environmental cge modeling using two approaches - ccs and … · economics of global warming...

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




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




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: 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




Comparison

Incremental coe, ¢/kWh 3.12 5.66 2.27 2.88

Energy Penalty, % 23.0 34.1 15.9 27.7


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: 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




Capture Plant



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




Comparison

Incremental coe, ¢/kWh 2.10 1.86 1.42 0.98

Energy Penalty, % 11.6 14.7 16.1 9.8


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)

44

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


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


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


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


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


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


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


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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