Study on actual GHG data for diesel, petrol, kerosene and natural gas, Interim Report

Study on actual GHG data for diesel, petrol, kerosene and natural gas, Interim Report
DG ENER
FRAMEWORK SERVICE CONTRACT
SRD MOVE/ENER/SRD.1/2012-409-LOT 3-COWI
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EUROPEAN COMMISSION
DG ENER
STUDY ON ACTUAL GHG
DATA FOR DIESEL,
PETROL, KEROSENE AND
NATURAL GAS
INTERIM REPORT
WORK ORDER: ENER/C2/2013-643
OCTOBER 2014
EUROPEAN COMMISSION
DG ENER
STUDY ON ACTUAL
GHG DATA FOR
DIESEL, PETROL,
KEROSENE AND
NATURAL GAS
INTERIM REPORT
WORK ORDER: ENER/C2/2013-643
OCTOBER 2014
Study on actual GHG data for diesel, petrol, kerosene and natural gas
Interim Report
Table of Contents
LIST OF FIGURES ........................................................................ 7
LIST OF TABLES ........................................................................ 11
ABBREVIATIONS ....................................................................... 14
SUMMARY .................................................................................. 17
1
REVIEW AND PROGRESS OF STUDY TASKS .................. 19
1.1
Introduction .................................................................................................... 19
1.2
Legal Context ................................................................................................ 20
1.3
Overview of Study Tasks ............................................................................... 21
1.3.1 Task a: Literature survey ........................................................................... 21
1.3.2 Task b: Data acquisition ............................................................................ 22
1.3.3 Task c: Models to estimate max and min GHG emissions ......................... 23
1.3.4 Task d: Emissions due to accidents and other operational failures ............ 24
1.3.5 Task e: Other issues related to sustainability ............................................ 24
1.3.6 Task f: Emissions projections up to 2030 .................................................. 25
1.4
Contribution of The Present Study to Oil and Gas GHG Emissions Assessment
25
1.4.1 JEC Report: Well-To-Tank (WTT) emissions............................................. 27
1.4.2 NETL Report: An Evaluation of the Extraction, Transport and Refining of
Imported Crude Oils and the Impact on Life Cycle Greenhouse Gas Emissions
28
1.4.3 ICCT Study: Upstream Emissions of Fossil Fuel Feedstocks for Transport
Fuels Consumed in the European Union ................................................... 29
1.4.4 ICF Study: Independent Assessment of the European Commission’s Fuel
Quality Directive’s “Conventional” Default Value ....................................... 29
1.4.5 Jacobs Consultancy Report: EU Pathway Study: Life Cycle Assessment of
Crude Oils in a European Context ............................................................. 30
1.4.6 ICF Study: Desk Study on Indirect GHG Emissions from Fossil Fuels....... 31
1.4.7 NETL: Life Cycle Greenhouse Gas Inventory of Natural Gas Extraction,
Delivery and Electricity Production ............................................................ 32
1.4.8 OGP Report: Environmental Performance Indicators - 2012 Data ............. 33
1.4.9 Upstream greenhouse gas (GHG) emissions from Canadian oil sands as a
feedstock for European refineries .............................................................. 33
1.5
Progress Achieved Till October 2014 ............................................................. 34
1.5.1 Key dates of project evolution ................................................................... 36
2
TASK A: LITERATURE SURVEY ........................................ 37
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Interim Report
2.1
Survey Approach ........................................................................................... 37
2.2
Presentation Of Literature Database .............................................................. 39
3
TASK B: DATA ACQUISITION ............................................ 41
3.1
EU Oil and Gas Supply .................................................................................. 41
3.1.1 EU crude oil supply ................................................................................... 41
3.1.2 Supply of refined products from third countries ......................................... 43
3.1.3 EU natural gas supply ............................................................................... 45
3.2
General Methodological Considerations for GHG Life Cycle Emission
Assessment ................................................................................................... 49
3.2.1 Fuels examined ......................................................................................... 49
3.2.2 Categorization of data collection ............................................................... 49
3.2.3 Geographical coverage ............................................................................. 51
3.2.4 Choice of baseline year ............................................................................. 51
3.2.5 System boundaries ................................................................................... 51
3.2.6 Global Warming Potential (GWP) used ..................................................... 51
3.2.7 Utilization of Minimum/Maximum approach ............................................... 51
3.3
Methodological Approach for Oil .................................................................... 52
3.3.1 Introduction ............................................................................................... 52
3.3.2 Upstream .................................................................................................. 56
3.3.3 Midstream ................................................................................................. 67
3.3.4 Downstream .............................................................................................. 87
3.3.5 GHG emissions of refined products ........................................................... 91
3.3.6 GHG emissions of unconventional crude oil and natural gas ..................... 95
3.4
Methodological Approach for Natural Gas GHG Assessment ........................ 96
3.4.1 Natural gas supply chain ........................................................................... 96
3.4.2 Methodology for assessing GHG emissions .............................................. 98
3.4.3 Natural Gas Streams ................................................................................. 99
3.4.4 Upstream ................................................................................................ 103
3.4.5 Midstream ............................................................................................... 107
Algeria
115
LNG production ................................................................................................ 115
3.4.6 Downstream ............................................................................................ 120
3.5
Approach for Data Collection ....................................................................... 123
3.5.1 Correspondence with oil and gas companies .......................................... 123
3.5.2 Approach for actual emissions data collection ......................................... 126
3.6
ACTUAL DATA FOR CRUDE OIL ...................................................................... 129
3.6.1 Russia and FSU countries ....................................................................... 130
3.6.2 Azerbaijan ............................................................................................... 134
3.6.3 Norway 136
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3.6.4 United Kingdom....................................................................................... 142
3.6.5 Nigeria 145
3.6.6 Denmark ................................................................................................. 146
3.6.7 Angola 148
3.6.8 Carbon Disclosure Project (CDP) reports ................................................ 149
3.6.9 Refining 150
3.6.10
3.7
Overview and evaluation of actual data collection progress for oil151
ACTUAL DATA FOR NATURAL GAS .................................................................. 154
3.7.1 Russia 155
3.7.2 The Netherlands...................................................................................... 157
3.7.3 Germany ................................................................................................. 158
3.7.4 Norway 159
3.7.5 United Kingdom....................................................................................... 160
3.7.6 Qatar
3.8
162
Data for Models ........................................................................................... 163
3.8.1 Data for OPGEE...................................................................................... 163
3.8.2 Data for PRIMES-Refinery ...................................................................... 167
3.8.3 Data for GHGenius.................................................................................. 170
3.9
Literature Data ............................................................................................. 180
4
TASK C: GHG EMISSIONS MODELLING.......................... 182
4.1
The OPGEE Model ...................................................................................... 183
4.1.1 Model rationale and structure .................................................................. 183
4.1.2 Required Inputs ....................................................................................... 185
4.1.3 Parametric significance ........................................................................... 186
4.1.4 Produced outputs .................................................................................... 194
4.1.5 Draft results............................................................................................. 197
4.2
The PRIMES-Refinery Model ....................................................................... 198
4.2.1 Model rationale and structure .................................................................. 199
4.2.2 Required Inputs and Outputs of the model .............................................. 204
4.2.3 Estimating the GHG emissions due to transportation from refineries to filling
stations 205
4.3
The GHGenius model .................................................................................. 208
4.3.1 Model rationale and structure .................................................................. 208
4.3.2 Model parameters and structure modification .......................................... 208
4.3.3 Required Inputs ....................................................................................... 210
4.3.4 Parametric significance ........................................................................... 211
4.3.5 Produced outputs .................................................................................... 212
5
TASK D: INDIRECT EMISSIONS ....................................... 215
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5.1
System Boundary Definition ......................................................................... 215
5.2
Attributional And Consequential Emissions .................................................. 215
5.3
Main Indirect Emissions ............................................................................... 217
5.3.1 Attributional emissions sources ............................................................... 217
5.3.2 Consequential emissions sources ........................................................... 219
5.4
Methodology For Assessment Of Indirect Emissions ................................... 220
5.5
Data collection for indirect emissions ........................................................... 222
5.5.1 Induced land GHG emissions .................................................................. 222
5.5.2 Accidents ................................................................................................ 224
5.5.3 Military GHG emissions ........................................................................... 225
5.6
Preliminary Results ...................................................................................... 226
6
TASK F: PROJECTIONS UP TO 2030 ............................... 228
6.1
Introduction to the Methodology ................................................................... 228
6.2
The PRIMES Energy Systems Model .......................................................... 229
6.2.1 Model structure ....................................................................................... 229
6.2.2 Model coverage....................................................................................... 229
ANNEX A: COORDINATES ...................................................... 231
Annex A.1: Oil fields.............................................................................................. 231
Annex A.2: Terminals............................................................................................ 232
Annex A.3 Ports .................................................................................................... 234
ANNEX B: MAPS ...................................................................... 237
Annex B.1: Oil fields maps .................................................................................... 237
Annex B.2: Oil pipeline maps ................................................................................ 241
ANNEX C: LITERATURE DATABASE EXTRACT .................... 246
ANNEX D: LETTER TEMPLATE FOR OIL AND GAS DATA
REQUEST .......................................................................... 270
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LIST OF FIGURES
Figure 1.1: Diagram with project Tasks and flows of information inputs ...................... 21
Figure 1.2: Time schedule of project Tasks as in the proposal .................................... 35
Figure 2.1: Snapshot of the literature database........................................................... 40
Figure 3.1: EU crude oil supply 2010 - 2014 (source: DG ENER) ............................... 41
Figure 3.2: EU crude oil by country in 2012 (source: DG ENER)................................. 42
Figure 3.3: Russian crude oil exports in million b/d (source: CDU-TEK) ...................... 42
Figure 3.4: Transneft’s Druzhba deliveries plan for 1st Quarter of 2011 in million b/d
excluding transit (source: Transneft) ................................................................... 43
Figure 3.5: Russian diesel export forecast 2014 – 2020 and OECD Europe diesel
supply forecast 2014-2020 (source: OGJ, based on ESAI Energy study) ............ 44
Figure 3.6: EU Natural Gas Imports, Production and Consumption in million cubic
meters for 2012. .................................................................................................. 45
Figure 3.7: EU natural gas supply by country of origin, 2012 (source: IEA) ................. 46
Figure 3.8: Gas trade flows in Europe (source: IEA) ................................................... 48
Figure 3.9: Overview of the strategy for the assessment of GHG emissions for crude oil
and natural gas ................................................................................................... 50
Figure 3.10: Physical flow of crude oil illustrating the basic stages that are examined by
the study ............................................................................................................. 53
Figure 3.11: Main steps for the assessment of GHG emissions of gasoline, diesel and
kerosene ............................................................................................................. 53
Figure 3.12: Crude oil benchmarks used worldwide (source: ICE) .............................. 54
Figure 3.13: Quantities produced globally and properties of main crudes (source: ENI
2012)................................................................................................................... 56
Figure 3.14: Map of representative oil fields and their terminals ................................. 64
Figure 3.15: Exports in million b/d including transit through Russian ports Quarter 1 of
2010 to Quarter 1 of 2011 (source: CDU) ............................................................ 69
Figure 3.16: Map of major ports importing crude oil in Europe .................................... 71
Figure 3.17: The Baltic Pipeline System. Gas pipelines are shown in red colour, oil
pipelines in green and the dashed line shows the planned pipelines. (source: EIA)
............................................................................................................................ 72
Figure 3.18: Russian crude oil analysis from oil field to MCON ................................... 77
Figure 3.19: Map with main routes of Russian pipelines supplying crude oil to Europe78
Figure 3.20: Location of major refineries in Europe ..................................................... 87
Figure 3.21: EU 28 imports of refined products (in barrels of oil per day) for specific
refined products from Russia and USA (source: Eurostat) .................................. 91
Figure 3.22: Methodology for the assessment of emissions from refined products ...... 92
Figure 3.23: Map of Russian Refineries supplying refined products to EU .................. 94
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Figure 3.24: Natural gas supply chain (Source: CE, Delft) .......................................... 97
Figure 3.25: Natural gas streams methodological approach........................................ 98
Figure 3.26: Natural gas streams arriving to the South East EU region ..................... 101
Figure 3.27: Natural gas streams arriving to the North EU region ............................. 101
Figure 3.28: Natural gas streams arriving to the South West EU region .................... 102
Figure 3.29: Natural gas streams arriving to the Central EU region........................... 102
Figure 3.30: Map of natural gas producing fields supplying the EU ........................... 105
Figure 3.31: Map of LNG supply of the EU including liquefaction plants and importing
terminals ........................................................................................................... 110
Figure 3.32: Map of major Russian natural gas pipelines arriving to Europe (Source:
Wikipedia) ......................................................................................................... 111
Figure 3.33: Map of the Norwegian Continental Shelf natural gas pipelines .............. 114
Figure 3.34: Algerian natural gas transport pipelines map (Source: Sonatrach) ........ 115
Figure 3.35: Qatar energy infrastructure map (Source: EIA) ..................................... 117
Figure 3.36: Map of the Greenstream pipeline .......................................................... 118
Figure 3.37: Map of the UK Natural gas international pipelines ................................. 119
Figure 3.38: Netherlands gas transmission map ....................................................... 120
Figure 3.39: Flaring emissions (in bcm) according to the NOAA/GGFR database and
flaring to oil ratio (scf/bbl) for the calculated based on EIA production volumes for
2011 .................................................................................................................. 131
Figure 3.40: Flaring of associated gas in target countries in bcm according to national
statistics for the years 2006 – 2012, in billion cubic meters (source: EBRD) ..... 132
Figure 3.41: Comparison of associated flaring volumes in bcm between national
statistics and NOAA estimates (source: EBRD) ................................................ 132
Figure 3.42: APG production and flaring in Russia by zone in bcm, 2010 (KPMG) ... 133
Figure 3.43: BP’s emissions in Azerbaijan for 2012 (emission in kilotonnes) ............ 135
Figure 3.44: BP in Azerbaijan gross flaring volumes by asset in kilotonnes (source: BP)
.......................................................................................................................... 136
Figure 3.45: GHG emissions produced for petroleum from various origins (in kg of
carbon equivalent per barrel of oil produced) (source OGP, Environment Web) 137
Figure 3.46 : Breakdown of GHG emissions by source in metric tonnes CO 2 equivalent
for Norway (source: NPD) ................................................................................. 138
Figure 3.47: GHG emissions of representative Norwegian oil fields in tonnes of CO2
equivalent (source: Norwegian Environmental Directorate) ............................... 139
Figure 3.48: GHG emissions per unit of output of oil (in tonnes CO2 equivalent per m3
of oil) (source: NPD and own elaboration) ......................................................... 139
Figure 3.49: Breakdown of emissions of the UK oil sector by source (in million metric
tonnes) (source: DEFRA) .................................................................................. 143
Figure 3.50: Total atmospheric CO2 emissions and emissions due to consumption of
fuel gas for energy production (in tonnes CO2 equivalent) for three oil fields
(source: NEXEN)............................................................................................... 143
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Figure 3.51: CO2 emissions from production facilities in the North Sea (source: DEA)
.......................................................................................................................... 147
Figure 3.52: Fuel consumption (gas) for upstream activities (source: DEA) .............. 147
Figure 3.53: CO2 emissions from consumption of fuel per mtoe (source: DEA) ........ 148
Figure 3.54: Gas flared (source: DEA) ...................................................................... 148
Figure 3.55: Emissions of the refinery sector per country for 2012 in kt CO2 equivalent
as verified by the European Trading Scheme – ETS (source: European
Environmental Agency) ..................................................................................... 151
Figure 3.56: Breakdown of emissions of the UK gas sector by source in kilotonnes CO 2
(source: DEFRA) ............................................................................................... 161
Figure 3.57: Flaring (% of sweet gas) for Qatargas for the 1st half of 2014 ............... 163
Figure 3.58: GHG intensity (tonne CO2 eq. GHG/ tonne LNG) for Qatargas for the first
half of 2014 ....................................................................................................... 163
Figure 3.59: UK Gas Leakage Rate over the years 2002 – 2012 (source: DECC) .... 174
Figure 4.1: Schematic chart with the various stages of the LCA analysis included in the
OPGEE model (Source: OPGEE model documentation) ................................... 184
Figure 4.2: Sensitivity analysis on the API gravity: results obtained using the OPGEE
model ................................................................................................................ 189
Figure 4.3: Sensitivity analysis on the Water to Oil Ratio (WOR): results obtained using
the OPGEE model............................................................................................. 190
Figure 4.4: Sensitivity analysis on the Flaring to Oil Ratio (FOR): results obtained using
the OPGEE model............................................................................................. 191
Figure 4.5: Sensitivity analysis on the Venting to Oil Ratio (VOR): results obtained
using the OPGEE model ................................................................................... 192
Figure 4.6: Sensitivity analysis on the marine shipping Origin- destination (O-D)
distance: results obtained using the OPGEE model .......................................... 194
Figure 4.7: Draft results on GHG emissions of five MCONs using the OPGEE model
(input data from Task b) .................................................................................... 198
Figure 4.8: Schematic representation of the main processes included in the
representative refinery structure of the PRIMES-Refinery model....................... 200
Figure 5.1: Identification of indirect emission sources related to oil and gas pathway
from well to tank ................................................................................................ 217
Figure B.1: Nigerian pipelines oil and gas fields map ................................................ 237
Figure B.2: Algerian pipelines, oil and gas fields map (source: Ministère de l’Energie et
des Mines) ........................................................................................................ 238
Figure B.3: Iraq’s pipelines, oil and gas fields map (source: Platts) ........................... 238
Figure B.4: Arabian oil and gas pipeline system........................................................ 239
Figure B.5: Libyan pipelines, and oil fields map (source: Goldman Sachs) ............... 240
Figure B.6: Major Caspian oil and gas pipeline system (source: EIA) ....................... 241
Figure B.7: Russian oil and gas pipeline system (source: Theodora Maps) .............. 242
Figure B.8: Balkan oil and gas pipeline system (source: Theodora Maps) ................ 242
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Figure B.9: Oil and gas pipeline system of Central Europe (source: Theodora Maps)
.......................................................................................................................... 243
Figure B.10: Oil and gas pipeline system of North Africa (source: Theodora Maps) . 244
Figure B.11: Oil and gas pipeline system of Middle East (source: EIA) ..................... 245
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LIST OF TABLES
Table 3.1: Imports of refined products by FSU and USA (source: Bloomberg) ............ 43
Table 3.2: EU natural gas supply share by mode of transport ..................................... 47
Table 3.3: European imports and deliveries of crude oil for 2012 (source: European
Commission, DG ENER) ..................................................................................... 58
Table 3.4: List of representative MCONs and oil fields ................................................ 61
Table 3.5: Different grades for Urals crude oil (source: Argus Media) ......................... 62
Table 3.6: Price assessments for crude oil transported via the Druzhba pipeline
(source: Argus Media) ......................................................................................... 62
Table 3.7: Representative MCONs and their operators ............................................... 66
Table 3.8: Most significant oil terminals supplying crude oil to Europe ........................ 68
Table 3.9: Crude oil tanker categories (source: Lloyds) .............................................. 70
Table 3.10: EU refining locations and capacities linked to Druzhba pipeline ............... 72
Table 3.11: Russian and Caspian pipeline supplying Europe (source: EIA) ................ 78
Table 3.12: Major pathways of the 5 most significant MCONs imported in Europe ...... 86
Table 3.13: Emission factors of gasoline used for estimating fugitive emissions from
filling stations in Denmark (Source: NERI, 2009) ................................................. 91
Table 3.14: Russian refineries exporting ULSD to Europe (source: OGJ, company
websites) ............................................................................................................. 93
Table 3.15: Overview of feedstock input of representative US refinery (adopted by
Jacobs, 2012) ..................................................................................................... 95
Table 3.16: Major natural gas suppliers of the EU..................................................... 100
Table 3.17: Key characteristics of natural gas producing countries supplying the EU 28
.......................................................................................................................... 107
Table 3.18: EU 28 Natural gas consumption for road transport in 2012 (source
Eurostat) ........................................................................................................... 122
Table 3.19: Overview of the correspondence with oil and gas associations,
agenciesand companies ................................................................................... 126
Table 3.20: Overview of actual data sources, type of data collected and data coverage
.......................................................................................................................... 129
Table 3.21: Russian reported emissions per lifecycle stage for 2012 for oil and natural
gas (source: UNFCCC) ..................................................................................... 134
Table 3.22: BP in Azerbaijan net GHG emissions per asset (in kilotonnes) ............... 136
Table 3.23: Overview of Statoil’s 20 facilities (terminals and platforms) with the highest
GHG emissions (Scope 1 and Scope 2), as those reported to CDP. ................. 140
Table 3.24: Emission data for Norway for oil and natural gas................................... 141
Table 3.25: UNFCCC Emission data for United Kingdom for oil and natural gas....... 144
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Table 3.26: The twenty oil fields with the largest flaring volumes per day in UK for 2013
(source: DECC) ................................................................................................. 145
Table 3.27: Twenty Nigerian fields with the largest flaring volumes........................... 146
Table 3.28: Environmental data by BP’s activities in Angola for the years 2006-2012
(source: BP) ...................................................................................................... 149
Table 3.29: Scope 1 and Scope 2 reported values for oil and gas emissions for specific
companies (source: CDP) ................................................................................. 150
Table 3.30: Sources of measured and reported emission data organized per process
country and MCON ........................................................................................... 153
Table 3.31: Overview of natural gas actual data sources .......................................... 155
Table 3.32: GHG actual emissions from the Russian export pipelines to Europe (in
million tonnes of CO2 equivalent) (source: Wuppertal Institute) ........................ 156
Table 3.33: UNFCCC country data for the Netherlands (source: UNFCCC) .............. 158
Table 3.34: Breakdown of emissions of the UK gas sector by source in million metric
tonnes (source: DEFRA) ................................................................................... 159
Table 3.35: Releases of major pollutants for Snøhvit and Troll oil fields (source:
Norwegian Environment Directorate) ................................................................ 159
Table 3.36: Carbon emissions for Kvitebjørn and Åsgard oil fields (source: Norwegian
Environment Directorate) .................................................................................. 160
Table 3.37: RasGas company cumulative emissions 2007-2013 .............................. 162
Table 3.38: Overview of literature sources for OPGEE inputs ................................... 166
Table 3.39: List of refineries located in the EU countries (Source: Oil and Gas Journal,
2013)................................................................................................................. 170
Table 3.40: EU Gas Supply (million cm).................................................................... 171
Table 3.41: Regional EU Power Supply (the percentage of power supplied by each
type of generation) ............................................................................................ 172
Table 3.42: Regional EU Power Generation Efficiency ............................................. 172
Table 3.43: Electric Power Distribution Losses ......................................................... 172
Table 3.44: Natural Gas Producers Power Mix ......................................................... 173
Table 3.45: Typical Energy Consumption Data for NG Stages .................................. 174
Table 3.46: Lengths of major natural gas pipelines supplying the EU ....................... 176
Table 3.47: LNG transport distances from LNG suppliers to importers in the EU ...... 176
Table 3.48: Pipeline lengths from gas fields to liquefaction plants in Algeria and Libya
.......................................................................................................................... 177
Table 3.49: The 26 Natural gas transmission systems length (Source: ENTSOG) .... 178
Table 3.50: Natural gas distribution losses in EU countries for 2012 (Source: Eurostat)
.......................................................................................................................... 179
Table 3.51: Electricity consumption in pipeline transport in EU countries for 2012
(Source: Eurostat) ............................................................................................. 180
Table 3.52: Emissions data provided by CE Delft for CNG and small scale LNG ...... 180
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Table 4.1: Typical input to the OPGEE model for the calculation of the GHG emissions
per field (values for the generic type of field included in OPGEE ....................... 188
Table 4.2: Typical output of the OPGEE model ......................................................... 196
Table 4.3: Representative crude oil types considered in the PRIMES-Refinery model:
classification by API gravity and sulphur content ............................................... 202
Table 4.4: Main refining processes used in the PRIMES-Refinery model .................. 203
Table 4.5: Estimated carbon intensity of refined petroleum products due to
transportation from refineries to filling stations (also including fugitive emissions at
the level of filling stations). Source: E3MLab calculations.................................. 208
Table 4.6: Typical GHGenius Output on the emissions of natural gas ....................... 212
Table 4.7: Typical GHGenius Output by Specific Gas ............................................... 213
Table 4.8: Typical GHGenius Output for the Total Energy Consumption ................... 213
Table 4.9: Typical GHGenius Output for the Secondary Energy Use by Type ........... 214
Table 5.1: Potential indirect GHG emissions for oil consumed in the EU................... 221
Table 5.2: Share of oil production affected by specific indirect GHG emissions ........ 222
Table 5.3: Unit GHG emissions for specific indirect effects ....................................... 227
Table 5.4: Average indirect GHG emissions for oil consumption in EU ..................... 227
Table 5.5 Average indirect GHG emissions for natural gas consumption in EU ........ 227
Table A.0.1: Geographical coordinates of representative oil fields (source: own
elaboration) ....................................................................................................... 232
Table A.0.2: Geographical coordinates of representative oil field terminals (source: own
elaboration) ....................................................................................................... 233
Table A.0.3: Geographical coordinates of major European oil importing ports (source:
own elaboration) ............................................................................................... 236
Table C.0.1: Extract from the generic literature database until the interim report delivery
.......................................................................................................................... 247
Table C.0.2: Extract from the specific literature database until the interim report delivery
.......................................................................................................................... 269
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ABBREVIATIONS
ACG
Azeri–Chirag–Gunashli
AFRA
Average Freight Rate Assessment
AGR
Acid Gas Removal
AIS
Automatic Identification System
APEX
Analysis of Petroleum Exports
APG
Associated Petroleum Gas
API
American Petroleum Institute
BAT
Best Available Techniques
BCF
Billion Cubic Feet
BPS
Baltic Pipeline System
BTC
Baku-Tbilisi-Ceyhan
CARB
California Air Resources Board
CDU TEK
Central Dispatching Department of Fuel Energy Complex
CDP
Carbon Disclosure Project
CHP
Combined Heat and Power
CI
Carbon Intensity
CIF
Cargo Insurance Freight
CNG
Compressed Natural Gas
CNPC
China National Petroleum Corporation
CPC
Caspian Pipeline Consortium
DEA
Danish Energy Agency
DECC
Department of Energy and Climate Change
DEFRA
Department of Environment, Food and Rural Affairs
DG ENER
Directortate General for Energy
DUC
Danish Underground Consortium
DWT
Dead Weight Tonnage
EBRD
European Bank for Recontstruction and Development
EC
European Commission
EEA
European Environment Agency
EIA
U.S. Energy Information Administration
EOR
Enhanced Oil Recovery
ETS
European Trading Scheme
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EU
European Union
EW
Environmental Web
FCC
Fuel Catalytic Cracking
FOB
Free on Board
FOR
Flaring to Oil Ratio
FQD
Fuel Quality Directive
FSU
Former Soviet Union
GGFR
Global Gas Flaring Reduction
GHG
Greenhouse Gas
GOR
Gas-to-oil ratio
GWP
Global Warming Potential
HCICO
High Carbon Intensity Crude Oil
ICCT
International Council on Clean Transportation
ICE
Inter Continental Exchange
IEA
International Energy Agency
IFP
Institut Français du Pétrole
ILUC
Indirect Land Use Change
IPCC
Intergovernmental Panel on Climate Change
IPIECA
International
Association
ISO
International Organization for Standardization
JEC
JRC - EUCar and CONCAWE
JRC
Joint Research Centre
LCA
Lifecycle Assessment
LCFS
Low Carbon Fuel Standard
LCFS
Low Carbon Fuel Standard
LNG
Liquefied Natural Gas
MCON
Marketable Crude Oil Name
MENA
Middle East and North Africa
mmcm
million cubic meters
MS
Member State
MTA
Million Tonne per Annum
NCS
Norwegian Continental Shelf
NETL
National Energy Technology Laboratory
NG
Natural Gas
NNPC
National Nigeria Petroleum Company
NOAA
National Oceanic and Atmospheric Administration
Petroleum
Industry
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Conservation
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NPD
Norwegian Petroleum Directorate
NWE
NorthWest Europe
OGJ
Oil and Gas Journal
OGP
International Association of Oil & Gas Producers
OPGEE
Oil Production Greenhouse gas Emissions Estimator
OSPAR
Oslo and Paris Convention
PDVSA
Petroleos de Venezuela
RED
Renewable Energy Directive
SCO
Synthetic Crude Oil
SOC
(Iraq’s state-owned) South Oil Company
SOR
Steam-to-Oil Ratio
TEOR
Thermally Enhanced Oil Recovery
toe
tonne of oil equivalent
ToR
Terms of Reference
TSP
Technical Service Provider
UAE
United Arab Emirates
UGTS
United Gas Transmission System
ULCC
Ultra Large Crude Carrier
ULSD
Ultra Low Sulphur Diesel
UNFCCC
United Nations Framework Convention on Climate Change
VFF
Venting, Flaring and Fugitive
VLCC
Very Large Crude Carrier
VOR
Venting to Oil Ratio
WOR
Water to Oil Ratio
WSPA
Western State Petroleum Association
WTI
West Texas Intermediate
WTO
World Trade Organization
WTT
Well-to-Tank
WTW
Well-to-Wheel
WWF
World Wildlife Fund
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SUMMARY
This project, “Study on actual GHG data for diesel, petrol, kerosene and natural gas”, is
implemented by EXERGIA S.A. (Leader), in collaboration with E3M-Lab (Economics
Energy Environment Modelling Laboratory) of the National Technical University of
Athens and COWI A/S. This Report is submitted at the end of the 6th month that is end
of October, whereas the total project duration is 15 months.
The project implementation is organized in six discrete Tasks (a to f) with the addition
of the project management Task 0. Two of the Tasks, namely Task a: Literature
survey and Task b: Data acquisition, have been completed and two of the Tasks,
namely Task c: Models to estimate max and min GHG emissions and Task d:
Emissions due to accidents and other operational failures are in good progress
according to the project schedule. The remaining two Tasks, namely Task e: Other
issues related to sustainability and Task f: Emissions projections up to 2030 have
been initially considered. In general the proposed schedule of project activities has
been followed and till the time of Interim Report there is no indication that amendments
are necessary.
The major effort of the Consultant has been addressed to the activities of data
acquisition and especially in collecting lifecycle Actual GHG emissions data, both for oil
and natural gas, in accordance to the main objective of the project mandate. Thus, all
open sources of relevant information have been investigated, mainly availed by
national, international organizations and oil and gas associations. Furthermore, all
major oil and natural gas companies have been contacted related to oil and gas
streams directed to the EU and requested specific and disaggregated data per
process. The results were satisfactory in countries where organized GHG emissions
are registered and relevant reporting procedure are in place (e.g. Norway, UK,
Netherlands, Denmark, etc.). On the other hand, aggregated actual data were also
identified in the UNFCCC reports of Annex I countries and in specific reports of
companies operating the oil and gas fields. The response of the oil and gas companies
contacted for provision of GHG disaggregated data was very poor till now. For the
cases where actual could not be found, we intend to assess GHG emissions by using
two models, namely OPGEE for oil and GHGenius for natural gas. Consequently, the
necessary input data for these models were gathered. Especially, regarding the
estimation of the downstream oil sector GHG emissions we updated the PRIMESRefinery model with recent information about the EU refining capacity and
developments.
Resonable assumptions were made in order to structure the estimations of GHG
emissions in comprehensive and realistic pathways for the EU, we proceeded to
reasonable assumptions. The Marketable Crude Oil Name (MCON) system was used
as the basis for oil sector pathways definition and the Gas Stream concept for natural
gas sector respectively. In addition, focus was given on the most significant flows of oil
and gas imported in the EU, leaving aside the small and insignificant fuel flows.
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Therefore, around 100 pathways of oil products (petrol, diesel, kerosene) GHG
emissions estimations were considered and respectively around 40 pathways for
natural gas products (CNG, LNG) supplying transportation. For all these pathways the
lifecycle GHG estimation will be carried out either as an elaboration of actual data, or
as a model output or as a combination of both approaches.
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1.1
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REVIEW AND PROGRESS OF STUDY TASKS
INTRODUCTION
In order to reach the targets set by the Renewable Energy and Fuel Quality Directives,
a certain percentage of fuels used in the transport sector nowadays have to be
replaced by biofuels. Sustainability issues arising from the enhanced use of biofuels
and the Greenhouse Gas (GHG) emissions from their whole lifecycle have been
discussed extensively; however, there is no detailed information about the actual
lifecycle GHG emissions of fossil fuels consumed in the transport sector.
In many cases, lifecycle GHG emissions of biofuels are compared to the respective
average emissions of oil products used as fuels in transport. In order to provide a fair
and clear picture of fossil fuel GHG emissions directed to transport, more detailed data,
especially throughout Europe, are needed. Therefore, the overall aim of this project is
to provide lifecycle GHG emissions based on the actual data as possible. The
considerable information uncertainty endorsed to collection and elaboration of these
data might be tackled with estimations on the range of the GHG emission quantities in
the form of minimum and maximum values.
Therefore, the lifecycle Carbon Intensity (CI) of petrol, diesel, kerosene and natural gas
will be assessed in a “well-to-tank” approach. In general, “well-to-tank” emissions refer
to those ones associated with fuel pathways from extraction up to fuelling the tanks of
land, sea and air transportation means. A chain of significant production stages of oil
and gas, like exploration, exploitation, upgrading, transportation, transmission, refining,
distribution, etc. are considered; thus excluding the final stage of combustion in the
transportation means’ engines.
The study results will be based on data acquisition from reliable and official sources
and on output from consistent and widely acceptable GHG emissions and energy
models.
The project has been assigned through the REQUEST NO: ENER/C2/2013-643 and
will be implemented by EXERGIA S.A. (leader), in collaboration with E3M-Lab
(Economics Energy Environment Modelling Laboratory) of the National Technical
University of Athens and COWI A/S. These three organisations are core members of
the consortium led by COWI Belgium, which participates in the Framework Service
Contract SRD MOVE/ENER/SRD.1/2012-409-LOT3-COWI. The group of organizations
accumulates important experience in energy and GHG modelling relative to energy
policy decision making, collection and elaboration of data and analysing sustainability
issues.
Lastly, readers should note that the report presents the views of the Consultant, which
do not necessarily coincide with those of the European Commission.
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LEGAL CONTEXT
The EU policy on GHG emissions of oil products is implemented under the context of
two Directives:


(RED) Renewable Energy Directive (2009/28/EC) and
(FQD) Fuel Quality Directive (2009/30/EC)
In the framework of mandatory national overall targets and measures for the use of
energy from renewable sources provided by the RED, the overall target set for the EU
is at least a 20 % share of energy from renewable sources in the Community’s gross
final consumption of energy in 2020. According to Article 3/4 of the RED, each
Member State shall ensure that the share of energy from renewable sources in all
forms of transport in 2020 is at least 10 % of the final consumption of energy in
transport in that Member State. The blending of biofuels is one of the methods
available for Member States to meet this target, and is expected to be the main
contributor. Also in Article 17/2 it is provided that under sustainability criteria biofuels
under consideration should reduce GHG emissions by at least 35% compared to
substituted gasoline or diesel. Thus volumetric targets are set, but also some sort of
mandatory CI performance is imposed, which is implemented in the broader area of
conventional fuel substitution. The latter GHG emissions percentage increases to 50%60% by January 1, 2017 according to set provisions.
On the other hand, the FQD, Article 7a mandates that Member States shall require
suppliers to reduce as gradually as possible life cycle greenhouse gas emissions per
unit of energy from fuel and energy supplied by actually up to 6 % by 31 December
2020; thus setting this way a Low Carbon Fuel Standard (LCFS). As in the RED, the
greenhouse gas emission saving from the use of biofuels taken into account shall be at
least 35 %. Furthermore, with effect from 1 January 2011, suppliers shall report
annually, to the authority designated by the Member State, on the greenhouse gas
intensity of fuel and energy supplied within each Member State by providing, as a
minimum, the following information:


the total volume of each type of fuel or energy supplied, indicating where
purchased and its origin; and
lifecycle greenhouse gas emissions per unit of energy.
An accurate accounting of the lifecycle GHG emissions of fossil fuel extraction based
on actual data is important for the implementation of both Directives, due to the
required fulfilment of the volumetric target. Especially in the case of the FQD the
accounting is requested also as a necessary tool to assess and verify GHG emissions.
A differentiated accounting of GHG emissions of various oil and gas streams
contributes in demonstrating cases of low and high carbon fuels, but also in
considering measures for reductions in the carbon intensity at the stages of extraction,
transportation and refining, in principle. The comparison with alternative or renewables
based fuels (biofuels, electricity, CNG, LNG, etc.), mentioned in both Directives,
becomes substantial and realistic in the case of differentiated accounting. Therefore a
combination of policies could be undertaken towards fulfilling the set targets for the
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transportation fuels.
1.3
OVERVIEW OF STUDY TASKS
Figure 1.1 depicts the main Tasks of the project and the main data flows and
information linked with the project tasks. In the following Sections a brief description of
these Tasks is presented.
Figure 1.1: Diagram with project Tasks and flows of information inputs
1.3.1
Task a: Literature survey
The starting point of the literature survey is the in-depth analysis of EU legislation
related to GHG emissions of transport fuels and its targets, as well as the Member
States’ laws that comply with these targets. More specifically, the Directives that are
being used as reference, i.e. the Renewable Energy Directive (RED), along with the
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National Renewable Energy Action Plans submitted by the Member States and the
Fuel Quality Directive (FQD) are analysed thoroughly, in order to understand the
requirements of EU policies and their implementation within the legislation of each
Member State. Moreover, all relevant EC Communications and Initiatives will be
reviewed, in order to further comprehend the principles and recommendations of EU
GHG emissions policy.
The literature survey covers also a broad range of subjects related to GHG emissions
of lifecycle of diesel, petrol, kerosene and natural gas and will break these down by
type. The subjects that are covered will include e.g. GHG emissions calculation
methods, fuel extraction, fuel transport, fuel refinement, etc. Additionally, the literature
survey includes a broad range of information resources that are also broken down by
type, e.g. private companies reports, international organisations reviews, scientific
papers, etc.
The literature survey focuses on the most up-to-date data and knowledge on the
subject of GHG emissions and is based on two methods: extensive online literature
search, as well as identifying valuable items based on discussion and communication
with stakeholders. The consultant sets the criteria, in communication with the
Contracting Authority, that allow sorting out the various reading materials, in order to
create a literature database.
The main output of this Task is a comprehensive categorised literature database based
on the assessment of available documentation.
1.3.2
Task b: Data acquisition
It is stressed that the outcome of the assignment is largely dependent on the
development of a detailed and robust database. In principle, the Consultant bases
the analysis on actual data provided mainly by public organizations, oil companies
and oil companies’ associations. However, acknowledging the fact that oil companies
have been reluctant to disclose data in the past, information from other sources are
used for the development of the database that will be the basis for the assessment of
the GHG emissions (to be carried out during Tasks c and f).
This project mandate suggests a two-step approach regarding data collection that
involves data acquisition from private companies and data acquisition from other open
access sources, including international organisations. Necessary information refers to
all sectors of the oil and gas fuels value chain (upstream, midstream, downstream), i.e.
data pertaining to the crude oil extraction, tanker transportation, gas production and
transmission, LNG and CNG transformation, energy consumption in refineries,
venting/flaring emissions, data regarding unconventional oil and gas production and
transportation, etc.
The main output of this Task is the database on direct GHG emissions from the
lifecycle of diesel, petrol, kerosene and natural gas concentrating on the year 2012 that
will be the main input to the following modelling Tasks.
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Task c: Models to estimate max and min GHG emissions
The focus of this study is the assessment of the well-to-tank (WTT) GHG emissions of
petroleum fuels and natural gas. Actual data of GHG emissions are considered in
priority, however in cases of lack of proper data the use of specialized models,
namely OPGEE for oil and GHGenius for gas, are used to estimate the necessary
GHG emissions. These models are modified to adapt to the EU reality in terms of gas
and oil imports and transmission, processing up to distribution to tanks of final
consumers. Differentiated oil pathways based on Marketable Crude Oil Names
(MCONs) are used for oil types reaching the EU refineries. Respectively the main gas
streams of gas are used to represent the gas pathways from the main gas producing
fields up to their entry to the transmission systems of the EU countries and their
transfer to distribution to final consumers in the form of CNG or LNG.
The GHG emissions associated with petroleum fuels and natural gas are estimated
based on the data collected during the course of Task b; in principal this study intends
to make use of actual data obtained from private companies and other sources, as
specified by the requirements of Task b. In case disclosure of actual data by
companies is not feasible, other sources will be used; the latter will be determined
during the development of the database that will be undertaken in Task b. The already
existing OPGEE and GHGenius databases serve as guidance to determine information
requirements and as checks to verify the quality and accuracy of the new data to be
collected.
The present study additionally takes into account oil from unconventional sources.
Emissions due to bituminous sand, shale oil and gas extraction and upgrading are
estimated separately. The estimation will take into account emissions due to energy
consumption and venting/flaring emissions within the unconventional oil and gas
extraction and upgrading stages.
The midstream GHG emissions pertain to emissions resulting from the feedstock
transportation from the extraction source to the refinery gate. Emissions mainly occur
due to the energy consumption during the transport of petroleum and its products and
gas. In addition to seaborne transportation, land transportation (most commonly via
pipelines) is included. For natural gas transportation the present study will use the
currently available PRIMES gas supply model and database, which is very detailed and
has sufficient resolution, including all current and future gas pipelines (Eurasian and
North Africa coverage) as well as details on the global trade, liquefaction and
gasification of LNG.
The present study estimates GHG emissions of petroleum fuels during the upstream
and midstream sectors at world level, i.e. feedstock originating from all continents will
be taken into account. However, only the EU refinery system will be taken into
consideration in regard to the processing of the fossil fuels at downstream operations.
In order to associate emission factors to the concrete refinery output products (diesel,
petrol, kerosene) in a more adequate manner, the study uses a methodology, which
allows calculation of both average emission and marginal emission factors. This
method includes allocation of emissions to individual products based on marginal
emission content.
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The output of Task c is the minimum and maximum GHG emission factors associated
with the WTT supply chain of diesel, petrol, kerosene and natural gas for the year
2012.
1.3.4
Task d: Emissions due to accidents and other operational
failures
The objective of this Task is to evaluate the importance of the various sources of
indirect GHG emissions identified within the existing literature and data resources. The
indirect emission sources have to be considered in addition to the direct emissions
related to upstream, midstream and downstream processes. The most significant
sources of indirect GHG emissions of fossil fuels include (among others):



