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Social Costs of Innovative Electricity Generation Technologies in the Present and till 2050 Philipp Preiss, Rainer Friedrich and Volker Klotz Institute of Energy Economics and the Rational Use of Energy (IER) Department of Technology Assessment and Environment (TFU) Universität Stuttgart Tel.: +49(0)711 - 685-878 35, Fax.: +49(0)711 - 685-878 73, [email protected]
1 Abstract A consistent assessment of electricity generating technologies and a comparison of such technologies has to take into account not only the generation costs (private costs), but also the external effects associated with the generation, e.g. risks to human health, ecosystem damages, reduction of crop yields, material deteriora-tion, change in energy supply security, the effects of global warming and other effects. This paper provides new estimates on social costs of different electricity generation technologies operating in Germany, and in addition PV and concentrated solar power (CSP) in the Mediterranean area. Social costs are obtained by summing up external costs (i.e., monetary value of impacts on human health, crops, building materials, bio-diversity and costs due to climate change) and private costs, i.e. internal electricity generation costs. External costs are calculated applying the ExternE methodology (European Commission, 2005). This in-cludes the Impact Pathway Approach (IPA), which is a site specific bottom-up approach. First, the impacts and risks of an activity, here of generating electricity, are estimated. Therefore, life cycle inventory (LCI) data are applied, i.e. not only the operation phase of the technology but also up- and downstream processes like fuel supply, etc. are taken into account. Then, to make the different impacts comparable with each other and with private costs, these impacts are converted into a common unit by using a method derived from wel-fare economics, i.e. by measuring the willingness to pay to avoid a risk or impact. The derived damages, expressed as external costs, can be added and compared with other costs and other advantages and disadvan-tages. The list of investigated technologies includes nuclear and fossil fired power plants, renewable (PV, Solar Thermal (CSP), Wave & Tidal and Off-Shore Wind) and bio-fuel technologies. Results are provided for new (current state-of-the-art) technologies at present and for technologies that assumingly become available in 2025 and 2050. The data was derived within the integrated European project NEEDS (European Commis-sion, 2008b). Chapter 2 provides an overview of the methodology adopted for external costs calculation. Chapter 3 describes the methodology adopted for private costs calculations. Chapter 4 summarises the results of external and internal costs to social costs. Finally, in Chapter 5 some conclusions are drawn. Keywords: External Costs, Impact Pathway Approach, ExternE, Social Costs, Life Cycle Impact Assessment
2 External Cost Calculation External effects arise from the direct impacts of the economic activities of an economic agent A (e.g. enter-
prises, private and public budgets) on the production or consumption options of other economic agents B, if
that impact is not fully accounted for by the agent A. If these effects are negative they can be expressed as
external costs. The calculation of external costs was performed with the online tool EcoSenseWeb (Preiss
and Klotz, 2008).
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2.1 ExternE Methodology
The ExternE methodology (External costs of Energy (European Commission, 2005) and (ExternE Home-
page)) provides a framework for transforming impacts that are expressed in different units (e.g. global warm-
ing potential [CO2eq], human health impacts [DALY] or damage to the biodiversity due to acidification [loss
of biodiversity]) into a common unit, namely monetary values.
It has the following principal stages:
1) Definition of the activity to be assessed and the background scenario where the activity is embedded;
definition of the important impact categories and externalities.
2) Estimation of the impacts or effects of the activity (in physical units). The impacts are the difference
between the impacts of the scenarios with and without the activity. This is important in order to calculate
marginal impacts if non-linear effects are taken into account. Dispersion modelling is necessary in order to
allocate impacts to certain sources of emission.
3) Monetisation of the impacts, leading to external costs.
4) Assessment of uncertainties and sensitivity analysis.
5) Analysis of the results and drawing of conclusions.
2.2 The Impact Pathway Approach
The impact pathway approach (IPA) is used to quantify environmental impacts as defined above. The princi-
pal steps are illustrated in Figure 1.
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⇒ impact(e.g., cases of asthma due to ambient
concentration of particulates)
DOSE-RESPONSE FUNCTION(or concentration-response function)
⇒ cost(e.g., cost of asthma)
MONETARY VALUATION
DISPERSION(e.g. atmospheric dispersion model)
⇒ emission(e.g., kg/yr of particulates)
⇒ increase in concentrationat receptor sites
(e.g., µg/m3 of particulatesin all affected regions)
SOURCE(specification of site and technology)
DOSE
Dose-ResponseFunction
- Emission: specification of the relevant technolo-
gies and pollutants, e.g. kg of oxides of nitrogen
(NOx) per kWhel emitted by a power plant at a spe-
cific site
- Dispersion: calculation of increased primary and
secondary pollutant concentrations in all affected
regions
- Impact: calculation of the cumulated exposure
from the increased concentration, followed by calcu-
lation of impacts (damage in physical units) due to
this exposure using concentration-response func-
tions, e.g. cases of asthma due to increase in O3
- Cost: valuation of impacts in monetary terms, e.g.
multiplication by the monetary value of a case of
asthma.
