Over the past three decades, sustainability has grown to become a central element in the agenda of policy makers, businesses, non-governmental organizations, scientists and the civil society as a whole. However, a key issue in this movement remains unresolved: How can we truly measure the sustainability of a given product, service, or technology? Furthermore, how can we incorporate sustainability into decision making in order to ensure the coexistence of humans and nature in productive harmony?
Most authors agree with the Brundtland Report in that sustainability comprises three inter-related dimensions: environment, economy and society (Brundtland
1987). It is also widely accepted that sustainability analyses need to apply a life cycle approach, thus taking into consideration extraction and processing of raw materials, manufacturing, transport activities, utilization of the product by the final user and end-of-life actions, as described in ISO 14040 and 14044. The first systematic methodology aimed at evaluating the sustainability of products and services using a life cycle perspective dates back to 1987, and it has been attributed to the Oeko-Institut (Germany) (Kloepffer
2008; Nzila et al.
2012). This framework, originally named
Product Line Analysis (Produktlinienanalyse), was refined in subsequent public and private initiatives to become
Product Sustainability Assessment (PROSA) (Grießhammer et al.
2007). A fundamental step ahead in this field was attributed to the
Coordination Action for innovation in Life Cycle Analysis for Sustainability (CALCAS (2006–2009), a research project financed by the European Commission (Zamagni et al.
2009) that sets the principles of modern life cycle-based sustainability assessments (LCSA). This was followed by other actions aimed at improving, standardizing, testing and promoting the use of this methodology. Noteworthy among these are the EU-funded PROSUITE (2009–2013) project (Blok et al. 2013), the UNEP/SETAC life cycle initiative (UNEP/SETAC
2015), the SETAC Europe 18th LCA Case Study workshop in LCSA (Cinelli et al.
2013) and the special issues on LCSA published by the International Journal of Life Cycle Assessment (Zamagni
2012; Zamagni et al.
2013).
These publications define two alternative approaches to life cycle-based sustainability analysis:
Life Cycle Sustainability Assessment, hereafter LCSA (assessment), and
Life Cycle Sustainability Analysis, hereafter LCSA (analysis) (Sala et al.
2013; Zamagni et al.
2013). The main proponent of the former is the UNEP/SETAC Life Cycle Initiative whose report “Towards a Life Cycle Sustainability Assessment. Making informed choices on products” describes LCSA (assessment) as the summation of the results obtained from the use (under the same system boundaries) of three independent analysis tools: environmental life cycle analysis (E-LCA), life cycle costing (LCC) and social life cycle analysis (S-LCA) (Ciroth et al.
2011). The LCSA (assessment) framework has received criticisms due to its mechanistic approach and lack of flexibility, which obviates the complexity of real systems and the interdependencies that exist between the three sustainability dimensions (Zamagni et al.
2013).
The theory and practice of LCSA (analysis) are described in the various reports produced under the CALCAS project. This methodological approach involves an expansion in the scope of E-LCA with the aim of incorporating into the analysis the economic and societal dimensions of the system, as well as different analysis levels (micro, meso, macro). This has been reported to be more difficult to apply than the LCSA (assessment) approach proposed by UNEP/SETAC as it should take into consideration behavioural relations, sustainability dimensions interactions, time effects, market and demand changes, etc. In addition, LCSA (analysis) provides more flexibility in the selection of analytical tools and provides an integrated framework where the results may be evaluated in combination. In this new methodology, the life cycle inventory analysis and the life cycle impact assessment phases described in ISO 14040 are merged together into a single modelling phase where inventory data is converted into a series of sustainability indicators (Heijungs et al.
2009). Thus, LCSA (analysis) may be regarded as a trans-disciplinary integration framework of models rather than a model in itself (Guinee et al.
2010).
1.1 Life cycle-based sustainability assessment methodology
Owing to its early stage of development, there is still no clear consensus on the practical application of life cycle-based sustainability assessment. This section aims to provide a global vision on how the scientific community has been responding to key methodological issues in the practical application of this methodology. For this purpose, a literature review was carried out using the Web Of Science (WOS) search engine to evaluate the scientific output generated up until September 2015.
A literature search using the strings “Life Cycle Sustainability Assessment” and “Life Cycle Sustainability Analysis” produced 66 items (including peer-reviewed journal articles, conference proceedings and books), whose contents were revised thoroughly. Eleven of these publications were discarded for low quality (the sustainability content was too vague and limited, without quantification or use of recognized tools) or lack of relevance (the study only covered one sustainability dimension) reducing the scope to 55 items. Twenty-eight out of these 55 publications (51%) were dedicated to define methodological proposals from a theory perspective. The remaining 27 described the practical application of life cycle-based sustainability assessment through a series of case studies on specific products belonging to different sectors (primarily energy generation, construction and waste treatment). Most papers published prior to 2014 dealt with methodology development, while interest shifted towards practical application in subsequent years. A description of all these studies is available in the Electronic Supplementary Material.
Regarding the methodological framework of the case studies reviewed, most of them (48%) opted for the
LCSA (
assessment) (corresponding to LCA + LCC + S-LCA). This may be due to a more clearly defined framework of the former methodology and also the widespread acceptance of the UNEP/SETAC Guidelines (Ciroth et al.
2011). The second most widely utilized framework (15%) was hybrid LCA-input-output (IO) analysis, an integrated approach that allows using the same economic inventory to evaluate all three sustainability dimensions (Onat et al.
2014). Owing to its top-down approach, the precision of this methodology depends on the quality and disaggregation of regional and multiregional IO databases, which may not always be available and updated for the regions of interest. The
LCSA (
analysis) approach was only used in 4 of these case studies (7%), while the remaining 17 publications reviewed (30% of the total) opted for ad hoc LCSA frameworks, the most common being the
tiered approach (Neugebauer et al.
