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Social Indicators Research
Erschienen in: Social Indicators Research 1/2020

06.07.2019 | Original Research

Identifying Social Indicators for Sustainability Assessment of CCU Technologies: A Modified Multi-criteria Decision Making

verfasst von: Parisa Rafiaani, Zoumpolia Dikopoulou, Miet Van Dael, Tom Kuppens, Hossein Azadi, Philippe Lebailly, Steven Van Passel

Erschienen in: Social Indicators Research | Ausgabe 1/2020

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Abstract

Carbon capture and utilization (CCU) technologies capture CO2 waste emissions and utilize them to generate new products (such as fuels, chemicals, and materials) with various environmental, economic, and social opportunities. As most of these CCU technologies are in the R&D stage, their technical and economic viability are examined with less attention to the social aspect which is an important pillar for a holistic sustainability assessment. The lack of systematic social impact research is mainly due to the difficulty of identifying and quantifying social aspects through the entire life cycle of products. We will fill this gap for CCU technologies and identify the main social indicators. A multi-criteria decision making tool: technique for order of preference by similarity to ideal solution (TOPSIS) was applied to empirically determine which indicators are more relevant for assessing the social impact of a company operating CCU activities within a European context. First, seeing that social impact categories are linked to key stakeholder groups, we considered workers, consumers, and local communities as relevant stakeholders. Second, the main social impact categories and their potential performance indicators associated to each group of stakeholders were listed using the United Nations Environment Program/Society of Environmental Toxicology and Chemistry (UNEP/SETAC) guidelines. In the third step, an online questionnaire was distributed to identify the main social categories and indicators for CCU, to which 33 European CCU experts responded. Finally, a modified TOPSIS was applied to rank the indicators based on their relevance. We found that the indicators related to “end of life responsibility” and “transparency” within a CCU company achieved the highest rank affecting the consumers group, whereas “fair salary” and “equal opportunities/discriminations” were determined as the most relevant impact categories for the workers. For the local community group, “secure living conditions” and “local employment” received the highest priority from the experts’ point of view. Furthermore, “health and safety” considerations were identified as one of the most important criteria affecting all three groups of stakeholders. The ranking list of the main social indicators identified in our study provides the basis for the next steps in the social sustainability assessment of CCU technologies; that is, data collection and impact assessment. Our outcomes can also be used to inform the producers regarding the most and least relevant social aspects of CCU so that the potential social impacts caused by their production activities can be improved or prevented.
Vorheriger Artikel A Multivariate Indicator to Compute Middle Class Population
Nächster Artikel Is Linking Social Capital More Beneficial to the Health Promotion of the Poor? Evidence from China