Figure 1: The principal steps of an impact pathway analysis, for the example of air pollution
2.3 Technology Description
The NEEDS LCI data for the considered reference power plants are taken from (Krewitt, 2009) and
(Frischknecht, 2008). The technologies investigated within the NEEDS project are described in more detail
in the corresponding reports (listed in Table 1) of the different NEEDS partners.
Table 1: List ofreports on technical data, costs and LCI for each technology
Technical data, costs and life cycle inventories of advanced fossil fuels (Dones et al., 2008)
Technical data, costs and life cycle inventories of fuel cell power plants (Gerboni et al., 2008)
Technical data, costs and life cycle inventories of offshore wind farms (DONG Energy, 2008)
Technical data, costs and life cycle inventories of PV applications (Frankl et al., 2008)
Technical data, costs and life cycle inventories of solar thermal power plants (Viebahn et al., 2008)
Technical data, costs and life cycle inventories of biomass power plants (Gärtner, 2008)
Technical data, costs and life cycle inventories of nuclear power plants (Lecointe et al., 2007) Technical specification of reference technologies wave and tidal power plant (Sørensen and Naef, 2008)
In the calculation of the LCI data, the supply of materials and energy carriers, as well as the electricity mix
and transport services were considered for average European conditions.
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In case of CHP power plant there are two main products generated in the power plants: heat and electricity.
The emissions and resource use of the production process was allocated to these co-products based according
to their exergy.
2.4 Life Cycle Inventory (LCI)
The Life Cycle Inventory (LCI) is one phase of the Life Cycle Assessment (LCA) methodology, which is
standardised in the ISO norm series 14040 et seq. The norm ISO 14041 specifies the conduction of LCI cal-
culation. For each electricity generation technology a LCA analysis was performed. Figure 2 gives an over-
view of these processes and life cycle stages contributing to the life cycle of electricity generation.
The process of electricity generation is divided
into four sub-processes representing the life cycle
phases. The process fuel supply is relevant for
electricity generation technologies that are based
on hard coal, lignite, oil, natural gas, biomass and
nuclear energy.
Figure 2: Generic Structure of the LCI calculation on electricity generation
Detailed process chain analysis (including all direct and indirect emissions), the material and energy demand
as well as the waste and the release of emissions were identified and quantified. These results for the indi-
vidual processes are referred to the functional unit of one kilowatt hour (1 kWhel) of generated net electricity
(i.e. electricity, which is supplied to the grid) and summed up along the process chain. Within NEEDS sev-
eral different scenarios have been defined in order to provide LCI data for different technology developments
and configurations. These technology development scenarios are called Pessimistic (PE), Realis-
tic/Optimistic (RO), and Very Optimistic (VO).
The general assumptions valid for all datasets are the following:
Pessimistic (PE)
“Socio-economic framing conditions do not stimulate market uptake and technical innovations.”
- it is assumed that there is no technological development (i.e. the datasets are left unchanged) except for
transports (due to legal requirements) and electricity mixes
- the business as usual (BAU) electricity mix scenario is applied on European electricity supply.
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Realistic/Optimistic (RO)
“Strong socio-economic drivers support dynamic market uptake and continuous technology development. It
is very likely that the respective technology gains relevance on the global electricity market.”
- the pathway of technology development is as far as possible according to predictions and goals of the in-
dustry that seem reasonable to be achieved
- a “440 ppm CO2 electricity mix” scenario is applied on European electricity supply
Very Optimistic (VO)
“A technological breakthrough makes the respective technology on the long term a leading global electricity
supply technology.”
- improvements according to the optimistic-realistic scenario are introduced earlier
- a switch to cleaner energy generating technologies (e.g. oil to gas) is more common or more pronounced
- the enhanced renewable electricity mix scenario (Renew.) is applied on European electricity supply.
The different scenarios result in different LCI data because of e.g., different underlying energy mix and dif-
ferent assumptions regarding the possible development of technologies.
The LCI data are based on the climate change ‘440 ppm COeq stabilisation scenario’, as it basically repre-
sents current European policy targets.
Substances considered for external cost calculation:
NH3, As, Cd, CO2, Cr-IV, N2O, Dioxins, Formaldehyde, Pb, Hg, CH4, Ni, NOx, NMVOC, primary particu-
late matter (PPMcoarse and PPM2.5), SO2, radioactive noble gases, aerosols, C-14, Cs-137, H-3, Iodines, Kryp-
ton-85, Pb-210, Radon-222, Th-230, Uranium-238.
