Acceptance of energy technologies in context: Comparing laypeople's risk perceptions across eight infrastructure technologies in Germany
Graphical abstract
Introduction
Tackling the challenges of climate change and natural resource depletion requires political measures and new technological solutions which reduce greenhouse gas (GHG) emissions and save resources (IRP, 2019; UNEP, 2019). Carbon Capture and Utilization (CCU) can reduce emissions and the use of fossil resources by using CO2 captured at point sources (e.g., power plants) as a substitute for fossil feedstock, e.g., for the production of plastic products or fuels (Kätelhön et al., 2019; Von der Assen and Bardow, 2014). Depending on the application, the possible reductions CCU yields vary (Cuéllar-Franca and Azapagic, 2015). For example, for the production of polyols, which are required for the manufacturing of foam mattresses, 13–16% of fossil resources, and 11–19% of GHG emissions, can be saved by using CO2 as raw material (Von der Assen and Bardow, 2014). However, it has to be noted that the CCU process can require a higher energy input than conventional production processes (Abanades et al., 2017).
The environmental benefits of CCU mainly lie in the saving of fossil resources. As such, CCU needs to be distinguished from the concept of Carbon Capture and Storage (CCS), which aims to mitigate climate change by limiting the CO2 concentration in the atmosphere. In CCS captured CO2-emissions are permanently stored underground, for example, in saline aquifers or depleted oil fields. The amount of CO2 that can be permanently stored by applying CCS considerably exceeds the demand for CO2 in CCU applications (due to limited production capacities and resulting feedstock demands for CCU) (Bui et al., 2018). However, if viewed as a supplement to other low emission technologies with higher GHG reduction potential, such as Power-to-X and electromobility, CCU can help to mitigate climate change as well. If the demand for renewable electricity which these low emission technologies require is met, the surplus energy can be used for CCU, resulting in additional CO2 reductions (Kätelhön et al., 2019).
The successful implementation of CCU technologies does not only rely on their technical and economic feasibility, but also on the public's approval (Jones et al., 2017b). As previous studies in the context of energy infrastructure technologies have shown (e.g., for electricity transmission, Cain and Nelson, 2013; wind power, Langer et al., 2018; nuclear energy, Harris et al., 2018; and CCU, Arning et al., 2019), a technology's acceptance decreases as the concerns about its negative effects increase, thus making it crucial to consider the public's risk perception. Previous research already provided basic insights into the acceptance of CCU and its risk perception (e.g., Arning et al., 2017; Perdan et al., 2017). However, these studies exclusively focused on CCU and did not include a benchmark to other large-scale technologies. Because of this it has been difficult to assess the severity of technology-specific fears as a barrier for the acceptance of CCU. It is therefore important to figure out whether, when evaluated together with a series of established infrastructure technologies, CCU is rated as being harmless, risky, or somewhere in between both extremes. To address this research gap, the present study researches laypeople's perceived risks for CCU compared to seven other infrastructure technologies (fossil, nuclear, and renewable energies). In that way, risks can be put into perspective to assess the relevance of the risk perception as a possible barrier for the roll-out of CCU.
Section snippets
Social acceptance and risk perception of CCU
In this section, an overview of the current state of research on the risk perception for novel infrastructure technologies is provided. First, the basics of risk perception theory and the role of the perceived risks for the acceptance of infrastructure technologies are introduced, as well as the factors that influence the risk perception. Subsequently, the current state of research on the public perception of CCU with special regard to the perceived risks and their impact on the acceptance is
Method
To compare the risk perception for CCU with other infrastructure technologies, an online questionnaire was designed. Before describing the survey sample and the procedure applied for the data analysis, this section first provides a description of the self-assessment of risk perception as a valuable methodology for measuring laypeople's unbiased perspective. In contrast to domain expert's technical description of risks, laypeople's—the ones who will have to accept and adopt novel technologies in
Results
Firstly, risk perceptions for CCU and the seven renewable and conventional energy infrastructure technologies are compared. Moreover, the relationship between the risk evaluations for the three technology fields CCU, conventional, and renewable energy technologies is examined. Finally, the effect of person-related factors on the risk perception is investigated.
Putting CCU risks into perspective (RQ1)
In this section, the results are discussed, methodological limitations are addressed, and recommendations for an information and communication concept for the roll-out of CCU are derived. Additionally, an outlook on the future research follow-up studies should pursue is provided.
The present study found the risk perception for CCU to be at a medium level, which is in line with previous work that revealed concerns to be low to medium (Arning et al., 2018, 2019; Perdan et al., 2017). In the
Conclusion and policy implications
The aim of the present study was to put the perception of risks for CCU into perspective by comparing it to the perceived risks for seven other infrastructure technologies (five renewable and two conventional energy technologies). It was found that the risk perception for CCU was rather low, being perceived as riskier than renewables but less hazardous than conventional energy technologies. The perception of risks for CCU also correlated with that of both conventional and renewable energy
CRediT authorship contribution statement
Anika Linzenich: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing. Katrin Arning: Conceptualization, Data curation, Investigation, Methodology, Supervision, Validation, Writing - original draft, Writing - review & editing. Martina Ziefle: Funding acquisition, Project administration, Resources, Supervision, Validation, Writing - original draft, Writing - review & editing.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgment
The authors would like to thank Freya Willicks, Lisanne Simons, Mona Frank, Susanne Gohr, Lena Lummertzheim, and Anna Rohowsky for research support. Further thanks go to Luca Liehner for graphics support. We thank the editor Prof. Dr. Carlos Henggeler Antunes and two anonymous reviewers for their valuable suggestions which proved very helpful in improving the paper.
This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy –
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