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Literatur
Afsordegan, A., Sánchez, M., Agell, N., Zahedi, S., & Cremades, L. V. (2016). Decision making under uncertainty using a qualitative TOPSIS method for selecting sustainable energy alternatives. International Journal of Environmental Science and Technology,13, 1419–1432.
Amine, M. E., Pailhes, J., & Perry, N. (2014) Comparison of different multiple-criteria decision analysis methods in the context of conceptual design: Application to the development of a solar collector structure. In Proceedings of joint conference on mechanical, design engineering advanced manufacturing, Toulouse, France June 2014, France (pp. 1–6).
Aparcana, S., & Salhofer, S. (2013). Development of a social impact assessment methodology for recycling systems in low-income countries. International Journal of Life Cycle Assessment,18(5), 1106–1115.
Arning, K., van Heek, J., & Ziefle, M. (2017). Risk perception and acceptance of CDU consumer products in Germany. Energy Procedia,114, 7186–7196.
Baumann, H., Arvidsson, R., Tong, H., & Wang, Y. (2013). Does the Production of an Airbag Injure more People than the Airbag Saves in Traffic? Journal of Industrial Ecology, 17(4), 517–527.
Behzadian, M., Khanmohammadi Otaghsara, S., Yazdani, M., & Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with Applications,39, 13051–13069.
Bocin-Dumitriu, A., Perez Fortes, M.-M., Tzinas, E., & Sveen, T. (2013). Carbon capture and utilisation workshop background and proceedings. Scientific and technical report by the Joint Research Centre of the European Commission. https://​doi.​org/​10.​2790/​11560.
Bruhn, T., Naims, H., & Olfe-Kräutlein, B. (2016). Separating the debate on CO2 utilisation from carbon capture and storage. Environmental Science & Policy,60, 38–43.
Buchholz, T., Volk, T. A., & Luzadis, V. A. (2009). Multi criteria analysis for bioenergy systems assessments. Energy Policy,37(2), 484–495.
Cartelle Barros, J. J., Coira, M. L., de la Cruz López, M. P., & Caño Gochi, A. D., (2015). Assessing the global sustainability of different electricity generation systems. Energy, 89, 473–489.
Colodel, C. M., Kupfer, T., Barthel, L. P., & Albrecht, S. (2009). R&D decision support by parallel assessment of economic, ecological and social impact: Adipic acid from renewable resources versus adipic acid from crude oil. Ecological Economics,68(6), 1599–1604.
Converse, J. M., & Presser, S. (1986). Survey questions: Handcrafting the standardized questionnaire. Beverly Hills, CA: Sage.
Cook, C., Heath, F., & Thompson, R. L. (2000). A meta-analysis of response rates in web- or internet-based surveys. Educational and Psychological Measurement,60(6), 821–836.
Cuéllar-Franca, R. M., & Azapagic, A. (2015). Carbon capture, storage and utilisation technologies: A critical analysis and comparison of their life cycle environmental impacts. Journal of CO2 Utilization,9, 82–102.
Dikopoulou, Z., Nápoles, G., Papageorgiou, E. I., & Vanhoof, K. (2015). Ranking and aggregation of factors affecting companies’ attractiveness. In 5th International symposium on knowledge acquisition and modelling, Atlantis Press, London.
Doukas, H., Karakosta, C., & Psarras, J. (2010). Computing with words to assess the sustainability of renewable energy options. Expert Systems with Applications,37, 5491–5497.
Dreyer, L. C., Hauschild, M. Z., & Schierbeck, J. (2010). Characterization of social impacts in LCA. Part 1: Development of indicators for labour rights. International Journal of Life Cycle Assessment,15(3), 247–259.
Ekener-Petersen, E., & Finnveden, G. (2013). Potential hotspots identified by social LCA—part 1: A case study of a laptop computer. International Journal of Life Cycle Assessment,18(8), 127–143.
Foolmaun, R. K., & Ramjeeawon, T. (2013). Comparative life cycle assessment and social life cycle assessment of used polyethylene terephthalate (PET) bottles in Mauritius. International Journal of Life Cycle Assessment,18(1), 155–171.
Gnansounou, E. (2011). Assessing the sustainability of biofuels: A logic-based model. Energy,36(4), 2089–2096.
Hardisty, P. E., Sivapalan, M., & Brooks, P. (2011). The Environmental and Economic Sustainability of Carbon Capture and Storage. International Journal of Environmental Research and Public Health, 8(5), 1460–1477.
Harms, D., Hansen, E. G., & Schaltegger, S. (2013). Strategies in sustainable supply chain management: An empirical investigation of large German companies. Corporate Social Responsibility and Environmental Management,20(4), 205–218.
Hasan, K. N., Saha, T. K., & Eghbal, M. (2014). Investigating the priority of market participants for low emission generation entry into the Australian grid. Energy,71, 445–455.
Hassini, E., Surti, C., & Searcy, C. (2012). A literature review and a case study of sustainable supply chains with a focus on metrics. International Journal of Production Economics,140(1), 69–82.
Hsieh, L. F., Chin, J. B., & Wu, M. C. (2006). Performance evaluation for university electronic libraries in Taiwan. The Electronic Library,24(2), 212–224.