2.5 Physical Impacts
Impact with regard to human health, ecosystem damages, reduction of crop yields, material deterioration and
effects of global warming have been quantified.
According to the IPA the physical impact to the receptors can be calculated by multiplying the concentration
or deposition in each grid cell with a) the number of receptors, e.g. population or natural soil surface, and b)
by a factor (concentration response function) per unit of concentration or deposition. The impact over the
whole area of Europe is than summed up. Since the impact to human health due to the main primary air pol-
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lutants (NH3, NOx, SO2, NMVOC, PPMco and PPM2.5) and their corresponding secondary pollutants nitrates,
sulfates (SIA = secondary inorganic aerosols) and ozone contribute most to the external costs this category is
explained in more detail in the paragraph below. Impacts due to radio nuclides, heavy metals, and to ecosys-
tems, crop yields, and material are described in detail in (European Commission, 2005), (Ott et al., 2006) and
(Preiss et al., 2008).
2.6 Concentration-Response Functions (CRF) and Monetary Values for
Human Health Impacts
In Table 2 an overview over the different health endpoints and the corresponding CRF for particulate matter
(PM) and ozone is given. These are the most important and most reliable CRF provided by (Torfs et al.,
2007). Furthermore, the monetary values per health endpoints are shown. The risk and age group fractions
are already included and the CRF can be applied to total population. The reduced life time expectancy
[YOLL] (Years of Lost Lifetime) is the most important endpoint with regard to the share of external costs.
Table 2: Overview of the CRF for particulate matter (PM) and ozone and corresponding monetary values
Pollutant and corresponding endpoint
Physical impact per person per µg per m3 [1/(µg/m3)] unit
Monetary Value per case or per YOLL [Euro]
External costs per person per µg per m3 [1/(µg/m3)]
primary PM & SIA < 2.5µm Life expectancy reduction - YOLLchronic 6.51E-04 YOLL 40,000 2.60E+01net Restricted activity days 9.59E-03 days 130 1.25E+00Work loss days 1.39E-02 days 295 4.10E+00Minor restricted activity days 3.69E-02 days 38 1.40E+00
primary and SIA < 10µm Increased mortality risk (infants) 6.84E-08 cases 3,000,000 2.05E-01New cases of chronic bronchitis 1.86E-05 cases 200,000 3.71E+00Respiratory hospital admissions 7.03E-06 cases 2,000 1.41E-02Cardiac hospital admissions 4.34E-06 cases 2,000 8.68E-03Medication use / bronchodilator use (adult) 4.03E-04 cases 1 4.03E-04Medication use / bronchodilator use (child) 3.27E-03 cases 1 3.27E-03Lower respiratory symptoms (adult) 3.24E-02 days 38 1.23E+00Lower respiratory symptoms (child) 2.08E-02 days 38 7.92E-01
Ozone - as SOMO35 (sum of ozone means 35 over ppb) Increased mortality risk 2.23E-06 YOLL 60,000 1.34E-01Respiratory hospital admissions 1.98E-06 cases 2,000 3.95E-03
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Pollutant and corresponding endpoint
Physical impact per person per µg per m3 [1/(µg/m3)] unit
Monetary Value per case or per YOLL [Euro]
External costs per person per µg per m3 [1/(µg/m3)]
Minor restricted activity days (MRAD) 7.36E-03 days 38 2.80E-01Medication use / bronchodilator use 2.62E-03 cases 1 2.62E-03Lower respiratory symptoms excluding cough 1.79E-03 days 38 6.81E-02Cough days 1.04E-02 days 38 3.96E-01
Values are taken from (Preiss et al., 2008), derived from (Torfs et al., 2007), (Desaigues et al., 2007) and (European Commission, 2005). YOLL = Years of Life Lost.
Example:
Due to operation of a coal fired power plant in Germany SO2 is emitted. Due to dispersion and chemical
transformation with background NH3 into ammonium sulphate this leads to a concentration increment of
secondary particulate matter with aerodynamic diameter smaller than 2.5 µm (PM2.5), in all regions of Eu-
rope - for example, also in Austria. In a certain EMEP grid cell (ca. 50 km x 50 km) in Austria a population
of 250,000 people is living. The yearly average concentration increment due to the emission in Germany is
0.031 ng/m3 PM2.5 per tonne of SO2 emitted. We can calculate the years of lifetime lost (YOLL) and the ex-
ternal costs as follows:
YOLL per tonne SO2_Ger = 0.031 ng/m3 * 6.51E-04 YOLL/µg/m3/person * 250,000 people = 0.005 YOLL.
