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The social footprint of permanent magnet production based on rare earth elements – a social life cycle assessment scenario
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Energy (2017) 000–000 984–990 EnergyProcedia Procedia142 00 (2017) www.elsevier.com/locate/procedia 9th International Conference on Applied Energy, Aug 21-24, 2017, Cardiff, United Kingdom
9th International Conference on Applied Energy, Aug 21-24, 2017, Cardiff, United Kingdom
The social footprint of permanent magnet production based on rare The social productionscenario based on rare earthfootprint elementsof – apermanent social lifemagnet cycle assessment The 15th International Symposium on District Heating and Cooling earth elements – a social life cycle assessment scenario Schlör, Holgera*, Zapp, Petraa, Marx, Josephinea, Schreiber, Andreaa, Venghaus, Sandraa, a a a thePetra feasibility of using the aheatAndrea demand-outdoor Hake,Josephine Jürgen-Friedrich Schlör,Assessing Holgera*, Zapp, , Marx, , Schreiber, , Venghaus, Sandraa, a Jülich, 52425 Jülich, Germanyheat demand forecast temperature functiona Forschungszentrum forHake, a long-term district Jürgen-Friedrich Abstract
a Forschungszentrum Jülich, 52425 Jülich, Germany
I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc
a
IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal Abstract UN-Habitat stated in 2012 bthat renewable could generate moreLimay, employment Veolia“investment Recherche &in Innovation, 291energies Avenue Dreyfous Daniel, 78520 France and income for urban c households [1]” and for UN-Habitat renewable energies are a central element of the environmental sustainability of urban areas Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France UN-Habitat stated in 2012 that “investment renewable energies could generate more transformation employment and income for urban [2]. Renewable energy technologies are seen byinthe UN as instruments to support the urban process [1]. However, households [1]” and for UN-Habitat renewable energies are a central element of the environmental sustainability of urban areas renewable energy technologies such as direct-drive wind turbines based on permanent magnets need non-renewable resources [2]. energy technologies by the analyse UN as instruments support the transformation However, suchRenewable as rare earth minerals [3-5]. are Weseen therefore rare earth to production in urban Australia, Malaysia process (Mount [1]. Weld), USA renewable technologies such Obo). as direct-drive wind turbines based on takes permanent magnets need non-renewable resources (Mountain Pass), and China (Bayan The Mount Weld process chain place in three countries (Australia, Malaysia, Abstract energy such as The rare Mountain earth minerals [3-5]. We production in Obo Australia, Malaysia (Mount Weld),InUSA China). Pass process takestherefore place inanalyse the USArare andearth China. All Bayan processes take place in China. our (Mountain Pass), and China (Bayan Obo). The Mount Weld process chain takes place in three countries (Australia, Malaysia, social lifeheating cycle assessment we use addressed the five major social impactascategories (labour & decent work,for health & safety, District networks (sLCA), are commonly in the literature one of the mostrights effective solutions decreasing the China). The Mountain Passfrom process takes place in the USA andsuggested China. All Bayan Obo processes take placetointhem China. In our human rights, governance, community & infrastructure) [6,systems 7] by UNEP/SETAC [8] and assign 21 the social greenhouse gas emissions the building sector. These require high investments which are returned through heat social cycle use the five major social impact (labour rights & decent safety, indicators of the 2012changed Social(sLCA), Hotspots Database [6]and to cover every socialcategories theme in our sLCA. sales.life Due to assessment the climateweconditions building renovation policies, heat demand in the work, futurehealth could&decrease, human rights, community infrastructure) 7] suggested byproduction UNEP/SETAC [8]the andthree assign themproduction 21 social Using the sLCA model, wereturn estimate the& social footprint [6, function for every step of raretoearth prolonging thegovernance, investment period. indicators ofscope theon2012 Social Database [6] to cover every social theme in our sLCA. chains. Based presented footprint functions, the total social footprint of the temperature three rare earth production is The main ofthethis paperHotspots is social to assess the feasibility of using the heat demand – outdoor function for heat sites demand Using the for sLCA model, estimate the development social footprint function every of The the the three rareis earth production estimated year 2015 based on located the of(Portugal), the Humanfor Development (HDI). For Mountain Pass process, forecast. Thethedistrict ofwe Alvalade, in Lisbon was usedproduction as aIndex case step study. district consisted of 665 chains. Based on thevery social footprint the taking total footprint of the three raresignificantly earth production is our analysis reveals lowconstruction social risks for thefunctions, process parts place in the United States and social buildings that vary inpresented both period and typology. Threesocial weather scenarios (low, medium, high) andhigher threesites district estimated forscenarios theThe yearAustralian 2015 on the(shallow, development of thecause Human Development (HDI). For the Mountain process, risks in China. processes of Mount Weld also a very smallIndex social footprint, whereas the Pass processes in renovation were based developed intermediate, deep). To estimate the error, obtained heat demand values were our analysis reveals very low social risks for the social process parts taking theand United States significantly higher social Malaysia and China cause a asignificantly higher footprint. The place BayaninObo processes have a considerably higher social compared with results from dynamic heat demand model, previously developed validated byand the authors. risks in China. The Australian processes of Mount Weld cause also a very small social footprint, whereas the in footprint than the other two process chains. The results showed that when only weather change is considered, the margin of error could be acceptable for someprocesses applications Malaysia China cause a significantly higher footprint. Bayanconsidered). Obo processes have a after considerably higher social (the errorand in annual demand was lower than 20%social for all weatherThe scenarios However, introducing renovation footprint than the other two increased process chains. ©scenarios, 2017 The Authors. Published by Elsevier Ltd. (depending on the weather and renovation scenarios combination considered). the error value up to 59.5% Peer-review under responsibility the scientific committee of the Summit Applied Energy The value of slope coefficient of increased on average within the World range Engineers of 3.8% up to 8%– per decade, that Symposium corresponds&to the © 2017 2017 The The Authors. Published by Ltd. © Published by Elsevier Elsevier Ltd. Forum: Low Carbon Cities Urban Energy Joint Conference. decrease inAuthors. the number of&heating hours of 22-139h duringofthe season (depending combination Peer-review under responsibility of the scientific committee the heating 9th International Conferenceononthe Applied Energy.of weather and Peer-review responsibility of the of theintercept World Engineers – Applied renovation under scenarios considered). On scientific the other committee hand, function increasedSummit for 7.8-12.7% perEnergy decadeSymposium (depending & on the Forum: Carbon Cities & Social Urban Energy Joint Conference. Keywords: Rare Earth Elements, LCA, Marginal Footprint coupledLow scenarios). The values suggested couldSocial be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations. Keywords: Rare Earth Elements, Social LCA, Marginal Social Footprint
© 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Keywords: Heat demand; Forecast; Climate change
Peer-review under responsibility of the scientific committee of the World Engineers Summit – Applied Energy Symposium &
1876-6102 © 2017 The Cities Authors. by Elsevier Forum: Low Carbon & Published Urban Energy JointLtd. Conference.
