17.1 Guidelines for Social Life Cycle Assessment
Managing social issues requires the implementation of specific evaluation tools. Life cycle methodologies have gained great consensus among academics and practitioners for the assessment of the impacts of the whole life cycle of a product or service. Among them, social life cycle assessment (s-LCA) is the latest methodology developed, specifically devoted to the evaluation of potential positive and negative social impacts of a product or service, taking into account all activities that are related to the extraction and processing of raw materials, manufacturing, distribution, use, maintenance, recycling and final disposal. The life cycle approach can prevent the shifting of burdens between geographical areas, supply chain steps or life cycle phases when evaluating impacts, as well as highlighting possible hotspots.
S-LCA methodology is similar to the environmental LCA methodology, as both methods are based on the ISO 14040 framework. However, while the procedures of goal and scope definition, inventory analysis, impact assessment and interpretation are common, s-LCA differs in the data that is collected. S-LCA highlights the social consequences of the activities and assesses their organisational and societal context in the supply chain.
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Social impacts are considered as the effects on the different typologies of stakeholders involved, such as workers, local communities, value chain actors, consumers, societies and children [1]. S-LCA seeks to improve the product’s supply chain by providing information on social aspects for decision-makers. Its specific objective is to assess social impacts in the same way environmental LCA does it for environmental ones. But, while LCA is regulated by specific ISO standards (14040-44:2021, in the updated version), about s-LCA there is not still a standardised methodology, and the most diverse methodologies have been proposed in the literature. The s-LCA guidelines from UNEP [1] are based on social and socio-economic impact categories (e.g. human rights, working conditions, health and safety, etc.) with 40 subcategories and five stakeholder groups (society, worker, consumer, value chain actors and local community) and on context-dependent inventory indicators. The UNEP guidelines do not provide an agreed and standardised framework for social indicators that reflect and measure the social impacts of technologies and processes along product life cycles and supply chains. However, they represent the present landmark in the field.
Presently, a specific ISO standard, the 14075 ‘Principles and framework for social life cycle assessment’, is under development (in the preparatory phase), and recently UNEP (2020) updated the Guidelines for s-LCA and the Methodological Sheets for subcategories in s-LCA [2], providing a methodological overview for practitioners about possible evaluation procedures. According to them, there are two main impact assessment approaches, and each of them responds to different practical research aims: the reference scale approach (type I) and the impact pathway approach (type II). The Methodological Sheets provide a list of possible stakeholder groups to be considered in the evaluation processes, namely, workers, local communities, value chain actors, consumers, society and children; for each of them, subcategories of assessment are suggested (40 in total).
17.1.1 The Reference Scale Approach
Type I s-LCA assesses the social performance or risks of companies or organisations involved in the product system, by comparing their behaviour to a reference scenario (e.g. specific legal regulations or norms). The comparison is made according to specific primary or secondary data and information or stakeholders’ opinions, and therefore the evaluation consists in the description of a current status (in the short term) and not in the accounting of the links between the activity and long-term impacts. Therefore, the characterisation process is mainly based on interpretation. Results are expressed in performance reference points (PRPs), which are ‘thresholds, targets, or objectives that set different levels of social performance or social risk’ [1]. PRPs consent estimating the magnitude and significance of potential social impacts associated with organisations in the product system, but they are context-dependent, often based on international standards, local legislation or industry best practices and, therefore, not generalisable.
Type I s-LCA methodology suffers many issues because it comprises a multiplicity of qualitative approaches in terms of data collected and their significance, the use of the functional unit (FU) to scale inventory input is very often optional and the characterisation step consists in an implicit or explicit value judgement on the collected data [3, 4]. Furthermore, studies framed within this typology often disregard the main typical elements of life cycle studies such as the system boundaries, the time boundaries, the cutoff criteria and the evaluation of each single life cycle phases. They provide a qualitative assessment of the social performance of behaviours and activities linked to a product or service system [5], by means of value judgements made on collected data and result characterisation made with different relative weights [3, 4]. The most used characterisation methods applied within type I s-LCA found in literature are based on comparisons to norms and best practices, socio-economic contexts, stakeholders’ judgements on companies’ compliance, experts’ evaluations or comparison of alternatives [5]. Moreover, weighting is mainly conducted to give a relative importance judgement to specific categories of impact or stakeholder group, sometimes by means of multicriteria methods or other participative approaches.