Huang, I. B., Keisler, J., & Linkov, I. (2011). Multi-criteria decision analysis in environmental sciences: ten years of applications and trends. Science of the Total Environment,409(19), 3578–3594.
Huguenin, J.-M. (2015). Data envelopment analysis and non-discretionary inputs: How to select the most suitable model using multi-criteria decision analysis. Expert Systems with Applications,42, 2570–2581.
Hwang, A., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. New York: Springer.
Jahoda, M., Deutsch, M., & Cook, S. (1962). Research methods in social relations. New York: Holt, Rinehart and Winston.
Jones, Ch. R., Radford, R. L., Armstrong, K., & Styring, P. (2014). What a waste! Assessing public perceptions of Carbon Dioxide Utilisation technology. Journal of CO 2Utilization, 7, 51–54.
Jones, S., Snowden-Swan, L., Meyer, P., Zacher, A., Olarte, M., & Drennan, C. (2015b). Fast pyrolysis and hydrotreating: 2014 State of Technology R&D and projections to 2017. Richland, WA: PNNL-24176, Pacific Northwest National Laboratory.
Kaya, T., & Kahraman, C. (2011). Multicriteria decision making in energy planning using a modified fuzzy TOPSIS methodology. Expert Systems with Applications,38, 6577–6585.
Klankermayer, J., & Leitner, W. (2015). Love at second sight for CO2 and H2 in organic synthesis. Science,350, 629–630.
Krosnick, J. A., Holbrook, A. L., et al. (2002). The impact of ‘no opinion’ response options on data quality. Non-attitude reduction or an invitation to satisfice? Public Opinion Quarterly,66, 371–403.
Kuramochi, T., Ramírez, A., Turkenburg, W., & Faaij, A. (2011). Techno-economic assessment and comparison of CO capture technologies for industrial processes: Preliminary results for the iron and steel sector. Energy Procedia,4, 1981–1988.
Manik, Y., Leahy, J., & Halog, A. (2013). Social life cycle assessment of palm oil biodiesel: A case study in Jambi Province of Indonesia. International Journal of Life Cycle Assessment,18(7), 1386–1392.
Mankins, J. C. (2009). Technology readiness assessments: A retrospective. Acta Astronautica,65, 1216–1223.
Maroun, M. R., & La Rovere, E. L. (2014). Ethanol and food production by family smallholdings in rural Brazil: Economic and socio-environmental analysis of micro distilleries in the State of Rio Grande do Sul. Biomass and Bioenergy,63, 140–155.
Marshall, D., McCarthy, L., Heavey, C., & McGrath, P. (2015). Environmental and social supply chain management sustainability practices: Construct development and measurement. Production Planning & Control,26(8), 673–690.
Martínez-Blanco, J., Lehmann, A., Muñoz, P., Antón, A., Traverso, M., Rieradevall, J., et al. (2014). Application challenges for the social LCA of fertilizers within life cycle sustainability assessment. Journal of Cleaner Production,69, 34–48.
Mendoza, G. A., & Prabhu, R. (2003). Qualitative multi-criteria approaches to assessing indicators of sustainable forest resource management. Forest Ecology and Management,174(1–3), 329–343.
Monroe, M. C., & Adams, D. C. (2012). Increasing response rates to web-based surveys. Journal of Extension,50(6), 6–7.
Naims, H. (2016). Economics of carbon dioxide capture and utilization—A supply and demand perspective. Environmental Science and Pollution Research,23(22), 22226–22241.
Niero, M., & Kalbar, P. (2019). Coupling material circularity indicators and life cycle based indicators: A proposal to advance the assessment of circular economy strategies at the product level. Resources, Conservation and Recycling,140, 305–312.
Okoli, C., & Pawlowski, S. D. (2004). The Delphi method as a research tool: An example, design considerations and applications. Information & Management,42(1), 15–29.
Onat, N. C., Gumus, S., Kucukvar, M., & Tatari, O. (2016a). Application of the TOPSIS and intuitionistic fuzzy set approaches for ranking the life cycle sustainability performance of alternative vehicle technologies. Sustainable Production and Consumption,6, 12–25.
Onat, N. C., Kucukvar, M., Tatari, O., & Zheng, Q. P. (2016b). Combined application of multi-criteria optimization and life-cycle sustainability assessment for optimal distribution of alternative passenger cars in US. Journal of Cleaner Production,112, 291–307.
Papong, S., Itsubo, N., Malakul, P., & Shukuya, M. (2015). Development of the social inventory database in Thailand using input–output analysis. Sustainability,7(6), 7684–7713.
Payne, S. (1951). The art of asking questions. Princeton: Princeton University Press.
Pérez-Fortes, M., & Tzimas, E. (2016). Techno-economic and environmental evaluation of carbon dioxide utilisation for fuel production. Synthesis of methanol and formic acid; EUR 27629 EN. https://​doi.​org/​10.​2790/​981669.
Poe, G. S., Seeman, I., McLaughlin, J., Mehl, E., & Dietz, M. (1988). Don’t know boxes in factual questions in a mail questionnaire. Public Opinion Quarterly,52, 212–222.
Quadrelli, E., Centi, G., Duplan, J.-L., & Perathoner, S. (2011). Carbon dioxide recycling: emerging large-scale technologies with industrial potential. Chemsuschem,4, 194–1215.
