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.
| Original language | English |
|---|---|
| Pages (from-to) | 201-211 |
| Number of pages | 11 |
| Journal | Global Environmental Change |
| Volume | 50 |
| DOIs | |
| Publication status | Published - 1 May 2018 |
Funding
The research leading to these results has received funding from the European Union’s Seventh Framework Programme FP7/2007–2013 under grant agreement n° 282846 (LIMITS), n° 603942 (PATHWAYS) and the European Union’s Horizon 2020 research and innovation programme under grant agreement n° 730035 (REINVENT). CW acknowledges funding support from the European Union’s Seventh Framework Programme FP7/2007–2013 under grant agreement n° 308329 (ADVANCE). BvdZ acknowledges the financial assistance from the European Union’s Horizon 2020 Programme under grant agreement n° 642260 (TRANSrisk). The authors are indebted to all contributing technology experts for partaking in this research. We would also like to thank Hilke Rösler for her research assistance and the anonymous peer-reviewers for their comments which substantially improved the manuscript. Appendix A
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 13 Climate Action
Keywords
- 2 degrees
- Climate change
- Expert elicitation
- Integrated assessment
- Technology diffusion
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