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Some specific databases are available for type I s-LCA, such as PSILCA (Product Social Impact Life Cycle Assessment), which provides information on social aspects of products over their life cycles, for almost 15,000 industry sectors and commodities and for 69 qualitative and quantitative indicators, considering global supply chains and services, and to detect social hotspots. Similarly, the Social Hotspots Database (SHDB) consists of a multiregional economic input-output data which provides local and global supply chains and links these to a broad range of social metrics aligned per sector and per country. It is a tool to help companies and organisations to manage their social responsibility; it enables quick identification and prioritisation of social risks in supply chains through data classified by country and sector, as well as a methodology for quantifying social impact. They are effective to identify social impacts at the country level but only by means of aggregated data showing averages across different technologies and geographical areas; therefore, these databases are of limited value in distinguishing between alternative operations and locations for products and services [6].
17.1.2 The Impact Pathway Approach
Type II s-LCA is aimed at predicting the consequences of the product system, and it evaluates actual or potential social impacts through causal or correlation/regression-based relationships (the impact pathways) between the product or service life cycle and social impacts in the short or long term. The characterisation process is based on an analytical and quantifiable identification of the consequences of the life cycle.
According to [7] and [1], type II s-LCA is epistemologically and methodologically in line with environmental LCA, where inventory inputs are quantitatively linked with environmental impacts. To harmonise all the life cycle approaches (life cycle assessment and life cycle costing), a type II s-LCA methodology could be more suitable, because it allows:
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an objective assessment of potential impacts aligned with ISO norms 14040-44:2021.
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Connecting quantitatively inventory input to possible impacts.
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A rational use of elements such as the functional unit, the setting of system boundaries and the rational choice of cutoff criteria, which are often blurred and confused in type I s-LCA approaches.
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Generalising the insights to similar productive sectors.
Many methods have been proposed within this group. [8] reviewed 28 studies and highlighted three main paths to include impact pathways in s-LCA:
(i)
applying more variables composing impact pathways, or frameworks gathering several pathways.
(ii)
Using and testing already existing pathways empirically (mainly linking income data with health impacts at a macroscale).
(iii)
Applying known and already quantified characterisation models or factors from other research works to case studies.
Examples of impact pathways can be found in the work [9], which proposed the Preston pathway to assess the social impacts of banana industry in terms of relations between the increased economic activity and the growth in income, which leads to improvements in the health of a country’s population.
[10] proposed the Wilkinson pathway to assess the anticipated change in the infant mortality rate caused by a change in income distribution in the population of a country, itself generated by an important change in a life cycle.
Recently, the psychosocial risk factor (PRF) impact pathway [11] has been proposed to assess the social impacts of a product life cycle by quantifying the risk of psychosocial impacts on different typologies of stakeholders, according to the duration of exposure to certain living and working conditions that can lead to health issues. According to the definition by [12], PRFs are the aspects and characteristics of work planning and management that can potentially lead to physical or psychological damage. The psychosocial risks are measured in odds ratios (ORs), a statistical measure of the intensity of association between two variables, e.g. as the ratio between the odds of exposure for people with a disease and the odds of exposure for healthy people [13]. Measuring the psychosocial risks with the ORs is a retrospective analysis of a phenomenon, expressed with a nondimensional value, and it can assume values between 0 and + ∞. A value of 1 indicates that there is no association between disease and exposure, while values >1 indicate a positive association (the risk factor can provoke the disease/disorder); higher values show a stronger association between exposure and disease [14].
Data are retrieved from previous scientific studies that analysed the relationships between specific living and working conditions and diseases (or disorders), for example, the association between low income and myocardial infarction (OR: 3.53) and stroke (OR: 3.73) [15] or long working hours and metabolic syndrome (OR: 1.66) [16].
All possible stakeholder groups can be potentially covered: workers (from entrepreneurs to labourers), consumers, local communities’ members, citizens, value chain actors and children.
Operatively, s-LCA is divided into four steps, the same as indicated in the ISO norms 14040-44 [17, 18]:
1.
Goal and scope: definition of the system boundaries, categories of impact, functional unit, cutoff criteria, foreground and background processes, taking into account all possible phases of the system under study.
2.
Inventory analysis: data collection can be conducted both using primary sources (surveys, interviews, participatory approaches) and secondary sources (scientific and grey literature). All required data should be properly allocated to their life cycle phases (e.g. planning, manufacturing, transport, use and disposal).