Rafiaani, P., Kuppens, T., Van Dael, M., Azadi, H., Lebailly, Ph, & Van Passel, S. (2018). Social sustainability assessments in the biobased economy: Towards a systemic approach. Journal of Renewable and Sustainable Energy Reviews,82(2), 1839–1853.
Ragland, C. J., Feldpausch-Parker, A., Peterson, T. R., Stephens, J., & Wilson, E. (2011). Socio-political dimensions of CCS deployment through the lens of social network analysis. Energy Procedia,4, 6210–6217.
Rogers, E. (2003). Diffusion of innovations. New York, NY: Free Press.
Santoyo-Castelazo, E., & Azapagic, A. (2014). Sustainability assessment of energy systems: integrating environmental, economic and social aspects. Journal of Cleaner Production, 80, 119–138.
Scott, J. A., Ho, W., & Dey, P. K. (2012). A review of multi-criteria decision-making methods for bioenergy system. Energy,42(1), 146–156.
Searcy, C. (2012). Corporate Sustainability Performance Measurement Systems: A Review and Research Agenda. Journal of Business Ethics, 107(3), 239–253.
Stamford, L., & Azapagic, A. (2011). Sustainability indicators for the assessment of nuclear power. Energy, 36(10), 6037–6057.
Streimikiene, D., Balezentis, T., Krisciukaitiene, I., & Balezentis, A. (2012). Prioritizing sustainable electricity production technologies: MCDM approach. Renewable and Sustainable Energy Reviews,16, 3302–3311.
Sultana, A., & Kumar, A. (2012). Ranking of biomass pellets by integration of economic, environmental and technical factors. Biomass and Bioenergy,2(39), 344–355.
Thomassen, G., Van Dael, M., & Van Passel, S. (2018). The potential of microalgae biorefineries in Belgium and India: An environmental techno-economic assessment. Bioresource Technology,267, 271–280.
Traverso, M., Asdrubali, F., Francia, A., & Finkbeiner, M. (2012). Towards life cycle sustainability assessment: an implementation to photovoltaic modules. International Journal of Life Cycle Assessment,17(8), 1068–1079.
Turcksin, L., Macharis, C., Lebeau, K., Boureima, F., Mierlo, J. V., Bram, S., et al. (2011). A multi-actor multi-criteria framework to assess the stakeholder support for different biofuel options: The case of Belgium. Energy Policy,39(1), 200–214.
Tyagi, M., Kumar, P., & Kumar, D. (2015). Analyzing CSR issues for supply chain performance system using preference rating approach. Journal of Manufacturing Technology Management,26(6), 830–852.
Vaillancourt, P. M. (1973). Stability of children’s survey responses. Public Opinion Quarterly,37, 373–387.
van Heek, J., Arning, K., & Ziefle, M. (2017). Reduce, reuse, recycle: Acceptance of CO-utilization for plastic products. Energy Policy,105, 53–66.
Van Schoubroeck, S., Springael, J., Van Dael, M., Malina, R., & Van Passel, S. (2019). Sustainability indicators for biobased chemicals: A Delphi study using multi-criteria decision analysis. Resources, Conservation and Recycling,144, 198–208.
Velasquez, M., & Hester, P. T. (2013). An analysis of multi-criteria decision making methods. International Journal of Operations Research,10(2), 56–66.
Vinyes, E., Oliver-Solà, J., Ugaya, C., Rieradevall, J., & Gasol, C. M. (2013). Application of LCSA to used cooking oil waste management. International Journal of Life Cycle Assessment,18(2), 445–455.
Vreys, K., Lizin, S., Van Dael, M., Tharakan, J., & Malina, R. (2019). Exploring the future of carbon capture and utilisation by combining an international Delphi study with local scenario development. Resources, Conservation and Recycling, 146, 494–501.
Wang, E. (2015). Benchmarking whole-building energy performance with multi-criteria technique for order preference by similarity to ideal solution using a selective objective-weighting approach. Applied Energy,146, 92–103.
Wang, S.-W., Hsu, C.-W., & Hu, A. H. (2016). An analytic framework for social life cycle impact assessment—Part 1: Methodology. International Journal of Life Cycle Assessment,21, 1514–1528.
Wang, J.-J., Jing, Y.-Y., Zhang, C.-F., & Zhao, J.-H. (2009). Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renewable and Sustainable Energy Reviews,13(9), 2263–2278.
Wassermann, S., Schulz, M., & Scheer, D. (2011). Linking public acceptance with expert knowledge on CO storage. Outcomes of a Delphi approach. Energy Procedia,4, 6353–6359.
Xu, Q., Zhang, Y.-B., Zhang, J., & Lv, X.-G. (2015). Improved TOPSIS model and its application in the evaluation of NCAA basketball coaches. Modern Applied Science,9(2), 259.
Metadaten
Titel
Identifying Social Indicators for Sustainability Assessment of CCU Technologies: A Modified Multi-criteria Decision Making
verfasst von
Parisa Rafiaani
Zoumpolia Dikopoulou
Miet Van Dael
Tom Kuppens
Hossein Azadi
Philippe Lebailly
Steven Van Passel
Publikationsdatum
06.07.2019
Verlag
Springer Netherlands
Erschienen in
Social Indicators Research / Ausgabe 1/2020
Print ISSN: 0303-8300
Elektronische ISSN: 1573-0921
DOI
https://doi.org/10.1007/s11205-019-02154-4

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