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Global Environmental Change
Article . 2018 . Peer-reviewed
License: Elsevier TDM
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Global Environmental Change
Article . 2018 . Peer-reviewed
http://dx.doi.org/10.1016/j.gl...
Article
License: Elsevier TDM
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Comparing future patterns of energy system change in 2 °C scenarios to expert projections

Authors: Detlef P. van Vuuren; Detlef P. van Vuuren; Valentina Bosetti; Valentina Bosetti; Charlie Wilson; Mathijs Harmsen; Mathijs Harmsen; +5 Authors

Comparing future patterns of energy system change in 2 °C scenarios to expert projections

Abstract

Integrated assessment models (IAMs) are computer-based instruments used to assess the implications of human activity on the human and earth system. They are simultaneously also used to explore possible response strategies to climate change. As IAMs operate simplified representations of real-world processes within their model structures, they have been frequently criticised to insufficiently represent the opportunities and challenges in future energy systems over time. To test whether projections by IAMs diverge in systematic ways from projections made by technology experts we elicited expert opinion on prospective change for two indicators and compared these with the outcomes of IAM studies. We specifically focused on five (energy) technology families (solar, wind, biomass, nuclear, and carbon capture and storage or CCS) and compared the considered implications of the presence or absence of climate policy on the growth and diffusion of these technologies over the short (2030) to medium (2050) term. IAMs and experts were found to be in relatively high agreement on system change in a business-as-usual scenario, albeit with significant differences in the estimated magnitude of technology deployment over time. Under stringent climate policy assumptions, such as the internationally agreed upon objective to limit global mean temperature increase to no more than 2 °C, we found that the differences in estimated magnitudes became smaller for some technologies and larger for others. Compared to experts, IAM simulations projected a greater reliance on nuclear power and CCS to meet a 2 °C climate target. In contrast, experts projected a stronger growth in renewable energy technologies, particularly solar power. We close by discussing several factors that are considered influential to the alignment of the IAM and expert perspectives in this study.

Countries
Italy, United Kingdom, Netherlands, Italy
Keywords

690, 330, Monitoring, Geography, Planning and Development, Management, Monitoring, Policy and Law, Expert elicitation, Technology diffusion, 2 DEGREES, CLIMATE CHANGE, EXPERT ELICITATION, INTEGRATED ASSESSMENT, TECHNOLOGY DIFFUSION, GLOBAL AND PLANETARY CHANGE, GEOGRAPHY, PLANNING AND DEVELOPMENT, ECOLOGY, MANAGEMENT, MONITORING, POLICY AND LAW, Taverne, SDG 13 - Climate Action, Climate change, Integrated assessment, SDG 7 - Affordable and Clean Energy, Planning and Development, Global and Planetary Change, Geography, Ecology, Policy and Law, 320, Management, 2 degrees

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    26
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
26
Top 10%
Top 10%
Top 10%
Green
hybrid