102,043 research outputs found
Social innovation enablers to unlock a low energy demand future
No full textWe initiate the process of developing a comprehensive low energy demand (LED) innovation narrative by applying the framework 'Functions of Innovation Systems' (FIS) and identifying the key conditions under which technology interventions can be improved and scaled up over the next three decades to contribute to climate change mitigation. Several studies have argued that the potential for LED-focused mitigation is much larger than previously portrayed and have shown that adopting a wide variety of energy-reducing activities would achieve emissions reductions compatible with a 1.5 C temperature target. Yet, how realistic achieving such a scenario might be or what processes would need to be in place to create a pathway to a LED outcome in mid-century, remain overlooked. This study contributes to understanding LED's mitigation potential by outlining narratives of LED innovation in three end-use sectors: industry, transport, and buildings. Our analysis relies on the FIS approach to assess three innovations in these sectors. A key insight is that the distinct characteristics of LED technology make enabling social innovations crucial for their widespread adoption. Finally, we identify a set of eight social enablers required for unlocking LED pathways
Expression of eotaxin, interleukin 13 and tumour necrosis factor-alpha in dermatitis herpetiformis.
No full textObstetric complications and clinical presentation in first episode of psychosis
No full textVerdolini N, Mezquida G, Valli I, Garcia-Rizo C, Cuesta M, Vieta E, Bioque M, Lobo A, González-Pinto A, Pina-Camacho L, Corripio I, Garriga M, Baeza I, Martínez-Sadurní L, Bitanihirwe B, Cannon M, Bernardo M; PEPs GROU
The Future Costs of Nuclear Power Using Multiple Expert Elicitations: Effects of RD&D and Elicitation Design
No full textCharacterization of the anticipated performance of energy technologies to inform policy decisions increasingly relies on expert elicitation. Knowledge about how elicitation design factors impact the probabilistic estimates emerging from these studies is, however, scarce. We focus on nuclear power, a large-scale low-carbon power option, for which future cost estimates are important for the design of energy policies and climate change mitigation efforts. We use data from three elicitations in the USA and in Europe and assess the role of government research, development, and demonstration (RD&D) investments on expected nuclear costs in 2030. We show that controlling for expert, technology, and design characteristics increases experts' implied public RD&D elasticity of expected costs by 25%. Public sector and industry experts' cost expectations are 14% and 32% higher, respectively than academics. US experts are more optimistic than their EU counterparts, with median expected costs 22% lower. On average, a doubling of public RD&D is expected to result in an 8% cost reduction, but the uncertainty is large. The difference between the 90th and 10th percentile estimates is on average 58% of the experts' median estimates. Public RD&D investments do not affect uncertainty ranges, but US experts are less confident about costs than Europeans.Author's Origina
Quantifying the Effects of Expert Selection and Elicitation Design on Experts’ Confidence in their Judgments about Future Energy Technologies
No full textExpert elicitations are frequently used to characterize future technology outcomes. However their usefulness is limited, in part because: estimates across studies are not easily comparable; choices in survey design and expert selection may bias results; and over-confidence is a persistent problem. We provide quantitative evidence of how these choices affect experts’ estimates of the costs of future energy technologies. We harmonize data from 19 elicitations, involving 215 experts, on the 2030 costs of 5 energy technologies: nuclear, biofuels, bioelectricity, solar, and carbon capture. We control for expert characteristics, survey design, and public R&D investment levels on which the elicited values are conditional. We find that, on average, when experts respond to elicitations in person, they ascribe lower confidence (larger uncertainty) to their estimates than when responding via mail or online. In-person interviews also produce more optimistic assessments of best-case (10th percentile) outcomes. The impacts of expert affiliation—government, private sector, or academic—and geography—US or EU—are also significant; academics and US experts have lower confidence than other types of experts. Higher R&D investment levels have no effect on the confidence of experts’ judgments. R&D reduces both the median and breakthrough (10th percentile) cost estimates, although the size of the effect varies across technologies. These results indicate the source, direction, and size of bias in energy technology elicitations. They also point to the technology specificity of some of the effects. These biases should be seriously considered, both in interpreting the results of existing elicitations and in designing new ones
The power of biomass: experts disclose the potential for success of bioenergy technologies
No full textThis paper focuses on technologies which use thermo-chemical or biochemical processes to convert biomass into electricity. We present the results from an expert elicitation exercise involving sixteen leading experts coming from different EU Member States. Aim of the elicitation was to assess the potential cost reduction of RD&D (Research, Development and Demonstration) efforts and to identify barriers to the diffusion of these technologies. The research sheds light on the future potential of bioenergy technologies both in OECD (Organisation for Economic Co-operation and Development) and non-OECD countries. The results we present are an important input both for the integrated assessment modeling community and for policy makers who draft public RD&D strategies.JRC.H.3 - Forest Resources and Climat
The effects of expert selection, elicitation design and R&D assumptions on experts' estimates of the future costs of photovoltaics
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