Ne Energy Externalities Development for Sustainability · 2009-06-12 · analytical tools developed and used in NEEDS, ... The results presented by different Research Streams of NEEDS

New Energy Externalities Development for Sustainability

EXECUTIVE SUMMARY

1 INTRODUCTION AND OBJECTIVES

2 BUILDING CONSENSUS AROUND THE NEEDS RESULTS 3 HOT TOPICS AND CONTROVERSIAL ISSUES

3.1 Uncertainties and limitations

3.2 Private costs of future energy technologies 3.3 Climate change 3.4 Full coverage of relevant externalities 3.5 Back-up costs 3.6 Social acceptance 3.7 Variability and transfer

4 TECHNOLOGY RANKING: THE ULTIMATE CHALLENGE?

5 SO: HOW DO ENERGY TECHNOLOGIES ULTIMATELY COMPARE?

6 CONCLUSIONS


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Executive summary

This document is a summary account of the final debate organised in Spring 2009 to ascertain the extent of the consensus achieved within the NEEDS community on selected scientific and policy relevant issues, notably including technology comparison and ranking, the expected performances (costs, efficiency, market penetration) of new and emerging energy options, and the valuation of “difficult” externalities.

There is a generalised consensus on the methodological approaches adopted and on the analytical tools developed and used in NEEDS, notwithstanding the fact that in some instances different approaches have been used “in competition”.

Numerical results are also broadly consensual. In the few cases where disagreements on results have emerged (e.g. the private costs of selected energy technologies, the preferred values for GHG costs, particularly in the short-medium term), these appear to reflect the unavoidable uncertainty attached to any prediction.

Some unavoidable degree of controversy remains for what concerns the meaning and the interpretation of selected results, and in particular the use that can/should be made of the NEEDS numerical outputs to derive a possible ranking of future energy technologies.

On the other hand, consensus has clearly emerged on the intrinsic limits of the very concept of technology ranking, especially when based on one-dimensional criteria, while the abundant results generated by NEEDS allow to compare future technology options and their potential role in future EU energy systems according to a variety of perspectives.


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1. Introduction and objectives

As the old saying goes, “…put 10 experts around the table, and you’re sure to get at least 11 different opinions”. With a multidisciplinary team of more than 60 participating institutions, NEEDS faced the painstaking challenge of achieving consensus on such complex issues as e.g. “what will be the lifecycle costs of energy technologies in 2050?”, “ is it possible to transfer external cost values from one electricity generation plant to another?”, “is there a robust methodology to measure social acceptability?”, and many others.

Indeed, after almost 5 years of intense collaboration, heated debates and hard work, we certainly cannot claim to have ironed out all controversies. This reflects – among other factors - the innovative nature of the research carried out and the varying level of maturity of the many scientific issues addressed. It also reflects the intrinsic difficulty of tackling such issues as risk assessment, understanding the complex physical phenomena that characterise climate change, or predicting the long-term dynamics of citizens’ and stakeholders’ preferences. Ultimately, achieving full consensus would have been nothing less than… suspicious!

The final NEEDS conference, hosted by the Economic and Social Council of the EU on 16-17 February 2009, while primarily focusing on the presentation of the most significant results achieved by the project and of their value as inputs to policy making, was also the opportunity for staging an extended debate with the participation of some 120 experts representing academia, public and private stakeholders, and the civil society. The discussion proved extremely lively and further allowed to highlight the many achievements of the project, as well as a number of issues that remain – at least partly – controversial.

Despite the limited time available (NEEDS has officially concluded its work on February 28th, 2009), it therefore seemed interesting and appropriate to follow-up the conference discussions with a final wrap up exchange of views among the lead scientists within the project. The aim of the exercise was to summarise the current position of the NEEDS experts on those issues where some degree of controversy still remains. To trigger the debate, these issues were summarised in the following condensed form:

The results presented by different Research Streams of NEEDS (and, in particular, by RS1a on LCA, RS1b on Externalities Valuation, and RS 2b on Stakeholders Perspective) appear to lead to different technology rankings. What are the scientific reasons behind this? It is recognised and agreed by all that externality valuation (monetary) still needs to be further improved, notably to take (better) account of a variety of criteria (e.g. risk aversion) which are not well captured so far. Does this state-of-the-art “penalise” some technologies more than others? And, if so, what can be done to correct such distortions without waiting for future RTD developments?