Emissions from accidents outside of normal operation conditions: These
include the emissions from the accident itself, the emergency response and
clean-up or remediation efforts.
Emissions from induced land development: The Induced Land Development
is the land use change that is caused by fossil fuel extraction in an indirect way,
i.e. the construction of access roads for oil and gas extraction etc. This type of
indirect emissions is in correspondence with GHG emissions produced by the
Indirect Land Use Change (ILUC), which is an important emissions source for
biofuels.
Emissions caused by military involvement: These include the military activities
and reconstruction efforts to protect and stabilise the supply of oil to global
markets, i.e. from military vehicles, military infrastructure etc.
The main output of this Task will be the data on indirect GHG emissions from the
lifecycle of diesel, petrol, kerosene and natural gas that will be considered in addition to
the direct emissions for the completion of the picture of 2012.
1.3.5
Task e: Other issues related to sustainability
Depending on the emission levels found for various fossil fuels, the EU is likely to be
faced with a variety of policy options. Indeed, the EU could decide to impose a cap on
the emissions of fossil fuels, which could in turn result in certain trade restrictions that
may be incompatible with international trade law. Furthermore, depending on the
values found, the EU could decide to revise the greenhouse-gas-emission saving
values, targets and other conditions, which are set in the Renewable Energy Directive
(2009/28/EC) and the Fuel Quality Directive (2009/30/EC). Therefore the objective of
Task e is to study the above two significant effects.
In light of the above, a Task exploring the various policy options as well as potential
trade law concerns appears pertinent. Therefore, the current Task includes a legal and
policy exercise addressing these issues.
The analysis and results of Task e will provide the EU with the necessary background
allowing it to continue framing a robust and sustainable policy, while avoiding exposure
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to potential WTO litigation.
1.3.6
Task f: Emissions projections up to 2030
The study will address the objective of Task f using the official projections provided
by E3M-Lab to the European Commission in 2013 using the PRIMES large scale
energy model. Projections of demand and supply of oil fuels and natural gas will be
used for a Reference and a Decarbonisation scenario as quantified using the PRIMES
energy system model for the European Commission in 2013. Refineries inputs and
outputs are also explicitly projected by the PRIMES model. PRIMES also provides
projections regarding net imports of refinery feedstock, ready-to-use refinery products
and natural gas. The coverage is by EU Member States.
The projected net imports of refinery feedstock and ready-to-use petroleum products by
PRIMES will be analysed based on country of origin and type, in order to obtain
detailed commercial flows. The analysis for projection years will be based on
assumptions relevant to current trends and to future production/import projections.
These assumptions will be harmonized to latest IEA World Outlook projection of global
oil/gas trade flows and regional production. For all projection years, average/marginal
emissions of the fuel WTT supply chain will be calculated. Emissions will be allocated
to each fuel based on the marginal emission content of fuels. Similarly to Task c, the
output of the analysis will be a range of GHG emissions resulting from the WTT supply
chain.
The output of Task f will be the minimum and maximum GHG emission factors for
projection years until 2030 (with emphasis up to 2020) associated with the WTT supply
chain. Similarly to the Task c output, results will be presented in a tabular format for
each fuel.
1.4
CONTRIBUTION OF THE PRESENT STUDY TO OIL AND GAS GHG
EMISSIONS ASSESSMENT
This project contributes to the scientific area of lifecycle GHG emissions assessment of
oil and gas directed to transport sector by combining methods and approaches, which
build on the existing experience and the available information by public institutions and
private companies. Certainly there is a number of important studies carried out in both
sides of Atlantic, which provide key background information for the current study as
they provide recent data and/or approaches. A brief presentation of these studies in the
following Sections provide an overview of their scope and main characteristics and
indicates the differences compared to our project analysis and scope.
The main characteristics of this study could be considered as follows:

Emphasis and priority is placed on the collection and use of actual data.
This approach is interpreted in two ways: either effort to use directly available
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



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GHG data coming from reliable sources or in case the analysis of the collected
data is not sufficient for direct use, utilization of actual data on verification
exercises concerning data produced from models or other analyses of relevant
studies.
The WTT approach includes full and thorough analyses of upstream,
midstream and downstream stages for the EU case. Therefore our approach
is absolutely related to the most significant pathways or streams of oil and gas
fuels addressed to the EU transportation sector, thus covering mostly the
presentation of the current situation (2012), but also carrying out the necessary
extrapolation up to 2030 by using the most well-known model (PRIMES) for the
EU energy economic policy assessments.
Linkage of upstream and midstream stages through the MCON concept.
The utilization of the concept of MCON aims at correlating the physical
properties characterizing crude oil as it is extracted from the oil field and those
of the crude oil blended during or before the refining process. Furthermore, the
concept of MCON practically facilitates the connection of the refinery input
(which has a marketable name) with the primary source of crude oil (at the oil
field).
Use of min/max methodology. The study aims at developing an integrated,
consistent and detailed methodology to evaluate the actual range of emissions
in the form of minimum, weighted average and maximum values that relate to
the whole lifecycle of diesel, petrol, kerosene and natural gas. The presentation
of final GHG emissions per MCON or final fuel in a range incorporates the
inherent uncertainties around GHG emission estimation and allows
policymakers to better evaluate the emissions of each primary source or final
fuel as these are illustrated in a more objective manner.
Incorporates indirect emissions and unconventional crude oil and natural
gas cases. We do not ignore the contribution of indirect GHG emissions,
although they are considered of small scale in comparison to the direct
emissions. Furthermore, we consider potential and characteristic pathways of
unconventional oil and gas that might play significant role in the supply of EU in
the forthcoming years.
Place particular emphasis on significant oil and gas streams for EU
supply. Especially, we consider that the size and the significance of the
Russian oil and gas directed to the EU requires proportional effort for the
analysis, given that the provision of information is poor at institutional and
energy company level. For example we try to cope with difficulties on the
disaggregation to specific types of crude oil, where several types of MCONs
might be depending on the mode of transport, port and transport costs. In
general although we pace a step forward on this analysis the lack of proper data
remains a restrictive factor.
Detailed assessment of crude oil emissions using the OPGEE model. In
the absence of direct GHG emissions data by oil companies, the Consultant has
used the OPGEE model for the assessment of GHG emissions for the upstream
and midstream life cycle stages. OPGEE is a complex engineering model that
requires a large amount of data as inputs. The collection of such data has been
a rather time consuming Task, since it requires research in a large amount of
sources. The effort and the resources that have been committed by the
Consultant for the collection of OPGEE inputs have been based on the
parametric analysis of inputs. For the missing inputs smart default values are
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used by the model. Our effort is to minimize the use of the default values and
thus to optimize the accuracy of the estimated GHG emissions.
Assessment of emissions of oil refined products imported in EU. Besides
crude oil imports, EU is increasingly importing refined oil products primarily from
Russia and United States of America. This fact is usually being overlooked in
relevant studies. In the context of this study the emissions of refined products
imported from the United States and Russia will be assessed as these
constitute significant part of EU final fuel supply.
1.4.1
JEC Report: Well-To-Tank (WTT) emissions
The present version of this report (version 4) has been published by the JEC
Consortium in July 2013 (JRC - EU Commission’s Joint Research Centre, EUCAR - the
European Council for Automotive R&D and CONCAWE - the oil companies’ European
association for environment, health and safety in refining and distribution) and replaces
the previous version (version 3c).
The current version of the study addresses the processes of producing, transporting,
manufacturing and distributing a number of fuels suitable for road transport
powertrains. Oil products and gas in the form of CNG are included also. It covers all
steps from extracting, capturing or growing the primary energy carrier to refuelling the
vehicles with the final fuel.
In this study, all fuels and primary energy sources (crude oil, coal, natural gas, shale
gas, LPG, biomass, nuclear energy, wind energy and electricity) that appear
relevant within the analysed timeframe, which broadly speaking is the next decade, i.e.
around 2020-2025, have been considered and it has been attempted to answer the
following questions:


What are the alternative uses for a given resource and how can it best be used?
What are the alternative pathways to produce a certain fuel and which of these
hold the best prospects?
The primary target of the study has been to establish the energy and greenhouse gas
(GHG) balance for the different routes. The methodology used is based on the
description of individual processes, which are discreet steps in a total pathway, and
thereby easily allows the inclusion of additional combinations, that will be regarded as
relevant in the future. The study is forward-looking and considers state-of-the-art
technology to assess and project future choices.
The average WTT GHG emissions for crude oil based fuels for Europe has been
estimated at slightly above 15 grCO2/MJ of final fuel. The processes that have been
analysed are production and conditioning at extraction source, transportation to the
market, conditioning and distribution and transformation near the market for all types of
fuels. The study concludes that crude oil refining is the most energy-consuming step
followed by crude production.
For Compressed Natural Gas (CNG) the GHG balance is estimated at approximately
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13 g CO2/MJ of final fuel for EU mix supply. CNG from imported natural gas on an
average distance of 7,000 km (typically Russia) is estimated at above 22 grCO2/MJ
final fuel, while CNG from imported NG from an average distance of 4,000 km (typically
Middle East, Caspian Sea) is estimated at approximately 16 grCO2/MJ. Emissions for
CNG coming from LNG stations vary from approximately 17 grCO2/MJ to 22 grCO2/MJ
(depending mainly on the vaporisation and liquefaction process).
Version 4.0 of the JEC WTT report is a comprehensive analysis of primary fuels
pathways and GHG balances. Even though, the high level methodology is analysed
sufficiently, the GHG emissions results are mostly aggregated and only in some cases
uncertainty is estimated (gas). Furthermore, emphasis is placed on detailed analysis of
alternative or unconventional fuels, whereas gas and oil products for transport are
rather treated in a way not relevant to their significance for the EU energy balance.
1.4.2
NETL Report: An Evaluation of the Extraction, Transport and
Refining of Imported Crude Oils and the Impact on Life Cycle
Greenhouse Gas Emissions
The National Energy Technology Laboratory (NETL) has analysed the full lifecycle
GHG emissions of transportation fuels derived from US crude oil and crude oil
imported to the US from the most significant exporting countries. The study analyses
the impact of crude oil from a WTT perspective for the following lifecycle stages:




Raw Material Acquisition (Associated Natural Gas Flaring and Venting, Bitumen
Extraction and Upgrading);
Emissions by Feedstock Source;
Raw Material Transport;
Liquid Fuels Production (refining of crude oils of different quality).
This analysis reveals that producing diesel fuel from imported crude oil results in WTT
GHG emissions that are, on average, 59% higher than diesel from domestic crude oil
(22.6 versus 14.2 grCO2eq/MJ). The study concludes that imported crude oils are on
average heavier and contain higher levels of sulphur, and the controls on venting and
flaring during crude oil production are not as good as in US operations. The study also
shows that Venezuela bitumen, Canada oil sands, and Nigerian crudes stand out as
having high GHG emissions compared to other sources.
The NETL clearly outlines the scope of the analysis and the system boundary for the
LCA. It takes into consideration the most important emission sources and excludes
from the analysis construction-related emissions and any emissions from land use
change. The analysis conforms to the International Standards Organization (ISO)
14040 and 14044 lifecycle assessment standards. Lastly, the analysis has been
conducted on a country basis, rather than crude oil type or oil field basis, which
provides a more generic assessment of crude oil type’s carbon intensity.
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1.4.3
Interim Report
ICCT Study: Upstream Emissions of Fossil Fuel Feedstocks for
Transport Fuels Consumed in the European Union
The main goal of this study prepared by the International Council for Clean
Transportation (ICCT) in collaboration with Energy Redefined (ER), Stanford University
and Defense Terre, is to define the Carbon Intensity (CI) for crude oils entering the
European Union up to the refinery gate. The analysis is based on the list of crude oil
imports published by DG ENER for 2010. Emphasis is given on the use of publicly
available data and publicly available LCA GHG assessment models.
The report begins with a thorough analysis of existing legislation and a presentation of
the sources of European crude oils. Then, it presents and compares productively the
results of several desk studies on the EU fossil fuel feedstock market and associated
empirical and modeled data on GHG emissions. Onwards, it provides information on
OPGEE, a spreadsheet model for lifecycle analysis of crude oil extraction and
transportation, developed by Stanford University and provides an estimate using that
model of the carbon intensity of crude oil supplied to the European Union. The
objective is to calculate the carbon intensity (CI) for the most important types of crude
oil entering the EU.
The analysis has been done on an oil-field basis by collecting key data for each one of
these. Each aggregated type of crude, as given in the DG ENER list, was further
correlated to oil fields contributing to each given type of crude oil entering the EU. In
total, 265 oil fields worldwide covering 93% of European oil consumption were
considered. Available data to be used as inputs in OPGEE were thoroughly analyzed
and commented within the report.
The study concludes that the biggest challenge in calculating the CI of crude oil
pathways is the collection of robust data. Given the available data, the volume
weighted average upstream emissions of crude oil arriving to European refineries were
estimated using OPGEE at 10 grCO2eq/MJ, which is lower than the CI of crude oil
consumed in California, but slightly higher than the estimations of previous studies.
This study includes one of the most comprehensive estimations for carbon intensity of
crude oil entering Europe and one of the few conducting a detailed analysis on an oil
field basis. However, it does not provide the percentage in which the oil fields
participate into the aggregated types of crude, thus being unclear on the method used
for the final calculation of carbon intensities of the aggregates.
1.4.4
ICF Study: Independent Assessment of the European
Commission’s Fuel Quality Directive’s “Conventional” Default
Value
This report has been prepared by ICF International in 2013 and analyzes the lifecycle
GHG emissions for diesel and petrol with a two-fold objective: (a) to analyze the
methodology that has been used in the last JEC reports (version v3c and version 4.0)
to determine the default conventional crude oil, gasoline and diesel carbon intensity
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values; and (b) building on that knowledge, to develop a more accurate carbon
intensity range for gasoline and diesel from conventional crude oils, using the OPGEE
model.
The study elaborates a lifecycle analysis from “well-to-tank” (WTT) perspective taking
into consideration the most important emissions sources during crude oil extraction and
production, venting, flaring, and fugitives, crude oil transport and refining. It gives
specific emphasis on data quality and availability since these are two of the most
important factors in LCA estimations. The study also points out the lack of reliable
reported data for crude oils outside Canada and the USA. In order to mitigate this, ICF
uses literature data that by definition introduce some bias in the analyses.
The study estimated as the most likely range of crude oil GHG intensity from
production processes using the OPGEE model at 2.0–5.9 grCO2eq/MJ and from VFF
(Venting, Flaring, Fugitive) releases at 3.8–11.0 grCO2eq/MJ.
The ICF study builds on existing LCA methodologies and conducts a comprehensive
literature review of existing studies. Unlike other studies which mainly analyze GHG
emissions on a regional or country basis, ICF uses the concept of MCON introduced by
California Air Resources Board (CARB), while the analysis of GHG emission intensity
per MCON is done via representative oil fields. Nonetheless, the coverage of specific
crude oils imported in Europe is limited. Furthermore, the number of representative oil
fields analyzed in order to assess carbon intensity of specific crude oil types remains
limited. Furthermore, there is no analysis for specific MCONs that constitute significant
part of European crude oil imports, such as Urals crude oil. Lastly, the rationale and
methodology for the choice of the specific dataset of MCONs and oil fields remains
unclear.
1.4.5
Jacobs Consultancy Report: EU Pathway Study: Life Cycle
Assessment of Crude Oils in a European Context
Jacobs Consultancy in collaboration with Life Cycle Associates was assigned in 20112012 by the Alberta Petroleum Marketing Commission, to carry out a study concerning
the lifecycle GHG emissions for crude oil pathways to Europe.
The goal of this Study was twofold: (i) to evaluate the lifecycle GHG emissions for
potential crude oil pathways to Europe for producing gasoline and diesel from
representative heavy crude oils from Alberta, Canada and (ii) to evaluate the lifecycle
GHG emissions of representative crude oils refined in representative refineries. This
approach should help achieve a better understanding of the variability in GHG
emissions for different pathways for producing gasoline and diesel for the EU market.
The intent of this work was to better understand the carbon intensity of pathways for
gasoline and diesel from particular individual crude oils. The approach of
representative pathways went beyond calculating carbon intensities from average
crude oils in an average European refinery, as such an approach would entail the
risk of losing the information that defines the range of carbon intensities for gasoline
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and diesel from different crude oils produced in different regions and refined in different
refineries.
Thus, the authors chose to rather select representative crude oils ranging from light to
heavy from the major supply regions for the purpose of their study. Therefore their
study does not cover all crude oils imported in Europe, but only the ones treated in
three representative refineries, namely:



FCC-Coking refinery – situated in Germany;
FCC-Visbreaking refinery – situated in France;
Hydrocracking-Visbreaking refinery – situated in Italy.
The results were compared to the GHG emissions from a US and a Russian refinery
exporting refined products to Europe, in order to point out that the location of the
refinery affects the lifecycle emissions.
The study concludes that Well to Tank (WTT) carbon intensities vary widely, depending
on how the crude is produced, the amount of gas flaring, the amount of fugitive
emissions released during production, and the emissions from oil refining, Also, the
limited availability of robust data is discussed, as well as the uncertainty in the
calculation due to this unavailability, especially in the production processes. The study
provides also a valuable assessment of the emissions of the refining sector depending
on the physical properties (API and sulphur content) of crude oil, the refinery
configuration the exact input blend of the refinery and the refinery final product (diesel
kerosene, petrol, etc.).
The average carbon intensity of diesel fuel produced from representative crude oils
refined in representative European refineries has been found to be in the order of 15
grCO2eq/MJ and around 18 grCO2eq/MJ respectively for the produced petrol.
1.4.6
ICF Study: Desk Study on Indirect GHG Emissions from Fossil
Fuels
The study was assigned by DG CLIMA to ICF international and was carried out in
2013. The overall objective is to provide an overview that enables the European
Commission to evaluate the indirect GHG emissions from fossil transport fuel
pathways.
Direct emissions are defined as the ones emitted from the processes of production,
transport and combustion of the fuel along its lifecycle, whereas the indirect emissions
are those that are influenced or induced by economic, geopolitical or behavioral
factors, but which are not directly related to extraction, processing, distribution or final
combustion of the fuels.
The study identifies and evaluates six possible sources of indirect GHG emissions from
fossil fuels:

Induced land development;
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




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Military involvement;
Accidents;
Marginal effect;
Price effects;
Export of co-products.
The study has been based on a thorough literature review in the field of indirect
emissions. Where possible, estimates on the emissions are provided. The report
concludes that there is no common characterization of direct and indirect sources of
GHG emissions between relevant stakeholders and those comprehensive
methodologies to calculate indirect emissions are still to be developed. Among the
above listed sources of emissions, only the emissions due to accidents are considered
as negligible, whereas the market mediated effects (i.e. prices effects and export of coproducts to other markets) appear to be the most important source, representing 2.2%
– 4.5% of the whole WTW GHG emissions.
The study is an important source for analyzing and estimating indirect emissions and
also provides the basis for defining the boundaries between direct and indirect GHG
emissions sources in the current project.
1.4.7
NETL: Life Cycle Greenhouse Gas Inventory of Natural Gas
Extraction, Delivery and Electricity Production
The main objective of the study is to present the methodology used by the National
Energy Technology Laboratory (NETL) of the U.S. Department of Energy to analyze
and create an inventory of GHG emissions related to natural gas lifecycle, including
extraction, transport and use of gas in the U.S. The inventory focuses on the “cradle-togate” value chain, i.e. the lifecycle up to the power station gate, therefore it is
considered as an upstream inventory in principle. The study utilizes data from 2009.
The report analyzes the upstream emissions of natural gas compared to those of coal
and concludes that despite the fact that natural gas combustion emits less greenhouse
gases than coal combustion, nevertheless the GHG emissions related to its production
and transport to the U.S. power plants are higher than those of coal. This conclusion is
probably related to the sources of natural gas consumed within the U.S. which are, at
their majority unconventional (56% unconventional sources of natural gas according to
the present report).
The overall emissions of the U.S. natural gas lifecycle including combustion are lower
than those of coal. However, the extraction and delivery of the gas has a large climate
impact 32 % of U.S. methane emissions and 3 percent of U.S. greenhouse gases. The
vast majority of the GHG emissions in extracted natural gas - 70 % of the total cradleto-gate emissions can be attributed to the use of the natural gas as fuel for extraction
and transport processes such as compressor operations.
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Interim Report
OGP Report: Environmental Performance Indicators - 2012 Data
The International Association of Oil & Gas Producers (OGP) has been collecting
environmental data from its member companies for the last 14 years on an annual
basis. These data are divided into the following categories, which follow the guidelines
provided within the “Oil and gas industry guidance on voluntary sustainability reporting”
by IPIECA/API/OGP:






Gaseous emissions;
Energy consumption;
Flaring;
Aqueous discharges;
Non-aqueous drilling fluids retained on cuttings discharged to sea;
Spills of oil and chemicals.
This report summarises the above listed environmental information on activities related
to exploration and production (upstream) carried out by OGP member companies in
2012. Data coverage is relatively low - 32% of 2012 world production - while regional
coverage varies from 96% in Europe to 8% in Former Soviet Union. Overall, data from
43 OGP member companies, representing upstream activities in 78 countries, are
presented in the report.
The results provided within this report are aggregated following confidential information
provided by member companies to OGP and no specific data by company or by field
are given.
1.4.9
Upstream greenhouse gas (GHG) emissions from Canadian oil
sands as a feedstock for European refineries
The study was carried out in 2010-2011 by Adam R. Brandt from Stanford University.
The issues the report focused on were the following:
a) to provide an overview and description of oil sands extraction, upgrading,
Synthetic Crude Oil (SCO) and bitumen, non-combustion process emissions
and land use change associated emissions;
b) to compare a variety of recent estimates of GHG emissions from oil sands and
to outline the reasons for variations between the estimates in surface mining, in
situ production, upgrading, refining and VFF;
c) to outline low, high and “most likely” estimates of GHG emissions from oil
sands, given results from previously produced estimates, and compare these
emissions to those of conventional EU refinery feedstock.
The author used EU-specific emission factors for transport and refining of fuels. The
study concludes that, while oil sands based crude oil is endorsed with higher emissions
than conventional crude oil, the production-weighted emission profiles are significantly
different and therefore, the regulatory frameworks should address this discrepancy with
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pathway-specific emissions factors that distinguish between oil sands and conventional
oil processes.
Closing, the author suggests the need for additional research of the uncertainties in
modelling GHG emissions from the Canadian oil sands. The most important
uncertainties mentioned are treatment of cogenerated electric power, treatment of
refining and the interaction of markets with LCA results.
1.5
PROGRESS ACHIEVED TILL OCTOBER 2014
The time schedule of the project Tasks as they have been set in the proposal is
presented in Figure 1.2. The time schedules of the Tasks are drawn with blue colour,
whereas the progress of Tasks is drawn with brown colour. In principle, project
execution until the delivery of this Report is focused on 4 Tasks, namely Tasks a, b, c
and d (and 0). The work in Task f has also been initiated, but it is not reported in detail
in this Interim Report.
Tasks/Months
(after
signature)
May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul
Task 0 Project
Management
Task a
Task b
Task c
Task d
Task e
Task f
Meetings and
deliverables
Kick-off
meeting
Draft Interim
report
Interim
Steering
group meeting
Interim report
X
X
X
X
Draft final
report
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Tasks/Months
(after
signature)
Interim Report
May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul
Final Steering
group meeting
X
Final report
X
Scheduled Tasks
Executed Tasks
Figure 1.2: Time schedule of project Tasks as in the proposal
The work in Task a: Literature survey has been carried out in time; thus the database
development and its enrichment with the main reports have been carried out. However,
the addition of necessary literature will continue until the end of the project as far as
new literature is produced and becomes available. It should be considered that this
Task has been completed.
The work in Task b: Data acquisition has lasted more time than expected, but it may
be stated that the main bulk of required information has been collected and it is
available to feed the models (Task c). The reason of longer time requirement could be
attributed to the difficulty to collect actual data, which might be either used directly or
will be the main input in the models for GHG estimations. It is worth mentioning that
great effort was dedicated to receive data from the involved private companies,
however the results were very poor till now. We continue to be in communication with
some of the organizations which might provide with actual data and hope this effort will
be fruitful at the end. Nevertheless, although the largest part of information has been
collected, we consider that improvements, additions and further elaborations of
collected information might be needed until the end of the GHG modelling Task c and
even until the end of the project. We may consider that this Task has been finished,
given the expressed need for necessary small amendments as far as the modelling
Task c develops.
The work in Task c: Models to estimate max and min GHG emissions has started
on time and is well developed. The two models under consideration, namely OPGEE
for oil and GHGenius for natural gas, have been thoroughly assessed and have been
modified to adapt to the specific needs of this project. More specifically, the
significance of the inserted parameters has been evaluated and the research of data
collection has been directed to ensure the proper calculation and assessment of these
parameters. Task c is carried out in parallel to Task b and this link and close
coordination is prerequisite in order to produce reliable and consistent results. Initial
and testing runs of both models have been already carried out and some initial outputs
are included in this report and willll be further developed to be presented in the
scheduled workshop. This Task is expected to produce final results by the end of
February 2014, as it was scheduled in the proposal.
The work in Task d: Emissions due to accidents and other operational failures has
started according to the schedule and is well developed as it is reported in the relevant
Chapter of this report. The approach and definition of the indirect emission cases have
been decided and analysed, the relevant literature and data collection have been
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carried out and preliminary results have been assessed for further verification and
comparison. It is estimated that this Task will be finished by the end of November as it
was initially scheduled.
As already mentioned Task f: Emissions projections up to 2030 has been initiated a
little earlier than scheduled in the proposal because the use of certain modules of
PRIMES (refining) are under development to incorporate the recent changes in the
sector and data of the gas module will be used to better detail gas transmission and
distribution activities within the EU countries.
Finally Task e: Other issues related to sustainability has not been elaborated till
now.
With regard to the other deliverables of the project, it is worth mentioning that the
schedule and the scope have been followed:



The kick-off meeting has been organized at the beginning of June, when all the
Tasks and the Consultant’s approach have been discussed with the EC desk
officer.
An additional half-day workshop has been organized in the premises of DG
ENER with main objective to coordinate efforts of the Consultant to receive
useful information from the EC services.
An interim workshop for presentation of the work carried out to experts from
main counterparts was organized on November 28 in Brussels at the premises
of DG ENER.
1.5.1
Key dates of project evolution
Until the time of submission of the Interim Report, that is end of October, the proposed
schedule of project Tasks has been followed. Our estimation is that we will continue
keeping the schedule until the end of the project. The key dates and next steps
onwards are expected to be:






November 28, 2014, presentation of project progress in interim workshop
organized in DG ENER.
End of November 2014, finalization of Task d on indirect emmissions.
End of February 2015, completion of main OPGEE and GHGenius model runs
(Task c).
End of April 2015, completion of runs of PRIMES model on 2020-2030
projections (Task f).
End of June 2015, completion of sustainability analyses (Task e).
End of July 2015, submission of the Final Report.
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2
Interim Report
TASK A: LITERATURE SURVEY
The literature survey was the initiating Task of the project and focused on identifying
and reviewing up-to-date documents publicized worldwide regarding life-cycle GHG
gas emissions of transport fuels.
The literature survey considered a number of subjects, including:



Important legal documents in the framework of the present project regarding the
Renewable Energy Directive (RED), which sets a target of 10% renewables in
the transport sector, the Fuel Quality Directive (FQD), which sets a target of 6%
reduction of GHG emissions from road transport, as well as relevant EC
Communications and initiatives which set the basis of the EU GHG emissions
policy.
A broad range of subjects related to lifecycle GHG emissions of diesel oil,
petrol, kerosene and natural gas. The subjects included regard GHG emissions
calculation methods, fuel extraction, fuel transport, fuel refinement, etc.
Broad range of information resources broken down by type, including private
companies reports, international organisations reviews, scientific papers, etc.
The literature survey focused on the most up-to-date data and knowledge on the
subject of life-cycle GHG emissions and was based on two methods: extensive on-line
literature search, as well as the identification of important relevant information sources
through communication with stakeholders i.e. oil and natural gas companies and
international organizations. The Consultant set the criteria which allowed the
classification of the various documents and the establishment of a tailor made literature
electronic database.
2.1
SURVEY APPROACH
A large number of documents could be in principle considered in the literature survey
related to oil and gas and the respective transportation fuels. It was considered
however that a more efficient and targeted approach would be required focusing on
documentation whose content is closely related to the subjects addressed by the
current study and considering as well their reliability and their significance on the
project topics for the potential future reader or researcher. The survey work focused on
collection of literature selected in accordance with criteria relating to the content and
the type of these documents.
Documents focusing on the following content topics were surveyed:

GHG emissions (direct/indirect) for oil and natural gas: The exact distinction
between direct and indirect emissions is related to the choice of the system
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boundaries. In general, direct emissions are related to the processes of
production, transport and combustion of the fuel along its life-cycle, while
indirect emissions are related to economic, geopolitical or behavioural factors
not directly related to the aforementioned processes.
Policies related to transportation fuels and GHG emissions: Documents
referring to policy and strategy aspects of GHG emissions and emission
reduction options.
Modelling and methodological aspects of Life-cycle Analysis (LCA) of
GHG emissions: Such documents include information regarding models used
widely for the estimation of GHG emissions such as OPGEE, GHGenius and
GREET or other aspects related to modelling specific aspects of the fuel life
cycle.
Conventional and unconventional oil and natural gas pathways,
processes and technologies: These type of documents describe engineering
and technological aspects of oil and natural gas production and extraction that
will help the reader understand sources of various types of emissions.



Furthermore, literature of the following types was surveyed:







Reports and studies: This is the main type of literature source utilized for the
elaboration of the project Tasks. It includes studies from international
organizations, national authorities, research institutes, consulting firms and oil
and gas companies, which provide comprehensive and up-to-date analyses of
life cycle GHG emissions of transportation fuels.
Books: Textbooks as literature sources providing fundamental technical
background for oil and gas exploration, production and transportation.
Research papers: Refers to papers published by universities and research
institutes and provide a valuable input for the project, particularly when related
to fundamental concepts for the assessment of carbon intensity of fossil fuels.
User manuals: Refers to the supporting documentation for the use of life-cycle
emission’s assessment and macroeconomic models (OPGEE, GHGenius,
GREET, PRIMES etc.) and are particularly useful for introducing these models
to the reader and for analysing methodological aspects of GHG emission’s
assessment.
Datasheets: Refers to data sets published by international organizations or
private entities (such as oil and gas companies) that provide input regarding
crude oil specifications, crude oil and natural gas production, transport and
refining data, overall emissions from their activities.
Presentations: Refers to presentations given by individual experts or
organizations which are a useful literature source, despite the fact that they may
not provide an in-depth analysis on specific issues. However, they can provide
a comprehensive overview of extensive studies and a compact summary of key
issues and results.
Legislation: It refers to documents such as relevant European Directives,
Regulations and Communications.
The literature survey was carried out during the first months of the project period
resulting the selection of a large number of documents on the basis of content as
mentioned above. It is planned that more literature will be added until the end of the
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project, as the project team will be collecting and registering additional documents in
the course of carrying out the other project Tasks.
In order to store the identified literature and to provide access to all project partners
and EC officials, an online literature database was created. The database will remain
active and will be updated throughout the duration of the project so as to include all the
necessary documentation that was utilized for the needs of the forthcoming Tasks of
the study. Currently the literature database includes references to more than 60
documents.
An updated list of the literature stored in the database, including all information
attached to each document is presented in Annex 8.3.
2.2
PRESENTATION OF LITERATURE DATABASE
The literature database is a tool developed for the needs of the project in order to store
and classify the documentation surveyed and provide a common document repository
accessible by all project partners and EU officials. It is a user-friendly web-based
platform designed specifically for use in the course of this project, providing reference
and information on the collected documents.
The database is available on-line at the web address http://ghg-oilgas-literature.eu.
Documents are added to the database along with certain “data fields” providing specific
additional information on each document. These fields can be used for sorting and
classifying the database documents according to a predefined order depending on the
content, thus facilitating the user in selecting specific document references for review.
For each document in the database, the following information is provided








Literature fields (Publisher, Author(s), date of publication);
Document type (Report, Research paper, Legislation, Datasheet, etc);
Content (Policy, Modelling, etc);
Lifecycle stage (the specific stage of the lifecycle of transport fuels the
document refers to - if applicable);
Geographical coverage (the geographic areas the document provides
information on);
Referenced model (the GHG emissions model the document refers to (if
applicable);
Key points i.e. a short review of the information provided within the document
and its relevance for the study;
Web link i.e. the internet location where the document can be found (if
applicable).
A snapshot of the literature database in presented in the following Figure 2.1 while
Annex 8.3 presents the complete list of documents and related information which is
currently stored in the literature database and the generic database.
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Figure 2.1: Snapshot of the literature database.
The Consultant has added a section under the name “generic literature database”
which includes documents of general interest i.e. handbooks, glossaries, general
environmental reports for GHG emissions and other relevant studies. These literature
sources are not vital for the elaboration of the study but include useful background
information for the potential reader.
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TASK B: DATA ACQUISITION
3
EU OIL AND GAS SUPPLY
3.1
3.1.1
EU crude oil supply
Europe is largely dependent on Former Soviet Union for its primary energy supply in
crude oil - approximately 40% - as it can be obtained by Figure 3.1. Europe produces
approximately 20% of its domestic consumption, while another 20% is approximately
being supplied from countries of the Middle East.
100%
90%
80%
70%
America
60%
Europe
50%
FSU
40%
Africa
30%
Middle East
20%
10%
0%
2013
2012
2011
2010
Figure 3.1: EU crude oil supply 2010 - 2014 (source: DG ENER)
Figure 3.2. illustrates the EU 28 crude oil supply by country of origin for 2012.
Currently, Russia is steadily the largest exporter of oil to Europe, exporting crude oil to
Europe from the areas of Urals-Volga, Western Siberia and Timan-Pechora under
several marketable names (Urals, Western Siberia and Russian Export Blend, also
known as REBCO). The second largest supplier of crude oil to Europe is Norway with
approximately 11% of total imports. Europe is also supplied significant quantities of
Arabian light and heavy crudes, as well as light and medium crude oils from Nigeria.
Apart from the Russian crude oil, Europe is supplied large quantities of crude oil from
other FSU countries, primarily Azerbaijan (Azeri light and Azeri BTC) and Kazakhstan
(Tengiz and CPC blend).
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Other
Venezuela
Kuwait
Egypt
Colombia
Mexico
Other African Countries
Angola
Other European countries
Iraq
Algeria
Azerbaijan
Libyan Arab Jamahiriya
Kazakhstan
Nigeria
Saudi Arabia
Norway
Russian Federation
Interim Report
2.84%
0.91%
0.98%
0.98%
1.01%
1.80%
2.19%
2.81%
3.05%
3.41%
4.11%
4.27%
5.71%
5.91%
8.31%
9.07%
10.92%
31.72%
0.00 %
5.00 %
10.00 %
15.00 %
20.00 %
25.00 %
30.00 %
35.00 %
Figure 3.2: EU crude oil by country in 2012 (source: DG ENER)
The largest part of Russian oil towards Europe is exported through the Transneft
pipeline system. The Transneft pipeline system spans over 31,000 miles in total and
reaches to the ports of Novorossiysk and Primorsk from which major crude oil exports
take place.. The Druzhba pipeline system trasnports the largest part of Russian oil to
Europe. Figure 3.3 provides the Russian crude oil exports of the years 2010 and 2011
via various modes of transport.
3
2.5
2
1.5
2010
2011
1
0.5
0
Ports
China
Druzhba
CPC
Railroad
exports
Exports
bypassing
Transneft
Figure 3.3: Russian crude oil exports in million b/d (source: CDU-TEK)
From the crude oil transported via the Druzhba pipeline Germany imports the largest
fragment with 0.45 million b/d and Poland comes next with 0.4 million b/d in the first
quarter of 2011, as it is shown in Figure 3.4. Hungary, Slovakia, Czech Republic
receive a smaller fragment of crude via the pipeline at the order of magnitude of 0.1
million b/d.
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Bosnia and
Herzegovina;
0.02
Czech
Republic;
0,10
Slovakia;
0.07
Germany; 0.45
Hungary; 0.12
Poland; 0.40
Figure 3.4: Transneft’s Druzhba deliveries plan for 1st Quarter of 2011 in million
b/d excluding transit (source: Transneft)
3.1.2
Supply of refined products from third countries
Besides crude oil imports, Europe is increasingly importing refined oil products
primarily from Russia and United States of America, as it can be seen in Table 3.1:
Daily imports
(1.000 barrels)
Annual imports
(1.000 barrels)
Imports from FSU 2013
559
204,035
Imports from FSU 2014 (until May 22)
629
229,585
Imports from US 2013
321
117,165
Imports from US 2014 (until May 22)
304
110,960
Total FSU+US imports 2013
880
321,200
Total FSU+US imports 2014 (projection)
933
340,545
Source and Year
Table 3.1: Imports of refined products by FSU and USA (source: Bloomberg)
The increase of refining output and quality of refined products in Russia over the last
years has been the result of recent regulatory reforms. Russia has adopted the
European fuel quality standards, both for imported and domestically manufactured
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ones, for road transport vehicles. As of January 2013, Russia switched to Euro-3
standards, which caps sulphur content at 350 ppm (diesel oil) and 150 ppm (petrol)
sulphur required. Euro-4 fuel standard will be implemented beginning 1 January 2015
(with max 50 ppm sulphur required), while Euro 5 fuel (with max 10 ppm sulphur
required beginning) as of 1 January 2016. These regulations have led Russian oil
companies to make investments in order to upgrade their refineries so as to produce
cleaner products, primarily Ultra Low Sulphur Diesel (ULSD). This has resulted into an
increased share of Russian refiners in the EU market at the expense of their European
competitors. Figure 3.5 illustrates that the ULSD is the major refined oil export product
to OECD EU and that the OGJ forecast anticipates increase for OECD EU diesel
imports; thus it can be considered that domestic EU diesel production is anticipated to
decline until 2020, with this gap between production and demand to be covered by
diesel imports from USA and FSU.
Figure 3.5: Russian diesel export forecast 2014 – 2020 and OECD Europe diesel
supply forecast 2014-2020 (source: OGJ, based on ESAI Energy
study)
The increased diesel production to Europe will be supported by expansions of the
Sever pipeline. More specifically, the operator of the pipeline, Transneft, has planned
two expansion projects of the pipeline. With a nominal capacity of 170,000 b/d to
facilitate ULSD exports from the Baltic Sea, the pipeline already operates above the
nominal capacity. In late 2013, the average diesel exports were 200,000 b/d, which
rose to a record of 235,000 b/d in January 2014. This implies that approximately half of
the refined products imported from Russia are transported to Europe via the Sever
pipeline.
United States exported 13.37 million tons (about 273,000 b/d) to Europe, or 42% of the
32.2 million tons (about 658,000 b/d) that was imported into the region in 2013
(Eurostat). The Netherlands with 576,000 tons of all ULSD imported into Europe is the
major importer, followed by France with 310,000 tons, the country with
Europe's biggest diesel deficit.
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EU natural gas supply
Unlike oil supply in the EU, which is almost exclusively dependent on imports from third
countries, natural gas supply is ensured by domestic production combined with imports
by non EU countries. In 2012, 66% of total natural gas demand in the EU was met by
imported gas, up from 45% in 1990. This growing dependence is caused in a large
extent by two factors: increasing demand for natural gas, as the cleanest and most
versatile fossil fuel, and decreasing domestic production for domestic use within the
EU. The large gas fields, which produce at relatively low cost, are becoming depleted,
while smaller and offshore gas fields are more expensive to exploit.
Dependence on natural gas imports varies widely among individual EU Member States.
Imports to the United Kingdom and Romania are relatively low, while Denmark and the
Netherlands are net exporters. On the other hand, six countries (Finland, Latvia,
Lithuania, Estonia, Slovakia and Bulgaria) are fully dependent on imports from Russia.
The most important suppliers of the EU natural gas market are Russia (23.24% of total
EU supply), Norway (21.45% of total EU supply - pipeline and LNG combined), the
Netherlands (17.55% of total EU supply), the UK (8.46% of total EU supply) and
Algeria (9.14% of total EU supply – pipeline and LNG combined). These five countries
provided almost 80% of the EU gas supply in 2012.
100000
90000
80000
70000
60000
50000
40000
30000
20000
10000
BG
EL
HR
IT
RO
SI
BE
CZ
DE
EE
LV
LT
LU
HU
NL
AT
PL
SK
DK
IE
FI
SE
UK
ES
FR
PT
0
EU Natural Gas Imports
EU Natural Gas production
EU Natural Gas Consumption
Figure 3.6: EU Natural Gas Imports, Production and Consumption in million
cubic meters for 2012.
As shown in the graph in Figure 3.6 the most important producers of natural gas in the
EU are the Netherlands, the UK and Germany. Italy, Romania, Poland and Hungary
consume almost the entire quantities of natural gas produced within their territory. The
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Netherlands, on the other hand, is a major exporter of natural gas, not only to the EU,
but also to third countries.
Figure 3.7: EU natural gas supply by country of origin, 2012 (source: IEA)
Figure 3.7 illustrates the countries supplying natural gas to EU and the corresponding
share for 2012.
Gas is imported into Europe by two ways: through pipeline in gaseous form or
alternatively by LNG supply chain, where it is liquefied in the country of origin,
transported in marine vessels and finally regassified at the entry points in Europe.
There are two major LNG suppliers to Europe, although smaller quantities may arrive
from other countries i.e. Algeria and Qatar. Algeria is also connected to the European
gas transmission system by pipeline through Spain and Italy. The EU countries
receiving the largest quantities of LNG are Spain, France, Italy and Germany. Overall,
the share of LNG in the European gas market is presented in Table 3.2.
EU NG supply mode
Quantity (million cubic meters - mmcm)
Percentage
Pipeline
430,682
89.3%
LNG
516,49
10.7%
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Table 3.2: EU natural gas supply share by mode of transport
The physical flows of natural gas within EU (blue lines) and the major importing
pipelines transporting gas to EU (red lines) are illustrated in the IEA map of
Figure 3.8:
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Figure 3.8: Gas trade flows in Europe (source: IEA)
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GENERAL METHODOLOGICAL CONSIDERATIONS FOR GHG LIFE
CYCLE EMISSION ASSESSMENT
3.2
3.2.1
Fuels examined
The overall aim of the assignment is to provide the actual, as possible, GHG emissions
of petrol, diesel, kerosene and natural gas through a lifecycle “well-to-tank” approach.
In this context, the Consultant assesses the upstream, midstream and downstream
emissions for existing pathways of crude oil and natural gas. Furthermore, the
Consultant develops a specific methodology for the assessment of LCA emissions for a
basket of the most significant grades of unconventional crude oil and natural gas that
will be imported and/or produced in Europe in the forthcoming years.
3.2.2
Categorization of data collection
Generally a GHG emissions inventory of actual data is comprised of calculated and
estimated emissions from individual emission sources that are aggregated to produce
the inventory. Emissions information is typically obtained either through direct on-site
measurement of emissions, or the combination of an emission factor and some
measure of the activity that results in the emission which is referred to as the activity
factor. Emission factors describe the emission rate associated with a given emission
source, which may be either based on site-specific measurements or published data.
Activity factors are generally a measured quantity, such as a count of equipment or
amount of fuel consumed.
According to ISO14041, data quality requirements should be specified. The
requirements should concern time, geographical and technical coverage of the data. To
meet those requirements, one may collect adequate data in several ways. Especially in
this project the collected data have been classified according to the source of origin
that implies also the level of reliability. A three stage hierarchy of data collection with
highest priority of course placed on the Actual Data has been considered, as it is the
mandate of this project:


Actual Data gathered from existing data bases of renown national and
international organizations as well from certified data availed by oil and gas
companies. These data are in principle based on direct measurements, mass
balances, validated emission factors and relevant engineering calculations
which have been verified.
Modelling data, calculated from runs of the three models used in this project,
namely OPGEE, GHGenius and PRIMES. These data are actually covering the
cases where actual data are not available or there is lack of them. In order to run
these models a large number of input data are required and have been
collected. These latter data are in principle actual data.
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
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Literature data, coming from other studies in GHG emissions for which the
Consultant has no access on the detailed way these estimations have been
carried out. This latter stage will be used only in cases where the previous two
stages fail to provide reliable results and hopefully its contribution in the project
output will be negligible.
Therefore the Consultant has collected actual emission data both for oil and natural
gas in priority i.e. data verified through measurements and calculations as those are
provided by energy companies or authorities related to GHG emissions. In order to do
so, the Consultant has investigated all open sources of relevant information, mainly
availed by national, international organizations and oil and gas associations.
Furthermore, all major oil and natural gas companies related to oil and gas streams
directed to the EU have been contacted and requested specific and disaggregated data
per process. Another source of actual data have been reports published by oil and
natural gas companies, which typically include aggregated data, with limited usefulness
for our analyses and comparative purposes.
The procedure and the priorities in GHG data collection that has been explained above
is presented in Figure 3.9:
Figure 3.9: Overview of the strategy for the assessment of GHG emissions for
crude oil and natural gas
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3.2.3
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Geographical coverage
The study examines the GHG emissions of petrol, diesel oil, kerosene and natural gas
in the form of CNG or small scale LNG used in the transportation sector of EU 28
countries. It must be noted that at the time the ToR was written Croatia was not a full
MS. Thus, the country coverage has been extended to include Croatia also.
3.2.4
Choice of baseline year
The baseline year for the assessment of carbon intensity has been chosen to be 2012,
primarily because there is a large availability of data for this year regarding all lifecycle
stages of the oil value chain, namely upstream, midstream and downstream.
3.2.5
System boundaries
In general, “well-to-tank” emissions refer to those associated with exploration,
production, fuel recovery, upgrading, pipeline and maritime transportation, refining,
LNG transformation, gas transmission and storage, CNG compression and distribution
to final consumers, thus excluding the emissions resulting from the final combustion in
the transportation means’ engines.
3.2.6
Global Warming Potential (GWP) used
The latest versions of OPGEE (1.1c) and GHGenius (4.03a) use the GWP of 2007, as
most of the recent LCA studies. Therefore, it has been considered as preferable option
to utilize the GWP 2007 instead of the 2013 GWP in order to ensure consistency of
figures and allow comparisons between various studies.
3.2.7
Utilization of Minimum/Maximum approach
The study aims to develop an integrated, consistent and detailed methodology to
evaluate the actual range of emissions in the form of minimum, weighted average and
maximum values that relate to the whole lifecycle of diesel oil, petrol, kerosene and
natural gas. Unlike other relevant studies, which provide one single value regarding
GHG emissions per field or fuel type, the present study through the utilization of a
minimum/maximum approach allows various uncertainties to be better expressed and
consequently policymakers to better understand the range of GHG emissions of each
oil and gas stream and final fuel, as these are evaluated in a more realistic and
objective manner.
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The potential range in the value of GHG emissions of each oil and gas pathway can be
influenced by the following parameters, as also by other ones:
A. Upstream



Different fields constituting the source of each pathway (MCON or Gas stream).
Variable quantities of oil or gas production for a specific field.
Differences in oil field characteristics (particularly API gravity and depth), as
also in the natural gas characteristics contributing to a pathway of oil or gas.
B. Midstream



Mode of transport for a specific oil or gas pathway (marine/pipeline).
Different final destinations of crude oil or gas per mode of transport.
Uncertainties related to the exact properties of a crude pipeline blend.
C. Downstream



Exact constitution of a crude oil blend for the refining process.
Estimations of emissions for the oil and gas distribution systems within a
country.
Estimations of crude yields on specific products during the refining process.
3.3
3.3.1
METHODOLOGICAL APPROACH FOR OIL
Introduction
The methodology for the assessment of GHG emissions of crude oil has been adapted
to the three main stages of oil handling chain: upstream, midstream and downstream.
Figure 3.10 illustrates the main stages of crude oil handling chain and indicates at high
level the general pathways followed in the assessment of each oil grade. In the
following sections more detailed presentations of these pathways will be explained. It is
worth considering that 35 crude oil pathways in the upstream and midstream stages
will be considered covering approximately 88% of the crude oil imports in the EU in
2012. Finally 105 streams (35 for each one of diesel oil, petrol, kerosene) of oil
products are considered in the downstream stage up to the tank of transport means.
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Figure 3.10: Physical flow of crude oil illustrating the basic stages that are
examined by the study
The nine methodological steps for the calculation of the Carbon Intensities (CI) or GHG
emissions in the three stages for each oil pathway are illustrated in Figure 3.11.
Essentially four components of CI are distinguished in each oil pathway and the
relevant calculation or data collection effort will be directed accordingly. In the following
Sections of this Chapter each stage and the relevant approach of the Consultant is
thoroughly analyzed.
Figure 3.11: Main steps for the assessment of GHG emissions of gasoline, diesel
and kerosene
Oil trading fundamentals
Oil is a very particular commodity since it is simultaneously a financial asset, but also
has a physical dimension. Therefore, the pricing of crude oil in the financial markets is
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inevitably related to its physical characteristics, production techniques, transportation
and storage patterns. The complexity in the pricing of crude oil is related to the various
types of internationally traded crude oil with different qualities and characteristics which
have a bearing on refining yields. Therefore, different crude oils have different prices.
The adoption of the market-related pricing system by many oil exporters in 1986-1988
constituted a shift from a system in which prices were first administered by the large
multinational oil companies in the 1950s and 1960s and then by OPEC for the period
1973-1988 to a market base system. In the current system, the prices of these crudes
are usually set at a discount or a premium to a benchmark price of a crude oil
according to their quality and their relative supply and demand balance. The main
benchmarks currently used are: Brent, West Texas Intermediate (WTI) and DubaiOman.
Other reference benchmark is the OPEC reference basket, which is the weighted
average of the following blends of oil:












Saharan Blend (Algeria)
Ecuador
Iran Heavy (Islamic Republic of Iran)
Basra Light (Iraq)
Kuwait Export (Kuwait)
Es Sider (Libya)
Bonny Light (Nigeria)
Qatar Marine (Qatar)
Arab Light (Saudi Arabia)
Murban (UAE)
BCF 17 (Venezuela)
Girassol (Angola)
Other significant reference crude oils include Tapis crude oil, which is traded in
Singapore, Urals oil used in Russia and Mexico's Isthmus. Figure 3.12 presents the
extent of oil benchmarks used worldwide.
Figure 3.12: Crude oil benchmarks used worldwide (source: ICE)
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The names of the above mentioned crude oils indicate their origin but also and most
particularly their commercial recognition in the oil markets. These names are used in
the marketing of crude oils and are generally understood as Marketable Crude Oil
Names (MCONs).
Marketable Crude Oil Name
One of the novelties of the study is the utilization of the concept of Marketable Crude
Oil Name (MCON) in order to correlate the physical properties characterizing crude oil
as it is extracted from the oil field and those of the crude oil blended during or before
the refining process. Furthermore, the concept of MCON facilitates practically the
connection of the refinery input (which has a marketable name) with the primary source
of crude oil (at the oil field).
More specifically, the concept of MCON has been introduced by the California Air
Resources Board (CARB) in order to match the marketable crude oil names to their
respective field sources. The ultimate purpose of this classification is to systematize the
various types of crude oils in order to identify High-Carbon Intensity Crude Oils
(HCICOs) at a second stage and implement regulatory barriers on polluting crudes
imported in the State of California. The initial crude oils of the list have been provided
to the Air Resources Board by the Western State Petroleum Association (WSPA) and
augmented with other proprietary information resources:




International Crude Oil Handbook (ICOM)
Energy Information Administration list of crude oil names (EIA‐856)
Journal of Commerce – Petroleum Import Exports Reporting System
Crude Information Management System from PetroTech Intel
For the crude oils selected in the CARB list a sequential procedure to assign “pass” or
“fail” according to LCA GHG emissions is implemented based on:




Flaring intensity
Thermally enhanced oil recovery (TEOR)
Mining extraction of bitumen
Use of upgrading facilities to produce synthetic crude oils
Currently, CARB has identified over 250 MCONs globally, while the list is often
reviewed. MCON characteristics are constantly changing due to large number of oil
fields, oil fields relative contribution in the MCON, depletion of oil fields, and emergence
of new exploration and development effort. Figure 3.13 below illustrates the most
important crudes.
In the Proposal for a Council Directive (COM(6.10.2014) 617 final) on laying down
calculation methods and reporting requirements pursuant to Directive 98/70/EC, a
number of 618 Feedstock Trade Names are specified and included in the proposed
methodology for calculating the greenhouse gas intensity of conventional fuels directed
to transport sector. Nevertheless the need for using Feedstock Trade Names for crude
oils is the same as in CARB with MCONs, i.e. to adopt a more precise crude oil naming
that is widely recognized in the market and easier to link to GHG emissions.
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Figure 3.13: Quantities produced globally and properties of main crudes (source:
ENI 2012)
3.3.2
Upstream
Step 1: Identification of key MCONs for Europe
The starting point of this study step is the list published by DG ENER regarding imports
and deliveries of crude oil for 2012, which is illustrated in Table 3.3 as this has been
considered the most reliable source of the crude oils imported in Europe.
Region
617
71,007
115,08
% of
Total
Imports
0.02 %
3,429
382,270
111,50
0.09 %
33,221
3,746,230
112,77
0.82 %
Iranian Light
13,665
1,508,091
110,36
0.34 %
Basrah Light
79,604
8,401,086
105,54
1.98 %
Kirkuk
Other Iraq
Crude
Kuwait Blend
61,288
6,717,371
109,60
1.52 %
10,909
1,121,944
102,84
0.27 %
33,600
3,636,667
108,23
0.83 %
Country of
Origin
Type of crude
oil
Abu Dhabi
Upper Zakum
Other Iran
Crude
Iranian Heavy
Iran
Middle
East
Iraq
Kuwait
Volume
(1000 bbl)
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CIF price (2)
($/bbl)
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Region
Country of
Origin
Type of crude
oil
Oman
Other
Middle East
Countries
Oman
621
69,620
112,14
% of
Total
Imports
0.02 %
Other Middle
East Crude
433
55,264
127,58
0.01 %
282,801
31,412,348
111,08
7.02 %
Arab Medium
17,468
1,917,619
109,78
0.43 %
Arab Heavy
Berri (Extra
Light)
38,376
4,092,054
106,63
0.95 %
15,672
1,728,847
110,31
0.39 %
591,703
64,860,417
109,62
14.68 %
106,964
11,814,595
110,45
2.65 %
8,301
934,748
112,61
0.21 %
1,992
240,228
120,60
0.05 %
65,971
7,407,561
112,28
1.64 %
12,561
1,405,290
111,88
0.31 %
16,594
1,858,782
112,02
0.41 %
Congo (DR)
Crude
5,811
637,775
109,75
0.14 %
Heavy
8,832
946,578
107,17
0.22 %
18,595
2,075,434
111,61
0.46 %
6,612
728,845
110,23
0.16 %
175,327
19,828,547
113,09
4.35 %
16,405
1,819,254
110,90
0.41 %
124,749
13,936,209
111,71
3.10 %
91,210
10,524,436
115,39
2.26 %
206,569
23,681,373
114,64
5.13 %
14,383
1,599,594
111,21
0.36 %
77,954
8,858,861
113,64
1.93 %
9,571
1,064,795
111,25
0.24 %
968,402
109,362,907
112,93
24.03 %
1,622
177,421
109,38
0.04 %
1,622
177,421
109,38
0.04 %
132,683
15,433,873
116,32
3.29 %
204,049
22,932,053
112,39
5.06 %
22,030
2,618,938
118,88
0.55 %
Arab Light
Saudi
Arabia
Middle
East
Algeria
Angola
Cameroon
Congo
Congo (DR)
Egypt
Africa
Gabon
Libyan Arab
Jamahiriya
Saharan Blend
Other Algeria
Crude
Cabinda
Other Angola
Crude
Cameroon
Crude
Congo Crude
Medium/Light
(30-40o)
Other Gabon
Crude
Medium (3040o)
Heavy
Light (>40o)
Medium
Nigeria
Other
African
Countries
Tunisia
Light (33-45o)
Condensate
(>45o)
Other Africa
Crude
Tunisia Crude
Africa
Australia
Papua New
Guinea
Papua New
Guinea Crude
Australia
Azerbaijan
FSU
Interim Report
Kazakhstan
Other FSU
countries
Azerbaijan
Crude
Kazakhstan
Crude
Other FSU
Crude
Volume
(1000 bbl)
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Total Value
($ 1000)
CIF price (2)
($/bbl)
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Study on actual GHG data for diesel, petrol, kerosene and natural gas
Region
Country of
Origin
Type of crude
oil
Russian
Federation
Other Russian
Fed. Crude
Urals
Norway
Europe
United
Kingdom
Canada
Colombia
Mexico
America
Other L.
America
countries
United
States
Venezuela
13.40 %
647,728
71,665,578
110,64
16.07 %
1,546,607
172,304,045
111,41
38.38 %
42,716
4,871,698
114,05
1.06 %
42,622
4,837,953
113,51
1.06 %
69,118
7,759,280
112,26
1.71 %
225,439
25,590,415
113,51
5.59 %
39,138
4,493,530
114,81
0.97 %
34,095
3,906,708
114,58
0.85 %
104,909
11,463,813
109,27
2.60 %
Flotta
14,075
1,620,525
115,13
0.35 %
Forties
38,083
4,274,373
112,24
0.94 %
Brent Blend
Other UK
Crude
56,028
6,359,949
113,51
1.39 %
93,937
10,659,678
113,48
2.33 %
760,159
85,837,922
112,92
18.86 %
Brazil Crude
Light Sweet
(>30o API)
Other
Colombia
Crude
Olmeca
26,412
2,920,991
110,60
0.66 %
3,634
407,144
112,03
0.09 %
30,410
3,152,847
103,68
0.75 %
331
36,790
111,15
0.01 %
Isthmus
12,393
1,374,428
110,90
0.31 %
Maya
50,426
5,193,475
102,99
1.25 %
1,485
167,421
112,74
0.04 %
60
4,851
80,75
0.00 %
2,785
298,050
107,01
0.07 %
3,716
410,023
110,34
0.09 %
4,933
540,946
109,67
0.12 %
25,055
2,556,660
102,04
0.62 %
161,640
17,063,627
105,57
4.01 %
75
8,456
112,17
0.00 %
4,030,208
449,614,795
111,56
100. %
Denmark
Crude
Statfjord
Ekofisk
Other Norway
Crude
Oseberg
Other Europe
Crude
Other Latin
America Crude
Other US
Crude
Medium (2230o)
Heavy (1722o)
Light (>30o)
Extra Heavy
America
World
World
% of
Total
Imports
110,45
Europe
Brazil
CIF price (2)
($/bbl)
59,653,602
Gullfaks
Other
European
countries
Total Value
($ 1000)
540,118
FSU
Denmark
Volume
(1000 bbl)
Interim Report
Other crudes
Table 3.3: European imports and deliveries of crude oil for 2012 (source:
European Commission, DG ENER)
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Step 2: Representative MCONs and oil fields
One significant methodogical pitfall of the DG ENER list – relevant to the study - is that
the used term “type of crude” oil does not necessarily correspond to specific MCONs
as expected. Instead, crudes are presented in an aggregated form that does not allow
for the precise identification of MCONs imported in Europe. For example, the “Nigerian
Light” crude oil corresponds to several MCONs. Furthermore, the list uses also
aggregate figures such as “Other Norwegian Crude” which again corresponds to
several marketable names (MCONs). Therefore, the Consultant has determined to use
the concept of representative MCON so that one or two representative MCONs are
used for each “type of crude oil”. The choice of representative MCONs has been based
on the following principles:



Largest quantities of related MCONs imported and/or produced in Europe.
Representative MCONs have been chosen on the basis of quantities of crude
oil imported and/or produced in Europe in order to maximize the coverage the
DG ENER aggregates. Thus, MCONs with the higher quantities of imports or
production (for European crudes) have been chosen as representative.
However, in the case of certain countries (i.e. Nigeria, Angola, Libya) it has
been difficult to exactly identify the quantities imported in Europe from all
MCONs and therefore determined the one with the largest imports. In these
cases, it has been assumed that the MCON that corresponds to the fields with
the largest production is representative of the DG ENER aggregate.
Maximum geographical coverage of the exporting country. Another
significant consideration for the choice of representative MCONs has been the
maximization of the geographic coverage of the exporting country. This is
necessary because our background analysis using the OPGEE and work
previously done has shown that crudes extracted within a specific vicinity exhibit
similar upstream emissions. This has been anticipated because the reservoirs
of fields that are located closely most likely have the same geological
characteristics.
Significance of MCON in EU crude supply over the years. The supply of
Europe and Member States in specific MCONs does not exhibit significant
variations over time. However, the choice of a specific baseline year for the
study might not capture significant crude oil sources. For instance, Iranian crude
is significant for EU crude oil supply (4.00 % of EU imports in 2011 and 2.47%
in 2012 %,), but no quantities were imported in 2013 for political reasons.
However, it is anticipated that in the close future Europe will start importing
again Iranian. Similarly the Venezuelan extra heavy crude oil (Boscan), in 2012
constituted 0.62% of EU supply and is anticipated according to our market
prospects that it play a constantly increasing role in Europe’s crude oil supply.
Therefore, it has been determined to include of the scope the analysis these
two crudes.
In order to take account only MCONs that constitute significant fragment of EU supply,
the Consultant has removed aggregates comprising less than 0.8% of EU imports with
the exception of Venezuela bitumen. Additionally, the aggregates “other Europe crude”
and “other UK crude” have been removed. With the removal of these aggregates the
EU import coverage reaches the satisfactory level of 87.84%.
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Following the choice of representative MCON, an intensive analysis of the oil fields
comprising each MCON has followed. The extent to which an oil field is representative
of an MCON (and by extension affects its physical characteristics) is highly volatile as
this depends on the number of fields feeding an MCON and spans over time. For
instance, the Stratfjord blend is fed by the oil fields of Statfjord, Snorre, Sygna,
Satellites Statfjord North and East, which demands for manageable effort regarding
data collection. However, for crude aggregates such as Brent there are over 70 fields
feeding the MCON. Furthermore, the analysis of work previously done and primarily the
analysis of upstream emissions conducted by ICCT using the OPGEE model has
shown oil fields with small geographical proximity have similar upstream emissions.
Thus, it has been considered that the choice of the fields with the highest production is
representative for each MCON. The revised DG ENER list with representative fields
and MCONs is illustrated in Table 3.1. This list is considered for the analyses carried
out onwards in this study.
Region
Country of
Origin
Type of crude
oil
Share
Iranian Heavy
0.82 %
Iranian Heavy
Basrah Light
1.98 %
Basrah Light
Kirkuk
Kuwait Blend
1.52 %
0.83 %
Kirkuk
Kuwait Blend
Arab Light
7.02 %
Arab Light
Arab Heavy
Saharan Blend
0.95 %
2.65%
Angola
Other Angola
Crude
1.64%
Arab Heavy
Saharan Blend
Dalia
Girassol
Greater Plutonio
Gachsaran
Rumaila (South)
West Qurna
Kirkuk
Burgan
Gwahar
Kurais
Manifa
Hassi Messaoud
Block 17/Dalia
Girassol
Greater Plutonio
Libyan Arab
Jamahiriya
Medium (3040o)
Light (>40o)
4.35%
Es Sider
Es Sider
3.10%
El Sharara
Bonga
Forcados
El Sharara
Bonga
Forcados Yokri
Agbada
Caw Thorne
Channel
Escravos Beach
Azeri-ChiragGunashli (ACG)
Azeri-ChiragGunashli (ACG)
Tengiz
Tengiz
TevlinskoRusskinskoye
Uryevskoye
Samotlor
Vat-Yeganskoye
Povkhovskoye
Iran
Iraq
Middle
East
Kuwait
Saudi Arabia
Algeria
Africa
Medium
2.26%
Light
5.13%
Representative
MCON
Nigeria
Bonny light
Escravos
Azerbaijan
Kazakhstan
Azerbaijan
Crude
3.29 %
Kazakhstan
Crude
5.06 %
Azeri light
Azeri BTC
CPC Blend
Tengiz
FSU
Russian
Federation
Other Russian
Fed. Crude
13.40 %
Western Siberia
Light
Representative
Oil field Name
Druzhba
Urals
16.07 %
Urals
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Romashkino
Unvinskoye
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Study on actual GHG data for diesel, petrol, kerosene and natural gas
Country of
Origin
Region
Type of crude
oil
Interim Report
Representative
MCON
Share
Representative
Oil field Name
PamyatnoSasovskoye
Denmark
Crude
Statfjord
Ekofisk
Other Norway
Norway
Crude
Europe
Oseberg
Gullfaks
Forties
Brent Blend
UK
Other UK
Crude
Mexico
Maya
America
Venezuela
Extra Heavy
Total EU import coverage:
Denmark
1.06 %
DUC
Halfdan
1.06 %
1.71 %
0.97%
0.85 %
0.94 %
1.39 %
Statfjord
Ekofisk
Troll
Asgard Blend
Oseberg
Gullfaks blend
Forties
Brent Blend
Statfjord
Ekofisk
Troll B/C
Tyrihans
Oseberg
Gullfaks
Buzzard
Ninian
2.33 %
Captain
Captain
1.25 %
0.62 %
87. 84%
Maya
Boscan
Cantarell
Boscan
5.59%
Table 3.4: List of representative MCONs and oil fields
One significant methodological difficulty for the disaggregation is that for a specific type
of crude oil, there might be several types of MCONs or grades depending on the mode
of transport (e.g. pipeline or maritime), exporting port, etc. This difficulty is mostly
related to Russian crudes and the case of Urals crude oil is illustrated in Table 3.5. The
presented grades of Urals are mostly imported in Europe via several ports and the
Druzhba pipeline.
Grade
Typical
°API
gravity
Typical
Sulphur
(%)
Conversion
factor (t/bl)
Basis/
Location
Timing
Urals NWE
30.83
1.44
7.2161
CIF
Northwest
Europe
Loading 1025 days
ahead
Urals Med
80,000t
30.84
1.29
7.2165
CIF Augusta,
Italy
Loading 1025 days
ahead
80,000
Urals Med
140,000t
30.84
1.29
7.2165
CIF Augusta,
Italy
Loading 1025 days
ahead
140,000
Urals fob
Primorsk
30.83
1.44
7.2161
FOB
Primorsk,
Baltic
-
100,000
2
7.2156
0
FOB UstLuga, Baltic
-
Urals fob
Ust-Luga
3
1
Cargo
size
(tonnes)
0
0
0
Urals fob
Novorossiys
k 80,000t
30.84
1.29
7.2165
FOB
Novorossiysk
, Black Sea
-
80,000
Urals fob
30.84
1.29
7.2165
FOB
-
140,000
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Typical
°API
gravity
Grade
Typical
Sulphur
(%)
Conversion
factor (t/bl)
Novorossiys
k 140,000t
Urals cif
Black Sea
80,000t
Basis/
Location
Interim Report
Timing
Cargo
size
(tonnes)
-
80,000
Novorossiysk
, Black Sea
30.84
1.29
7.2165
CIF Black
Sea
Table 3.5: Different grades for Urals crude oil (source: Argus Media)
Similarly, there are several grades (usually referred as price assessments in crude oil
pricing) for deliveries of Russian Urals crude to refineries in eastern inland Europe via
the Druzhba (Friendship) pipeline, which have the same physical properties of oil and
thus the same emissions related to upstream activities, but different emissions related
to crude oil transport. Table 3.6 presents the reality with the Druzhba pipeline delivering
the same MCON to different destinations in EU.
Grade
Druzhba
Czech
Republic
Druzhba
Slovakia
Druzhba
Hungary
Druzhba
Poland
Druzhba
Germany
Druzhba
Czech
Republic
Typical
°API
gravity
Typical
Sulphur
(%)
Conversion
factor (t/bl)
Basis/ Location
Timing
Cargo
size
(tonnes)
Delivered
during the
previous month
10,000t
tranche
30.82
1.60
7.2156
fit Budkovce,
Slovakia (for
Czech delivery)
30.82
1.60
7.2156
fit Budkovce,
Slovakia (for
Slovak delivery)
Delivered
during the
previous month
10,000t
tranche
7.2156
fit Fenyeslitke,
Hungary (for
Hungarian
delivery)
Delivered
during the
previous month
10,000t
tranche
7.2156
fit Adamowo,
Poland (for
Polish delivery)
Delivered
during the
previous month
10,000t
tranche
Delivered
during the
previous month
10,000t
tranche
Delivered
during the
previous month
10,000t
tranche
30.82
30.82
1.60
1.60
30.82
1.60
7.2156
fit Adamowo,
Poland (for
German
delivery)
30.82
1.60
7.2156
fit Budkovce,
Slovakia (for
Czech delivery)
Table 3.6: Price assessments for crude oil transported via the Druzhba pipeline
(source: Argus Media)
Reliability of the choice of representative MCONs and oil fields
It must be noted that for few specific cases there is a small possibility that a chosen
representative MCON or oil field might not arrive at Europe, particularly for MCONs
presented in an aggregated way (e.g. Nigerian crudes). However, this is strongly
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mitigated by the fact that the likelihood that the specific MCONs (e.g. Bonny light)
arriving at Europe is increased as these are the most important crudes in terms of
quantities for the specific category (e.g. Nigerian Light). Furthermore, a background
consistency check has been made with several sources (Platts, Argus, Lloyd’s,
Bloomberg) so as to ensure that the specific MCON actually arrives at Europe.
Similarly, the rationale for the choice of a representative oil field based on production
volumes entails a small risk that oil from the specific fields might not arrive at Europe.
For Russian and FSU crudes, this risk is very limited as most of these crudes (and
respectively oil fields) enter the same pipeline system that supplies Europe directly or
via maritime. The possibility that an oil field is not fully representative is increased in
the case where a large number of oil fields comprise an MCON (e.g. Brent, Forties,
Bonny light). In this case, even though the field might not supply crude oil to Europe the
reliable assumption that the field has similar characteristics to its neighboring fields and
therefore emissions has been made. This assumption has been validated by
background analysis of neighbouring fields in OPGEE which produce results in the
same range of values.
The sites of all fields and the exporting ports of the MCONs considered in this study are
presented in Figure 3.14.
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Figure 3.14: Map of representative oil fields and their terminals
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Step 3: Collection of actual data from oil companies and national authorities
Following the finalization of representative MCONs and oil fields, the Consultant started
the procedure for collecting actual data of MCONs and their representative oil fields.
The main sources of these data are either the oil companies that are operators of the
specific oil fields or the national authorities responsible for oil activities in each country.
The list of the targeted field and MCON operators for the representative MCONs
considered in this study as well as the other involved companies are presented in
Table 3.7
Representative
MCON
Operator
Other companies
Iranian Heavy
National Iranian
Oil Company
-
BP
China National Petroleum Corporation (CNPC)
Iraq’s state-owned South Oil Company (SOC)
Iraq National Oil
Company
Exxon Mobil, Royal Dutch Shell, Lukoil, Statoil
Kirkuk
North Oil
Company
London-based BP, Iraq Petroleum Company, Iraq's
National Oil Company
Kuwait Blend
Kuwait Oil
Company
-
Arab Light
Saudi Aramco
-
Arab Heavy
Saudi Aramco
-
Saharan Blend
Sonatrach
-
Dalia
Total
Total is operator with 40% interest. Esso Exploration
Angola holds 20%, BP holds 16.67%, Statoil holds
23.33%.
Girassol
Total
Esso Exploration Angola (20% interest), BP (16.7%),
Statoil (13.3%) and Norsk Hydro (10%).
Greater Plutonio
BP
Sonangol Sinopec International, a joint venture
between the Chinese and the Angolan state oil
companies,
Es Sider
NOC /
ConocoPhilips /
Marathon / Hess
-
El Sharara
Repsol, Akakus
Total / OMV /
Statoil
Bonga
Shell Nigeria
Royal Dutch Shell, ExxonMobil, Total S.A., Eni
Forcados
Shell Nigeria
-
Bonny light
Chevron
Shell
Escravos
Chevron ELF
-
BP
Chevron with 11.3%; SOCAR with 11.6%; INPEX
with 11%; Statoil with 8.6%; ExxonMobil with 8%;
TPAO with 6.8%; Itochu with 4.3%; and Hess with
2.7%
Basrah Light
Azeri light
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Representative
MCON
Interim Report
Operator
Other companies
Azeri BTC
AIOC
BP
Shareholders of the Azeri-Chirag-Gunashli offshore
field include BP with 34.1367% of
stakes, ChevronTexaco - 10.2814%,SOCAR 10%, INPEX - 10%, Statoil - 8.5633%, ExxonMobil 8.006%, TPAO - 6.75%, Devon Energy 5.6262%, Itochu - 3.9205% and Hess - 2.7213%.
Russia's Lukoil oil company pulled out of the project
in 2003 selling all of its interest to INPEX.
Tengiz
Tengizchevroil
Chevron Corporation (50%), ExxonMobil (25%),
KazMunayGas (20%)
CPC blend
Tengizchevroil
Chevron Corporation (50%), ExxonMobil (25%),
KazMunayGas (20%)
Druzhba
Lukoil
-
Lukoil
-
Lukoil
-
Lukoil
-
Lukoil
-
Siberia Light
Urals
Lukoil
DUC
Maersk Oil
Gas A/S, Royal Dutch Shell, Chevron Corporation
Statfjord
Statoil
Ekofisk
ConocoPhillips
Skandinavia AS
Petoro, Statoil, Eni, ConocoPhillips, Total S.A.
Troll
Statoil
Petoro (56%), Royal Dutch Shell (8.1%),
ConocoPhillips (1.62%) and Total S.A. (3.69%)
Asgard Blend
Statoil
Petoro (35.69%), Eni Norge (14.82%), Total E&P
Norge (7.68%) and ExxonMobil (7.24%)
Oseberg
Statoil
ConocoPhillips Skandinavia AS 6.17 %, ExxonMobil
Exploration & Production Norway AS 28.22 %,
Petoro AS 28.94 %, Statoil Petroleum AS 36.66 %
Gullfaks blend
Statoil
Norsk Hydro the former Saga Petroleum
Forties
NEXEN
PETROLEUM
U.K. LIMITED
Suncor Energy - 30%, BG Group - 22%, Edinburgh
Oil & Gas - 5%
Brent Blend
Canadian
Natural
Resources
Limited (UK)
Eni 13%
Captain
Chevron
Texaco North Sea UK Company (85%) and the
Korea Captain Company Limited (15%)
Maya
Pemex
-
Boscan
Empresa Mixta
Petroboscan
Petroleos de Venezuela (PDVSA) and Chevron
Table 3.7: Representative MCONs and their operators
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Step 4: Modelling of upstream emissions in OPGEE model
The literature review and the direct contacts with oil companies till present have made
explicit that oil companies are cautious regarding the emission figures they publish,
which are presented in generic and aggregated manner. Furthermore, data collected
by national authorities or environmental organizations are typically on a country level
which is insufficient for the analyses and comparisons of this study.
In order to mitigate the difficulty to obtain actual GHG emissions data on a field or
MCON level the OPGEE model might be used for the estimation of GHG emissions of
several MCONs. Therefore, the effort of the project team focused in gathering
necessary data which are input for OPGEE. The main sources of these were official
reports and publications from international organizations and oil companies involved in
oil exploitation.
The rationale and the structure of the OPGEE model concentrates on simulating the
upstream and midstream processes per oil field; details about the model are presented
in the next Sections of this report.
3.3.3
Midstream
Step 5: Assessment of crude oil pathways to Europe
The purpose of this step is to estimate the GHG emissions related to the transport of
crude oil to Europe. The Consultant has initially located the loading terminals for each
MCON as they are presented in Table 3.8. These terminals are used for the calculation
of distances towards the main EU unloading ports. The relevant estimation of distances
and GHG emissions will be presented in the next Sections.
Type of crude
oil
Representative
MCON
Representative Oil field
Name
Terminal
Name
Iranian Heavy
Iranian Heavy
Gachsaran
Kharg Island
Rumaila (South)
Al Basrah Oil Terminal
Basrah Light
Basrah Light
West Qurna
Al Basrah Oil Terminal
Kirkuk
Kirkuk
Kirkuk
Ceyhan
Kuwait Blend
Kuwait Blend
Burgan
Mina al Ahmadi
Gwahar
Ras Tanura
Arab Light
Arab Light
Kurais
Ras Tanura
Arab Heavy
Arab Heavy
Manifa
Ras Tanura
Saharan Blend
Saharan Blend
Hassi Messaoud
Arzew
Dalia
Block 17/Dalia
Dalia FPSO
Other Angola
Girassol
Girassol
Girassol FPSO
Crude
Medium (3040o)
Greater Plutonio
Greater Plutonio
Greater Plutonio FPSO
Es Sider
Es Sider
Es Sider
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Type of crude
oil
Light (>40o)
Interim Report
Representative
MCON
Representative Oil field
Name
Terminal
Name
El Sharara
El Sharara
Zawiya
Bonga
Bonga
Bonga FPSO
Forcados
Forcados Yokri
Forcados Terminal
Agbada
Bonny Terminal
Caw Thorne Channel
Bonny Terminal
Escravos Beach
Escravos Terminal
Medium
Bonny light
Light
Escravos
Azerbaijan
Crude
Kazakhstan
Crude
Other Russian
Fed. Crude
Urals
Azeri light
Azeri BTC
Azeri-Chirag-Gunashli
(ACG)
Azeri-Chirag-Gunashli
(ACG)
Supsa
Ceyhan
CPC Blend
Tengiz
Ceyhan
Tengiz
Tengiz
Novorossiysk
Tevlinsko-Russkinskoye
Novorossiysk, Primorsk
Uryevskoye
Novorossiysk, Primorsk
Samotlor
Novorossiysk, Primorsk
Vat-Yeganskoye
Novorossiysk, Primorsk
Povkhovskoye
Novorossiysk, Primorsk
Romashkino
Novorossiysk, Primorsk
Unvinskoye
Novorossiysk, Primorsk
Pamyatno-Sasovskoye
Novorossiysk, Primorsk
Western Siberia
(light)
Urals
Denmark Crude
DUC
Halfdan
Fredericia
Statfjord
Statfjord
Statfjord
Statford
Ekofisk
Ekofisk
Ekofisk
Teeside
Other Norway
Crude
Troll
Troll B/C
Mongstad
Asgard Blend
Tyrihans
Asgard FPSO
Oseberg
Oseberg
Oseberg
Sture
Gullfaks
Gullfaks blend
Gullfaks
Mongstad
Forties
Forties
Buzzard
Hound Point
Brent Blend
Brent Blend
Ninian
Sullom Voe
Other UK
Crude
Captain
Captain
Captain FPSO
Maya
Maya
Cantarell
Caya Arcas
Extra Heavy
Boscan
Boscan
Bajo Grande
Table 3.8: Most significant oil terminals supplying crude oil to Europe
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Maritime transport
Europe is supplied with crude oil either via maritime transport from major ports that are
interconnected with oil pipelines or directly from oil terminals. More specifically,
significant part of Russian oil arrives in Εurope via Primorsk which is Russia's largest
oil terminal, with a loading capacity of 1.5 million b/d. It is located near St. Petersburg
and is a two-berth harbor that can accommodate ships with maximum length of 307
meters. Novorossiysk is Russia's main oil terminal at the Black Sea coast. Its load
capacity is 950,000 b/d, and it can load tankers up to 150,000 deadweight tonnes
(dwt). Tuapse is located on the northeastern shore of the Black Sea, southeast of
Novorossiysk. Two of the six berths load crude oil. The port mainly exports Siberian
Light. Its loading capacity is about 350,000 b/d. In addition, the terminal has more than
580.000 barrels of oil and oil products storage capacity. The port can accommodate
tankers with up to 80,000 dwt. Yuzhny terminal is located in Ukraine, near Odessa,
although it mainly exports Russian and Kazakh crude oil via the Black Sea. This port's
load capacity is 315,000 b/d, and it can accommodate vessels up to 70,000 dwt.
Additionally, other significant Russian oil ports are at Ventspills, Ust Luga and Gdansk
in Poland; all of them are exporting Urals oil.
In terms of quantities imported, the largest Russian oil terminal is Primorsk which in
2011 exported over 1.3 million b/d. Novorossiysk is the largest Russian oil terminal in
the Black sea, through which Russia exported approximately 0.9 million b/d in 2011, as
it can be obtained from Figure 3.15.
From these ports crude oil arrives at Europe via various categories of tankers the
categories of which are illustrated in Table 3.9 and will be used in the calculation of
GHG emissions of oil maritime transport.
1.6
1.4
1.2
1
2010
0.8
2011
0.6
0.4
0.2
0
Novorossisk
Tuapse
Kozmino
Primorsk
Yuzhny
Figure 3.15: Exports in million b/d including transit through Russian ports
Quarter 1 of 2010 to Quarter 1 of 2011 (source: CDU)
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DWT Range
(tonnes)
Description
Aframax
80,000 - 119,000
This is the largest crude oil tanker size in the AFRA (Average
Freight Rate Assessment) tanker rate system.
Suezmax
120,000 - 150,000
This is the maximum size crude oil ship that can pass
through the Suez Canal in Egypt.
150,000 - 319,999
These are very large crude oil carriers that transport crude oil
from the Gulf, West Africa, the North Sea and Prudhoe Bay
to destinations in the United States, Mediterranean Europe
and Asia. Although VLCCs are otherwise too large, it is
possible to ballast these vessels through the Suez Canal.
320,000 - 999,999
These are the largest man-made vessels that move.
Currently, the largest ULCC is 564,939 dwt. These ships sail
the longest routes, typically from the Gulf to Europe, the
United States and Asia. They are so large that they require
custom-built terminals for loading and unloading.
Name
VLCC
ULCC
Table 3.9: Crude oil tanker categories (source: Lloyds)
Figure 3.16 illustrates the major ports that have facilities for unloading of crude oil in
Europe. These ports are the recipients of crude oil transported from the exporting ports
of the representative MCONs which have been presented above.
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Figure 3.16: Map of major ports importing crude oil in Europe
Pipeline transport
The largest part of the Russian oil is supplied to Europe via the Druzhba pipeline
system, which remains the largest oil pipeline in the world. The vast majority of the oil
refined in Poland, Slovakia, Hungary, Eastern part of Germany and Czech Republic is
supplied via the Druzhba pipeline. Table 3.10 presents the main destinations of the
Druzhba pipeline and the capacity of refineries which are supplied by the pipeline.
The Baltic Pipeline System (BPS) is a Russian oil transport system operated by the
oil pipeline company Transneft. The BPS transports oil from the Timan Pechora region,
Western Siberia and Urals-Volga regions to Primorsk oil terminal. Main sections of the
BPS I are the Yaroslavl Kirishi pipeline and Kirishi-Primorsk pipeline. The capacity of
the BPS I is 76.5 million tons of oil per year. The Baltic Pipeline System II is the second
route of the Baltic Pipeline System. The BPS-II was completed in 2011 and became
operational in 2012. The pipeline runs from Unecha to the port of Ust Luga (west of St.
Petersburg and passes through Smolensk. It has a total length of 1,170 km and a
capacity of 50 million tons per year. The main routes are presented in Figure 3.17.
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Country
Location
Capacity (MTA)
Lithuania
Mazeikiai
9.4
Gdansk
10.5
Plock
17.8
Leuna
11.2
Schwedt
12.0
Litvinov
5.1
Kralupy
3.1
Padubice
1.0
Slovakia
Bratislava
5.7
Hungary
Szazhalombatta
7.9
Poland
Germany
Czech Republic
TOTAL
83.7
Table 3.10: EU refining locations and capacities linked to Druzhba pipeline
Figure 3.17: The Baltic Pipeline System. Gas pipelines are shown in red colour,
oil pipelines in green and the dashed line shows the planned
pipelines. (source: EIA)
The Caspian Pipeline Consortium (CPC) oil pipeline, was commissioned in 2001 and
runs from Kazakhstan's Tengiz oil field to the Russian port of Novorossiysk at the Black
Sea. The consortium transported an average of 684,000 b/d of crude oil in 2011,
including 608,000 b/d from Kazakhstan and 76,000 b/d from Russia. In addition,
approximately 53,000 b/d of Tengiz crude was discharged at Atyrau, Kazakhstan, for
loading onto rail cars. In 2011, CPC partners began the expansion of the pipeline
capacity to 1.4 million b/d. The project will be implemented in three phases, with
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capacity increasing until 2016. The expansion is expected to provide additional
transportation capacity to accommodate increased production from Tengizchevroil.
The Baku-Novorossiysk pipeline is 830 miles long and has a capacity of 100,000
bbl/d. The pipeline runs from the Sangachal Terminal to Novorossiysk, Russia on the
Black Sea. SOCAR operates the Azeri section, and Transneft operates the Russian
section. An ongoing dispute between SOCAR and Transneft concerning transportation
tariffs occasionally complicates the pipeline's operation. There are proposals to
increase the pipeline capacity to between 180,000 and 300,000 bbl/d, a key
transportation addition as production grows in the ACG oil field and throughput from
Kazakhstan increases in the future. In 2010, Baku-Novorossiysk transported
approximately 45,500 b/d.
Since the collapse of the Soviet Union, European countries have begun investing in
alternative export routes. The Baku-Tbilisi-Ceyhan (BTC) pipeline is a 1-million b/d
line in Azerbaijan, which came online in 2006. Kazakhstan has a contract with
Azerbaijan and the BTC Pipeline Company to ship up to 500,000 b/d of oil via the BTC
pipeline. Kazakh oil supplies were loaded into the BTC for re-export for the first time in
October 2008. Oil supplies are delivered by tanker across the Caspian to Baku. The
BTC pipeline system runs 1,110 miles from the ACG field in the Caspian Sea, via
Georgia, to the Mediterranean port of Ceyhan, Turkey. From there the oil is shipped by
tanker mainly to European markets.
Kazakhstan's other major oil export pipeline, Uzen-Atyrau-Samara, is a northbound
link to Russia's Transneft distribution system, which provides Kazakhstan with a
connection to world markets via the Black Sea. The line was upgraded in 2009 by the
addition of pumping and heating stations and currently has a capacity of approximately
600,000 b/d. Before the completion of the CPC pipeline, Kazakhstan exported almost
all of its oil through this system.
Represe
ntative
MCON
Arab
Light
Oil field
Gwahar
Bonny
light
Pathway
Comments
Pipeline
Total
(miles)
Marine
Total
(miles)
Tanker
size
(DWT)
MIN
Ghawar oil field Ras Tanura - Agioi
Theodoroi
93
4,375
100,000
CENTRAL
Ghawar oil field Ras Tanura - Le
Havre
93
7,171
200,000
MAX
Ghawar oil field Ras Tanura Rotterdam
93
7,456
100,000
MIN
Agbada oil field Bonny terminal Huelva
42
4,215
135,000
CENTRAL
Agbada oil field Bonny terminal -
42
5,704
135,000
Min/max
Agbada
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Represe
ntative
MCON
Oil field
Pathway
Min/max
Comments
Interim Report
Pipeline
Total
(miles)
Marine
Total
(miles)
Tanker
size
(DWT)
Trieste
Bonny
light
MAX
Agbada oil field Bonny terminal Gothenburg
42
6,311
135,000
MIN
Caw Thorne
Channel oil field Bonny terminal Huelva
17
4,215
135,000
CENTRAL
Agbada oil field Bonny terminal Trieste
42
5,704
13,500
MAX
Caw Thorne
Channel oil field Bonny terminal Gothenburg
17
6,311
135,000
MIN
Samotlor - Surgut
- Perm - Ufa Samara - Saratov
Volgograd NovorossiskCostanza
1,880
504
135,000
CENTRAL
Romashkino Perm - Ufa Samara - Saratov
Volgograd NovorossiskTrieste
1,881
1,850
135,000
MAX
Samotlor - Surgut
- Perm - Ufa Samara - Saratov
Volgograd NovorossiskRotterdam
1,880
4,999
135,000
MIN
Samotlor - Perm Primorsk - Gdansk
1,862
699
100,000
CENTRAL
Samotlor - Perm Primorsk Rotterdam
1,862
1,495
100,000
MAX
Samotlor - Perm Primorsk - Megara
oil terminal
1,862
5,495
100,000
Germany
Samotlor - Surgut
- Perm - Plock Leuna
2,912
0
-
Poland
Samotlor - Surgut
- Perm - Plock
2,528
0
-
Czech
Republic
Samotlor - Surgut
- Perm - Ufa Almetyevsk Syzran - Unecha -
2,751
0
-
Caw
Thorne
Channel
Novorossisk
Siberia
Light
Samotlor
Primorsk
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Represe
ntative
MCON
Oil field
Interim Report
Pipeline
Total
(miles)
Marine
Total
(miles)
Tanker
size
(DWT)
Slovakia
Samotlor - Surgut
- Perm - Ufa Almetyevsk Syzran - Unecha Mozyr - Uzhgorod
- Bratislava
2,983
0
-
Hungary
Samotlor - Surgut
- Perm - Ufa Almetyevsk Syzran - Unecha Mozyr - Uzhgorod
- Szazhalombatta
2,692
0
-
MIN
Romashkino Perm - Ufa Samara - Saratov
Volgograd NovorossiskCostanza
1,036
504
135,000
CENTRAL
Romashkino Perm - Ufa Samara - Saratov
Volgograd NovorossiskTrieste
1,036
1,850
135,000
MAX
Romashkino Perm - Ufa Samara - Saratov
Volgograd NovorossiskRotterdam
1,036
4,999
135,000
MIN
Romashkino Perm - Primorsk Gdansk
1,838
699
100,000
CENTRAL
Samotlor - Perm Primorsk Rotterdam
1,838
1,495
100,000
MAX
Romashkino Perm - Primorsk Megara oil
terminal
1,838
5,495
100,000
Germany
Romashkino Almayetsk Syzran - Unecha Mozyr - Plock Schwedt - Leuna
1,888
0
-
Poland
Romashkino Almayetsk Syzran - Unecha -
1,504
0
-
Pathway
Min/max
Comments
Mozyr - Uzhgorod
- Bratislava Kralupy - Litvinov
Novorossisk
Urals
Romash
kino
Primorsk
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Represe
ntative
MCON
Oil field
Interim Report
Pipeline
Total
(miles)
Marine
Total
(miles)
Tanker
size
(DWT)
Czech
Republic
Romashkino Almayetsk Syzran - Unecha Mozyr - Uzhgorod
- Bratislava Kralupy - Litvinov
1,727
0
-
Slovakia
Romashkino Almayetsk Syzran - Unecha Mozyr - Uzhgorod
- Bratislava
1,960
0
-
Hungary
Romashkino Almayetsk Syzran - Unecha Mozyr - Uzhgorod
- Szazhalombatta
2,040
0
-
MIN
Troll - Mongstad Gothenburg port Gotheburg refinery
86
439
80,000
CENTRAL
Troll - Mongstad Gothenburg port Wilhelshaven
86
583
80,000
MAX
Troll - Mongstad Trieste port Trieste refinery
86
4,055
80,000
Pathway
Min/max
Comments
Mozyr - Plock
Troll
Troll B/C
Troll B/C
Table 3.12 presents the main oil pipelines supplying crude oil to Europe as well the
capacities of the pipelines and the estimated distances to the main destinations. Also
Figure 3.19 presents in a regional map the main routes of Russian oil pipelines
supplying oil to Europe.
Due to the above presentation of the Russian oil pathways it is evident that there is
high complexity in defining the MCONs and their precise oil field components. Figure
3.18 presents the approach of the Consultant in representing the midstream pathways
and the relevant Russian MCONs, especially those directed to EU destinations.
Therefore oil transported by Druzhba constitutes one MCON which differentiates in the
GHG emissions according to the country of delivery due to different distances and a
min-max calculation will be used. On the other hand we consider two Urals MCONs
due to the two pathways used to export it by maritime (Primorsk, Novorossiysk) and
one Siberian Light MCON export through Novorossiysk.
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Figure 3.18: Russian crude oil analysis from oil field to MCON
Length
(miles)
Capacity
(million
bbl/d)
Druzhba
Northern Route:
Belarus, Poland
Germany;
Southern Route:
Belarus, Ukraine,
Slovakia, Czech
Republic, Hungary
2,400
2
Baltic
Pipeline
System I
Timan Pechora to
Primorsk Terminal
730
1.5
Baltic
Pipeline
System 2
Unecha to Ust-Luga
Terminal
620
1
Pipeline
Route
Details
North-West
Pipeline
System
Polotsk to Butinge
and Ventspils
500
0.3
Branches off of Druzhba
near Russia-Belarus
border and transports
Russian oil via Belarus
to Latvia and Lithuania
Caspian
Pipeline
Consortium
(CPC)
Tengiz (Kazakhstan)
to Russian Black Sea
port of Novorossiysk
940
0,7
Planned expansion to
1.4 million b/d by 2016
Baku-TbilisiCeyhan
Connects ACG, Shah
Deniz, Tengiz
1,000,000
bbl/d
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Pipeline
Route
Interim Report
Length
(miles)
Capacity
(million
bbl/d)
830
0.1
Details
(BTC)
BakuNovorossiys
k Pipeline
Sangachal Terminal
(Azerbaijan) to
Russian Black Sea
port of Novorossiysk
Planned expansion to
0.3 million b/d
Source: Transneft, IHS, PFC Energy, Petroleum Economist
Table 3.11: Russian and Caspian pipeline supplying Europe (source: EIA)
Rail export routes
Rail exports comprise a very small portion of Russian oil exports. Rail transport
generally used as an alternative to Transneft's pipeline network, although rail transport
is generally more expensive than pipeline transportation. It is referred that Russia
exports crude oil and petroleum products by rail to Estonia and Latvia. These quantities
are small and will be ignored in this study.
Figure 3.19: Map with main routes of Russian pipelines supplying crude oil to
Europe
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Step 6: Estimation of midstream GHG emissions
The Consultant has approached the transportation of crudes (MCONs) by ships at the
refinery gate by correlating discharges of crude oil cargoes at ports (which is an
information relatively available) with neighbouring refineries. It has been taken into
account that most EU refineries either own an oil terminal or are built close to ports.
Similarly, most refineries in Central Europe are built alongside major crude oil
pipelines. The precise blend input of refineries - either via marine transport or pipeline is unfortunately not available as it is of high commercial value for refineries and has
therefore been impossible to find this information in a consistent and reliable manner.
One possible source of this information could be maritime databases using vessel
tracking via the automatic Identification System (AIS) that most ships have installed
over the last decade.
Maritime transport
A database that contains such information and reviewed by the Consultant is APEX
(Analysis of Petroleum Exports) providing details of laden tanker movements for
vessels greater than 10,000 DWT engaged in world-wide crude oil trades and laden
tanker movements for vessels greater than 60,000 DWT in world-wide oil product
trades as well as current tanker activities for specific size ranges.
The APEX database is a product of Lloyd's List Intelligence that draws on the extensive
movements database of its parent company Informa Group. The database is compiled
from movements observed by over 1,500 Lloyd's Agents worldwide, supplemented with
data from the network of AIS stations; the world's largest, and satellite AIS data. From
this database Lloyd's List Intelligence extracts movements’ details for all tankers and
combination carriers in excess of 10,000 DWT. These data is then analysed by a team
of analysts who identify the laden voyages which are then inputted into the APEX
database.
Even though the APEX database is probably one of the most comprehensive
commercial information tools for the analysis of maritime crude oil shipments it has
been considered as insufficient for the purpose of this study, as in several cases the
precise type of the shipment is not explicitly mentioned or stated as “multiple cargo”
which does not allow for further analysis. Furthermore, despite its depth of information
regarding maritime transport, the database does not contain information regarding
pipeline oil transport. However, it must be stated that the database contains a wealth of
information relevant to:









Vessel name
Cargo type and tonnes
Crude type
API of crude transported
Loading port and date
Discharge port and date
Refinery capacity at place
Refinery location, capacity and owner
Distance
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
Interim Report
Dead Weight Tonnage
Other useful programs for identifying ships vessel movements carrying crude oil is the
Sea Web tool by IHS, combining comprehensive data regarding ships, ports, real-time
positions and historic vessel movements. A similar tool including ship vessel
movements is FleetMon.
However, it has still been impossible to fully contemplate the EU refineries input blend
by the shipments arriving in relevant ports as most of the times several crudes are
loaded from the loading port making it impossible to fully analyse the exact type of
crude a vessel is carrying. Furthermore, there is also the probability of double counting
of vessels particularly for voyages off Rotterdam.
In order to mitigate this uncertainty, the Consultant has finally used the information
filled in by Member States to DG ENER and elaborated it to identify which MCONs are
imported by each Member State on a country basis. Furthermore, the ports which
have crude oil terminals have been linked to the nearby refineries; therefore we may
approximate minimum and maximum distances of MCONs transportation from loading
port to the gates of EU refineries.
Pipeline transport
As discussed during Step 5, Europe is supplied crude oil via a complex pipeline system
of thousand kilometres starting from Western Siberia and supplying Central Europe.
The exact type of crude of the Druzhba pipeline cannot be defined with precision as
crude oil from various fields enters the pipeline and oil is unloaded in various refineries
on its length. Our analysis based on information from Argus and Platts has concluded
that the crude oil, with the same physical properties, transported via the Druzhba
pipeline is transported to 5 EU destinations. Background analysis of the upstream
Russian oil sector has indicated that the Druzhba pipeline carries on average 2/3 of oil
from the Urals area and 1/3 from the Western Siberia in general.
Modelling of midstream emissions in OPGEE
Following the identification of major pathways of imported oil in Europe, the GHG
emissions due to crude oil transport have been calculated using the OPGEE model.
Taking into consideration that each MCON, either via marine transport or pipeline, is
exported to several EU countries, the Consultant identifies the minimum, weighted
average and maximum distance of the followed route. In the context of the Interim
Report we have estimated the GHG emissions of the 5 most significant MCONS - in
terms of quantities delivered in EU. In this exercise the upstream and midstream
calculations for CI have been carried out and the indicative results will be presented in
the next Sections.
Represe
ntative
MCON
Arab
Oil field
Gwahar
Pathway
Min/max
MIN
Comments
Ghawar oil field -
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Pipeline
Total
(miles)
Marine
Total
(miles)
Tanker
size
(DWT)
93
4,375
100,000
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Represe
ntative
MCON
Light
Bonny
light
Bonny
light
Oil field
Pathway
Comments
Pipeline
Total
(miles)
Marine
Total
(miles)
Tanker
size
(DWT)
Ras Tanura - Agioi
Theodoroi
Agbada
Caw
Thorne
Channel
Novorossisk
Siberia
Light
Min/max
Interim Report
CENTRAL
Ghawar oil field Ras Tanura - Le
Havre
93
7,171
200,000
MAX
Ghawar oil field Ras Tanura Rotterdam
93
7,456
100,000
MIN
Agbada oil field Bonny terminal Huelva
42
4,215
135,000
CENTRAL
Agbada oil field Bonny terminal Trieste
42
5,704
135,000
MAX
Agbada oil field Bonny terminal Gothenburg
42
6,311
135,000
MIN
Caw Thorne
Channel oil field Bonny terminal Huelva
17
4,215
135,000
CENTRAL
Agbada oil field Bonny terminal Trieste
42
5,704
13,500
MAX
Caw Thorne
Channel oil field Bonny terminal Gothenburg
17
6,311
135,000
MIN
Samotlor - Surgut
- Perm - Ufa Samara - Saratov
Volgograd NovorossiskCostanza
1,880
504
135,000
CENTRAL
Romashkino Perm - Ufa Samara - Saratov
Volgograd NovorossiskTrieste
1,881
1,850
135,000
MAX
Samotlor - Surgut
- Perm - Ufa Samara - Saratov
Volgograd NovorossiskRotterdam
1,880
4,999
135,000
MIN
Samotlor - Perm Primorsk - Gdansk
1,862
699
100,000
CENTRAL
Samotlor - Perm Primorsk -
1,862
1,495
100,000
Samotlor
Primorsk
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Represe
ntative
MCON
Oil field
Pipeline
Total
(miles)
Marine
Total
(miles)
Tanker
size
(DWT)
Samotlor - Perm Primorsk - Megara
oil terminal
1,862
5,495
100,000
Germany
Samotlor - Surgut
- Perm - Plock Leuna
2,912
0
-
Poland
Samotlor - Surgut
- Perm - Plock
2,528
0
-
Czech
Republic
Samotlor - Surgut
- Perm - Ufa Almetyevsk Syzran - Unecha Mozyr - Uzhgorod
- Bratislava Kralupy - Litvinov
2,751
0
-
Slovakia
Samotlor - Surgut
- Perm - Ufa Almetyevsk Syzran - Unecha Mozyr - Uzhgorod
- Bratislava
2,983
0
-
Hungary
Samotlor - Surgut
- Perm - Ufa Almetyevsk Syzran - Unecha Mozyr - Uzhgorod
- Szazhalombatta
2,692
0
-
MIN
Romashkino Perm - Ufa Samara - Saratov
Volgograd NovorossiskCostanza
1,036
504
135,000
CENTRAL
Romashkino Perm - Ufa Samara - Saratov
Volgograd NovorossiskTrieste
1,036
1,850
135,000
MAX
Romashkino Perm - Ufa Samara - Saratov
Volgograd NovorossiskRotterdam
1,036
4,999
135,000
MIN
Romashkino Perm - Primorsk Gdansk
1,838
699
100,000
CENTRAL
Samotlor - Perm Primorsk -
1,838
1,495
100,000
Pathway
Min/max
Comments
Rotterdam
MAX
Novorossisk
Urals
Interim Report
Romash
kino
Primorsk
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Represe
ntative
MCON
Oil field
Pipeline
Total
(miles)
Marine
Total
(miles)
Tanker
size
(DWT)
Romashkino Perm - Primorsk Megara oil
terminal
1,838
5,495
100,000
Germany
Romashkino Almayetsk Syzran - Unecha Mozyr - Plock Schwedt - Leuna
1,888
0
-
Poland
Romashkino Almayetsk Syzran - Unecha Mozyr - Plock
1,504
0
-
Czech
Republic
Romashkino Almayetsk Syzran - Unecha Mozyr - Uzhgorod
- Bratislava Kralupy - Litvinov
1,727
0
-
Slovakia
Romashkino Almayetsk Syzran - Unecha Mozyr - Uzhgorod
- Bratislava
1,960
0
-
Hungary
Romashkino Almayetsk Syzran - Unecha Mozyr - Uzhgorod
- Szazhalombatta
2,040
0
-
MIN
Troll - Mongstad Gothenburg port Gotheburg refinery
86
439
80,000
CENTRAL
Troll - Mongstad Gothenburg port Wilhelshaven
86
583
80,000
MAX
Troll - Mongstad Trieste port Trieste refinery
86
4,055
80,000
Pathway
Min/max
Comments
Rotterdam
MAX
Troll
Interim Report
Troll B/C
Troll B/C
Table 3.12 presents the main information collected and assumed for the pathways of the
5 most significant MCONs imported in EU.
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Repres
entative
MCON
Arab
Light
Oil field
Pathway
Gwahar
Bonny
light
Bonny
light
Agbada
Caw
Thorne
Channel
Novorossisk
Siberia
Light
Comments
Pipeline
Total
(miles)
Marine
Total
(miles)
Tanker
size
(DWT)
MIN
Ghawar oil field Ras Tanura - Agioi
Theodoroi
93
4,375
100,000
CENTRAL
Ghawar oil field Ras Tanura - Le
Havre
93
7,171
200,000
MAX
Ghawar oil field Ras Tanura Rotterdam
93
7,456
100,000
MIN
Agbada oil field Bonny terminal Huelva
42
4,215
135,000
CENTRAL
Agbada oil field Bonny terminal Trieste
42
5,704
135,000
MAX
Agbada oil field Bonny terminal Gothenburg
42
6,311
135,000
MIN
Caw Thorne
Channel oil field Bonny terminal Huelva
17
4,215
135,000
CENTRAL
Agbada oil field Bonny terminal Trieste
42
5,704
13,500
MAX
Caw Thorne
Channel oil field Bonny terminal Gothenburg
17
6,311
135,000
MIN
Samotlor - Surgut
- Perm - Ufa Samara - Saratov
Volgograd NovorossiskCostanza
1,880
504
135,000
CENTRAL
Romashkino Perm - Ufa Samara - Saratov
Volgograd NovorossiskTrieste
1,881
1,850
135,000
MAX
Samotlor - Surgut
- Perm - Ufa Samara - Saratov
Volgograd NovorossiskRotterdam
1,880
4,999
135,000
MIN
Samotlor - Perm Primorsk - Gdansk
1,862
699
100,000
CENTRAL
Samotlor - Perm -
1,862
1,495
100,000
Min/max
Samotlor
Primorsk
Interim Report
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Repres
entative
MCON
Oil field
Interim Report
Pipeline
Total
(miles)
Marine
Total
(miles)
Tanker
size
(DWT)
Samotlor - Perm Primorsk - Megara
oil terminal
1,862
5,495
100,000
Germany
Samotlor - Surgut
- Perm - Plock Leuna
2,912
0
-
Poland
Samotlor - Surgut
- Perm - Plock
2,528
0
-
Czech
Republic
Samotlor - Surgut
- Perm - Ufa Almetyevsk Syzran - Unecha Mozyr - Uzhgorod
- Bratislava Kralupy - Litvinov
2,751
0
-
Slovakia
Samotlor - Surgut
- Perm - Ufa Almetyevsk Syzran - Unecha Mozyr - Uzhgorod
- Bratislava
2,983
0
-
Hungary
Samotlor - Surgut
- Perm - Ufa Almetyevsk Syzran - Unecha Mozyr - Uzhgorod
- Szazhalombatta
2,692
0
-
MIN
Romashkino Perm - Ufa Samara - Saratov
Volgograd NovorossiskCostanza
1,036
504
135,000
CENTRAL
Romashkino Perm - Ufa Samara - Saratov
Volgograd NovorossiskTrieste
1,036
1,850
135,000
MAX
Romashkino Perm - Ufa Samara - Saratov
Volgograd NovorossiskRotterdam
1,036
4,999
135,000
MIN
Romashkino Perm - Primorsk Gdansk
1,838
699
100,000
CENTRAL
Samotlor - Perm Primorsk -
1,838
1,495
100,000
Pathway
Min/max
Comments
Primorsk Rotterdam
MAX
Novorossisk
Urals
Romash
kino
Primorsk
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Repres
entative
MCON
Oil field
Interim Report
Pipeline
Total
(miles)
Marine
Total
(miles)
Tanker
size
(DWT)
Romashkino Perm - Primorsk Megara oil
terminal
1,838
5,495
100,000
Germany
Romashkino Almayetsk Syzran - Unecha Mozyr - Plock Schwedt - Leuna
1,888
0
-
Poland
Romashkino Almayetsk Syzran - Unecha Mozyr - Plock
1,504
0
-
Czech
Republic
Romashkino Almayetsk Syzran - Unecha Mozyr - Uzhgorod
- Bratislava Kralupy - Litvinov
1,727
0
-
Slovakia
Romashkino Almayetsk Syzran - Unecha Mozyr - Uzhgorod
- Bratislava
1,960
0
-
Hungary
Romashkino Almayetsk Syzran - Unecha Mozyr - Uzhgorod
- Szazhalombatta
2,040
0
-
MIN
Troll - Mongstad Gothenburg port Gotheburg refinery
86
439
80,000
CENTRAL
Troll - Mongstad Gothenburg port Wilhelshaven
86
583
80,000
MAX
Troll - Mongstad Trieste port Trieste refinery
86
4,055
80,000
Pathway
Min/max
Comments
Rotterdam
MAX
Troll
Troll B/C
Troll B/C
Table 3.12: Major pathways of the 5 most significant MCONs imported in Europe
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3.3.4
Interim Report
Downstream
Step 7: Estimation of GHG emissions during the refining process
This step refers to the calculation of the GHG emissions that are related to the refining
of crude oil. Figure 3.20 illustrates the location of the major refineries in EU. It can be
seen from the map that refineries are typically built close to ports or have their own port
terminals to ensure crude oil supply. Refineries located in Central Europe are supplied
crude oil primarily via the Druzhba pipeline or via small pipelines that are connected to
port terminals.
Figure 3.20: Location of major refineries in Europe
Actual emission data for the refining stage are available by each EU country from the
Environmental Energy Agency (EEA) and refer to the total emissions due to energy
branch consumption of fossil fuels by refineries. However, these emissions are not
assigned to each refinery output as it is required to calculate emissions over the life
cycle of mineral oil fuels. In addition, the refineries consume electricity and steam
which are partly self-produced and so involve GHG emissions directly as part of the
statistics on energy branch consumption of refineries and partly due to energy
purchased from the market; in this case the related GHG emissions are indirect. Also
refineries may also sell electricity and steam to third parties, as their own production
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facilities may be larger than refining needs require. Therefore, two more calculation
issues arise:


firstly to calculate total GHG emissions that directly and indirectly are
associated to refining needs in total;
secondly to allocate reasonably GHG emissions to each fuel output.
Allocation of direct and indirect emissions of a refinery
The first calculation requires data which are not directly available by Eurostat as the
statistics do not show separately sales of electricity and steam by the refineries but
only purchases of distributed steam and electricity. The fuels used for on-site
generation of steam in refineries are provided in statistics; however they are not
distinguished from similar fuels consumed by refineries for other purposes (e.g. in
boilers). Therefore, total steam generated by refineries is not known in the statistics. So
the methodology can rely only on Eurostat statistics for the assessment of the total
GHG emissions in the refining system of each European country. To fill this gap the
PRIMES model database has performed enrichment of the data on steam using the
CHP surveys by country available by Eurostat and other information sources (plant
inventory from Platts and other sources including a survey over concrete refinery
companies). Based on these extended statistics and using modelling of the entire
steam and electricity sector the PRIMES REFINERIES model calibration routine has
performed reconstitution of statistical data for past years (latest calibration year is
2010) in which the calibration routine estimates in detail how steam is produced in
refineries and which are the amounts of input and output of electricity as well as the
sales and purchases of these energy forms at the level of the entire refinery sector in
each European country. Based on these calibrated data for 2010 it is thus possible to
calculate total direct and indirect GHG emissions for the refinery sector in each
European country.
Allocation of GHG emissions to each product output
The second calculation stage is to allocate the total GHG emissions (direct and
indirect) to each product output from the refineries in each European country. This
requires a methodological approach because the allocation cannot be straightforward
as refining is a process using energy and feedstock to produce multiple product
outputs. The methodologies proposed in the literature range from simple approaches
based on average emission factors leading to an allocation on total emissions in
proportion to energy equivalent amounts of product outputs up to complex approaches
based on marginal emission factors derived from a modelling of the refinery process.
The second approach is generally superior from a methodological perspective but
requires more complex modelling and detailed information.
The intention of the Consultant is to apply the second approach and to exploit the
existing refining modelling framework of the PRIMES-Refineries model. For this
purpose the Consultant proceeded intensively in an extension of the model in order to
accommodate multiple crude oil types as inputs to the refinery modelling and also to
separate stylised refinery types and so capture more adequately the emission
estimation and the allocation of emissions to output products. Therefore, to calculate
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the GHG emissions that occur during refining, the Consultant will use an extended
modelling tool of the PRIMES-Refineries sub-model which has been developed and
maintained by E3MLab. The main purpose of following a model based analysis is
mainly to allocate to each refined petroleum product (for our analysis: diesel, petrol,
kerosene) a specific carbon intensity factor based on the estimation of marginal
emissions.
Refining of crude oils involves a range of different energy intensive processes that
produce multiple petroleum products. A large difference can be observed in product
yield, energy use and emissions between different refinery types depending on the type
of crude and the complexity of the refining technology. Model calibration techniques are
used to estimate product yields and the associated energy consumption and emissions
in stylised refinery types by country. The capacity data of refining processes have been
from the OGJ database which has been acquired for use in this study.
The use of a single configuration for European refineries is not appropriate because of
the diversity of refinery units, the crude feedstock and production yields. To account for
the large diversity, the PRIMES-Refineries model simulates stylised representative
refinery types to reflect the average flow scheme met in European refineries and to
capture the diversity. The refinery configuration includes major process units related to
separation, upgrading and conversion of crude oil. The modelling approach is based on
the fact that different products go through different processes within the refinery, thus
production flows are used to simulate the various streams leading to the products of
interest (petrol, diesel and kerosene).
The GHG emissions resulting from the feedstock refining are relevant to the type of
feedstock used by the refinery. The resulting GHG emissions from the petroleum
refining are therefore influenced by the energy intensity and the energy use by process.
In reality, a variety of crudes of different quality is fed in the refining industry. Refineries
process blends of crudes and adjust their processing conditions for the optimization of
products yields. In order to gain a better evaluation of the carbon intensity of crudes
with different characteristics, E3MLab will extend the PRIMES-Refinery model to
include different types of crude oils as an input to the stylised refinery types. In this
context, three broad categories have been already identified based on the API gravity
and sulphur content (Heavy, Medium, Light).
The reason for selecting API gravity and sulphur content as the key criteria for
distinguishing the crude types is that they indicate the quality of the crude and influence
the level and the conditions of processing. According to engineering data the API
gravity and sulphur content are the main features which can explain the diversity of
fossil fuel consumption, hence emissions, in the various types of refining processing.
Average emissions need to be partitioned to each individual petroleum fuel produced.
Most common approaches involve the emission allocation to the individual refinery
products based on the product proportion to the total quantity produced or based on
the energy content of the commodities. In order to associate emission factors with the
concrete refinery output products (diesel, petrol, kerosene) in a more adequate
manner, a methodology developed by the Institut Français du Pétrole (IFP) will be
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used. This method includes allocation of emissions to individual products based on
marginal emission content.
Step 8: Estimation of GHG emissions during transportation of refined products
This step presents the approach that is followed by the Consultant for calculating the
GHG emissions that take place during the transportation of the refined petroleum
products from the production point (i.e. the refinery) to the consumption point (i.e. filling
station). The transportation of the refined petroleum products from the refineries to the
filling stations in EU countries usually takes place via three modes: road freight, freight
rail and inland waterways, which are currently operating mainly on fossil fuels. The
share of each transport mode participating in the transportation of the refined
petroleum products differs by EU country; this implies that the carbon intensity during
transportation is different by country. The Consultant has further considered the fugitive
GHG emissions at the stage of the filling stations.
Data on the refined petroleum products transported by transport mode at a national
level (in tons and ton-kilometers) have been retrieved from EUROSTAT. Data on the
average carbon intensity per transport mode are drawn from the PRIMES-TREMOVE1
transport model, developed and maintained by E3MLab. The values used have also
been validated with the values reported in the TRACC2S database. Regarding the
fugitive GHG emissions at the level of the filling stations, the Consultant has used
typical emission factors from literature as illustrated in Table 3.13:
Period
Reloading of
tankers, kg
NMVOC per
tonne gasoline
Refuelling of
vehicles, kg NMVOC
per tonne gasoline
Sum of reloading
and refuelling, kg
NMVOC per tonne
gasoline
Source
19851990
1.26
1.52
2.80
Fennmann
&Kilde, 1994
1991
0.64
1.52
2.16
Fennmann
&Kilde, 1994
19921995
0.08
1.52
1.60
GB EMF,
Fennmann &
Kilde, 1994
1.38
Interpolation
between
1995 and
2000
1997
1.17
Interpolation
between
1995 and
2000
1998
0.96
Interpolation
between
1996
1
2
http://www.e3mlab.ntua.gr/e3mlab/PRIMES%20Manual/PRIMES%20TREMOVE_v3.pdf
http://traccs.emisia.com/
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Period
Reloading of
tankers, kg
NMVOC per
tonne gasoline
Refuelling of
vehicles, kg NMVOC
per tonne gasoline
Interim Report
Sum of reloading
and refuelling, kg
NMVOC per tonne
gasoline
Source
1995 and
2000
1999
20002007
0.08
0.46
0.75
Interpolation
between
1995 and
2000
0.53
GB EMF
Table 3.13: Emission factors of gasoline used for estimating fugitive emissions
from filling stations in Denmark (Source: NERI, 2009)
3.3.5
GHG emissions of refined products
The assessment of GHG emissions of refined products imported in EU has usually
been overlooked in relevant studies. In the context of this study, the emissions of
refined products imported from the United States and Russia will be assessed, as
these constitute significant part of EU final fuel supply as illustrated in Figure 3.21
below. It has to be mentioned also that some negligible quantities of refined products
are imported in EU from other countries (MENA) - which are constantly decreasing
over the years – so they are not taken into account in the analysis.
50000
45000
40000
USA - Total fuel oil
35000
USA - Kerosene
30000
USA - Gasoline
25000
USA - Gas/diesel oil
20000
Russia - Total fuel oil
15000
Russia - Kerosene
Russia - Gasoline
10000
Russia - Gas/diesel oil
5000
0
2008
2009
2010
2011
2012
Figure 3.21: EU 28 imports of refined products (in barrels of oil per day) for
specific refined products from Russia and USA (source: Eurostat)
The methodology for the assessment of emissions from refined products is shown in
Figure 3.22. The approach for the assessment of GHG emissions of imported refined
oil products is identical to that of conventional crude oil for the upstream and midstream
processes. The upstream emissions will be assessed through the collection of actual
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data and in the absence of these via the OPGEE model. Based on the analysis of the
midstream sector and given the locations of the Russian refineries it has been
considered that the MCON used for refining is exclusively Urals crude oil, while
refineries in USA use a blend of several MCONs. Thus, there are two major streams of
refined products to Europe: one from Russian and one from USA. In order to account
for the GHG emissions of these imported fuels during the refining process in Russia
and USA, the Consultant will use proxy values of emission factors based on calculation
of emissions for refineries in European countries provided that they have similar
refinery configuration to Russia and USA and other emission factor estimates based on
literature for refineries in Russia and USA which are different from European refineries.
Emissions due to the distribution of refined products will be assessed using the same
approach for oil products refined in EU. In all cases, a minimum and maximum
methodology will be used so as to represent a range of carbon intensity values where
applicable.
Figure 3.22: Methodology for the assessment of emissions from refined products
Imported products from Russian refineries
Table 3.14 summarizes the most significant Russian refineries supplying refined
products to Europe with their key characteristics such as capacity, crude type
feedstock, crude oil supply mode and ULSD compliance. It is worth considering that all
Russian refineries presented in Table 3.14 export or will start exporting Euro V - ULSD
compatible diesel to Europe.
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Refinery
Transport
mode of
final
product
Volgograd
refinery
Petroleum
products
are shipped
by rail, road
and river
transport
Lukoil
225,200
Kirishi
refinery
Sever
pipeline
Surgutne
ftegas
335,900
Perm
refinery
Rail road
and river
transport
and also
via the
Perm
Andreyenk
a –Ufa
pipeline
Lukoil
Sever
pipeline
TNK-BP
and
Gazprom
Neft,
Yaroslavl
Nizhnekam
sk Refinery
Owner
TAIF-NK
Capacity
(b/d)
279,142
Interim Report
Crude
supply
Crude
feedstock
Crude oil is
supplied to
the Refinery
via the
Samara –
Tikhoretsk
pipeline
Refines a
blend of light
WestSiberian and
Lower-Volga
crudes
ULSD compliance
Euro 5 compatible
Euro 5 compatible
Crude oil is
supplied to
the Refinery
via the
Surgut–
Polotsk
pipeline
&the
Kholmogory
–Klin
pipeline
Refines a
blend of
crudes from
the northern
part of Perm
Region
and from
Western
Siberia
Output of Euro 5 ULSD
fuel will increase by
325,000 tons per year.
8,700
The refinery
processes
West
Siberian
Crude
From January 2012, the
Refinery, intends to stop
producing motor fuels,
which do not conform to
the Euro 4/ Euro 5
standards
120,493
The refinery
processes
locally
produced
crude oil &
gas
condensate
The crude is
medium
heavy & sour
Since May 2008, TAIFNK completely shifted to
the production of motor
gasoline, environmental
standards EURO 4
Since June, 2012 TAIFNK switched to 100%
diesel fuel, quality
standard EURO 5
Table 3.14: Russian refineries exporting ULSD to Europe (source: OGJ, company
websites)
Figure 3.23 below shows the location of Russian refineries on the map and links them
to major crude oil pipelines. It can be obtained that all of them are supplied oil primarily
from the Urals region and therefore the Urals MCON has been considered as their
main feedstock. Moreover, the largest part of refined products is supplied to Europe via
the Sever product pipeline which runs alongside the Baltic pipeline System. The
conduit links several refineries in European Russia to the Baltic Sea, thereby giving
them a means of exporting ULSD fuel. More specifically the pipeline runs from Kstovo
to Primorsk via Yaroslavl and Kirishi with a total length of 1056 km. From Primorsk the
refined products are shipped to several European countries.
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Imported products from USA refineries
In the context of the Interim Report, the Consultant has focused particularly on the
refined products arriving to Europe from Russia, because of the fact that less work has
been conducted in the analysis of the Russian upstream and midstream sector and
therefore more effort is required. On the contrary, for the United States there is a
wealth of information regarding upstream, midstream and downstream sector, as well
as their emissions. For refined products arriving from the United States the Consultant
will assume that these are refined in a High Conversion refinery located on the US Gulf
Coast and exporting diesel oil to Europe, with main discharge port being Rotterdam. A
typical input blend of a US refinery based on the work conducted by Jacobs3 is
illustrated in Table 3.15.
Figure 3.23: Map of Russian Refineries supplying refined products to EU
3
EU Pathway Study: Life Cycle Assessment of Crude Oils in a European Context, Jacobs Consultancy,
2012
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MCON
High conversion US Gulf Coast
Forties
√
Arab Medium
√
Bonny Light
√
Tupi
√
Bachaquero
√
Urals
√
SCO from Coking upgrader processing mined bitumen
√
Athabasca dilbit
√
Athabasca bitumen
√
Mariner
√
Table 3.15: Overview of feedstock input of representative US refinery (adopted
by Jacobs, 2012)
3.3.6
GHG emissions of unconventional crude oil and natural gas
At the end of the baseline year of the study (2012) unconventional fuels are not traced
in the EU energy balance. However, it is expected that unconventional crude oil and
natural gas will definitely be imported in Europe in the future. Therefore, the GHG
emissions assessment is not priority regarding the estimations and analyses of Tasks b
and c, but it will be helpful and complementary to the projections of Task f. The
PRIMES model will indicate the quantities of unconventional crude oil and natural gas
that Europe will be importing by 2030.
The rationale for the assessment of the GHG emissions from unconventional crude oil
is similar to that of crude oil. The Consultant based on current market trends, literature
survey and its own assessments will determine the MCONs and the gas streams which
constitute reasonable options for the EU relevant demand projected by the PRIMES
model. Indicatively, key unconventional MCONs or gas streams that are representative
will be analyzed could be the following:




Alberta Oil Sands
Venezuela Bitumen
US Barnett Shale Gas
Marcellus Shale Gas
Actual emission data for the assessment of upstream emissions of unconventional
crude oil have been searched and collected for all the above mentioned characteristic
cases. Due to the CARB analyses and the studies assigned by the US and Canadian
authorities, expressing their interest to promote the unconventional oil and gas
resources, there is availability of actual data and measurements carried out by reliable
institutions. The OPGEE model might be also used for the modelling of upstream
emissions of unconventional crudes, since it has already incorporated five production
techniques specified by the type of extraction and the upgrading technology, namely:

Bitumen mining with integrated upgrading;
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



Interim Report
Bitumen mining with non-integrated upgrading;
In situ production via non-thermal methods;
In situ production via steam assisted gravity drainage;
In situ production via cyclic steam stimulation.
It has to be noted that there are several techniques for processing and upgrading
unconventional crude oils and gases but it is anticipated that processes internally built
in OPGEE and GHGenius will suffice for modelling the GHG emissions of certain
MCONs and gas streams. In addition to the two models, there is a large variety of
information regarding the upstream emissions of unconventional crudes that can be
utilized for the assessment of GHG emissions, as well as for comparative and
validation purposes. Several studies, particularly from the USA and Canada, have
assessed the LCA GHG emissions.
The midstream GHG emissions occurring due to the transport of crude oil and gas (in
principle through LNG) from the extraction point to the refineries or the transmission
systems will be assessed utilizing the same approach as for conventional crude oil and
natural gas. In the case that three unconventional fuels are considered 3 representative
upstream cases with relevant minimum and maximum values will be assessed.
Eventually, the emissions of approximately 10-15 streams will be considered in total:


two per final oil product (petrol, diesel and kerosene), 6 in total and
8 in total for CNG/LNG distributed to the four EU regions, in compliance to the
study assumptions.
Lastly, distribution emissions will be calculated by using the approach and the emission
factors as for conventional crude oil and natural gas.
METHODOLOGICAL APPROACH FOR NATURAL GAS GHG
ASSESSMENT
3.4
3.4.1
Natural gas supply chain
Oil and natural gas systems encompass wells, gas gathering and processing facilities,
storage, and transmission and distribution pipelines. These components are all
important aspects of the natural gas cycle—the process of getting natural gas out of
the ground and to the end user, which can generally be broken out into five sectors.
Each sector is defined as follows:



Production, focuses on taking raw natural gas from underground formations.
Processing, focuses on stripping out impurities and other hydrocarbons and
fluids to produce pipeline grade natural gas that meets specified tariffs (pipeline
quality natural gas is 95-98 % methane).
Transport, focuses on the movement of natural gas from the producing region
to the consuming region. After processing, gas is often transported over very
large distances. Most of this transport takes place through pipelines, although,
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there is a significant amount of gas that is liquefied at the producing region,
transported via marine vessels as LNG (Liquefied Natural Gas) and finally
regassified at the delivery point. Therefore, we distinguish two options for
natural gas transport:
 Via Pipeline,
 Via LNG
Transmission and Storage, focuses on delivery of natural gas from the
interconnection point to city gate stations or industrial end users. Transmission
occurs through a network of high-pressure pipelines. Natural gas storage also
falls within this sector. Natural gas is typically stored in depleted underground
reservoirs, aquifiers, and salt caverns.
Distribution, focuses on the delivery of natural gas from the major pipelines to
the end users (e.g., residential, commercial and industrial).
In the oil industry, some underground crude contains natural gas that is entrained in the
oil at high reservoir pressures. When oil is removed from the reservoir, associated or
solution natural gas is produced. In case the exploration field produces in principle
natural gas, then this gas might be called non-associated gas. Both associated and
non-associated gas are considered conventional natural gas as part of this work. The
basic pathways of the typical natural gas supply chain are presented in Figure 3.24.
Figure 3.24: Natural gas supply chain (Source: CE, Delft)
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Methodology for assessing GHG emissions
The main stages of the natural gas value chain to be examined for the purpose of the
present study are presented in Figure 3.25. As shown in this Figure, the lifecycle of
natural gas is divided into 3 main stages: upstream, midstream and downstream.
The upstream stage contains the natural gas production and processing sectors.
The midstream stage contains the transport of natural gas from the producing region to
the consuming region for which there are three options:



Option 1: The gas produced outside the EU is transported via pipeline to the
corresponding EU regions;
Option 2: The gas produced outside the EU is liquefied and transported by
vessels to the corresponding EU LNG terminals, where it is re-gasified and fed
to the transmission system;
Option 3: The gas produced indigenously in the EU is either consumed within
the producing country, or transported to other EU countries through the
interconnected transmission systems.
Finally, the downstream stage contains the transmission and distribution of natural
gas inside the EU regions.
Figure 3.25: Natural gas streams methodological approach
Following this approach, the EU natural gas supply has been distinguished into main
streams according to their origin, mode of transport and delivery point within the EU
that will be presented in the following Sections. The carbon intensity (CI) of the
considered natural gas streams is estimated as the sum of the carbon intensities of
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each of the corresponding separate stages (upstream, midstream, downstream) that
characterise each stream.
3.4.3
Natural Gas Streams
Step 1: Assumption for EU regions
The starting point for assessing the GHG emissions of natural gas supplied to the EU is
to define the main gas streams arriving to the consumption regions. We need to keep a
rational number of gas streams that will allow obtaining a reasonable and
representative picture of GHG emissions of the main gas streams supplying EU and on
the other hand maintaining the necessary detail by distinguishing the CI performance
and differentiation of various gas streams. To this end we need to make a number of
assumptions, and under the most significant of them, EU has been divided into 4
consuming regions, namely South East EU, Central EU, North EU and South West EU.
The four groups were selected in principle on the basis of common natural gas
characteristics, e.g. common transportation pipelines or LNG suppliers. Thus in our
analyses the gas streams under assessment are driven to 4 destinations instead of 26;
with this aggregation we achieve relevant grouping of similar, more or less, CI cases in
downstream and midstream, without losing in detail and differentiation of results.
In the context of the present study, Cyprus and Malta were not taken into account for
the assessment of GHG emissions in the natural gas value chain, as they were not
natural gas consuming countries in 2012.
Step 2: Natural gas producing countries
In order to determine the major natural gas suppliers of the EU, the Consultant has
elaborated on the annual IEA data for 2012 regarding natural gas imports and
indigenous production by country of origin. These imports and EU production are
transported to the national transmission systems either through LNG or by
transportation pipelines. Small quantities of gas imports or production (in general less
than 500 million cubic meters per year) were considered negligible and will be not
examined in detail in this study. Such small quantities are generally transacted in the
spot market and thus are not representative of the EU natural gas supply. Following
this analysis, the major natural gas suppliers to the EU are presented in Table 3.16.
Step 3: Finalization of the natural gas streams
After eliminating the negligible quantities of natural gas consumed within the EU, the
Consultant has identified the main streams of natural gas arriving to each of the four
EU regions. The final streams are illustrated in Figures Figure 3.26 to Figure 3.28.
Therefore 29 transport pipeline streams and 9 LNG streams are considered for GHG
emissions assessment. Since there are 4 main pipeline systems supplying EU with
Russian natural gas, this fact is taken into consideration and either distinguished
streams by pipeline are considered or in case of small differences in CI the streams are
aggregated and the min, max approach is used to cover small differences and
uncertainties.
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Supplier
Share in the EU gas supply
In 2012
Germany
2.59%
Denmark
1.17%
Netherlands
17.08%
Poland
1.25%
Hungary
0.29%
Italy
1.74%
Romania
2.21%
UK
8.23%
Russia
22.61%
Norway
20.34%
Algeria
6.84%
Libya
1.30%
Other
3.93%
Algeria LNG
2.05%
Norway LNG
0.53%
Nigeria LNG
2.22%
Qatar LNG
5.63%
Local production
Transport by pipeline
LNG transported by
marine vessels
Table 3.16: Major natural gas suppliers of the EU
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Figure 3.26: Natural gas streams arriving to the South East EU region
Figure 3.27: Natural gas streams arriving to the North EU region
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Figure 3.28: Natural gas streams arriving to the South West EU region
Figure 3.29: Natural gas streams arriving to the Central EU region
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Upstream
The upstream stage includes exploration and drilling, extraction of natural gas and
processing.
Exploration and drilling represent a small percentage of the total GHG emissions of the
lifecycle of natural gas and in addition, emissions data for this stage are very hard to
identify. Exploration cannot be directly linked to production. Some exploration will lead
to production, some will not. This means that it is hard to include exploration in a
lifecycle approach that tries to assess environmental impacts associated with a unit of
natural gas. Therefore, exploration is the least significant stage in the lifecycle of
natural gas, in terms of GHG emissions.
Extraction of non-associated natural gas requires little more energy than letting the gas
flow from the reservoir. Extraction of non-associated natural gas gives a mixture of raw
gas, condensed higher hydrocarbons, free water and carried along particles. The raw
gas is isolated from solids and fluids by flashing, the so-called primary separation. The
isolated raw gas will have an elevated temperature due to the higher temperatures in
the reservoirs and a pressure of several to several hundreds of bars. It does not yet
have sufficient quality to allow transportation to the consumer for application.
Further processing basically involves the separation of the methane fraction (CH4) in
the raw gas from co-products or pollutants such as:





Water vapour
Acid gases (CO2, sulphurous compounds)
Nitrogen (N2)
Condensable hydrocarbons (C5+)
Ethane, propane, butane.
Which processes are applied depends on raw gas quality as well as required standard
for the processed gas. Energy consumption and emissions at the processing stage
depend on the quality of the raw natural gas. Gas from fields yielding low calorific gas
may be mixed with high calorific gas to match required market standards. The
hydrocarbons heavier than methane but lighter than pentane do not necessarily have
to be separated, except for the production of some chemicals. They may be separated
for economic reasons, as ethane and LPG (propane/butane) are excellent naphtha
cracker feedstock and LPG (as well as C5+) may be sold as automotive fuels. Isolation
of the so-called Natural Gas Liquids (NGL) can be economically viable in certain
regions with a high demand and low (alternative) supply. The chemical composition of
these hydrocarbons (NGL) is similar, yet their applications vary widely. Ethane
occupies the largest share of NGL field production. It is used almost exclusively to
produce ethylene, which is then turned into plastics. Much of the propane, by contrast,
is burned for heating, although a substantial amount is used as petrochemical
feedstock. A blend of propane and butane, sometimes referred to as LPG or autogas is
a popular fuel in some parts of Europe, Turkey, and Australia; however LPG is not
among the transport fuels considered in this study. Natural gasoline (pentanes plus)
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representing 10-15% of NGL can be blended into various kinds of fuel for combustion
engines, and is useful in energy recovery from wells and oil sands. Natural Gas Liquids
(NGL) representing partly a feedstock used in refineries or blended to produce petrol
have not been considered as independent streams in this study, but are considered as
contributing to the GHG emissions produced in the oil refining process.
In the case of associated gas, the natural gas may already be separate from the oil
(free gas) or it may be dissolved in the oil (dissolved gas). Extra steps are involved in
either case to separate the gas before processing takes place.
Most treatment processes require electricity for valves, pumps, etc. The electricity is
often produced on site in case of off shore production and treatment or in case of fields
located in remote areas. Otherwise electricity may be taken from the grid.4
Venting and flaring gas
One of the most important GHG emitting activities of the upstream stage is gas flaring
and venting. Flaring is the controlled burning of natural gas in the course of routine oil
and gas production operations. This burning occurs at the end of a flare stack or boom.
Gas processing plants remove the water, H2S, CO2 and natural gas liquids from the
raw natural gas to produce the market-ready natural gas. Flares are used to dispose of
the unmarketable gases. All gas plants have flares to burn off gas safely during
emergencies or "upset" conditions that interrupt the normal day-to-day operations.
Many of the small plants are licensed to flare H2S rich gas after it has been removed.
Venting is the controlled release of gases into the atmosphere in the course of oil and
gas production operations. These gases might be natural gas or other hydrocarbon
vapours, water vapour, and other gases, such as carbon dioxide, separated in the
processing of oil or natural gas.
Flaring produces predominantly carbon dioxide emissions, while venting produces
predominantly methane emissions. The two gases have different effects, however. The
global warming potential of a kilogram of methane is estimated to be twenty five times
that of a kilogram of carbon dioxide when the effects are considered over one hundred
years (GWP 2007). When considered in this context, flaring will generally be preferred
over venting the same amount of gas in the design of new facilities where sufficient
amounts of gas will be produced to run a flare.5
Natural gas producers
The main natural gas producers for the EU 28, apart from indigenous production, are
Russia, Norway, Algeria, Nigeria, Qatar and Libya. Intra-EU producers include the
Netherlands, Germany, the UK, Denmark, Italy, Hungary, Poland and Romania. Figure
3.30 illustrates the main natural gas producing fields supplying the EU.
4
5
The Natural Gas Chain - Toward a global life cycle assessment, Delft, CE, 2006
Flaring & venting in the oil & gas exploration & production industry, OGP Report No: 2.79/288 January 2000
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Each producing country has its own characteristics regarding their upstream activities,
which are summarized in Table 3.17.
Figure 3.30: Map of natural gas producing fields supplying the EU
Producing
country
Russia
Norway
Major natural
gas fields
Characteristics
Yamburg –
Urengoy
Yamal
Medvezh’ye
Russia's reserves account for about a quarter of the
world's total proven reserves. The majority of these
reserves are located in Siberia, with the Yamburg,
Urengoy, and Medvezh'ye fields alone accounting for
more than 40% of Russia's total reserves, while other
significant deposits are located in northern Russia.
Troll
The majority of Norwegian gas fields are offshore
platforms located in the North Sea.
Despite maturing major natural gas fields in the North
Sea, Norway has been able to sustain increases nearly
every year in total natural gas production since 1993 by
continuing to develop new fields.
Norway's largest producing natural gas field is Troll,
which according to estimates from the NPD represented
about 27% of Norway's total natural gas production in
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Characteristics
2013. The three other largest producing fields in 2013
were Ormen, Lange Asgard and Kvitebjorn. These four
fields accounted for just over 60% of Norway's total dry
natural gas production in 2013.
Algeria
Nigeria
Qatar
Libya
Hassi R'Mel
Algeria's largest natural gas field, Hassi R'Mel, was
discovered in 1956. Located in the center of the country
to the northwest of Hassi Messaoud, it holds more than
half of Algeria's total proved natural gas reserves.
According to the Arab Oil & Gas Journal, Hassi R'Mel
accounted for three-fifths of Algeria's gross natural gas
production in 2012. The remainder of Algeria's natural
gas reserves is located in associated and nonassociated fields in the southern and south eastern
regions of the country.
Hassi R’Mel also serves as a gathering point for natural
gas from other gas fields located in the Algerian desert.
Escravos
Nigeria is the largest holder of natural gas proven
reserves in Africa and the ninth largest holder in the
world, while ranked as the world's 25th largest natural
gas producer. Natural gas production is restricted by the
lack of infrastructure to monetize natural gas that is
currently being flared. The majority of the natural gas
reserves are located in the Niger Delta.
North field
Qatar was the world's fourth largest dry natural gas
producer in 2012 (behind the United
States, Russia, and Iran), and has been the world's
leading liquefied natural gas (LNG) exporter since 2006.
Qatar is also at the forefront of gas-to-liquids (GTL)
production, and the country is home to the world's
largest GTL facility.
Nearly all of Qatar's natural gas production comes from
the North Field, which is part of the largest nonassociated natural gas field in the world.
The Qatari North Field contains about 25 trillion cubic
meters (Tcm), which accounts for 14% of worldwide
natural gas reserves. The South Pars field, a geologic
extension of the North field, contains an estimated 8
trillion cubic meters (Tcm) of natural gas. Thus, this
single accumulation contains about 20% of the world's
natural gas reserves. Based on current production
capacity, the North field has reserve-production ratio of
more than 400 years.
Wafa
Bahr Es Salam
Libya is the fourth largest natural gas reserve holder in
Africa.
Libya’s natural gas production and exports increased
considerably after 2003 with the development of the
Western Libya Gas Project and the opening of the
Greenstream pipeline to Italy. Flows through the
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Characteristics
Greenstream pipeline were disrupted during most of the
2011 civil war.
Netherlands
UK
Germany,
Denmark, Italy,
Hungary, Poland
and Romania
Groningen
The Netherlands is the second-largest producer and
exporter of natural gas in Europe, following Norway.
Most of its natural gas fields are located offshore in the
North Sea, although a number of them are located
onshore, including Groningen, one of the ten largest
natural gas fields in the world. The government has
capped production at Groningen, which accounts for
approximately 75% of the country's natural gas output
as part of a policy to stem reserve declines and
encourage production from smaller fields.
ShearwaterElgin area
SAGE
The UK is the second largest producer of natural gas in
EU. Most of the UK natural gas reserves occur in three
distinct areas: 1) associated fields in the UKCS; 2) nonassociated fields in the Southern
Gas Basin, located adjacent to the Dutch sector of the
North Sea; and 3) non-associated fields in the Irish Sea.
The largest concentration of natural gas production in
the UK is the Shearwater-Elgin area of the Southern
Gas Basin. The area contains five gas fields: Elgin,
Franklin, Halley, Scoter, and Shearwater. UK's largest
share of natural gas production among all fields and
gathering systems comes from the Scottish Area Gas
Evacuation (SAGE) system, which produced a total of
6.9 billion cubic meters (bcm) in 2011. In addition to
SAGE, the Shearwater-Elgin Area Line
(SEAL) produced more than 5.6 bcm of natural gas
during the year.
multiple
These EU countries have small domestic oil and natural
gas production and rely heavily on imports. However,
their indigenous production covers an important share of
their internal natural gas demand while in some cases
export to their neighboring countries.
Table 3.17: Key characteristics of natural gas producing countries supplying
the EU 28
3.4.5
Midstream
The midstream stage concerns the transport of natural gas from the producing region
to the consumption region. There are two ways of transportation of natural gas to the
EU entry points: long distance pipelines from third countries and LNG tankers, whereas
indigenous production flows through the EU transmission systems. The latter will be
considered in the downstream stage as it utilizes the interconnected transmission
systems of EU countries to reach its destination, therefore the related GHG emissions
are linked to the transmission network of each EU country.
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In the case of transport via pipeline, the midstream stage includes the route carrying
the natural gas from the processing plant to the EU entry point. The total pipeline
“system” may consist of the pipeline, compression stations, import/export stations and
metering. Normally, pipeline diameters range from 25 to 150 cm.
Before transport, gas is compressed to pressures of approximately 70 bar. In the case
of subsea pipelines, the initial pressure may be higher (more than 200 bar) due to the
impossibility of intermediate transfer compression. Pressure loss due to friction of gas
along the pipeline wall is compensated by intermediate compressor stations along the
pipeline. Compressors are almost always driven by natural gas, as this is obviously
easily available.
Apart from energy consumption for the transport itself, maintenance and check-up
activities – especially in remote areas – may require energy. Another source of gas
‘consumption’ during transport is leakage. As the gas, methane, is a powerful
greenhouse gas, leaks may have a significant environmental effect.
For international gas pipelines, the major environmental impact comes from the gas
combustion to run the compressor stations. The impact is larger with increased
distance. Some of the critical points in the transmission process for gas consumption
are turbine compressors that burn natural gas at compressor stations along the way,
electric motors and gas engines, power generation, and leaks of methane gas –
fugitive emissions – during transmission. Fugitive emissions are a major component of
GHG emissions from natural gas systems, however they are often difficult to accurately
identify.
In the case of LNG production, the midstream stage includes also the transportation
of natural gas to the liquefaction plant and the process of liquefaction. Liquid natural
gas (LNG) is natural gas cooled to a low temperature (-162oC) so it becomes a liquid
that hence occupies a much smaller volume. It can be transported over long distances
without the need for a fixed infrastructure. The LNG process consists of several steps:
liquefaction, transport, storage, and regasification.
Liquefaction of LNG means cooling the natural gas to below its condensation
temperature of –162°C. The heavier hydrocarbon components in the natural gas
condense at higher temperatures and are therefore liquefied – and removed – during
the process. LNG often consists of both methane and ethane, the latter re-added to
fluid methane after methane liquefaction (ethane liquefying before methane does). Byproducts of LNG production are LPG and gasoline, the heavier fractions of the raw
natural gas.
The LNG is stored in full containment tank normally consisting of a concrete outer tank
and an inner tank of 9% nickel steel. The boil-off gas and pre-cooling and loading
vapours are compressed and used as fuel gas for the liquefaction units or flared.
Transportation to and from storage is driven by pumps. Storage may also take place at
other stages in the LNG chain (after international transport or before regasification).
Again, boil-off gas is mostly put to use, but may be vented in emergencies.
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Long-distance transport of LNG takes place primarily by cargo ships with an insulation
system to keep the temperature at -162oC. The LNG is often carried in separate tanks.
Boil-off gas provides a large fraction of the fuel need for the ship, also on the return
journey when some LNG is left in the tanks to ensure that the gas concentration in the
tanks is above the upper explosion limit (UEL).
Regasification consists of increasing the LNG temperature often by heat exchange with
(sea) water at roughly ambient temperature or heated. The gas is then ready to be
transported in the regular regional transmission and distribution network after quality
control. The major functions of LNG receiving terminals are: (1) regasification of
liquefied natural gas, (2) in some countries, calorific value adjustment by adding LPG,
and (3) pressurization of the natural gas for supply to customers. These processes all
use energy.
The above described two supply chains differ not only from the physical and
economical point of view, but also from the environmental one. In order to transport the
gas from the production fields to Europe, energy is required and its overall amount
differs according to the way and the path the gas is imported. Furthermore other
factors, like methane fugitives and nitrous oxide emissions, are affected not only by the
physical characteristics of the chain, but also from the technology used and from
obsolescence of installations.6
Figure 3.31 presents the geographical locations of liquefaction plants supplying the EU
28 with LNG, as well as the EU importing terminals.
In the following paragraphs, the major natural gas supply routes to the EU are
presented according to the corresponding producing country and mode of transport.
6
The Natural Gas Chain - Toward a global life cycle assessment, Delft, CE, 2006
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Figure 3.31: Map of LNG supply of the EU including liquefaction plants and
importing terminals
Russia
Transportation of Russian natural gas to Europe proceeds through several pipelines,
connecting gas fields in the North of Russia through the United Gas transportation
system to the European countries. Figure 3.32 presents the main natural gas export
pipelines from Russia to Europe.
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Figure 3.32: Map of major Russian natural gas pipelines arriving to Europe
(Source: Wikipedia)
The “Brotherhood” pipeline (Urengoy-Pomary-Uzhgorod) is the largest gas
transportation route. It can carry over 100 bcm gas per year, transiting Ukraine and
running to Slovakia. In Slovakia, the pipeline is split and one branch goes to the Czech
Republic. Russian gas transported through the Czech Republic flows in the direction of
Waidhaus and Hora Svaté Kateřiny via Uzhgorod, as well as from the Yamal-Europe
gas pipeline, with Olbernhau and Brandov as entry points. Its second branch goes to
Austria. This country plays an important role in the delivery of Russian natural gas to
Italy, Hungary, Slovenia and Croatia. Gas deliveries through this pipeline started in
1967.
The Yamal-Europe pipeline runs across Russia, Belarus and Poland reaching
Germany. Its length is beyond 2,000 km, 14 compressor stations are operational along
it. The pipeline construction began in 1994 close to the German and Polish borders,
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and first sections of the pipeline were brought online as early as in 1996. The
Belarusian part where Gazprom has become the sole investor was commenced in
1997. Upon commissioning of the last compressor station in 2006, Yamal – Europe
reached full capacity – 33 billion m3 per annum.
The South East gas transportation route through Romania carries Russian gas to this
country, transiting Ukraine and Moldova, and runs further to the Balkan countries and
Turkey. The pipeline construction began in 1986, and the second line was added in
2002.
Furthermore, the consumers in Finland receive Russian gas through the gas
transportation system in the Leningrad Region.
The Nord Stream offshore pipeline laid on the bottom of the Baltic Sea with capacity of
55 bcm per year allows direct gas transportation for clients in Western Europe,
primarily in Germany, bypassing transit states.7
Norway
All gas pipelines on the Norwegian Continental Shelf with third party customers are
owned by a single joint venture, Gassled, with regulated third party access. The
Gassled system is operated by the independent system operator, Gassco AS, a
company wholly owned by the Norwegian State. In 2010, the Gassled system
transported 97.3 bcm of gas to Europe.
Norway operates several important natural gas pipelines that connect directly with EU
countries, specifically France, the United Kingdom, Belgium, and Germany. The most
important pipelines are:






Franpipe, with a capacity of 19.85 bcm/y, exports gas to Dunkirk, France.
Zeepipe I, IIA, and IIB have a total capacity of 68.18 bcmy and transport gas to
Zeebrugge, Belgium.
Europipe I and II, with a total capacity of 42.2 bcm/y, export to Dornum,
Germany.
Norpipe, with a total capacity of 11.54 bcm/y, runs to Emden, Germany.
Vesterled, capacity 14.06 bcm/y, links to St. Fergus, Scotland.
Langeled, capacity 25.98 bcm/y, links to Easington on the east coast of
England.
In 2010, the Gassled system was again expanded through the merger with the Gjøa
Gas Pipeline. When new gas infrastructure facilities are merged into Gassled, the
ownership interests are adjusted in relation to the relative value of the assets and each
owner's relative interest.8
7
8
Gazprom website
Statoil website
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Figure 3.33 depicts the natural gas pipelines reaching the EU from the Norwegian
Continental Shelf.
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Figure 3.33: Map of the Norwegian Continental Shelf natural gas pipelines
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Algeria
Algeria was the first country in the world to export LNG in 1964. Algeria exports natural
gas to Europe via pipelines and on tankers in the form of liquefied natural gas (LNG). It
has three transcontinental export gas pipelines: two natural gas transport pipelines to
Spain and one to Italy. Algeria's LNG plants are located in the coastal cities of Arzew
and Skikda. Figure 3.34 presents the map with the main locations and pipelines of the
Algerian gas system. In this map, the MEDGAZ pipeline appears as “under
construction”, although it has been operating since 2011.
Figure 3.34: Algerian natural gas transport pipelines map (Source: Sonatrach)
LNG production
In 2013, Algeria was the world's seventh-largest exporter of LNG, accounting for about
5% of the world's total exports. Algeria has liquefaction units located along the
Mediterranean Sea at Arzew and Skikda, with a total design capacity to process almost
96 million cubic meters per day of natural gas. The considered LNG streams from
Algeria arriving to Europe consist of a pipeline leading the natural gas from the
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producing fields to the liquefaction plants and secondly marine vessel transportation.
The corresponding GHG emissions of these streams will be estimated as a
combination of these two modes of transport.
Algeria's domestic natural gas pipeline system transports natural gas from the Hassi
R'Mel fields and processing facilities, owned by Sonatrach, to export terminals and
liquefaction plants along the Mediterranean Sea. There are two main domestic pipeline
systems transporting natural gas to the liquefaction terminals: (i) the Hassi R'Mel to
Arzew system which is a collection of pipelines that move natural gas from Hassi R'Mel
to the export terminal and the LNG plant at Arzew and the Hassi R'Mel to Skikda
system which transports natural gas from the Hassi R'Mel fields to the Skikda LNG
plant.
Pipeline transport
Besides LNG, Algeria transports natural gas to Spain and Italy via three major
pipelines. The largest pipeline, Pipeline Enrico Mattei (GEM), came online in 1983 and
runs 1,650 km from Algeria to Italy via Tunisia. GEM's capacity is more than 36 bcm
per year and it is jointly owned by Sonatrach, the Tunisian government, and Eni. The
Pedro Duran Farell (GPDF) pipeline started in 1996 and travels 525 km to Spain via
Morocco. GPDF's capacity is about 11 bcm per year. The newest pipeline, MEDGAZ,
came online in 2011 and is owned by Sonatrach, Cepsa, Endesa, Iberdrola, and GDF
Suez. It stretches 200 km onshore and offshore, from Algeria to Spain via the
Mediterranean Sea.
Qatar
Qatar is the world's largest producer of (LNG), accounting for about 15% of world
liquefaction capacity. Nearly all of Qatar's natural gas production comes from the North
Field, which is part of the largest non-associated natural gas field in the world, although
some smaller fields contribute production volumes as well.
Most of the field lies about 3,300 meters below the Arabian Gulf in water depths of
about 65 meters, and is intersected by the Qatar-Iran border. The field spans 9,700
square kilometres. The Qatari North Field portion covers an area of over 6,000 square
kilometres, almost half of the entire surface area of Qatar.
With a limited demand for domestic consumption, Qatar Petroleum (QP), the stateowned company, and its international business partners have aggressively developed
export markets. Most exports are in the form of liquefied natural gas (LNG).
Qatar's natural gas liquefaction facilities and related industries are located in Ras
Laffan Industrial City, site of the world's largest LNG export facility. Ras Laffan is a selfcontained city built by the government to support the processing and export of natural
gas.
Figure 3.35 presents the major energy infrastructure in Qatar.
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Figure 3.35: Qatar energy infrastructure map (Source: EIA)
Libya
Libya's rank as a producer and reserve holder is less significant for natural gas than it
is for oil. Most of its natural gas production is exported to Italy via pipeline. OGJ
estimated that Libya's proved natural gas reserves were 1.5 trillion cubic meters,
making it the fourth largest natural gas reserve holder in Africa.
Libya's capacity to export natural gas increased dramatically after October 2004, when
the 595 km Greenstream pipeline came online. The pipeline starts in Mellitah, where
natural gas piped from the onshore Wafa and offshore Bahr Es Salam fields is treated
for export. It runs underwater to Gela, on the island of Sicily, and the natural gas flows
onward to the Italian mainland (Figure 3.36). The Greenstream pipeline is operated by
Eni in partnership with NOC. According to PFC Energy, total capacity is 11 billion cubic
meters per year since the most recent capacity expansion.
Natural gas exports via Greenstream were completely suspended for nearly eight
months from March 2011 to mid-October 2011 due to the civil war. Exports partially
recovered to 228 Bcf in 2012, albeit lower than the 2010 level of 332 Bcf, according to
the BP 2013 Statistical Review.
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Figure 3.36: Map of the Greenstream pipeline
UK
The UK, in spite of being an EU 28 country, because of its geographical characteristics
(not part of inland Europe), has several international pipelines, interconnecting it to the
rest of the EU. The main pipeline exporting natural gas from the UK to the rest of the
EU is the Interconnector pipeline which runs between Bacton, England and Zeebrugge,
Belgium.
The Interconnector, inaugurated in 1998, is capable of bidirectional operation, meaning
either it can export natural gas from the UK to continental Europe ("forward mode"), or
it can import natural gas into the UK ("reverse mode"). Since it began operating, the
Interconnector has mostly operated in forward mode, however during late fall and
winter seasons, the pipeline has tended to operate in reverse mode. The pipeline has
undergone three phases of expansion, with additional capacity and compression added
between 2005 and 2007. The interconnector is currently capable of transporting 60
million cubic meters per day in forward mode and 75 million cubic meters per day in
reverse mode. The international pipelines connecting the UK to other European
countries are illustrated in Figure 3.37
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Figure 3.37: Map of the UK Natural gas international pipelines
Netherlands
Most of the Dutch natural gas fields are located offshore in the North Sea, although a
number of them are located onshore, including Groningen, one of the ten largest
natural gas fields in the world.
Natural gas produced in the Netherlands is shipped via an extensive domestic and
export pipeline system, which connects the country with United Kingdom, Germany,
and Belgium. In addition to pipeline natural gas, the Netherlands now serves as a
transport hub for liquefied natural gas (LNG). The Gas Access to Europe (GATE) LNG
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import terminal became operational in September 2011, with imported volumes
purchased by Austrian, Danish, and German distribution and utility companies.
On December 1, 2006, the Balgzand-Bacton Line (BBL), the first pipeline to link the
Netherlands and the United Kingdom, began operating and supplying the UK with
natural gas from the Dutch mainland. The 236 km pipeline has a capacity of
approximately 45 Bcm per day.
Figure 3.38 presents the main pipelines departing from Groningen, Netherlands
transmitting natural gas.
Figure 3.38: Netherlands gas transmission map
3.4.6
Downstream
The downstream stage is the final step in the natural gas supply chain and includes
transmission, storage and distribution of gas to the end-users.
Natural gas is introduced into a pipeline transmission system at various points such as
liquefied natural gas (LNG) terminals, processing plants near indigenous gas
production fields, and interconnections with other natural gas transmission pipelines
and long transportation pipelines. Gas storage sites are also connected to the
transmission systems. The transmission and transportation pipelines are supported by
gas fuelled compressors.
The delivery of natural gas to the end user by a distribution system does not contain
any compression as distribution involves moving smaller volumes of gas at much lower
pressures over shorter distances to a great number of individual users. The medium
pressure distribution network is normally operated at a pressure below 15 bar and the
electric compressors of CNG production are usually connected at this pressure.
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Transmission and distribution networks are equipped with a high number of valves
(safety valves and operating valves). Meters and customer lines are also part of the
distribution network.
Venting and fugitive emissions
Natural gas can be released to the atmosphere during operation of transmission
systems. This is problematic not only in terms of product loss, but also due to the fact
that the primary component of natural gas is methane, a powerful greenhouse gas 25
times more potent than carbon dioxide. Generally natural gas emissions are divided
into intended releases (venting) and unintended emissions (fugitive). Intended releases
highly depend on the technology involved in the process. For example, compressor
seals try to minimize the flow of natural gas between the rotating shaft and the casing
of the compressor. Emission levels depend on the technology used, the age of
equipment and the availability of new technology. Often retrofitting is not possible due
to space requirements or other local circumstances.
Pressure controllers and other such equipment periodically release a certain amount of
gas, but this can be used for purposes such as preheating of gas before pressure
reduction. Maintenance of equipment is necessary, but this often requires internal
inspections of parts containing natural gas. This gas must be released first for worker
safety. All extensions or repairs of the pipeline network, for example by welding, can
only be executed if the natural gas is purged and replaced by air to avoid incidents.
Those releases contribute a high percentage of the total emissions of gas companies.
The unintended releases can be the result of leakage from equipment in use or
damage to pipelines. All flange connections between parts should in theory be tight, but
in some cases there are gaps that allow gas to escape into the atmosphere. Also,
valves are intended to seal completely to restrict the flow of gas, but this does not
always happen. Finding these leaks is an important Task for worker safety but also
helps both the environment and profitability.
Pipe damage can either be caused by material failures or corrosion, but the main
cause is third-party damage, commonly during excavation. Companies take care to
prevent such damage, e.g. through internal pigging or cathodic corrosion protection
and through educating people doing excavation.9
EU natural gas consumption in road transport
For the purpose of the present project, only natural gas that is consumed in the
transport sector will be considered for 2012, which is the baseline year. It is considered
that the use of natural gas by transport means could be either as Compressed Natural
Gas (CNG) or as LNG through small-scale LNG systems. In 2012 CNG could be
actually traced as transportation fuel, whereas LNG is expected to be consumed as
fuel for big trucks and vessels in the forthcoming years.
9
Reduction of Greenhouse gases - A Technology Guide, Produced by: International Gas Union, 2012
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As it is shown in Table 3.18, the majority of EU countries do not present any
consumption of natural gas for road transport and even in the countries that do have
vehicles powered by natural gas, the corresponding quantities of fuel consumed are
rather small. The only countries where the consumption of natural gas for road
transport represented a substantial percentage of the total natural gas consumption in
2012 are Sweden, Bulgaria and Italy. Actually quantities of gas fuelled to other
transport means are negligible.
The GHG emissions assessments, and therefore the gas streams, will not be restricted
to the countries where there is gas consumption in transport in 2012 but will consider
all natural gas streams supplied to EU 28 countries will be considered, as gas use in
transport will be projected to 2030 (Task f of the study) and thus might be assessed in
these projections.
Road consumption
(million cubic
meters)
Road consumption/
Total NG
consumption %
BG - Bulgaria
79.03
2.66
EL - Greece
17.50
0.41
HR - Croatia
1.01
0.03
924.04
1.23
RO - Romania
0.00
0.00
SI - Slovenia
0.84
0.10
BE - Belgium
10.37
0.06
CZ - Czech Republic
15.25
0.18
DE - Germany
259.03
0.30
EE - Estonia
0.00
0.00
LV - Latvia
0.00
0.00
LT - Lithuania
3.60
0.11
LU - Luxembourg
0.00
0.00
HU - Hungary
1.37
0.01
NL - Netherlands
24.21
0.05
AT - Austria
9.01
0.10
PL - Poland
0.00
0.00
SK - Slovakia
0.00
0.00
DK - Denmark
0.00
0.00
IE - Ireland
0.00
0.00
FI - Finland
6.72
0.18
SE - Sweden
59.48
5.05
UK - United Kingdom
0.00
0.00
ES - Spain
93.12
0.29
FR - France
98.60
0.23
PT - Portugal
13.76
0.31
Consuming country
IT - Italy
Table 3.18: EU 28 Natural gas consumption for road transport in 2012 (source
Eurostat)
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APPROACH FOR DATA COLLECTION
3.5
3.5.1
Correspondence with oil and gas companies
As discussed in previous sections, a key target of this study is the collection of actual
GHG emissions data. Thus, in line with the ToR requirements, the Consultant has
come in direct communication with oil and natural gas production companies, national
authorities as well as international organizations, in order to request actual data
regarding field specific GHG emissions from the oil and gas upstream operations by
each specific company. Specifically, GHG emissions data were requested on a field
basis for the following activities both for oil and natural gas:



Exploration, production and processing
Venting, flaring and fugitive gas
Transportation
The communication with the companies has been done both in a formal and informal
manner. After establishing a contact with the relevant persons within each company,
either by telephone or by e-mail, a formal letter was sent to them (a template of which
is presented in Annex D). The purpose of this letter, which was signed by the Project
Manager, was to request the provision of actual (emissions) data. The letter also
mentioned the scope and the objectives of the project and stated the relevant support
and interest of the European Commission. Onwards, follow-up communication by
telephone and e-mail were made to the responsible persons within the oil and gas
companies in order to establish a direct line of communication.
It should be mentioned as a general conclusion that oil and gas companies and their
associations have been proven to be reluctant in providing actual emissions data till
present and most of those who replied to the request for data, have guided us to look
through their sustainability and environmental reports (if they exist). Unfortunately,
these reports usually include aggregated and cumulative data covering the whole
range of the company’s activities, with few exceptions, and sometimes extending
beyond oil activities.
Similarly, national authorities responsible for oil and gas activities or
environmental authorities in key countries were contacted (e.g.
Norwegian Petroleum Directorate, Association of Oil and Gas
Producers, etc.) even though these institutions typically publish
most of the data they have available from their members or
participating oil and gas companies. Table 3.19: Overview of the
correspondence with oil and gas associations, agenciesand
companies
summarizes the correspondence with companies and institutions contacted, the
departments contacted (if applicable), the way of communication and their response.
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Generally the data collection output based on direct communication and request of
existing actual data was very poor and it was disappointing that most of the contacted
responsible officials tried to avoid replying or pass the request to other organizations,
sometimes not so relevant to provide detailed information.
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Oil
Company
Position/Department
Letter
sent by
e-mail
Letter
sent by
post
Interim Report
Comments
Data
provided
Oil
Statoil
Maersk
Total
Senior Advisor
Sustainability
Group Sustainability,
Head of Positioning &
Strategic Risk
Management, Lead,
Climate Change
Director Sustainable
Development and
Environment
yes
yes
yes
yes
yes
yes
Redirected to the
Norwegian
Petroleum
Directorate
Redirected to the
competent
persons from
Maersk oil, who
did not reply
Letter sent to his
assistant but no
reaction
Not yet
Not yet
Not yet
ENI
Environment Manager
yes
yes
No reaction
Not yet
Shell
CO2 Policy Manager
yes
no
No reaction
Not yet
BP
Head of Energy &
Carbon Policy and
Strategy
yes
no
No reaction.
Not yet
Lukoil
Contact in the
Refining department
yes
no
Chevron
Principal Advisor,
Climate Change
yes
no
Conoco
Phillips
Various
no
no
yes
yes
no
no
yes
No
Nexen
Repsol
Saudi
Aramco
HSE and Assurance
manager
Deputy Director of
Corporate
Responsibility
Environmental
Coordinator
Asked for a
contact person in
the Environmental
Department but
no reaction
Redirected us to
OGP
Never managed
to contact anyone
within Conoco
Phillips
Redirected us to
OGP
Never managed
to contact anyone
within Repsol
Not yet
Not yet
Not yet
No reaction
Not yet
Natural gas
Gazprom
Junior Environmental
Researcher
yes
no
No reaction
Not yet
Qatargas
Head of Environment
yes
no
No reaction
Not yet
Sonatrach
Various
yes
no
No reaction
Not yet
Associations and organizations
OGP
Environmental
Director
yes
yes
CDP
Director, Global
Operations
yes
yes
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No reaction. Only
reaction when
redirected by
Chevron, but no
further data
provided
A long
communication
Not yet
Not yet
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Oil
Company
Position/Department
Letter
sent by
e-mail
Letter
sent by
post
Interim Report
Comments
Data
provided
was established
with the CDP,
who were willing
to help but did not
have the
authorization to
provide us with
data or contact
details from the
reporting
companies
National authorities
NPD
Various
yes
no
Contacted them
by telephone, but
they informed us
that all data they
can provide are
already public in
their website
Not yet
Table 3.19: Overview of the correspondence with oil and gas associations,
agenciesand companies
3.5.2
Approach for actual emissions data collection
According to the data collection priority described in Section 3.2.2 the first step of the
study was to collect actual data from oil companies and organizations regarding the
carbon intensity of specific MCONs or crude oils extracted from specific fields. For the
MCONs for which poor or unreliable emission data were collected, the GHG emissions
will be also assessed via the OPGEE model. Similarly, for natural gas sources and
streams when actual data have been considered as insufficient GHG emissions will
also be assessed via GHGenius. In any case actual emission sources are extremely
useful for comparisons with emissions calculated via models.
The progress of the correspondence with oil and gas companies has clearly indicated
that the receipt of few actual data should be expected. Therefore, the Consultant has
chosen to adapt its data collection strategy and search for actual data from published
documents of national authorities, public organizations and company reports. It should
be noted that the collection of actual data continues after the formal finalization of Task
b. Furthermore, due to the fact that the reply from most oil companies is still pending,
there is always the possibility that actual data might be obtained beyond the scheduled
duration of Task b. These data will be adapted and utilized appropriately by the
Consultant.
The Table is organized on the basis of the targeted country or region. This way of
presentation of the collected actual data has been preferred due to the fact most of the
times information is found on a country basis. Furthermore, the data source is
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mentioned as well as the data type (flaring, venting, fuel consumption, refining, etc.)
and the scope they cover (country or field specific).
The literature sources where actual data were found till present are summarized in
Table 3.20.
Country/
Region
Source
Actual data type
Coverage
EU wide or various countries
Russia,
Norway, UK,
Netherlands
Worldwide
EU wide
UNFCCC Annex I
country reports for
2012
National Oceanic and
Atmospheric
Administration
(NOAA)
Environmental Energy
Agency – European
Trading Scheme
Emissions and co-efficient
factors for the following activities
regarding crude oil:
 Production
 Flaring and venting
 Transport
 Refining
 Distribution
Country data