If we multiply the number of YOLL with the corresponding monetary value we get the external costs, i.e.
0.005 YOLL * 40,000 Euro per YOLL = 200 Euro per tonne of SO2 emitted in Germany - just for this one
grid cell in Austria.
However, this procedure is carried out for each grid cell in the whole of Europe and regarding all quantifi-
able impacts. This leads to an average cost of ca. 9,500 Euro per tonne of SO2 emitted in Germany. For other
countries and other substance also external cost values have been calculated.
2.7 Evaluation of Climate Change due to Greenhouse Gases (GHG)
The evaluation of greenhouse gas emissions is a crucial and highly controversial task. Within the NEEDS
project (European Commission, 2008b) a considerable share of resources has been used to drive a recom-
mendation for reasonable range of values based on most recent insights and scientific results.
The optimal point of greenhouse gas emissions is the one where the real marginal damage costs are equal to
the real marginal avoidance costs. However, these costs are not known and can only be estimated by differ-
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ent models. If the calculation of marginal damage costs is based on observable preferences of the society, i.e.
certain value choices regarding discounting and equity weighting the results are relatively small (Anthoff,
2007). However, the application of alternative value choices leads to a very large range of results. Moreover,
large uncertainties and possible gaps exist in the damage assessment. Therefore, and in order to account for
the precautionary principle the values in Table 3 have been recommended, which are based on marginal
avoidance costs based on certain agreed aims.
Scenario I reflects the ambitious policy targets for reaching a maximum of 2°C temperature increase, i.e.
reduction of ca. 20% CO2 in 2020 (compared to 1990) in the EU.
Scenario II is assumed to be more realistic and is directly inspired by the post-Kyoto scenario.
Both scenarios reflect marginal avoidance costs. It has to be emphasised that avoidance costs estimates re-
garding GHG have also wide ranges depending on future developments, emission targets and evaluation
settings and therefore, also have large uncertainties (Kuik et al., 2008).
Table 3: Recommended marginal external costs of GHG [Euro2005 per tonne emission CO2eq ] within
NEEDS
Year 2010 2025 2050
Scen I 23.5 51 198
Scen II 23.5 32 77
2.8 Uncertainties
External cost estimates are notorious for their uncertainties and many people have questioned the usefulness
of external costs. The first reply to this critique is that even an uncertainty by roughly a factor of three is
better than infinite uncertainty. However, a considerable share of uncertainties is not of a scientific nature
(data and model uncertainty) but results from ethical, so called value choices (e.g. valuation of lost life years
in different regions of the world, i.e. equity weighting) and uncertainty about the future. One approach to
reduce the range of results arising from different assumptions on discount rates, valuation of mortality, etc. is
to reach agreement on (ranges of) key values.
The uncertainties have been discussed and quantified for example in (Spadaro and Rabl, 2007) and (Spadaro
and Rabl, 2008). As a rule of thumb the range of possible results (67% confidence interval) is estimated as to
be ca. one third and up to three times the average values of external costs for main air pollutants. Regarding
the estimates for heavy metals or impacts due to climate change this factor is ca. 4-5.
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In order to show the influence of this uncertainty a factor of 2.5 and 0.4 will be applied to the external costs
except of the GHG and the influence on the ranking of technologies with regard to the social costs will be
shown.
The ExternE methodology aims to cover all relevant (i.e. not negligible) external effects. However, in the
current state of knowledge, there are still gaps and uncertainties. The purpose of ongoing research is to cover
more effects and thus reduce gaps and in addition refine the methodology to reduce uncertainties. The latest
developments have been achieved in the EU-projects NEEDS (European Commission, 2008b) and CASES
(European Commission, 2008a).
2.9 External Costs per kWhel
External cost per kWh electricity have been calculated multiplying the LCI data with generalised damage
factors “Euro per unit of emission” in a certain region or country, derived with the software tool EcoSen-
seWeb (Preiss and Klotz, 2008). For emissions due to operation damage factors for Germany have been ap-
plied. For all other life cycle stations average European (EU27) damage factors have been applied. In case
of solar thermal, i.e. concentrated solar power (CSP) the facility is assumed to be located in South Spain or
Algeria, because such a plant can not be sited in Germany as the direct solar radiation would not be suffi-
cient.
It has to be emphasised that the LCI data per kWh will vary for the technologies depending on the actual
location due to several factors, such as fuel supply chains but also efficiency of thermal power plants due to
different ambient temperatures. Moreover, it has to be noted that the efficiency of wind and photovoltaic
technologies significantly depend on the location where they operate because the availability of solar radia-
tion or advantageous average wind speeds influences directly the life time electricity output and therefore,
the emissions and also the private costs per kWh. For example, the solar radiation [kWh/m2] in Southern
Italy can be up to factor 2 larger than in Northern Europe.
