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Economics of Global Warming
WP-EGW-02
Environmental CGE Modeling using two
Approaches - CCS and Transportation:
An Application to Europe
Stefanie Arndt, René Döring, Marika Geißler et al.
Final report of the study project: ‘What to Do with CO2?’ (Oct. 2006)
Dresden University of Technology Chair for Energy Economics and Public Sector Management
Chair of Energy Economics and Public Sector Management Dresden University of Technology
Department of Business Management and Economics
Environmental CGE Modeling using two
Approaches - CCS and Transportation:
An Application to Europe
Final report of the study project: ‘What to do with CO2?’
Authors: Stephanie Arndt, René Döring, Marika Geißler, Katrin Krämer,
Tim Leonhardt, Robert Miersch, Rico Neumann, Maria Nieswand,
Pia Scheibe, Christoph Scheier, Susanne Schmidt, André Schneider,
Anke Voigt, Lars Wieschhaus
Academic Advisors: Dipl.-Vw. Jan Abrell, Prof. Dr. Christian von Hirschhausen
Dresden, October 2006
EE²EE²
II
Environmental CGE Modeling using two
Approaches - CCS and Transportation:
An Application to Europe
Arndt, S., Döring, R. , Geißler, M., Kraemer, K.*, Leonhardt, T., Miersch, R., Neumann, R.,
Nieswand, M., Scheibe, P., Scheier, C., Schmidt, S., Schneider, A., Voigt, A., Wieschhaus, L.
*Corresponding author: Katrin Kraemer
E-mail: [email protected]
Dresden University of Technology
Dpt. of Business Management and Economics
Chair of Energy Economics
01069 Dresden
Abstract The European Emission Trading Scheme (EU ETS) launched in 2005 includes the CO2 emissions of
the energy and energy intensive sectors but not the CO2 emissions caused of the transport sector which
account for about 25% of the total CO2 emissions and are still rising. Because governments neither
know the abatement costs of each sectors nor the European allowance price, inefficiencies in
allocation of the allowances are resulting.
This raises the question what are the gains of including the transport sector into the EU ETS. The
European Commission considers integrating aviation in the EU ETS and plans to have a proposal at
the end of 2006. On national level there are on going discussions to extend the EU ETS by including
road traffic. The existing studies are based on partial equilibrium models and taking the allowance
price as exogenous. The MIT Emission Prediction and Policy Analysis (EPPA) replicate the private
transport in a general equilibrium model but without taking into account an allowance trading scheme.
In this paper we apply a Computable General Equilibrium (CGE) model for the EU 15 which
reproduces the EU ETS. We explicitly model aviation, private and public transport as well as freight
services. The possibility of carbon capture and storage is suggested as backstop technology in the
electricity sector. The model is implemented in GAMS / MPSGE using the GTAP 6 database. Further
transport data are collected of European statistics and fitted into the macro database by using the
method developed by Paltsev et al. (2005).
By integrating the transport sectors into the ETS the marginal abatement costs of the obliged sectors
will adapt which results in welfare increase. Due to the low short run gasoline price elasticity
(Graham, D. J., and S. Glaister, (2002)) the demand side reactions will be marginal.
III
List of Contents
List of Tables...........................................................................................................................VI
List of Figures ....................................................................................................................... VII
Abbreviations .......................................................................................................................VIII
Symbols....................................................................................................................................XI
1 Introduction ....................................................................................................................... 1
1.1 The Institutional Framework in the Context of ETS ............................................ 1
1.1.1 Kyoto Protocol ...................................................................................................................1 1.1.2 The Legal Basement of the Emission Trading ...................................................................2 1.1.3 Further Legal Arrangements...............................................................................................2 1.1.4 Implementation in Europe ..................................................................................................3
1.2 Economic Impacts of Separating Transportation from a Cap-and-Trade
System ....................................................................................................................... 3
2 Carbon Capture and Storage Technologies .................................................................... 5
2.1 Introduction .............................................................................................................. 5
2.2 Technologies .............................................................................................................. 5
2.2.1 Capture ...............................................................................................................................7 2.2.1.1 Post-Combustion Capture ..........................................................................................7 2.2.1.2 Pre-Combustion Capture............................................................................................9 2.2.1.3 Oxy-Fuel Combustion..............................................................................................10 2.2.1.4 Other Future Concepts .............................................................................................11
2.2.2 Storage..............................................................................................................................15 2.2.2.1 Transportation..........................................................................................................15 2.2.2.2 EOR – Enhanced Oil Recovery ...............................................................................16 2.2.2.3 ECBMR – Enhanced Coal Bed Methane Recovery ................................................16 2.2.2.4 Depleted Oil and Gas Reservoirs.............................................................................17 2.2.2.5 Deep saline aquifers.................................................................................................17 2.2.2.6 Ocean .......................................................................................................................18
2.2.3 Conclusion........................................................................................................................19
2.3 The Economics of CCS........................................................................................... 19
2.3.1 Capture .............................................................................................................................20 2.3.1.1 Cost Model...............................................................................................................20 2.3.1.2 Conclusion ...............................................................................................................26
2.3.2 Transmission ....................................................................................................................27 2.3.2.1 Pipeline ....................................................................................................................27 2.3.2.2 Ship tankers .............................................................................................................28
IV
2.3.2.3 Conclusion ...............................................................................................................29 2.3.3 Storage..............................................................................................................................30
2.3.3.1 Geological................................................................................................................30 2.3.3.2 EOR / ECBM...........................................................................................................31 2.3.3.3 Ocean .......................................................................................................................33 2.3.3.4 Conclusion ...............................................................................................................35
2.3.4 Economic Outlook............................................................................................................35
2.4 Implementation of CCS in a Model ...................................................................... 36
2.4.1 Introduction ......................................................................................................................36 2.4.2 EPPA ................................................................................................................................36 2.4.3 MARKAL.........................................................................................................................38 2.4.4 MiniCam...........................................................................................................................40
3 The Transportation Sector - Structure and Introduction into an Emission Trading
System............................................................................................................................... 44
3.1 Technological Description of the Transportation Sector.................................... 44
3.2 CO2 Reduction Methods for the Transport Sector.............................................. 45
3.2.1 Technological Innovations ...............................................................................................45 3.2.2 Approaches for Emission Trading in the Transportation Sector ......................................47
3.2.2.1 Down-Stream Approach ..........................................................................................47 3.2.2.2 Mid-Stream Approach .............................................................................................47 3.2.2.3 Up-Stream-Approach...............................................................................................48 3.2.2.4 Valuation of the Different Approaches....................................................................48 3.2.2.5 Emission Trading Versus Fuel Tax .........................................................................49
4 Modeling........................................................................................................................... 50
4.1 General Equilibrium .............................................................................................. 50
4.1.1 A General Formulation of an Economy ...........................................................................51 4.1.2 The 2x2 Production Model – an Algebraic Formulation..................................................52 4.1.3 Concluding Remarks ........................................................................................................55
4.2 The Global Trade Analysis Project (GTAP) Model ............................................ 56
4.2.1 GTAP................................................................................................................................56 4.2.1.1 Accounting Relationships ........................................................................................57 4.2.1.2 Behavioural Equations.............................................................................................60
4.2.2 GTAP-E............................................................................................................................62 4.2.2.1 The Production Side ................................................................................................62 4.2.2.2 The Consumption Side ............................................................................................64
4.2.3 Incorporating the energy data in GTAP ...........................................................................66
V
4.3 The Emissions Prediction and Policy Analysis (EPPA) Model .......................... 69
4.3.1 The Structure of EPPA .....................................................................................................69 4.3.2 Equilibrium Structure .......................................................................................................71 4.3.3 Nesting Structure ..............................................................................................................71
4.3.3.1 Production Sectors ...................................................................................................72 4.3.3.2 Consumption Sector.................................................................................................73 4.3.3.3 Disaggregating the Transport Sector .......................................................................74
4.4 The Data Base ......................................................................................................... 75
4.4.1 Applied Data Base............................................................................................................75 4.4.2 Modelling of the Transport Sector ...................................................................................75
4.4.2.1 The Transport Sector in GTAP 6.............................................................................75 4.4.2.2 Transportation in the Household Sector ..................................................................76 4.4.2.3 Disaggregating the Petroleum and Coal Products Sector ........................................76 4.4.2.4 Disaggregating the Other Transport Sector .............................................................77
4.5 Model description ................................................................................................... 77
4.5.1 Nesting structures .............................................................................................................78 4.5.1.1 Production................................................................................................................78 4.5.1.2 Nesting Production Structure of Sectors excluding Transport.................................78 4.5.1.3 Nesting Production Structure of Transport Sector...................................................80
4.5.2 Consumption ....................................................................................................................80 4.5.3 Armington Aggregation....................................................................................................81
4.6 Implementation....................................................................................................... 82
4.6.1 GAMS ..............................................................................................................................82 4.6.2 MPSGE.............................................................................................................................82
5 Scenarios and Results...................................................................................................... 83
5.1 Baseline Model ........................................................................................................ 83
5.2 Scenario 1 – Trading System for Carbon Emission Rights excluding
Transportation Sector ........................................................................................... 83
5.3 Scenario 2 – Trading System for Carbon Emission Rights including
Transportation Sector ........................................................................................... 84
5.4 Results...................................................................................................................... 85
6 Conclusions and Outlook................................................................................................ 87
Appendix A: Transport.......................................................................................................... 88
Appendix B: GTAP Nomenclature ....................................................................................... 92
References ............................................................................................................................. 102
VI
List of Tables
Table 1: Performance of IGCC capture plants, studies adjusted........................................................... 22 Table 2: Performance of PC capture plants, studies adjusted ............................................................... 23 Table 3: Performance of NGCC capture plants, studies adjusted ......................................................... 25 Table 4: Cost of pipeline transmission of CO2...................................................................................... 28 Table 5: Estimated CO2 storage cost in geological formations............................................................. 30 Table 6: Estimated CO2 storage costs of EOR projects ........................................................................ 32 Table 7: Estimated CO2 storage cost for ECBMR projects................................................................... 33 Table 8: Cost Calculation of CCS technologies.................................................................................... 39 Table 9: Approaches to account CO2 .................................................................................................... 47 Table 10: Sectors and Resource Factors in the EPPA model................................................................ 72
VII
List of Figures Figure 1: The main technologies for carbon capture from power plants ................................................ 6 Figure 2: CO2 storage options ................................................................................................................. 7 Figure 3: The AZEP Process................................................................................................................. 12 Figure 4: The CLC process, MyOx (oxidized carrier), MyOx-1 (reduced carrier) ................................... 13 Figure 5: Solid Oxide Fuel Cell ............................................................................................................ 14 Figure 6: ZECA Process........................................................................................................................ 15 Figure 7: Natural Gas Price Development ............................................................................................ 26 Figure 8: Comparison of transmission cost........................................................................................... 29 Figure 9: Electricity production capacity .............................................................................................. 40 Figure 10: Electricity Generation by Type - Global 550 ppmv Case with CCS Technologies............. 42 Figure 11: One Region Closed economy without Government Intervention in GTAP structure ......... 58 Figure 12: Multi Region Open Economy in GTAP .............................................................................. 60 Figure 13: Production Structure in GTAP............................................................................................. 61 Figure 14: GTAP-E Production Structure ............................................................................................. 63 Figure 15: GTAP-E Capital-Energy Composite Structure.................................................................... 64 Figure 16: GTAP-E Government Purchases ......................................................................................... 65 Figure 17: GTAP-E Household Private Purchases................................................................................ 66 Figure 18: GTAP-E Production Structure with Carbon Tax................................................................. 68 Figure 19: GTAP-E Final Demand Structure with Carbon Tax............................................................ 68 Figure 20: The circular flow of goods and resources in EPPA ............................................................. 70 Figure 21: Structure of Services, Transportation, Energy Intensive and Other Industries.................... 73 Figure 22: Structure of the Electricity Sector........................................................................................ 73 Figure 23: Structure of the Household Sector ....................................................................................... 74 Figure 24: Nesting production structure of sectors excluding transport ............................................... 79 Figure 25: Nesting production structure of the transportation sector.................................................... 80 Figure 26: Consumption of private households .................................................................................... 81 Figure 27: Consumption of public household ....................................................................................... 81 Figure 28: Armington Aggregation for only one import region (our model)........................................ 81 Figure 29: Carbon emission cut and resulting welfare change in scenario 1 ........................................ 84 Figure 30: Carbon emission cut and resulting welfare change in scenario 2 ........................................ 85 Figure 31: Comparison of scenarios...................................................................................................... 85 Figure 32: Savings in welfare losses depending on different rates of overall emission caps................ 86
VIII
Abbreviations
AGE Applied General Equilibrium
APE American Petrol Institute
ASU Air Separation Unit
AZEP Advanced Zero Emission Power Plant
bbl barrel
BImSchG German act of immission control
(Bundes-Immisionsschutzgesetz)
BSA Burden Sharing Agreement
BtC billion metric tons of carbon
BTU British Thermal Unit
CBM Coalbed methane
CCS Carbon Capture and Storage
CDE Constant Difference of Elasticities
CDM Clean Development Mechanism
CES Constant Elasticity of Substitution
CGE Computable General Equilibrium
CLC Chemical Looping Combustion
CO Carbon Monoxide
CO2 Carbon dioxide
coe Cost of Electricity
CRS Constant Returns to Scale
CRTS Constant Returns To Scale
DEA diethanolamine
DEHSt German Emissions Trading Authority
(Deutsche Emissionshandelsstelle)
DMFC Direct Methanol Fuel Cell
e.g. for example
ECBMR Enhanced Coal Bed Methane Recovery
EGR Enhanced Gas Recovery
EHKostV German emission trading cost ordinance
(Emissionshandelskostenverordnung)
EJ Exa Joule
EOR Enhanced Oil Recovery
EPPA Emissions Prediction and Policy Analysis
ETP Energy Technology Perspective
IX
ETS Emission Trading System
EU European Union
GAMS General Algebraic Modeling System
GDX Gridded-Data-as-Text - Format
GHG Policy Analysis Greenhouse Gas
Gt Giga tons
GTAP Global Trade Analysis Project
GTAP-E GTAP-Energy
H2 hydrogen
H2O Water
IEA International Energy Agency
IET International Emission Trading
IGCC Integrated Gasification Combined Cycles
IGSM Integrated Global System Model
IPCC Intergovernmental Panel on Climate Change
JGCRI Joint Global Change Research Institute
JI Joint Implementation
kJ Kilo Joule
kPa Kilo Pascal
kWh kilowatt hour
LHV Low Heating Value
LNG Liquefied Natural Gas
LPG Liquefied Petroleum Gas
MCFC Molton Carbonate Fuel Cell
MCM Mixed Conducting Membrane
MCP Mixed Complementary Problem
MDEA methyldiethanolamine
MEA Monoethanolamine
MiniCAM Mini Climate Assessment Model
MIT Massachusetts Institute of Technology
MPSGE Mathematical Programming System for General
Equilibrium
Mt Mega tons
MWe megawatt electric
MWh megawatt hour
NAP National Allocation Plan
NGCC Natural Gas Combined Cycles
O&M Operations and Maintenance
X
OECD Organisation for Economic Cooperation and
Development
OGIP Original gas in place
OOIP Original oil in place
PC Pulverized Coal Power Cycles
PEMFC Proton Exchange Membrane Fuel Cell
PNNL Pacific Nothwest National Laboratory
ppmv parts per million by volume
ProMechG Projekt-Meschanismen-Gesetz
PSA Pressure Swing Adsorption
SACS Sleipner Aquifer for CO2 Storage
SAM Social Account Matrix
scm standard cubic metres
SO2 Solfur dioxide
SOFC Solid Oxide Fuel Cell
t ton
TEHG German act of Greenhouse gas emission trading
(Treibhausgas-Emissionshandelsgesetz)
TEHG Treibhausgas-Emissionshandelsgesetz
TOE Tons of Oil Equivalent
TSA Temperature Swing Adsorption
UBA German Federal Environmental Agency
(Umweltbundesamt)
UNFCCC United Nations Framework Convention on
Climate Change
ZECA Zero Emission Coal Alliance
ZuG German act of allocation (Zuteilungsgesetz)
ZuV German allocation ordinance
(Zuteilungsverordnung)
XI
Symbols
D(p) demand for goods given prices
DF(p) factor demand
K capital
L labor
M household income
pi price of good i
S(p) supply of goods
u utility function
w wage rate
w,r interest rate
xi good of firm i
αH consumption elasticity of household h
αi production elasticity of firm i
γH constant specified by the utility of household h
γi constant specified by the technology of firm i
λ Lagrange multiplier
Ψ(x1,x2,λ) Lagrange function
1
1 Introduction
Transportation is among the rapidly growing energy consuming segments of the economy. As long as
there is no feasible technology that substitutes conventional fuel combustion in vehicles for equal-
zero-emission drives, carbon emissions will increase commensurate to energy demand. The emissions
share of transport sector is about one quarter of total carbon emissions in most OECD countries.
Towards emission reduction it is a major challenge to integrate the transport sector, particularly
private transport, in a cap-and-trade system cost effectively, as can be seen in the European Union
Emission Trading System (EU ETS), which still omits transportation.
Besides transportation the electricity generation sector is responsible for nearly one third (IEA, 2004)
of global emissions. The two approaches for reducing carbon emissions, the technology one and
introduction of allowances play a role in this sector, too. The technology approach contains higher
efficiencies and the utilization of Carbon Capture and Storage (CCS) technologies. In contrast to
transportation power production is already a part of the EU ETS.
This report is structured as follows. Section 1 gives a short introduction in the current legal framework
and the state of implementing the trading system in Europe. CCS technologies, their costs and three
selected models from different studies including CCS are presented in section 2. The modeling of CCS
is not implemented in this project. Section 3 describes the current transportation sector on the one
hand and shows possible ways of including transportation into the EU ETS on the other hand. As there
are existing projects that are focusing on modeling trading systems and implementing transportation
sections 4.2 and 4.3 give a review on the most important ones after an algebraic introduction in 4.1. In
section 4.4 our data base is specified and subsequently in sections 4.5 and 4.6 we construct a model to
constitute the proposal of implementing the transportation sector into the EU ETS of section 3. Finally
two scenarios and the results are presented in section 5 while we conclude and give an outlook in
section 6.
1.1 The Institutional Framework in the Context of ETS
1.1.1 Kyoto Protocol
To slow down the greenhouse effect with its most important consequence, the global warming, the
Kyoto Protocol was decided in 1997. In the Kyoto Protocol, made under the United Nations
Framework Convention on Climate Change (UNFCCC), 38 countries committed to reduce their
emissions of carbon dioxide and five other greenhouse gases1, or engage in emissions trading if they
maintain or increase emissions of these gases. The objective of the Kyoto Protocol, as written in the
1 methane, nitrous oxide, hydrofluorocarbon, perfluorinated hydrocarbon, sulphur hexafluoride
2
Article 2 of the convention, is “to achieve, in accordance with the relevant provisions of the
Convention, stabilization of greenhouse gas concentrations in the atmosphere at a level that would
prevent dangerous anthropogenic interference with the climate system”. Therefore an overall reduction
of greenhouse gases based on the level of 1990 of 5% was decided for developed countries2. In May
2002 all fifteen then-members of the European Union (EU) ratified the Kyoto Protocol and thereby
agreed to reduce their emissions by 8% in comparison to the base year 1990 during the time period of
2008-2012. Germany as a member of the EU committed itself to the reduction target of 21%
(Bergmann et. al., 2005). To reach these targets the Kyoto Protocol defines three mechanisms: Joint
Implementation Projects (JI), Clean Development Mechanism (CDM) and International Emission
Trading (IET). The IET takes the centre stage in this paper. In the following chapter the basic
principles of the Emission Trading will be explained more detailed.
1.1.2 The Legal Basement of the Emission Trading
The EU released a couple of directives to achieve the Kyoto Protocol. The member states have a
certain amount of leeway as to exact rules to be adopted. On this account the implementation of the
directives are different in the several countries. In the following the regarding directives are mentioned
and the implementation is illustrated on the example of Germany. In October 2003 the European
Parliament and the Council of the European Union published the Directive 2003/87/EC establishing a
scheme for greenhouse gas emission allowance trading within the Community. This directive was
implemented in Germany in July 2004 with the Act of Greenhouse Gas Emission Trading (TEHG). In
some important points the TEHG sets up on the arrangements of the Act of Immission Control from
2002 (BimSchG). Thus the legal requirement is made to observe the commitments which where made
in the Kyoto Protocol. Within the Act of Allocation 2007 (ZuG 2007) the operator of assets get legal
rights, the emission certificates, allocated. The act of allocation sets up on the National Allocation Plan
(NAP) and is substantiated by the Allocation Ordinance 2007 (ZuV 2007). Therefore the rules of the
free allocation of the certificates to the parties involved in emission trading are determined. The
Emission Trading Cost Ordinance 2007 (EHKostV 2007) regulates the fees for the financing of the
administration which is produced by the appliance of the both acts, the act of emission trading and the
act of allocation.
1.1.3 Further Legal Arrangements
The Project Mechanisms Act (ProMechG) is an act on the introduction of project-based mechanisms
in accordance with the Kyoto Protocol and is the implementation of the Directive 2004/101/EC and
the amendment of the Heat-Power Cogeneration Act. This article of law creates the necessary national
2 http://ec.europa.eu/environment/climat/kyoto.htm
3
foundations for the generation of credits for emission reductions that are achieved through projects in
the framework of JI and the CDM. It regulates in particular provisions on the procedures and
prerequisites for the official approval of a planned project activity required according to international
provisions.
The fee ordinance for the ProMechG sets the framework for the charging of generating emission
credits from the project mechanisms of the Kyoto Protocol. The competent authority for the
enforcement of the ProMechG is the Federal Environmental Agency (UBA) and its German Emissions
Trading Authority (DEHSt).
1.1.4 Implementation in Europe
The European Commission was taken legal actions against four Member States for not having fully
transposed the Emissions Trading Directive into national law by 31 December 2003. Greece, Italy,
Belgium and Finland were taken to the European Court of Justice.
Until now all European Member States transposed the directive into national law. Thus the European
emission trading system could start on 1st of January in 2005. The group of participants partaking in
the first period (2005 - 2007) of emission trading consists of emission intensive industrial facilities and
plants of the energy industry.
The emission trading of the transport sector could be integrated in the existing emission trading. Then
only one kind of certificates would exist and the trading could take place between the sectors industry,
energy and transport.
1.2 Economic Impacts of Separating Transportation from a Cap-and-Trade System
There are several studies dealing with economic impacts of a system exempting sectors from
allowance trade, which is referred to as a hybrid environmental regulation system.
The idea of trading emission allowances is to achieve the most efficient abatement option by taking
advantage of market based instruments, i.e. decentralized market mechanisms. Cost efficiency can be
obtained, if tradable allowances yield equal marginal abatement cost across all sectors. Either there is
a comprehensive market for carbon allowance trading or a regulator has to possess perfect information
of the international carbon price and the emitters’ abatement cost curves to hold the efficiency
conditions.