Peer-review under responsibility of the scientific committee of the World Engineers Summit – Applied Energy Symposium & Forum: Low Carbon Cities & Urban Energy Joint Conference. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of the 9th International Conference on Applied Energy . 10.1016/j.egypro.2017.12.157
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Schlör Holger et al. / Energy Procedia 142 (2017) 984–990 Holger Schlör/ Energy Procedia 00 (2017) 000–000
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1.1. Habitat III and the meaning of renewables for urban development Urban lifestyles offer attractive options, but the highly aggregated nature of a city often leads to higher resource intensity, and the concentration of consumption and waste production poses additional challenges for sustainable city design [1, 9]. Sustainable and nexus-oriented resource management requires a major transformation of existing systems to achieve resilient and ecological functioning of urban systems. The energy sector is at the centre of this technological transition process [10], because renewable energy technologies are seen as instruments for success in this transformation process [4]. The UN Habitat III Conference 2016 also supports the International Energy Agency (IEA) in demanding renewable energy for urban systems [9, 11]. The UN identified urban areas as “the greatest drivers … fostering energy efficiency [and] renewable energy [for ] the urban economy [9].” Renewables, such as solar cells or wind turbines, are techniques for sustainable energy development. However, these renewable energy technologies need non-renewable mineral resources and especially rare earth minerals [4, 12, 13]. Rare earth elements (REEs) are used in nearly every renewable energy technology, in solar panels, fuel cells, batteries, wind power magnets, energy-saving lighting and automotive catalysts [13-15]. In the following we will analyse what social impact such a strategy may have by simultaneously considering that “investment in renewable energies could generate more employment and income for urban households [9].” 1.2. Introduction to social life cycle assessment (sLCA) and its social foundation framework Social life cycle assessment is an important analysis tool for revealing the social effects of current production and consumption patterns [16]. We used the UNEP/SETAC Guidelines [1] and the Social Hotspots Database (SHDB) developed by the NGO New Earth [3] and distributed by GreenDelta [2] for our sLCA. The Social Hotspots Database (SHDB) of 2013 [17] is based on the Global Trade Analysis Project (GTAP) of 2004 and was published in 2008. * The SHDB contains social quantitative and qualitative information from the years 2010-2012, which is weighted according to social risk (low, medium, high, and very high) for 227 countries and 57 sectors.† The SHDB enabled us to assign social risk points (social footprint) to every single production step in rare-earth-based magnet production [6, 18]. The social footprint determines the effects of production and consumption patterns on the social capital of society: the social foundation of society. We divided the social foundation of society into five main categories [17] according to the SHDB: labour rights & decent work, health & safety, human rights, governance, community & infrastructure [6, 7] and assigned to them 21 social indicators to cover every social dimension with at least one indicator in our sLCA (Fig.1). These indicators describe and characterise the social foundation of society. The social foundation framework combines “the concept of planetary boundaries with the complementary concept of social boundaries [19]” and thereby defines “a framework for defining the safe and just operating space for humanity that integrates social wellbeing into the original planetary boundaries concept [20].” We describe the labour rights and a decent life with eight indicators which include the need for adequate labour laws and the right to strike as essential labour rights. We describe health and safety with the indicators: risk of fatality from disease due to occupation and risk of loss of life (death by exposure to carcinogens). The human rights categories as the central element of every society cover the rights of the indigenous population, gender equity, human health issues and the Heidelberg barometer. The governance system is described by two indicators: fragility in the legal system of civil, common and religious laws which “provides information on the extent to which an independent judiciary exists [17]“ and the risk of corruption, which “generates economic distortions in the public sector [17]“ and undermines the trust in public institutions, or as Rogow and Lasswell put it: “A corrupt act violates responsibility toward at least one system of public or civic order and is in fact incompatible with (destructive of) any such system. A system of public or civic order exalts common interest over special interest; violations of the common interest for special advantage are corrupt [21]“. The state of the community and of the infrastructure is
* †
https://www.gtap.agecon.purdue.edu/databases/ GreenDelta, Social Hot Spots Database in openLCA, Quick explanation
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described by five indicators: too few hospital beds, the quality of drinking water and sanitation, the conditions for smallholders, and whether children go to school.
