufacturing SMEs, utilizing longitudinal data derived from biannually repeated surveys of randomly selected SMEs in ten provinces in Vietnam over the period of 2011-2015. Additionally, the results of this study indicate the significant positive effects of domestic raw materials on firm performance. Meanwhile, international raw material sources present SMEs with several disadvantages in maintaining the effectiveness of SMEs' operations. In addition, the results also highlight that the overflow of raw materials from non-state enterprises has negative effects on firm performance. Alternatively, this study aims to fill the literature gap on supply chain management to suggest to SMEs some justifiable strategies to fortify sustainable growth and the rational flow of raw materials.
... One recent study suggested that policymakers should evaluate and include demand for critical raw materials in their climate change mitigation planning, specifically relating to countries' nationally determined contributions (NDCs) . How and why some raw materials are assessed as critical is subject to increasing research interest (Graedel and Reck, 2016;Schrijvers et al., 2020). ...
Chapter
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Mitigating climate change will require major changes to energy systems. It is widely acknowledged that fossil fuels can affect local and national development pathways, for better or worse. Low-carbon energy systems use renewable energies instead of fossil fuels. With only a few exceptions, renewable energies use flows that are often diffuse and distributed geographically, and renewables are therefore assumed to reduce the risk of a resource curse (Månsson, 2015). The energy transition is framed by some as 'geopolitical', as it creates both relative winners and losers, depending on, for example, how natural resource endowments are distributed (Overland et al., 2019; Vakulchuk, Overland and Scholten, 2020). Compared to fossil energy, low-carbon energy technologies contain both more metals and new ones too. Some of these metals are geographically concentrated and found in countries with fragile institutions and high levels of corruption. Policy responses may therefore be required to avoid some of the drawbacks associated with fossil fuels (Ali et al., 2017; Bazilian, 2018; Lee et al., 2020). The aim of this chapter is to provide an overview of the present state of knowledge of how a renewable energy transition affects metal demand and the risk of a resource curse in mining countries. The chapter starts with an overview of metals that are used in low-carbon energy systems and are perceived as critical. Next, the chapter summarizes insights from the existing literature on the potential metal demand for a renewable energy transition. The final section then turns to the supply side to address from where these resources could come and what impacts this could have for states and local mining communities. 2 LOW-CARBON ENERGY SYSTEMS AND THEIR DEMAND FOR CRITICAL METALS Renewable energy systems require more materials in total and some different materials than their fossil fuel counterparts. Materials are used in all steps of the supply chain and some metals are used in several steps. To grasp which materials and how much can be required for low-carbon energy transitions, the entire supply chain needs to be analysed. This section there-1 This is an open access work distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 Unported (https:// creativecommons .org/ licenses/ by-nc-nd/ 4 .0/).
... The list was compiled by the International Institute for Sustainable Development (IISD) and is presented in Table 1. 45 While there is no perfect methodology and several different standards and indicators can be used to assess criticality, 48,49 the IISD taxonomy is widely accepted and used by scholars and practitioners alike, including the International Renewable Energy Agency, 50 the European Commission, and 31 academic articles. 44 Table 1 lists the types of critical materials that go into the production of solar, wind, EVs, and storage technologies and that are therefore expected to experience steep demand growth. ...
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The energy transition is causing a surge in demand for minerals for clean energy technologies, giving rise to concerns about the sources and security of supplies of critical materials. Although Central Asia was one of the Soviet Union's main sources of metals and industrial minerals, it has been forgotten in contemporary global critical materials analyses. Here we review the Central Asian mineral resource base and assess its current and potential contributions to global supply chains. We find that the importance of Central Asia lies mainly in the diversity of its mineral base, which includes mineable reserves of most critical materials for clean energy applications. This renders the region important in mineral economics, security of supply, and geopolitical perspectives alike. In sum, Central Asia is likely to become a new hotspot for mineral extraction and a major global supplier of selected critical materials for clean energy technologies.
... With a growing data-storage demand [6], around 20 to 70 million EOL hard-disk drives (HDDs) are generated per year. Besides waste management issues, the growing demand of critical and precious metals used in these two technologies means they can be threatened by sudden supply restrictions [20]. These problems can be solved by changing to a circular economy which reinforces the concepts of reduce, reuse, and recycle (3R) [15]. ...