Flaring volumes for oil and
natural gas
Country level and
field level

Refining emissions
Country data
National reporting
National Atmospheric
Emission Inventory






Upstream oil activities
Upstream gas
Gas leakage
Venting
Flaring
Refining
Country data
Department of Energy
and Climate Change
(DECC)

Quantities of gas flared
Country data
UK
Norwegian Oil and
Gas association
Norway
Norwegian
Environment Agency
Denmark
Oil and gas production
Emissions for the following oil
activities:
 Well testing
 Flaring
 Boilers
 Engines
 Turbines
Data regarding all Norwegian oil
and gas fields and facilities:
 Energy use
 Production volumes
 Emissions

Fuel consumption (gas) per
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Country data
Oil and gas field
specific data
Country level and
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Country/
Region
Source
Actual data type
Annual Report 2013,
DEA



Russia and
the Caspian
Region
Nigeria
Associated Petroleum
Gas Flaring Study for
Russia, Kazakhstan,
Turkmenistan and
Azerbaijan, EBRD
(2012)
Associated Gas
Utilization in Russia
Annual Report 2011,
KPMG
Nigerian National
Petroleum Corporation
Annual Report 2013
(NNPC)
field
CO2 emissions from
production facilities in the
North Sea
CO2 emissions from
consumption of fuel per m.
toe
Gas flaring
Interim Report
Coverage
field-specific level


Flaring emissions
Flared quantities of natural
gas
Country data


Flaring emissions per region
Flaring emissions per
company
APG utilization rates
Country data
Flaring quantities for a large
number of fields
Field specific
data


Company reporting

Carbon
Disclosure
Project
BP
Nexen
Petroleum
CNR
International
BP
Carbon Disclosure
Project (CDP)





Exploration, production &
gas
processing
Storage, transportation &
distribution
Speciality operations
Refining
Data provided
per company
Country specific
data as well field
specific data
particularly for
Azeri Chirag
Gunashli
For company oil
fields (Buzzard,
Ettrick, Scott)
BP Sustainability
report 2012
Azerbaijan



Flaring emissions
Flaring volumes
Production emissions
Nexen Petroleum U.K.
Limited Environmental
Statement 2012
CNR International UK
Operations
Environmental
programme Annual
Report 2013

Flaring and production GHG
emissions


Combustion
Flaring
Field specific
data for Ninian
System Oil fields



Actual direct emissions
Actual indirect emissions
Flaring volumes
Country data for
(oil and gas)
assets owned by
BP Sustainability
report 2012 Angola
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Country/
Region
Source
Actual data type
Interim Report
Coverage
the specific
company
Table 3.20: Overview of actual data sources, type of data collected and data
coverage
The Table is organized on the basis of the targeted country or region. This way of
presentation of the collected actual data has been preferred due to the fact most of the
times information is found on a country basis. Furthermore, the data source is
mentioned as well as the data type (flaring, venting, fuel consumption, refining, etc.)
and the scope they cover (country or field specific).
3.6
ACTUAL DATA FOR CRUDE OIL
A valuable data source including reliable information for oil and gas for various lifecycle
stages have been the UNFCCC country reports. However, it has to be noted that the
available data regard only Annex I countries and more specifically Russia, Norway, UK
and the Netherlands (from the oil producing countries). The National Oceanic and
Atmospheric Administration (NOAA) has conducted an extensive work on the
elaboration of actual data for flaring both on a country and field level. However, it must
be stated that data provided per field regard flaring both from oil and gas activities and
a tailor made methodology has to be developed in order to disaggregate emissions for
further analysis. Actual data for the European refining sector have been found per
country by the European Environmental Agency, as those reported and verified for the
European Trading Scheme.
The main sources of actual data for the UK oil and gas sector are included in the
National Atmospheric Emission Inventory created by maintained by DEFRA. Norway
has been the country for which the most actual data have been found for oil and gas
both on country and field specific level. The main source of data for Norway has been
the Norwegian Environment Agency and the Norwegian Petroleum Directorate (NPD),
while Statoil published a wealth of data in line with national regulatory requirements.
For Denmark, the Danish Energy Agency (DEA) in its annual reports includes actual
emission data for oil and gas activities in its annual reports. Another significant source
of actual data has been a study conducted by EBRD regarding the flaring emissions for
Russia, Kazakhstan, Turkmenistan and Azerbaijan, which has collected statistics from
national authorities from the aforementioned countries. This study is particularly
important as in these countries there a remarkable difficulty for obtaining reliable data.
Lastly, actual data regarding gas flaring volumes per oil field and company for Nigeria
are included in the Annual Statistical Bulletin published by the National Nigerian
Petroleum Company (NNPC).
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Other sources of actual data include environmental and sustainability reports from oil
and gas companies. More specifically, BP in its sustainability report for Azerbaijan
provides actual emission data per asset (field, pipeline) as well as cumulative figures,
while for Angola it provides only cumulative figures for the entire company. NEXEN
petroleum provides actual data for the oil fields it operates in UK and particularly for
Buzzard which is a representative field.
In the following Sections 3.6.1 – 3.7.7 the actual data that have been collected by
various sources for oil and gas activities till present are presented exhaustively per
region or country. Followingly, in Section 3.6.8 the emissions from oil and gas activities
of various companies are presented per lifecycle process, as those have been reported
to the Carbon Disclosure project. In Section 3.6.9 the actual emissions of the European
refining sector are presented per country. Finally, in Section 3.6.10 an overview of the
actual data that have been collected is being made in order to evaluate the needs for
data collection for the OPGEE and GHGenius models.
3.6.1
Russia and FSU countries
Country data
In general, few actual GHG emission data from upstream activities are available for
Russia and FSU countries, with the exception of flaring emissions. Τhe analysis of
flaring emissions from Russian oil fields is of particular importance because these are
extremely high - the largest among all oil producing countries as illustrated in Figure
3.39. Furthermore, as it can be obtained by the Figure 3.39, Russia has one of the
largest flaring to oil ratio among countries studied by NOAA (i.e. associated gas flared
volume per unit of oil extracted). The relevant ratio has been calculated by using gas
flared volumes by NOAA/GGFR estimated and EIA oil production volumes per country
and is also an important input for the modelling of GHG emissions in OPGEE.
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40
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3000
35
2500
30
2000
25
20
1500
15
1000
10
500
5
0
0
Flaring volumes in bcm (2011) - NOAA
Flaring to oil ratio in scf/bbl (2011)
Figure 3.39: Flaring emissions (in bcm) according to the NOAA/GGFR database
and flaring to oil ratio (scf/bbl) for the calculated based on EIA
production volumes for 2011
Besides the NOAA database, there are several studies dealing with flaring emissions
both for Russia and FSU countries. Particularly a study conducted by Carbon Limits on
behalf of EBRD provided a comprehensive overview of Russian and other FSU
countries’ flaring emissions (Figure 3.40) presenting official statistics from FSU
countries. Another study dealing with Russia’s flaring emissions has been elaborated
by KPMG on behalf of WWF Russia, which has collected several actual GHG emission
data via request from oil companies.
Figure 3.40 summarizes the associated petroleum gas flaring volumes for Russia and
other FSU countries. Data for Russia have been taken from the Central Dispatch Office
of the Russian Fuel and Energy Industry (CDU TEK), for Kazakhstan from the Ministry
of Oil and Gas, for Turkmenistan from NOAA/GGFR and Carbon Limits estimates
based on IHS data sources. For Azerbaijan figures have been taken from BP’s
sustainability reports. As expected, Russia has by far the largest emissions among the
examined countries. Furthermore, despite Russia’s commitments for taking policy
action regarding flaring reduction, emissions increase steadily since 2009.
A significant issue relevant to Russian and other FSU countries’ flaring emissions is the
inconsistency among published data by various sources, as there are large differences
in flaring volumes published between national statistics, company figures and NOAA
estimates. The discrepancy in flaring volumes between official statistics and NOAA
assessments for Russia and Kazakhstan is clearly illustrated in Figure 3.41.
The gap between NOAA values and official statistics can be attributed to three factors
(EBRD, 2013):

Difficulties in converting luminosity to flaring volumes. This is related to several
factors such as the possibility of overestimating or underestimating flaring
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

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volumes via appropriate conversion factors. Furthermore, NOAA satellite
images capture only specific snapshots - and not measurements - and therefore
do not take into account seasonal variations.
Flaring volumes do not consider only flaring from associate petroleum gas but
also other sources such as non-associated gas from gas processing plants or
refineries.
Underestimates of flaring from national statistics.
18
16
14
12
Russia
10
Kazakhstan
8
Turkmenistan
6
Azerbaijan
4
2
0
2006
2007
2008
2009
2010
2011
2012
Figure 3.40: Flaring of associated gas in target countries in bcm according to
national statistics for the years 2006 – 2012, in billion cubic meters
(source: EBRD)
60
50
Russia NOAA
40
Russia Official
statistics
30
Kazakstan NOAA
20
Kazakstan Official
statistics
10
0
2007
2008
2009
2010
2011
Figure 3.41: Comparison of associated flaring volumes in bcm between national
statistics and NOAA estimates (source: EBRD)
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Regional dispersion of Russian flaring volumes
Figure 3.42 illustrates the Associated Petroleum Gas (APG) production volume per
region and the APG flared volumes. It is evident that the largest fraction of APG
production comes from Western Siberia with more than half of it being produced in
Khanty-Mansi Autonomous Okrug. Large part of this APG is flared – approximately 5
bcm, with Eastern Siberia having the same flaring volumes. Together these two areas
accounted for approximately 80% of Russian flaring emissions as it can be obtained by
Figure 3.42. Further analysis of these data can be used for the assessment of flaring
emissions for Urals and Siberia Light MCONs, even though it is doubtful whether these
emissions can be reliably attributed to specific MCONs and oil fields.
40.00
35.00%
35.00
30.00%
30.00
25.00%
25.00
20.00%
20.00
15.00%
15.00
10.00%
10.00
5.00%
5.00
-
0.00%
KhMAO
YNAO
APG production, bcm
Eastern
Siberia
Volga
region
Komi
Republic
APG flaring, bcm
Far East
Ural
The rest
APG flaring volumes in Russia by zone, %
Figure 3.42: APG production and flaring in Russia by zone in bcm, 2010 (KPMG)
UNFCCC emissions data for Russia
A significant source of reported GHG emission data are the Annex I country reports
submitted to UNFCCC. These include actual data both for oil and natural gas for key
processes i.e. exploration, production, transport, refining, distribution, flaring and
venting. The fact that figures are presented also in the form of emission factors (i.e.
total emissions per well, emissions per ton of oil produced or refined, etc.) is
particularly important, because they can be used directly in OPGEE and in GHGenius
which calculates GHG emissions by use of proper emission factors. Table 3.21
summarizes the UNFCCC reported data for Russia and indicates the level of detail of
analysis of these reports.
GREENHOUSE GAS
SOURCE AND SINK
CATEGORIES
ACTIVITY DATA
Description
Unit
Value
IMPLIED EMISSION
FACTORS
CO2
CH4
1. B. 2. a. Oil
Exploration
number of
1000
181.70
220,845.96
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
CO2
CH4
(Gg)
(kg/unit)
I.
EMISSIONS
74,454.96
204A58
908A40
40.13
13.53
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GREENHOUSE GAS
SOURCE AND SINK
CATEGORIES
ACTIVITY DATA
Description
Unit
Value
Interim Report
IMPLIED EMISSION
FACTORS
CO2
CH4
EMISSIONS
CO2
(Gg)
(kg/unit)
producing and
capable wells
(4)
CH4
numb.
oil produced
Mt
497.43
314,758.69
1,690,370.7
156.57
840.83
iii. Transport
(oil transported
in pipelines)
Mt
523.35
571.23
6,295.17
0.30
3.29
iv. Refining / Storage
oil refined
Mt
271.45
NE
36,871.12
NE
10.01
v. Distribution of Oil
Products
oil refined
kt
271,453.00
NE
NE
NE
NE
vi. Other
(NGL
production)
kt
21,322.00
355.79
1,910.72
7.59
40.74
84.34
13,525.23
ii. Production
1. B. 2. b. Natural
Gas
number of
producing and
capable wells
1000
numb.
gas produced
iii. Transmission
i. Exploration
9.79
172,553.69
72,163.80
1.69
0.71
10 m
654,650.00
121.98
3,629.24
79.85
2,375.88
(total gas
transmission)
kt
541,054.50
5.18
8,915.31
2.80
4,823.67
iv. Distribution
gas consumed
10 m
6
3
137,236.60
NE
20,908.30
NE
2,869.38
v. Other leakage
gas consumed
10 m
6
3
388,079.50
NE
8,904.32
NE
3,455.59
6
3
343,301.70
NE
9,450.51
NE
3,244.38
6
3
44,777.80
NE
4,716.82
NE
211.21
8.78
839.62
ii. Production /
Processing
at industrial plants
and power stations
in residential and
commercial sectors
(gas
consumed)
(gas
consumed)
6
3
10 m
10 m
1. B. 2. c. Venting
i.
oil produced
Oil
ii. Gas
iii. Combined
length of
pipelines
(NGL
production)
kt
497,425.00
13.99
1,609.93
6.96
800.82
km
175,100.00
8.50
IE
1.49
IE
kt
21,322.00
15.81
1,819.80
0.34
38.80
36,594.35
219.95
Flaring
i.
oil production
Oil
gas production
ii. Gas
kt
6
3
10 m
497,425.00
IE
IE
IE
IE
654,650.00
3,725.88
22.94
2,439.15
15.01
(Assotiated
6
3
iii. Combined
10 m
17,077.60
2,000,000.0
12,000.00
34,155.20
204.93
gas flaring)
NE (Not Estimated): For existing emissions and removals which have not been estimated
IE (Included Elsewhere): For emissions or removals estimated but included elsewhere in the inventory instead of the expected
category
Table 3.21: Russian reported emissions per lifecycle stage for 2012 for oil and
natural gas (source: UNFCCC)
3.6.2
Azerbaijan
Additional data for Azerbaijan have been found in the website of BP, which publishes
detailed GHG emission data in its Sustainability Report for 2012.
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4500
4000
3500
3000
2500
2000
1500
1000
500
0
Interim Report
780
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
760
740
720
700
680
660
640
620
2008
2009
2010
2008
2011 2012
2009
2010
2011
2012
Operational net GHG emissions in kilotonnes
Gross direct carbon dioxide (BP and co-ventures)
Normalized operational GHG emissions (tonnes per
thousand barrels oil equivalent)
Net direct emissions (BP only)
Figure 3.43 illustrates BP’s and its co-ventures’ direct CO2 emissions in Azerbaijan as
well as its net GHG emissions. It is evident that both company emissions and
cumulative emissions including co-ventures have remained relatively steady over the
period examined (2008 - 2012).
4500
4000
3500
3000
2500
2000
1500
1000
500
0
780
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
760
740
720
700
680
660
640
620
2008
2009
2010
2011 2012
2008
2009
2010
2011
2012
Operational net GHG emissions in kilotonnes
Gross direct carbon dioxide (BP and co-ventures)
Net direct emissions (BP only)
Normalized operational GHG emissions (tonnes per
thousand barrels oil equivalent)
Figure 3.43: BP’s emissions in Azerbaijan for 2012 (emission in kilotonnes)
Table 3.22 summarizes BP’s net GHG emissions per asset. It is worth mentioning that
the Azeri oil field has the largest cumulative emissions, followed by the fields of Chirag
and Gunashli (also known cumulatively as ACG field). There are extremely useful data
as they can be compared with the emissions calculated for ACG field in OPGEE, which
is a representative oil field for two MCONs.
Asset / Facility
2011
2012
Central Azeri
130.0
117.2
West Azeri
52.6
44.0
East Azeri
44.6
46.0
Chirag
36.6
54.3
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Asset / Facility
2011
2012
Deepwater Gunashli
88.8
70.6
Shah Deniz
1.9
2.1
Istiglal rig
3.4
3.8
Dada Gorgud rig
2.0
3.6
Sangachal terminal (Azeri-Chirag-Deepwater Gunashli)
247.8
252.5
Sangachal terminal (Shah Deniz)
41.8
44.8
Baku-Tblisi-Ceyhan pipeline in Azerbaijan
22.7
19.4
South-Caucasus Pipeline in Azerbaijan
0.2
0.2
Western Route Export Pipeline in Azerbaijan
4.0
4.3
Table 3.22: BP in Azerbaijan net GHG emissions per asset (in kilotonnes)
In 2012, about 475.9 kilotonnes of hydrocarbons were flared from BP’s operations in
Azerbaijan. By implementing measures such as improving the reliability of the flash gas
compressors at offshore installations, replacing existing engines on gas injection
compressors and a gas export compressor at Central Azeri compression and water
injection platform with more reliable and higher capacity engines, repairing flare valve
at Chirag, post-turnaround flaring minimization at Deepwater Gunashli, BP claims that
the overall level of flaring in 2012 compared to 2011 was reduced by 19%.
Nevertheless, Figure 3.44, presents gross flaring by asset in kilotonnes, from where it
can be obtained that Chirag had the highest flaring volumes in 2012.
250
Sangachal
terminal (SD)
Sangachal
terminal (ACG)
Chirag
200
150
Deepwater
Gunashli
East Azeri
100
West Azeri
50
Central Azeri
0
2008
2009
2010
2011
2012
Figure 3.44: BP in Azerbaijan gross flaring volumes by asset in kilotonnes
(source: BP)
3.6.3
Norway
The environmental performance of the Norwegian petroleum sector compared to other
oil producing regions worldwide is illustrated in Figure 3.45, from where it be obtained
that it is one of the cleanest. This has been the result of a number of policy instruments
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and regulations deployed by the Norwegian government to regulate emissions from the
oil and gas business. The most important of these are the carbon tax, Norway’s
participation in the EU emission trading market, flaring provisions in the Petroleum
Activities Act, the requirement to assess power from shore when planning
developments, emission permits and the Best Available Techniques (BAT)
requirement. These instruments have prompted a number of measures by the
petroleum sector that led to significant emissions reductions over the last years.
Figure 3.45: GHG emissions produced for petroleum from various origins (in kg
of carbon equivalent per barrel of oil produced) (source OGP,
Environment Web)
The Climate and Pollution Agency, the Norwegian Petroleum Directorate and the
Norwegian Oil Industry Association have established a joint database for reporting
emissions to air and discharges to sea from the petroleum activities under the name
«Environmental Web» (EW). In addition, all operators on the Norwegian continental
shelf report GHG emissions and discharge data directly into the database. All these
data are characterized by high consistency and transparency.
A major source of actual data for Norway has been the Annual Environmental Report
published the Norwegian Petroleum Directorate, which includes detailed emissions for
all major pollutants (CO2 NOX, CH4, VOC etc.). After a peak in 2008 GHG emissions
have been steadily declining until 2012, as it can be seen in Figure 3.46. The main
source of atmospheric emissions has been power generation using natural gas and
diesel. The level of these emissions depends mainly on energy consumption by the
facilities and the energy efficiency of power generation. The second largest source of
this emission type is gas flaring. Flaring takes place to only a limited extent and is
constantly decreasing pursuant to the provisions of the Petroleum Activities Act, but is
permitted for safety reasons and in connection with certain operational problems.
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16000000
14000000
12000000
Turbines
10000000
Engines
8000000
Boilers
Flaring
6000000
Well TesTing
4000000
Other sources
2000000
0
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Figure 3.46 : Breakdown of GHG emissions by source in metric tonnes CO2
equivalent for Norway (source: NPD)
For Norway a detailed source of actual emission data has been the Norwegian
Environment Directorate, including total cumulative emissions and fuel consumption for
all representative oil fields that are studied. Figure 3.47, illustrates the GHG emissions
for these representative oil fields. As it can be observed in the Figure, the fields that
exhibit the largest emissions are Oseberg followed by Gullfaks. Despite the adoption of
stringent environmental regulations by Norway and the adoption of more energy
efficient technologies by companies active in the Norwegian Continental Shelf, the
GHG emissions from representative oil fields remained either stable, decreased or
increased in absolute values by the time.
The increase of GHG emissions of representative oil fields can be better perceived by
estimating the emissions per unit of output of oil from each oil field, which is illustrated
in Figure 3.48. Given the fact that production in the specific fields steadily decreases
over time, a general conclusion that can be drawn is that as fields become mature and
depleted the energy intensiveness of oil extraction increases in order to maintain
pressure at acceptable levels, which results in higher emissions per unit of output of oil
over time. The GHG emissions per unit of oil produced are extremely useful for
comparisons with the outputs of OPGEE, when these will be produced at a later stage
of the project.
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1400000
1200000
1000000
Ekofisk
800000
Gullfaks
Troll B and C
600000
Stratford
400000
Oseberg
200000
0
2008
2009
2010
2011
2012
2013
Figure 3.47: GHG emissions of representative Norwegian oil fields in tonnes of
CO2 equivalent (source: Norwegian Environmental Directorate)
0.60
0.50
0.40
Ekofisk
Gullfaks
0.30
Stratford
0.20
Oseberg
0.10
0.00
2008
2009
2010
2011
2012
2013
Figure 3.48: GHG emissions per unit of output of oil (in tonnes CO2 equivalent
per m3 of oil) (source: NPD and own elaboration)
As discussed, reporting of GHG emissions in Norway is detailed, transparent and
mandated by national legislation. In this context, all companies are obliged to report the
emissions from their upstream activities. Detailed emission figures per asset have also
been provided by Statoil (including oil and gasification terminals apart from oil and gas
fields). Table 3.23 summarizes the GHG emissions of the 20 facilities owned by Statoil
with the highest Scope 1 and Scope 2 GHG emissions (see paragraph 3.6.8 for
explanations), according to CDP, which are equivalent to direct emissions according to
the system boundaries defined in this study.
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Facility
Scope 1
emissions
(metric tonnes
CO2eq)
Mongstad Drift PA
1,656,310
KÅRSTØ
1,049,019
Interim Report
Scope 2
emissions
(metric tonnes
CO2eq)
Total
Emissions
(metric tonnes
CO2eq)
1,656,310
4,766
1,053,785
MELKØYA
897,690
897,690
SLEIPNER
833,527
833,527
Mongstad - Kraftvarmeverket
606,209
Oseberg feltsenter
744,972
744,972
ÅSGARD B
716,617
716,617
KALUNDBORG
518,678
GULLFAKS A
471,987
471,987
HEIDRUN
394,343
394,343
ÅSGARD A
347,539
347,539
TJELDBERGODDEN
345,576
Troll C
336,883
336,883
NORNE
282,587
282,587
SNORRE A
279,780
279,780
Troll B
274,739
274,739
CPF
268,292
268,292
STATFJORD B
261,563
261,563
Peregrino FPSO
256,409
256,409
GULLFAKS C
236,620
236,620
210,897
102,421
471
817,106
621,099
346,047
Table 3.23: Overview of Statoil’s 20 facilities (terminals and platforms) with the
highest GHG emissions (Scope 1 and Scope 2), as those reported to
CDP.
Another source of data for the Norwegian oil sector is the Norwegian UNFCCC report.
Data are provided both for oil and gas regarding all major lifecycle stages excluding the
combustion stage. These data are presented at country level and have been developed
based on the methodology of UNFCCC. Emissions reported to UNFCCC will be
compared with national statistics in order to assess their consistency. Table 3.24
presents these data for the Norwegian oil and gas sectors.
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GREENHOUSE GAS
SOURCE AND
SINK CATEGORIES
ACTIVITY DATA
Description
Unit
Value
Interim Report
IMPLIED EMISSION FACTORS
CH4
CO2
N2O
EMISSIONS
CO2
(Gg)
(kg/unit)
1. B. 2. a. Oil
i. Exploration
number of
wells drilled
kg
ii. Production
oil produced
10 m
iii. Transport
oil loaded in
tankers
iv. Refining / Storage
v. Distribution of Oil
Products
IE
IE
IE
IE
PJ
3,959.922
21,350.109
1,674.20
84.545
6.630
Oil refined
PJ
551.619
2.093
4.104
1,154.670
2.264
Gasoline
sold
PJ
45.353
284,906.605
N.
12.921
N.
13.512
1.842
ii. Production /
Processing
gas
produced
gas
consumed
gas
consumed
i. Oil
ii. Gas
iii. Combined
3
N.
NE
IE
IE
IE
IE
114,727.0
IE
IE
IE
IE
NE
IE
IE
IE
IE
NE
IE
NE
IE
0.030
(specify)
NE
NE
NE
13.512
1.812
specify
NE
NE
NE
13.512
1.812
N.
NO
NO
NO
NO
119.833
14.676
specify
(e.g. PJ oil
produced)
(e.g. PJ gas
produced)
Oil and gas
produced
6
3
10 m
km
PJ
IE
IE
IE
IE
IE
IE
IE
IE
IE
IE
7,967.106
15,041.019
1,842.12
119.833
14.676
1,359.733
0.726
34.853
0.004
Flaring
i. Oil
IE
111,523
specify
v. Other
Leakage
at industrial plants
and power stations
in residential and
commercial sectors
1. B. 2. c. Venting
IE
IE
i. Exploration
iv. Distribution
8A893
IE
3
NO
1,252A136
NE
1. B. 2. b. Natural Gas
iii. Transmission
CH4
Oil flared
PJ
0.461
75,650,118
9,456.26
709.22
Gas flared
ii. Gas
PJ
18.178
72,883,963
39,686.4
559.16
1,324.881
0.721
NE (Not Estimated): For existing emissions and removals which have not been estimated
IE (Included Elsewhere): For emissions or removals estimated but included elsewhere in the inventory instead of the expected
category
NO (Not Occurring): For emissions and removals of GHG that do not occur for a particular gas or source/sink category
Table 3.24: Emission data for Norway for oil and natural gas
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3.6.4
Interim Report
United Kingdom
Country data
Actual emission data on a national level for the oil and gas activities of the United
Kingdom are being collected by the National Atmospheric Emission Inventory that has
been developed by the Department of Environment, Food and Rural Affairs (DEFRA).
Such data are presented in Figure 3.49. As it can be obtained from theFigure, the most
significant emission source is flaring, which accounted for approximately 85% of total
emissions of the UK oil sector in 2012, followed by venting which accounted for 7% of
total emissions in 2012.
Another major source of actual emissions data for the UK has been the country’s report
under the UNFCCC, which is presented in Table 3.25. As discussed for Russia and
Norway, UNFCCC is a useful source of information, since each country is obliged to
submit data periodically in a consistent and reliable manner. However, the same
limitations apply, including the difficulty to use data that are presented on an
aggregated level. Generally the UNFCCC data are anticipated to be more useful for the
assessment of natural gas GHG emissions via the GHGenius model and also for
verification and comparison with other data sources at aggregated level.
The Department of Energy and Climate Change (DECC) also publishes flaring volumes
per oil field. Table 3.26 illustrates the 20 oil fields with the largest flaring volumes in
2013. Flaring volumes are reported for Buzzard, Ninian and Captain, which are the
three representative fields for UK crudes in the context of this study.
Apart from data presented on a national basis, actual emission data for specific oil
fields are also available by specific companies, which operate specific oil and gas
fields, through their environmental reports. NEXEN petroleum in its Environmental
Statement for 2012 publishes data for 3 key oil and gas fields that operates i.e.
Buzzard, Ettrick and Scott, as it is presented in Figure 3.50. According to the
company’s report, the main combustion GHG emission from these sources is carbon
dioxide (CO2), along with smaller emissions of oxides of nitrogen, nitrous oxide, sulphur
dioxide, carbon monoxide, methane and volatile organic compounds. The largest
portion of carbon dioxide emissions offshore comes from combustion of fuels for
energy production on-board the installations.
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4000
3500
3000
2500
2000
1500
1000
500
0
2008
2009
2010
2011
2012
Upstream Oil Production - process emissions
Upstream Oil Production - Onshore Oil Loading
Upstream Oil Production - Offshore Oil Loading
Upstream Oil Production - Oil terminal storage
Petroleum processes
Upstream Oil Production - Offshore Well Testing
Upstream Oil Production - venting
Upstream Oil Production - flaring
Figure 3.49: Breakdown of emissions of the UK oil sector by source (in million
metric tonnes) (source: DEFRA)
350000
300000
250000
200000
150000
100000
50000
0
2010
2011
2012
Scott
Total CO2 emitted
2010
2011
Buzzard
2012
2010
2011
2012
Ettrick
Fuel gas (CO2 equivalent)
Figure 3.50: Total atmospheric CO2 emissions and emissions due to
consumption of fuel gas for energy production (in tonnes CO2
equivalent) for three oil fields (source: NEXEN).
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GREENHOUSE GAS
SOURCE AND
SINK CATEGORIES
Interim Report
IMPLIED EMISSION
FACTORS
ACTIVITY DATA
Description
Unit
Value
CO2
CH4
EMISSIONS
CO2
(Gg)
(kg/unit)
1. B. 2. a. Oil
i. Exploration
ii. Production
iii. Transport
iv. Refining /
Storage
v. Distribution of
Oil Products
vi. Other
Well testing
fuel use
Oil produced
(net)
Offshore
loading of oil
only
Oil refinery
throughput
(net)
(e.g. PJ oil
refined)
Onshore
loading of oil
ii. Production /
Processing
iii. Transmission
iv. Distribution
v. Other
Leakage
at industrial plants
and power stations
in residential and
commercial sectors
1. B. 2. c. Venting
i. Oil
ii. Gas
iii. Combined
Well testing
fuel use
Natural gas
production
(net)
Final gas
consumption
Final gas
consumption
35.43
9.66
t
11,003.84
3,200.00
25.00
35.21
0.28
PJ
1,941.49
110.84
1,320.70
0.22
2.56
t
7,704,447.21
NO
60.55
NO
0.47
PJ
2,989.07
NO
2,013.11
NO
6.02
NA
NO
NO
NO
NO
2,034.99
NO
166.63
NO
0.34
248.55
189.47
PJ
1. B. 2. b. Natural Gas
i. Exploration
CH4
t
36,670.50
2,800.00
45.00
102.68
1.65
PJ
1,464.78
95,344.39
2,201.52
139.66
3.22
GWh
553,368.15
0.12
3.47
0.23
6.92
GWh
553,368.15
2,960.79
87,953.71
5.90
175.21
Total gas use
TJ
1,597,035.52
0.05
1.54
0.08
2.46
Not applicable
PJ
NO
NO
NO
NO
NO
Total gas use
PJ
1,597.04
0.05
1.54
0.08
2.46
None
None
NA
NA
NA
NA
NA
NA
9.13
8.54
0.58
35.89
13.15
22.73
None
IE
IE
IE
IE
IE
3,257.35
13.34
Flaring
i. Oil
Mass of gas
flared
t
1,155,734.92
2,604.16
10.63
3,009.72
12.28
ii. Gas
Mass of gas
flared
t
107,241.69
2,309.02
9.86
247.62
1.06
Mass of gas
Mg
IE
IE
IE
IE
IE
flared
NE (Not Estimated): For existing emissions and removals which have not been estimated
IE (Included Elsewhere): For emissions or removals estimated but included elsewhere in the inventory instead of the
expected category
NO (Not Occurring): For emissions and removals of GHG that do not occur for a particular gas or source/sink category
NA (Not Applicable): For activities in a given source/sink category that do not result in emissions or removals of a specific
gas
iii. Combined
Table 3.25: UNFCCC Emission data for United Kingdom for oil and natural gas
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3
Average Flare million m per day
Average Flare million ft per
day
CHESTNUT
0.12
4.32
BRENT
0.12
4.15
FOINAVEN
0.09
3.11
NINIAN
0.09
3.03
BRAE SOUTH
0.08
2.97
BUZZARD
0.08
2.72
THISTLE
0.07
2.58
ALBA
0.07
2.42
FORTIES
0.07
2.39
CAPTAIN
0.06
2.18
BLAKE
0.05
1.79
ORION
0.05
1.70
BERYL
0.05
1.62
CLAIR
0.04
1.55
BALLOCH
0.04
1.49
BRUCE
0.04
1.48
AFFLECK
0.04
1.45
STARLING
0.04
1.39
LENNOX
0.04
1.39
MURCHISON
0.04
1.37
Producing Oil Fields
3
Table 3.26: The twenty oil fields with the largest flaring volumes per day in UK for
2013 (source: DECC)
3.6.5
Nigeria
In general, no actual data have been found for Nigeria apart from flaring which is one of
the most significant emission sources of the Nigerian oil sector. According to the
National Oceanic and Atmospheric Administration (NOAA), Nigeria flared slightly more
than 515 Bcf of natural gas in 2011 - or more than 21% of gross natural gas production
in 2011. Natural gas flared in Nigeria accounts for approximately 10% of the total
amount flared globally. The amount of gas flared in Nigeria has decreased in recent
years, from 575 Bcf in 2007 to 515 Bcf in 2011.
According to Shell, one of the largest gas producers in the country, the impediments to
decreasing gas flaring has been the security situation in Niger Delta and the lack of
partner funding that has slowed progress on projects to capture associated gas. The
company recently reported that it was able to reduce the amount of gas it flared in 2012
because of improved security in some Niger Delta areas and stable co-funding from
partners that allowed the installation of new gas-gathering facilities and repair of
existing facilities damaged during the militant crisis of 2006 to 2009.
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Table 3.27 illustrates the 20 Nigerian fields with the largest flaring volumes, according
to NNPC. It is obvious that the percentage of gas flared varies significantly per field and
company, making it difficult to draw uniform conclusions.
Gas produced
(in mscf)
Gas utilized
(in mscf)
Gas flared
(in mscf)
Percentage
of gas flared
(in mscf)
27,569,340
0
27,569,340
100%
22,556,733
0
22,556,733
100%
IDU FIELDS
NPDC
ND
WESTERN
NAOC
36,747,486
25,197,140
11,550,346
31%
OFON
Total E&P
11,499,725,25
369,991
11,129,734
97%
KWALE FIELDS
NAOC
32,221,463
21,351,330
10,870,133
34%
OKONO/OKPOHO
NPDC
11,009,360
563,254
10,446,106
95%
AMENAM/KPONO
Total E&P
108,950,287,53
98,541,400
10,408,888
10%
AKRI FIELDS
NAOC
12,754,634
2,796,994
9,957,640
78%
ERHA
ESSO
112,226,569
102,889,639
9,336,930
8%
OBR/OBI FIELDS
NAOC
183,725,459
175,018,183
8,707,276
5%
USAN
TUPNI
14,874,000
6,539,000
8,335,000
56%
DELTA
Chevron
7,253,193
51,274
7,201,919
99%
MEREN
Chevron
15,115,125
8,093,216
7,021,909
46%
OSHI FIELDS
OBEN/SAPELE/AM
UKPE
QIT
NAOC
18,830,177
11,903,725
6,926,452
37%
NPDC
6,819,131
0
6,819,131
100%
Mobil
8,638,294
1,980,359
6,657,935
77%
PARABE/EKO
Chevron
6,978,580
382,997
6,595,583
95%
OSO
Mobil
86,660,679
80,170,335
6,490,344
7%
AGBAMI
STARDEEP
93,068,067
86,700,089
6,367,978
7%
EDOP
Mobil
42,521,467
36,178,579
6,342,888
15%
EBOCHA FIELDS
NAOC
21,531,182
15,433,333
6,097,849
28%
Field
Company
UTOROGU/UGHELI
UTOROGU/UGHELI
Table 3.27: Twenty Nigerian fields with the largest flaring volumes
3.6.6
Denmark
With regard to the climatic and environmental impact of the Danish oil and gas sector,
the Danish Energy Agency (DEA) manages the atmospheric emissions of CO2 from the
combustion and flaring of natural gas and diesel oil, the effects of offshore oil and gas
activities, the conditions in established international nature protection areas and the
impact of oil and gas projects on the marine environment. Emissions, discharges and
any marine spills are managed by the Ministry of the Environment, partly on the basis
of regulations issued under the auspices of the international collaboration under the
Oslo and Paris Convention (OSPAR). The Danish Subsoil Act regulates the volumes of
gas flared, while CO2 emissions (including flaring) are regulated by the Danish Act on
CO2 Allowances.
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The evolution CO2 emissions from the North Sea production facilities since 2003 are
presented in Figure 3.51. It can be shown that CO2 emissions totaled at about 1.695
million tons in 2012, the lowest level in the past ten years, with both the quantity of fuel
and gas flared being reduced. Gas used as a fuel accounted for approximately 90% of
total gas consumption offshore in 2012, while the remaining 10% was flared. The
development in the use of gas as fuel on Danish production installations is illustrated in
Figure 3.53. The general increase until 2007 can be attributed to the rising oil and gas
production and ageing fields. The main reason for the sharp drop from 2008 onwards is
energy-efficiency measures taken by the operators, as reported by DEA.
Figure 3.51: CO2 emissions from
production facilities in the
North Sea (source: DEA)
Figure 3.52: Fuel consumption (gas)
for upstream activities
(source: DEA)
CO2 emissions due to fuel consumption have increased relative to the size of
hydrocarbon production over the past decade, as illustrated in Figure 3.54.The reason
for this increase is that oil and gas production has dropped more sharply than fuel
consumption; this means that CO2 emissions due to fuel consumption have increased
relatively to the size of production.
The flaring of gas declined substantially from 2006 to 2012 in all fields with the
exception of the Harald Field where flaring has remained unchanged. This
development is attributable to more stable operating conditions on the installations,
changes in operations and focus on energy efficiency. As appears from Figure 3.55,
which shows the volumes of gas flared, flaring varies considerably from one year to
another. The large fluctuation in 2004 is partially due to the tie-in of new fields and the
commissioning of new facilities. In 2012, gas flaring totaled 71 million Nm3.
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Figure 3.53: CO2 emissions from
consumption of fuel per
mtoe (source: DEA)
3.6.7
Interim Report
Figure 3.54: Gas flared (source: DEA)
Angola
BP in its 2012 Sustainability Report published actual data regarding the emissions from
its activities of oil extraction activities in Angola. These data are illustrated in Table
3.28, where it is observed that the company’s total emissions have decreased by
approximately 10% in 2012 compared to 2011. Similarly, flared gas quantities have
decreased slightly in 2012.
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Environment
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2006
2007
2008
2009
2010
2011
2012
Total hydrocarbons
produced (million
barrels oil equivalent
per day)
133
140
202
211
170
123
149
Equity share direct
carbon CO2 (tonnes)
484,666
940,541
1,208,764
1,162,490
1,055,204
1,006,583
898,618
Equity share indirect
CO2 (tonnes)
0
0
0
0
0
0
0
Equity share direct
methane (CH4)
(tonnes)
1,643
4,160
2,644
2,502
2,444
2,079
3,220
Equity share direct
GHG (tonnes CO2
equivalent)
519,169
1,027,811
1,264,288
1,215,032
1,106,528
1,050,242
966,229
Total gas flared
(tonnes)
1,987
148,882
200,221
138,093
227,851
323,693
308,095
Sulphur dioxide
(SOx) (tonnes)
108
232
206
259
98
298
559
Nitrogen oxides
(NOx) (tonnes)
1,587
5,800
2,923
1,849
928.4
1,060
3,828
Non-methane
hydrocarbons
(NMHC) (tonnes)
260
825
6,210
4,789
6,766
11,391
1,568
Table 3.28: Environmental data by BP’s activities in Angola for the years 20062012 (source: BP)
3.6.8
Carbon Disclosure Project (CDP) reports
CDP is an international, not-for-profit organization providing a global system for
companies and cities to measure, disclose, manage and share vital environmental
information. The CDP reported emissions are organized per company into 3 Scopes for
the emissions for oil and natural. Scope 1 emissions include the total global direct
emissions from sources owned or controlled by the reporting organization and more
specifically:
 Stationary combustion: boilers, furnaces, engines, etc;
 Mobile combustion: automobiles, planes, ships, trains, etc;
 Process emissions: cement manufacturing, aluminum smelting, gas and oil
production, refining, etc;
 Fugitive emissions: equipment
refrigeration, etc
leaks,
hydrofluorocarbon emissions from
Scope 2 emissions include indirect GHG emissions that the company has caused
through its consumption of energy in the form of electricity, heat, cooling or steam.
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Scope 3 emissions include indirect emissions that arise as a consequence of an
organization's activities from sources that are owned or controlled by others.
It must be noted that the distinction between Scope 1, 2 and 3 emissions does not align
with the definition of direct and indirect emissions set in the context of this study. Thus,
Scope 1 and 2 emissions of CDP correspond to the direct emissions as those have
been defined in this study. Table 3.29 provides the Scope 1 and Scope 2 emissions
(sum) for four companies. It can be seen that EXXON and CHEVRON have the largest
emissions. It can also be observed that large part of the companies’ emissions comes
from refining activities. However, the reporting methodology of companies to CDP has
not been studied or evaluated.
Company
Segment
2008
2009
2010
2011
2012
CHEVRON
Exploration, production
& gas processing
Refining
0
0
42,482,952
41,785,072
39,593,574
0
0
22,978,452
23,328,912
21,553,218
Speciality operations
0
0
1,158,459
789,899
1,261,745
0
0
66,619,863
65,903,883
62,408,537
62,000,000
60,000,000
63,000,000
68,000,000
68,000,000
EXXON
Total
Exploration, production
& gas processing
Refining
REPSOL
Total
Exploration, production
& gas processing
Storage, transportation
& distribution
Speciality operations
STATOIL
59,000,000
58,000,000
60,000,000
59,000,000
55,000,000
121,000,000
118,000,000
123,000,000
127,000,000
123,000,000
0
0
23,566
21,288
27,522
0
0
46,562
57,168
45,264
0
0
1,233,028
404,448
327,788
Refining
0
0
505,224
558,076
1,115,982
Retail & marketing
0
0
134,752
91,886
105,930
Total
Exploration, production
& gas processing
Storage, transportation
& distribution
Refining
0
0
1,943,132
1,132,866
1,622,486
13,059,999
11,524,551
11,629,031
11,649,562
0
118,924
106,470
75,661
89,178
0
2,101,460
2,346,222
2,877,636
3,094,512
0
15,280,383
13,977,243
14,582,328
14,833,252
0
Total
Table 3.29: Scope 1 and Scope 2 reported values for oil and gas emissions for
specific companies (source: CDP)
3.6.9
Refining
Actual data for the emissions of the European refining sector10 for 2012 are illustrated
in Figure 3.55 These data are verified emissions of the European Trading Scheme
(ETS) and therefore fully reliable. It can be seen that the largest refining emissions take
10
http://www.eea.europa.eu/data-and-maps/data/data-viewers/emissions-trading-viewer
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place in Germany, Poland and Italy. These figures can be used for comparisons with
the outputs of PRIMES-Refineries, once these have been produced.
500,000
450,000
400,000
350,000
300,000
250,000
200,000
150,000
100,000
50,000
Austria
Belgium
Bulgaria
Cyprus
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Latvia
Liechtenstein
Lithuania
Luxembourg
Malta
Netherlands
Norway
Poland
Portugal
Romania
Slovakia
0
Figure 3.55: Emissions of the refinery sector per country for 2012 in kt CO2
equivalent as verified by the European Trading Scheme – ETS
(source: European Environmental Agency)
3.6.10 Overview and evaluation of actual data collection progress for
oil
As it has been evident till present, the Consultant has reviewed a large number of
resources for the collection of actual emission data. Ideally, information should have
been found on an MCON or oil field basis. However, given the reluctance of oil and gas
companies to provide actual data, often data have been found on a country basis with
few exceptions. Unfortunately, cumulative emission data found on a country basis
cannot be directly used for the purpose of comparisons without further analysis (apart
from cross-country comparisons) but given the scarcity of information, these country
level data are extremely valuable. There are also cases where actual emission data are
found per company as published in sustainability and environmental reports, which
usually refer to company’s entire activities or the data are poorly broken down. This
type of information can be used for comparisons of the carbon intensity of specific
lifecycle stages (e.g. production of oil) between companies.
Following the identification of actual data sources, the Consultant has classified the
information collected by lifecycle stage both on a country and MCON level i.e.
production, venting flaring fugitive, transport refining and distribution, as illustrated in
Table 3.30. The purpose of this systematization is to identify the MCONs for which no
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actual data have been found (green colour marking) and inevitably its GHG emissions
will have to be assessed using the OPGEE model.
As a general conclusion, significant actual information on a country level has been
found for Norway, Denmark and United Kingdom for most lifecycle stages. Partial
information for flaring has been found for Russia and FSU countries. Lastly few data
have been found for Nigeria regarding only flaring emission and Angola.
The collection of field specific data has been a more difficult Task, because when oil
companies have no legal obligation to report them officially they have no actual
incentive. Actual GHG emission data have been found for Norwegian representative
fields. For representative fields located in UK i.e. (Buzzard, Captain and Forties) flaring
emissions have been found, as well as total emissions for the Buzzard oil field.
Surprisingly, significant data have been found for total emissions and flaring for the
ACG field in Azerbaijan. Flaring volumes are also available for all Nigerian fields, as
well as production and flaring emission for key Danish fields comprising the DUC
MCON.
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Actual emission data sources
Country
Country level data
Production
VFF
Transport
Refining
Distribution
Total
Iran
Iraq
Kuwait
Saudi Arabia
Algeria
Angola
BP
BP
BP
Libya
Nigeria
NNPC
Azerbaijan
EBRD,
BP
BP
Kazakhstan
EBRD,
BP
BP
EBRD,
KPMG,
UNFCCC
UNFCCC
DEA
DEA
UNFCCC
EEA
Norway
NPD,
UNFCCC
NPD,
UNFCCC
UNFCCC
EEA,
UNFCCC
UK
DEFRA,
UNFCCC
DEFRA,
UNFCCC
UNFCCC
DEFRA,
EEA,
DECC,
UNFCCC
Russia
Denmark
UNFCCC
UNFCCC
UNFCCC
NPD
Representative
MCON
Iranian Heavy
Basrah Light
Kirkuk
Kuwait Blend
Arab Light
Arab Heavy
Saharan Blend
Dalia
Girassol
Greater
Plutonio
Es Sider
El Sharara
Bonga
Forcados
Bonny light
Escravos
Azeri light
Azeri BTC
Tengiz
CPC blend
Druzhba
Siberia Light
Urals
DUC
Stratfjord
Ekofisk
Troll
Asgard Blend
Oseberg
Gullfaks blend
Forties
UNFCCC
Mexico
Venezuela
DEFRA
Brent Blend
Captain
Maya
Boscan
MCON (or field) specific data
Production
VFF
BP
BP
BP
BP
NNPC
NNPC
NNPC
NNPC
BP
BP
BP
BP
DEA
Transport
Refining
Distribution
Total
BP
BP
BP
BP
DEA
MAERSK OIL
CDP/STATOIL
CDP/STATOIL
CDP/STATOIL
CDP/STATOIL
CDP/STATOIL
NEXEN
DECC,
NEXEN
DECC
DECC
NEXEN
Table 3.30: Sources of measured and reported emission data organized per process country and MCON
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3.7
Interim Report
ACTUAL DATA FOR NATURAL GAS
The sources of actual data for natural gas are largely the same as those of oil. In
addition, given the fact that several fields produce both oil and natural gas, GHG
emissions provided by several sources are addressed both to oil and natural gas.
Thus, any further allocation of emissions to either oil or gas requires the development
of appropriate methodology. The main sources of actual data for natural gas are
summarized in Table 3.31 and analysed accordingly in the following sections.
Significant sources of actual data have been identified in the UNFCCC Annex I country
reports for Russia, Norway, Germany, Netherlands and United Kingdom. A significant
source of actual measurements of the Russian pipeline system and relevant emission
assessments comes from the work carried out by the Wuppertal Institute. Additionally
in United Kingdom, DEFRA published detailed data for major natural gas activities at a
country level. Furthermore, field specific data have been found for certain Norwegian
gas fields. Lastly, partial actual emission data for Qatar natural gas derive from the
involved gas companies’ reports. The actual data that have been collected are
presented in the Sections below.
Country/
Region
Source
Actual data type
Coverage
EU wide or various countries
Russia,
Norway, UK,
Netherlands
UNFCCC Annex I
country reports for
2012
Worldwide
National Oceanic
and Atmospheric
Administration
(NOAA)
Emissions and co-efficient factors for
the following activities regarding
natural gas:
 Exploration
 Production/processing
 Flaring and venting
 Transport
 Distribution
 Other leakages