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The final debate was organised in 2 rounds: first, Stream Leaders were asked to formulate short statements addressing the above issues. The result was circulated to all contributors, and a second round of comments/responses was then elicited from all NEEDS partners willing to contribute.

This document illustrates the outcome of the discussion. At the outset, it seemed difficult to achieve unanimous consensus, and the main goal of the exercise was to record diverging positions and the scientific arguments behind them. In fact, the debate showed that some degree of consensus can be achieved on most basic controversial matters, and that the main reason behind remaining divergences is the objective uncertainty that still surrounds a number of issues. Accordingly, this document presents the main outcomes of the debate without explicitly attributing the various statements to individual authors1.

1 Contributions to the debate were made by: Rainer Friedrich, Stefan Hirschberg, Wolfram Krewitt, Richard Loulou, Stale Navrud, Philipp Preiss, Milan Scasny, Denise Van Regermorten


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2. Building consensus around the NEEDS results

NEEDS has generated, among other results, a wealth of new evidence that is directly relevant to policy decisions. Irrespective of its variety and complexity, the basic process followed for the production of numerical outputs can be schematised in a fairly standard manner along the following logic:

For instance, in NEEDS:

While controversial issues usually emerge in the last steps of this chain, when results (e.g monetary values of external costs) are published and subject to interpretation (e.g. technology ranking), the first challenge is to understand whether disagreements on results (or their interpretation) actually mask/reflect divergences on the early stages of the process, i.e. assumptions or/and methodologies.

A first important conclusion of the debate is that there is a generalised consensus on the methodological approaches adopted in NEEDS and on the analytical tools developed and used to operationalise these methodologies, notwithstanding the plurality of methodological approaches that have been used in NEEDS and the fact that in some instances different approaches have been used “in competition” (e.g. monetisation of risk Vs qualitative appraisal of stakeholders’ risk perception).

As an immediate consequence, numerical results are also broadly consensual, to the extent that they reflect the consensus on methodological approaches. In the few cases where disagreements on results have emerged (e.g. the private costs of selected energy technologies, the preferred values for GHG costs, particularly in the short-medium term), these appear to reflect the difference in specific assumptions (e.g. the future performance of advanced technologies, the dynamics of individual preferences and the preferred value of discount rates to be subsequently applied for the costing of selected externalities). In fact, it appears that these (moderate) disagreements reflect, in turn, the unavoidable uncertainty attached to any prediction, which is an important component of any scientific debate, and has been explicitly tackled in NEEDS, with dedicated project tasks and Deliverables.

Assumptions & input data

Characteristics & performances

of future technologies

Methodologies & tools

LCA impact pathway

Results

Private costs, external costs

Interpreta-tions

Technolo-gies

ranking


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Ultimately, controversies appear to concentrate in the very last step of the process, i.e. for what concerns the meaning and the interpretation of selected results, and in particular the use that can/should be made of the NEEDS numerical outputs to derive a possible ranking of future energy technologies. The issue of ranking is explicitly addressed in a further section of this document.


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3. Hot topics and controversial issues

3.1 Uncertainties and limitations

As previously remarked, all values about the future are uncertain, and a systematic assessment of uncertainty ranges - and of the extent that these affect the validity of the numerical results - is an integral part of any serious research. When it comes to assessing the uncertainty attached to the monetary valuation of external costs, three main factors can be broadly identified:

• an insufficient knowledge of physical processes (e.g. effects of global warming, ecosystem changes and internal feedbacks, etc.)

• the difficulty in accurately predicting the future evolution of ‘exogenous’ factors such as e.g. long-term economic growth, the dynamics of individual preferences, etc.

• the limitations of the state-of-the-art scientific methods, for what concerns both the accurate modelling of physical phenomena (e.g. airborne pollutants dispersion, ecosystem changes etc.) and the monetary valuation of their impacts (e.g. the social value of biodiversity, of visual intrusion etc.)

Finally, the robustness of external cost values is affected by the considerable variability of specific cost items across regions and sites, and the intrinsic limitations of the methods and tools for value transfer.

NEEDS has contributed to reducing these uncertainty factors in many areas, generating new knowledge, improving the accuracy of models, extending the coverage of essential data and testing alternative approaches and alternative assumptions through sensitivity analyses.This notwithstanding, uncertainties remain in a number of areas, which may contribute to explaining some diversities in the final interpretation of results, reflecting the legitimate subjectivity of the experts (e.g. “are optimistic scenarios too optimistic?”) in those areas where science does not (yet) provide clear and certain answers. The following paragraphs briefly illustrate the outcome of the NEEDS debate on those issues where some degree of controversy still remains.