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Thesis
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Thesis
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Sustainable metal supply will be essential to achieve climate and sustainability goals (e.g., Paris agreement), for instance by providing the necessary raw materials for renewable energy infrastructure systems. The potential exploitation of mineral resources from the deep sea (e.g., polymetallic nodules) can play a major role in this supply. A holistic environmental analysis is needed, in order to consider the entire value chain of the products obtained out of deep-sea exploitation. Therefore, the objective of this study was to perform a prospective life cycle assessment (LCA) of deep-sea-sourced commodities and compare it to equivalent products obtained from terrestrial mining. It considered as reference flow one tonne of (dry) nodules, using a cradle-to-gate approach up to the final metal commodities, analyzing the delivery to the market of 10.5 kg of copper, 12.8 kg of nickel, 2.3 kg of cobalt and 311.3 kg of ferromanganese. Three environmental impact categories were analyzed, i.e., climate change, acidification and photochemical oxidant formation. Overall, onshore activities (e.g., hydrometallurgical processing) are the main hotspots for environmental impacts of metals sourced from the deep sea; offshore activities play a minor role in the value chain. While photochemical oxidant formation impacts would be similar to terrestrial alternatives, the deep-sea-sourced commodities can bring environmental gains in the order of 38% for climate change and up to 72% for acidification. As this study shows, a strategic selection of the location for onshore processing of the polymetallic nodules is key to target cleaner production, not only because of the distance from the nodules site, but especially because of the available energy mix. The results should be interpreted with care, though, due to intrinsic limitations of the LCA study, e.g., the prospective nature of this study, the limited access to terrestrial mining data, amongst others. Nonetheless, regardless the limitations a prospective LCA imposes, this study highlights some important potential benefits that commodities from deep-sea polymetallic nodules can bring to society with respect to three important environmental impacts.
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Environmental aspects are more and more relevant for raw material policy-making and responsible sourcing strategies. This trend is partly based on growing public awareness of problems and impacts associated with extraction and processing of ores and minerals. Disaster events such as the tailing dam failures in Kolontár (Hungary, October 2010) and Bento Rodriguez (Brazil, November 2015) quite frequently highlight the fact that many mining and processing practices are associated with substantial environmental impacts and risks for the local and even regional environments. However, there is also increasing recognition that the rather devastating environmental performance of many past and current mining projects is a major reason for communities around the world to oppose both the development of new and the expansion of existing mines. Although mining companies constantly have to increase their efforts to secure the social license to operate, many scholars already point out that both environmental impacts and associated social and political reactions are emerging as a decisive factor determining current and future raw material supply. In light of these concerns, raw material policy-making requires solid information on environmental hot spots in mining, as well as on raw materials of particular concern. Whereas indicators and information systems are already well developed for geological, technical, structural, political, regulatory, and economic supply risks, there is currently no holistic method and information system for environmental concerns associated with the mining of raw materials. Although life cycle assessment can provide methodological support for various environmental aspects, it has substantial weaknesses in the fields of ecosystem degradation, impacts on fresh- and groundwater resources, and hazard potentials from episodic disaster events. This paper presents a methodology that aims to fill this gap. Our proposed method provides a system of 11 indicators allowing the identification of raw material-specific environmental hot spots and rankings of raw materials. Although the indicator system is qualitative in nature, its composition and aggregation cover the most relevant environmental concerns arising from mining and allow prioritizing of raw materials from a global environmental perspective.
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Certain non-energy materials have been identified as being critical to the manufacturing sector and wider economy due to having a high risk of supply disruption combined with high economic importance. The criticality of specific raw materials is becoming increasingly acute as the escalating use of resources is driven by an increasing global population. Critical materials are vital elements in the value chain yet their supply risk may often be ineffectively addressed by traditional supply chain management strategies. Most research to date has been focused at a national or industrial policy level thus many manufacturers are unaware if their operations are at risk from critical materials at a product level. This paper presents a framework that takes a systematic approach to identifying, assessing and mitigating risk associated with critical materials bilaterally along the value chain to facilitate manufacturers in the identification, assessment and mitigation of critical material supply risk. This paper also describes how the framework can be facilitated for application in industry through preliminary design specifications towards a development of a decision support tool.
Technical Report
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Purpose Guidance is needed on best suited indicators to quantify and monitor the man-made impacts on human health, biodiversity and resources. Therefore, the UNEP-SETAC Life Cycle Initiative initiated a global consensus process to agree on an updated overall life cycle impact assessment (LCIA) framework and to recommend a non-comprehensive list of environmental indicators and LCIA characterization factors for 1) climate change, 2) fine particulate matter impacts on human health, 3) water consumption impacts (both scarcity and human health), and 4) land use impacts on biodiversity. Method The consensus building process involved more than 100 world-leading scientists in task forces via multiple workshops. Results were consolidated during a one week Pellston WorkshopTM in January 2016 leading to the following recommendations. Results LCIA framework: The updated LCIA framework now distinguishes between intrinsic, instrumental and cultural values to assess, with DALY to characterize damages on human health and with measures of vulnerability included to assess biodiversity loss. Climate change impacts: Two complementary climate change impact categories are recommended: a) The Global Warming Potential 100 years (GWP 100) represents shorter term impacts associated with rate of change and adaptation capacity, and b) the Global Temperature change Potential 100 years (GTP 100) characterizes the century-scale long term impacts, both including climate-carbon cycle feedbacks for all climate forcers. Fine particulate matter (PM2.5) health impacts: Recommended characterization factors (CFs) for primary and secondary (interim) PM2.5 are established, distinguishing between indoor, urban and rural archetypes. Water consumption impacts: CFs are recommended, preferably on monthly and watershed levels, for two categories: a) The water scarcity indicator “AWARE” characterizes the potential to deprive human and ecosystems users and quantifies the relative Available WAter REmaining per area once the demand of humans and aquatic ecosystems has been met, and b) the impact of water consumption on human health assesses the DALYs from malnutrition caused by lack of water for irrigated food production. Land use impacts: CFs representing global potential species loss from land use are proposed as interim recommendation suitable to assess biodiversity loss due to land use and land use change in LCA hotspot analyses. Conclusions The recommended environmental indicators may be used to support the UN Sustainable Development Goals in order to quantify and monitor progress towards sustainable production and consumption. These indicators will be periodically updated, establishing a process for their stewardship.