Böhringer et al. (2005) investigate efficiency costs of the EU ETS as a hybrid trading scheme. In its
trial period the EU ETS only covers carbon emissions from certain sectors, such as generation of
energy and steel production, thereby exempting e.g. transportation. The European emission market is
also segmented into multiple domestic and a single international market. Each member state has to
specify a national mitigation policy to meet its domestic Burden Sharing Agreement (BSA). It is a
major problem neglected in the public debate that a domestic regulator lacks perfect information on
the international price of carbon allowances and marginal abatement cost curves of all domestic
4
emission sources in order to make up the optimal NAP. Decentralized market mechanisms might not
work here and cost efficiency could be seriously limited due to this fundamental information problem.
Additionally up to the present day emission allowances are grandfathered, i.e. distributed for free, to
market participants. Such a lump sum approach would not affect efficiency in a comprehensive
market, which is not the case in a hybrid market. The study of Böhringer et al. (2005) presents a
numerical analysis of the German market for carbon allowances. As a result impendence of large
excess costs of hybrid regulation becomes apparent, if allocation deviates from the efficient level.
With that perspective it stands to reason that the EU ETS should be extended to cover all emitting
sectors in the future, particularly the transport sector.
5
2 Carbon Capture and Storage Technologies
2.1 Introduction
CO2 is an omnipresent greenhouse gas influencing the climate change intensely. With a share of over
29% (IEA, 2004) power generation represents a significant part of CO2 emission worldwide.
To realise lower CO2 emissions in the power generation sector several opportunities exist. One
possibility is to increase the efficiency factor of fossil power plants. Another one is the combustion of
gas instead of coal. Furthermore the extension of current applications of renewable energies could be a
CO2 abating option. Besides these options Carbon Capture and Storage (CCS) technologies represent
an attractive alternative which will be described in this section.
Besides a technical presentation an economical evaluation follows using different studies of
established institutions is reviewed and compared. Beyond this different approaches for modelling
CCS are presented including an overview about the results.
2.2 Technologies
This section deals with technologies constituted to reduce CO2 emissions within the power generation
sector. CO2 is an unavoidable by-product generated through the combustion process in fossil power
plants. Therefore CCS technologies can contribute to a high future appliance of fossil fuels along with
relatively lower CO2 emissions.
Capture technologies are well-established technologies in other industrial sectors like the chemical one
or the oil industry3 where CO2 separation methods are used since the 1970s (Herzog, 1999). In the
chemical branch CO2 is produced to realize specific processes e.g. the production of urea. Despite
large-scale applications in other industries, capture technologies have not yet been optimized for
implementation in the power generation sector. That is why many research projects investigate future
technical and economical feasibility of power plant concepts emitting almost no CO2. The capturing of
CO2 represents the most significant part of costs for CCS. The discussion about capture and further
costs of CCS can be read in section 2.3.
With the purpose of lower CO2 emissions of power plants the first step is the utilisation of capture
technologies like Post-Combustion Capture, Pre-Combustion Capture or Oxy-Fuel Combustion, which
are seen in Figure 1. After the generation of a nearly pure CO2 gas stream CO2 is compressed and
transported to a storage site. These technologies are described in the next chapter called storage
technologies.
3 Detailed information about the utilisation of CO2 in the oil industry is given in the next section (EOR).
6
Figure 1: The main technologies for carbon capture from power plants
Source: VGB (2004, p.20)
The Post-Combustion option implements the separation of CO2 after the combustion of fuel and flue
gas treatment. Capturing before fuel combustion is called Pre-Combustion Capture. The third method
for capturing is the enhancing of CO2 concentration in flue gas achieved by the Oxy-Fuel process.
Besides these technologies further concepts are in discussion for future utilisation. The Advanced Zero
Emission Power Plant (AZEP) that integrates Mixed Conducting Membranes to generate pure oxygen
and the Chemical Looping Combustion (CLC) concept which utilise an absorber to separate air.
Another approach is the Fuel Cell’s one. Furthermore a project of the Zero Emission Coal Alliance
investigates the implementation of the ZEC Technology.
Besides capturing of CO2 storage is the latest process to withdraw the nature cycle from anthropogenic
CO2 finally. The aim of this technology is to keep CO2 safe in subsurface geological or ocean
formations for long time, Figure 2.
7
Figure 2: CO2 storage options
Source: IEA (2001)
Subsurface geological formations have been the earth’s largest reservoirs for hydrocarbons for million
of years e.g. coal, oil or natural gas. Hence there is a big potential to store CO2 in these reservoirs
permanently. The first engineered injection of CO2 was enforced in Texas, USA, in the early 1970s as
a project of enhanced oil recovery. Other projects were started all over the world with various
technologies, too. It is necessary to divide the storage technology into two parts. One possibility is the
geological storage where the CO2 is injected into depleted oil / gas reservoirs (Section 2.2.2.4), deep
saline aquifers (Section 2.2.2.5) or using the conducted CO2 to create a value added product (Section
2.2.2.2, Section 2.2.2.3). Another possibility represents the ocean storage (Section 2.2.2.6) that is still
in the research phase. All storage options are characterized by their storage potential, costs and
feasibility. In all technical options one has to guarantee that the storage does not influence the
environment negatively. For this reason ocean storage is discussed controversial because of the still
unknown effects on the marine environment.
The following sections will describe carbon capture and storage possibilities.
2.2.1 Capture
2.2.1.1 Post-Combustion Capture
The main principle of this type of carbon capture is the separation of CO2 from flue gas after the flue
gas treatment. IPCC (2005) expects this method being the best applied retrofit for Natural Gas
8
Combined Cycle power plants (NGCC) or Pulverized Coal power plants (PC). There are different
options to remove CO2 after the combustion4:
- chemical and physical absorption
- chemical and physical adsorption
- cryogenic fractionation
- membrane separation
Chemical and physical absorption
The chemical absorption is the most feasible capture application for power plants (VGB, 2004). This
process has been proven for more than 60 years in the chemical- and oil industry to separate sulphur
oxides from carbon dioxide.
At middle and low partial pressures (3 – 15 kPa) (IPCC, 2005) aqueous alkaline solvents like
monoethanolamine (MEA), diethanolamine (DEA), methyldiethanolamine (MDEA) or sterically
hindered amines are used to absorb CO2 from the cooled and treated flue gas stream in an absorber.
This ‘rich’ solvent contains chemically bounded CO2. Afterwards a stripper separates CO2 and
regenerates the solvent. This chemical reaction which recovers the solvent for further absorption needs
a high amount of thermal energy (100°C – 140°C) (IPCC, 2005) that is taken from the steam cycle. On
the one hand side 80 – 95% (IPCC, 2005) of the CO2 is not emitted to the atmosphere but on the other
hand side a reduction of the efficiency factor of the power plant about 11 – 14% is effected
(Göttlicher, 2003). The ‘lean’ solvent is cooled down to absorber temperature (40°C – 60°C) (IPCC,
2005) and is pumped back into the absorber. Absorption via monoethanolamine is the most
widespread process with the reversible fundamental chemical reaction:
C2H4OHNH2 + H2O + CO2 ↔ C2H4OHNH3+ + HCO3
- The absorption process proceeds from the left to the right side and the regeneration takes place from
the right to the left side (Herzog et al., 2004).To decline abrasion of amines it is useful to install the
flue gas treatment in front of the capture facilities. Impurity in flue gas yields to less absorbed carbon
dioxide because the amine solvent also reacts with sulphur oxides or nitrogen oxides.
The state of development of chemical absorption processes is very high due to the large-scale technical
application. It is a commercial available technology suitable for huge mass flows and delivers food-
grade CO2 that can be used in beverages. At high partial pressures a physical absorption is applied
along with solvents like cold methanol (selexol) or polyethylene glycol (rectisol).
4 These four separation technologies could be applied in combination with the two other mentioned main capture principles – Pre-Combustion and Oxy-fuel Combustion, too.
9
Chemical and physical adsorption
At this process CO2 is adsorbed on solids with high surface areas like zeolites, activated carbons and
aluminium - or silica gels. The regeneration of the adsorbent takes place either via increasing the
temperature (Temperature Swing Adsorption - TSA) or by decreasing pressure (Pressure Swing
Adsorption – PSA). Because of low capacity, low CO2 selectivity and high-energy requirements for
regeneration the adsorption option is not competitive (VGB, 2004).
Cryogenic Fractionation
The main principle of this capture process is the cooling below -100°C (IPCC, 2005) and the
following condensation of flue gas. The process presumes of this option is a high CO2 concentrated
flue gas (above 90%) (Ploetz, 2003). Combination of capturing and compression before the CO2 is
transported is an advantage of this capture method. Ploetz (2003) points out relatively high-energy
requirements and the elimination of substances with freezing points above the separation temperature
as disadvantages of this technology.
Membrane Separation
The base of this capture operation is the certain property of the applied membrane that it lets pass
through a gas. Either CO2 streams through the pores nor CO2 is solved and the remaining flue gas
streams through the membrane. The efficiency of the membrane process offers relatively low values at
the state of the art. Furthermore there are higher costs in comparison with the absorption technology.
To increase the separation rate a hybrid membrane, a membrane/solvent system was developed. The
system consists of a gaseous and a liquid phase that is separated by a gas permeable barrier (IPCC,
2005). CO2 diffuses through the membrane and is absorbed by the liquid (alkaline solvent). Due to the
use of the membrane the effort of treating flue gas before it streams into the capture facility is reduced
along with the pressure drop. That can result in a smaller decrease of efficiency.
2.2.1.2 Pre-Combustion Capture
Pre-Combustion Capture base on the sequestration of carbon before primary fuel is combusted in an
air or oxygen atmosphere. This technology is expected to be applicable in Integrated Coal Gasification
Combined Cycle power plants (IGCC).
First step is the gasification of coal to produce a synthetic gas consisting of hydrogen and carbon
monoxide. Another possibility is the partial oxidation of gaseous or liquid primary fuels to produce the
synthetic gas. In a second step a conversion of the synthetic gas into CO2 and hydrogen takes place in
the so-called water-gas shift reaction5. This reaction is implemented with the help of steam taken from
the water vapour that is expanded in the turbine. Subsequently the rest of the condensate is removed
5 CO + H2O CO2 + H2 + 41 kJ/mol (VGB, 2004)
10
and it remains only a composite of CO2 and hydrogen. After this process the concentration of CO2 is
nearly 30% (VGB, 2004). That is why the partial pressure of CO2 is significantly higher compared to
the post-combustion process and less energy is necessary for separation. Most applicable is the
separation using physical absorption that is most appropriate for higher partial pressures as mentioned
above. Remaining hydrogen can be used in a gas turbine combined cycle to generate electricity.
The capturing with physical absorption avoided the emission of around 90% of CO2. An alternative of
the physical absorption in the future could be the extraction of hydrogen by membranes. In this case
CO2 remains and will be sent to a storage site (VGB, 2004). The capture process including synthetic
gas is proven for large-scale productions in the petro-chemical sector (VGB, 2004). The main
application for the power plant sector could be IGCC plants but the IPCC (2005) states that no IGCC
with carbon capture has yet been engineered.
2.2.1.3 Oxy-Fuel Combustion
The normal electricity generating process in a power plant includes the combustion of air and fuel in
the boiler. At the oxy-fuel process air is separated into oxygen and nitrogen in an Air Separation Unit
(ASU) in front of the boiler. The production of the necessary amount of oxygen is implemented by a
cryogenic air separation. Along with compression to approximately 5 bar and a cooling down to –
180°C air is conducted and separated in the distillation equipment (VGB, 2004). Afterwards only the
pure oxygen is piped into the boiler to be combusted with fuel. This type of combustion results in far
too high temperatures (about 3500°C) (IPCC, 2005) that will destruct the combustion facility. To
regulate the temperature on a level that the facility materials are able to sustain6 portions of the flue
gas and gaseous or liquid-water are recycled back to the combustion chamber. The resulting product of
the combustion and following condensation of water vapour is a flue gas with a proportion of CO2
ranging from 80 to 98% (IPCC, 2005). The value depends on the composition of the applied fuel and
the quality of the combustion process. The remaining impurities such as sulphur oxides, nitrogen
oxides, oxygen, noble gases and particulates are removed by the following flue gas treatment that is
more compact because of the less proportion of impurities in the flue gas stream (VGB, 2004).
According to Göttlicher (2003) the efficiency factor is reduced by 7 – 11% due to additional energy
effort for cryogenic air separation and compression of CO2 for the transport to users or a storage site.
The advantage of the oxy-fuel technology is that a flue gas with a high concentration of CO2 is
produced. Hence a direct sequestration of CO2 is not necessary but merely a cleanup of the gas stream
from water vapour and impurities. With the oxy-fuel option nearly 99% (Plass, 2004) of the CO2 could
be hold back from emitting to the atmosphere. The necessary facilities for combustion with pure
oxygen can be retrofit in all types of current power plants or build in new plant concepts. Despite air
separation is a proven process in the chemical industry large efforts on the integration of the oxy-fuel
combustion process in existing or new power plants are required.
6 temperatures for gas turbine cycles range from 1300 to 1400°C and for coal-fired boilers about 1900°C (IPCC, 2004)
11
2.2.1.4 Other Future Concepts
Besides the capture technologies as a part of a power plant research is undertaken for developing new
power plant processes. Therefore future concepts are described in the following. The fuel cell
constitutes a part of future power plants e.g. in the ZECA process.
• AZEP (Advanced Zero Emission Power Plant)
• CLC (Chemical Looping Combustion)
• Fuel Cells
• ZECA (Zero Emission Coal Alliance)
AZEP – Advanced Zero Emission Power Plant
The AZEP concept is based on the integration of a MCM membrane transport process7 as a part of a
conventional gas turbine system8, Figure 3. The combustion chamber is displaced by a MCM-reactor
consisting of a ‘low’ temperature heat exchanger, a combustion chamber, a MCM membrane and a
high temperature heat exchanger. The membrane implements a surface adsorption followed by
decomposition into ions. The oxygen ions are transported sequentially through the membrane by ion
diffusion. Oxygen permeates the membrane and is combusted with methane to CO2 and water. Both
form a sweep gas circulating through the MCM-reactor. That is why the MCM-reactor implements a
heat- and an oxygen transfer between the air stream on the retentive side and the circulating sweep gas
on the permeate side of the membrane. The oxygen free air is heated to 1200°C (Sundkvist et al.,
2002) within the high temperature heat exchanger and afterwards the air stream expands in a turbine to
generate electricity. The gas steam containing of CO2 and water is heated and used to produce
electrical energy in a turbine.
The reduction of the efficiency factor is stated with 2% and total CO2 emissions are avoided. The
nitrogen oxide level in the oxygen depleted air stream is far below 1 ppm (Sundkvist et al., 2001).
7 MCM – Mixed Conducting Membranes 8 there are more technical solutions than the one with the gas turbine but this is the most efficient, cost effective and promising application (Sundkvist et al., 2001)
12
Figure 3: The AZEP Process
Source: Sundkvist et al. (2001, p.55)
CLC – Chemical Looping Combustion
During the CLC process oxygen is absorbed from a solid material. In the following a fuel reduces the
solid with oxygen and energy is released shown by Figure 4.
First the carrier material (a metal oxide e.g. nickel oxide) transfers the oxygen from air to the fuel and
secondly it absorbs the energy released by the reaction in the fuel reactor9. The energy-rich metal
oxide circulates back in the air reactor where the energy is released and the metal oxide is re-oxidised
to repeat the cycle. The two other products of the fuel reactor are CO2 and water. According to
Mattisson et al. (2001) a pure CO2 gas stream can be achieved by application of a condenser.
The electrical power generation can either be implemented by a gas turbine cycle or by a steam turbine
cycle. The exothermic oxidisation in the air reactor provides an air stream that can be expanded in a
gas turbine or heats a water cycle to generate steam and powers a steam turbine. The CO2 stream can
also be used for expansion in a gas turbine or for downstream utilisation of a steam turbine (IPCC,
2005).
The advantage of this combustion method is the inherent separation of the gas stream which contains
CO2 and water. Furthermore the flue gas mostly consists of nitrogen. There is no extra energy effort
necessary to separate CO2 from flue gas.
9 The combustion temperature is capped by applied metal oxide, e.g. Fe-oxides, 800°C or Ni-oxides, 1050°C (VGB, 2004)
13
Figure 4: The CLC process, MyOx (oxidized carrier), MyOx-1 (reduced carrier)
Source: Mattisson et al. (2001, p. 47)
Fuel Cells
Fuel Cells are another possible technology offering an exhaust with an enhanced concentration of CO2
and therefore less effort is needed to separate it. The main components are an anode that is not
consumed, a cathode and an electrolyte that mostly contains zirconia today (Forschungszentrum
Jülich, IWV), which can be seen in Figure 5. At the anode the continuously replenished fuel (e.g.
hydrogen or natural gas) reacts with oxygen that is transferred from the cathode through the electrolyte
to the anode. During the transfer of oxygen ions, electrons flow back to the cathode. This electron
stream is utilised for further electrical appliance. The anode flue gas is a composite of CO2, water and
unconverted fuel. That is why the residual fuel has to be consumed or separated from the CO2. New
processes add a membrane that implements an oxidisation of fuel with permeated oxygen or an
extraction of hydrogen.
For an application in a power plant, e.g. downstream of a coal gasification facility, high temperature
fuel cells like Solid Oxide Fuel Cell (SOFC) or Molten Carbonate Fuel Cell (MCFC) can be
practicable. An integrated steam cycle could use waste heat for generating further electrical energy
(VGB, 2004).
14
Figure 5: Solid Oxide Fuel Cell
Source: FCTec
ZECA – Zero Emission Coal Alliance
ZECA is an international collaboration of industrial, government and research institutes that
investigates the ZEC Technology. The ZEC system consists of a hydro gasification reactor, a calcium
oxide reformer, a calcination vessel and a solid oxide fuel cell, Figure 6. In the reactor coal is gasified
without air but under allowance of hydrogen to produce a gas stream which mainly contains methane.
In the next step of the process the methane flow is converted in the calcium oxide reformer into
hydrogen and limestone. One part of the hydrogen is utilised in a solid oxide fuel cell to generate
electricity and the other part is conducted in the hydro gasification reactor. The CO2 enriched exhaust
of the SOFC flows through the calcination vessel to react with limestone and produce on the one hand
a calcium oxide sorbent that is recycled back in the reformer and on the other hand a steam containing
pure CO2 (VGB, 2004).
The disposal of CO2 is realised by a mineral carbonation process that forms the sequestration part of
the ZEC Technology (Ziock et al., 2001). The mineralization of CO2 is described as a slow and energy
intensive process that is currently not on a mature level by the IPCC (2005). The efficiency is noted
with 68.9% by Ziock et al (2001).
15
Figure 6: ZECA Process
Source: VGB (2004, p.53)
2.2.2 Storage
2.2.2.1 Transportation
Transportation constitutes the link between capture and storage and is generally used to conduct CO2
to storage facilities. The most common transportation system for CO2 represents the pipeline. This
system has already proven its functionality for transporting oil or gas in long distances. Pipelines are
static buildings that have to sustain extreme conditions like weather (e.g. temperature) or high internal
pressures. After the capture process the gaseous CO2 should be dry and free of hydrogen sulphides
during transportation because of the increasing implicated corrosion inside the pipeline. A grave result
of corrosion could be a burst pipe from which leakage the CO2 escapes to the atmosphere. For this
reason it is necessary to monitor regularly the current status of the pipelines. Besides the gaseous
transportation of CO2 there is also the possibility to transport it solid or liquid. Liquefied CO2 can be
additional transported by ship, rail or road. In that case the technology of liquefied natural gas (LNG)
and liquefied petroleum gas (LPG) can be applied because the properties of CO2 differs not much of
this one from gas. The solidification is less effective than other options because of higher costs and
energy intensity operation. In whole the way of transportation depends on the geological storage
location, investment costs for infrastructure and transportation volumes. The most cost effective
transport options are pipelines and ships because of a huge transportation volume.
16
2.2.2.2 EOR – Enhanced Oil Recovery
In an energy constrained world the producers of oil try to convey maximum amounts to increase their
earnings and to allay humans demand. With standard extraction techniques you can only use a
proportion of the oil that is primary in the field. One technical option to deliver more oil offers the
Enhanced Oil Recovery (EOR) through CO2 flooding. This technology allows an additional recovery
of 7%-23% (IPCC, 2005) of the original oil in place (OOIP). The appliance requires a minimal
reservoir depth of 800m (IEA, 2004). The captured CO2 is transported via pipeline from the CO2
source to the EOR facilities and will be compressed by a special pump followed by injection through
the injection well into the reservoir. Through injecting the CO2 into the oil field the internal pressure
increases. CO2 EOR depends on reservoir temperature, pressure and crude oil composition. With
temperatures up to 120°C, CO2 is mixed with oil (=miscible flood). Beyond this temperature the CO2
replaces the oil (=immiscible flood). Miscible floods are generally applicable for low viscosity oils
and miscible floods for medium to heavy oils10. In using miscible floods the incremental pressure
results in a mixture of oil, water and CO2 and reduces the viscosity of oil. Furthermore the lower oil
viscosity results in a better dissolution of the oil from the pore spaces. In the step the mixture is
conducted to the surface by a producing well that is arranged parallel to the injection well. After
extracting the oil alloy it is necessary to separate the water and CO2 from the oil via a separation unit.
Less than 50% and down to 33% of the injected CO2 remains in the oil field. The other proportion
returns with the extracted oil. To re-use this CO2 for further processes you have to dehydrate and
compress it. This recycled CO2 is now mixed with the captured CO2 to repump it through the injection
well again. Outside the CO2 storage potential of EOR the technology has been developed with the
perspective of oil recovery. Hence EOR technology creates the highest benefit of all options but will
store CO2 only temporarily.
2.2.2.3 ECBMR – Enhanced Coal Bed Methane Recovery
Another storage option that results in a value added product represents the Enhanced Coalbed Methane
Recovery (ECBMR). The CO2 is stored in deep unmineable coal seams11 where the coal conveying is
not worthwhile because of technical unfeasibility and inefficiency. Coalbed methane (CBM)
production takes up an important role for natural gas supply. Pumping water in deep coal seams with
lower pressure causes methane (CH4) desorption from coal. Coal is a big pore trap for CH4 thus
methane is also called as “black damp”. The methane concentration in deep coal seams ranges from 5
to 25 scm/t coal (IEA, 2004). But only 20% to 60% of original gas-in-place (OGIP) (Bock et al., 2003)
can be recovered by primary production through CBM. In theory it is possible to recover more than
90% of OGIP with CO2-ECBMR. At this juncture you use a certain property of coal while CO2 is
10 Light oil has a gravity of 25° – 48° API and medium/heavy oil is characterized by a gravity of 12° – 25° API. API degree is
a dimension of the American Petroleum Institute that measures the specific volume of crude oil. 11 The bulk of these coal seams are located in a depth about 1500m.
