Stefan Hirschberg 1, Warren Schenler 1, Peter Burgherr 1, Christian Bauer 1 and Marek Makowski 2
1 Laboratory for Energy Systems Analysis, Energy Departments, Paul Scherrer Institut (PSI), Switzerland
2 International Institute for Applied Systems Analysis (IIASA), Austria
The present paper summarizes progress achieved in indicator-based sustainability assessment of energy technologies. This includes: establishment of a comprehensive set of technology-specific indicators with high level of acceptability by the engaged stakeholders; quantification of all indicators for four countries; development of new Multi-criteria Decision Analysis (MCDA) methods and web-based MCDA implementation; application of MCDA with a variety of stakeholders, demonstrating the merits of the process, strengths and weaknesses of the analyzed technologies, and the unavoidable impact of stakeholder preferences.
The recently finalized EU-Project NEEDS (“New Energy Externality Developments for Sustainability”) generated a wide range of results within such areas as Life Cycle Assessment (LCA), assessment of external costs and scenario modeling. The Research Stream "Technology Roadmap and Stakeholder Perspectives" aimed at broadening the basis for decision support by examining the robustness of the results under various stakeholder perspectives. This objective was pursued by combining knowledge expressed in terms of technology attributes with stakeholder preferences. Use of Multi-criteria Decision Analysis (MCDA) enabled explicit and integrative consideration of a wide spectrum of technology-specific environmental, economic and social characteristics.
The development and implementation of the MCDA approach included: (a) developing a structured set of sustainability criteria, and surveying stakeholders on their appropriateness and acceptance; (b) integrating environmental, economic and social indicator results from this and other research streams into a technology database for use in the MCDA process; (c) developing a range of new MCDA tools for ranking the NEEDS technologies and selecting the best for use; (e) implementing an interactive, web-based interface for collecting stakeholder criteria preferences; and (f) collecting the individual user inputs, ranking technologies, identifying patterns by means of sensitivity mapping, and comparing MCDA results with total (internal plus external) costs.
Total costs and external costs of electricity generation
Costs are called “external” if they are not born by the party that causes them, but rather by society as a whole. They include the costs of health damages that result from air pollution. Such damages are monetized, i.e. are measured in or converted to monetary units, and also include those resulting from future climate change. These are very uncertain today, and can vary over a large range. Further aspects are the reduced harvests and damages to buildings caused by air pollution.
Not all factors that play a role in the judgment of a technology are measured in Francs and Rappen: This is controversial, above all the significance of subjective aspects like perceived risks or visual disturbances to the landscape.
In spite of these limitations, external costs are very valuable for cost-benefit analysis.
The total cost is obtained by adding the production (or internal) and external costs of electricity together, and is sometimes also used as a measure of sustainability, although this is controversial. Non-monetized factors are then naturally not considered.
Sustainability criteria and indicators
A full set of technology-specific evaluation criteria and indicators, covering the environmental, economic and social dimension of sustainability, was established by PSI with support from partners . The set partially builds on the results of a literature survey and quantitative sustainability assessments from earlier projects. Social criteria and indicators were established in a pioneering work by University of Stuttgart . The social aspects associated with energy systems are to a limited extent reflected in external cost estimates.
The overall set enables catching the essential characteristics of technologies and differentiating between them. In general, the proposed criteria and indicators found wide acceptance among stakeholders both in terms of content as well as its hierarchical structure. Table 1 shows the full set of sustainability criteria employed in the NEEDS project. There are 36 associated indicators, thereof:
These indicators were quantified and then combined in a unique database that includes 36 separate indicators for each of 26 future technologies (in the year 2050) in four countries, i.e. France, Germany, Italy and Switzerland. Comparisons between the various indicators illustrate the differences in profiles and thus strengths and weaknesses of the various technological options and the associated fuel cycles. While improvements are envisioned for all technologies considered, the most remarkable progress has been credited for the future economic performance of renewables, in particular solar technologies.
Development of sustainability assessment at PSI
1999-2000: First Multi-Criteria Analysis for the Swiss electricity supply
1999-2003: China Energy Technology Program – MCDA application for China, including an interactive tool
2002-2004: MCDA application for the case of Germany.