Fig. 1: Social foundation
We assigned the indicators of figure 1 also to the three dimensions of the Human Development Index (HDI) [22] to enable a scenario calculation for 2015 of the social footprint based on the SHDB of 2012. Six indicators (9, 10, 14, 17, 18, 20) can be assigned to the first dimension ‘a long and healthy life’, one indicator ‘children out of school’ belong to the second dimension of the HDI ‘education index’ and 14 indicators (1-8, 11, 12, 13, 15, 16, 21) describe the third dimension ‘a decent standard of living’. The selected SHDB and HDI indicators describe the social foundation of society. As a summary, we can say that the ecological footprint registers the effect of production and consumption patterns on the ecological capital and the social footprint determines the effects on the social capital of society, which we define as the social foundation of any society. The social LCA converts the social footprint into social risk points, in the same way the ecological footprint converts the lifestyle of a person into the space which is necessary to provide the resources used. 1.3. The example of magnet production based on rare earth elements We analyse rare earth production in Australia, Malaysia (Mount Weld), USA (Mountain Pass), and China (Bayan Obo). The physical interrelations (e.g. materials, energy demand, emissions, waste) are analysed by an LCA to capture the different process chains: mining, beneficiation, separation, metal and magnet production, which build the system boundaries of our analysis. In the case of Mount Weld, mining and beneficiation (crushing, grinding, magnetic separation, flotation) takes place in Australia, separation in Malaysia, electrolysis and magnet production in China. The mining, beneficiation, and separation of the Mountain Pass processes take place in the USA and electrolysis and magnet production again in China. In Bayan Obo, all the processes take place in China. The functional unit is the central principle of LCA, which provides a reference for all in- and outputs and enables the comparability of the LCA results [16]. The functional unit of our analysis is per kg permanent magnet produced. The functional unit captures the technical functionality of the analysed product and enables us to compare the social risks associated with producing permanent magnet in Australia, China and USA. Hence, the functional unit represents the technical functionality of the product.
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1.4. Results In the following, we present the results of our social footprint model based on the SHDB. 1.4.1. Mountain Pass (MP) The analysis of the Mountain Pass process chain reveals, as shown in figure 2, the development of the mining, processing, separation, electrolysis and magnet social footprint function subject to the chosen indicators.
Fig. 2: Mountain pass social footprint
Fig. 3: Mount Weld social footprint
The figure reveals that the social footprints of the Mountain Pass processes taking place in the USA (Mining, processing, separation) are very low. The footprint significantly increases for the processes (electrolysis, magnet production) taking place in China. 1.4.2. Mount Weld (MW) For the Mount Weld process chain the main production steps are presented in figure 3. The figure reveals that the social footprint constantly increases with every new social indicator. The social footprint of mining is nearly as low as that of Mountain Pass. The processing footprint is more or less equal to those of Mountain Pass, whereas the social footprint of the processes taking place in Malaysia are clearly higher. The total social footprint of the Chinese electrolysis and magnet production is nearly the same as that of Mountain Pass. 1.4.3. Bayan Obo (BO) Figure 4 reveals the significantly higher social footprints in nearly every production step of the Chinese process chain. Only the social mining costs in China are in the same order as those of the two production sites. The magnet process results are the same because in all three production chains magnet production takes place in China.
Schlör Holger et al. / Energy Procedia 142 (2017) 984–990 Author name / Energy Procedia 00 (2017) 000–000
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Fig. 4: Bayan obo social footprint 1.4.4. Scenario 2015 Based on the presented social footprint functions, the total social footprint of the three rare earth production sites – Mount Weld (Australia), Mountain Pass (USA), Bayan Obo (China) – is estimated for the year 2015, because the most recent data of the SHDB are from 2012. The 2015 scenario is built on the latest data of the HDI of 2015 [22]. The HDI is considered as a reference for deriving the possible social development in the analysed countries. If the social situation of the country improves it is assumed that the value of the HDI increases and the social footprint decreases. If, on the other hand, the social situation of the country gets worse, the HDI of that country decreases and the social footprint increases. Hence, it is assumed that a correlation exists between the development of the HDI and the social situation of the country measured by the social footprint. Table 1: Human Development Index (HDI) between 2012 and 2015
Development of the Human Development Index Australia (Mount Weld)
China (Bayan Obo)
USA (Mountain Pass)
0.713 0.723 0.734 0.738
0.915 0.916 0.918 0.920
2012 0.933 2013 0.936 2014 0.937 2015 0.939 Source: Authors, 2017 based on UNDP, 2016
Table 1 shows that the social situation of all three countries improved between 2012 and 2015 because the HDI increased. The highest increase occurred in China followed by Australia and the USA. The development of the HDI enables us to draw conclusions about the changes of the social situation in the three countries, which allows us to estimate the development of the social footprint beyond the year 2012 of the SHDB. Therefore, using the already estimated social footprint functions and the marginal social footprint function of the three production sites, the marginal and total social risks per kg permanent magnet of the three production sites are estimated for 2015. Based on our sLCA model, we obtain three social footprint equations: 1. For the Bayan Obo (BO) production chain we identify the following social footprint equation:
2015
2
2
BOTotal risk HDI 2012 7.0614 x 530.26 x 227.32 7740, R = 0.9877, x=social indicators The function shows that the total social risk per kg permanent magnet produced in Bayan Obo for 2015 is 7740 social risk points. The marginal social footprint for Bayan Obo is represented by the following equation: BO 2015 HDI 2012 2 7.0614 x 530.26 212 x The marginal social footprint for Bayan Obo is thus 212 social risk points. For the Australian-Malaysian production chain of Mount Weld, we obtain the following social footprint function:
2.