17
injected. The process is based upon displacing the primarily coal-attached CH4 with the injected CO2.
Coal seams are safe traps and may be great storage space for CO2 because coal prefers to adsorb CO2
more than CH4. However the storage potential is marginal and is estimated worldwide at 3 to
100GtCO2. In Germany storage capacity is estimated at 3100 to 8300 MtCO2 (Donner et al., 2006).
Besides the small storage potential it is not possible to use the CO2-saturated coal for energy. ECBMR
is attractive for methane recovery but it will be not used at first for storage besides other sequestration
options.
2.2.2.4 Depleted Oil and Gas Reservoirs
Depleted oil or gas fields are prime reservoirs to store CO2 permanently for many years. The traps had
been safe for millions of years and gas/oil did not escape autonomously. Another reason for excellent
appliance determines the good knowledge about the geological structure and physical properties of
oil/gas. The technique is quite simple because only one injection well is needed conducting the CO2
downwards. In the future storage potential will increase with the number of depleted reservoirs. But
most widespread oil and gas reservoirs are located in the Middle East and former Soviet Union. Hence
this implies a cost intensive transport, as mostly transporting long distances. Compared to other
storage options the depleted oil/gas fields have some additional advantages. You can re-use the
equipment for hydrocarbon production in large parts and the exploration costs are relatively small
(IEA, 2004). With a total capacity of 1,000 GtCO2 depleted gas fields are much larger than depleted
oil fields and more widespread (IEA, 2004). But storage potential varies from time to time as it
depends on new oil/gas field explorations.
2.2.2.5 Deep saline aquifers
Saline reservoirs are deep water-filled aquifers that are theoretical suitable for CO2 - storage. These
sedimentary rocks are saturated with formation water or brines and are widespread. The contained
saline water is unsuitable for agriculture use or just as potable water. CO2 is injected into a depth of
800m below (cap) rocks with low porosity and dissolves partially in the water. This results in an
abrasive and abuzz aerated solution that can react with minerals to carbonates. Thus the sealing of the
injection well has to be prepared against these abrasive fluids to guarantee a trap with leakages nearly
zero. Required techniques to store CO2 in deep saline aquifers would use from similar ones of depleted
oil or gas fields.
The Sleipner Project
The Norwegian Sleipner Vest sector about 250km from the shoreline of Norway is the first
commercial project (SACS12) started for geological storage. It is operated by Statoil. Sleipner Vest is a
12 Sleipner Aquifer for CO2 Storage Monitoring and Research Project
18
natural gas reservoir combines gas recovery and CO2 - storage. CO2 is pumped via a bore hole into the
Utsira13 brine - saturated sandstone formation that is located 800m below the seabed and 250m thick.
Since the end of 1996 approximately one million tons per year of captured CO214 has been injected
into the aquifers under the North Sea. It is expected that the storage volume cover a total of 20 MtCO2
over lifetime (IPCC, 2005). The SACS is a demonstrable project for technically feasibility and zero
leakages.
2.2.2.6 Ocean
The ocean takes up 71% (IPCC, 2005) of earth’s surface and represents therewith the biggest storage
potential for CO2. Hence it stands to reason that researches for possibilities to use the ocean for storage
are essential. Every year the ocean absorbs autonomously about one-third (Adhiya et al., 2001) of
annual anthropogenic emissions15 and contains an amount of 50 times the quantity of CO2 placed in
atmosphere (IPCC, 2005). Presently there are two possibilities to store CO2 into deep ocean. One is to
take the high-pressurized captured gas and pump it via pipeline through a diffuser into depths between
1,000 and 2,000m. At these positions the CO2 will ascend like “droplet plumes” to 500m due to
buoyancy while dissolving in seawater. Thenceforward the dissolved CO2 reaches the oceans surface
in vaporous or bubbly conditions. Enveloping the CO2-droplet in a special hydrate film may maximize
the ascending time due to heavier weight relative to water. Second option is to inject the CO2 in deeper
depths down to 3,000m (IPCC, 2005). The CO2 will sink to the sea bottom and builds so called “CO2
lakes”. In this situation CO2 becomes heavier than seawater. Generally there is the possibility to
conduct the CO2 directly via pipeline into the sea or via tanker to a swimming platform wherefrom you
inject it afterwards in the same manner via a vertical pipeline. Furthermore the “biological pump” can
be used to save the CO2. The ocean contains phytoplankton that absorbs a special amount of CO2 from
the atmosphere. Marine animals assimilate this phytoplankton through their food chain and emit the
CO2 to atmosphere again. Only a small share of this phytoplankton will not be involved in the food
chain and sink to deeper oceans to remain there. In theory it is possible to enrich the phytoplankton
with iron oxide to proliferate.
Scientists differ about the possible storage-time varying from some decades (Donner et al., 2006) up
to 1000 years (IPCC, 2005). As still no representative projects were started, nobody can give an exact
prognosis16. Ocean storage is the most controversial discussed issue under the storage options because
it is currently in the research phase and no one can forecast the effects on marine environment.
13 Norwegian sea area 14 About 9% of Sleipner Vest gas 15 Approx. 7 GtCO2 yr-1 16 Two pilot projects had been cancelled in Norway and Hawaii on the basis of public criticism.
19
2.2.3 Conclusion
Future electricity demand will exceed current electricity generation by fossil fuels. Regarding to the
climate change higher fossil fuel combustion rates can only be achieved by simultaneous retention of
CO2 emissions. CCS represents a great possibility to mitigate CO2 emissions.
There are many research projects undertaken to investigate capture and storage opportunities of CO2 in
the electricity generation sector. Even today it is technically practicable to integrate carbon capture
into power plants. Nevertheless energy penalties caused by carbon capture are too high for commercial
appliance and big research effort is required to improve efficiencies of capture technologies.
The problem of CO2 storage does not only seem to be technical difficulties but also economic
feasibilities first. Projects as Sleipner Vest demonstrate the imperative of getting storage started in
large scale. But the only commercial applied storage technology represents CO2 EOR. However this
mature technology is one example for using CO2 for benefits without sustainability concerning the
storage duration. In handling with all storage options it is strongly necessary to guarantee safe traps for
CO2 to protect our environment. Besides all storage options ocean storage represents the most
controversial one because of the still unknown environmental effects.
2.3 The Economics of CCS
Introduction and Methodology
After the explicit technological presentation of CCS technologies in the previous chapters the
following part deals with the economic aspects of capturing and storing carbon dioxide. Analysing the
process of CCS, three major costs components can identified – costs of capturing (including
compression), costs of transmission and costs of storage. Each of the components will be examined
separately. We will discuss their technological specific investments and identify the estimated
abatement costs based on different published studies. Furthermore the key parameters which are
significantly influencing the technology costs will be pointed out. Hence that CCS technologies are
still an early stage of implementation and therefore published costs should be regarded as indicative
values only (Hendriks, et. al. 2004).
Various ways exist to calculate costs and emission abatement (Freund et. al. 2002). As values of
several parameters will change over the operating life of a facility (e. g. capacity factor, unit fuel cost)
also costs will vary from year to year. To take such effects into consideration costs have to be
discounted and economically evaluated. According to Freund (2002) three methodologies are used in
public studies. At first arising costs can be discounted to the present and then related to total emission
reduction over the life of the project (net present cost). Using this method, timing of greenhouse gas
abatement is neglected. Another possibility is to discount costs and emission abatement based on a
schedule, in which the arising costs and mitigation are listed and discounted to the present (net present
20
value). A third method in use is the counting of levelized costs, which are these costs that would
produce the same net present value as an assumed stream of variable year-to-year costs.
2.3.1 Capture
Capture costs include all costs resulting from operations taking place at the power plant including
costs of compression to produce a CO2 stream of high purity and high pressure.To express the added
costs of carbon capture the following measures are used (IPCC 2005):
- Capital cost
- Incremental product cost
- Cost of CO2 captured
- Cost of CO2 avoided
Capital costs are the sum of direct equipment expenses required for the selected capture system. Some
analysts also include the cost of interest during construction. Incremental product cost represents the
effect of capture on costs of generating electricity. It presents the difference in electricity costs
between a system with and without capture.
Cost of CO2 captured can be interpreted as the price of CO2, if it is sold as an industrial commodity.
The measure reflects the economic viability of a CO2 capture system given a market price (IPCC
2005).
Costs of CO2 avoided takes into account the additional energy requirement of a capture plant and
therefore higher greenhouse gas emissions. It can be interpreted as the average costs of reducing one
unit CO2 providing the same amount of useful electricity as a plant without capture. From this it
follows that costs of avoided CO2 are always higher than this for captured CO2.
2.3.1.1 Cost Model
In order to point out potential costs of CCS we present estimations by Herzog (2004) and David
(2000). Both authors compare plants with and without capture and show how CCS affects the
economics of power plants. Their evaluations focus on three major CO2 capture power plants,
Integrated Gasification Combined Cycle (IGCC), Pulverized Coal Fired Single Cycle (PC) and
Natural Gas Combined Cycles (NGCC). Latter is a relatively new technology.
The capture technology Oxy-fuel which was mentioned above has not been taken into consideration in
this paper beside the post- and pre-combustion because a systematic analysis of cost – efficiency has
not been done yet. Oxy-fuel processes are speculative concepts based on theoretical assumption and
have not been established in practice yet. Herzog and David extracted the following data from
different studies:
• Capital Cost (C) in $/kW
• Cost of electricity due to fuel, and operation and maintenance (COEO&M) in mills/kWh
• Heat rate in Btu/kWh defined on a low heating value (LHV)
21
• Incremental capital cost in $/kg of CO2 per hour
• Incremental cost of electricity due to operation an maintenance in mill/kg of CO2
• Energy requirements of the capture process in kWh/kg of CO2
The first three parameters characterize the power plant without capture (reference plant). The last three
characterize the performance of the capture process.
In these studies different types of power plants were adjusted to a common economic basis to compare
the economic impacts of capture. Plants were standardized on a yearly operating hour of 6,750 hrs per
year, a capital charge rate of 15% per year, a coal price of $1.24 per million BTU and a natural gas
price of $2.93 per million BTU.
Integrated Gasification Combined Cycles (IGCC)
David (2000) compared the costs of CO2 capture of the IGCC technology using studies from Argonne
(1997), Milan (1998), SFA Pacific (1998), Utrecht (1994), EPRI (1991) and IEA (1999) shown in
Table 1: Performance of IGCC capture plants, studies adjusted.
22
Table 1: Performance of IGCC capture plants, studies adjusted
Data Description/Study Argonne Milan SFA Pacific Utrecht EPRI IEA
Reference Plant
coe: CAPITAL, mills/kWh 30.4 35.1 29.7 28.9 36.5 33.6
coe: FUEL, mills/kWh 11.1 9.7 8.9 9.7 11.5 9.1
coe: O&M, mills/kWh 9.3 5.8 7.9 6.5 10.4 9.6
Capital Cost, $/kW 1332 1536 1300 1265 1600 1471
Net Power Output, MW 413.5 404.1 400.0 600.0 431.6 408.0
CO2 Emitted, kg/kWh 0.790 0.709 0.674 0.760 0.868 0.710
Thermal Efficiency (LHV), % 38.2 43.7 47.3 43.6 36.8 46.3
Heat Rate (LHV), Btu/kWh 8938 7817 7210 7826 9280 7369
Cost of electricity, ¢/kWh 5.08 5.06 4.65 4.50 5.85 5.23
Capture Plant
coe: CAPITAL, mills/kWh 38.5 43.7 40.3 41.1 49.1 50.3
coe: FUEL, mills/kWh 12.1 11.3 11.3 11.7 14.3 11.1
coe: O&M, mills/kWh 11.2 7.2 7.2 9.4 18.8 14.9
Capital Cost, $/kW 1687 1913 1767 1799 2152 2204
Net Power Output, MW 377.5 345.6 314.4 500.0 347.4 382.0
CO2 Emitted, kg/kWh 0.176 0.071 0.088 0.040 0.105 0.134
Thermal Efficiency (LHV), % 34.8 37.3 37.2 36.3 29.6 38.2
Heat Rate (LHV), Btu/kWh 9791 9140 9173 9399 11528 8932
Cost of electricity, ¢/kWh 6.18 6.22 6.25 6.21 8.23 7.63
Comparison
Incremental coe, ¢/kWh 1.10 1.16 1.59 1.71 2.38 2.39
Energy Penalty, % 8.7 14.5 21.4 16.7 19.5 6.4
Mitigation Cost, Capture vs.
Ref., $/ ton of CO2 avoided 18 18 27 24 31 42
Source: David (2000)
For the purpose of implementing a capture process an average capital investment of $2,304 per kW is
required. Incremental cost of electricity for used IGCC capture plants varies from 1.1 to 2.39 ¢/kWh.
Thus the average incremental cost can be calculated at 1.72 ¢/kWh. The energy penalty varies from
6.4% up to 21.4%. Mitigation cost ranges from $18 to 42 per ton of CO2 avoided. Newer studies report
ranges from $13 to 37 per ton of CO2 avoided (IPCC 2005) resulting from technical improvements in
power generation and capture technology. Therefore the average cost fall from $27 to $23 per ton CO2
avoided.
Further total fuel costs of the plant with capture are higher than this without capture, because CO2
capture systems require significant amounts of energy which also reduces net plant efficiency. Thus
23
power plants with capture require more fuel to generate the same net power output as the same plant
without capture.
Pulverized Coal Power Cycles (PC)
David (2000) compared the costs of CO2 capture of the PC technology using studies from SFA Pacific
(1998), Utrecht (1994), EPRI (1991) and IEA (1999). Data extracted and adjusted are shown in Table
2:
Table 2: Performance of PC capture plants, studies adjusted
Data Description/Study Utrecht EPRI SFA Pacific IEA
Reference Plant
coe: CAPITAL, mills/kWh 26.3 25.8 29.7 23.3
coe: FUEL, mills/kWh 10.3 11.7 9.5 9.3
coe: O&M, mills/kWh 5.9 10.3 7.9 7.2
Capital Cost, $/kW 1150 1129 1300 1022
Net Power Output, MW 600 513.3 400.0 501
CO2 Emitted, kg/kWh 0.800 0.909 0717 0.722
Thermal Efficiency (LHV), % 41.0 36.1 44.4 45.6
Heat Rate (LHV), Btu/kWh 8322 9440 7680 7482
Cost of electricity, ¢/kWh 4.25 4.78 4.71 3.98
Capture Plant
coe: CAPITAL, mills/kWh 47.3 56.7 46.2 42.4
coe: FUEL, mills/kWh 13.4 17.8 11.3 12.8
coe: O&M, mills/kWh 12.9 29.9 12.3 13.4
Capital Cost, $/kW 2073 2484 2022 1856
Net Power Output, MW 462 338.1 336.5 362
CO2 Emitted, kg/kWh 0.100 0.138 0.128 0.148
Thermal Efficiency (LHV), % 31.5 23.8 37.4 33.0
Heat Rate (LHV), Btu/kWh 10832 14331 9130 10339
Cost of electricity, ¢/kWh 7.37 10.44 6.98 6.86
Comparison
Incremental coe, ¢/kWh 3.12 5.66 2.27 2.88
Energy Penalty, % 23.0 34.1 15.9 27.7
Mitigation Cost, Capture vs.
Ref., $/ ton of CO2 avoided 45 73 39 50
Source: David, 2000
24
For implementing a capture process capital cost increases at around $2,109 per kW. The comparison
of the reference and capture plant shows an average incremental cost of electricity of 3.48 ¢/kWh and
average mitigation cost of around $52 per ton of CO2 avoided. Mitigation costs of PC plants are higher
than these of IGCC. Hence energy penalty is lower for capture in IGCC plants than for post-
combustion capture in PC (Thambimuthu et. al.2003). Newer studies show costs differing from $29 to
51 per ton of CO2 avoided, also based on technical improvements. The energy penalty varies from
15.9% up to 34.1%. Results are higher than for an NGCC plant because coal has larger carbon content
than gas.
Further the IEA GHG (2004) noted that each dollar per GJ increase in coal price would increase the
cost of electricity by $8.2 per MWh for a new PC plant without capture and by $10.1 per MWh for a
PC plant with capture (IPCC 2005).
Natural Gas Combined Cycles (NGCC)
David (2000) reviewed the following studies to compare costs: SFA Pacific (1998), Trondheim
(1992), IEA (1999) and Politecnico di Milano from Italy (1999) all shown in Table 3.
25
Table 3: Performance of NGCC capture plants, studies adjusted
Data Description/Study SFA Pacific Trondheim IEA Milan
Reference Plant
coe: CAPITAL, mills/kWh 11.1 17.2 9.5 12.1
coe: FUEL, mills/kWh 16.7 19.2 17.8 18.8
coe: O&M, mills/kWh 3.0 2.7 2.2 2.2
Capital Cost, $/kW 485 754 414 531
Net Power Output, MW 400.0 721.2 790.0 373.2
CO2 Emitted, kg/kWh 0.330 0.400 0.370 0.374
Thermal Efficiency (LHV), % 60.0 52.2 56.2 53.3
Heat Rate (LHV), Btu/kWh 5688 6536 6071 6400
Cost of electricity, ¢/kWh 3.07 3.91 2.94 3.30
Capture Plant
coe: CAPITAL, mills/kWh 25.9 30.1 17.9 18.4
coe: FUEL, mills/kWh 18.8 22.5 21.2 20.8
coe: O&M, mills/kWh 6.9 5.2 4.5 3.6
Capital Cost, $/kW 1135 1317 786 807
Net Power Output, MW 353.7 615.3 663.0 336.6
CO2 Emitted, kg/kWh 0.056 0.046 0.061 0.037
Thermal Efficiency (LHV), % 53.0 44.5 47.2 48.1
Heat Rate (LHV), Btu/kWh 6433 7667 7229 7097
Cost of electricity, ¢/kWh 5.17 5.77 4.36 4.29
Comparison
Incremental coe, ¢/kWh 2.10 1.86 1.42 0.98
Energy Penalty, % 11.6 14.7 16.1 9.8
Mitigation Cost, Capture vs.
Ref., $/ ton of CO2 avoided 77 53 46 29
Source: David (2000)
The incremental electricity cost at the NGCC capture plants varies from 0.98 to 2.10 ¢/kWh. Thus the
average cost amounts to 1.59 ¢/kWh. The energy penalty varies from 9.8% up to 16.1%. Mitigation
cost averages at $51 per ton of CO2 avoided. Current studies report avoiding cost of CO2 from $37 to
$54 (IPCC 2005). NGCC costs are especially sensitive to the price of natural gas, which has risen
significantly in recent years (Figure 7).
26
Figure 7: Natural Gas Price Development
Source: Oilnergy (www.oilnergy.com, 2006)
NGCC systems have typically been found to have lower electricity production costs than new PC and
IGCC plants (with or without capture) if the gas price is stable and below $4 per GJ for the whole
project lifetime (IPCC 2005). But if gas prices will rise more and more, the economics of NGCC
plants will have changed. But yet no studies have been published concerning higher gas prices.
Based on the assumptions of IEA (2004) (IPCC 2005) the cost of electricity for an NGCC plant
without capture will increase by $6.8 per MWh for each dollar per GJ increase in natural gas price
(assuming no change in plant utilization or other factors of production). Newer NGCC plants with
CCS would notify a slightly higher increase of $7.3 per MWh. This demonstrates that the price of
natural gas is an important parameter determining which type of power plant will provide the lowest
cost of electricity in the context of a particular situation.
2.3.1.2 Conclusion
Technological improvements, learning and economies of scale in power generation and capture
technology can lower the capture costs. Recapitulating the average cost of electricity is calculated for
the three main capture technologies (IGCC, PC, and NGCC). However, the average incremental cost
of electricity amounts to 1.72 ¢/kWh in pre-combustion capture for IGCC plants and 3.48 ¢/kWh for
the post-combustion capture in PC power plants. The average cost of electricity increases by 1.59
¢/kWh for the NGCC. Further average mitigation costs amount to $27 per ton CO2 avoided for the
IGCC plant, and for PC $52 per ton CO2 avoided. For a NGCC plant mitigation costs are estimated at
$51 per ton CO2 avoided.
Key cost drivers in the capture process are the heat rate, the required energy amount and the capital
costs. The variation of heat rates has a bigger effect on costs than changes in energy requirements. A
higher heat rate reduces the cost of electricity for the reference and the capture power plant. Additional
27
required energy for the capture process just affects the capture power plant (Herzog 2000). According
to the IPCC (2005) the efficiency of IGCC technologies is similar to the efficiencies of PC power
plants, so fuel costs should be similar for both. In the case of higher gas prices rising continuously,
NGCC plants often have higher electricity production costs than coal-based plants, with or without
capture. Therefore IGCC capture plants could be compete with NGCC capture plants. However, the
difference in costs between PC and IGCC plants with or without CO2 capture can vary significantly. It
depends on the coal type and other local factors. If carbon sequestration becomes necessary, IGCC
plants will be more economical than PC plants. Anyhow most changes were predicted in the IGCC
technology and smaller ones are planned in the NGCC and PC. Since full-scale NGCC, PC and IGCC
systems have not been built with CCS yet, the absolute or relative costs of these systems cannot be
stated with a high degree of confidence at this time.
2.3.2 Transmission
As CO2 can be transported in a similar manner like natural gas or petroleum, technologies can be
adopted and engineers can profit from the back experience. Commercially CO2 is already transported
via pipelines in a gaseous form with high pressure and via ship tankers in a liquid state. Cost of
transmission highly depends on the amount of CO2 transported and on the covered distances. Further
the steel price is a significant component which has a great influence on the capital costs of pipelines
and tankers (IPCC 2005). First, cost of pipeline transport and second this for the marine transportation
will be examined.
2.3.2.1 Pipeline
Before calculating the costs of pipeline transport the following technical parameters have to be taken
into consideration:
- Amount of CO2 to be transported
- Length of pipeline
- Inlet and outlet pressure
Knowing the mass of the CO2 transported per year or over the total project life and the required
pressure the diameter of the pipeline can be calculated. Therefore capital costs and O&M costs can be
examined. The type of terrain plays a decisive role. According to the IPCC (2005) densely populated
areas, mountains or nature reserve areas for example can double costs, because additional safety
measures are required and accessibility to construction will be more difficult. Offshore pipelines will
be more costly as onshore ones because CO2 is transported at higher pressure and lower temperature.
Furthermore it is noted that it would be more favourable to collect CO2 into one single pipeline to
transport it to the storage site than separately, although small projects will suffer from higher costs and
will be more sensitive to the transportation distance.
28
The potential CO2 transmission costs presented below are taken from studies of Gale (2004), Heddle
(2003) and Freund (2002).