3.2 Private costs of future energy technologies

The degree of uncertainty affecting the future values of technology costs increases with the pace and magnitude of the anticipated technological improvement: new and emerging technologies are thus more affected by uncertainty than mature technologies for which learning curves can already incorporate past observations. Among the EPG technologies for which NEEDS has conducted new and detailed assessments, those more affected by uncertainty are therefore PV, CCS, wave and tidal energy technologies and Generation IV nuclear.

In fact, the future development of private costs of a given technology depends on a range of socio-economic conditions (e.g. market introduction schemes, policy targets, R&D expenditures, etc.). Variations can be significant, and sensitivity analysis is therefore of the essence. NEEDS (and specifically the LCA stream of research) has adopted a systematic approach to sensitivity


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analysis, whereby for all energy technologies three alternative development scenarios have been devised: (i) pessimistic, (ii) optimistic/realistic and (iii) very optimistic, which notably differ in terms of investment costs assumptions (higher costs for pessimistic scenarios and lower costs for optimistic ones).

The results indicate that the differences in private costs projections between ‘pessimistic’ and ‘optimistic’ technology scenarios are indeed significant. Whatever ranking based on the NEEDS results will clearly reflect these ranges.

3.3 Climate change

Climate change damage costs are known to be particularly uncertain, reflecting various factors, and notably (i) the currently insufficient scientific knowledge about the physical phenomena associated to climate change and the subsequent value of physical impacts (health effects, impacts on crops and ecosystems, impacts of extreme weather events, increased needs of air cooling and decreased needs of heating), and (ii) the very long term horizon of climate change effects and the subsequent very high sensitivity to the future evolution of individual preferences, discount rates etc.

Accordingly, the range of values considered as ‘reasonable’ by scientists within (and outside) NEEDS still covers several orders of magnitude. Moreover, CO2-emission characteristics differ widely across technologies, and as a result the total value of external costs associated to certain technologies (e.g. fossil fuels) is in fact dominated by GHG-related costs, while those same costs play a marginal role for other technological options (e.g. nuclear and selected renewables). In the NEEDS context, this considerable difference in the weight of GHG costs across energy technologies is a major additional obstacle, which affects not only the reliability of the absolute cost values but, possibly more importantly, the robustness of any attempt to rank technologies based on their total external costs.

3.4 Full coverage of relevant externalities

While it is clear that any assessment and decision to be taken in the current context can only be based on available and accepted knowledge, it is also largely recognised that for a number of external cost categories a reliable estimation is so far beyond the reach of state-of-the-art research. These cost categories – which primarily include costs associated to a variety of risks – are summarised in the table below:

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COST CATEGORY

BAU

MAIN OBSTACLES TO CALCULATION

Assessment of ‘Damocles-risks’

No agreed methodology is so far available to estimate these risks

Risk associated to terrorism

The basic information that would be required to estimate these risks is in general not publicly available

Risk associated to CCS (and in particular risks associated to possible re-leases of CO2)

Due to the recently emerging character of CCS options, almost no information is so far available on either probabilities or damagesblicly available

Security of supply

(especially for natural gas)

No agreed methodology is so far available to estimate these risks

Visual annoyance

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Most of the obstacles identified above are likely to be progressively removed in the future, thanks to additional research and data collection, some of which is already underway (e.g. on security of supply). Transaction costs to generate reliable cost figures may nevertheless remain high e.g. for visual annoyance costs whenever site-specific assessments (WTP or other CVM to elicit individual preferences) are required.

As for Damocles risks, however, the difficulties are of a more conceptual nature, and it does not seem realistic, at least in the short term, to achieve consensus on a mainstream methodology to tackle the general issue of risk aversion in an analytical and quantitative manner. We know for example that in Switzerland the closer to Nuclear Power Plants people live, the lower their risk aversion towards nuclear; the further they are from the plant the higher their risk aversion. In other words those most exposed are least averted. And why are people not risk averted towards large Hydro Power Plants (considering the poor record of hydropower accidents world-wide?