2.9.1 Which External Costs have been considered?
Considered are releases of substances or energy (noise, radiation) into environmental media (air, indoor air,
soil, water), that cause - after transport and transformation - considerable (not negligible) harm to ecosys-
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tems, humans, crops or materials. Regarding climate change impacts damage costs and avoidance cost ap-
proach is taken into account.
Regarding accidents public and partly occupational risks caused by accidents have been considered by use of
expectation value (i.e. risk = potential outcome * probability).
Regarding insecurity of energy supply unexpected changes in availability and prices of energy carriers leads
according to (European Commission, 2008a) to small externalities.
Nuclear fuel cycle waste disposal and nuclear reactor accident
The assessments done by (European Commission, 1995) indicated the external costs (mEcu = 0.001 Ecu) of
waste disposal from waste disposal facilities. Low level waste (LLW) and high level waste (HLW) lead to
ca. 0.0302 mEcu/kWh with a 0% discount rate (DR) and 0.00000853 mEcu/kWh for a 3% DR. Regarding
nuclear reactor accident a range of 0.00235 - 0.104 mEcu/kWh for different reactor accidents was reported
(risk aversion is not included).
External Costs of Transport of Oil and Gas and Transmission of Electricity
The external costs of transport of oil and gas have been investigated within the NEEDS project (research
stream Rs1c) and results have been reported in (FEEM and NTUA, 2007).
The external costs of Transmission of Electricity has been investigated and described in (Vito, 2007).
Overall, the studies indicates that the externalities of transport of oil and gas, and the transmission of electric-
ity are likely to be small compared to those of power generation if they are expressed per kWhel consumed
for a whole country. Nonetheless, local effects can be quite significant to the concerned population.
2.9.2 Which Effects Are Not Included ?
As they are not considered as externalities:
- Effects on Employment
- Depletion of non-renewable resources (oil, gas, silicon, copper, etc.)
- Research and development (sunk costs)
- Income and damage distribution
- Local, site specific ecosystem damage (however, they are addressed and at least partly compensated
within the Environmental Impact Assessment).
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As they are considered as externalities but agreed methods or reliable information are not available,
though impacts on the result may be large:
- Assessment of risk aversion (so called Damocles risks, i.e. low probability- high damage risks) –
agreed method not available
- Risk of terrorism or proliferation – information not publicly available
- Visual Intrusion or annoyance (large variability, thus benefit transfer difficult)
- Risk analysis of carbon storage – no quantitative information yet available
- Security of supply for natural gas - methodology not available.
In general not included are unknown or unquantifiable impacts. However, as far as possible, critical issues
are at least mentioned and will be included in future research.
The external cost values for technologies in present and future years are costs in the corresponding year but
expressed in Euro2000 prices.
3 Private Costs Calculation Private costs are all costs per kWhel borne by the electricity producer, but without taxes (VAT) and subsidies.
They include investment, operation and maintenance, fuel, supplies and services, dismantling, waste dis-
posal, and in case of the necessity of provision of reserve capacity also back-up costs. The estimation and
projection of costs have been made for current plants, plants built 2025 and some educated guesses have
been made for 2050 by Markus Blesl and Steffen Wissel. Private costs have been also reported in (Blesl et
al., 2008) and in the NEEDS reports listed in Table 1. The current state and long-term development of gener-
ating costs is based on present best predictions about the evolution of the considered technologies and energy
price assumption up to 2050.
The lower end of the range of private costs represents values from the NEEDS (Table 1) realistic-optimistic
scenario. The upper bound uses
- for renewables: a realistic but less optimistic estimation
- for natural gas: 70% higher prices
- for CCS: a doubling of estimated costs for carbon transport and storage
- for nuclear: 20% (2025) respectively 80% (2050) higher investment costs.
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It has to be born in mind that all values, but especially the once for year 2050 are highly uncertain due to
long time span in the future.
Costs of building, maintaining and running different types of generating systems are included. To quantify
the full generating costs the Average Levelised Lifetime Generating Costs (ALLGC`s) are calculated for each
considered technology. The methodology calculates the generation costs on the basis of net power supplied
to the station busbar, where electricity is fed to the grid. The cost estimation methodology discounts the time
series of expenditures to their present values in a specified base year by applying a discount rate. A discount
rate takes into account that the time value of money does not have the same value as the same sum earned or
spent today. The levelised lifetime cost per kWh of electricity generated is the ratio of total lifetime expenses
versus total expected outputs, expressed in terms of present value equivalent. This cost is equivalent to the
average price that would have to be paid by consumers to repay exactly the investor/operator for the capital,
fuel expenses and Operation and Maintenance (O&M) expenses, inclusive the rate of return equal to discount
rate. The date selected as base year for the following calculations is Euro in year 2000. Hence, the normal
inflation is excluded from the calculations. However escalation of fuel prices and increased O&M costs, e.g.
