Michela Catenacci

The Future Prospect of PV and CSP Solar Technologies: An Expert Elicitation Survey

In this paper we present and discuss the results of an expert elicitation survey on solar technologies. Sixteen leading European experts from the academic world, the private sector and international institutions took part in this expert elicitation survey on Photovoltaic (PV) and Concentrated Solar Power (CSP) technologies. The survey collected probabilistic information on (1) how Research, Development and Demonstration (RD&D) investments will impact the future costs of solar technologies and (2) the potential for solar technology deployment both in OECD and non-OECD countries. Understanding the technological progress and the potential of solar PV and CPS technologies is crucial to draft appropriate energy policies. The results presented in this paper are thus relevant for the policy making process and can be used as better input data in integrated assessment and energy models.

Potentials and Limits of Bayesian Networks to Deal with Uncertainty in the Assessment of Climate Change Adaptation Policies

Bayesian networks (BNs) have been increasingly applied to support management and decision-making processes under conditions of environmental variability and uncertainty, providing logical and holistic reasoning in complex systems since they succinctly and effectively translate causal assertions between variables into patterns of probabilistic dependence. Through a theoretical assessment of the features and the statistical rationale of BNs, and a review of specific applications to ecological modelling, natural resource management, and climate change policy issues, the present paper analyses the effectiveness of the BN model as a synthesis framework, which would allow the user to manage the uncertainty characterising the definition and implementation of climate change adaptation policies. The review will let emerge the potentials of the model to characterise, incorporate and communicate the uncertainty, with the aim to provide an efficient support to an informed and transparent decision making process. The possible drawbacks arising from the implementation of BNs are also analysed, providing potential solutions to overcome them.

Going Electric: Expert Survey on the Future of Battery Technologies for Electric Vehicles

The paper describes the results of a survey, carried out with leading EU experts, on the capacity of both fully electric and plug-in hybrid vehicles to reach commercial success in the next twenty years. The success of electric transport is hampered by a combination of low range, scarce efficiency and high costs of batteries. Costs are expected to decrease in response to increasing sales volume and technical improvements, and advances would result from adequate investments in research, development and demonstration (RD&D). Experts’ judgements are collected to shed light on the inherently uncertain relationship between RD&D efforts and consequent technical progress, and to assess the complex dynamics that will hinder or support the widespread diffusion of electric vehicles. The analysis of the experts’ data results in a number of important policy recommendations to guide future RD&D choices and target commitments both for the EU and its member states.

Expert Judgments about RD&D and the Future of Nuclear Energy

Probabilistic estimates of the cost and performance of future nuclear energy systems under different scenarios of government research, development, and demonstration (RD&D) spending were obtained from 30 U.S. and 30 European nuclear technology experts. We used a novel elicitation approach which combined individual and group elicitation. With no change from current RD&D funding levels, experts on average expected current (Gen. III/III+) designs to be somewhat more expensive in 2030 than they were in 2010, and they expected the next generation of designs (Gen. IV) to be more expensive still as of 2030. Projected costs of proposed small modular reactors (SMRs) were similar to those of Gen. IV systems. The experts almost unanimously recommended large increases in government support for nuclear RD&D (generally 2-3 times current spending). The majority expected that such RD&D would have only a modest effect on cost, but would improve performance in other areas, such as safety, waste management, and uranium resource utilization. The U.S. and E.U. experts were in relative agreement regarding how government RD&D funds should be allocated, placing particular focus on very high temperature reactors, sodium-cooled fast reactors, fuels and materials, and fuel cycle technologies.

Advanced Biofuels: Future Perspectives from an Expert Elicitation Survey

This paper illustrates the main results of an expert elicitation survey on advanced (second and third generation) biofuel technologies. The survey focuses on eliciting probabilistic information on the future costs of advanced biofuels and on the potential role of RD&D (Research, Development and Demonstration) efforts in reducing these costs and in supporting the deployment of biofuels in OECD and non-OECD countries. Fifteen leading experts from different EU member states provide insights on the future potential of advanced biofuel technologies both in terms of costs and diffusion. This information results in a number of policy recommendations with respect to public RD&D strategies and is an important contribution to the integrated assessment modelling community.

Integrated assessment of sea-level rise adaptation strategies using a Bayesian decision network approach