Eventually, alternative/complementary approaches are necessary, which NEEDS has experimented (particularly in the research stream dealing with stakeholders’ perspective), with a preliminary set of results that shed a stimulating light on this highly sensitive issue (to what extent is it possible to explain the divergences between ‘objective’ results derived from the state-of-the-art analytical methods and the ’subjective’ results derived from stakeholders’ surveys? Are these divergences primarily the consequence of irrational behaviour and ideological biases or/and are they mainly due to the insufficient lack of solid scientific knowledge? And to what extent are these two shortcomings feeding each other?)

In the short term, what matters is to understand whether the current limitations affect the ‘policy support power’ of the available results. It is quite obvious that an incomplete coverage of potential impacts favours those technologies which cause impacts that cannot be quantified when external costs are used as the basic indicator for comparative ranking. If e.g. risks from long-term storage of CO2 are not known or cannot be quantified in monetary terms, external costs shall not be used as a basis for comparing CCS technologies against any other energy technology.

In fact, there appears to be a reasonable consensus that the possible (future) inclusion of additional external costs such as visual intrusion or security of supply is not likely to modify the current estimations in a substantial manner, and that technology ranking3 will hardly be affected. The main exception, once again, are external costs associated to specific risks, and in particular to the Damocles risk, for which the current lack of an agreed approach to deal with risk aversion makes it difficult to gauge the possible consequences of its inclusion.

2 Risk is calculated as the product of (i) the probability of occurrence of an accident (or of other unwanted/unpredicted events entailing negative consequences) by (ii) the magnitude of the damage in case the negative event occurs. Damocles risks are those associated to technological options for which the probability is low or very low while the potential damage is large or very large. Typical examples are nuclear plants or, in a different sector, air travel.

3 The issue of ranking is discussed in a further section of this document


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3.5 Back-up costs

A complete social cost accounting framework should include all cost categories that can analytically be attributed to the various technology options. Back-up costs (i.e. those costs that must be faced to ensure that energy supply will be guaranteed at the desired level even in the event of unexpected plant breakdown/closure) should therefore be considered along with other private and external costs. The issue here is not so much to calculate the value of back-up costs, but rather to attribute them to specific energy options: the efforts required for ensuring firm capacity depend on the overall configuration of the supply system and can hardly be allocated to a single technology. More generally (as further discussed in this document), the efficiency of the energy system is affected in many ways by the qualitative and quantitative mix of energy sources, and by their spatial and temporal organisation.

3.6 Social acceptance

A policy relevant comparison of energy technologies is not possible if the indicator(s) used to compare them do not properly address key issues affecting societal acceptance of a given technology, and it so happens that social acceptance is particularly important precisely for those factors that are most affected by the current methodological limitations (e.g. risks associated to nuclear accidents, to CCS leakages etc.).NEEDS has made a significant step forward in this area with the development of an original approach, based on a novel set of indicators (notably including energy-specific social indicators alongside with economic and environmental ones) and on Multi Criteria Decision Analysis (MCDA).

3.7 Variability and transfer

Site dependence of many external cost categories is a well-known problem, which also affects different energy technologies in different ways. Renewable Energy Sources (RES) are in general considered to be most affected by this variability: for instance, NEEDS has allowed to confirm that the impacts of wind turbines or wind farms on landscape are the biggest barrier in the Czech Republic, while it is not the case in North Africa where wind farms are mostly installed in deserted areas. Significant variability can also be found for private costs, e.g. in relation to the need to build dedicated/new transmission lines for grid connection of isolated RES plants.NEEDS has developed and formalized a structured methodology for value transfer, and despite some remaining limitations (e.g. the above mentioned example of visual annoyance), its application within the project has proved its robustness and has allowed to significantly extend the geographical coverage of the available datasets on external costs.

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4. Technology ranking: the ultimate challenge?

Eventually, the debate that took place in the final stages of NEEDS has shown that the one area where controversies persist is technology ranking. While it seems only natural that the abundance of numerical evidence produced and the systematic comparison it allows of technology performances would ideally lead to some kind of ranking, disagreements remain on the ranking-oriented interpretation of such evidence. In fact, as discussed below, the real issue is not only – and in fact not so much – on whether the NEEDS results are ‘good enough’ to allow for technology ranking, but rather on whether it makes sense to attempt any ranking that would be solely based on the individual merits of energy technologies.

Indeed, a technology ranking based on the monetary valuation of social costs (private costs plus damage costs) can be used to issue statements regarding the efficiency of individual technologies and to support recommendations about which technologies should be preferred in a future energy mix. However, by no means this directly leads to the conclusion that only the technology with the lowest social costs should be used.