Table 4: Cost of pipeline transmission of CO2
Parameter Unit Gale Heddle Freund
Length of pipeline km 300 300 100 300 100 400
Pipeline Transport onshore offshore onshore onshore onshore onshore
Throughput mill t/year 1.5 2.16 5
Inlet pressure bar 140 152 110
Cost of transmitting $/t CO2 6 15 1.78 6.49 1.1 4.2
Source: According to Heddle (2003), Gale (2004), Freund (2002)
Estimations are based on a single 500 MWe IGCC with CO2 capture. For this type and size of plant
Gale assumed a transport of about 1.5 million tons per year of CO2. Costs estimation is based on an
annual discount rate of 10% and a project life of 25 years. Heddle used a capital charge rate of 15%.
The pipeline is designed to handle 7,389 tons of CO2 per day (2.16 million tons CO2 per year). Both
studies do not consider compression costs. The onshore CO2 pipelines are assumed to be across
cultivated land in Europe. Freund assumed a transported throughput of CO2 about 5 million tons per
year. Capital charge rate is not reported.
Over an onshore distance of 300 km Gale calculated a transmission cost about $6 per ton of CO2,
which is equivalent to 0.2 ¢/kWh of electricity generated (Gale et al, 2004). Offshore transmission is
more expensive. The costs are $15 per ton of CO2 for a length of 300 km. With $6.49 per ton of CO2
transported. Heddle nearly agrees with Gale concerning the costs results for the 300 km pipeline. The
costs comparison for the 100 km pipeline of Heddle ($1.78 per ton CO2) and Freund ($1.1 per ton
CO2) shows similar results too. Differences may result from the amount of throughput per year.
Freund assumed the twofold throughput of CO2.
As transport costs are a function of the CO2 mass flow rate, economies of scale are reached with
annual CO2 flow rates in excess of 10 million tons per year. At these rates, transport costs will be less
than $1 per ton of CO2 per 100 km (Bock et. al. 2003). Transmission cost further depends on the plant
size. If net power output raises cost of transmitting CO2 it will decrease significantly. Gale assumed
that the costs for onshore pipelines would be about $2 per ton of CO2 from a 5000 MW of gas fired
power generation.
2.3.2.2 Ship tankers
Because transmission is not bound on a network of pipes, the use of ship tankers is more flexible to
transport CO2 to a storage site. On the other hand loading, unloading and intermediate storage facilities
are required. For transportation CO2 has to be liquefied under high energy consumption in a
liquefaction facility. Besides tankers will require fuel, leading to additional emissions, they have to be
29
taken into account. IEA GHG (2004) estimated 2.5% extra CO2 emissions for a transport distance of
200 km and about 18% for a distance of 12,000 km. O&M costs mainly includes labour, electricity
cost, harbour fees and maintenance.
Since presently no system has been implemented on scale (i.e. in the range of several million tonnes of
carbon dioxide handling per year) the different costs are not well known in detail yet. Ships which are
currently used for the transportation of CO2 are tanker transporting liquefied petroleum gas (LPG).
Freund (2002) reports costs for a tanker of 22,000 scm at $50 million. Estimated costs of transmitting
are about $2 per ton of CO2, not including costs at the port and the injection facility. In comparison to
the pipeline transmission cost, ship tankers will be cheaper for large distances. Further other factors as
loading terminals, pipeline shore crossings, water depth, seabed stability, fuel costs, construction costs,
different operating costs in different locations, security, and interaction between land and marine
transportation routes affect costs of both transmission systems (IPCC 2005).
2.3.2.3 Conclusion
Costs have been estimated for both pipeline and marine transportation of CO2. Costs highly depend on
the distance and the quantity of CO2 transported. In the case of pipelines, costs depend on the type of
pipeline (onshore or offshore) and on the type of area and density of population. An alternative for
long transportation distances are ship tankers.
Figure 8: Comparison of transmission cost
Source: IPCC (2005)
Figure 8 summarizes the different costs for transportation of CO2 by miscellaneous alternatives. In this
diagram the dependence of costs in terms of distance is shown. Ship transport becomes cost-
competitive with pipeline transport over larger distances.
30
2.3.3 Storage
The economics of storage composes of costs caused by actions taken from the delivery point, the
injection in the reservoir and monitoring of CO2. First costs of storage in geological formations (depleted oil and gas reservoirs, aquifers) will be
discussed. In order to answer the question whether costs can be partially offset by application of
enhanced oil or coalbed methane recovery these two techniques will be examined apart from
geological storage. Further the option of storing CO2 in the deep ocean storage will be object of the
study. To give an idea of potential storage costs the study by Heddle (2003) is used and compared with
other published papers.
2.3.3.1 Geological
Pressure, permeability, thickness and depth of the chosen reservoir are important parameters that will
affect safety, costs and efficiency of storage. To get this information feasibility studies comprising
geological, geophysical and engineering studies are required. In the case of the Sleipner project Torp
(2004) estimated costs for site characterization about $1.9 million. As mentioned parameters can vary
widely from reservoir to reservoir costs will be quite site specific. High permeability and thickness
leads to decreasing in storage costs. On the other hand costs will increase with reservoir pressure
which results in lower injectivity (Heddle, et. al. 2003).
For the purpose of injecting CO2, wells have to be drilled and infrastructure has to be built up. For the
Snøhvit project Kaarsten (2002) estimated drilling and completion costs of the offshore well at $21
million. For the Sleipner field Torp reports $15 million. In total $80 million were invested at Sleipner,
including compression facilities and other equipment. Operating cost was estimated at $7 million per
year comprising, mainly caused due to maintenance work and fuel costs. Both projects are offshore
therefore costs appear higher than these in Table 5:
Table 5: Estimated CO2 storage cost in geological formations
Parameter Unit Gas reservoir Oil reservoir Aquifer
Pressure MPa 3.5 13.8 8.4Thickness m 31 43 171Depth m 1,524 1,554 1,239Permeability md 1 5 22Pipe distance km 100 100 100Capital cost million $ 17.7 9.18 2.15O&M cost million $ 1.97 0.97 0.1Injection rate per well t/d 156 360 9,363Number of wells 48 21 1CO2 storage cost $/tCO2 4.87 3.82 2.93
Source: Heddle (2003)
31
Heddle examined costs of three geological formations, depleted gas reservoir, depleted oil reservoir
and a deep saline aquifer. Estimated data for the base case is summarized in Table 5. High and low
cost cases show a range of $1.20 to 19.43 per ton CO2 stored for the gas reservoir, $1.21 to 11.16 per
ton CO2 stored for the oil reservoir and in case of the aquifer costs range from $1.14 to 11.71 per ton
CO2 stored. The sensitivity analyses identified thickness and permeability as those parameters with the
greatest impact on storage costs for depleted gas reservoirs while for oil reservoirs pressure has
highest effects on storage costs.
Other published studies indicate similar costs spans of $5 to 17 per ton CO2 stored for saline aquifers
and $7 to 10 per ton CO2 stored for depleted gas fields (Freund et. al,. 2003).
2.3.3.2 EOR / ECBM
Enhanced production of oil or coalbed methane (CBM) has the distinct advantage that it is the only
storage option which has potential to generate an economic return and therefore can offset storage
costs. But hence these technologies have been developed with the aim of optimal recovery of oil or
CBM and not for optimal storage of CO2.
Costs of storage are mainly determined by the price of oil (or CBM) and the CO2 effectiveness
(Heddle et. al., 2003). Last describes the amount of CO2 required to produce one barrel enhanced oil
or in case of ECBMR the amount to produce one scm of enhanced CBM.
Further important parameters affecting the economics of EOR projects are oil production rate, CO2
recycle ratio and well depth. Normally it is assumed that primary and secondary recovery already has
been taken. This has the advantage that oil production wells already exist and often only reworking or
conversion of these is required. Capital has to be invested for compressors, separation and recycle
equipment and for further well drillings. Operating and maintenance costs comprise the CO2 purchase
(or capture) price, energy costs and field operating costs (IPCC 2005). Heddle (2003) assumed for
case 1 below a sum of $27 million for operating costs and around $183 million for capital investment.
The production of CBM via injection of CO2 is an immature technology that has not been represented
on commercial scale yet (IPCC 2005). The process is quite energy intensive and a large number of
injection wells is required. Further fields have to be taped new, resulting in higher investment and also
operating costs. The EIA (2003) reported equipment costs ranging from $286,400 to $912,200 and
annual operating costs from different ECBMR fields of $82,700 to $119,200 assuming ten wells and
depths from 1,000 ft (305 m) to 3,000 ft (915 m). Therefore mitigation costs for ECBM studies appear
higher than in EOR cases. Factors affecting the economics are similar to those of EOR fields. Storage
costs increase with well depth, CO2 effectiveness and pipeline distance. Increases in CBM production
rate and gas prices let costs decrease (Heddle, et. al. 2003).
32
Table 6: Estimated CO2 storage costs of EOR projects
Heddle Damen Parameter Unit Case 1 Case 2 Case 3
Location Saudi Arabia
Los Angeles Basin
Operating lifetime years 20 15 15
t CO2/bbl enhanced oil 0.45 0.43CO2 effectiveness scm CO2/bbl enhanced oil 170 255 243
CO2 recycle ratio 3 2 2EUR/bbl 17.50 17.50Oil price $/bbl 15 22.42 22.42
Depth m 1,219 2,000 1,676Pipe distance km 100 50 50Previous water flooting yes yes yes
bbl enhanced oil/day 22,142 Total oil production Mbbl enhanced oil/field17 11.67 2.58
Number injection wells 56 16 18EUR/tCO2 -3 19CO2 storage cost $/tCO2 -12.21 -3.84 24.3218
Source: Heddle (2003) and Damen (2003)
Presented costs in Table 6 are taken from Heddle (2003) and Damen (2003). With an average amount
of 170 scm CO2 required to produce one barrel of enhanced oil Heddle estimated net storage costs of
$-12.21 per ton CO2 stored. Negative costs indicate that the project generates a surplus due to the
purchase of the produced oil. With higher operating depths and minor CO2 effectiveness Damen
obtains storage costs ranging from $-3.84 to 24.32 per ton CO2 stored, although higher oil prices are
assumed. This results due to the fact that Damen based his calculations on smaller oilfields where total
estimated oil production is much lower and also lifetime is shorter than in the case of Heddle. Besides
the chosen CO2 effectiveness implicates a higher amount of CO2 required which results in higher
costs. In a sensitivity analysis both studies showed the strong dependence of economic feasibility on
the oil price. Net savings of around $19 per ton CO2 at oil prices of $40 per barrel (Damen) are shown.
Heddle even is more optimistic reporting a return of $30 per ton CO2 if oil price is $23 per barrel.
Current oil prices will considerably change the economics of EOR projects.
17 Production of enhanced oil over lifetime of 15 years 18 costs include capture cost from a hydrogen plant that has to be retrofitted in order to generate a pure CO2 stream
33
Table 7: Estimated CO2 storage cost for ECBMR projects
Heddle Damen Parameter Unit Case 1 Case 2 Case 3 Location China CanadaCO2 effectiveness scm CO2/scm enhanced CBM 2 1.64 1.64
EUR/GJ 1.7 3Gas price $/GJ 2 2.2 3.84
Depth m 610 1000 1000Pipe distance km 100 50 50
Mscm enhanced CBM/day 1.88 PJ 149 66Total CBM production Mscm19 4,162 1,843.5
Number CO2 wells 135 36 42Number CBM wells 135 49 56
EUR/tCO2 5 6CO2 storage cost $/tCO2 -5.59 6.4 7.7
Source: Heddle (2003) and Lysen (2003)
Concerning the economics of ECBM recovery Heddle again show a positive calculation, estimating a
surplus of $5.59 per ton CO2. In comparison ECBM projects for cases 2 and 3 are assumed to operate
at greater depths. Therefore investment costs for injection and production wells will increase resulting
in CO2 storage costs of $6.4 per ton stored for china and of $7.7 per ton stored in the case of Canada.
Also total production over lifetime is lower than in the case of Heddle. In both studies the sensitivity
analysis demonstrated that gas price and CO2 effectiveness have the greatest impact on storage costs.
2.3.3.3 Ocean
Costs of ocean storage are a function of the transported distance and injection depth. The system
boundary composes of the offshore transport of CO2 and the injection facility at the ocean. Costs of
onshore transport are not part of ocean storage. Determine economics of ocean storage can yet be just
an approximation because the precise mode of injection and preferred depth are still unclear (Freund,
et. al. 2002) and field experiments are not possible. This results in a great variation of parameters used
for estimation and so also in high spans of reported costs.
First storage via subsea pipeline and second via ship tankers will be examined.
Via pipeline
To run pipelines on the sea floor capital investments for the subsea pipeline, the injection unit and
boost compressors are required. Costs nearly only depend on the distance and amount of CO2 to be
transported. Some studies do not take into account cost for compression, although they show
19 total CBM production over 20 years, calculated assuming a LHV of 35.8 MJ/scm for CBM gas (Damen, et. al. 2003)
34
significant impact on storage costs. Besides reporting of taken assumptions in published studies are
often poor. Therefore storage costs ranging from $1.5 to $31.1 per ton CO2 net stored can be found.
The subsea pipeline scenario of Sarv (1999) as one example comprises of six parallel-laid pipes with a
diameter of 30 inch. It is assumed that CO2 storage takes place 500 km from the shoreline. Capital
costs were estimated at $2,084 million and total O&M costs at $81.8 million per year with project
lifetime set on 20 years. Based on the data and under the assumption of 200 million tons of CO2
disposed per year, costs of $1.5 per ton CO2 disposed was estimated. Hence cost of compression was
not taken into consideration.
In comparison Heddle assumed a smaller scenario with a subsea pipeline of 100 km and a diameter of
14.2 inch, capital costs of around $74.75 million and, O&M costs 5.6 million. These costs include
expenses for compressors $9.355 million. Transporting 22,167 ton of CO2 per day (around 8.1 million
per year) storage costs are $5.53 per ton CO2. The examined high and low cost cases show a range of
$2.9 to 14.23 per ton CO2 stored.
Comparing further studies storage costs range from $5.7 to 6.2 per ton CO2 for pipeline length of 100
km at a depth of 3,000 m. Costs for larger transportation distances (500 km) are given at $31.1 per ton
CO2.
Via tanker
For the purpose of storing CO2 in the deep ocean via use of tanker, costs can be divided in the
following three components (IPCC 2005):
- coastal/onshore tank storage of CO2
- shipping of CO2 (tanker)
- injection platform, vertical pipe and nozzle (or injection ship, pipe and nozzle)
Not all studies include costs for onshore based collection centres and just take into account storing
costs comprising shipping and injection. Among other factors the tanker ship will influence costs due
to CO2 capacity, speed and fuel usage. Heddle estimated around $55.3 million per tanker with a
capacity of 22,000 scm and a speed of 33 km/hr while Sarv (1999) published costs of $1,900 million
for oceanic tanker with the same capacity. Capital investment for the offshore injection platform is
given at $200 million (Heddle) and $100 million (Sarv).
When calculating CO2 storage costs, fuel consumption and therefore emission of additional CO2
caused by ship transport has to be taken into account. To consider boil-off and exhaust emission the
appropriate measure would be net storage costs instead of costs of CO2 shipped.
For injection of tanker transported CO2 Sarv assumed a vertical 64 inch pipeline with a length of 3,000
m where 200 million CO2 shall be injected yearly. Reported capital cost case were $2,034 million
including $100 million for the offshore floating platform. O&M costs are assumed to be $151 million
per year. With this database Sarv obtains costs of $1.8 per ton CO2 disposed. Hence that here extra
35
emission of the tanker and investments for onshore storage facilities are not taken into account. Costs
just describe offshore transportation and injection.
In comparison estimations by Heddle (2005) include all three mentioned components and consider a
boil off of 1% per day. With an assumed amount of 22,167 tonnes of CO2 per day transported (around
8.1 million per year) and emissions of tanker and boil-off the net storage will be 8.04 million CO2 per
year. The base case uses three tankers of 22,000 scm, one vertical pipeline of 6.5 inch and
transportation distance of 100 km. For onshore facilities $50 million were assumed. Total capital
investment for the base case is $550.8 million. O&M costs are around $13 million per year. Therefore
Heddle estimated $17.64 per tonne CO2 net stored. For larger offshore distances (300 km) and a boil-
off of 2% reported costs are $22.79 per ton CO2 net stored.
In further studies cost estimations are more positive reporting $11.5 and 12.8 ton CO2 stored for (100
km and 500 km). With consideration of extra emission costs increase at $11.9 and 13.2 ton CO2 net
stored. At all, published studies agree that ocean storage via tanker could be only economic compared
to subsea pipelines if CO2 is injected at great distances as costs of subsea pipelines scales with the
pipeline length. The reported critical distance ranges from 500 km to 800 km. This will depend on the
size of projects and amount of CO2 to be transported.
2.3.3.4 Conclusion
Storing CO2 is still a new climate change mitigation option. Commercial assessment is yet limited to
projects of enhanced oil recovery. Concerning other geological storage option there is only the
Sleipner project in the North Sea. Further projects for saline formation are planned in Norway,
Australia and Germany (IPCC 2005). Ocean storage has not yet been applied in any way. Therefore
economic evaluation of CO2 storage can only base on estimations from field experiments or on
experiences of similar technologies. Costs will depend highly on type of storage option and the site-
specific characteristics of the chosen reservoir. Enhanced oil and coal bed methane recovery are the
only options where injection of CO2 and storage can generate a surplus. Current oil prices will make
these projects even more attractive but projects have to be optimized for CO2 storage in order to secure
permanent storage.
Local regulations will influence the assessment of storage technologies like in the case of the Sleipner
project at which the CO2 tax in Norway made storage more economic.
2.3.4 Economic Outlook
Carbon capture and storage in geological reservoirs are widely seen as promising options to reduce
emissions. Technological improvements, economies of scale as well as research and development will
impact the reduction of capture and storage costs. Hence the capital costs will decrease and the
efficiency will increase significantly. A further reduction of capital and energy costs depends on
solvents and system components. Future costs reduction include the investigation of innovative
36
technologies like new types of power plants and power cycling. The highest reduction in energy
requirements is predicted for IGCC and PC plants in the carbon capture process (David 2000).
Geological and ocean storage might not provide permanent storage for all of the CO2 injected. The
question arises of how the possibility of leakage from reservoirs can be taken into account in the
evaluation of different storage options and in the comparison of CO2 storage with mitigation options in
which CO2 emissions are avoided. Non-permanent storage options will be economically attractive
which depends on the leakage rate, discount rate and relative carbon permit prices.
The size of the future CCS market depends on the stringency of the policy requirements assuming that
climate stabilization targets are reached. Another additional fact is the carbon intensity. Investments
are required for the integration of CCS as a whole in the electricity sector but they are subject to major
uncertainties. The uncertainties include the fuel prices, the level of economic growth, the carbon
dioxide constraints, and economic viability of low-carbon technologies, and policy implementation. In
addition to current and future CCS technological costs there are other not well known circumstances
which will affect the future deployment of CCS (e.g. costs related to the monitoring and regulatory
framework, possible environmental damage costs, and possible public-acceptance problems). There
exist a considerable scope for new ideas to reduce costs of CO2 capture and storage. These ideas will
accelerate the development and introduction of CCS.
2.4 Implementation of CCS in a Model
2.4.1 Introduction
The future technologies of capture and storage depend on different factors which are not known in
advance. Further a modeling of the electricity sector based on available information is necessary to
make certain decisions concerning the development in the near term and over the century. This section
examines some models of capture and storage technologies including the ‘top – down’ and ‘bottom –
up’ approach of several studies. The ‘top – down’ model represents the overall energy – economic
view, while the ‘bottom – up’ model focuses on the physical and geographical details. The section is
composed of models, their assumptions and their results. The chosen papers support the understanding
of the global potential for the CCS technologies as a mechanism for emission abatement.
2.4.2 EPPA
McFarland et al. introduced a top-down model with integrated bottom-up engineering data based on
the MIT EPPA model. The purpose was to simulate three scenarios for the electric power sector with
two CCS technologies to observe future effects of CO2 emissions. Competing with existing electricity
generation technologies three new electricity generation options were adopted: (a) a natural gas
combined cycle (NGCC or advanced gas) technology without CCS, (b) a natural gas combined cycle
37
technology with CCS and (c) an integrated coal gasification technology with CCS. These technologies
were introduced into multiple regions of a global economic model competing with conventional fossil
generation, nuclear and renewable power generation within EPPA’s electricity sector.
CElectricity = CGeneration + CTD + CSequestration + κPCarbon (1)
As shown in Eq. (1) the total unit costs of electricity are determined as the sum of generation,
transmission and distribution (T&D), sequestration and cost of carbon that is not captured. The factor
κ20 describes the technology-specific rate of carbon emitted to the atmosphere for each unit of
electricity produced. The model started in 1995 and went recursively on 5-years steps through 2100.
Every scenario was simulated and compared with each other. The reference scenario contains no
greenhouse gas constraints in any region. A second scenario includes carbon taxes which are phased in
2010 with $50 per metric ton carbon and increases by $25 every five years to a maximum of $200 by
2040. Thirdly they created a concentration stabilization scenario introducing a greenhouse gas quota in
each region. Greenhouse gas emissions are reduced by 18% from 2000 to 2010 and had been
decreased by 12% averagely in subsequent periods dependent on current gross national product
(GNP). Beyond 2100 CO2 concentrations amounts approximately 550 ppm. Emissions decrease
explicit in both policy scenarios in contrast to reference situation. In 2100 the tax case realizes lower
emissions by 37% from reference. Since 2040 CO2 emission had been accelerated rapidly the
maximum tax level is reached. The intensity scenario follows climbing emission path21 and declines as
from 2025 by 3 - 4% periodically. Results of latter case reached 1995 emission levels in 2085 and
represent lowest CO2 emissions of all cases. But imply high carbon-equivalent prices rising
exponentially to $1600/mtCeq by 2100 in using CCS technologies which resulted in higher fossil fuel
demand and slight availability of explicit low-carbon emitting technologies. In the reference scenario
total electricity production increased up to 64 trillion kWh in 2100 with a conventional technology22
share of 78%. The role of capture technologies became more important in the tax case. The whole mix
of generation technologies changed strongly where CCS technologies for coal and gas entered the
market at a carbon price at $100/mtC by 2020. Electricity generation by gas CCS reached 16% of total
production in 2040 and after these decades portion declined caused by growing natural gas prices.
From 2075 on the coal CCS technology expands rapidly and passed conventional technologies with a
share of 50% of total electricity generation. The tax scenario leads to a total electricity generation of
57 trillion kWh with a deviation of 11% from reference by 2100. The adoption of CCS is nearly
similar in the stabilization scenario. Gas and coal capture generation penetrated the market by 2040 at
carbon prices of $100/mtCeq similar to latter scenario’s entry price. Even in 2070 the coal CCS
generation reached proportion of over 50% total electricity produced and gradually displaced the
20 κNGCC = 0,092 kg C/kWh, κGas CCS = 0,010 kg C/kWh, κCoal CCS = 0,020 kg C/kWh 21 These increased emissions were caused in GNP growth. 22 conventional technologies are primarily coal-based
38
leading advanced gas and conventional generating technologies since coal capture had been entered
the market. Rising natural gas prices were responsible for a decline in appliance of gas generation
beyond 2050, too. The global electricity production in that case drops more than 20% from reference
levels in 2100.
