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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/25145

Title: Identifying social indicators for sustainability assessment of CCU technologies: using a multi-criteria decision making technique
Authors: Rafiaani, Parisa
Dikopoulou, Zoumpolia
Van Dael, Miet
Kuppens, Tom
Azadi, Hossein
Lebailly, Philippe
Van Passel, Steven
Issue Date: 2017
Citation: 2nd International Conference on the Sustainable Energy and Environmental Development (SEED2017), Krakow, Poland, 14-17/11/2017
Abstract: Carbon Capture and Utilization (CCU) technologies capture CO2 waste emissions and utilize them to generate new products (e.g., fuels, chemicals and materials) with various environmental, economic and social opportunities. However, as most of these CCU technologies are in the R&D stage, their technical and economic viability are examined with very little attention to the social aspects. Besides, the lack of systematic research into social impacts is mainly due to the difficulty in identifying as well as quantifying social aspects through the entire life cycle of CCU products. The first step within social life cycle assessment (SLCA) is to identify the relevant social indicators. Within SLCA it is common to involve stakeholders in indicating which social impact categories and related indicators are most relevant to them. As there are multiple social indicators and stakeholders’ opinions, the identification step is a multi-criteria decision making issue. To address this, in this study a Multi-Criteria Decision Making Technique called TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is applied which is rarely utilized for the assessment of social performances within the biobased economy. TOPSIS is employed to empirically determine the relative importance of the indicators for measuring social impacts. To do so, first the relevant stakeholders, potential social impact categories and subcategories, and potential performance indicators are listed using UNEP/SETAC guidelines. Second, through an online questionnaire survey, CCU experts at international level provide linguistic instead of numerical ratings to the social sub-categories and their potential indicators. Afterwards, TOPSIS is used to generate aggregate scores for impact subcategories and to identify indicators of high importance. Finally, sensitivity analysis is performed to determine the influence of criteria weights on the decision making process. The final set of main social indicators resulting from our study provides the basis for the next steps in the social sustainability assessment of CCU technologies, i.e. data collection and impact assessment. Furthermore, our outcomes can be also used to inform the producers regarding the most and least important social issues for CCU technologies so that the potential social impacts caused by their production activities can be improved or prevented.
URI: http://hdl.handle.net/1942/25145
Category: C2
Type: Conference Material
Appears in Collections: Research publications

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