due to higher staff and materials costs, are considered. The results taken for this paper are based on 5% dis-
counting. The introduction of the intermittent renewable energies, like wind or solar power, affects the elec-
tricity generating system. The inflexibility, variability, and relative unpredictability of intermittent energy
sources are the most obvious barriers to an easy integration and widespread application of wind and solar
power. Due to the fluctuation by producing energy with wind and solar plants a back-up technology is neces-
sary for compensating this. The back-up cost of not assured generating power of solar and wind plants can be
calculated with equations derived from (Friedrich et al., 1989).
What is important for strategic decisions about research and development is the possible development of
costs in the future, i.e. until 2050. The methodology used here is a combination of learning curves, i.e. a
trend projection of the past cost reduction into the future, and a technical analysis of improvements discussed
for each technology.
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4 Social Cost Calculation Social costs are private cost plus external costs. In Figure 3 the external cost of present new technology are
displayed. The category “HH_others” includes impacts due to heavy metals, radionuclide, formaldehyde and
dioxins, and is (due to the small amounts emitted), mostly negligible. The category “Land Use” evaluates the
potential loss of biodiversity due to land transformation. The category “CropsMaterialBioDiversity” displays
the impacts due emissions of SO2, NOx and NH3 which leads to acid deposition, eutrophication due to N
deposition and to ozone. “Human Health class” includes all effects due to main air pollutants towards human
health, as described in Table 2.
0 1 2
Lignite
Hard Coal
Gas CC
Nuclear
Bio fuelled ''typical' current
Fuel Cell' 'typical' current
Solar Thermal
PV tilted roof, sc-Si, retrofit
Wind offshore park 160MW
3[Euro-Cent2000 per kWh]
Greenhouse Gas
Human Health class
CropsMaterialBioDiversity
Land Use
HH_others
Figure 3: External cost of new technologies at the present (risk aversion, terrorism and visual intru-sion not included)
13
In Figure 4 the ranking according to the social costs of these technologies is displayed. The different contri-
butions to the private costs and to the external costs of each technology add up to the total social costs.
Please note the different scale of the x-axes [Euro-Cent2000 per kWh]. The external costs are distinguished in
GHG costs and all other external costs are sub summarised in the category “other Ext Cost”. The uncertainty
range indicates the uncertainty of these external costs.
0 5 10 15 20 25 30 35 40 45 50 55
Nuclear
Lignite
Gas Comb. Cycle
Wind Offshore
Biomass
Solar Thermal
Nat. Gas Fuel Cell
PV Roof, Retrofit
[Euro-Cent per kWh]
Invest Costs
Fuel Costs
O&M Costs
Back Up
GHG Costs
other Ext Costs
with uncertaintyrange
Figure 4: Ranking according to social costs of electricity generation technologies in the year 2010 (risk aversion, terrorism and visual intrusion not included)
In the following Figures the external costs and the social costs of typical average technologies in 2025 and
2050 are presented in diagrams.
The external costs are shown in Figure 5 and Figure 8. The external costs are based on LCI data correspond-
ing to the “440ppm” and Realistic / Optimistic scenario (RO).
The technologies are ranked according to the total external costs based on the greenhouse gas evaluation
“Scenario II”, i.e. the lower, more realistic external costs regarding greenhouse gas emissions. However, the
difference to the external costs if “Scenario I” values are used is added on top of the columns. It becomes
quite obvious that the external costs of fossil fuelled technologies are dominated by the costs of greenhouse
gases (mainly CO2). However, it is also shown that the combustion technology regarding biomass has very
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high external costs due to main air pollutants, i.e. the impact on human health. The external costs of solar
thermal, PV, wave and tidal, wind off-shore and nuclear power are all very small.
0
1
2
3
4
5
6
Biomas
s
Coal_C
ond.
Lignit
e_Con
d.