2015
2
2
MWL HDI 2012 5.0675 x 385.25 x 94.88 5890, R 0.9887 The equation shows that the social risk is, with 5890 risk points, significantly lower than that of the Bayan Obo process chain. We also obtained a lower marginal footprint for the Mount Weld production site: MWL 2015 HDI 2012 2 5.0675 x 385.25 161.2 x For Mountain Pass (USA), we obtain the following equations:
3.
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MPM HDI 2012 4.1283 x 313.07 x 143.47 4720, R 0.9886 . It is thus the lowest total social risk per kg permanent magnet of the three production sites. The marginal social footprint is also the lowest of the three production chains: MPM 2015 HDI 2012 2 4.1283 x 313.07 131.1 x The scenario shows that the Mountain Pass process chain causes the lowest marginal social costs (131.1 social risk points (132 in 2012)) in 2015 and the lowest total social costs (4720 risk points (4745 (2012)) per kg permanent magnet produced, followed by the marginal social risks of the Mount Weld process chain (161.2 social risk points (162, 2012)) and the total social risks (5890 social risk points, 5927 (2012)).). Bayan Obo has the highest social risks but the decrease in social footprint from 2012-2015 is also estimated to be the largest there. The marginal social costs decrease from 220 to 212 social risk points and the total social cost is reduced from 8020 to 7740 per kg permanent magnet produced.
1.5. Summary On the basis of the SHDB, our SLCA model allows us to determine the social footprint of the production of rare earth elements for rare-earth permanent magnets for 2012. Our model further enables to also assess the future development of the social conditions for producing permanent magnets derived from the development of the Human development index using the sLCA scenarios. The analysis shows that the three rare earth production sites in the four countries generate social risks by producing rare earth elements for the permanent magnets used in wind turbines. The fabrication of rare earth technical parts for the renewable energy system, which is regarded by both the German government and the UN Habitat Conference as a solution for the current unsustainable energy system, is not free from social risks. These social risks arise because of the general fabrication conditions of the industrial sectors producing these parts. To enable people to live within a safe and just space, the political and economic institutions have to develop strategies to reduce these risks and protect the environment by avoiding CO2 and other emissions and not simultaneously endangering the social foundation of society. 1.6. References [1] UN-HABITAT. State of the world's cities 2012/2013. Prosperity of cities. Nairobi: United Nations Human Settlements Programme (UN-HABITAT); 2012. [2] UN Habitat. 2015 Global City Report2016. [3] Roelich K, Dawson DA, Purnell P, Knoeri C, Revell R, Busch J, et al. Assessing the dynamic material criticality of infrastructure transitions: A case of low carbon electricity. Applied Energy. 2014;123:378-86. [4] Campbell W. Rare Earth Minerals: The new non-renewables. Nature blog: Nature; 2014. [5] U.S. DEPARTMENT OF ENERGY. CRITICAL MATERIALS STRATEGY. Washington: DOE; 2011. [6] Norris C, Norris G, Aulisio D. Efficient Assessment of Social Hotspots in the Supply Chains of 100 Product Categories Using the Social Hotspots Database. Sustainability. 2014;6:6973-84. [7] Benoit-Norris C, Cavan DA, Norris G. Identifying Social Impacts in Product Supply Chains:Overview and Application of the Social Hotspot Database. Sustainability. 2012;4:1946-65. [8] UNEP/SETAC (Society of Environmental Toxicology and Chemistry). Guidelines for social life cycle assessment of products. Nairobi: UNEP; 2009. [9] Habitat III (United Nations Conference on Housing and Sustainable Urban Development). Quito Declaration of the Habitat III. Quito: United Nations; 2016. [10] Rifkin J. The third industrial revolution: How the internet, green electricity, and 3-D printing are ushering in a sustainable era of distributed capitalism. World Financial Review. 2012;2012:8-12. [11] IEA. World Energy Outlook 2008. Paris: IEA; 2008. [12] Smith Stegen K. Heavy rare earths, permanent magnets, and renewable energies: An imminent crisis. Energy Policy. 2015;79:1-8. [13] American Physical Society (APS), Materials Research Society (MRS). Energy Critical Elements. Washington:
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Materials Research Society,; 2011. [14] Hoggett R, Bolton R, Candelise C, Kern F, Mitchell C, Yan J. Supply chains and energy security in a low carbon transition. Applied Energy. 2014;123:292-5. [15] Arent D, Pless J, Mai T, Wiser R, Hand M, Baldwin S, et al. Implications of high renewable electricity penetration in the U.S. for water use, greenhouse gas emissions, land-use, and materials supply. Applied Energy. 2014;123:368-77. [16] van Haaster B, Ciroth A, Fontes J, Wood R, Ramirez A. Development of a methodological framework for social life-cycle assessment of novel technologies. Int J Life Cycle Assess. 2017;22:423-40. [17] Norris CB, Norris GA, Cavan DA. Social hotspot database. Supporting documentation update: 2013. York Beach, Maine: New Earth; 2013. [18] New Earth/ Social Hotspots Database project. Social hotspot database web portal. Introductory User Tutorial. York Beach, Maine, 03910, United States of America: New Earth; 2014. [19] Raworth K. A safe and just space for humanity. Can we live within the doughnut? Oxfam Discussion Papers. 2012;2012. [20] Dearing JA, Wang R, Zhang K, Dyke JG, Haberl H, Hossain MS, et al. Safe and just operating spaces for regional social-ecological systems. Global Environmental Change. 2014;28:227-38. [21] Rogow AA, Lasswell HD. Power Corruption and Rectitude. Englewood Cliffs, New Jersey: Prentice-Hall; 1963. [22] United Nations Development Programme (UNDP). Human Development Report 2016. New York: UNDP; 2016.