3.
Impact assessment: it consists in choosing the most appropriate impact assessment method, according to the objective of the study. Qualitative and quantitative methods are available. As mentioned in the previous paragraphs, it is possible to pay attention to the companies’ behaviour as well as to the functioning of the product’ or service’s life cycle.
4.
Interpretation of results obtained, retrieving insights useful for stakeholders (private or public ones), practitioners and academics.
This methodological diversity in s-LCA studies is due to the specific characteristics of social sciences, which are multiparadigmatic, and many worldviews can be held: indeed, many scientific methods are available for the assessment of social phenomena, such as quantitative, qualitative and mixed methods [7]. Therefore, up to now, both interpretivist and post-positivist epistemological positions have been applied in the s-LCA scientific literature [7]. Most of the studies published have been evaluating in a qualitative or normative way a wide range of impact categories mostly linked to companies’ behaviour (e.g. child labour, corruption, fair wages, safety, etc.), rather than to the life cycle functioning; few studies can be found in literature quantifying cause-effect relationships between life cycle functioning and areas of protection (AoP) in an objective and generalisable way [7].
Further efforts should be made on standardisation possibilities and the alignment to other life cycle methodologies, and testing of methods is necessary to overcome present obstacles and increase the applicability and interpretability results [19].
17.2 Experiences in the s-LCA of Batteries
While literature is rich of studies focused on the environmental impacts of battery production, the social aspects have been little investigated or are limited to social acceptance.
Indicators for s-LCA are often based on qualitative information rather than quantitative, given the nature of the social aspects under assessment. No standardised set of social indicators exists; thus, the choice of social indicators in s-LCA is challenging and possibly subjected to bias.
The typology of s-LCA methodology (type I or type II) strongly influences the typology of data to be collected, as well as the results to be obtained. In the case of type I, site-specific data should be collected, and the social impacts retrieved would be mainly linked to the company’s conduct in a specific geographic and sociocultural context. In the case of type II, both primary and secondary data can be collected, and social impacts are quantifiable and directly linked to the life cycle processes.
Identifying the social impacts of battery supply chain must necessarily include all life cycle phases, such as the extraction and processing of raw materials, the production of intermediates, the production of battery cells, the assembly of the battery pack as final product and the disposal or recycling. Raw materials come from different mining sites, often concentrated in few countries. For example, cobalt is mainly extracted in Congo (about 60%), followed by Russia and Australia, from where lithium predominantly comes from. China is the largest producer of aluminium and graphite but also copper and manganese.
To review the specific literature on the topic, a search on the principal scientific research engine (e.g. Scopus, Web of Science) has been made using the keywords ‘social life cycle assessment’ or ‘SLCA’ and ‘batteries’. Eight contributions have been found (Table 17.1), mostly published since 2019. Only three of them are focused specifically and solely on the assessment of social impacts [20‐22], while all the other papers make a multidimensional assessment, taking into account more sustainability dimensions, and therefore combining more methods, in some cases by means of multicriteria decision-making (MCDM) methods [23‐26]. Among the studies reviewed, three analyse specifically the production sustainability of batteries [21, 23, 24], three are focused on the production of battery electric vehicles (BEV) [20, 25, 26] and two are devoted to the assessment of the mining phase [22, 27]. Indeed, it is widely shared among reviewed papers that significant risks originate from raw material extraction [21, 22, 27].