2004-2006: Sustainability assessment model for the Swiss electricity supply in collaboration with the utility company Axpo and other partners (for today and 2030).
2005-2009: EU Project NEEDS – Sustainability assessment of innovative electricity supply technologies to 2050 under the leadership of PSI, and with cooperation of industry and NGO’s.
2010-2014: THELMA project – Sustainability assessment of personal vehicles.
Assessment results and conclusions
Using MCDA, the technology-specific set of sustainability indicators was combined with stakeholder preferences. This approach allows establishing a ranking of technologies based on distinct stakeholder profiles and investigation of the associated sensitivities. IIASA developed a number of new MCDA methods satisfying the requirements of the NEEDS Project . IIASA supported by PSI implemented a web-based tool for the most suitable method, enabling stakeholders to specify their preference profiles, iterate them and establish the ranking of future technologies. The overview of the results based on all stakeholder responses is shown in Fig. 1 along with total costs .
While within the external cost estimation framework applied in NEEDS nuclear energy exhibits the lowest total costs, its ranking in the MCDA framework tends to be lower, mainly due to consideration of a variety of social aspects not reflected in external costs. Thus, nuclear energy ranks in MCDA mostly lower than renewables, which benefit from much improved economic performance. Coal technologies have mostly lower total costs than natural gas. In the MCDA framework coal on the other hand performs worse than centralized natural gas options; the latter are in the midfield and have thus ranking comparable to nuclear. The performance of CCS is mixed.
The individual preference profiles have a decisive influence on the MCDA-ranking of technologies. Given equal weighting of environmental, economic and social dimensions and emphasis on the protection of climate and ecosystems, minimisation of objective risks and affordability for customers, the nuclear options are top ranked.
On the other side, focusing on radioactive wastes, land contamination due to hypothetical accidents, risk aversion and perception issues, terrorist threat and conflict potential, the ranking changes to the disadvantage of nuclear energy. This emphasizes the need of further technological developments towards mitigating the negative impacts of these issues.
The ranking of fossil technologies highly depends on the emphasis put on the environmental performance, which in relative terms remains to be a weakness, more pronounced for coal than for gas. Renewables show mostly a stable very good performance in terms of relatively low sensitivity to changes in preference profiles, based on highly improved economics.
 Hirschberg, S. et al. (2008) Final Set of Sustainability Criteria and Indicators for Assessment of Electricity Supply Options. EU-Project NEEDS, Deliverable n° D3.2 – RS2b.
 Renn, O., Hampel, J. and Brukmajster, D. (2006) Establishment of social criteria for energy systems. EU-Project NEEDS, Deliverable n° D2.3 – RS2b.
 Makowski, M., Granat, J., Ogryczak, W. (2009) Overview of Methods Implemented in MCA: Multiple Criteria Analysis of Discrete Alternatives with a Simple Preference Specification. Interim Report IR-09-24, IIASA, Laxenburg, Austria.
 Schenler, W., Hirschberg, S., Burgherr, P., Makowski, M. (2009) Final Report on the Sustainability Assessment of Electricity Supply Options. EU-Project NEEDS, Deliverable n° D10.2 – RS2b.
Dr. Stefan Hirschberg leads the interdisciplinary Laboratory for Energy Systems Analysis (LEA), which belongs both to the Nuclear Energy and Safety, and the General Energy Departments. The Laboratory aims to contribute to effective decision-making on long-term technology strategies in energy supply and demand, ensuring full integration of relevant environmental, economic and social factors. LEA also develops methodologies, and carries out the associated risk analyses, within the framework of Human Reliability Assessment (HRA). The activities within LEA, in cooperation with its various external partners, cover the following three project areas:
Technology Assessment (GaBE)
The project involves analyses of fossil, nuclear and renewable energy technologies. It is based on an interdisciplinary framework, thus enabling comparisons to be made between current and future options for the electricity, heating and transport sectors.
Analyses are undertaken of energy systems, and associated technological changes, at the Swiss, European and global levels, all aimed at improving understanding of available options for the realisation of more sustainable energy mixes for the future.
Risk and Human Reliability
Main contributions here are to the solution of current and future issues relating to the handling of human factors in the context of Probabilistic Safety Assessment (PSA).
[Released: September 2011]