Technology ranking is not such a solid concept, because technologies are not always in a situation of pure competition (they are not pure substitutes). In the Power generation sector for instance, it is often found that technologies A and B are partly complementary, and partly competing. This is due to the seasonal and diurnal characteristics of each, and to the difficulty of modulating their production to follow the load curve. For example: to say that Wind turbines are “better” or “worse” than some baseload plant is meaningless, because it ignores the essential fact that Wind turbines cannot fully replace baseload plants. More sensibly, one should evaluate and compare bundles of technologies, rather than individual technologies. For instance, a bundle consisting of wind turbines + large dam hydro plant could be compared with a bundle consisting of CSP + biomass plant. Some bundles may combine more than two technologies (e.g. Nuclear + gas turbine + pumped storage). Unfortunately, the number of possible bundles grows very rapidly and therefore becomes hard to even enumerate. This is precisely why integrated energy models (such as the TIMES model developed and extensively applied in NEEDS) are useful, since they can select optimal bundles without having to enumerate them explicitly.

Technology ranking is a static concept. External costs estimates generated by NEEDS through the improvement and application of the methodology originally developed in ExternE, as well as any technology ranking based on such estimates, are correct only at the margin , i.e. in terms of being added to an existing baseload energy system. What is being estimated are (averaged) marginal external costs, which are therefore highly – but exclusively - relevant when discussing a (marginal) change to an existing bundle of energy technologies.


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Ranking technologies is as solid as the methods used for ranking and the data used in the implementation. Any method and dataset - and this applies to all the analytical frameworks used in NEEDS (LCA, Impact Pathway Approach, energy-economic optimisation models, MCDA) - is subject to limitations and uncertainties of different nature. Rankings based on these methods will obviously reflect their limitations and uncertainties.

• LCA analyses physical entities (inputs and outputs of processes) and therefore primarily deals with variables that can be observed and measured, which increases its credibility. In NEEDS, LCA has been developed in a highly innovative direction, whereby processes have been analysed not only based on their present, known characteristics, but also in the perspective of their future evolution (time- and scenario-dependent). While adding valuable insights to the discussion about future energy systems, this additional dimension of LCA clearly opens the door to uncertainties that are typical (and unavoidable) of any foresight exercise. The heated debate on the dynamics of private costs for selected emerging tech-nologies is a clear illustration of this phenomenon.

• Monetary valuation of external costs (typically carried out along the Impact Pathway Ap-proach – IPA) generates values of social costs and benefits that can then be directly added and compared in the framework of e.g. Cost Benefit Analyses, or Green Accounting prac-tices. It is based on the bottom-up estimation of actual damage costs (for which it clearly depends on the availability of high quality LCA data), and has the major advantage of providing results that are expressed in one and the same unit of measure (€). Its limitations primarily arise from the difficulty in measuring selected cost categories, thereby opening the door to possible criticisms about the complete coverage of all costs and benefits.

• Integrated energy models aim at the identification of optimal energy mixes by modelling the interaction over time between technology characteristics, resource availability, technol-ogy costs (both private and external), prices, as well as a variety of policy dependent vari-ables and constraints like capacities for building new power plants, emission caps, policy targets regarding renewable energy, etc. The optimal mix(es) found by such models will typically depend on the scenario being simulated, on the time period considered, and on the country being simulated. As for limitations, it can be argued that optimisation should not only be based on costs.

• The MCDA approach (especially as applied in NEEDS) has a much broader scope than LCA or External cost valuation. First, it accommodates the most essential LCA-results; sec-ond, it accommodates the dominant contributors to external costs (global warming and health effects); third, it treats various types of risks in an explicit manner; fourth, it accom-modates social concerns (risks being one example) that partially cannot be treated based on natural sciences; fifth, it deals with practical policy relevant issues such as operational aspects and security of supply (though admittedly in a much simplified manner that could be further advanced). The most important difference between MCDA and other approach-es is that the earlier is a discursive approach; the approach as such will not resolve major controversies but gives the opportunity for representing explicitly the controversial aspects, dealing with them in a structured manner, increasing the sensitivity of stakeholders and decision-makers to strengths and weaknesses of technologies, helping to understand own priorities and guiding the debate on very complex issues.


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The table below summarises the main strengths and limitations of the 4 analytical frameworks developed and applied in NEEDS.