Table 17.1
Review of social life cycle assessment of batteries
Author | Field of application | Objectives | Methods | Social categories or indicators | Involved actors | Affected stakeholders | Main results |
|---|---|---|---|---|---|---|---|
Egbue [20] | Electric vehicle (EV) Li-ion batteries | To assess the social and socio-economic impacts along some parts of the lithium life cycle, in particular extraction and production impacts | s-LCA | Not available | Not available | Society, workers, local communities | Understanding and tracking impacts of lithium for EV batteries over some of its life cycle processes. s-LCA can be used by engineering managers to improve social and socio-economic conditions of production and consumption of lithium |
Sansa et al. [23] | Batteries | Proposing a new model for the selection of sustainable design options, able to deal with the uncertainties and the imprecisions due to the technological choices and their potential impacts since early design phase of the product | Environmental LCA (ELCA), economic LCA (EcLCA), s-LCA and the fuzzy analytic network process | Experts, involved to confirm results | Employees, consumers, managers, governors | The design option PDO1 (lithium iron phosphate, 2 volts, durability of 1000–2000 cycles and specific energy of 90–120 Wh/kg) is considered the most suitable for the design of the product since it generates the minimum impacts through all the life cycle phases | |
Guo [24] | Lead-acid battery, Li-ion battery, Nas battery and NiMH battery | Developing a life cycle sustainability decision-making framework for the prioritisation of electrochemical energy storage under uncertainties by combining MCDM method and life cycle sustainability assessment | LCA, LCC, s-LCA and two MCDM methods: Bayesian best-worst method (BWM) and fuzzy TOPSIS (technique of order preference similarity to the ideal solution) | Social acceptance, electric power system reserve capacity reduction | Five top-tier experts of energy storage including three professors and two practitioners, involved in the weighting process | Society | Result indicates the Li-ion battery has the best life cycle sustainability performances according to eight sustainability criteria from four pillars: economy, environment, society and technology |
Thies et al. [21] | Lithium-ion batteries | Assessing the social sustainability hotspots of lithium-ion batteries with a spatially differentiated resource flow model of the supply chain. Comparing three supply chain configurations | s-LCA: Social Hotspots Database in openLCA | Child labour, corruption, occupational toxics and hazards, poverty | Not available | Children, workers, society | The Germany-focused production entails much lower risks in the cell production and pack assembly stage compared to the China-focused production. The results confirm that significant risks originate from the production of raw materials, with graphite production, cobalt sulphate production and nickel sulphate production being the main contributors based on actual production shares |
Wang et al. [25] | BEVs | To assess the life cycle sustainability of BEVs in China, and the results obtained by comparison with internal combustion engine vehicles (ICEVs) will be used to analyse the developmental advantages and problems of BEVs | LCA, LCC, s-LCA, TOPSIS | Freedom of association and collective bargaining, child labour, fair salary, forced labour, equal opportunities/discrimination, health and safety for workers and consumers, feedback mechanism, access to material resources, local employment, contribution to economic development, technology development, policy and subsidy | Questionnaires and on-site interviews with stakeholders in the three phases of manufacturing, operation and recycling of the vehicles for data gathering | Workers, consumers, local community, society, government | A comparison of BEVs and ICEVs. The study found that the life cycle sustainability of ICEVs in China was better than that of BEVs |
Wilken et al. [26] | Electric vehicles and internal combustion engine vehicles | Presenting a novel approach to analyse ICEV-, BEV- and FCEV-type (fuel cell electric vehicle) passenger cars on a multidimensional basis | LCA, LCC, PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) | The social assessment was realised through the application of specific weighting scenarios as part of the MCDM process | To exclude bias and keep the assessment feasible, neither stakeholder representatives nor ‘experts’ were involved in this study | Car owners or users | The weights and preference thresholds only marginally affect the rankings: the BEV alternatives based on renewable electricity (i.e. BEV_wind/PV) share the upper ranks with the conventional vehicles (i.e. ICEV_diesel/gas) in the majority of scenario combinations, whereas BEV_EU-mix and all of the FCEV alternatives are mostly ranked lower |
Mancini et al. [27] | Responsible sourcing initiatives for cobalt | Comparing the situation of two pilot projects about the general situation at cobalt small-scale mining sites in Congo (DRC). Providing the basis to discuss the lessons learned for the assessment and monitoring of responsible sourcing programmes and of due diligence schemes and possible implications for policy | OECD Guidance, CCCMC (China Chamber of Commerce of Metals, Minerals and Chemicals Importers and Exporters) guidance, IFC (International Finance Corporation) Performance Standards, s-LCA | Local community: health and safety, local employment and economy, social benefits/losses, cultural heritage and land rights, discrimination, forced migration/resettlement and land rights and poverty Workers: health and social well-being, wages, social benefits, working conditions, discrimination, freedom of association and collective bargaining, training and education, job satisfaction and engagement | Interviews to miners, miners’ representatives, pilot initiative implementers, ex-child workers for data gathering | Local communities, workers | Results show that the systems analysed are rather effective in implementing the changes that they are designed to make, especially in the case of life-threatening working conditions, child labour and corruption. However, the risk categories addressed by these projects are dictated by downstream expectations and do not necessarily correspond to the demands of the miners they are designed to protect. For instance, price calculation and income as well as gender considerations are particularly salient aspects and are not captured by responsible sourcing programmes but are part of the s-LCA framework |