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Availableonline onlineatatwww.sciencedirect.com www.sciencedirect.com Available Energy Procedia 00 (2017) 000–000
ScienceDirect ScienceDirect
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Energy (2017) 000–000 984–990 EnergyProcedia Procedia142 00 (2017) www.elsevier.com/locate/procedia 9th International Conference on Applied Energy, Aug 21-24, 2017, Cardiff, United Kingdom
9th International Conference on Applied Energy, Aug 21-24, 2017, Cardiff, United Kingdom
The social footprint of permanent magnet production based on rare The social productionscenario based on rare earthfootprint elementsof – apermanent social lifemagnet cycle assessment The 15th International Symposium on District Heating and Cooling earth elements – a social life cycle assessment scenario Schlör, Holgera*, Zapp, Petraa, Marx, Josephinea, Schreiber, Andreaa, Venghaus, Sandraa, a a a thePetra feasibility of using the aheatAndrea demand-outdoor Hake,Josephine Jürgen-Friedrich Schlör,Assessing Holgera*, Zapp, , Marx, , Schreiber, , Venghaus, Sandraa, a Jülich, 52425 Jülich, Germanyheat demand forecast temperature functiona Forschungszentrum forHake, a long-term district Jürgen-Friedrich Abstract
a Forschungszentrum Jülich, 52425 Jülich, Germany
I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc
a
IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal Abstract UN-Habitat stated in 2012 bthat renewable could generate moreLimay, employment Veolia“investment Recherche &in Innovation, 291energies Avenue Dreyfous Daniel, 78520 France and income for urban c households [1]” and for UN-Habitat renewable energies are a central element of the environmental sustainability of urban areas Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France UN-Habitat stated in 2012 that “investment renewable energies could generate more transformation employment and income for urban [2]. Renewable energy technologies are seen byinthe UN as instruments to support the urban process [1]. However, households [1]” and for UN-Habitat renewable energies are a central element of the environmental sustainability of urban areas renewable energy technologies such as direct-drive wind turbines based on permanent magnets need non-renewable resources [2]. energy technologies by the analyse UN as instruments support the transformation However, suchRenewable as rare earth minerals [3-5]. are Weseen therefore rare earth to production in urban Australia, Malaysia process (Mount [1]. Weld), USA renewable technologies such Obo). as direct-drive wind turbines based on takes permanent magnets need non-renewable resources (Mountain Pass), and China (Bayan The Mount Weld process chain place in three countries (Australia, Malaysia, Abstract energy such as The rare Mountain earth minerals [3-5]. We production in Obo Australia, Malaysia (Mount Weld),InUSA China). Pass process takestherefore place inanalyse the USArare andearth China. All Bayan processes take place in China. our (Mountain Pass), and China (Bayan Obo). The Mount Weld process chain takes place in three countries (Australia, Malaysia, social lifeheating cycle assessment we use addressed the five major social impactascategories (labour & decent work,for health & safety, District networks (sLCA), are commonly in the literature one of the mostrights effective solutions decreasing the China). The Mountain Passfrom process takes place in the USA andsuggested China. All Bayan Obo processes take placetointhem China. In our human rights, governance, community & infrastructure) [6,systems 7] by UNEP/SETAC [8] and assign 21 the social greenhouse gas emissions the building sector. These require high investments which are returned through heat social cycle use the five major social impact (labour rights & decent safety, indicators of the 2012changed Social(sLCA), Hotspots Database [6]and to cover every socialcategories theme in our sLCA. sales.life Due to assessment the climateweconditions building renovation policies, heat demand in the work, futurehealth could&decrease, human rights, community infrastructure) 7] suggested byproduction UNEP/SETAC [8]the andthree assign themproduction 21 social Using the sLCA model, wereturn estimate the& social footprint [6, function for every step of raretoearth prolonging thegovernance, investment period. indicators ofscope theon2012 Social Database [6] to cover every social theme in our sLCA. chains. Based presented footprint functions, the total social footprint of the temperature three rare earth production is The main ofthethis paperHotspots is social to assess the feasibility of using the heat demand – outdoor function for heat sites demand Using the for sLCA model, estimate the development social footprint function every of The the the three rareis earth production estimated year 2015 based on located the of(Portugal), the Humanfor Development (HDI). For Mountain Pass process, forecast. Thethedistrict ofwe Alvalade, in Lisbon was usedproduction as aIndex case step study. district consisted of 665 chains. Based on thevery social footprint the taking total footprint of the three raresignificantly earth production is our analysis reveals lowconstruction social risks for thefunctions, process parts place in the United States and social buildings that vary inpresented both period and typology. Threesocial weather scenarios (low, medium, high) andhigher threesites district estimated forscenarios theThe yearAustralian 2015 on the(shallow, development of thecause Human Development (HDI). For the Mountain process, risks in China. processes of Mount Weld also a very smallIndex social footprint, whereas the Pass processes in renovation were based developed intermediate, deep). To estimate the error, obtained heat demand values were our analysis reveals very low social risks for the social process parts taking theand United States significantly higher social Malaysia and China cause a asignificantly higher footprint. The place BayaninObo processes have a considerably higher social compared with results from dynamic heat demand model, previously developed validated byand the authors. risks in China. The Australian processes of Mount Weld cause also a very small social footprint, whereas the in footprint than the other two process chains. The results showed that when only weather change is considered, the margin of error could be acceptable for someprocesses applications Malaysia China cause a significantly higher footprint. Bayanconsidered). Obo processes have a after considerably higher social (the errorand in annual demand was lower than 20%social for all weatherThe scenarios However, introducing renovation footprint than the other two increased process chains. ©scenarios, 2017 The Authors. Published by Elsevier Ltd. (depending on the weather and renovation scenarios combination considered). the error value up to 59.5% Peer-review under responsibility the scientific committee of the Summit Applied Energy The value of slope coefficient of increased on average within the World range Engineers of 3.8% up to 8%– per decade, that Symposium corresponds&to the © 2017 2017 The The Authors. Published by Ltd. © Published by Elsevier Elsevier Ltd. Forum: Low Carbon Cities Urban Energy Joint Conference. decrease inAuthors. the number of&heating hours of 22-139h duringofthe season (depending combination Peer-review under responsibility of the scientific committee the heating 9th International Conferenceononthe Applied Energy.of weather and Peer-review responsibility of the of theintercept World Engineers – Applied renovation under scenarios considered). On scientific the other committee hand, function increasedSummit for 7.8-12.7% perEnergy decadeSymposium (depending & on the Forum: Carbon Cities & Social Urban Energy Joint Conference. Keywords: Rare Earth Elements, LCA, Marginal Footprint coupledLow scenarios). The values suggested couldSocial be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations. Keywords: Rare Earth Elements, Social LCA, Marginal Social Footprint
© 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Keywords: Heat demand; Forecast; Climate change
Peer-review under responsibility of the scientific committee of the World Engineers Summit – Applied Energy Symposium &
1876-6102 © 2017 The Cities Authors. by Elsevier Forum: Low Carbon & Published Urban Energy JointLtd. Conference.