STRENGTHS LIMITATIONS

BAUComplete account of inputs and outputsCan accommodate time- and scenario-o-dependenceProvides fundamental input to external cost valuation

Uncertainties associ-ated to long-term dynamics of private costsIndirect link to decision making process

All results in one and the same (monetary) unitBased on real damage costsCan accommodate sensitivity to critical parameters (value of life, costs of climate change, etc.)

Complete account of inputs and outputsCan accommodate time- and scenario-o-dependenceProvides fundamental input to external cost valuation

LCA

External cost valuation

Integrated energy models

Accommodates inputs from LCA and External costs valuationExplicit representa-tion of risk and other social concernsProvides an effective and comprehensive platform for dialogue

MCDA


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If finally appears (and this was in fact one of the founding motivations of the NEEDS Integrated Project!) that none of the individual approaches can, alone, generate a straightforward ranking of energy technologies, while their combined use provides a variety of inputs that are directly relevant (and usable) to policy making. In summary:

• the fact that ranking methods are not capable to cover all the aspects of interest is not a valid argument for not using them;

• technology comparison through social costs does not lead to an absolute ranking, but rather one that (only) incorporates all quantifiable criteria;

• rankings based on social costs cannot substitute models that take into account a wider set of variables and constraints. On the other hand, the comparison of the average social costs of different technologies can be used to iteratively crosscheck the model results e.g. to ascertain whether the introduction of certain technologies can be considered ‘reasonable’;

• the differences of opinion about the use of total costs as an aggregated indicator of tech-nology performance are nothing new. This has been one (among several) motivations behind the inclusion of MCDA in NEEDS, as an additional framework of assessment. The results well reflect these issues and the impact of factors not included in the total cost ap-proach and emphasize the need of scientifically guided/supported discursive processes with stakeholder involvement;

• transparency in the presentation and explanation of the results of such a complex and multifaceted project as NEEDS is more important than full convergence, when one aims at building the trust of decision makers.


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5. So: how do energy technologies ultimately compare?

Despite the various caveats highlighted in the previous section, a wealth of new, significant evidence is available from NEEDS on the absolute and relative performances of energy technologies, which should be put in perspective.

At the outset, one should recognize that nuclear plays a special role in this debate, as it is well known that the controversies about ranking are usually triggered by the inclusion of nuclear power in the basket of compared technologies. Some argue that nuclear energy should not be explicitly compared (social costs-wise) to other electricity generation options, owing to the imbalance created by the risk aversion factor. While the opinions within the NEEDS team diverge on this specific issue, a number of statements can be made that reflect the outcome of the final NEEDS debate:

• Social costs figures provide evidence on those cost categories that lend themselves to quan-tification and monetization;

• Nuclear energy is clearly ’favoured’ by a direct comparison of quantifiable social costs, in that the Damocles risk is not included;

• The Damocles risk associated to nuclear is however not the only cost that is currently unac-counted for: similar risks should be estimated for other energy options for which it is likely to be also large (e.g. hydropower), and other risk typologies should also find their place in the social cost accounting frameworks, such as e.g. those possibly associated to the cur-rently less known CCS options);

• On the other hand, there are other external cost categories that are higher for nuclear than for competing technologies: this is typically the case for up- and down- stream costs, which are mostly negligible for the majority of energy options (at least when compared to the external costs arising from the process itself), while they are significant in the nuclear case. For instance, NEEDS has estimated that external costs arising from the operation of exem-plary power plants in 3 Central and Eastern European Member States is about 0.03-0.06 €c/kWh (varies with plant, location and year), while they can be as high as 0.12-0.15 €c/kWh across the entire lifecycle;

• Additional ‘distortions’ arise from the large uncertainty still remaining on the costs associat-ed to climate change and GHG emissions, whose relative weight varies enormously across technology options;

• One possible option would be to explicitly compare only those energy technologies that exhibit similar orders of magnitude for the various cost categories, leading e.g. to compare fossil fuel with biomass powered plants on the one hand, while comparing nuclear with RES on the other;


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Other considerations are however also important when attempting comparisons based on social costs:

• new power lines and their impacts, including visual intrusion and ERF (both documented and loss of well-being due to fear of impacts) largely depend on the energy technology used (and on the overall energy technology mix) . The need to build powerlines is in gener-al higher for renewables like hydro and wind (which have to be developed where the wind and hydro resources are located) than for fossil fuels and nuclear power plants (which can be built closer to where the population and industry needing electricity are located).