Muller et al. [22] | Flexible and modular mining plant (MMP) | The goal of this study is to assess the social implications of a new mining paradigm, small-scale ‘switch-on switch-off’ (SOSO) mining, which is based on the design of a flexible and modular mining plant (MMP) and aims at exploiting quickly and safely European small high-grade deposits of raw materials, including critical | s-LCA (PSILCA v2.0 database) | Society: contribution to economic development, value chain actors, corruption, fair competition and promoting social responsibility Local community: access to raw material resources, safe and healthy living conditions, local employment and migration, respect of indigenous rights Workers: health and safety, fair salary, social benefits, working time, child labour and freedom of association | Interviews with members of the project in charge of the MMP development, deployment and operations | Society, local communities, workers, children | Switching the electricity supply system increases the overall risk due to the increase in potential impacts occurring on the renewable energy supply chain (e.g. battery manufacturing). When switching the country of operation to Greece, the overall potential impacts are predicted to decrease |
All the studies reviewed had the goal of proposing an assessment framework able to address decision-making towards more sustainable solutions, since early phases of the product or project. The most recurring impact category concerns workers’ conditions, especially in terms of health and safety, freedom of collective bargaining, fair wages and child labour. Of studies, 50% also take into consideration local communities and 62% also the whole society. Lithium-ion battery production is the most assessed scenario.
Concerning results [23] affirmed that batteries with lithium iron phosphate, voltage of 2 V, durability of 1000–2000 cycles and specific energy of 90–120 Wh/kg can be considered the most suitable for the design of the product because of lower impacts through all the life cycle phases. [24] compared different typologies of batteries and concluded that lithium-ion battery has the best life cycle sustainability performances according to eight sustainability criteria from four pillars (economy, environment, society, technology). [21] highlighted that when the cell production and pack assembly stage is conducted in Europe (Germany, in their case study), it entails much lower risks compared to the China-focused production: they confirm that significant risks originate from the production of raw materials, with graphite production, cobalt sulphate production and nickel sulphate production being the main contributors based on actual production shares. Concerning the production of the vehicles, contrasting results are obtained in [25, 26], which both applied multicriteria decision-making methods. In the first case, comparing battery electric vehicles and internal combustion engine vehicles (ICEVs), the authors found that the life cycle sustainability of ICEVs in China was better than that of BEVs. In the second study, [26], weights and preference thresholds only marginally affected the rankings. BEV alternatives based on renewable electricity (i.e. wind or photovoltaic plants) share the upper ranks with conventional vehicles (i.e. diesel/gas) in many scenario combinations, whereas BEV with electricity from the European Union (EU) 2012 electricity mix (BEV_EU-mix) and all the fuel cell electric vehicle alternatives are mostly ranked lower.
17.3 Conclusions
Results from the literature review on the batteries or electric vehicle supply chain showed that, while the environmental impacts are mainly and regularly investigated by scholars, the social repercussions of this production process are very poorly considered or are limited to social acceptance. Probably this is due to the difficulty with the different s-LCA methodologies, not yet standardised in one unique approach, the complexity of the indicators’ choice and the obstacles to obtaining data from the specific production sector and for all life cycle phases. This is especially for raw material extraction and processing which seems to be the riskiest stage in terms of impacts but also the production of intermediates, the production of battery cells, the assembly of the battery pack as final product and the disposal or recycling. It is interesting to note that although social is little applied to the sector analysed, most existing studies prefer to conduct integrated analyses with other impact assessment methodologies, in the light of a multiperspective approach, by confirming the need to conduct analyses to assess the sustainability of production processes as holistically as possible. On the other hand, from an exclusive social point of view, the inclusion in the same investigation of impact evaluations on different types of stakeholders remains a very challenging issue; in fact, those most analysed are always the workers’ group, with the recurring impact category on work conditions (health and safety, freedom of collective bargaining, fair wages and child labour). The major conclusions that can be retrieved are about the necessity of more research to clearly define the possible social impacts of batteries, especially objective analyses that can clearly quantify the impacts deriving from the life cycle phases and that allow comparisons among different scenarios, which can be highly variegated.
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