Based on the results of this simulation McFarland et al. ascribed the coal CCS technology the most
economical long-term potential in future for CO2 emission reduction. CCS of gas technologies does
not become competitive by limited gas resources caused by increasing natural gas prices. Generally
the adoption of CCS will make good economic sense in cooperation with policy constraints on CO2
emissions.
2.4.3 MARKAL
Gielen (2004) analyzed the CCS technologies using the IEA Secretariats’ Energy Technology
Perspective (ETP) model. It belongs to the so called MARKAL family of bottom – up approaches
describing the global energy demand and supply for the periods 2000 to 2050. In this model the world
is divided into 15 regions, which are: Australia/New Zealand, Africa, Canada, China, Central and
South America, Eastern Europe, the Former Soviet Union, India, Japan, Mexico, Middle East, Other
Developing Asia, South Korea, USA and Western Europe.
ETP is a linear programming model that minimises an objective function calculated as a sum of
annualised costs of an energy system. An equilibrium that would be achieved in an ideal market and
maximization of welfare is represented by the model solution. The ETP model is based on perfect
foresight and does not include the risks of the technology development and political conditions. The
advantage of this type of model is that it estimates long-term investment decisions for complex
systems due to future technology features which differ from current technology. The model base
consists of technology data including several existing technologies and new ones that cover the whole
energy system.
The parts of CCS CO2 capture, transport and storage are modelled. For the electricity sector CO2 the
capture process has been modelled including manufacturing processes in the energy intensive
industries and the production of transportation fuels. In the electricity sector, fossil fuel fired power
plants with capture compete with the same plants without capture and miscellaneous other low-CO2
energy supply options such as renewables. Storage alternatives include onshore and offshore aquifers,
CO2 use for Enhanced Oil Recovery (EOR), Enhanced Gas Recovery (EGR) and Enhanced Coalbed
Methane Recovery (ECBM).
The analysis of Gielen presents the characteristics of CO2 capture technologies divided into costs
expressed per kWh electricity and per ton of CO2 captured. Storage and transport costs are not
included in this calculation. All selected costs in Table 8 are computed for a specific price of $1.5 per
GJ for coal and $3.0 per GJ for gas.
39
Table 8: Cost Calculation of CCS technologies
Fuel/Technology Starting Capture Cost Electricity Cost Additional Cost
[$/t CO2] [Mils/kWh] [Mils/kWh]
Prospective technologies
No CO2 Capture
Coal, IGCC 2010 37.4
Coal, IGCC 2020 33.0
Gas, CC 2005 26.1
Gas, CC 2015 25.2
With CO2 Capture
Coal, IGCC, Selexol 2010 20 52.3 14.9
Coal, IGCC, Selexol 2020 11 41.0 8.0
Gas, CC, Back-end CA 2010 29 36.8 10.7
Gas, CC, Front-end
Selexol 2020 25 34.8 9.6
Speculative technologies
No CO2 Capture
Coal, IGCC & SOFC 2030 41.3
Gas, CC & SOFC 2025 30.6
With CO2 Capture
Coal, IGCC & SOFC 2035 13 49.0 7.7
Gas, CC & SOFC 2030 28 39.2 8.6
Note: CA = Chemical Absorption. CC = Combined Cycle. IGCC Integrated Gasification Combined Cycle. SOFC = Solid Oxide Fuel Cell. Source: Gielen et. al. (2004)
These operating figures contain a significant cost reduction potential for both coal and gas fired power
plants. Gielen estimated that the additional electricity costs for plants with CCS will decrease. Further
CCS technologies will be more competitive with other mitigation options. Cost reduction will cause
high efficient capture technologies and higher efficient power plants with low quantities of captured
CO2. Plants with CCS technology require additional equipment and energy use in comparison to the
same plants without CCS caused by additional electricity costs. Therefore it can become a key
technology for CO2 emission reduction in the first half of the 21st century. Without these technologies
the CO2 emission stabilization would increase significantly in the long run.
The electricity sector represents by far the most important sector in which CCS can be applied.
According to the ETP model analysis, up to 78% of all CO2 capture will occur in the electricity sector
by 2050. Regarding the power generation the part of renewables will increase importantly due to
learning effects concerning their use. By contrast the part of fossil fuelled power plants with CCS will
40
decline. The learning potential for renewables is an important uncertainty for the future role of CCS
reviewed in Figure 9.
Figure 9: Electricity production capacity
Source: Gielen et. al. (2004)
The scenarios of the analysis point out the key factors which have an impact on the use of CCS
technologies: the future acceptance of nuclear energy, the electricity market structure and economic
growth. Currently it is imaginable that these different technologies can coexist in the future.
CCS projects can reduce CO2 emissions significantly by several Megatons. Uncertainties should be
minimised with the aid of additional Research and Development regarding the feasibility and the
permanence of storage. Continuous validation and monitoring systems need further development. The
paper of Gielen points out possibilities to develop systems similar to the Clean Development
Mechanism (CDM).
2.4.4 MiniCam
Kim and Edmonds23 investigate in their study “Potential for Advanced Carbon Capture and
Sequestration Technologies in a Climate Constrained World” the future realisation of carbon capture
and storage technologies for the stabilization of atmospheric CO2 concentration. Therefore they utilise
the MiniCAM Model from the Pacific Northwest National Laboratory (PNNL). This global partial
equilibrium model enables the simulation of interactions of population, economy, energy, agriculture,
land – use, greenhouse gas emissions and atmospheric dispositions. The application supports the
investigation of the impact of climate change policies and technologies on emissions mitigation.
According to Kim et al. (2000) the MiniCAM Model runs in 15 year time steps from 1990 to 2095 and
23 both are researchers of the Joint Global Change Research Institute (JGCRI), a collaboration of the Pacific Northwest National Institute and the University of Maryland
41
includes 14 regions. The model is able to link carbon taxes, carbon permit trading and carbon
constraints with numerous fossil and non-fossil based technologies worldwide.
The Reference scenario adopts an assumption of a future coal dominated world from the
Intergovernmental Panel on Climate Change (IPCC) excluding any emission restrictions or efforts to
reduce GHG emissions. Besides this reference scenario the study includes various cases with and
without the utilisation of carbon capture and sequestration technologies. These further elements of the
analysis contain different atmospheric CO2 concentration scenarios that constitute constraints of 450,
550, 650 and 750 parts per million of volume (ppmv). In addition to the one coal dominating reference
assumption an alternative oil and gas based reference case is investigated.
Results of this analysis are predictions about the development of primary energy consumption, future
amount of generated electricity, carbon emissions and carbon taxes whose levy will be necessary to
achieve a stabilized CO2 concentration of the atmosphere. All results except the latter one are
subdivided into fuel and region (OECD and Non – OECD countries24). Each value is compared to the
reference case. The authors mention that detailed comparisons across fuels and regions are provided
for the 550 ppmv case only, as it represents the middle range of the extremes studied. For more
detailed results than mentioned below we refer to Kim et al. (2000).
Despite no assessment of carbon storage is made by the researchers they note that necessary storage
capacity is available when comparing the cumulative emissions to the reservoir estimates of Herzog et
al. (1997).
In the reference case the primary energy consumption quadruples from 1990 to 2095. This expresses a
growth slightly above 1250 EJ per year in 2095. 56% of the total global energy consumption will be
contributed by coal along with 24% gas and 6% oil. Sources like biomass, solar, nuclear and hydro
will contribute 14% of primary energy consumption in 2095. Nearly 70% of primary energy will be
consumed by Non – OECD countries due to the rapid economic and energy consumption growth. The
global demand for electricity will even exceed the primary energy consumption growth as there is a
nine-fold increase from 1990 to 2095. By the end of the next century coal will contribute to 47% of
electrical power generation while gas will contribute to 27%. Carbon emissions will increase from 6
BtC in 1990 to 24 BtC in 2095.
In a next investigated case Kim and Edmonds introduce carbon emission constraints but neither
capture nor storage technologies. Due to the imposed constraints global reference energy system will
change dramatically. For the 550 ppmv case primary energy consumption is reduced by 33% in 2095.
According to the authors the global energy system moves toward conversation along with use of non–
carbon fuels (e.g. solar, hydro, biomass or nuclear) and moves away from fossil fuels. Beside
reduction of primary energy consumption the generation of electricity declines, too. Electricity
generation in 2095 is reduced by 14% in the 550 ppmv case in comparison to the reference level.
Induced by restrictions combustion of coal is nearly eliminated in 2095. Due to a lower content of
24 the USA representative for the OECD and China for Non – OECD
42
carbon gas and oil are still used but less in relation to the reference scenario. For the restricted (550
ppmv) scenario without capture and storage technologies gas and oil contribute to 97% of total CO2
emissions by the end of next century. The remaining 3% are caused by coal.
In the concentration case with Carbon Capture and Storage technologies electricity generation will
exceed the value of the reference case by 11% despite declining numbers of consumed primary
energy. Kim and Edmonds mentioned a transition to more and more utilisation of electricity for energy
services. As the main reasons for lower consumption of primary energy the authors cite fuel efficiency
improvements, greater use of electricity for end – use energy services and conservation from higher
fuel prices.
Fossil fuels will contribute to 81% of electricity, Figure 10. Due to higher efficiencies of CCS power
plants and the CCS technology alone higher input rates of fossil fuels are possible within given
constraints of CO2 concentrations in the atmosphere.
Figure 10: Electricity Generation by Type - Global 550 ppmv Case with CCS Technologies
Source: Kim et al. (2000, p. 38)
The two researchers point out that higher efficiencies of future power plants alone are not sufficient to
reach the concentration targets. The major mitigation of emission is provided by capture technologies.
By 2095, the comparison of carbon taxes for the 550 ppmv case shows a tax of $89 per ton of carbon
with application of CCS and $319 without utilisation of CCS technologies. Compared to 450 and 550
ppmv cases carbon taxes fall in the less stringent cases with 650 and 750 ppmv from 2020 to 2095.
Increasing carbon taxes are explained by the writers of the study with falling oil prices induced by the
43
rising switch to electricity in all end – use sectors, especially in the transportation sector. To achieve
fuel switching from oil to electricity in the transportation sector increasing carbon taxes are necessary.
The analysis also focused on the costs of stabilization. Therefore direct total costs are defined as the
deadweight loss to the global economy for required mitigation of carbon emission at certain carbon
taxes. Kim and Edmonds measure the value of CCS technologies by calculating the difference
between the deadweight loss of meeting concentration targets without CCS and with CCS. This
difference is in the 550 ppmv case quoted with $1.741 billion25.
Particularly the authors point out that the stabilization of atmospheric CO2 concentration can be
achieved at lower costs with capture and sequestration technologies.
25 present value discounted at 5% (Kim et al., 2000)
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3 The Transportation Sector - Structure and Introduction into an
Emission Trading System
3.1 Technological Description of the Transportation Sector
Transportation means moving a good or a person from one place to another using means of transport.
Especially the motorized transport provided by vehicles across air, water, tracks and streets plays a
major role in emission considerations. In EU 15 the transportation sector accounts for 26.54%26 of all
carbon dioxide emissions. We concentrate on carbon dioxide corresponding to the regulations in the
Kyoto protocol and with regard to its quite simple measurement, even though each other greenhouse
gas has a much more dangerous effect on the atmosphere (see table global warming potentials).
Another aspect is that working measures on CO2 emission reduction usually also minimize the amount
of other emissions like SO2 and particles. On the other hand the volume of traffic continuously
increased during the last decades and threatens the efforts made concerning the energy efficiency of
vehicles. From 1997 to 2010 kilometers travelled increased by 23% and emissions by 15%.
Transport activities can be distinguished into transport of persons and transport of freight. They will
differ significantly from each other in matters of driven distances, chosen means of transport, cost
structure, transport occasion and last but not least in unit of measurement. Persons mainly use their
own car. Today out of 1000 inhabitants 495 have a private car. In urban regions public transport
means such as underground, trams, buses and taxis gain in importance. There exists a great variety in
transporting freight. For short distance routes mostly trucks are in use. Ship transportation is
considered as quite cheap and practicable for homogenous and bulk goods moved on inland waterways
as well as across oceans. Long-distance transports are mainly conducted by aircrafts. Irrelevant for our
purposes is transportation of oil and gas via pipelines, which has an unimposing share in terms of
traded volume and emissions in relation to the total amount of transportation.
These are the so called direct emissions produced by the described means of transport. The indirect are
e.g. burning coal to provide current for trains. They are mainly already integrated into the European
Emission Trading System (ETS) so that they do not affect our considerations. Our aim is to find a way
to integration the direct emissions into the ETS. The general reduction plan aims at reducing them
about 334 Mio. tons CO2, i.e. 8% based on the year 1990. Usually a higher price for one good results
in a lower demand for it. As we will see in section 3.2.2 every approach will mean higher costs for the
consumers. But they have a range of possibilities to reduce their emissions.
26 Based on values in Annex 1
45
First of all measures have to be implemented to reduce the kilometers driven. Mobility is defined as
the average total number of ways per day and person. In detail usually information on average number
of ways, length of ways, differences in mobility concerning age and type of household, used means,
aim of way is collected. In some countries short-haul (10 – 100 km) and long-haul (more than 100 km)
distances are distinguished. Unfortunately at the moment there is no general statistic on the mobility of
persons available in Europe. Every country has its own definitions and methods of measurement. For
another view on the topic the relationship between mobility and time budgets can be used. In general
this means improving the local infrastructure with physical rearrangements and offering a variety of
public transportation possibilities can help to fulfill the persons’ requirements concerning mobility in
the future without increasing the volume of traffic. That is an essential governmental challenge.
3.2 CO2 Reduction Methods for the Transport Sector
Transportation accounts for a huge amount of CO2 emissions in Europe as we showed in the previous
part. So it seems to be necessary to find methods to reduce the climate harming carbon dioxide
emissions. Therefore mainly two approaches can be pointed out. On the one hand we can reduce CO2
emission by technological innovation and on the other hand we can give emissions a value by
installing an emission trading system.
3.2.1 Technological Innovations
Technological inventions are an approach to reduce specific fuel consumption. They play a major role
in long-term considerations. Recent trends in research are fuel cells and hybrid cars. Fuel cells are an
innovative and almost emission free power technology for electric vehicles. Combustion takes place in
a galvanic element with a theoretical degree of efficiency of around 83%. Between two electrodes
there is an ion exchanging electrolyte. Fuels cells can be distinguished along to the used fuel and
electrolyte. Especially the PEMFC (Proton Exchange Membrane Fuel Cell) is an easily to handle and
already mature technology that is applied in producing current as well as in cars and buses. By
reforming methane and methanol, hydrogen is produced as fuel and provides a power up to 250 kW
with a degree of efficiency of 60%. The DMFC (Direct Methanol Fuel Cell) is an enhanced PEM fuel
cell, with the advantage of leaving out the conversion of liquid methanol to hydrogen. Still some
efforts in physical lifetime and stability of the catalyst are necessary until the DMFC can be applied.
Hybrid cars combine a fuel cell with a conventional diesel motor and change engine according to the
current driving situation. When starting to drive and usually in towns the diesel aggregate comes to
use for its lower rate of consumption while on motor-ways the fuel cell is more efficient. This change
is made automatically without disturbing the driver. So a long range of one tankful can be reached and
46
the driver is not dependent on a near hydrogen station. Up to now still unfavorable is the vehicles’
heaviness.
Another field of study are new construction methods for vehicles. Starting with rearrangements of
small parts in the cars up to a completely new design of the whole carriage the principles of
lightweight construction get implemented. Combined with efforts in material research lots of
ameliorations have been made. High strength steels improve accident performance as well as a
substantial reduction of weight. New processes allow a more extensive use of magnesium and
aluminium. Even natural fibers such as hemp became interesting for constructing engineers.
Reducing the vehicle’s specific emissions is another field of new technological applications usually
associated with lower interventions and investments as the foresaid technologies. Newly developed or
rediscovered fuels contain less carbon, so that altogether emissions can be considerably reduced.
A certain consumption of fuels registered by the gas stations produces a well defined amount of
carbon dioxide emissions independent from the means of transport. Every fuel has its specific
emission factor. A gasoline car in the EU 15 emits 173 g/km while a diesel vehicle only emits 156
g/km. This averages out to 166 g/km; other fuels like the so called bio fuels have little influence on
that figure. In Germany the intention for the share of alternative fuels is an increase on around 25%.
The automobile industry committed in 1998 to reduce the specific CO2 emissions of new vehicles by
20% until 2008. This means a limit of 140 g/km or an average consumption of 6.2 liters per 100 km.
Extra Low Emission vehicles are a new generation of diesel motors that have similar emission figures
as gas vehicles. Up to now their high price retarded a common use. At the moment new cars consume
on average 6.9 liters and the whole German vehicle fleet 7.8 liters. Voluntary commitments like this
one appear to be only an efficient instrument and an alternative to legal regulations when there is some
governmental and public pressure behind it.
Other governmental arrangements are targeted on the customers’ autonomy of decision. There are
plans to introduce a national control and customer information system that registers the average carbon
dioxide emissions and fuel consumption of new cars. Another possibility is to oblige car salesmen to
inform their potential purchasers about the emission and consumption figures.
Costs for any governmental arrangements are obviously higher than by a self regulation through the
market. Many surveys determine the emission trading system as the most efficient instrument to
reduce CO2 emissions.27 In the next part we will show that by choosing a good implementation method
for an emission trading scheme it can even give strong incentives for technological innovation.
27 E.g. Bergmann, H. et. a.l (2005):
47
3.2.2 Approaches for Emission Trading in the Transportation Sector
This section shows different flexible methodologies of emission trading in the transport sector. The
approaches are separated by the actors which are acting in the transport market. Hence the participants
can be divided in
- The “Supplier of fuel”, which are producing or importing fuel
- The “producer of means of transportation”, which are producing cars and are responsible for
the exhaust of emissions
- The “participants of transport”, which are those who actually produce the emissions by
consuming fuel.
According to the participants there are three different approaches to account CO2 in the transport
sector shown in Table 9.
Table 9: Approaches to account CO2
Participant Approach
Supplier of fuel Up-Stream
Producer of means of transportation Mid-Stream
Participants of transport Down-Stream
In the following the approaches are explained further.
3.2.2.1 Down-Stream Approach
The down-stream approach sets at the road user and aims a causer-fair and direct delimitation of the
CO2 emissions with the final consumer of fuels as the last member in the energy flow chain. Hence all
emission sources are required to hold emission permits.
At first an absolute CO2 emissions aim would be specified for a certain period. After producing CO2
emission forecast is for passenger transportation and freight transportation the goal will be divided to
the respective sectors for the period.
The system leads over price effects to a rising of the price of fuels and traffic services and in
accordance to an adjustment of the total demand to the cap and/or to the reduction decrease.
3.2.2.2 Mid-Stream Approach
The mid-stream approach sets at the means of transport manufacturer aims at the change of the relative
prices between different motor vehicle types and sets so a direct incentive for the reduction of the
specific emissions by technical innovations and actions. All manufacturers of road vehicles would be
engaged to the indication of the number of sold vehicles and the according specific CO2 emissions
and/or on the basis standard fuel consumption of the new vehicles. Besides product groups (e.g. upper
class cars, cars in the medium range and small cars) would be formed, for which the emission-relevant
factors (middle lifetime, middle yearly road performance, number of set off vehicles in the product
48
group) were determined. The manufacturers would receive certificates over a grandfathering in
dependence of its market shares (number of the sold vehicles). At the year end the sold quantities of
new vehicles were compared with the existing emission rights. Are more (less) products sold than
rights present are, then the manufacturer would have to buy (or to sell) the appropriate quantity of
emission rights. The costs of the emission trade would put down on the product prices and over-rolled
on the final consumer. The rights could be acted thereby on an open market unrestrictedly or however
on a closed market only within the vehicle manufacturers.
3.2.2.3 Up-Stream-Approach
The up-stream approach tries to capture the supply of fuels and the according CO2 emissions of traffic
at the beginning of the energy flow chain (for example with the refineries or importers). Because of
the direct correlation of fuel quantity introduced to the market and the emission quantity developing
with the burn of fuel whole emissions can be measured. Among all participants involved, who make
available and/or introduce CO2 relevant sources of energy to the market, the CO2-target could take
place via grandfathering, auctions or a mixture of both.
All relevant sources of energy, especially fuel products, which are delivered from the participants,
would be registered in a registration procedure. For each participant the sold fuel quantity was
compared with the existing emission rights. If more (or less) fuel is sold than rights exists, then the
participant would have to buy (or to sell) the according quantity of emission rights The costs of the
emission trade were passed on by impacts on the product prices to the final consumer. The rights could
be sold again on an open market unrestrictedly or however alternatively on a closed market only
between the participants involved.
3.2.2.4 Valuation of the Different Approaches
Regarding the criterion of precision to reach the CO2 target those approaches with direct emission
targets fared best. Approaches like the mid-stream approach reach however a clearly smaller exactness
of reaching the ecological aim, because the fulfilment of absolute CO2 aim depends on the concrete
handling of the vehicle owner (speed and acceleration behaviour, etc.).
The conformity to insert an emission trading into the existing social, economical and legal framework
is better with an approach using specific emission targets, as this allows a wider scope. Absolute target
produces in a situation of scarce certificates a clearly higher pressure on the market.
There are significant differences between the number and type of market participants under an up-
stream and a down-stream design, which directly influence transaction costs. An upstream design will
have far fewer and much bigger participants than a downstream design. In terms of the impact on
administrative efficiency, fewer players in an upstream design will be easier to manage and monitor. A
downstream design has the potential to become impractical, with potentially large numbers of
49
participants including small businesses and domestic households, leading to high administration and
monitoring costs (Baron, 2002).
Altogether it can be noted that an up-stream approach for a CO2 emission trading in the traffic sector
appears superior due to clearly smaller transaction costs as a down-stream approach. Due to the
possibility, to capture all energy-conditioned CO2 emissions from the traffic sector completely and in
absolute height seizes, as well as the relatively small bureaucratic expenditure by the use of existing
logging systems, the up-stream approach shows in opposite to the down-stream approach clear
advantages. Its disadvantage lies meanwhile in the fact that it only exerts an indirect influence on an
increase of energy efficiency of the combustion engines over the vehicle demand. This applies
however to a down-stream approach equally.
3.2.2.5 Emission Trading Versus Fuel Tax
The most important tax, which concerns the traffic sector, is with distance the fuel tax. Because of the
direct correlation between fuel consumption and CO2 emissions the fuel tax is quite suitable as a
climate political instrument. But the present arrangement of fuel tax deviates however in some points
from the action committed basis. Thus the tax rates differ in fuel sorts and, also within these sorts,
after the content lead and sulphur. This is in environmental economical aspects only fair and efficient,
if differences in the tax rates relate to the climatic damaging character. In the present arrangement this
is however only in beginnings the case. In order to achieve a fair principle regarding to the causation
of CO2, some changes have to take place.