• the ExternE methodology was originally developed to deal with external costs from fossil fuel cycles and emission to air and their impacts on health, agriculture and materials. In spite of the developments within the Externe Project Series and NEEDS to better deal with other sorts of impacts than emissions to air (e.g. biodiversity as pioneered by NEEDS), the original focus on health impacts, agriculture and materials from air emissions is still the most advanced and reliable part of the external costs estimates. Thus, external costs estimates for renewables like hydro and on-shore wind (for which pollutant emissions are almost negligible) are subtotals to a much larger degree than for fossil fuels.

In any instance, provided the information on what is really accounted for is clearly presented, there is no scientific reason to refrain from the publication of results.

Ultimately, both the LCA and the External Cost Valuation approaches developed in NEEDS have delivered results that are policy relevant per se in terms of technology comparison. As for the outcome of the Integrated Energy Modelling– which has fully incorporated the inputs from both approaches – it was not meant to (and does not) provide evidence in the form of an explicit comparison of energy technologies, but rather a rich set of optimal energy mixes associated to a several differentiated scenarios and a number of variants thereof. When it comes to the final word on energy technology comparison, it seems therefore appropriate to primarily refer to the findings of the MCDA activity, which also accommodates the inputs from LCA and External Cost valuation, while relying on a broader assessment platform that explicitly represents those factors that are not (so far) amenable to consensual monetization:

• the individual preference profiles have a decisive influence on the MCDA-ranking of tech-nologies; this influence is particularly pronounced for technologies that have a highly differentiated profile, i.e. that show top performance on a number of indicators but also weak relative performance on some other. Such technologies may be controversial; nuclear energy is the most pronounced example having these features.

• thus, given equal weighting of environmental, economic and social dimensions and em-phasis 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 strong disadvantage of nuclear energy. This emphasizes the need of further technological devel-opments towards mitigating the negative impacts of these issues.


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• 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 the inclusion of a variety of social aspects not reflected in external costs. Thus:

• nuclear energy ranks in MCDA mostly lower than RES, which benefit from much improved economic performance

• RES whose production costs are assumed to be strongly reduced (drastically in the case of solar technologies), have a rather wide range of total costs, with biomass technologies (es-pecially poplar) on the high side and solar and wind on the low. The latter have total costs comparable or even lower than fossil, depending on which value is used for the highly uncertain CO2-damage costs;

• in the MCDA-framework RES show the most robust behaviour, i.e., in comparison to fossil and nuclear options, lower dependence of ranking on the differences in preference pro-files; this applies especially to solar technologies;

• 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 a ranking comparable to nuclear;

• the performance of CCS is mixed, i.e. in MCDA fossil technologies with CCS may rank bet-ter or worse than the corresponding technologies without CCS, depending on which spe-cific CCS option is used. Total costs justify coal with CCS when the costs of CO2-damages are in the upper range of values.

• 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.


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6. Conclusions

As repeatedly stated, the value of the NEEDS results goes well beyond hypothetical rankings of energy technology options, not least owing to the largely recognised meaninglessness of any ranking that would rely on a one-dimensional aggregated indicator.

Technology comparisons can be made in a variety of ways, depending notably on the background context (e.g. the structure of the existing energy system, the level of the existing scientific and industrial know how) and on the scope and scale of the decision at stake (e.g. identification of priorities for long term research, or short term investment decisions, or taxation policies, or target setting in the area of GHG emission, air quality, etc.)

NEEDS has produced abundant evidence that feeds into the entire range of problematics and policy decisions. It has done so by (i) improving the scientific knowledge in many critical areas, (ii) applying new knowledge, models and tools to the actual calculation of a wide range of quantitative results (iii) supplementing the quantitative evidence with discursive – though analytical – assessments.

Broad consensus has been achieved within the NEEDS community on both the validity of the methodologies and on the importance of integrating different analytical frameworks to increase the coverage and the robustness of each individual approach.

Some degree of controversy persists, not so much on the numerical results generated by each stream of research, but rather on their ‘consensual interpretation’, particularly when it comes to the difficult challenge of establishing a univocal technology ranking.

Other remaining divergences mainly reflect the current state of uncertainty associated to some key parameters (e.g. costs of climate change) and the lack of solid approaches for the monetary valuation of risks.

Documents

Ne Energy Externalities Development for Sustainability · 2009-06-12 · analytical tools developed and used in NEEDS, ... The results presented by different Research Streams of NEEDS