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The diversity of raw materials used in modern products, compounded by the risk of supply disruptions—due to uneven geological distribution of resources, along with socioeconomic factors like production concentration and political (in)stability of raw material producing countries—has drawn attention to the subject of raw material “criticality.” In this article, we review the state of the art regarding the integration of criticality assessment, herein termed “product‐level supply risk assessment,” as a complement to environmental life cycle assessment. We describe and compare three methods explicitly developed for this purpose—Geopolitical Supply Risk (GeoPolRisk), Economic Scarcity Potential (ESP), and the Integrated Method to Assess Resource Efficiency (ESSENZ)—based on a set of criteria including considerations of data sources, uncertainties, and other contentious methodological aspects. We test the methods on a case study of a European‐manufactured electric vehicle, and conclude with guidance for appropriate application and interpretation, along with opportunities for further methodological development. Although the GeoPolRisk, ESP, and ESSENZ methods have several limitations, they can be useful for preliminary assessments of the potential impacts of raw material supply risks on a product system (i.e., “outside‐in” impacts) alongside the impacts of a product system on the environment (i.e., “inside‐out” impacts). Care is needed to not overlook critical raw materials used in small amounts but nonetheless important to product functionality. Further methodological development could address regional and firm‐level supply risks, multiple supply‐chain stages, and material recycling, while improving coverage of supply risk characterization factors.
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Organizations of all sizes are vulnerable to critical material supply disruptions. Although there is a significant body of literature that examines how large entities such as nations and governments can assess and mitigate criticality, there is very little work that addresses firm-level criticality in a way that is actionable for businesses. This work uses literature review and case study analysis to understand the impact of critical material supply risk at the firm level, and to determine salient internal indicators. A total of 42 criticality studies were reviewed and the findings were used to develop a matrix to assess and monitor criticality risk using internal firm-specific data. The matrix incorporates three categories of risk including product concept viability, production, and profitability. It also contains four key business functions including finance, procurement, marketing, and production. These aspects were chosen because they are relevant to all businesses that produce and sell manufactured goods, and because they represent dynamics that are within the control of an individual firm. Unlike the global and national level indicators emphasized in most current research, the indicators proposed in this research are derived from data that firms can compile with reasonable ease. Finally, this work considers the role of the organization in criticality risk assessment and mitigation through an examination of the data needed to complete the aforementioned matrix and the likely sources of that information. The findings of this analysis elucidate the gap between internal and external and micro- and macro- criticality assessment, as well as provide a framework for firm-level criticality mitigation.
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In recent literature, the concept of criticality aspires to provide a multifaceted risk assessment of resource supply shortage. However, most existing methodologies for the criticality assessment of raw materials are restricted to a fixed temporal and spatial reference system. They provide a snapshot in time of the equilibrium between supply and demand/economic importance and do not account for temporal changes of their indicators. The static character of criticality assessments limits the use of criticality methodologies to short‐term policy making of raw materials. In the current paper, we argue for an enhancement of the criticality framework to account for three key dynamic characteristics, namely changes of social, technical, and economic features; consideration of the spatial dimension in site‐specific assessments; and impact of changing governance frameworks. We illustrate how these issues were addressed in studies outside of the field of criticality and identify the dynamic parameters that influence resource supply and demand based on a review of studies that belong to the general field of resource supply and demand. The parameters are grouped in seven categories: extraction, social, economic, technical, policy, market dynamics, and environmental. We explore how these parameters were considered in the reviewed studies and propose ways and specific examples of addressing the dynamic effects in the criticality indicators. Furthermore, we discuss the current work on future scenarios to provide reference points for indicator benchmarks. The insights and guidelines derived from the review and our recommendations for future research set the foundations for an enhanced dynamic and site‐specific criticality assessment framework.