In general there is no quantity goal in a tax solution. It can be found out only over a trial-and-error
procedure. If the necessary effect is reached, it can not be hold for a long time because it loses its
incentive effect in the course of the time, because it does not adapt automatically to an increase of the
general price or level of income. An emission trade considers this problem automatically, because the
cap exists. This is one of the largest advantages of an emission trading system in relation to a tax
solution.
The advantage of CO2 taxation can be seen in the probably much smaller transaction costs of
implementation. While emission trading requires new structures and hence additional transaction costs
are caused, a pure tax increases would cause no considerable additional transaction costs. A change of
tax rate in accordance with the relative climatic damage character (orientation at the carbon content)
would only involve probably small administrative auxiliary costs.
The price of additional transaction costs of an emission trading system can be seen as a price for
higher efficiency against the tax solution.
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4 Modeling
A variety of models have been used to examine, how an economy might react to changes in policy,
technology or other external factors. Input-output models28, computable general equilibrium29 (CGE)
models and (linear and non linear) optimization models are noteworthy. We devote this chapter solely
to CGE models. Due to numerous research institutes, applying this model, they play an important role
in policy benchmarking. So we chose CGE modeling as a basis for our approach.
CGE systems incorporate utility- and profit-maximizing behavior, therefore demand and supply
equations as well as capacity constraints. These models are essentially empirical versions of the
Walras general equilibrium system and use the theoretical (neoclassical) assumptions of that system.
A CGE model consists of equations, which describe model variables, and a database consistent with
these equations. The database provides real economic data for policy analysis and comprises input-
output tables of transaction values and elasticities of substitution, which are dimensionless values
representing the behavioral response of producers and consumers30, respectively. These input-output
tables are referred to as Social Accounting Matrices (SAMs) and represent a mapping of the economy.
The empirical basis creates the constraints for the model structure and for sectoral detail. Moreover
there are often tradeoffs to be made between realistic detail for several technologies and the
computational demand of solving a complex model.
The structure of this section is as follows. In the next section we will give an introduction to general
equilibrium or Walras’ equilibrium theory. The next two sections will give an overview of two
common CGE models. In Section 4.2 the structure of the Global Trade Analysis (GTAP) model, a
worldwide economic and static model featuring a substantial database, is presented. Section 4.3
contains a description of a dynamic model more appropriate for specific examinations relating to
emission policies and based on GTAP, referred to as the Emissions Prediction and Policy Analysis
(EPPA) Model. The next section 4.4 represents the data base we use in our model approach and
section 4.5 describes its theoretical structure. Based on this data set, section 4.6 deals with the model’s
implementation in the General Algebraic Modeling System (GAMS).
4.1 General Equilibrium
General equilibrium theory was first developed by Leon Walras in the late nineteenth century; hence a
general equilibrium is often called Walras’ equilibrium. The general equilibrium approach seeks to
explain a whole economy by relating prices, production and consumption of all goods.
28 For a further discussion of input-output models see Perman et. al (2003) 29 Computable or applied general equilibrium models are derived from input-output models. We will use the term computable general equilibrium (CGE). 30 In the following the terms households and firms are used for consumers and producers respectively.
51
First we will describe the basic structure of an economy and the conditions it is subject to in a rather
general way. Subsequently a demonstration of a general equilibrium system is given, by means of an
example often utilized in literature, namely a 2x2 model of a production economy. This model consists
of two production factors and two goods. It is the basis for high dimensional problems applied for
general equilibrium analysis.
4.1.1 A General Formulation of an Economy
Basically an economy consists of agents, i.e. households and firms, and commodities. Households are
characterized by their utility function representing their preferences and possess an initial endowment
of commodities, i.e. factors. Firms demand these factors from households to produce goods according
to the production function that specifies the production technology. We assume that the technology
exhibits constant returns to scale and the firms make zero profits. Then the household’s budget is
specified only by the income earned by selling the factors.
Assume an economy defined by a representative household, featured with an initial factor endowment
and characterized by its utility function, by N firms and their production functions and by N
commodities. Further assume agents take prices for granted. Given these assumptions a Walras’
equilibrium is specified by prices and quantities such that:
(1) The household maximizes its utility under the budget constraint
(2) The firms maximize their profits
(3) The markets are either cleared or in excess supply
From condition (1) we obtain the household’s demand functions, which specify the optimal demand
for goods given prices, i.e. D(p). Since we assume zero profits, the income of the household consists
only of the sold initial endowment. Additionally, assume that the household is not able to consume its
endowment and hence it always sells its total endowment of factors.
From condition (2) we drive the optimal factor demand of the firms, which depends on the prices, that
is DF(p). Having this, the optimal supply of goods follows from the production technology and is a
function of the prices, i.e. S(p).
The optimal demand of the households, the optimal factor demand and commodity supply of the firms
obtained from the first two conditions, we can make up the following equation for the prices
S(p)D(p) ≤ This issue and the state of the prices in different cases of condition (3) will be discussed more
elaborated in the next section, were an algebraic example is given.
52
The First Fundamental Theorem of Welfare
Note that we seek for an equilibrium assuming profit maximization, which only ensures efficiency.
This has nothing to do with maximizing social welfare.
If every good is traded in a market at publicly known prices, and if households and firms act perfectly
competitively, then the market outcome, that is the Walras’ equilibrium, is Pareto optimal. This is
specified as the First Fundamental Theorem of Welfare, which in short states that under a complete
market and perfect competition the competitive equilibrium31 is Pareto optimal.
4.1.2 The 2x2 Production Model – an Algebraic Formulation
Now we will be more specific and assume an economy with a representative household and two firms.
This 2x2-model, two factors and two goods, provides a basic structure for more-dimensional, more
complex models, which are implemented in CGE systems. What follows is an algebraic presentation
of a 2x2 production-economy. Symbols not described in the text are specified in the list of
abbreviations.
Model Assumptions
The household has an initial endowment of capital (K) and labor (L) and obtains income only by
offering these two factors. The interest rate r and the wage rate w are earned per unit capital and labor,
respectively, sold. Firm 1 produces the good x1 and firm 2 produces the good x2, whereas each firm
uses capital (K) and labor (L) as inputs. Consider p1 and p2 as the prices of the goods.
Both firms and the representative household are characterized by Cobb-Douglas functions, i.e.
constant returns to scale (CRS).
Specifically, the utility function for the household is given by
It is initially endowed with
11 2 1 2( , ) H H
Hu x x x xα αγ −=
K a n d L
53
The technologies of the firms are
Competitive Equilibrium
Given this model, a competitive equilibrium consists of the quantities x1, x2, K1, K2, L1 and L2 and the
prices p1, p2, w and r such that
(1) Given prices, the household solves
KrLw M xpxp M ts
xxxxuxx
1
Hxx
DD HH
+=
+≥
== −
221
12121),(21
..
]),([max),(21
ααγ
(2) Given prices, the firms solve (i={1,2})
)]([max),( 1
),( iiiiiiiLK
Di
DI rKwLLKpLK i
ii+−== −ααγπ
(3) The markets are either cleared or in excess supply
Solving the household’s Maximization
The optimal bundle to be consumed follows by maximization of the utility function u(x1, x2). The
household’s choice must be consistent with its budget constraint, whereas the income M is given by
the initial endowment (K and L) and the factor prices (w and r).
31 i.e. the Walras Equilibrium. In the following we use the term competitive equilibrium.
1 1
2 2
11 1 1 1 1 1 1
12 2 2 2 2 2 2
( , )
( , )
x f K L K L
x f K L K L
α α
α α
γ
γ
−
−
= =
= =
S Di i
Di
i
Di
i
x x
K K
L L
≥
≥
≥
∑
∑
54
KrLw M xpxp M ts
xxxxuxx
1
Hxx
DD HH
+=
+≥
== −
221
12121),(21
..
]),([max),(21
ααγ
The Lagrangian of this maximization problem becomes
)(),,( 221112121 xpxpMxxxx HH
H +−+=Ψ − λγλ αα
Deriving the first order conditions and solving them simultaneously, we get the demand functions,
which give the optimal demand quantity of the households depending on the prices
Solving the Firms’ Maximization
A solution to the profit maximization problem
)]([max),( 1
),( iiiiiiiLK
Di
DI rKwLLKpLK i
ii
+−== −ααγπ
leads to the firms’ factor demand. Deriving the first order conditions and doing a bit of algebra yields
the factor demand functions. The optimal supply quantities are given by deploying the optimal factor
demand in the production function. Thus, the following set of equations (i = {1, 2}) specifies the
optimal behavior of the firms
( )
( ) ( )
1 11
2 22
1
DH
DH
Mx pp
Mx pp
α
α
=
= −
( ) ( )1
( , )
( , ) (1 )
( , , ) i i
D ii i i i
D ii i i i
S D Di i i i i
pK p r xr
pL p w xw
x p w r K Lα α
α
α
γ−
=
= −
=
55
Market clearing and Walras’ Law
The market clearing conditions are
Walras’ Law states that either the market condition holds with equality, i.e. the good is scare, or the
good is in excess supply (net supply > net demand). If supply equals demand the price is positive, but
if there is more quantity supplied than demanded the price drops to zero.
Denote (xiD-xi
S) as the excess demand function. Then it follows that the product of the market clearing
condition and the associated price is always zero since exactly one of them is zero (but not both!).
4.1.3 Concluding Remarks
So far we have derived the demand functions for the households and the factor demand functions for
the firms. These functions and the market clearing conditions determine the general equilibrium. Note,
if we have two markets and one of them is cleared or features zero prices, we are guaranteed that the
second market is in equilibrium, which is implied by the conditions of Walras’ Law. In general Varian
(1999) demonstrates, if there are markets for k goods, only k-1 independent equations for k-1 prices
are to be solved. We are free to set the final market k equal to a constant conveniently to 1. This price
is then called the numeráire price.
Walras’ Law states a relationship between prices and market clearing, hence it is known as a Mixed
Complementary Problem (MCP). The benefit of Mixed Complementary Problem is a linkage between
two common modeling approaches, namely bottom-up and top-down. The former provides a detailed
description of production technologies, which often refer to optimization problems meeting a given
demand subject to restrictions. On the other hand this rather technical approach lacks treatment of
market interactions due to model complexity. The latter approach dealing with econometrically-
specified production functions adopts broader economic framework and higher degree of endogeneity
in behavioral response to policy shocks, but features less treatment of specific sectoral and technical
detail. Böhringer (2005) emphasizes MCP bridges a gap between conventional bottom-up and top-
{ }1 2
1 2
1, 2S Di i
D D
D D
x x i
K K K
L L L
≥ ∈
≥ +
≥ +
( ) { }( )( )
1 2 1 2
1 2 1 2
0, 0, * 0 1, 2
0, 0, * 0
0, 0, * 0
D S D Si i i i i i
D D D D
D D D D
x x p x x p i
K K K r K K K r
L L L w L L L w
− ≥ ≥ − = ∈
+ − ≥ ≥ + − =
+ − ≥ ≥ + − =
56
down CGE models for policy analysis, since it relaxes so called integrability problems inherent in
bottom-up models. Both optimization and market equilibrium problems are equivalent and subject to
integrability conditions that imply efficient allocation. MCPs can be solved by using the General
Algebraic Modeling System (GAMS). GAMS is specifically designed for modeling large scale
problems and especially useful to solve complex general equilibrium systems. How to implement a
high dimensional general equilibrium is discussed in section 4.6.
4.2 The Global Trade Analysis Project (GTAP) Model
After explaining the theory of CGE-modelling, the authors will describe the structure of GTAP, the
extended energy version GTAP-E and the changes in the database in more detail. For better
understanding of the model, the used abbreviations are listed in the Appendix B.
4.2.1 GTAP
The Global Trade Analysis Project (GTAP) is a global network conducting quantitative analysis of
international policy issues on a global basis because the world economy becomes more integrated.
This project was established in 1992 and it consists of several components (see Hertel, 1997, p. 3):
• A fully documented, publicly available, global data base
• A standard modelling framework
• Software for manipulating the data and implementing the standard model (GEMPACK)
• A global network of researchers, linked through the Internet, with a common interest in
multiregional analysis of trade and resource issues
• A World Wide Web32 site for distributing software, data and other project-related items of
interest
• A consortium of national and international agencies providing leadership and a base level of
support
The GTAP standard model is a multi-regional static AGE model which captures world economic
activities in 57 different industries of 87 regions in the actual version 6 data package (GTAP
homepage33). These data base corresponds to the global economy in the year 2001. Applied General
Equilibrium (AGE) models are capable in providing “an elaborate and realistic representation of the
economy including the linkages between all agents” (Brockmeier, 2001, p.4).
32 https://www.gtap.agecon.purdue.edu/ 33 See: https://www.gtap.agecon.purdue.edu/databases/v6/default.asp or the Appendix B: GTAP Nomenclature.
57
Because the theory behind the GTAP model is similar to other standard, multi-regional AGE models,
the underlying equation system includes two different kinds of equations:
• accounting relationships, which means that receipts and expenditures of every agent is
balanced
• behavioural equations, which are based upon microeconomic theory (e.g. the
behaviour of optimizing agents in economy)
By giving an overview of the model structure we first focus on the accounting relationships and follow
the way of Brockmeier (2001) introducing the economic activities step by step. After that, we
characterise some important aspects of the behavioural equations.
4.2.1.1 Accounting Relationships
One Region Closed Economy Without Government Inventions
At the starting point there is a regional household which collects all the income that is generated in the
closed economy. This aggregated Cobb Douglas utility function allocates expenditure using three
forms of final demand:
• private household expenditure (PRIVEXP)
• government expenditures (GOVEXP) and
• savings (SAVE).
In this approach each component of final demand maintains roughly a constant share of total regional
income. So the standard closure of GTAP is represented (Brockmeier, 2001 p.5). This
equiproportional change in private expenditures, government expenditures and savings, caused by an
increase in regional income, as “the unambiguous indicator of welfare” (Hertel, 1997, p.15) is a great
advantage of the formulation of the regional expenditure.
To close the economy producers are added in the second step. This closed structure is shown in Figure
11 displaying only the value flows in the economy34. Because of the absence of taxes the only source
of income for regional households is the “sale” of endowment commodities to the firms which is
represented by the Value of Output at Agents´ prices (VOA). Together with intermediate goods
(VDFA35) the firms combine these endowment commodities in order to produce goods for final
demand (Hertel, 1997, p. 15 f.). For selling these consumption goods the firms receive payments from
the private households (VDPA36) and the government (VDGA37), from the other producers for
intermediate inputs and from the savings sector for investment goods (NETINV) to satisfy the regional
household’s demand for savings.
34 In the opposite direction exist corresponding flows or ownership of an asset. 35 VDFA = Value of Domestic purchases by Firms at Agents´ prices 36 VDPA = Value of Domestic purchases by Private households at Agents´ prices 37 VDGA = Value of Domestic purchases by Government household at Agents´ prices
58
The use of the nested production technology, which is described later in the section about the
behavioural equations in more detail, exhibits production of one single output in every sector and
assumes a weakly separation between the primary factors of production and the intermediate inputs.
Figure 11: One Region Closed economy without Government Intervention in GTAP structure
Source: Brockmeier (2001, p. 7)
One Region Closed Economy With Government Inventions
In the next step government interventions are added as additional value flows representing transfers
(either voluntary or involuntary) which are not accompanied by flows of goods or services crossing
the market in the opposite direction. These value flows denote net tax revenues38 because they include
both taxes and subsidies. They are paid by the government and the households as consumption taxes
as additional expenditures and by the producers as taxes on intermediate inputs and production taxes
net of subsidies. Now, the regional income consists not only of VOA, but also of the sum over all
taxes net of subsidies. Another result of introducing policy interventions is the distinction between
market prices and agent’s (tax inclusive) prices.
38 Named „TAXES“ in the graphs.
59
Multi-Region Open Economy
The last step to the multi-region open economy integrates a trading sector in the model. To prevent
putting all regions in one graph, which would be too much, all regions except one are combined to one
region called “Rest of the World” (ROW). The one single region is then used to show the changes in
the model structure which is required to model an open economy. By doing this, the accounting
relationships of all agents have changed again. The graph is shown in Figure 12.
Let us first take a look on the production side. The firms get additional revenues for selling
commodities to the Rest of the World. These exports are denoted by VXMD39. On the other hand, they
spend their revenues also on imported intermediate inputs (VIFA40) additional to the buying of
primary factors and domestically produced intermediate inputs. The additional consumption taxes on
imported inputs to the regional household are included in the TAXES flow so there is no change in the
graph.
An important fact of the whole GTAP model is the use of the so-called Armington assumption in the
trading sector. This means it is possible to distinguish imports by their origin and explains intra-
industry trade of similar products. Thus, imported commodities are assumed to be separable from
domestically produced goods and combined in an additional nest in the production tree where the
elasticity of substitution is equal across all uses. This assumption yields an optimal mix of imported
and domestic goods determined by the firms.
On the demand side, the government and private households spend their income not only on
domestically produced but also on imported commodities which are denoted as VIGA41 and VIPA42.
Both agents pay also additional commodity taxes on imports to the regional household. Imported
commodities are combined with domestically produced commodities in a composite nest analogous to
the production side. In this nest the elasticity of substitution is assumed to be equal across uses.
Since the variation in the third component of final demand, savings, cannot easily be represented in the
graph, it is simply denoted as GLOBAL savings because savings and investment are computed on a
global basis. If all other markets are in equilibrium under the zero profit condition for all firms and the
budget constraint for all households, then global investment must equal global savings to satisfy
Walras’ Law.
Finally, we have to check the accounting relationships for the Rest of the World. The income for the
ROW consists of payments for selling their goods for private consumption, government, and firms.
These revenues will be spent on commodities exported from the single region to the ROW, denoted as
39 VXMD = Value of exports evaluated at (exporter’s) market prices. 40 VIFA = Value of imported firms purchases evaluated at agent’s prices. 41 VIGA = Value of expenditure on imported tradable commodities by government household evaluated at agent’s prices 42 VIPA = Value of expenditure on imported tradable commodities by private household evaluated at agent’s prices.
60
VXMD43, and on import taxes, denoted as MTAX44, and export taxes, denoted as XTAX45, paid to the
regional household.
Figure 12: Multi Region Open Economy in GTAP
Source: Brockmeier (2001, p. 16)
4.2.1.2 Behavioural Equations
The behavioural equations of this model appear in the so-called “technology tree”. An Example
displays technology of firms in each of the industries in Figure 13. The intention of such a production
tree is to represent separable, constant returns-to-scale technologies (Hertel, 1997, p. 38). The
individual inputs demanded by firm are located at the bottom of the inverted tree. In this example
these are the primary factors of production: land, labor and capital. They are aggregated in the “Value-
Added Nest”. Additionally, domestic and imported inputs enter as Armington goods in firms purchase
43 VXMD = Value of exports evaluated at (exporter’s) market prices. 44 MTAX = Import tax revenues 45 XTAX = Export tax revenues 45 XTAX = Export tax revenues
61
intermediate inputs. In the branches of the production tree substitution possibilities are restricted by
only one parameter. This CES46 assumption imposes that the elasticity of substitution in a nest is equal
between its components, i.e. between the individual primary factors in the value-added nest as well as
between the intermediate inputs. There is only one exception. In the highest nest the output is
aggregated via a Leontief – function which restricts a non-substitution between composite
intermediates and primary factors (Hertel, 1997, p. 40).
Figure 13: Production Structure in GTAP
Source: According to Hertel (1997, p. 39)
For each “nest” or branch in the technology tree there are two types of equations. The first describes
the substitution among inputs within the nest and follows directly from the CES form of the
production function of that branch. The second type of equation determines the unit cost for the
composite good produced by its appropriate branch. This composite price then enters its superior nest
in order to determine the demand for this composite (Hertel, 1997, p. 41 f.).
As described in the section before, the regional household behaviour is governed by an aggregated
utility function specified by private consumption, government consumption and savings47. Similar to
the equations of firms’ behaviour, the government demand equations consist of an aggregated price
index for all government purchases and the conditional demands for composite tradable goods which
46 CES = Constant Elasticity of Substitution 47 The approach of including savings in the utility function is taken over from the work of Howe (1975, „Development of the Extended Linear Expenditure System from Simple Saving Assumptions“, European Economic Review 6:305-310).
0
Capital Labor Land
σD σVA
Leontief
Domestic
Output
Value - Added
Imported
Intermediate Inputs
CES CES
62
are allocated between imports and domestically produced goods. The distinction between firms’ and
household import demands are the different import shares.
In the way of using the CDE48 functional form, the private household is treated differently. One
difference is the minimum expenditure that attains a pre-specified level of private household utility
and is used to normalize individual prices49. Another characteristic of CDE is that the own-price and
income elasticities are not constant, only in some special cases such as Cobb-Douglas.
The problem of macroeconomic closure is done in an easy way to equal the global demand for savings
and the global demand for investment in the post-solution equilibrium. The neoclassical mechanism of
introducing a global bank assembles savings by using receipts from the sale of a homogeneous savings
commodity to the individual regional households and disburses investments by purchasing shares in a
portfolio of regional investment goods. The size of this portfolio adjusts to accommodate changes in
global savings (Hertel, 1997, p.54).
After explaining the standard GTAP model we will now describe an extended model, which represents
the energy issue in more detail.
4.2.2 GTAP-E
An important commodity in many economic activities is energy because its usage affects the
environment via CO2 emissions and the Greenhouse Effect. In the standard GTAP model the energy-
economic-environment-trade linkages are incomplete. The reason is the absence of energy substitution
which is a key factor in this chain of linkages. To incorporate this energy substitution, the GTAP
model is extended to a version called GTAP-E which was developed by Burniaux and Truong (2002).
In addition, GTAP-E includes carbon emissions from the combustion of fossil fuels as well as a
mechanism to trade them. Another improvement is the computation of a Social Account Matrice
(SAM) which provides a full account of the carbon tax revenues and expenditures and a more specific
treatment of carbon emission trading.
4.2.2.1 The Production Side
On the production side, energy must be taken out of the intermediate input “nest” to be incorporated
into the “value-added” nest (compare Figure 13 in the section before and Figure 14) which is done in
two steps.
48 CDE (= constant difference of elasticities) displays a midway between CES and fully flexible functional forms. 49 For the formula of the CDE implicit expenditure function and more detail see Hertel (1997, p. 49 f.).
63
Figure 14: GTAP-E Production Structure
Source: Burniaux and Truong (2002, p. 31)
At first, energy commodities are split into “electricity” and “non-electricity” groups. Within the non-
electricity group (σNELY) some degree of substitution is allowed as well as between the electricity and
the non-electricity group (σENER). In a second step, the energy composite is combined with capital to
produce an energy-capital composite which is in turn combined with other primary factors in a value-
added-energy nest (VAE)50. This capital-energy composite structure is shown in Figure 15.