Lignit
e_IG
CC
Coal_I
GCC
Lignit
e_IG
CC_CCS
Coal_I
GCC_CCS
FuelCell
Gas
Gas C
CGT
FuelC
ell B
iogas
Gas C
CGT CCS
PV roof
Centra
l
PV Ope
n Cen
tral
Solar th
ermal
PV Ope
n Sou
th
Wav
e&Tida
l
Nuclea
r PW
R
Wind
off-s
hore
[Eur
o-C
ent 2
000 p
er k
Wh]
GHG_highGHGLand UseHuman Health otherCrops Material BioDiversityHuman Health main air pollut
Figure 5: External costs in 2025 (RO), operation in Germany (except of Solar thermal and PV South) (risk aversion, terrorism and visual intrusion not included)
In Figure 6 and Figure 7 the social costs for the year 2025 are displayed. In Figure 9 and Figure 10 the social
costs for the year 2050 are displayed
Columns show quantifiable social costs for technologies with the first year of operation in the year 2025 and
2050. However, both, private costs and external costs span a range of uncertainty. The external costs include
impacts to human health due to main air pollutants, greenhouse gases (GHG) and other quantifiable external-
ities. The external costs of GHG are based on certain values for 2025 and 2050, as shown in Table 3. The
blue bars exemplify the range of social costs based on the “best guess” of external costs plus the lower and
the upper range of private costs. The red lines indicate the uncertainty range of external costs of non-
greenhouse gases. This influence of the uncertainty of the non-GHG is demonstrated by the application of
factor of 2.5 for the upper and 0.4 for the lower value. The range of private costs is especially large for the
PV technologies.
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0
5
10
15
20
25
30
35
FuelCell
Gas
PV roof
Centra
l
FuelC
ell B
iogas
Biomas
s
PV Ope
n Cen
tral
Solar th
ermal
PV Ope
n Sou
th
Coal_C
ond.
Gas C
C CCS
Coal_I
GCC
Lignit
e_IG
CC
Coal_I
GCC_CCS
Lignit
e_IG
CC_CCS
Lignit
e_Con
d.
Wind
off-s
hore
Gas C
C
Wav
e&Tida
l
Nuclea
r PWR
[Eur
o-C
ent 2
000 p
er k
Wh]
upper range due to uncertainty of non-GHG external costs
range of social costs due to range of private costs
lower range due to uncertainty of non-GHG external costs
Figure 6: Social costs of electricity generation technologies in the year 2025 - operation in Germany - (except of Solar thermal and PV South) (risk aversion, terrorism and visual intrusion not included) based on GHG evaluation according to scenario II, i.e. lower, more realistic external costs regarding greenhouse gas emissions
0
5
10
15
20
25
30
35
FuelC
ell G
as
PV roof
Centra
l
FuelC
ell B
iogas
Biomas
s
PV Ope
n Cen
tral
Coal_C
ond.
Solar th
ermal
Lignit
e_IG
CC
PV Ope
n Sou
th
Coal_I
GCC
Lignit
e_Con
d.
Gas C
C CCS
Coal_I
GCC_CCS
Gas C
C
Lignit
e_IG
CC_CCS
Wind
off-s
hore
Wav
e&Tida
l
Nuclea
r PWR
[Eur
o-C
ent 2
000 p
er k
Wh]
upper range due to uncertainty of non-GHG external costs
range of social costs due to range of private costs
lower range due to uncertainty of non-GHG external costs
Figure 7: Social costs of electricity generation technologies in the year 2025 - operation in Germany - (except of Solar thermal and PV South) (risk aversion, terrorism and visual intrusion not included) based on GHG evaluation according to scenario I, i.e. lower, more realistic external costs regarding greenhouse gas emissions
16
In 2050 the LCI data of the different technologies is in general lower than in 2025. However, the monetary
value of impacts to human health and to biodiversity is increasing with increasing willingness to pay (WTP)
to avoid these impacts. It is assumed that the WTP increases proportional (corrected by a factor of 0.85 for
the income elasticity) with the rate of economic growth (which is assumed to be ca. 2% per year till 2030 and
after 1% per year till 2050).
0
2
4
6
8
10
12
14
16
Lignit
e_IG
CC
Coal_I
GCC
Biomas
s
FuelC
ell G
as
Gas C
CGT
Lignit
e_IG
CC_CCS
Coal_I
GCC_CCS
FuelC
ell B
iogas
Gas C
CGT CCS
Solar th
ermal
PV roof
Centra
l
PV Ope
n Cen
tral
Wav
e&Tida
l
PV Ope
n Sou
th
Wind
off-s
hore
Nuclea
r Gen
IV
[Eur
o-C
ent 2
000 p
er k
Wh]
GHG_highGHGLand UseHuman Health otherCrops Material BioDiversityHuman Health main air pollut
Figure 8: External costs in 2050 (RO), operation in Germany (except of Solar thermal and PV South) (risk aversion, terrorism and visual intrusion not included)
The technologies in Figure 8 are again ranked according to the total external costs based on the Scenario II,
i.e. the lower, more realistic external costs regarding greenhouse gas emissions. In future the external costs
of fossil fuelled plants are even more dominated by GHG emission. Even the technologies including CCS
cause considerable external costs due to emission of GHG. In Figure 9 and Figure 10 the social costs are
displayed.