2015; Peukert et al.
2015).
1
The CALCAS project describes 28 tools suitable to assess different aspects of sustainability including E-LCA, LCC, S-LCA, IO, material flow analysis, cost benefit analysis, eco-efficiency analysis, external costs (ExternE), life cycle optimization, etc. (Schepelmann et al.
2008). In the case studies reviewed, the analysis tools most widely used by far are conventional E-LCA for the environmental dimension (in 85% of the publications evaluated), LCC for the economic dimension (in 55%) and S-LCA for the social dimension (in 26%). Sixty-three percent of the publications implemented or proposed the combined use of these three methodologies, as suggested in the UNEP/SETAC Guidelines.
E-LCA is a stablished tool already recognized by the European Commission as best framework for assessing the potential environmental impacts of products (European Commission
2003), while LCC is a mature tool, usually considered for evaluating the life cycle costs of products and services (Hunkeler et al.
2008). However, the adequacy of LCC to evaluate economic sustainability has been questioned by different experts (Jorgensen et al.
2013; Wood and Hertwich
2013) who agree that other indicators (such as value added, labour and capital productivity, or ratio of output per factor input) may provide a more realistically and society-oriented description of economic well-being (Wood and Hertwich
2013). These and other economic performance indicators, like labour costs or international commerce, may be calculated using IO methodology. In the case of the social dimension, the use of ad hoc methods to evaluate the social sustainability is common practice due mainly to the incipient state of development of S-LCA. Central to this evolution stands the UNEP-SETAC Life Cycle Initiative (UNEP-SETAC Life Cycle Initiative
2009) and its report
Guidelines for Social Life Cycle Assessment of Products. Practitioners often report the need for more research in the development and application of this methodology to improve consistency in the procedures and uniformity in the presentation of results. While 40% of the revised case studies propose the use of the UNEP-SETAC Guidelines to evaluate social performance, only 7% of them actually implement this methodology, and this is done in a simplified manner using “workers” as the only impact and stakeholder category.
In order to facilitate decision-making, the LCSA needs to be completed with a final step that involves the evaluation, integration and aggregation of results obtained for each of the three sustainability dimensions (as it is also required for E-LCA and S-LCA results). The aggregation step is currently a matter of debate. The main difficulty when aggregating the results is the quantification of the relative significance of each sustainability dimension and indicator selected (the weighting process). This problem may be addressed using multi-criteria decision making (MCDM) methods, as they are able to create tailored weighting sets to aggregate diverse indicators. Wang et al. (
2009) performed a review of MCDM methods applied to evaluate sustainability in the energy sector and reported the analytic hierarchy process (AHP) as the most popular one. However, since the weighting exercise clearly conditions the objectivity of the final results, some authors prefer to not aggregate the results, but to integrate them into a graphic layout. This may be used directly by decision makers, while keeping open (and sometimes facilitating) the possibility of applying certain weighting sets for results aggregation. The use of graphic methods to integrate results in a transparent and visual manner has been proposed and used by different authors (Finkbeiner et al.
2010; Hardi and Semple
2000; Jesinghaus
2000). Specific diagrams designed for this purpose are the Life Cycle Sustainability Dashboards and the Life Cycle Sustainability Triangle. The former is designed to display, integrate and aggregate results for each analysis dimension using a colour-coded panel and a given weighting set that allows to rank the sustainability of different alternatives (Traverso et al.
2012). The Life Cycle Sustainability Triangle is useful to discern which of two alternatives has higher sustainability on the basis of three different indicators (one for each sustainability dimension) and different weighting sets (Finkbeiner et al.
2010). Of the 27 case studies revised, 33% did not use any type of aggregation or integration method and 26% used different types of diagrams to display the results in an integrated way. Most of these diagrams compare the results of different alternatives in relative terms, setting the best and worst results for each alternative as maximum and minimum performance in each area. Only two of those studies applied the Life Cycle Sustainability Dashboard and aggregated the results considering equal weighting factors. The remaining 40% applied or proposed the use of different types of MCDM for results aggregation, being the AHP the most common (15%).
Regarding the completeness of the case studies revised, only 30% of them included the analysis of the three sustainability pillars together with the aggregation of results (using a weighting method) and the final interpretation, while the other 70% of studies were missing either the analysis on the social/economic area, and/or the final integration of results. This is an indication of the major challenge behind assessing and integrating all three sustainability areas with a life cycle perspective. More LCSA case studies are needed to facilitate the development of a sound and unified methodological framework, and show the way to future practitioners.
1.2 Goal of this study
This article responds to the needs expressed by the scientific community to test the use of life cycle-based sustainability analysis for different products and in different sectors. Due to its innovative approach and potential advances, the study has been based on the premises of the LCSA (analysis) framework, covering the three dimensions (environmental, economic and social) of sustainability. The methodology has been applied to evaluate the sustainability of HYSOL (from HYbrid SOLar), a novel type of hybrid concentrated solar power (CSP) plant designed to operate using both solar energy and auxiliary fuels. The incorporation of high capacity thermal energy storage (TES) and the use of aeroderivative turbines with thermal recovery for the integration of auxiliary fuels has been reported to improve efficiency, dispatchability and firmness in the generation of power, compared with conventional CSP. The interest of this paper lays not only on the sustainability results obtained for the HYSOL technology but primarily on the operationalization of LCSA (analysis) framework. These include definition of structural concepts (general approach, definition of objectives, analysis tools and choice indicators for each sustainability dimension, communication of results), practical issues such as the combination of different analysis levels and integration of different sustainability dimensions, and the definition of system boundaries for each sustainability dimension.