50 The term „value-added-energy“ is used to emphasize energy is now present in this nest.
64
Figure 15: GTAP-E Capital-Energy Composite Structure
Source: Burniaux and Truong (2002, p. 31)
4.2.2.2 The Consumption Side
Like in the standard GTAP model, the consumption side is separated in government and private
consumption and savings. The government consumption in GTAP-E is structured as shown in Figure
16 with a separation of the energy commodities from the non-energy commodities. Note if the
substitution elasticity σGENNE would be equal to 1 like the elasticity σGEN, the structure of the GTAP-E
government consumption expenditure is identical to the CES-structure of the original GTAP model.
65
Figure 16: GTAP-E Government Purchases
Source: Burniaux and Truong (2002, p. 37)
The private household consumption is assumed to be structured according to the CDE functional form
of the standard GTAP model as described before. According to the fact, that four of five energy
commodities (coal, oil, gas and electricity) have similar income and substitution parameters, the
energy commodities are aggregated to a single composite. This composite has a CES sub-structure to
allow flexible substitution between the individual energy commodities (see Figure 17). With the
substitution elasticity σPEN = 1, we assume similarity to the value of σGEN of the government purchase.
66
Figure 17: GTAP-E Household Private Purchases
Source: Burniaux and Truong (2002, p. 38)
After explaining the theory of the GTAP-E model, we will describe the changes in the data base in the
next paragraph.
4.2.3 Incorporating the energy data in GTAP
One main reason for the success of GTAP is the global data base which “combines detailed bilateral
trade, transport and protection data characterizing economic linkages among regions, together with
individual country input-output data base which accounts for intersectoral linkages within regions”
(Dimaranan and McDougall, 2002, p. 1-2). The actual data base version 6 consists of 57 sectors and
87 regions. A complete list of these is online on the website51.
To construct an energy related data base the original data has to be modified in some applications. The
energy data is integrated from various sources but mainly from the International Energy Agency
(IEA)52 and consists of price and quantity data. These data must be transformed in the GTAP value
51 See https://www.gtap.agecon.purdue.edu/databases/v6/default.asp or the Appendix B, Annex 4 and 5. 52 For information how gaps of missing data are filled in and the data is re-calibrated to archieve domestic and global consistency between GTAP and IEA statistics see Complainville and van der Mensbrugghe (1998).
67
terms. A problem here is the missing of information. How these gaps are filled is presented by
Malcolm and Truong (1999).
One difference between IEA and GTAP is the treatment of energy sources that are used almost
exclusively to generate electricity, i.e. renewable energy and nuclear power. In GTAP they are part of
the electricity sector, in the IEA energy balance they are single positions. In order to avoid double
counting, they will not be aggregated in the GTAP electricity sector (Dimaranan and McDougall,
2002, p. 17-4 f.).
Because the prices of different energy products are expressed in a variety of units, a physical unit
conversion factor is needed. This factor converts these prices into the unit tons of oil equivalent
(TOE). Note that the factor for a single energy source accounts for all countries53.
Based on the GTAP energy volume data the CO2-emissions of the combustion of fossil fuels are
calculated using a formula developed by Lee (2002, p.3). The emissions depend on the fuel
consumption, a conversion coefficient, a ratio of carbon stored, an emission factor and a fraction of
carbon oxidized. The result is a table of the CO2-emissions and the volume of energy consumption for
every energy commodity in every sector for every region54. One exception is the electricity sector. The
emissions of electricity are set zero to avoid double counting because electricity is produced from
other primary fuels with non-zero CO2-emissions (Wang, 2004, p.98).
The emissions are included in the GTAP equation system via a carbon tax which may be applied
domestically by the regions. The carbon tax revenue is collected by the representative agent in each
region. This carbon tax policy is equivalent to an emission permit system where the permit price
coincides with the carbon tax (Rutherford and Paltsev, 2000). The implication on the nesting structure
is shown in Figure 18 for the production and in Figure 19 for the final demand in a MPSGE program.
53 A table of the conversion factor is printed in Dimaranan and McDougall (2002, p. 17-14). 54 Lee (2002) shows tables with CO2-emissions and energy consumption for Australia, China, Japan, Taiwan, India, USA, Canada, France, Germany and the Netherlands in the year 1997 which corresponds to the GTAP Version 5 Database.
68
Figure 18: GTAP-E Production Structure with Carbon Tax
Source: Rutherford and Paltsev (2000, p. 17)
Figure 19: GTAP-E Final Demand Structure with Carbon Tax
Source: Rutherford and Paltsev (2000, p. 20)
After we explain the static GTAP model, another global equilibrium model is described in the next
paragraph, which is in contrast to GTAP a dynamic one. It is named EPPA.
69
4.3 The Emissions Prediction and Policy Analysis (EPPA) Model
The Emissions Prediction and Policy Analysis (EPPA) model is a recursive dynamic general
equilibrium model of the global economy that simulates the economy through time. EPPA is
developed by the Joint Program of Science and Policy of Global Change, an interdisciplinary research
center of the Massachusetts Institute of Technology (MIT). Principle-applications are calculations of
anthropogenic emissions of greenhouse gases and analysis of abatement policies. In the latter case
EPPA often serves as a stand-alone model. However, it is also an integral part of the MIT Integrated
Global System Model (IGSM), which is a comprehensive ecologic and economic model. Since it
contains economic and physical accounting to study the earth as an interacting system, EPPA is in a
way a hybrid model.
EPPA belongs to the class of CGE models and is based on the GTAP dataset and additional data of
GHG emissions. Depending on disaggregation more sources of economic and infrastructural data are
required, e.g. to disaggregate the transport sector. The following description of the EPPA model refers
basically to Paltsev, S. et al. (2005).
4.3.1 The Structure of EPPA
CGE models like EPPA could be illustrated as a circular flow of goods and services in the economic
system as shown in Figure 20. The consumer sector (households) controls the supply of capital and
labor for the producers (firms), who in turn serve the consumers final demand of goods and services.
Corresponding to this physical flow is a reverse flow of payments. Consumers are paid by the
producers for providing factors, i.e. labor and capital. Households spend their income to consume
goods and services and firms receive payments. Inter-industry transactions are not illustrated in Figure
20, but entirely incorporated in EPPA. The government also takes part in this economy and is modeled
as a passive entity that simply collects taxes and distributes the full value to the households. There is
no international market for factor trade integrated in EPPA, so account imbalances that might exist in
the base year are assumed to disappear gradually.
It is important to appreciate that agents are able to make tradeoffs among the inputs of both production
and consumption. The technical ability of firms and willingness of households to make such tradeoffs
is represented by the elasticities of substitution. These parameters are key determinants to estimate the
cost of mitigation policies.
Another important feature of EPPA is incorporation of the flows of carbon-based fuels and resources,
their calorific values and emissions of greenhouse gases in order to analyze the effect of certain
policies on specific sectors. The impact of carbon policies is modeled by introducing a constraint that
restricts carbon emissions from aggregate fossil fuel to a specified limit. This carbon constraint yields
a shadow value on carbon, similar to the fixed endowment of factors, such as labor and capital,
resulting in wage and interest rates. The benefit of the resulting shadow value is a price, which
emission allowances would take, if a permit trade system was implemented. The abatement costs are
70
indicated by the shadow price of each physical unit of greenhouse gas emitted. Note that the carbon
price behaves exactly like tax and has an economic value. Its revenues are entirely allocated to the
representative household.
Figure 20: The circular flow of goods and resources in EPPA
Source: Paltsev, S. et al., 2005, p. 5
In the case of international trade, some goods, e.g. crude oil and carbon emissions, are treated as
perfect substitutes. However, most goods in the trade flows among regions are subject to the
Armington Assumption (1969), which is widely adopted in global CGE models. It states that
commodities are differentiated by their country of origin and assumes them to be imperfect-
substitutes. This means in particular that domestically produced goods are distinct from imported
goods produced by the same industry. The degree of substitution-possibilities between domestic and
imported goods is measured by the Armington substitution elasticity. Paltsev et. al. (2005) points out
that the Armington elasticity is a key parameter in determining the leakage rate of greenhouse gases in
response to climate policy. For example, a carbon constraint placed on a subset of countries, will raise
the costs of producing energy intensive goods in those countries. Firms will response by increasing the
share of imported energy intensive commodities and therefore reduce the share of domestic energy
intensive commodities. In turn, foreign producers not facing a carbon constraint will expand
production. Thus carbon emissions are partly relocated to countries without a carbon constraint.
A fundamental feature of EPPA is capturing the dynamics of the economy through time, which is
represented by savings-investment decisions and technological change. The benchmark equilibrium of
the base year 1997 is calibrated on a converted GTAP dataset and solved recursively from 2000
71
onwards at 5-year intervals. Savings and investment are based only on current period variables, thus
EPPA belongs to the class of recursive dynamic models. Technological change is modeled using three
assumptions. First, the supply of labor and natural resources increases through time. Second, the
energy efficiency improves, i.e. energy input per unit output decreases. This process is not price-
driven, but given exogenously. Third, EPPA includes a number of backstop technologies. Energy
generation technologies that are currently not in service or play no major role, could take more market
share as prices of conventional technologies rise. An increase of prices may be caused by resource
depletion or imposition of emissions constraints.
4.3.2 Equilibrium Structure
EPPA is formulated and solved in MPSGE55 using the mixed complementary problem (MCP)
approach. This formulation consists on three inequalities to be satisfied: the zero profit, market
clearing and income balance condition. It agrees in principle with the 2x2 production model, described
in section 4.1.2.
4.3.3 Nesting Structure
All production sectors and the sector of final consumption are modeled using nested Constant
Elasticity of Substitution (CES) functions (σ=const.). Cobb-Douglas (σ=∞) and Leontief (σ=0)
production functions are special cases of the CES. The benefit of nested CES production functions is
flexibility in setting fuel and electricity related elasticity parameters, to which emission and abatement
costs are especially sensitive. An overview of the sectors and primary factors in EPPA is presented in
Table 10.
In its latest version (EPPA4) the model’s disaggregation reaches a level beyond that of the GTAP
dataset and previous versions of EPPA. Transport Sector for instance, aggregated with other industries
recently is split-up in detail, which allows a more careful study of potential growth over time and
implications for the economy’s energy intensity.
55 A mathematical programming system for general equilibrium (MPSGE) analysis operating as a subsystem within GAMS;
For documentation see www.mpsge.org.
72
Table 10: Sectors and Resource Factors in the EPPA model
Source: Paltsev, S. et al., 2005, p. 14
4.3.3.1 Production Sectors
Figure 21 shows the nest structure of the Services, Transportation, Energy Intensive and Other
industries. Vertical lines in the intermediate input nest (top nest of Figure 21) indicate a Leontief
production function and hence the elasticity of substitution parameter is zero (σ=0). Note that the
Energy Aggregate of the Capital-Labor-Energy (KLE) bundle is split up into an Electricity and Non-
Electricity nest. Non-Electricity represents a single nest of fuels including coal, oil, gas, and refined oil
(ROIL). Since crude oil is used only in the ROIL sector as well as coal use is significant mostly in the
EINT sector, σEN refers especially to the substitution of refined oil and gas.
Imported goods are aggregated as goods from different regions (σMM) and further combined with
domestic goods (σDM) to enter in the intermediate input nest as a composite of Armington
commodities.
The most disaggregated and detailed sector included in EPPA is the electricity sector (Figure 22).
Conventional fossil fuel, Nuclear, Hydro and Advanced Generation Technologies enter as perfect
substitutes (σ=∞), whereas Wind & Solar are taken out of this nest due to disadvantages as
intermittency and remote locations. Thus both renewable technologies and the bundle of perfect
substitutes are part of the top nest exhibiting an elasticity of σEWS.
73
Figure 21: Structure of Services, Transportation, Energy Intensive and Other Industries
Source: Paltsev, S. et al., 2005, p. 18
Figure 22: Structure of the Electricity Sector
Source: Paltsev, S. et al. (2005, p. 19)
4.3.3.2 Consumption Sector
The nested CES structure is also an appropriate instrument to express preferences of the representative
household. Figure 23 shows the corresponding illustration of the household sector.
It is noteworthy that the CES function used to describe consumption is a Cobb-Douglas consumption
function and hence homogenous of degree one. This indicates constant returns to scale (CRTS), which
74
conveniently simplifies the model’s solution. To avoid inconsistencies with long term trends, CRTS is
only assumed within a period. Between periods elasticities are functions of income to capture the
change of consumption with proceeds over time.
Figure 23: Structure of the Household Sector
Source: Paltsev, S. et al. (2005, p. 23)
4.3.3.3 Disaggregating the Transport Sector
Since it is one of the most rapidly growing energy consumers, the detailed disaggregation of the
transport sector in EPPA is essential for quantitative analysis of environmental policy. Moreover
existing fuel taxes are often rated much higher than in other sectors of the economy. Disaggregation of
transport comprises two activities: industry transportation and household transportation. Industry
transportation provides other sectors, including households, with transportation services and is
presented in Figure 21.
Household transportation is completely excluded from the aggregated energy and energy consumption
nest. Transport enters in Total Consumption with Other Consumption as shown in Figure 23.
Since disaggregating the transport sector in EPPA is very similar to the approach we use in our model,
this issue is described more elaborated in the next section.
75
4.4 The Data Base
To make the results concise we do not use the complete GTAP regions and sectors. The data mapping
is declared in this chapter. After a short overview of the region and sector aggregation in our model,
the modelling of the transport sector is illustrated.
4.4.1 Applied Data Base
Our model data is based on the GTAP Version 6 Data Base. The changes in the mapping are explained
in this paragraph.
As we want to integrate the European transportation sector in the ETS, we split the world into two
regions. One is called Europe (abbreviated EUR), consisting of the 15 Countries of the EU before the
May 1st 200456, and the other GTAP regions are aggregated to the Rest of the World (ROW).
The sectors are also reduced to six commodities with a concentration of the energy related sectors. As
described in the chapter 4.4.2.3 the gasoline is separated out of the original GTAP petroleum and coal
(P_C) account. The rest of this sector is combined with the energy sector which consists of the original
sectors “Gas manufacture, distribution”, “Coal”, “Oil” and “Gas” to a new sector called “fossil fuels”
(FOS). The sectors “Metals nec”, “Minerals nec”, “Paper products, publishing”, “Chemical, rubber,
plastic prods” and “Ferrous metals” represent energy-intensive industries and are aggregated to the
energy-intensive sector (EINT). The electricity sector (ELY) is not changed in any way. The transport
sector (TRN) is mapped as an aggregation from the original GTAP transport sectors “Sea transport”
(WTP), “Air transport” (ATP) and “Transport nec” (OTP). The last sector is called “Macro good”
(MAC) and is an aggregation of the residual 43 original GTAP sectors.
The factors of production are labor (LAB), assembled of land, skilled and unskilled labor, and capital
(CAP) which is an aggregation of capital and natural resources.
4.4.2 Modelling of the Transport Sector
In the last sections we gave a brief survey of the models GTAP and EPPA, now we describe the
transportation sector and its rearrangements in our model.
4.4.2.1 The Transport Sector in GTAP 6
Among the 57 sectors treated in GTAP 6 are three transportation sectors: air transport (ATP), water
transport (WTP), and other transport (OTP). In these sectors, transport of persons and transport of
freight is combined. The OTP sector includes land transport, transport via pipelines, supporting and
auxiliary transport activities, and activities of travel agencies. Own supplied transport of households is
56 Namely: Austria, Belgium, Denmark, Finland, France, Germany, United Kingdom, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain and Sweden.
76
not depicted. Furthermore, expenditures on motor fuels are not indicated separately. To implement the
transport sector in the existing ETS system, it is useful to adjust EPPA and the appropriate GTAP 6
database.
4.4.2.2 Transportation in the Household Sector
Within the 3 transportation sectors mentioned above, GTAP 6 completely covers commercial
transportation purchased by the household. Transportation services produced by the household itself,
especially expenditures on private automobiles are not represented sufficiently. The resulting
aggregation of household’s fuel consumption makes it impossible to implement household’s own
supplied transportation in an upstream emission trade system.
Disaggregating Household Transport
To study household transportation explicitly it is necessary to disaggregate the GTAP 6 Data into
purchased and own supplied transport. For this purpose, we follow Paltsev et al. (2004a).57 In
consumers’ final consumption, own supplied transport related purchases are already included as a
mixture of inputs from different sectors. Our aim is to find the affected GTAP sectors and to figure out
the shares of consumption in these sectors that goes to own supplied transportation.
According to Paltsev et al. (2004a) we indicate two sectors, our macro Sector (MAC) which includes
purchases of vehicles, maintenance, insurance, tires, oil change, etc. and the GTAP sector petroleum,
coal products (P_C) which includes fuel. Finally, for our model, only the appropriate fuel demand
from the P_C sector is of importance. So we just consider fuel demand as households own supplied
transport. Household budget surveys provided by EUROSTAT, 1999 state household expenditures on
refined oil products for own supplied transportation as a share of total household expenditure on all
refined oil products. For the EU 15 the share accounts 85.8%. This amount represents the household
consumption from the new gasoline sector. To balance the database, the remaining P_C account,
within the household consumption block, is added to the fossil fuels sector. The transport consumption
of the households is now divided into purchased transport and gasoline consumption for own supplied
transport. Figure 26 illustrates the associated nesting structure.
4.4.2.3 Disaggregating the Petroleum and Coal Products Sector
In GTAP 6 transport related fuel is included in the aggregated P_C sector. Moreover this sector
includes other refined petroleum products, coke oven products and processing of nuclear fuel. For the
implementation of the transportation sector in an upstream emission trading system it is indispensable
to find out fuel demand of all corresponding transport consumption.
57 see chapter 4.3.3.3
77
Therefore the existing P_C sector has to be divided into transport related fuels (GASOLINE) and a
residual, which is put into the fossil fuels sector. For the calculation of the production shares we used
the EUROSTAT database PRODCOM which provides detailed product output information at the EU
level. The P_C sector in PRODCOM is divided into 36 products of which 9 products represent fuels
for the transportation sector. Because there is no data for processing of nuclear fuel, it is ignored.
Regrettably, information for several products is incomplete, so we have to apply the following
procedure. If available, we use production data from 2001, for the missing information we use
production data from other years (1999, 2000 or 2002). If no production data is available, we calculate
an approximation by dividing the products export (PRODCOM, 2001) by the P_C sector’s export
quota from GTAP (19.22%). As there is neither Production nor export data, the remaining sectors are
ignored. Annex 4 illustrates the aggregation, amount and source of data. In this way we calculate a
production share of 71.94% that goes to the new gasoline sector. The residual is added to the fossil
fuels sector.
Household’s expenditures on GASOLINE are calculated via the share identified in chapter 4.3.2.1. As
there is no reliable date, representing transport fuel consumption of industry sectors, the gasoline
consumption share of the sectors transport, macro, electricity, gasoline and fossil fuels are assumed to
be 100%, for the sector EINT, which most likely uses most of the included coke oven products, it is
simplifying set 72%, according to the production share.
4.4.2.4 Disaggregating the Other Transport Sector
In our model, all transportation sectors are aggregated. Thus we consider all types of transportation
and their demand for fuel. For further investigation it might be useful to analyse every transportation
sector in detail. Therefore a disaggregation of the OTP sector which includes land transport (Road and
Rail) would be essential. For example the included road transportation possesses high gasoline
consumption. Consequently it is worth to study this sector separately.
A possible approach to disaggregate OTP would be the use of shares from national Input-Output
tables, however most of the EU countries do not provide those tables sufficiently detailed. Another
approach, the usage of transport statistics also brings up problems. Statistics, representing the modal
split are broken down into transportation of freight and transportation of persons. The used units, ton
kilometres and person kilometres, are, on the one hand hard to combine and the resulting shares on the
other hand not comparable to the price data we use.
4.5 Model description
Based on the theory of General Equilibrium a model is specified by transforming the structure of
GTAP and GTAP-E and using their fundamental databases.
78
We assume a model that contains two regions, namely EU 15 and Rest of the World. Thereby trading
of goods from region s to region r is possible. Furthermore a private and a public household are acting
as two agents on the consumption side within the model. The production side is represented by six
industry sectors under the assumption of one-commodity-producing sectors is underlying. Those
producers are Electricity, Fossil Fuels, Macro Good, Energy Intensive and finally Transport and
Gasoline.
4.5.1 Nesting structures
For illustration and implication of the model nested structures are used. They are divided in a
production structure for the firms and a consumption structure for households. Another part is the
Armington aggregation to explain the import – export relation between region s and r. It is a
descriptive way to expose the dependency of one sector to another and the cost shares at each level
respectively.
In the case of the production block the top – level of the structure represents the total costs of the
sector j to produce the good i. The continuative levels always represent cost shares of the level and
derive from the level beneath and are passed on to the level above. The elasticities of substitution are
given for each level and show in which ratio one good, intermediate good or factor can be substituted
by the other one at the same level.
4.5.1.1 Production
Essentially two dissimilar production structures are specified. The justification can be detected by the
fact that the transport sector uses the commodity gasoline fundamentally different from other sectors
considered here. Therefore the producing sectors are treated separately in respect of their structure of
production.
4.5.1.2 Nesting Production Structure of Sectors excluding Transport
To represent the incorporation of the transport sector in the ETS each litre of gasoline sold yields
emission. As Figure 24 illustrates the production proceeding is characterised by several levels. On the
top level a Leontief function connects the nests of value added energy and transport intermediate
which indicates their property of non substitutability.
79
Figure 24: Nesting production structure of sectors excluding transport
4.5.1.2.1 Value Added Energy
The value added energy nest is a composite of labor on the one hand and capital and energy one the
other one. While those elements are substitutable with each other at any time horizon, energy and
capital are hardly in terms of short-run consideration. Thus, for example a producer is able to dispense
with labor and therefore enforce the input quantity of capital or energy but only dispense with capital
and therefore increase energy in the long-run. Capital and labor in their capacity of input factors are
not tradable in our model.
4.5.1.2.2 Energy
The nest energy is aggregated by two of the six commodities, electricity and fossil fuels. The usage of
fossil fuels is escorted by the production of CO2 and thus not substitutable that is indicated by the
elasticity equalising zero. Both can be produced domestically or be imported by a producer.
4.5.1.2.3 Transport Intermediate
In this chapter transport acts as an intermediate good. The sector itself is considered in chapter 4.5.1.3.
Due to the fact we are assuming non-substitutability between this composite’s parts,
Transport/Gasoline and Intermediate, the used elasticity equals zero. This assumption allows for the
absence of an alternative to the transport of the intermediate goods to the demanding firm. It is not
possible to take more of the good itself while reducing transportation services. Note, that another
result of the top-level’s Leontief function is that the nests of Transport/Gasoline and Intermediate as
well as the levels below, can not be substitutes of the nest value added energy including the factors
labor, capital and energy.