Peer-review under responsibility of the scientific committee of the World Engineers Summit – Applied Energy Symposium & Forum: Low Carbon Cities & Urban Energy Joint Conference. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of the 9th International Conference on Applied Energy . 10.1016/j.egypro.2017.12.157
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1.1. Habitat III and the meaning of renewables for urban development Urban lifestyles offer attractive options, but the highly aggregated nature of a city often leads to higher resource intensity, and the concentration of consumption and waste production poses additional challenges for sustainable city design [1, 9]. Sustainable and nexus-oriented resource management requires a major transformation of existing systems to achieve resilient and ecological functioning of urban systems. The energy sector is at the centre of this technological transition process [10], because renewable energy technologies are seen as instruments for success in this transformation process [4]. The UN Habitat III Conference 2016 also supports the International Energy Agency (IEA) in demanding renewable energy for urban systems [9, 11]. The UN identified urban areas as “the greatest drivers … fostering energy efficiency [and] renewable energy [for ] the urban economy [9].” Renewables, such as solar cells or wind turbines, are techniques for sustainable energy development. However, these renewable energy technologies need non-renewable mineral resources and especially rare earth minerals [4, 12, 13]. Rare earth elements (REEs) are used in nearly every renewable energy technology, in solar panels, fuel cells, batteries, wind power magnets, energy-saving lighting and automotive catalysts [13-15]. In the following we will analyse what social impact such a strategy may have by simultaneously considering that “investment in renewable energies could generate more employment and income for urban households [9].” 1.2. Introduction to social life cycle assessment (sLCA) and its social foundation framework Social life cycle assessment is an important analysis tool for revealing the social effects of current production and consumption patterns [16]. We used the UNEP/SETAC Guidelines [1] and the Social Hotspots Database (SHDB) developed by the NGO New Earth [3] and distributed by GreenDelta [2] for our sLCA. The Social Hotspots Database (SHDB) of 2013 [17] is based on the Global Trade Analysis Project (GTAP) of 2004 and was published in 2008. * The SHDB contains social quantitative and qualitative information from the years 2010-2012, which is weighted according to social risk (low, medium, high, and very high) for 227 countries and 57 sectors.† The SHDB enabled us to assign social risk points (social footprint) to every single production step in rare-earth-based magnet production [6, 18]. The social footprint determines the effects of production and consumption patterns on the social capital of society: the social foundation of society. We divided the social foundation of society into five main categories [17] according to the SHDB: labour rights & decent work, health & safety, human rights, governance, community & infrastructure [6, 7] and assigned to them 21 social indicators to cover every social dimension with at least one indicator in our sLCA (Fig.1). These indicators describe and characterise the social foundation of society. The social foundation framework combines “the concept of planetary boundaries with the complementary concept of social boundaries [19]” and thereby defines “a framework for defining the safe and just operating space for humanity that integrates social wellbeing into the original planetary boundaries concept [20].” We describe the labour rights and a decent life with eight indicators which include the need for adequate labour laws and the right to strike as essential labour rights. We describe health and safety with the indicators: risk of fatality from disease due to occupation and risk of loss of life (death by exposure to carcinogens). The human rights categories as the central element of every society cover the rights of the indigenous population, gender equity, human health issues and the Heidelberg barometer. The governance system is described by two indicators: fragility in the legal system of civil, common and religious laws which “provides information on the extent to which an independent judiciary exists [17]“ and the risk of corruption, which “generates economic distortions in the public sector [17]“ and undermines the trust in public institutions, or as Rogow and Lasswell put it: “A corrupt act violates responsibility toward at least one system of public or civic order and is in fact incompatible with (destructive of) any such system. A system of public or civic order exalts common interest over special interest; violations of the common interest for special advantage are corrupt [21]“. The state of the community and of the infrastructure is
* †
https://www.gtap.agecon.purdue.edu/databases/ GreenDelta, Social Hot Spots Database in openLCA, Quick explanation
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described by five indicators: too few hospital beds, the quality of drinking water and sanitation, the conditions for smallholders, and whether children go to school.
