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Physiological and behavioral reactions to renewable energy systems in various landscape types

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  • Spielhofer, R.
  • Thrash, T.
  • Hayek, U. Wissen
  • Grêt-Regamey, A.
  • Salak, B.
  • Grübel, J.
  • Schinazi, V.R.

Abstract

Renewable energy systems (RES) can impact landscape aesthetics and influence the public's perception of the landscape and their acceptance of large infrastructure projects. Perceptual processes have consequences for both physiological and behavioral reactions to visual landscape changes and have not been systematically assessed in the context of RES. In this paper, we measured participants' physiological (electrodermal activity) and behavioral (i.e., landscape preferences) responses to landscapes with different amounts of RES. The visual stimuli were composed of either a low or high amount of wind turbines and photovoltaic systems in seven different landscape types. Participants were asked to choose their preferred landscape image from pairs of sequentially presented images while we recorded their electrodermal activity. The results revealed that participants were significantly more physiologically aroused while viewing landscapes with high RES compared to landscapes with low RES. We also found that the participants significantly preferred landscapes with low RES to landscapes with high RES and that this effect was larger for some landscapes than others. The results also revealed significant differences in preferences among landscape types. Specifically, participants tended to prefer the more natural landscapes to the more urban landscapes. A systematic analysis of the visual features of these stimuli revealed a positive correlation between physiological arousal and the visual impact of photovoltaic systems. Overall, we conclude that both physiology and behavior can be relevant for studies of landscape perception and that these insights may inform planners and policy makers in the implementation of landscape changes related to RES.

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  • Spielhofer, R. & Thrash, T. & Hayek, U. Wissen & Grêt-Regamey, A. & Salak, B. & Grübel, J. & Schinazi, V.R., 2021. "Physiological and behavioral reactions to renewable energy systems in various landscape types," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    • Handle: RePEc:eee:rensus:v:135:y:2021:i:c:s1364032120306985
    DOI: 10.1016/j.rser.2020.110410
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    Cited by:

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    2. Russell McKenna & Stefan Pfenninger & Heidi Heinrichs & Johannes Schmidt & Iain Staffell & Katharina Gruber & Andrea N. Hahmann & Malte Jansen & Michael Klingler & Natascha Landwehr & Xiaoli Guo Lars', 2021. "Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments," Papers 2103.09781, arXiv.org.
    3. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    4. Salak, B. & Kienast, F. & Olschewski, R. & Spielhofer, R. & Wissen Hayek, U. & Grêt-Regamey, A. & Hunziker, M., 2022. "Impact on the perceived landscape quality through renewable energy infrastructure. A discrete choice experiment in the context of the Swiss energy transition," Renewable Energy, Elsevier, vol. 193(C), pages 299-308.
    5. Anna Codemo & Ambra Barbini & Ahi Mantouza & Anastasios Bitziadis & Rossano Albatici, 2023. "Integration of Public Perception in the Assessment of Licensed Solar Farms: A Case Study in Greece," Sustainability, MDPI, vol. 15(13), pages 1-25, June.
    6. Xinhui Fei & Yanqin Zhang & Deyi Kong & Qitang Huang & Minhua Wang & Jianwen Dong, 2023. "Quantitative Model Study of the Psychological Recovery Benefit of Landscape Environment Based on Eye Movement Tracking Technology," Sustainability, MDPI, vol. 15(14), pages 1-19, July.
    7. Salak, B. & Lindberg, K. & Kienast, F. & Hunziker, M., 2021. "How landscape-technology fit affects public evaluations of renewable energy infrastructure scenarios. A hybrid choice model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    8. Ioannidis, R. & Mamassis, N. & Efstratiadis, A. & Koutsoyiannis, D., 2022. "Reversing visibility analysis: Towards an accelerated a priori assessment of landscape impacts of renewable energy projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).

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