The exposure to sea-level rise (SLR) risks emerges as a challenging issue in the broader debate about the possible consequences of global environmental change for at least four reasons: the potentially serious impacts, the very high uncertainty regarding future projections of SLR and their effects on the environmental and socio-economic system, the multiple scales involved, and the need to take effective management decisions in terms of climate change adaptation. Unfortunately, mechanistic models generally demonstrated a limited ability to characterise in appropriate detail how complex coastal systems and their constituent parts may respond to climate change drivers and to possible adaptation initiatives. The research reported here develops an innovative methodological framework, which integrates different research areas - participatory and probabilistic modelling, and decision analysis - within a coordinated process aimed at decision support. The effectiveness of alternative adaptation measures in a lagoon in north-east Italy is assessed by means of Bayesian Decision Network (BDN) models, developed upon judgments elicited from selected experts. A concept map of the system was first developed in a group brainstorming context and was later evolved into BDN models, thus providing a simplified quantitative structure. Conditional probabilities, quantifying the causal links between the direct and indirect consequences of SLR on the area of study, are elicited from the experts. The proposed methodological framework allows the integrated assessment of factors and processes belonging to different domains of knowledge. Moreover, it activates an informed and transparent participatory process involving disciplinary experts and policy makers, where the main risk factors are considered together with the expected effects of the adaptation options, with effective treatment and communication of the uncertainty pervading the SLR issue. Finally, the framework shows potentials for being further developed and applied to consider new evidences and/or different adaptation strategies, and it results sufficiently flexible to be adopted and effectively reused in other similar case studies. Highlights? The methodology provided a versatile approach to assess climate adaptation policies. ? The project catalysed local debate on adaptation to sea-level rise. ? BDNs bridged science and policy and enhanced a transparent decision process. ? BDNs represented effective platforms to integrate empirical data and expert estimates. ? The methodological framework showed potential for reuse in other contexts.

The Future Prospects of PV and CSP Solar Technologies

The present article briefly discusses the results of an expert elicitation survey on solar technologies carried out within the ICARUS project on innovation in carbon-free energy technologies. Sixteen leading European experts from the academic world, the private sector and international institutions took part in this survey on Photovoltaic (PV) and Concentrated Solar Power (CSP) technologies. The elicitation process collected probabilistic information on (1) how Research, Development and Demonstration (RD&D) investments will impact the future costs of solar technologies and (2) the potential for solar technology deployment and diffusion both in OECD and non-OECD countries. Understanding the technological progress and the potential of solar PV and CPS technologies is crucial to draft appropriate energy policies. The results presented in this paper are thus relevant for the policy making process and can be used as better input data in integrated assessment and energy models.

Potentials of Bayesian Networks to Deal with Uncertainty in Climate Change Adaptation Policies

Bayesian networks (BNs) have been increasingly applied to support management and decision-making processes under conditions of environmental variability and uncertainty, providing logical and holistic reasoning in complex systems since they succinctly and effectively translate causal assertions between variables into patterns of probabilistic dependence. Through a theoretical assessment of the features and the statistical rationale of BNs, and a review of specific applications to ecological modelling, natural resource management, and climate change policy issues, the present paper analyses the effectiveness of the BN model as a synthesis framework, which would allow the user to manage the uncertainty characterising the definition and implementation of climate change adaptation policies. The review will let emerge the potentials of the model to characterise, incorporate and communicate the uncertainty, with the aim to provide an efficient support to an informed and transparent decision making process. The possible drawbacks arising from the implementation of BNs are also analysed, providing potential solutions to overcome them.

Governance and Environmental Policy Integration in Europe: What Can We Learn from the EU Emission Trading Scheme?

The European Union Emission Trading System (EU ETS) is a landmark environmental policy, representing the worlds first large-scale greenhouse gas (GHG) trading program. The coexistence of state actors and top-down processes with stakeholders participation and flexible abatement strategies make the EU ETS a powerful instrument of cross sectoral integration of environmental concerns, which benefits from a high level of interaction among the actors involved and a significant degree of information exchange. However, the same peculiarities of the system make it difficult to identify a correspondence with a single mode of governance. The EU ETS shows characteristics of the decision making processes and institutions engaged, the tools and instruments used as well as the actors involved, which change according to the different levels of governance, and belong both to the old and to the new modes of governance. The emission trading scheme represents a clear example of Multi-Level governance, where the different modes of governance interact among them and affect each other.

Expert Judgment Elicitation Protocols

While past data analysis can provide extremely valuable information on past dynamics and technology development, it is paramount to recognize the distorting effect of uncertainty on innovating firms’ behaviors and its determining role on current and future innovation processes. In order to account for uncertainty and to fill the lack of empirical or modeling data, the ICARUS project resorted to experts’ elicitations, which have been successfully used to collect information on future trends of technology costs. Expert judgments are the expressions of informed opinion that experts make based on their knowledge and experience with respect to technical problems (Hogarth, 1987; Morgan and Henrion, 1990; Cooke, 1991). Eliciting experts’ judgements means collecting subjective probabilities that a specific event will take place in the future, through specific methods of verbal or written communication. Experts’ judgements are particularly useful and are often required in probabilistic decision-making and in the evaluation of risks. They can fill the lack of information or complement other available data based on models’ predictions, thus providing an additional source of information. Expert judgement elicitation has been successfully used in the past to inform policy-makers, especially in the field of energy (Apostolakis, 1990). One prominent example in this respect is the study by the European Commission and the United States Nuclear Regulatory Commission during the 1990s focusing on nuclear power plants and the uncertainty surrounding accident consequence codes (Cooke and Goossens, 2004). The literature on decision analysis provides interesting theories on the techniques that should be applied to elicit expert judgments under uncertainty, support risk evaluation and inform a transparent decision-making process, especially if historical data is scarce and cannot inform on future developments, as is the case for energy projections (Morgan and Keith, 2008), nuclear engineering (Cooke and Goossens, 1999), climate change impacts and policy analysis (Morgan and Keith, 1995) and environmental policy in general (Morgan and Henrion, 1990).