Fig. 1: Social foundation
We assigned the indicators of figure 1 also to the three dimensions of the Human Development Index (HDI) [22] to enable a scenario calculation for 2015 of the social footprint based on the SHDB of 2012. Six indicators (9, 10, 14, 17, 18, 20) can be assigned to the first dimension ‘a long and healthy life’, one indicator ‘children out of school’ belong to the second dimension of the HDI ‘education index’ and 14 indicators (1-8, 11, 12, 13, 15, 16, 21) describe the third dimension ‘a decent standard of living’. The selected SHDB and HDI indicators describe the social foundation of society. As a summary, we can say that the ecological footprint registers the effect of production and consumption patterns on the ecological capital and the social footprint determines the effects on the social capital of society, which we define as the social foundation of any society. The social LCA converts the social footprint into social risk points, in the same way the ecological footprint converts the lifestyle of a person into the space which is necessary to provide the resources used. 1.3. The example of magnet production based on rare earth elements We analyse rare earth production in Australia, Malaysia (Mount Weld), USA (Mountain Pass), and China (Bayan Obo). The physical interrelations (e.g. materials, energy demand, emissions, waste) are analysed by an LCA to capture the different process chains: mining, beneficiation, separation, metal and magnet production, which build the system boundaries of our analysis. In the case of Mount Weld, mining and beneficiation (crushing, grinding, magnetic separation, flotation) takes place in Australia, separation in Malaysia, electrolysis and magnet production in China. The mining, beneficiation, and separation of the Mountain Pass processes take place in the USA and electrolysis and magnet production again in China. In Bayan Obo, all the processes take place in China. The functional unit is the central principle of LCA, which provides a reference for all in- and outputs and enables the comparability of the LCA results [16]. The functional unit of our analysis is per kg permanent magnet produced. The functional unit captures the technical functionality of the analysed product and enables us to compare the social risks associated with producing permanent magnet in Australia, China and USA. Hence, the functional unit represents the technical functionality of the product.
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1.4. Results In the following, we present the results of our social footprint model based on the SHDB. 1.4.1. Mountain Pass (MP) The analysis of the Mountain Pass process chain reveals, as shown in figure 2, the development of the mining, processing, separation, electrolysis and magnet social footprint function subject to the chosen indicators.
Fig. 2: Mountain pass social footprint
Fig. 3: Mount Weld social footprint
The figure reveals that the social footprints of the Mountain Pass processes taking place in the USA (Mining, processing, separation) are very low. The footprint significantly increases for the processes (electrolysis, magnet production) taking place in China. 1.4.2. Mount Weld (MW) For the Mount Weld process chain the main production steps are presented in figure 3. The figure reveals that the social footprint constantly increases with every new social indicator. The social footprint of mining is nearly as low as that of Mountain Pass. The processing footprint is more or less equal to those of Mountain Pass, whereas the social footprint of the processes taking place in Malaysia are clearly higher. The total social footprint of the Chinese electrolysis and magnet production is nearly the same as that of Mountain Pass. 1.4.3. Bayan Obo (BO) Figure 4 reveals the significantly higher social footprints in nearly every production step of the Chinese process chain. Only the social mining costs in China are in the same order as those of the two production sites. The magnet process results are the same because in all three production chains magnet production takes place in China.
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Fig. 4: Bayan obo social footprint 1.4.4. Scenario 2015 Based on the presented social footprint functions, the total social footprint of the three rare earth production sites – Mount Weld (Australia), Mountain Pass (USA), Bayan Obo (China) – is estimated for the year 2015, because the most recent data of the SHDB are from 2012. The 2015 scenario is built on the latest data of the HDI of 2015 [22]. The HDI is considered as a reference for deriving the possible social development in the analysed countries. If the social situation of the country improves it is assumed that the value of the HDI increases and the social footprint decreases. If, on the other hand, the social situation of the country gets worse, the HDI of that country decreases and the social footprint increases. Hence, it is assumed that a correlation exists between the development of the HDI and the social situation of the country measured by the social footprint. Table 1: Human Development Index (HDI) between 2012 and 2015
Development of the Human Development Index Australia (Mount Weld)
China (Bayan Obo)
USA (Mountain Pass)
0.713 0.723 0.734 0.738
0.915 0.916 0.918 0.920
2012 0.933 2013 0.936 2014 0.937 2015 0.939 Source: Authors, 2017 based on UNDP, 2016
Table 1 shows that the social situation of all three countries improved between 2012 and 2015 because the HDI increased. The highest increase occurred in China followed by Australia and the USA. The development of the HDI enables us to draw conclusions about the changes of the social situation in the three countries, which allows us to estimate the development of the social footprint beyond the year 2012 of the SHDB. Therefore, using the already estimated social footprint functions and the marginal social footprint function of the three production sites, the marginal and total social risks per kg permanent magnet of the three production sites are estimated for 2015. Based on our sLCA model, we obtain three social footprint equations: 1. For the Bayan Obo (BO) production chain we identify the following social footprint equation:
2015
2
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BOTotal risk HDI 2012 7.0614 x 530.26 x 227.32 7740, R = 0.9877, x=social indicators The function shows that the total social risk per kg permanent magnet produced in Bayan Obo for 2015 is 7740 social risk points. The marginal social footprint for Bayan Obo is represented by the following equation: BO 2015 HDI 2012 2 7.0614 x 530.26 212 x The marginal social footprint for Bayan Obo is thus 212 social risk points. For the Australian-Malaysian production chain of Mount Weld, we obtain the following social footprint function:
2.