17
0
5
10
15
20
25
30
PV roof
Centra
l
FuelC
ell G
as
Biomas
s
PV Ope
n Cen
tral
Lignit
e_IG
CC
Coal_I
GCC
FuelC
ell B
iogas
Gas C
CGT
Gas C
CGT CCS
PV Ope
n Sou
th
Coal_I
GCC_CCS
Lignit
e_IG
CC_CCS
Solar th
ermal
Wind
off-s
hore
Wav
e&Tida
l
Nuclea
r Gen
IV
[Eur
o-C
ent 2
000 p
er k
Wh]
upper range due to uncertainty of non-GHG external costs
range of social costs due to range of private costs
lower range due to uncertainty of non-GHG external costs
Figure 9: Social costs of electricity generation technologies in the year 2050 - operation in Germany - (except of Solar thermal and PV South) (risk aversion, terrorism and visual intrusion not included) based on GHG evaluation according to scenario II, i.e. lower, more realistic external costs regarding greenhouse gas emissions
0
5
10
15
20
25
30
Lignit
e_IG
CC
Coal_I
GCC
FuelC
ell G
as
PV roof
Centra
l
Gas C
CGT
Biomas
s
PV Ope
n Cen
tral
Gas C
CGT CCS
FuelC
ell Biog
as
Coal_I
GCC_CCS
Lignit
e_IG
CC_CCS
PV Ope
n Sou
th
Solar th
ermal
Wind
off-s
hore
Wav
e&Tida
l
Nuclea
r Gen
IV
[Eur
o-C
ent 2
000 p
er k
Wh]
upper range due to uncertainty of non-GHG external costs
range of social costs due to range of private costs
lower range due to uncertainty of non-GHG external costs
Figure 10: Social costs of electricity generation technologies in the year 2050 operation in Germany - (except of Solar thermal and PV South) (risk aversion, terrorism and visual intrusion not included)
18
based on GHG evaluation according to scenario I, i.e. lower, more realistic external costs regarding greenhouse gas emissions
5 Conclusions In the following the conclusions based on these results are listed:
- The ranking of technologies according to the external costs is very different from the ranking according to
private costs only. However, the assumptions regarding private costs are crucial.
- Social costs differ from private costs and thus, the external costs influence the ranking of electricity gener-
ating technologies.
- The comparison of different technologies cannot only be based on comparison of direct pressures, i.e. emis-
sions at the site of the power plant operation because the different up- and downstream processes can con-
tribute to a considerable share to the total life cycle impact.
- The majority of the external costs are caused by emission of main air pollutants and greenhouse gases. The
external costs caused by emission of main air pollutants are mainly caused by impacts to human health. With
regard to the fossil fuelled technologies (natural gas, lignite and hard coal) SO2 and NOx are main contribu-
tors and less impacts are caused due emissions of primary particulate matter and NMVOC.
- The results provide important input for the comparison, discussion and integration of the different options
for electricity generation technologies. However, other aspects have also to be taken into account, such as
potential, net stability, resource consumption and availability, security of supply, public acceptance, etc.
- Nuclear, wind, run-off water, wave and tidal energy are electricity generating options with low external and
social costs. However, especially run-off water has nearly reached its potential.
- Fluctuating technologies need back-up capacity, e.g. coal or gas or alternative renewable.
- For nuclear (EPR now, Generation IV after 2030) and on-shore wind in some countries problems with the
acceptance might occur.
- Lignite, where available and coal will continue to play a major role, especially with CCS (if CCS turns out
to have low environmental and technical risks) unless the costs for transport and storage are higher than an-
ticipated and the level of ambition for climate protection is not too high.
19
- At least until 2025 electricity production with solar plants continues to have the highest quantifiable social
costs.
- In the 2050 future solar thermal systems in Mediterranean countries could be the next best option with high
potential – especially, if the climate protection goals are very ambitious and CCS is not working efficiently
or has a limited potential.
- Natural gas will only play a role replacing coal, if the price for gas (and oil) is expected to stay moderate,
however, without CCS.
- Bio-fuel has relatively high external and social costs. But still, the use of residual biomass in large plants
might be a favourable option.
The resulting social costs data provide a basis for the recommendation to use the potential of nuclear, wind
and hydropower as far as possible, however the potential of these technologies is limited. The analysis
shows, that the remaining electricity demand in the near future still should be met by using lignite and coal.
Depending on the stringency of the climate change aims these plants would be equipped with CCS (carbon
capture and storage) or not. The environmental advantages of PV are too small to compensate the very high
investment costs in Germany. With ambitious climate change aims and if CCS turns out to be less economi-
cally or technically feasible the import of electricity generated by a solar thermal systems in Mediterranean
countries will become an option.
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