σ = 1
σ = 0.5 Value Added Energy
σ =0.1 Labor Capital/Energy
Energy
Fossil Fuels Electricity
Capital
CO2 Fossil Fuels
σ = 0
σ = 0
Transport/Gasoline
Cost function
Transport Intermediate
Intermediate
σ = 0
σ = 0.5 σ = 1
Transport Gasoline Macro Energy Intensive
CO2 Gasoline
σ = 0
80
4.5.1.2.4 Transport/Gasoline
For all sectors that are not producing transport as a commodity it is necessary to choose between
applying the transportation sector and executing the activity of transportation on its own. It is obvious
that the second case yields requirement of gasoline.
4.5.1.2.5 Intermediate
Intermediate is an aggregation of the commodities macro good and energy intensive good. Both are
international tradable and substitutable to each other.
4.5.1.3 Nesting Production Structure of Transport Sector
To illustrate the transport sector some changes are necessary. The most important input to produce
transport as a good is gasoline. As this input is not substitutable, it is transferred to the top level with
Leontief–substitution. The model does not allow the trading of gasoline because the ROW is not
meant to act as participant of the emission trading system. The other parts of the nesting structure stay
the same.
Figure 25: Nesting production structure of the transportation sector
4.5.2 Consumption
Both, private and public households spend their whole income for the consumption of commodities.
There are no savings within the model. The private household generates its income from the primary
factors capital, labor and CO2-Certificates as well as taxes on carbon emissions. Consuming
commodities the agents can chose between domestic and imported ones. The only difference between
σ = 0
σ = 0
CO2 Fossil Fuels
σ = 1
Electricity Fossil Fuels
σ = 1
Macro Energy Intensive
σ =0.1
Energy Capital
σ = 0.5
Labor Capital/Energy
σ = 0
Intermediate
Value Added Energy
Cost function
Transport Intermediate
Transport
σ = 0
Gasoline
Gasoline CO2
81
the private and the public household is transport. We assume that the private household in difference
to the public household cannot substitute between transport and other goods.
Figure 26: Consumption of private households
Figure 27: Consumption of public household
4.5.3 Armington Aggregation
In Figure 28 the nesting structure of the Armington aggregation is displayed. All goods except
gasoline can be domestic or imported. The imported good, whose origin can vary from region 1 to r, is
a composition of the commodity itself and the transport service. That means the value of the imported
good is always dependent on two factors which are not substitutable.
Figure 28: Armington Aggregation for only one import region (our model)
σ = 0.5
σ = 0
Expenditures
Transport
Transport Gasoline
σ = 1 Others
Electricity Macro Good Energy Intensive Fossil Fuels
σ = 0
σ = 4Armington Supply pa(i,r)
Aggregated Imported Commodity Domestic Commodity py(i,r)
Imported Commodity py(i,s) Transportation Service pt
σ = 0
Expenditures
Macro Good Energy Intensive Electricity Fossil Fuels Transport
82
4.6 Implementation
4.6.1 GAMS
The model and the nesting structure are implemented in the General Algebraic Modeling System
(GAMS). GAMS is a modeling system for mathematical linear, non-linear and mixed integer
optimization problems. It is very popular for solving CGE models (Löfgren, 2003, p.1). The
description of models with different constraints is implemented in algebraic statements and is
independent of the solution algorithms. Changes in the assumptions and the model specification can be
done easily (Rosenthal, R. E., 2006, p. 13). For a specific model the source code in GAMS can be read
as a documentation of the model itself, which is advantageously for the user. The GAMS program
package consists of different language compilers and solvers. There is one special tool for an easier
implementation of equilibrium models, called Mathematical Programming System for General
Equilibrium (MPSGE). The GTAP6inGAMS-Package58 by Rutherford is the basis tool for our model.
4.6.2 MPSGE
MPSGE works as a special subsystem in GAMS. It based on nested structured production and utility
functions with constant elasticities of substitutions (Rutherford, T. F., 1997, p. 1). We choose MPSGE
for implementing the nesting structure of our model because it simplifies the entering of the source
code into the computer. For the whole implementation you only need share-, elasticity-, tax- and
initial-endowment-parameters regarding to all levels of the nesting structure. It is not necessary to
write the complete algebraic code of the behavioral functions and constraints of each sector. As a
positive consequence the compact abstract source code in the MPSGE-syntax keeps a higher level of
clearness and less setup effort for the user compared to the realization in GAMS-syntax (Rutherford,
T. F., 1997, p. 2).
58 For more details see: http://www.mpsge.org/gtap6
83
5 Scenarios and Results
5.1 Baseline Model
As shown in parting section 4.4 the baseline model which is applied as the benchmark case for further
analysis consists of two regions, Europe 15 and ROW Carbon emissions are associated with the usage
of fossil fuels and gasoline as an interstage product in the production of the sectors macro good,
transportation, electricity, and energy intensive goods59. In both regions no carbon emission restriction
are stated. Therefore in the baseline model the price for carbon emissions is equal to zero. Potential
taxation is not considered here since it is not meant to be part of this study. The baseline mode neither
implements a trading nor a taxation system.
5.2 Scenario 1 – Trading System for Carbon Emission Rights excluding Transportation
Sector
To see the effects of the scenarios the change in welfare is the object to be measured. To appraise
welfare change the income of the private household is looked at. It is obvious that including a price or
tax for carbon leads to welfare losses because the price for all products will raise and thus the income
for the private household decreases. We will then compare the welfare effects of the scenarios.
In the first scenario only a carbon emission restriction in Europe 15 is established while simplifying
that there is none in ROW. Those constraints on carbon emissions lead to the implementation of
climate policy instruments to secure their abidance. We model two different of these instruments, a
carbon emission trading system as well as carbon emission taxes. Within this scenario the sectors of
electricity, energy intensive good and gasoline production are included in the carbon emission trading
system (ETS sectors). The remaining sectors namely fossil fuel production, macro good and
transportation (NETS sectors) do not participate in the ETS but are liable to carbon emission taxes The
carbon emission rights are owned by the private household as initial endowment which is demanded
by the ETS sectors. Furthermore the private household acts as the tax agent of the carbon emission tax
paid by the NETS sectors.
We compute sub-scenarios with different emission restrictions. At first the baseline emissions in
Europe 25 are cut by 5%. Subsequently the cut level increases in incremental steps by 2.5% until
finally the level of 22.5% is reached. The overall cut of the baseline carbon emissions leads to a new
overall carbon emissions budget in every scenario. These new budget must be allocated between the
ETS sectors, the NETS sectors and the household sector as a consumer. In every sub-scenario it is
assumed that the private households hold their baseline emissions. NETS sectors face a moderate
uniform carbon emissions cut of 2% from their NETS specific baseline carbon emissions. This is
59 For details about the nesting structure of the production sectors see the model description part.
84
implemented as mentioned above by carbon emission taxes in every sub-scenario. So the new carbon
emissions budget for the NETS sectors is 98% of their baseline emissions. Finally the new carbon
emission budget for the ETS sectors is derived as the residual of the overall budget after subtracting
the household’s volume and the new carbon emission budget of the NETS sectors. In Figure 29 the
results of scenario 1 excluding transport from the ETS are shown. The increasing constraint on
emissions result in welfare losses up to 10% compared to the baseline model.
Figure 29: Carbon emission cut and resulting welfare change in scenario 1
-12
-10
-8
-6
-4
-2
05 7,5 10 12,5 15 17,5 20 22,5
Carbon emission cut in %
Cha
nges
in W
elfa
re
5.3 Scenario 2 – Trading System for Carbon Emission Rights including Transportation Sector
In the second scenario we relocate the transportation sector from the NETS sectors to the ETS sectors
which are the paper’s major object of investigation. All remaining assumptions are valid like in
scenario 1 as well as the cut levels of the baseline emissions in the sub-scenarios. The calculation of
the new carbon emission budgets for the ETS sectors is done similarly as mentioned above. Figure 30
indicates the change in welfare which now leads to losses up to 7.5% which is an apparent difference
to scenario 1.
85
Figure 30: Carbon emission cut and resulting welfare change in scenario 2
-12
-10
-8
-6
-4
-2
05 7,5 10 12,5 15 17,5 20 22,5
Carbon emission cut in %
Cha
nges
in W
elfa
re
5.4 Results
Comparing the results of both scenarios Figure 31 shows lower losses in welfare in scenario 2
independently of the level of the carbon emissions cut.
Figure 31: Comparison of scenarios
-12 -10 -8 -6 -4 -2 0
5
7,5
10
12,5
15
17,5
20
22,5
Car
bon
emis
sion
cut
in %
Changes in WelfareScenario 2 Scenario 1
The analysis of different overall emission caps can be clarified by Figure 32. It evidences a positive
effect between savings in welfare losses by including the transportation sector in the ETS and the level
of the overall emissions cap.
86
Figure 32: Savings in welfare losses depending on different rates of overall emission caps
0
0,5
1
1,5
2
2,5
3
5 7,5 10 12,5 15 17,5 20 22,5
Carbon emission cut in %
Savi
ngs
in W
elfa
re L
osse
s
With the extension of the ETS it is possible to induce marginal abatement cost of carbon emissions in
a more specific level and for a wider basis of emitters. That means to widen the status quo ETS in the
EU by including the transportation sector would have positive effects on the welfare. This option
provides the opportunity to achieve emission reductions more cost efficient than not regarding the
transportation sector as an emitter with huge potential.
87
6 Conclusions and Outlook
Based on the issue of high leveled carbon emissions the report considers two approaches of abatement,
several technologies of CCS and ETS. According to existing projects a model is constructed that does
not include CCS but allows for different scenarios of the EU ETS. Within these scenarios we
furthermore introduce a tax for the NETS sectors. The two cases differ by scope of the ETS
concerning transport as a part of it. By computing the equilibrium results of the baseline mode and
both scenarios we can conclude that restriction of carbon emissions via an ETS and emission taxes
leads to losses in welfare. These climate policy instruments create a value for emitting carbon
emissions resulting in additional costs for the economy. Although the economy can lessen the losses of
welfare by shifting the transportation sector from NETS to ETS. We can conclude that by extending
the scope of participants in the trading system the aim of reduction could be reached more efficiently.
Thus, costs are allocated to more sectors and the abatement amount decreases for involved individuals.
There are two major aspects for further research. At first it is reasonable to implement CCS
technologies into the proposed model. Those technologies create the opportunity not only to trade
emission certificates but also to invest into physical abatement through capture and storage.
Furthermore elasticities of substitution are an important issue, because the equilibrium results are
highly affected by them. In our approach they are based on assumptions. Their calibration is
methodological more preferable. Because of the complexness of these two topics it needs more
detailed experience in CGE modeling for realization.
88
Appendix A: Transport Annex 1: Carbon Dioxide Emissions by Sector - 2001
89
Annex 2: Carbon Dioxide Emissions by Main Sector - 2001
90
Annex 3:
100-year global warming potential (GWP) estimates of the different greenhouse gases based on
the IPCC’s Third Assessment Reports (2001):
Carbon Dioxide CO2 1
Methane CH4 23
Nitrous Oxide NO2 296
HFC – 23 CHF3 12,000
HFC – 125 CHF2CF3 3,400
HFC – 134a CH2FCF3 1,300
HFC – 143a CF3CH3 4,300
HFC – 152a CH3CHF2 120
HFC – 227ea CF3CHFCF3 3,500
HFC – 236fa CF3CH2CF3 9,400
Perfluoromethane CF4 5,700
Perfluoroethane C2F6 11,900
Sulfur Hexafluoride SF6 22,200
91
Annex 4: Aggregation of the P_C sector
used values (€) source
TRANSPORT RELATED FUELS
Aviation gasoline 68'944'797 calculated
Motor gasoline, unleaded 10'635'679'804 2001
Motor gasoline, leaded 111'167'150 2002
White spirit, industrial 305'289'225 2002
Kerosene-type jet fuel 2'283'037'021 2001
Gasoline type jet fuel 15'416'025 calculated
Derv fuel (diesel for engines/transport) 13'113'928'059 2001
Gas/diesel oil 44'786'000 2001
Derv fuel (diesel for engines/gas-oil) 18'953'100'321 2001
OTHER FUELS
Coke-oven coke (obtained from plants) 588'880'047 2001
Brown-coal coke 22'940'996 1999
Coke, non-energy use 392'448'873 1999
Tar (mixture of aromatic and peat) 81'559'715 2000
Refinery feedstocks (process/ refinery) 2'010'699'011 calculated
Refinery feedstock 601'320'343 calculated
Light naphtha 793'098'315 2001
Refinery feedstock 101'559'834 2001
Heating gas-oil 4'887'297'514 2001
Refinery feedstock 4'610'198 calculated
Medium naphtha 221'437'241 2001
Refinery feedstock (fuel oil feedstock) 110'619'740 2001
Fuel oil LSC (sulphur content <1%) 2'100'116'682 2001
Fuel oil HSC (sulphur content >1%) 1'950'843'153 2001
Fuel-oil, non-energy (fuel industry) 11'419'771 calculated
Refinery feedstock (lubricat//ineries) 7'841'311 calculated
Lubricating oils (liquid dis//greases) 2'023'933'611 1999
LPG (mixture of light hydroc//fuel)
Refinery feedstock (LPG)
LPG non-energy (Propane/Butan/industry)
Refinery gas no data
available
Petroleum jelly, paraffine 325'146'521 2000
Petroleum coke (black solid carbon) 447'695'942 calculated
Petroleum bitumen 931'855'983 calculated
Other petroleum products (res//n.e.c.) 142'452'541 1999
Pitch and pitch coke
Petroleum resins (coumarone/ forms)
no data available
92
Appendix B: GTAP Nomenclature Annex 5: Regions in the GTAP Data Base Version 5 (identical to Version 6)
Source: Diamaran and McDougall (2002, Glossary)
93
Annex 6: Regions in the GTAP 6 Data Base and Mapping to Standard Countries
Number Code Name Member Regions (226) Code
1 AUS Australia Australia AUS
2 NZL New Zealand New Zealand NZL
3 XOC Rest of Oceania American Samoa ASM
Cook Islands COK
Fiji FJI
French Polynesia PYF
Guam GUM
Kiribati KIR
Marshall Islands MHL
Micronesia, Federated States of FSM
Nauru NRU
New Caledonia NCL
Norfolk Island NFK
Northern Mariana Islands MNP
Niue NIU
Palau PLW
Papua New Guinea PNG
Samoa WSM
Solomon Islands SLB
Tokelau TKL
Tonga TON
Tuvalu TUV
Vanuatu VUT
Wallis and Futuna WLF
4 CHN China China CHN
5 HKG Hong Kong Hong Kong HKG
6 JPN Japan Japan JPN
7 KOR Korea Korea, Republic of KOR
8 TWN Taiwan Taiwan TWN
9 XEA Rest of East Asia Macau MAC
Mongolia MNG
Korea, Democratic People’s
Republic of
PRK
10 IDN Indonesia Indonesia IDN
94
11 MYS Malaysia Malaysia MYS
12 PHL Philippines Philippines PHL
13 SGP Singapore Singapore SGP
14 THA Thailand Thailand THA
15 VNM Viet Nam Viet Nam VNM
16 XSE Rest of Southeast Asia Brunei Darussalam BRN
Cambodia KHM
Lao People’s Democratic Republic LAO
Myanmar MMR
Timor Leste TLS
17 BGD Bangladesh Bangladesh BGD
18 IND India India IND
19 LKA Sri Lanka Sri Lanka LKA
20 XSA Rest of South Asia Afghanistan AFG
Bhutan BTN
Maldives MDV
Nepal NPL
Pakistan PAK
21 CAN Canada Canada CAN
22 USA United States of America United States of America USA
23 MEX Mexico Mexico MEX
24 XNA Rest of North America Bermuda BMU
Greenland GRL
Saint Pierre and Miquelon SPM
25 COL Colombia Colombia COL
26 PER Peru Peru PER
27 VEN Venezuela Venezuela VEN
28 XAP Rest of Andean Pact Bolivia BOL
Ecuador ECU
29 ARG Argentina Argentina ARG
30 BRA Brazil Brazil BRA
31 CHL Chile Chile CHL
32 URY Uruguay Uruguay URY
33 XSM Rest of South America Falkland Islands (Malvinas) FLK
French Guiana GUF
Guyana GUY
95
Paraguay PRY
Suriname SUR
34 XCA Central America Belize BLZ
Costa Rica CRI
El Salvador SLV
Guatemala GTM
Honduras HND
Nicaragua NIC
Panama PAN
35 XFA Rest of Free Trade Area of the
Americas
Antigua & Barbuda ATG
Bahamas BHS
Barbados BRB
Dominica DMA
Dominican Republic DOM
Grenada GRD
Haiti HTI
Jamaica JAM
Puerto Rico PRI
Saint Kitts and Nevis KNA
Saint Lucia LCA
Saint Vincent and the Grenadines VCT
Trinidad and Tobago TTO
Virgin Islands, U.S. VIR
36 XCB Rest of the Caribbean Anguilla AIA
Aruba ABW
Cayman Islands CYM
Cuba CUB
Guadeloupe GLP
Martinique MTQ
Montserrat MSR
Netherlands Antilles ANT
Turks and Caicos TCA
Virgin Islands, British VGB
37 AUT Austria Austria AUT
38 BEL Belgium Belgium BEL
96
39 DNK Denmark Denmark DNK
40 FIN Finland Finland FIN
41 FRA France France FRA
42 DEU Germany Germany DEU
43 GBR United Kingdom United Kingdom GBR
44 GRC Greece Greece GRC
45 IRL Ireland Ireland IRL
46 ITA Italy Italy ITA
47 LUX Luxembourg Luxembourg LUX
48 NLD Netherlands Netherlands NLD
49 PRT Portugal Portugal PRT
50 ESP Spain Spain ESP
51 SWE Sweden Sweden SWE
52 CHE Switzerland Switzerland CHE
53 XEF Rest of EFTA Iceland ISL
Liechtenstein LIE
Norway NOR
54 XER Rest of Europe Andorra AND
Bosnia and Herzegovina BIH
Faroe Islands FRO
Gibraltar GIB
Macedonia, the former Yugoslav
Republic of
MKD
Monaco MCO
San Marino SMR
Serbia and Montenegro SCG
55 ALB Albania Albania ALB
56 BGR Bulgaria Bulgaria BGR
57 HRV Croatia Croatia HRV
58 CYP Cyprus Cyprus CYP
59 CZE Czech Republic Czech Republic CZE
60 HUN Hungary Hungary HUN
61 MLT Malta Malta MLT
62 POL Poland Poland POL
63 ROM Romania Romania ROM
64 SVK Slovakia Slovakia SVK
97
65 SVN Slovenia Slovenia SVN
66 EST Estonia Estonia EST
67 LVA Latvia Latvia LVA
68 LTU Lithuania Lithuania LTU
69 RUS Russian Federation Russian Federation RUS
70 XSU Rest of Former Soviet Union Armenia ARM
Azerbaijan AZE
Belarus BLR
Georgia GEO
Kazakhstan KAZ
Kyrgyzstan KGZ
Moldova, Republic of MDA
Tajikistan TJK
Turkmenistan TKM
Ukraine UKR
Uzbekistan UZB
71 TUR Turkey Turkey TUR
72 XME Rest of Middle East Bahrain BHR
Iran, Islamic Republic of IRN
Iraq IRQ
Israel ISR
Jordan JOR
Kuwait KWT
Lebanon LBN
Palestinian Territory, Occupied PSE
Oman OMN
Qatar QAT
Saudi Arabia SAU
Syrian Arab Republic SYR
United Arab Emirates ARE
Yemen YEM
73 MAR Morocco Morocco MAR
74 TUN Tunisia Tunisia TUN
75 XNF Rest of North Africa Algeria DZA
Egypt EGY
Libyan Arab Jamahiriya LBY
98
76 BWA Botswana Botswana BWA
77 ZAF South Africa South Africa ZAF
78 XSC Rest of South African Customs
Union
Lesotho LSO
Namibia NAM
Swaziland SWZ
79 MWI Malawi Malawi MWI
80 MOZ Mozambique Mozambique MOZ
81 TZA Tanzania Tanzania, United Republic of TZA
82 ZMB Zambia Zambia ZMB
83 ZWE Zimbabwe Zimbabwe ZWE
84 XSD Rest of Southern African
Development Community
Angola AGO
Congo, the Democratic Republic of
the
COD
Mauritius MUS
Seychelles SYC
85 MDG Madagascar Madagascar MDG
86 UGA Uganda Uganda UGA
87 XSS Rest of Sub-Saharan Africa Benin BEN
Burkina Faso BFA
Burundi BDI
Cameroon CMR
Cape Verde CPV
Central African Republic CAF
Chad TCD
Comoros COM
Congo COG
Cote d'Ivoire CIV
Djibouti DJI
Equatorial Guinea GNQ
Eritrea ERI
Ethiopia ETH
Gabon GAB
Gambia GMB
Ghana GHA
99
Guinea GIN
Guinea-Bissau GNB
Kenya KEN
Liberia LBR
Mali MLI
Mauritania MRT
Mayotte MYT
Niger NER
Nigeria NGA
Reunion REU
Rwanda RWA
Saint Helena SHN
Sao Tome and Principe STP
Senegal SEN
Sierra Leone SLE
Somalia SOM
Sudan SDN
Togo TGO
Source: https://www.gtap.agecon.purdue.edu/databases/v6/v6_regions.asp
Annex 7: List of GTAP Abbreviations
EINT energy intensive industries
GOVEXP government expenditures
KLE Capital-Labor-Energy bundle
MTAX Import tax revenues
NETINV investment goods
OWNTRN own supplied transport
PRIVEXP private household expenditure
ROIL refined oil
ROW Rest of the World
SAVE savings
TAXES net tax revenues
VAE value added energy
VDFA Value of Domestic purchases by Firms at Agents´ prices
VDGA Value of Domestic purchases by Government household at Agents´ prices
VDPA Value of Domestic purchases by Private households at Agents´ prices
VIFA Value of imported firms purchases evaluated at agent’s prices.
VIGA Value of expenditure on imported tradable commodities by government household
evaluated at agent’s prices
VIPA Value of expenditure on imported tradable commodities by private household
evaluated at agent’s prices.
VOA Value of Output at Agents´ prices
VXMD Value of exports evaluated at (exporter’s) market prices.
VXMD Value of exports evaluated at (exporter’s) market prices.
XTAX Export tax revenues
101
Annex 8: List of elasticities of substitution
σ elasticity of substitution
σD elasticity of substitution between imported and domestic goods
σVA elasticity of substitution in the value-added nest
σVAE elasticity of substitution in the value-added-energy nest
σM elasticity of substitution between the foreign regions
σLAB elasticity of substitution in the labor nest
σKE elasticity of substitution in the capital-energy composite nest
σENER elasticity of substitution in the energy composite nest
σNELY elasticity of substitution in the non-electric nest
σNCOL elasticity of substitution in the non-coal nest
σGEN elasticity of substitution in the energy composite nest for government purchase
σGENNE elasticity of substitution between energy composite nest and non-energy composite
nest in government demand
σGNE elasticity of substitution in the non-energy composite nest for government purchase
σPEN elasticity of substitution in the energy composite nest for private households´
purchase
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