2015
2
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MWL HDI 2012 5.0675 x 385.25 x 94.88 5890, R 0.9887 The equation shows that the social risk is, with 5890 risk points, significantly lower than that of the Bayan Obo process chain. We also obtained a lower marginal footprint for the Mount Weld production site: MWL 2015 HDI 2012 2 5.0675 x 385.25 161.2 x For Mountain Pass (USA), we obtain the following equations:
3.
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MPM HDI 2012 4.1283 x 313.07 x 143.47 4720, R 0.9886 . It is thus the lowest total social risk per kg permanent magnet of the three production sites. The marginal social footprint is also the lowest of the three production chains: MPM 2015 HDI 2012 2 4.1283 x 313.07 131.1 x The scenario shows that the Mountain Pass process chain causes the lowest marginal social costs (131.1 social risk points (132 in 2012)) in 2015 and the lowest total social costs (4720 risk points (4745 (2012)) per kg permanent magnet produced, followed by the marginal social risks of the Mount Weld process chain (161.2 social risk points (162, 2012)) and the total social risks (5890 social risk points, 5927 (2012)).). Bayan Obo has the highest social risks but the decrease in social footprint from 2012-2015 is also estimated to be the largest there. The marginal social costs decrease from 220 to 212 social risk points and the total social cost is reduced from 8020 to 7740 per kg permanent magnet produced.
1.5. Summary On the basis of the SHDB, our SLCA model allows us to determine the social footprint of the production of rare earth elements for rare-earth permanent magnets for 2012. Our model further enables to also assess the future development of the social conditions for producing permanent magnets derived from the development of the Human development index using the sLCA scenarios. The analysis shows that the three rare earth production sites in the four countries generate social risks by producing rare earth elements for the permanent magnets used in wind turbines. The fabrication of rare earth technical parts for the renewable energy system, which is regarded by both the German government and the UN Habitat Conference as a solution for the current unsustainable energy system, is not free from social risks. These social risks arise because of the general fabrication conditions of the industrial sectors producing these parts. To enable people to live within a safe and just space, the political and economic institutions have to develop strategies to reduce these risks and protect the environment by avoiding CO2 and other emissions and not simultaneously endangering the social foundation of society. 1.6. References [1] UN-HABITAT. State of the world's cities 2012/2013. Prosperity of cities. Nairobi: United Nations Human Settlements Programme (UN-HABITAT); 2012. [2] UN Habitat. 2015 Global City Report2016. [3] Roelich K, Dawson DA, Purnell P, Knoeri C, Revell R, Busch J, et al. Assessing the dynamic material criticality of infrastructure transitions: A case of low carbon electricity. Applied Energy. 2014;123:378-86. [4] Campbell W. Rare Earth Minerals: The new non-renewables. Nature blog: Nature; 2014. [5] U.S. DEPARTMENT OF ENERGY. CRITICAL MATERIALS STRATEGY. Washington: DOE; 2011. [6] Norris C, Norris G, Aulisio D. Efficient Assessment of Social Hotspots in the Supply Chains of 100 Product Categories Using the Social Hotspots Database. Sustainability. 2014;6:6973-84. [7] Benoit-Norris C, Cavan DA, Norris G. Identifying Social Impacts in Product Supply Chains:Overview and Application of the Social Hotspot Database. Sustainability. 2012;4:1946-65. [8] UNEP/SETAC (Society of Environmental Toxicology and Chemistry). Guidelines for social life cycle assessment of products. Nairobi: UNEP; 2009. [9] Habitat III (United Nations Conference on Housing and Sustainable Urban Development). Quito Declaration of the Habitat III. Quito: United Nations; 2016. [10] Rifkin J. The third industrial revolution: How the internet, green electricity, and 3-D printing are ushering in a sustainable era of distributed capitalism. World Financial Review. 2012;2012:8-12. [11] IEA. World Energy Outlook 2008. Paris: IEA; 2008. [12] Smith Stegen K. Heavy rare earths, permanent magnets, and renewable energies: An imminent crisis. Energy Policy. 2015;79:1-8. [13] American Physical Society (APS), Materials Research Society (MRS). Energy Critical Elements. Washington:
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Materials Research Society,; 2011. [14] Hoggett R, Bolton R, Candelise C, Kern F, Mitchell C, Yan J. Supply chains and energy security in a low carbon transition. Applied Energy. 2014;123:292-5. [15] Arent D, Pless J, Mai T, Wiser R, Hand M, Baldwin S, et al. Implications of high renewable electricity penetration in the U.S. for water use, greenhouse gas emissions, land-use, and materials supply. Applied Energy. 2014;123:368-77. [16] van Haaster B, Ciroth A, Fontes J, Wood R, Ramirez A. Development of a methodological framework for social life-cycle assessment of novel technologies. Int J Life Cycle Assess. 2017;22:423-40. [17] Norris CB, Norris GA, Cavan DA. Social hotspot database. Supporting documentation update: 2013. York Beach, Maine: New Earth; 2013. [18] New Earth/ Social Hotspots Database project. Social hotspot database web portal. Introductory User Tutorial. York Beach, Maine, 03910, United States of America: New Earth; 2014. [19] Raworth K. A safe and just space for humanity. Can we live within the doughnut? Oxfam Discussion Papers. 2012;2012. [20] Dearing JA, Wang R, Zhang K, Dyke JG, Haberl H, Hossain MS, et al. Safe and just operating spaces for regional social-ecological systems. Global Environmental Change. 2014;28:227-38. [21] Rogow AA, Lasswell HD. Power Corruption and Rectitude. Englewood Cliffs, New Jersey: Prentice-Hall; 1963. [22] United Nations Development Programme (UNDP). Human Development Report 2016. New York: UNDP; 2016.