Flaring volumes for oil and
natural gas fields
Country data
Country level
and field level
National reporting
Russia
UK
Wuppertal’s study
on GHG
Emissions
from the Russian
Natural Gas
Export Pipeline
System
National
Atmospheric
Emission



CO2 emissions
CH4 emissions
NOX emissions
CO2 emissions for the following
natural gas activities:
 Upstream gas activities
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Data regard the
entire Russian
pipeline system
Country data
Page 154
Study on actual GHG data for diesel, petrol, kerosene and natural gas
Country/
Region
Source
Inventory
Norway
Norwegian
Environment
Agency
Nigeria
Nigerian National
Petroleum
Corporation
Annual Report
2013 (NNPC)
Carbon
Disclosure
Project
Actual data type
Gas leakage at natural gas
supply
 Gas leakage at transmission
 Gas leakage at point of use
 Venting
 Flaring
Data regarding all Norwegian oil and
gas fields and facilities:
 Energy use
 Production volumes
 Emissions

BP
BP Sustainability
report 2012
Azerbaijan
RasGas
Company
Sustainability
Report for 2013




3.7.1
Flaring quantities for a large
number of oil and gas fields
Company reporting
 Exploration, production & gas
 processing
Carbon Disclosure  Storage, transportation &
Project (CDP)
 distribution
 Speciality operations
 Refining
Company report
Coverage





QatarGas
Interim Report


Oil and gas field
specific data
Field specific
data
Data provided
per company
Total emissions
Flaring emissions
Flaring volumes
Production emissions
Country specific
data as well field
specific data
particularly for
Shaz Deniz field
Direct CO2 emissions
Indirect CO2 emissions
Flaring emissions
Venting emissions
Data regarding
the entire
company
Flaring emissions
GHG intensity
Data regarding
the entire
company for the
st
1 semester of
2014
Table 3.31: Overview of natural gas actual data sourcesRussia
Apart from the UNFCCC data for the Russian natural sector emissions, very significant
actual data result from the Wuppertal’s institute study for GHG emissions from the
Russian Natural Gas Export Pipeline System that has been based on actual
measurements.
Table 3.32 shows the GHG emissions of Russian natural gas transport pipelines
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Interim Report
exporting to Europe in 2003 by gas and source. It shows that almost 70 % of GHG
emissions from gas transportation are CO2, primarily the exhaust from the gas turbines
used to drive the compressors, and the CO2 from Russian power generation which is
supplied to the electric motors used by the gas transportation pipelines. CO2 emissions
from ignited gas from breakdowns by contrast are of almost no relevance. The same is
also valid for N2O emissions which comes from the turbine exhausts or the power
supply, and accounts for some 1 % of greenhouse gas emissions along the export
corridors.
According to the study, the total CH4 losses accounted for slightly below 31% of GHG
emissions. Two thirds of this were emitted from leaks on fittings of the machines,
compressor stations and valve nodes on the pipelines. Another significant proportion is
due to the venting (i.e. the discharging of gas to atmosphere) of shop and pipelines for
maintenance and repair purposes; taking the worst-case assumptions that were made,
venting accounts for a good 5 % of GHG emissions along the export corridors.
GHG Emissions by plant section/mode
Million t CO2 equivalent
Share
Turbine exhaust
37.27
63.0%
Power supply (for electric drives)
3.03
5.1%
Breakdowns (ignited)
0.03
0.1%
Total CO2
40.33
68.2%
N2O (turbines and power generation)
0.58
1.0%
12.42
21.0%
Leaks from compressors
11.07
18.7%
Other leaks from compressor stations
0.04
0.1%
Leaks from pipelines
1.31
2.2%
1.32
2.2%
Fuel gas, startup gas and pulse gas supply
0.57
0.9%
Seal oil systems (shaft seals)
0.75
1.3%
3.48
5.9%
Compressor startup/shutdown
0.37
0.6%
Methane in turbine waste gas
0.09
0.2%
Maintenance/repairs to stations (incl. the (incl.
the venting of fittings and pipeline pigging)
1.05
1.8%
Maintenance/repairs to pipelines
1.97
3.3%
CH4 from breakdowns
0.15
0.3%
CH4 from underground storage (pro rata)
0.36
0.6%
CH4 from power supply
0.48
0.8%
Total CH4
Total of greenhouse gas emissions overall
18.21
59.12
30.8%
100.0%
CO2
CH4
Leaks from fittings and vents
operational (measured)
operational (calculated)
Table 3.32: GHG actual emissions from the Russian export pipelines to Europe
(in million tonnes of CO2 equivalent) (source: Wuppertal Institute)
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3.7.2
Interim Report
The Netherlands
Given the scarcity of actual data for natural gas compared to oil, the UNFCCC Annex I
country reports for 2012 are a significant source of actual emissions. The relevant
Tables have been presented both for oil and natural gas in Section 3.6.1, 3.6.3, 3.6.4,
for Russia, UK and Norway including emissions and co-efficient factors for exploration,
production/processing, distribution, leakages flaring and venting. UNFCCC actual
emission data for the Netherlands - which is mainly a gas producing country - are
presented in Table 3.33.
GREENHOUSE GAS
SOURCE AND
SINK CATEGORIES
ACTIVITY DATA
Description
Unit
Value
IMPLIED EMISSION
FACTORS
EMISSIONS
CO2
CO2
CH4
(Gg)
(kg/unit)
1. B. 2. a. Oil
728.47
v. Distribution of
Oil Products
number of
wells
drilled/tested
Refery input:
crude oil,
NGL
oil
transported
by pipeline
Refery input:
crude oil,
NGL
(e.g. PJ oil
refined)
vi. Other
(specify)
i. Exploration
ii. Production
iii. Transport
iv. Refining /
Storage
ii. Production /
Processing
iii. Transmission
iv. Distribution
number of
wells
drilled/tested
gas
produced
gas
transported
natural gas
distribution
network
IE
IE
IE
IE
PJ
NA
IE
IE
IE
IE
Gg
43.82
0.53
5.85
0.02
0.26
PJ
2,329.47
312,708.25
272.96
728.44
0.64
NE
NE
NE
NE
NE
NE
NE
NE
NE
NE
0.58
19.27
number
NA
IE
IE
IE
IE
PJ
2,409.00
IE
IE
IE
IE
PJ
3,250.52
58.58
2,062.75
0.19
6.71
124.47
3,105.78
100,952.8
0.39
12.57
IE
NE
IE
NE
IE
IE
NE
IE
NE
IE
IE
NE
IE
NE
IE
2.46
14.55
3
10 km
v. Other
Leakage
at industrial plants and
power stations
in residential and
commercial sectors
1. B. 2. c. Venting
i. Oil
ii. Gas
oil produced
gas
produced
iii. Combined
6
3
10 m
1.27
IE
IE
IE
IE
PJ
2,419.00
IE
IE
IE
IE
PJ
IE
IE
IE
2.46
14.55
59.14
0.31
IE
IE
Flaring
i. Oil
oil produced
0.89
IE
1. B. 2. b. Natural Gas
i. Exploration
CH4
6
3
10 m
1.27
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IE
IE
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GREENHOUSE GAS
SOURCE AND
SINK CATEGORIES
ACTIVITY DATA
Description
Unit
Value
Interim Report
IMPLIED EMISSION
FACTORS
EMISSIONS
CO2
CO2
CH4
(Gg)
(kg/unit)
gas
produced
ii. Gas
PJ
2,419.00
CH4
IE
IE
IE
IE
(specify)
iii. Combined
IE
IE
IE
59.14
0.31
NE (Not Estimated): For existing emissions and removals which have not been estimated
IE (Included Elsewhere): For emissions or removals estimated but included elsewhere in the inventory
instead of the expected category
NA (Not Applicable): For activities in a given source/sink category that do not result in emissions or removals
of a specific gas
Table 3.33: UNFCCC country data for the Netherlands (source: UNFCCC)
3.7.3
Germany
Likewise, Table 3.34 illustrates the UNFCCC data from natural activities for Germany
which is also an important gas producing country.
GREENHOUSE GAS
SOURCE AND
SINK CATEGORIES
ACTIVITY DATA
Description
Unit
Value
IMPLIED
EMISSION
FACTORS
CO2
CH4
EMISSIONS
CO2
CH4
(Gg)
(kg/unit)
1. B. 2. a. Oil
57.75
14.22
i. Exploration
number of
wells drilled
number
26.00
0.48
64.00
0.00
0.00
ii. Production
oil produced
Gg
2,622.82
0.31
0.01
0.82
0.02
iii. Transport
oil transported
in pipelines
Mt
102.92
NA
0.06
NA
5.66
iv. Refining /
Storage
oil refined
Mt
95.84
0.59
0.09
56.93
8.54
v. Distribution of
Oil Products
distribution of
oil products
kt
79,533.00
NO
NA
NO
NA
990.01
255.64
1. B. 2. b. Natural Gas
i. Exploration
ii. Production /
Processing
iii. Transmission
iv. Distribution
v. Other
Leakage
at industrial plants and
power stations
in residential and
commercial sectors
1. B. 2. c. Venting
numbers of
wells drilled
production
and
processing
high pressure
pipelines
distribution
net
gas
consumed
gas
consumed
gas
consumed
number
IE
IE
IE
IE
IE
TJ
341,510.00
2,898.92
5.53
990.01
1.89
km
64,023.00
NO
249.11
NO
15.95
km
439,466.00
NO
423.22
NO
185.99
TJ
1,301,080.0
NO
39.82
NO
51.81
TJ
IE
NO
IE
NO
10.14
TJ
1,301,080.00
NO
32.03
NO
41.67
IE
IE
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i. Oil
vented natural
gas
ii. Gas
iii. Combined
Interim Report
m
3
IE
IE
IE
IE
IE
m
3
IE
IE
IE
IE
IE
m
3
IE
IE
IE
IE
IE
406.64
6.41
Flaring
i. Oil
Gg
flared natural
gas
ii. Gas
m
3
IE
IE
IE
385.94
0.13
11,648,066
1,777.00
539.84
20.70
6.29
3
iii. Combined
m
IE
IE
IE
IE
IE
IE (Included Elsewhere): For emissions or removals estimated but included elsewhere in the inventory instead of
the expected category
NO (Not Occurring): For emissions and removals of GHG that do not occur for a particular gas or source/sink
category
NA (Not Applicable): For activities in a given source/sink category that do not result in emissions or removals of a
specific gas
Table 3.34: Breakdown of emissions of the UK gas sector by source in million
metric tonnes (source: DEFRA)
3.7.4
Norway
Table 3.35 illustrates the releases of major pollutants to the air (CO 2, CH4 and NOX) for
two major natural gas fields Snøhvit and Troll. It is evident that CO2 emissions for
Snøhvit have significantly decreased over the last decade, while for Troll field CO2
emissions have dropped down by 35% from 2009 to 2013.
Snøhvit: Releases of major
pollutants to the air (in 1000
tonnes per year)
CO2
CH4
NOx
Year
2004
1.60
0.00
35.08
2005
29.64
0.00
2006
51.75
2007
Year
Troll : Releases major pollutants the air
(CO2) (in 1000 tonnes per year)
CO2
CH4
NOx
2004
-
-
-
447.82
2005
-
-
-
3.25
449.26
2006
-
-
-
-
-
-
2007
-
-
-
2008
-
-
-
2008
-
-
-
2009
-
-
-
2009
689.35
1,594.24
4,498.87
2010
-
-
-
2010
705.61
1,446.13
4,396.74
2011
2.11
0.00
46.61
2011
713.37
1,441.18
5,438.67
2012
-
-
-
2012
685.46
1,435.92
4,631.69
2013
0.24
0.00
5.27
2013
443.50
1,560.64
3,852.90
Table 3.35: Releases of major pollutants for Snøhvit and Troll oil fields (source:
Norwegian Environment Directorate)
The emissions from two other significant Norwegian gas fields, Kvitebjørn and Åsgard,
are illustrated in Table 3.36. The cumulative emissions from Kvitebjørn have increased
over the last years as a result of increased gas production, even though it has to be
stated that emissions per unit of gas produced have decreased from 25 tonnes CO 2
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Interim Report
equivalent per million cubic meter in 2008 to approximately 11 tonnes CO2 equivalent
per million cubic meter in 2013. On the other hand, the emissions from Åsgard gas field
have slightly decreased over time, but have increased per unit of output. In general
emissions per unit of output for Åsgard are much higher compared to Kvitebjørn.
Kvitebjørn
Åsgard
Emissions in
CO2equivalents (in
tonnes per
year)
Production
volume of gas
(in m³ per
year)
Emissions per
unit of gas
produced
(tonnes/million
3
m per year)
Emissions in
CO2equivalents (in
tonnes per
year)
Production
volume of
gas (in m³
per year)
Emissions per
unit of gas
produced
(tonnes/million
3
m per year)
2008
77,176
3,139.538
24.58
1,008,090
21,694.066
46.47
2009
80,112
5,310.39
15.09
1,041,109
21,413.73
48.62
2010
77,324
6,331.126
12.21
1,011,688
20,189.455
50.11
2011
65,975
6,745.399
9.78
1,011,383
18,090.706
55.91
2012
65,961
7,232.191
9.12
1,058,664
18,453.788
57.37
2013
81,029
7126.765
11.37
933,613
15,829.225
58.98
Year
Table 3.36: Carbon emissions for Kvitebjørn and Åsgard oil fields (source:
Norwegian Environment Directorate)
3.7.5
United Kingdom
Actual emissions data for the natural gas sector in United Kingdom are illustrated in
Figure 3.56. It can be obtained that total atmospheric emissions of the UK gas sector
are higher compared to the oil sector. More specifically, the sum of emissions of the
gas sector have decreased with a slow pace from approximately 5,400 kilotonnes CO2
to 5,000 kilotonnes in 2012. The highest emissions are due to gas leakages at gas
supply points which in 2012 comprised 74% of the total gas emissions. The second
highest source is venting which in 2012 accounted for 10% of total emissions of the
sector.
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4500
4000
3500
3000
2500
2000
1500
1000
500
0
2008
2009
Upstream Gas Production - process emissions
Upstream Gas Production - Offshore Well Testing
Gas leakage at point of use
Upstream Gas Production - venting
2010
2011
2012
Upstream Gas Production - Gas terminal storage
Gas leakage at natural gas supply
Gas leakage at transmission
Upstream Gas Production - flaring
Figure 3.56: Breakdown of emissions of the UK gas sector by source in
kilotonnes CO2 (source: DEFRA)
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3.7.6
Interim Report
Qatar
Qatar is another significant gas producing country. No actual official statistics have
been identified from national authorities. However, actual emissions data have been
found by Qatargas and RasGas companies. Data for RasGas are summarized in Table
3.37 from where it is clear that GHG emissions in the period 2007-2013 have almost
doubled. However, it has to be noted that flaring emissions have decreased from 1.4 to
1.1 million tonnes of CO2
RasGas emissions 2007-2013
GHF emissions (million
tonnes)
2007
2008
2009
2010
2011
2012
2013
Total GHG emissions of CO2
equivalent
9.4
9.3
8.9
16.8
18.8
18.7
17.9
Total direct GHG emissions
9
9.2
8.6
15.9
18.4
18.3
17.7
from purchased electricity
0.3
0.1
0.3
0.4
0.4
0.4
0.2
CO2 from flaring
1.4
1.5
1.1
1.4
1.7
1.4
1.1
CO2 removal from feed and
vented
0.7
0.8
0.8
2.1
2.4
2.5
2.5
CO2 from combustion
6.6
6.6
6.4
12.4
13.8
13.9
13.6
Total CO2
8.7
8.8
8.3
15.9
17.9
17.8
17.2
Methane (CH4)
0.01
0.01
0.008
0.01
0.01
0.0009
0.0008
Nitrous oxide (N2O) (tonnes)
435
449
432
860
945
931
898
0.286
0.269
0.248
0.28
0.287
0.281
0.271
Tonnes GHG per tonne
hydrocarbon
Table 3.37: RasGas company cumulative emissions 2007-2013
Figure 3.57 and Figure 3.58 present Qatargas’s flaring emissions and GHG intensity
respectively until May 2014 for the industry average, the company’s target and the
company’s emissions. For flaring it can be seen that company emissions are below
industry average and well below company targets. Similarly, the company exhibits
satisfactory performance for GHG intensity which lies also below industry average and
company targets.
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1.4
0.442
1.2
0.44
1
0.438
Interim Report
0.436
0.8
0.434
0.6
0.432
0.4
0.43
0.2
0.428
0
0.426
Industry
average
Actual
Target
Figure 3.57: Flaring (% of sweet gas) for
Qatargas for the 1st half of
2014
3.8
3.8.1
Industry
average
Actual
Target
Figure 3.58: GHG intensity (tonne
CO2 eq. GHG/ tonne
LNG) for Qatargas for
the first half of 2014
DATA FOR MODELS
Data for OPGEE
According to the data collection strategy, in the absence of direct GHG emissions the
Consultant will use the OPGEE model for the assessment of GHG emissions for the
upstream and midstream life cycle stages. OPGEE is a complex engineering model
that requires a large amount of data as inputs. The collection of such data has been a
rather time consuming Task since it requires research in a large amount of sources, as
well as validation of their reliability. The effort and the resources that have been
committed by the Consultant for the collection of OPGEE inputs have been based on
the parametric analysis which is described in Section 4.1.3. For the missing inputs
smart default values or Consultant’s estimations have been used based on country
averages and expert opinion.
The most significant source of information for filling in OPGEE inputs has been the
companies’ websites. Usually these included detailed data regarding partners and
their share on specific oil fields, crude oil assays, API, sulphur content, field depth,
commingling fields comprising an MCON, the terminal that oil is loaded etc.
Furthermore, it can be assumed that these data are up-to-date and fully reliable. In
addition, crude oil assays for MCONs are found published on company websites.
Another significant and fully reliable source of information has been public databases
of national authorities and more specifically DECC for UK, DEA for Denmark, NPD
for Norway and NNPC for Nigeria. These include information regarding oil production
volumes, gas production volumes, water production for all major fields in the relevant
countries, field depth, gas injected water and other critical parameters for an oil field.
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The California Air Resources Board (CARB) has published in its website the bulk
assessment sheet of OPGEE for the crudes imported in California, which does not only
provide technical information for a number of fields, but also methodologies for
estimating inputs for OPGEE when no values are available. Apparently this approach is
available for MCONs, which are imported in California; however several of these
MCONs are also imported in Europe. Similarly, reservoir parameters for significant
crude oils can be found in other studies (e.g. Jacobs).
The NOAA/GGFR database has been a typical source of flared natural gas volume (in
bcm) used in several studies. Using the EIA crude oil production volumes the flaring to
oil ratio (FOR) has been calculated on a country basis, which provides a sufficient
approximation of the FOR compared to the generic values, when there are no field
specific data. Actual flaring to oil ratio has been available only for Nigerian Oil fields,
provided by NNPC. Another source of flaring and venting emissions has been the
submitted UNFCCC reports of countries of Annex I (UK, Russia, Germany,
Netherlands and Norway). The UNFCCC data include also reported data for
exploration, production, transport, refining/storage and distribution of oil products on a
country basis.
Private websites11 dealing with offshore oil and gas engineering, construction projects
and procurement have also been useful for data collection. These websites included
detailed data for several oil fields as well as a better understanding of oil extraction and
production techniques used specifically for each field.
Table 3.38 summarizes the main sources of OPGGE input parameters and the ease of
finding the specific type of information. The last column of the Table indicates whether
the Consultant has used own estimations based on background data in order to better
approach the input, compared to OPGEE’s default values.
11
Offshore technology and Subsea IQ
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OPGEE input
Ease of
finding
information
Operator’s
Website
Interim Report
OGJ
NOAA
UNFCCC
Offshore
tech.
Subsea
IQ
DECC
NPD
NNPC
DEA
CARB
Own
estimation
1. Production methods
√
1.1 Downhole pump
√
1.2 Water reinjection
√
√
√
1.3 Gas reinjection
√
1.4 Water flooding
√
1.5 Gas lifting
√
1.6 Gas flooding
√
1.7 Steam flooding
√
2. Field properties
2.1 Field location (Country)
√
√
√
√
√
√
√
√
√
2.2 Field name
√
√
√
√
√
√
√
√
√
2.3 Field age
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
√
2.4 Field depth
2.5 Oil production volume
√
2.6 Number of producing wells
2.7 Number of water injecting
wells
2.8 Well diameter
√
√
√
√
2.9 Productivity index
√
2.10 Reservoir pressure
3. Properties
3.1 API gravity
√
√
√
√
3.2 Gas composition
4. Production practices
4.1 Gas-to-oil ratio (GOR)
√
4.2 Water-to-oil ratio (WOR)
√
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
√
√
√
√
√
√
√
√
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OPGEE input
Ease of
finding
information
Operator’s
Website
Interim Report
OGJ
NOAA
UNFCCC
Offshore
tech.
Subsea
IQ
DECC
NPD
NNPC
DEA
CARB
Own
estimation
√
4.3 Water injection ratio
4.4 Gas lifting injection ratio
4.5 Gas flooding injection ratio
4.6 Steam-to-oil ratio (SOR)
4.7 Fraction of required
electricity generated onsite
4.8 Fraction of remaining gas
re-injected
4.9 Fraction of water produced
water re-injected
4.10 Fraction of steam
generation via cogeneration
5. Processing practices
√
5.1 Heater/treater
5.2 Stabilizer column
5.3 Application of AGR unit
5.4 Application of gas
dehydration unit
5.5 Application of
demethanizer unit
5.6 Flaring-to-oil ratio
√
5.7 Venting-to-oil ratio
√
√
√
√
√
5.8 Volume fraction of diluent
Table 3.38: Overview of literature sources for OPGEE inputs
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3.8.2
Interim Report
Data for PRIMES-Refinery
The key input data that are required for the PRIMES-Refinery model are the capacities
of the refining processes within the refinery configuration per EU country and the
various amounts of MCONs that enter European refineries. The Oil and Gas Journal
Worldwide Refining Survey presents analytical data for the worldwide refineries and
their capacities. A list of the refineries located in the EU countries is presented in Table
3.39. In particular, the survey provides information on the number of active refinery
industries in Europe, the main operations as well as charge and production capacity for
every single refinery. The various MCONs are aggregated and characterised by their
API gravity and sulphur content. This part is particularly important for allocating the
different MCONs entering the refinery gates of each EU country with the representative
crude type categories simulated in the PRIMES-Refinery model.
Feedstock supply for the refineries operations, as well as consumption of electricity and
gas are derived from the EUROSTAT energy balances. The total refined petroleum
products that are produced at a national level over the EU countries is also provided by
the EUROSTAT balances. The quantities of refined petroleum products imported in the
EU are provided in the Section 3.1.2. The survey of Oil and Gas Journal and the study
of Jacobs Consultancy will be used for the identification of the representative
configuration of the refineries exporting refined products to EU. A more detailed
presentation of the key input data to the PRIMES-Refinery model is included in Section
3.8.2.
Country
Austria
Belgium
Bulgaria
Croatia
Czech
Republic
Number
of
refineries
1
4
1
3
3
Denmark
2
Finland
2
Company
Location
OMV AG
Schwechat
AB Nynas Petroleum NV
Antwerp
ExxonMobil Refining & Supply Co.
Antwerp
Vitol Group
Antwerp
Total SA
Antwerp
Neftochim
Bourgas
Ina-Industrija Nafte d.d.
Rijeka
Ina-Industrija Nafte d.d.
Sisak
Ina-Industrija Nafte d.d.
Zagreb
Czech Refining Co.
Kralupy
Czech Refining Co.
Litvinov
Paramo AS
Pardubice
AS Dansk Shell
Fredericia
Dansk Statoil AS
Kalundborg
Neste Oil
Naantali
Neste Oil
Porvoo
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Country
France
Germany
Greece
Number
of
refineries
10
15
4
Interim Report
Company
Location
Calos
Dunkirk
ExxonMobil Refining & Supply Co.
Fos sur Mer
ExxonMobil Refining & Supply Co.
Port Jerome/NDG
Petrolneos Refining Ltd.
Lavera
LyondellBasell Industries
Berre l'Etang
Total SA
Donges
Total SA
Feyzin
Total SA
Gonfreville l'Orcher
Total SA
Grandpuits
Total SA
La Mede
Bayernoil Raffineriegesellschaft
GMBH
Vohburg/Ingolstadt/Neustadt
BP PLC
Gelsenkirchen
Hestya Energy BV
Wilhelmshaven
Deutsche BP AG Erdol Raffinerie
GMBH
Lingen
Deutsche Shell AG
Rheinland
Deutsche Shell AG
Harburg
H&R Chemisch-Pharmazeutische
Spezialitaeten GMBH
Salzbergen
H&R Oelwerke Schindler GMBH
Hamburg
Holborn Europa Raffinerie GMBH
Harburg
Klesch & Co.
Heide
Mineraloelraffinerie Oberrhein
GMBH
Karlsruhe
OMV AG
Burghausen
PCK Raffinerie GMBH
Schwedt
Gunvor Group Ltd.
Ingolstadt
Total SA
Leuna, Spergau
Hellenic Petroleum SA
Aspropyrgos
Hellenic Petroleum SA
Elefsis
Hellenic Petroleum SA
Thessaloniki
Motor Oil (Hellas) Corinth
Refineries SA
Aghii Theodori
Hungary
1
MOL Hungarian Oil & Gas Co.
Szazhalombatta
Ireland
1
Phillips 66
Whitegate
Eni SPA
Gela, Ragusa
Enii SPA
Livorno
Enii SPA
Sannazzaro, Pavia
Eni SPA
Taranto
Italy
15
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Country
Lithuania
Netherlands
Poland
Portugal
Romania
Number
of
refineries
1
6
4
2
9
Interim Report
Company
Location
Api Raffineria di Ancona SPA
Falconara, Marittima
Arcola Petrolifera SPA
La Spezia
ERG Reffinerie Medditerranee
North
Priolo, Sicily
ERG Reffinerie Medditerranee
South
Melilli, Sicily
ExxonMobil Refining & Supply Co.
Augusta, Siracusa
ExxonMobil Refining & Supply Co.
S. Martino Di Trecate
Iplom SPA
Busalla
Italiana Energia E Servizi SPA
Mantova
Raffineria di Milazzo SPA
Milazzo, Messina
Raffineria di Roma SPA
Rome
Saras SPA
Sarroch
AB Mazeikiu Nafta
Mazeikiai
BP PLC
Rotterdam
ExxonMobil Refining & Supply Co.
Rotterdam
Kuwait Petroleum Europoort BV
Rotterdam
Shell Nederland Raffinaderij BV
Pernis
Smid & Hollander Raffinaderij BV
Amsterdam
Total SA
Vlissingen
Grupa Lotos SA
Gdansk
Nafta Polska SA
Gorlice
Nafta Polska SA
Jaslo
PKN Orlen SA
Plock/Trezebina
Galp Energia
Leca da Palmeira, Porto
Galp Energia
Sines
Astra SA
Ploiesti
Petrobrazi SA
Ploiesti
Petrolsub SA
Bacau
Petromidia SA
Midia
Petrotel SA
Ploiesti
Rafinaria Darmanesti SA
Darmanesti
Rafo SA
Onesti, Bacau
Rompetrol SA Vega Refinery
Ploiesti
Steaua Romania SA
Cimpina
Slovakia
1
Slovnaft Joint Stock Co.
Bratislava
Slovenia
1
Nafte Lendava
Lendava
Spain
9
BP PLC
Castellon de la Plana
Cia. Espanola de Petroles SA
Cadiz
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Country
Sweden
United
Kingdom
Number
of
refineries
5
9
Interim Report
Company
Location
Cia. Espanola de Petroles SA
Huelva
Cia. Espanola de Petroles SA
Tenerife
Petronor SA
Muskiz Vizcaya
Repsol YPF SA
Cartagena Murcia
Repsol YPF SA
La Coruna
Repsol YPF SA
Puertollano, Ciudad Real
Repsol YPF SA
Tarragona
AB Nynas Petroleum
Gothenburg
AB Nynas Petroleum
Nynashamn
Preem Raffinaderi AB
Brofjorden-Lysekil
Preem Raffinaderi AB
Gothenburg
Shell Raffinaderi AB
Gothenburg
AB Nynas Petroleum
Eastham
Phillips 66
South Killingholme
Essar UK Ltd.
Stanlow
ExxonMobil Refining & Supply Co.
Fawley
Total SA
Killingholme South
Humberside
AB Nynas Petroleum
Dundee
Petrolneos Refining Ltd.
Grangemouth
Murco Petroleum Ltd.
Milford Haven
Valero Energy Corp.
Pembroke, Dyfed
Table 3.39: List of refineries located in the EU countries (Source: Oil and Gas
Journal, 2013)
3.8.3
Data for GHGenius
In the following Sections the most significant sources of data to be used as input to the
GHGenius model are presented.
Regional Natural Gas Supply/Demand
Natural gas supply and demand data for each EU country have been extracted and
elaborated from IEA database for the year 2012. The model input will be the quantities
of gas supplied by each producer. The data are shown in Table 3.40.
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Consuming
countries EU28
Interim Report
Producing countries
Germany
Denmark
Netherlands
Poland
Hungary
Norway
Norway
LNG
Nigeria
LNG
Qatar
LNG
Other
TOTAL
Bulgaria
0
0
0
0
0
0
0
0
0
0
2485
0
0
Greece
0
0
0
0
0
0
0
0
0
0
2453
0
734
0
0
0
0
2485
0
0
0
0
3187
Croatia
60
0
0
0
0
0
0
0
667
0
0
0
0
0
0
0
0
727
2904
0
2466
0
0
2726
0
0
7.877
0
18071
20843
1110
6469
0
5925
3850
72241
Romania
0
0
0
0
0
0
0
0
0
10935
2469
0
0
0
0
0
0
13404
Slovenia
0
0
0
0
0
0
0
0
61
0
365
139
139
0
0
0
0
704
Belgium
0
0
6780
0
0
7009
0
1690
0
0
0
0
0
0
0
2158
2158
19795
Czech Republic
0
0
0
0
0
3
0
0
0
0
7468
0
0
0
0
0
0
7471
5239
0
25952
0
0
24482
0
0
0
0
32632
0
0
0
0
0
5335
93640
Estonia
0
0
0
0
0
0
0
0
0
0
670
0
0
0
0
0
0
670
Latvia
0
0
0
0
0
0
0
0
0
0
1716
0
0
0
0
0
0
1716
Lithuania
0
0
0
0
0
0
0
0
0
0
3320
0
0
0
0
0
0
3320
Luxembourg
0
0
14
0
0
627
0
0
0
0
290
0
0
0
0
0
129
1060
Hungary
0
0
0
0
1.456
0
0
0
0
0
3576
0
0
0
0
0
4597
9629
586
1309
30.223
0
0
15868
761
4380
0
0
2931
0
0
0
0
0
0
56058
Austria
0
0
0
0
0
1981
0
0
0
0
8950
0
0
0
0
0
3239
14170
Poland
Italy
Germany
Netherlands
UK
Italy
Romania
Russia
Algeria
pipeline
Algeria
LNG
Libya
1888
0
0
6193
0
0
0
0
0
0
9769
0
0
0
0
0
0
17850
Slovakia
0
0
0
0
0
0
0
0
0
0
4801
0
0
0
0
0
0
4801
Denmark
0
3.345
0
0
0
622
0
0
0
0
0
0
0
0
0
0
0
3967
Ireland
0
0
0
0
0
0
0
4522
0
0
0
0
0
0
0
0
0
4522
Finland
0
0
0
0
0
0
0
0
0
0
3683
0
0
0
0
0
0
3683
Sweden
0
1130
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1130
United Kingdom
0
0
9566
0
0
26812
0
30222
0
0
0
0
0
0
0
13091
0
79691
Spain
0
0
0
0
0
2348
1684
0
0
0
0
10835
4014
0
5422
4675
0
28978
2156
0
9664
0
0
18380
158
0
0
0
6441
0
4160
0
3715
1886
0
46560
Portugal
0
0
0
0
0
0
0
0
0
0
0
2090
0
0
1853
164
0
4107
TOTAL
12833
5784
84665
6193
1456
100858
2603
40814
8605
10935
112090
33907
10157
6469
10990
27899
19308
495566
France
Table 3.40: EU Gas Supply (million cm)
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Table A.Table A.Regional Electric Power – EU
Electric power will be used for the compression of the natural gas to be used in CNG
compressors. This requires the emission profile for the average mix of electric power
used in each of the 26 countries considered by the model. These data are being
extracted and compiled from Eurostat data for the year 2012. The data are analysed by
country and are aggregated by EU region as it is shown in Table 3.41.
Electric Power Supply
EU Region
Coal
Oil
Gas
Nuclear
Wind Other Carbon Biomass Hydro Other
North
0.100
0.025
0.120
0.523
0.104
0.007
0.015
0.104
0.001
Central
0.385
0.016
0.175
0.168
0.081
0.029
0.065
0.078
0.002
SE
0.247
0.069
0.333
0.048
0.102
0.017
0.029
0.152
0.002
SW
0.277
0.007
0.436
0.000
0.024
0.008
0.002
0.237
0.000
Table 3.41: Regional EU Power Supply (the percentage of power supplied by
each type of generation)
The electric power calculations also require the efficiency of the thermal power plants;
these data are also extracted from Eurostat. Power plants that are combined heat and
power plants have their efficiencies calculated by allocating the energy input to the heat
and power on an energy basis. The results are analysed by country and aggregated to
EU regions as it is shown in
Table 3.43
Electric Power Efficiency
EU Region
Coal
Oil
Gas
Nuclear
Wind
Other Carbon Biomass
Hydro
North
0.395
0.615
0.557
0.350
1.000
0.395
0.329
1.000
Central
0.394
0.685
0.540
0.350
1.000
0.394
0.373
1.000
SE
0.354
0.461
0.548
0.350
1.000
0.354
0.191
1.000
SW
0.357
0.452
0.501
0.350
1.000
0.357
0.250
1.000
Table 3.42: Regional EU Power Generation Efficiency
Finally the electrical distribution losses are calculated on a country basis and
aggregated on a regional basis. The results are shown in
Table
3.43.
The
GHGenius model will use all of this information to calculate the GHG emission intensity
of the power consumed in each region.
EU Region
Power Distribution Losses
North
8.03%
Central
5.69%
SE
8.19%
SW
9.45%
Table 3.43: Electric Power Distribution Losses
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Regional Electric Power – Gas Producers
Some electricity is used in the natural gas upstream stage, i.e. in gas production and
processing stages. The power generation mix will be added to the model for all of the
producing regions, but the model will use the distribution efficiency and the generation
efficiency from the consuming region. Some of the producing countries have the
information required as they are part of the Eurostat’s database. The rest of the data
for other producers have been obtained from the IEA database. The power mix for all
considered natural gas producing countries is presented in Table 3.44.
Renewables
Coal
Oil
Gas
Nuclear
Other
Carbon
Wind
Biomass
Hydro
UK
0.39
0.01
0.28
0.19
0.01
0.06
0.04
0.02
Norway
0.00
0.00
0.02
0.00
0.00
0.01
0.00
0.96
Netherlands
0.24
0.01
0.54
0.04
0.05
0.05
0.07
0.00
Denmark
0.34
0.01
0.14
0.00
0.02
0.34
0.15
0.00
Germany
0.46
0.01
0.12
0.16
0.08
0.08
0.04
Italy
0.09
0.38
0.42
0.00
-
0.19
-
0.00
-
0.42
-
0.00
-
0.00
0.00
0.01
0.00
-
0.00
0.00
0.00
0.00
0.00
0.20
0.00
0.00
0.00
Romania
Poland
Hungary
Algeria
Libya
0.34
0.90
0.17
0.00
0.00
0.01
0.02
0.01
0.06
0.00
0.12
0.02
0.31
0.94
0.98
Nigeria
0.00
0.00
0.80
0.00
-
Qatar
0.00
0.00
1.00
0.00
-
0.11
0.33
0.01
0.04
0.01
0.08
Table 3.44: Natural Gas Producers Power Mix
Energy Consumption Gas Producers
The energy consumed in the production and processing of the natural gas is a key
input into the emission calculations. Data will be collected on the energy use in well
drilling, gas extraction, and gas processing stages for each gas producing region. The
input data table in the GHGenius model looks like the following table. Not all fuels will
be used in all stages in all producing regions. It is expected that the energy use will be
mostly natural gas, while some electricity and diesel fuel will also be consumed. Typical
values are shown in Table 3.45.
Energy Use in Gas Production Stages
EU Region
Well Drilling, Testing
and Servicing
Gas Extraction
Gas Processing
Fuel used, kJ/tonne gas
Crude oil
Diesel fuel
0
0
0
35,792
0
0
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Energy Use in Gas Production Stages
Well Drilling, Testing
and Servicing
Gas Extraction
Gas Processing
0
0
0
43,541
2,200,000
1,755,137
Coal
0
0
0
Electricity
0
0
79,741
Gasoline
93
0
0
Coke
0
0
0
Total
79,426
2,200,000
1,834,877
EU Region
Residual fuel
Natural gas
Table 3.45: Typical Energy Consumption Data for NG Stages
Gas that is supplied as LNG will be tracked separately in the model. The liquefaction
energy and any regasification energy will be added to the gas processing energy
requirements.
Methane Losses Gas Producers
Methane losses from the natural gas supply chain are a key differentiator in the
emission profile of different gas producing regions. GHGenius inputs the methane
emission losses as a percentage of gas produced for the well drilling and gas
extraction stage, the gas processing stage, the gas transmission stage, the gas
distribution stage and during the gas compression and dispensing stage. These data
will need to be collected for every gas producer in the model.
Wherever possible the data that will be used will be consistent with the year 2012.
Some of the developed producing countries do report this data by year. The following
Figure 3.59 on gas leakage reported for UK gas production shows how these
emissions can change over time.
0.450%
0.400%
Gas leakage
0.350%
0.300%
0.250%
0.200%
0.150%
0.100%
0.050%
0.000%
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Figure 3.59: UK Gas Leakage Rate over the years 2002 – 2012 (source: DECC)
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LNG losses will be dealt with in a similar manner to the energy consumption for LNG
production. Any additional losses will be added to the gas processing losses for each
LNG producer.
Solution Gas
A gas processing plant can remove higher hydrocarbons and contaminates from the
raw field gas. Some gas fields can have CO2 contents of 10% or greater. The CO2
content of these fields must be reduced to between 1 and 2% before the gas can enter
the pipeline system. This source of GHG emissions need to be identified for every gas
producer. For some producers the rate will be zero.
Transportation Distances
The energy consumed for gas transport and transmission is generally a difficult
exercise since natural gas pipelines can cross many transmission systems before
reaching delivery points. It may be necessary to calculate this energy use and
emissions from the transport and transmission line distances and an energy
consumption rate. A matrix has been developed with the transport distances of each
major pipeline transporting natural gas to the EU from every gas producing region to
the main delivery points and transmission system lengths for every EU consuming
region. The model will calculate the appropriate distance and energy use based on the
sources of gas used in each consuming region.
In order to calculate the GHG emissions related to natural gas transport from producing
countries to the EU, the transport distances have to be calculated for both modes of
transport: major pipelines and LNG. Separate matrices are developed for pipeline and
LNG supply systems. LNG shipping distances and an assumed size of the tankers is
used to calculate the energy consumption and emissions associated with these gas
sources.
Pipeline distances
The starting and ending points and lengths of all major pipeline routes arriving to the
EU are presented in Table 3.46. These distances derive from various sources, notably
the pipelines’ operators’ websites. After arrival to the corresponding ending point, the
natural gas flows in the interconnected EU transmission systems.
Producing
Country
Algeria
Russia
Pipeline name
Starts
Ends
Length (km)
MEDGAZ
Hassi R'Mel, Algeria
Almeria, Spain
787
TRANSMED
Hassi R'Mel, Algeria
Bologna, Italy
2,283
MEG Pipeline
Hassi R'Mel, Algeria
Cordoba, Spain
1,327
Brotherhood
Urengoy, Russia
Baumgarten, Austria
3,963
Yamal-Europe
Yamal, Russia
Germany
4196
Nord Stream
Southeastern
Europe
transport route
Franpipe
Vyborg, Russia
Greifswald, Germany
1,140
Urengoy, Russia
Greece
4,500
North Sea
Dunkirk, France
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Producing
Country
Pipeline name
Norway
Zeepipe (total)
Interim Report
Starts
Ends
Length (km)
North Sea
Zeebrugge, Belgium
1,416
Europipe (total)
North Sea
Dornum, Germany
1,328
Norpipe
Vesterled
Langeled
North Sea
North Sea
North Sea
Emden, Germany
Peterhead, Scotland
UK
354
360
1,666
UK
Interconnector
UK
Zeebrugge, Belgium
153
Libya
Green Stream
Melita
Sicily
516
Table 3.46: Lengths of major natural gas pipelines supplying the EU
LNG transportation distances
The distances between the major LNG exporting terminals of the LNG suppliers and
the major LNG importing terminals in the EU are presented in Table 3.47 and are
calculated based on the distances between the relevant ports.
LNG Producers
LNG transportation distances to the EU
in kilometers
Norway
Algeria
Nigeria
Qatar
Liquefaction terminals
LNG Importers
GR - Greece
Snohvit
Arzew
Skikda
Bonny
Ras
Laffan
Revithoussa
-
-
1963
-
-
Adriatic LNG
-
-
-
-
9310
La Spezia
-
-
978
-
-
SI - Slovenia
La Spezia
-
-
978
-
-
Central
EU
BE - Belgium
NL Netherlands
Zeebrugge
-
3502
-
9099
13290
Rotterdam
2571
-
-
9160
-
North
EU
UK - United
Kingdom
Isle Of Grain
-
3317
-
-
-
Milford Haven
Ferrol
(Mugardos)
Barcelona
-
-
-
-
12614
-
1880
-
-
-
6595
-
876
7791
9728
Cartagena
-
278
783
7195
9806
Bilbao
-
-
-
7902
12093
Huelva
IT - Italy
ES - Spain
South
West
EU
FR - France
PT - Portugal
Receiving Terminals
South
East
EU
5274
-
1428
6787
10560
Sagunto
-
-
-
7532
9819
Fos-sur-Mer
Montoir de
Bretagne
Sines
-
-
954
8230
-
3850
2698
-
8295
12486
-
-
-
6765
10838
Table 3.47: LNG transport distances from LNG suppliers to importers in the EU
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It must be noted that the LNG streams from Algeria and Libya to the EU include also a
transport distance by pipeline from the main gas producing field to the liquefaction
plants, in addition to the distance travelled by LNG carrying vessels. These distances
are presented in Table 3.48.
Producing
Country
Algeria
Libya
Pipeline
Starts
Ends
Distance
(km)
Hassi R'Mel - Arzew
Hassi R'Mel, Algeria
Arzew
515
Has Rmel Si - Skikda
Hassi R'Mel, Algeria
Skikda
616
Wafa - Melita
Wafa, Libya
Melita, Libya
598
Table 3.48: Pipeline lengths from gas fields to liquefaction plants in Algeria and
Libya
Transmission systems
As mentioned previously, the GHG emissions related to natural gas transmission and
distribution will be calculated as a function of the total pipeline length, by using
emission factors. Table 3.49 provides the natural gas transmission systems length for
each of the 26 EU countries supplied by gas. In addition to fugitive natural gas losses
in transmission pipelines, the self-consumption of gas for transmission compressors
will be assessed for the 26 national transmission systems based on EUROSTAT data.
Country
Natural gas transmission system
length (km)
Bulgaria
2,645
Greece
1,218
Croatia
2,184
Italy
31,531
Romania
13,000
Slovenia
1,018
Belgium
3,900
Czech Republic
3,643
Germany
29,216
Estonia
878
Latvia
320
Lithuania
Luxembourg
2,007
300
Hungary
5,564
Netherlands
11,500
Austria
1,595
Poland
9,709
Slovakia
2,270
Denmark
800
Ireland
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Natural gas transmission system
length (km)
Finland
1,186
Sweden
620
United Kingdom
7,880
Spain
9,236
France
37,200
Portugal
1,299
Table 3.49: The 26 Natural gas transmission systems length (Source: ENTSOG)
Distribution Systems
The methane losses for the distribution systems have to be developed for the 26 EU
countries. These are the losses for the gas once it leaves the high pressure
transmission system up to the CNG compressors through the local distribution
systems. The 2012 Eurostat data regarding distribution losses in EU countries are
presented in Table 3.50. These data concern both transmission and distribution
pipeline losses of natural gas. As shown in the table, some countries do not report the
losses of their networks and therefore relevant estimations have to be carried out. The
missing data will be sought from the corresponding system operators and their
associations.
Country
Natural gas network losses
(million cubic meters)
Bulgaria
12.63
Greece
22.84
Croatia
52.89
Italy
534.17
Romania
415.21
Slovenia
-
Belgium
-
Czech Republic
-
Germany
-
Estonia
-
Latvia
-
Lithuania
Luxembourg
Hungary
Netherlands
0.11
158.00
-
Austria
2.67
Poland
149.80
Slovakia
-
Denmark
3.17
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Natural gas network losses
(million cubic meters)
Country
Ireland
71.85
Finland
-
Sweden
-
United Kingdom
1,115.29
Spain
181.33
France
363.82
Portugal
21.27
Table 3.50: Natural gas distribution losses in EU countries for 2012 (Source:
Eurostat)
Distribution of CNG and small scale LNG
The final step in the lifecycle of natural gas required for transport is the distribution of
CNG and small scale LNG to end consumers. CNG compressors are usually
connected to the medium pressure distribution system and use electricity for
compression. In most cases the fuel is consequently transported to the CNG refilling
stations by trucks. Small scale LNG, on the other hand, is taken directly from the LNG
receiving terminals and transported to the corresponding small scale filling stations by
trucks or vessels. The associated GHG emissions to this lifecycle stage will be
calculated as a function of distances to potential CNG and small scale LNG refilling
stations by using emission factors.
In order to estimate GHG emissions associated to the compression of natural gas to
produce CNG, the study will be based on Eurostat’s data about electricity consumption
in pipeline transport in the EU. These data are presented in Table 3.51. It is assumed
that the most significant amount of electricity consumed in national gas networks is
being used for natural gas compression.
Country
Electricity consumption in gas
networks (terajoules)
Bulgaria
108
Greece
0
Croatia
68
Italy
1,616
Romania
68
Slovenia
0
Belgium
148
Czech Republic
133
Germany
0
Estonia
0
Latvia
86
Lithuania
83
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Electricity consumption in gas
networks (terajoules)
Luxembourg
0
Hungary
0
Netherlands
0
Austria
518
Poland
1,109
Slovakia
166
Denmark
0
Ireland
0
Finland
0
Sweden
0
United Kingdom
0
Spain
0
France
0
Portugal
50
Table 3.51: Electricity consumption in pipeline transport in EU countries for
2012 (Source: Eurostat)
In addition, CE Delft provides calculated emissions for CNG and small scale LNG
processing and transport in its report “The Natural Gas Chain - Toward a global life
cycle assessment”. These emissions are presented in Table 3.52.
It is worth mentioning that in the baseline year of 2012 only CNG activity to transport
means might be traced and consequently will be assessed in terms of GHG emissions.
The use of LNG as transport fuel will only be considered as an option within the
projections of the PRIMES model and therefore will be assessed as part of Task f.
Average data for CNG and LNG GHG emissions
(electricity not included)
Processing (gr CO2eq/MJ)
Long distance (gr CO2eq/MJ)
CNG - High pressure network
0.17
5.41
CNG - Low pressure network
0.17
5.41
0.36 (transport 1,000 km
assumed)
LNG
3.9
10.95
TABLE 3.52: EMISSIONS DATA PROVIDED BY CE DELFT FOR CNG
AND SMALL SCALE LNGLITERATURE DATA
According to the data collection strategy, in the absence of actual data and when major
difficulties related to data collection do not allow for reliable modelling in OPGEE, the
Consultant would use literature data from work previously done in order to assess GHG
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emissions of certain MCONs. The collection of actual data and the data for the inputs
till present has made evident that there is sufficient information for the assessment of
GHG emission of the MCONs that fall within the scope of the analysis and therefore
there is no purpose for utilizing pre-calculated carbon intensities from previous studies.
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TASK C: GHG EMISSIONS MODELLING
The presentation of the work carried out in the context of Task c concentrates on the
main methodological aspects of the models prepared for the calculation of the WTT
GHG emissions of petroleum fuels (diesel, petrol and kerosene) and natural gas. Three
models, namely OPGEE, GHGenius and PRIMES-Refinery, have been employed for
the estimation of total GHG emissions of the aforementioned refined petroleum
products and natural gas from the stage of the extraction process to their production
and distribution to the fill tanks in every EU country. The models will largely depend on
the data collected, as presented in Task b. Due to the large uncertainty endorsed to the
reliability of certain areas of data, minimum and maximum values of the GHG
emissions associated with the WTT supply chain of diesel, petrol, kerosene and natural
gas will be provided. The WTT supply chain of the petroleum products and natural gas,
as has already been stated, is divided into three sections:



Upstream emissions are classified into three broad categories: emissions
during exploration and field development, emissions during production and
surface processing emissions. The OPGEE model is a spreadsheet tool which
covers the feedstock extraction emissions and provides calculations of
emissions relevant to the exploration and drilling, the production and surface
separations, the secondary and tertiary recovery, water treatment and waste
disposal and the venting, flaring and fugitive emissions. The OPGEE model has
the capability to also calculate GHG emissions from unconventional oil sources
such as oil sands. The GHGenius model includes a module for the estimation of
the emissions resulting from the natural gas life cycle chain (e.g. producing,
processing, transporting and transforming the gas for use). The GHGenius
model, for the purposes of the current study, has been expanded to simulate
the region of the European Union.
Midstream emissions pertain to emissions resulting from the feedstock
transportation from the extraction source to the refinery gate. Emissions mainly
occur due to the energy consumption during the transportation of petroleum and
its products. Emissions from oil transportation are derived using the OPGEE
model which has been updated with actual Origin-Destination Matrices data and
the methods used to transport oil to Europe from extra-EU regions. GHGenius
is able to calculate GHG emissions related to the transportation of natural gas
from the gas supplier to the gas consuming region. The model is able to
calculate both emissions related to the transportation of natural gas through
pipelines and through shipping (the case of LNG).
Downstream emissions refer to the emissions during the processing of crude
oil in the refineries. The resulting GHG emissions from the crude oil refining are
influenced by specific crude oil properties, the amount of processing required
and the energy input. Energy consumption in the refineries refers to both own
consumption and purchased fuels (mainly electricity and natural gas). To
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allocate the GHG emissions during refining to each petroleum product the
PRIMES-Refinery model will be used. The allocation of the emissions to
individual products will be based on the marginal emission content following the
methodology developed by the Institut Français du Pétrole (IFP). Furthermore,
the present analysis will take into account emissions from transportation of both
refinery feedstock and of ready-to-use fuels. The latter case applies mainly
where refined petroleum products are imported to EU from Russian or US
refineries. This study will also provide estimates on the GHG emissions which
take place during the transportation of the refined petroleum products from the
European refineries to the European filling stations, as well as the fugitive
emissions at the stage of the filling stations.
4.1
4.1.1
THE OPGEE MODEL
Model rationale and structure
The Oil Production Greenhouse gas Emissions Estimator (OPGEE) is an engineering
based life cycle assessment (LCA) spreadsheet tool that estimates greenhouse gas
(GHG) emissions from the production, processing, and transport of crude petroleum.
The system boundary of OPGEE extends from initial exploration to the refinery gate.
The development of the OPGEE model was funded by the California Air Resources
Board. The model has been incorporated into the California’s Low Carbon Fuel
Standard (LCFS) and has been applied for the calculation of the GHG intensity for
crude oil baseline analysis. For the purposes of the present study, the OPGEE model is
modified to account for the EU petroleum fuel supply system, by using specific input
data related to the various MCONs imported to the European refineries.
The OPGEE model provides a very detailed platform for the evaluation of carbon
intensity and energy consumption at the upstream and midstream stages. OPGEE
includes emissions from all production operations required to produce and transport
crude hydrocarbons to the refinery gate. The production technologies included are the:
primary production, secondary production (water flooding), and major tertiary recovery
technologies (also called enhanced oil recovery or EOR). In addition, bitumen mining
and upgrading is included in a simplified fashion. The OPGEE model makes all the
calculations and correlations of the values utilizing various standard data about fuels
specifications, emissions factors and other conversion factors. A schematic chart
showing the various stages of the lifecycle assessment included in the OPGEE model
are presented in Figure 4.1 below:
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Figure 4.1: Schematic chart with the various stages of the LCA analysis included
in the OPGEE model (Source: OPGEE model documentation)
Type of processes included in OPGEE
OPGEE is modular in structure, with interlinked worksheets representing each
production stage. Within each major production stage, a number of activities and
processes occur (e.g., fluid production or fluid injection). The functional unit of OPGEE
is 1 MJ of crude petroleum delivered to the refinery entrance (a well-to-refinery, or
WTR process boundary). This functional unit is held constant across different
production and processing pathways included in OPGEE. OPGEE uses data from a
variety of technical reference works and its spreadsheet structure makes it a fully
transparent modelling tool. The main calculations for the total carbon intensity
estimation focus on the following processes:








Exploration, which contains pre-production emissions that occur during primary
exploration for petroleum.
Drilling and development, including emissions that occur during development
of crude oil production facilities.
Production and extraction, which models the work required to lift fluids from
the subsurface and to inject fluids into the subsurface.
Surface processing, which models handling of crude, water, and associated
gas with a set of common industry technologies.
Maintenance, regarding the venting and fugitive emissions associated with
maintenance.
Waste disposal, referring to the emissions about waste disposal.
Crude transport, allowing variation in the transport modes used to transport
crude oil from extraction to the refinery stage and the distance travelled.
Bitumen extraction and upgrading, modelling the extraction of crude bitumen
separately from the production of conventional crude oil.
All the processes of the upstream stage contribute to the total carbon intensity of each
MCON with its own percentage of GHG emissions.
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Flaring, venting and fugitive emissions represent the most important source of GHG
emissions from oil production operations. Venting and fugitive emissions arise from oil
field operations and devices. Sources include well work-overs and clean-ups,
compressor start-ups and blowdowns, pipeline maintenance, gas dehydrators, AGR
units, well cellars, separators (wash tanks, free knock outs, etc.), sumps and pits, and
components (valves, connectors, pump seals, flanges, etc.). Flaring of gas, either as a
means of disposal or as a safety measure, is a significant source of air emissions from
oil and gas installations. Even if continuous flaring ended, occasional burning of small
amounts of gas will still be necessary for safety reasons.
Another major factor is the use of the energy-intensive secondary and tertiary recovery
technologies, such as water flooding, gas lifting, gas flooding etc. For the application of
these technologies, additional energy is required in order to lift the crude oil from oil
well. Other emissions take place due to increased pumping and separation work
associated with increased fluid handling in depleted oil fields (i.e., fields with a high
water-oil ratio). At the midstream level, GHG emissions due to transportation can have
a significant share in the total GHG emissions assessed, especially when considering
crudes imported from distant world areas to the EU refineries.
4.1.2
Required Inputs
Key input data
In order to calculate the carbon intensity of the imported MCONs in European
refineries, a significant amount of data is needed to make the OPGEE model
functional. The data required relate to:





Production methods, such as downhole pump, water reinjection, gas
reinjection, water flooding, gas lifting, gas flooding, and steam flooding. The
selection of the production method depends on the difficulty that crude oil
appears in pumping up of the oil well.
Field properties referring to the field location, field name, field age, field depth,
oil production volume, number of producing wells, well diameter, productivity
index and average reservoir pressure. These field properties are determining
characteristics for the production process of the oilfield.
Fluid properties considering API gravity of crude oil, which characterize the
crude oil as “heavy” or “light” and composition of produced associated gas.
Production practices including gas-to-oil ratio (GOR), water-to-oil ratio (WOR),
water-injection ratio, gas lifting injection ratio, gas flooding injection ratio, steamto-oil ratio (SOR), fraction of required electricity generated on site, fraction of
remaining gas reinjected, fraction of water produced reinjected, fraction of
steam generation via co-generation and volume fraction of diluent. The
information about the production practices correlate with these of the production
methods and have significant role in the resulting emissions.
Processing practices that represent the use of heater/treaters, stabilizer
columns and gas processing units (AGR, dehydrator and demethanizer), the
ratio of gas flared to oil produced, and the ratio of gas vented to oil produced.
According to the quality of produced oil mixture, certain treating processes are
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applied for further treatment of gas, oil and water, which include in the oil
mixture.
Land use impacts including ecosystem carbon richness and relative
disturbance intensity. This parameter relates to the additional emissions of the
wider oilfield that are caused due to the disturbance of land during the drilling
and production processes.
Crude oil transport which determine transport modes and distances. Crude oil
transport covers the tracks (marine or by road) from the oil well to the European
refineries gates presenting the distances as well as the suitable mode that is
utilized for each distance.
The user is allowed to insert the desired data in the “User Inputs” section of the ‘User
Inputs & Results’ worksheet. This sheet enables the calculation of the carbon intensity
of one specific MCON. However, OPGEE has a built-in capability to analyse a number
of fields or oil production projects and bookkeep the results for comparison and further
analysis. The ‘Bulk Assessment’ worksheet has a similar structure to the ‘User Inputs &
Results’ worksheet, but is expanded to allow multiple projects to be assessed in one
computational run. In addition to running a number of fields in sequence, the bulk
assessment machinery has a built-in feature to programmatically resolve errors that
arise from input data inconsistencies.
All required inputs to OPGEE are assigned default values that can be kept as is or
changed to match the characteristics of a given oil field or marketable crude oil blend. If
only a limited amount of information is available for a given facility, most input values
will remain equal to defaults. Otherwise, if detailed field-level data are available, a more
accurate emissions estimate can be generated.
Table 4.1 presents the actual form of the input data required to operate the OPGEE
model and produce the lifecycle GHG emissions per field type. The table presented
includes the input data of the generic field type included in the OPGEE model.
4.1.3
Parametric significance
The Consultant has performed a sensitivity analysis over the most critical parameters
that can influence the outcome of the carbon intensity of the various crude types. The
scope of this analysis is to show the importance of specific oil field characteristics for
the calculations of the GHG emissions. A sensitivity analysis has been performed over
specific parameters while keeping all other inputs unchanged; the calculations refer to
the generic type of field considered in OPGEE (for the typical characteristics of the
generic type of field see Table 4.1). The main parameters included in the sensitivity
runs are the following:





API gravity
Water to oil ratio (WOR)
Flaring to oil ratio (FOR)
Venting to oil ratio (VOR)
Marine transport distance
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Unit
Value
Downhole pump
1
Water reinjection
1
Gas reinjection
1
Water flooding
0
Gas lifting
0
Gas flooding
0
Steam flooding
0
Field location (Country)
Generic
Field name
Generic
Field age
yr.
35
Field depth
ft
7,240
bbl/d
1,500
Number of producing wells
[-]
8
Number of water injecting wells
[-]
5
Well diameter
in
2.775
bbl/psi-d
3
psi
1,557
deg. API
30
N2
mol%
2
CO2
mol%
6
C1
mol%
84
C2
mol%
4
C3
mol%
2
C4+
mol%
1
H2S
mol%
1
scf/bbl oil
908
Water-to-oil ratio (WOR)
bbl water/bbl oil
4.31
Water injection ratio
bbl water/bbl oil
5.31
scf/bbl liquid
1,500
scf/bbl oil
1,362
bbl steam/bbl oil
3
Fraction of required electricity generated onsite
[-]
0
Fraction of remaining gas reinjected
[-]
0
Fraction of water produced water reinjected
[-]
1
Fraction of steam generation via cogeneration
[-]
0
Heater/treater
NA
0
Stabilizer column
NA
1
Application of AGR unit
NA
1
Application of gas dehydration unit
NA
1
Application of demethanizer unit
NA
1
scf/bbl oil
182
Oil production volume
Productivity index
Reservoir pressure
API gravity
Gas composition
Gas-to-oil ratio (GOR)
Gas lifting injection ratio
Gas flooding injection ratio
Steam-to-oil ratio (SOR)
Flaring-to-oil ratio
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Unit
Value
scf/bbl oil
0
[-]
0
Ocean tanker
Mile
5,082
Rail
Mile
800
Ocean tanker size, if applicable
Ton
250,000
gCO2eq/MJ
0.5
Venting-to-oil ratio
Volume fraction of diluent
Transport distance (one way)
Small sources emissions
Table 4.1: Typical input to the OPGEE model for the calculation of the GHG
emissions per field (values for the generic type of field included in
OPGEE
Sensitivity analysis on the API gravity
API gravity is a measure of how “heavy” or “light’ the crude oil is relative to water. The
generic field considered has an API equal to 30. The resulting carbon intensity of this
field is equal to 7.93 gr CO2eq/MJ according to the OPGEE results shown in Figure 4.2.
Three sensitivity runs have been performed for the API values while keeping all other
input unchanged relative to the generic field. The values picked for the API sensitivity
analysis are within the range found in literature; the range of API provided in Task b for
the various fields range from 22 to 44. In the 1st sensitivity, an API of 20 has been
considered which eventually results in a carbon intensity of 7.43 gr CO2eq/MJ and
represents a reduction of about 6% relative to the generic field (see Figure 4.2). In the
2nd sensitivity run, an API of 40 has been assumed resulting to a carbon intensity of
8.15 gr CO2eq/MJ which represents an increase of about 3% relative to the generic
field. In the 3rd sensitivity test, an API of 35 was assumed resulting to a carbon intensity
of 8.04 gr CO2eq/MJ which represents an increase of about 1% relative to the generic
field.
According to the model runs, it has been observed that an increase in the API gravity
(lighter crude oil), results in an increase of the total carbon intensity. This happens
because in the sensitivity runs the OPGEE model calculates the emissions without
changing any other parameter. However, in reality, oil fields with lower API gravity
usually involve different production methods and processes which will eventually
results in overall higher carbon intensity than lighter oil.
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10.00
API 30
API 40
API 35
API 20
GHG emissions [gCO2eq/MJ]
8.00
6.00
4.00
2.00
0.00
-2.00
GENERIC
-0.61
Sensitivity 1
-0.58
Sensitivity 2
-0.64
Sensitivity 3
-0.62
Transport
0.94
0.96
0.93
0.93
Misc.
0.50
0.50
0.50
0.50
Diluent
0.00
0.00
0.00
0.00
VFF
4.08
3.60
4.27
4.17
Waste
0.00
0.00
0.00
0.00
Maintenance
0.00
0.00
0.00
0.00
Upgrading
0.00
0.00
0.00
0.00
Processing
0.77
0.73
0.80
0.79
Production
0.92
0.89
0.95
0.93
Drilling
1.33
1.34
1.34
1.33
Exploration
0.00
0.00
0.00
0.00
Net lifecycle emissions
7.93
7.43
8.15
8.04
Offsite emissions
Figure 4.2: Sensitivity analysis on the API gravity: results obtained using the
OPGEE model
Sensitivity analysis on the Water to Oil Ratio (WOR)
Water-oil-ratio (WOR) is the ratio between the volume of water that comes out of the
crude oil mixture and the volume of oil at standard conditions. The generic field
considered has a WOR equal to 4.31 bbl water/bbl oil. The resulting carbon intensity of
this field is equal to 7.93 gr CO2eq/MJ according to the OPGEE results shown in Figure
4.3. Two sensitivity runs were performed on the WOR values. The values picked for the
WOR sensitivity analysis are within the range found in literature; the range of WOR
provided in Task b for the various fields range from 0,6 to 8,3 bbl water/bbl oil. In the 1st
sensitivity, a WOR of 1 bbl water/bbl oil and eventually results in a carbon intensity of
7.22 gr CO2eq/MJ which represents a reduction of about 9% (see Figure 4.3). In the 2nd
sensitivity test performed, a WOR of 8 bbl water/bbl oil was assumed resulting to a
carbon intensity of 8.84 gr CO2eq/MJ which represents an increase of about 11%
relative to the generic field. Increasing the WOR implies that additional operations are
required during the production process which results in an increase in the GHG
emissions during the production phase and eventually the overall GHG emissions.
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10.00
WOR: 8
WOR: 4.31
WOR: 1
8.00
GHG emissions [gCO2eq/MJ]
Interim Report
6.00
4.00
2.00
0.00
-2.00
Offsite emissions
Transport
Misc.
Diluent
VFF
Waste
Maintenance
Upgrading
Processing
Production
Drilling
Exploration
Net lifecycle emissions
GENERIC
-0.61
0.94
0.50
0.00
4.08
0.00
0.00
0.00
0.77
0.92
1.33
0.00
7.93
Sensitivity 1
-0.71
0.94
0.50
0.00
4.08
0.00
0.00
0.00
0.77
0.31
1.33
0.00
7.22
Sensitivity 2
-0.48
0.94
0.50
0.00
4.08
0.00
0.00
0.00
0.77
1.70
1.33
0.00
8.84
Figure 4.3: Sensitivity analysis on the Water to Oil Ratio (WOR): results obtained
using the OPGEE model
Sensitivity analysis on the Flaring to Oil Ratio (FOR)
Flaring is used to dispose of associated natural gas where there is no economic use for
the gas. Associated gas evolves from crude oil as it is brought to surface temperatures
and pressures, and is separated from oil before transport. Flaring mainly produces
carbon dioxide and water as waste products of combustion; however, combustion is
often incomplete which can result in emissions of carbon monoxide, nitrous oxide,
unburned hydrocarbons, particulate matter (including soot or black carbon), and VOCs.
Because of the hydrocarbon content, a flaring rise results to a significant increase in
the carbon intensity.
The generic field considered has a flaring to oil ratio equal to 182 scf/bbl oil. Three
sensitivity runs were performed on the flaring to oil ratio values because the range of
values found in literature varies between some hundreds of scf and thousands of scf. In
the 1st sensitivity, a flaring to oil ratio of 50 scf/bbl oil was considered which results in a
carbon intensity of 6.17 gr CO2eq/MJ, a reduction of about 22% relative to the generic
field. In the 2nd sensitivity, a flaring to oil ratio of 500 scf/bbl oil was assumed resulting
to a carbon intensity of 12.19 gr CO2eq/MJ which represents an increase of about 54%
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relative to the generic field (see Figure 4.4). In the 3rd sensitivity test performed a flaring
to oil ratio of 1000 scf/bbl was performed resulting to a carbon intensity of 18.97 gr
CO2eq/MJ which represents an increase of about 139% relative to the generic field. It is
evident from the modelling runs that the flaring to oil ratio is a critical parameter for the
calculation of the total GHG emissions per MCON.
20.00
FOR 1000
15.00
GHG emissions [gCO2eq/MJ]
FOR 500
10.00
FOR 182
FOR 50
5.00
0.00
-5.00
Offsite emissions
Transport
Misc.
Diluent
VFF
Waste
Maintenance
Upgrading
Processing
Production
Drilling
Exploration
Net lifecycle emissions
GENERIC
-0.61
0.94
0.50
0.00
4.08
0.00
0.00
0.00
0.77
0.92
1.33
0.00
7.93
Sensitivity 1
-0.76
0.94
0.50
0.00
2.41
0.00
0.00
0.00
0.83
0.92
1.33
0.00
6.17
Sensitivity 2
-0.23
0.94
0.50
0.00
8.11
0.00
0.00
0.00
0.62
0.92
1.33
0.00
12.19
Sensitivity 3
0.28
0.94
0.50
0.00
14.54
0.00
0.00
0.00
0.46
0.92
1.33
0.00
18.97
Figure 4.4: Sensitivity analysis on the Flaring to Oil Ratio (FOR): results obtained
using the OPGEE model
Sensitivity analysis on the Venting to Oil Ratio (VOR)
Venting is the controlled release of gases into the atmosphere in the course of oil and
gas production operations. These gases might be natural gas or other hydrocarbon
vapours, water vapour, and other gases, such as carbon dioxide, separated in the
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processing of oil or natural gas. In venting, methane is released directly into the
atmosphere.
The generic field considered has venting to oil ratio equal to 0 scf/bbl oil. Two
sensitivity runs were performed on the venting-to-oil ratio values while keeping all other
input unchanged relative to the generic field. In the 1st sensitivity, a venting to oil ratio
of 5 scf/bbl oil was considered which eventually results in a carbon intensity of 8.30 gr
CO2eq/MJ which represents an increase of about 5% (see Figure 4.5). In the 2nd
sensitivity run, a venting to oil ratio was assumed of 15 scf/bbl oil resulting to a carbon
intensity of 9.02 gr CO2eq/MJ, which represents an increase of about 14% relative to
the generic field. Figure 4.5 illustrates the results obtained from OPGEE.
12.00
VOR 15
10.00
VOR 0
VOR 5
GHG emissions [gCO2eq/MJ]
8.00
6.00
4.00
2.00
0.00
-2.00
Offsite emissions
Transport
Misc.
Diluent
VFF
Waste
Maintenance
Upgrading
Processing
Production
Drilling
Exploration
Net lifecycle emissions
GENERIC
-0.61
0.94
0.50
0.00
4.08
0.00
0.00
0.00
0.77
0.92
1.33
0.00
7.93
Sensitivity 1
-0.60
0.94
0.50
0.00
4.44
0.00
0.00
0.00
0.77
0.92
1.33
0.00
8.30
Sensitivity 2
-0.59
0.94
0.50
0.00
5.15
0.00
0.00
0.00
0.76
0.92
1.33
0.00
9.02
Figure 4.5: Sensitivity analysis on the Venting to Oil Ratio (VOR): results
obtained using the OPGEE model
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Sensitivity analysis on the maritime shipping distance
The transportation of crude oil from the extraction point to the refinery of a European
country is responsible for a part of the total lifecycle GHG emissions of this specific
crude. GHG emissions occur due to the consumption of fossil-based fuels during the
transportation usually by ocean tankers. An important variable for determining the GHG
emissions due to transportation by ships is the actual Origin - Destination (O-D)
distance. For the purposes of this sensitivity analysis, we have assumed different O-D
distances for the generic field considered in OPGEE, while keeping all other variables
unchanged.
The generic field considered has an O-D distance of 5082 km (ocean tanker). The
resulting carbon intensity of this field is equal to 7.93 gr CO2eq/MJ according to the
OPGEE results shown in Figure 4.6. Two differentiated O-D distances have been
considered for two sensitivity runs. The assumptions draw largely from data provided in
Task b and refer to the distances from two major exporting countries to EU ports. For
the 1st sensitivity run, the shipping distance was 699 miles from Samotlor to Gdansk.
After running the OPGEE model, the resulting carbon intensity was found to be 7.43 gr
CO2eq/MJ, which represents a decrease of about 7% relative to the generic field (see
Figure 4.6). In the 2nd sensitivity run, a distance of 7,456 miles from Ghawar to
Rotterdam was considered. The overall carbon intensity of the crude considered
increased to the levels of 8.22 gr CO2eq/MJ which represents an increase of about 3%
relative to the generic field. Indeed, the shipping distance does not represent an
important variable for the calculation of the GHG emissions using the OPGEE model.
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10.00
Ocean tank. 5082
Ocean tank. 7456
Ocean tank. 699
GHG emissions [gCO2eq/MJ]
8.00
6.00
4.00
2.00
0.00
-2.00
Offsite emissions
Transport
Misc.
Diluent
VFF
Waste
Maintenance
Upgrading
Processing
Production
Drilling
Exploration
Net lifecycle emissions
GENERIC
-0.61
0.94
0.50
0.00
4.08
0.00
0.00
0.00
0.77
0.92
1.33
0.00
7.93
Sensitivity 1
-0.60
0.43
0.50
0.00
4.08
0.00
0.00
0.00
0.77
0.92
1.33
0.00
7.43
Sensitivity 2
-0.60
1.22
0.50
0.00
4.08
0.00
0.00
0.00
0.77
0.92
1.33
0.00
8.22
Figure 4.6: Sensitivity analysis on the marine shipping Origin- destination (O-D)
distance: results obtained using the OPGEE model
4.1.4
Produced outputs
Table 4.2 illustrates a typical presentation of the OPGEE model outputs. As it can be
observed these are organized per lifecycle process and for each process the total
energy consumption and total GHG emission are given.
Output variables
Level 1
Level 2
Unit
Field name
Values
Generic
2.1 Exploration (e)
2.1.1 Total energy
consumption
2.1.2 Total GHG
emissions
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0
gCO2eq/MJ
0
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Output variables
Level 1
Interim Report
Level 2
Unit
Values
2.1.2.1
Combustion/land use
gCO2eq/MJ
0
2.1.2.2 VFF
gCO2eq/MJ
0
MJ/MJ
0.001
gCO2eq/MJ
1.33
2.2.2.1
Combustion/land use
gCO2eq/MJ
1.33
2.2.2.2 VFF
gCO2eq/MJ
0
MJ/MJ
0.012
gCO2eq/MJ
0.94
2.3.2.1
Combustion/land use
gCO2eq/MJ
0.92
2.3.2.2 VFF
gCO2eq/MJ
0.02
MJ/MJ
0.046
gCO2eq/MJ
4.74
2.4.2.1
Combustion/land use
gCO2eq/MJ
0.77
2.4.2.2 VFF
gCO2eq/MJ
3.97
MJ/MJ
0
gCO2eq/MJ
0.09
2.5.2.1
Combustion/land use
gCO2eq/MJ
0
2.5.2.2 VFF
gCO2eq/MJ
0.09
2.2 Drilling &
Development (d)
2.2.1 Total energy
consumption
2.2.2 Total GHG
emissions
2.3 Crude
production &
extraction (p)
2.3.1 Total energy
consumption
2.3.2 Total GHG
emissions
2.4 Surface
processing (s)
2.4.1 Total energy
consumption
2.4.2 Total GHG
emissions
2.5 Maintenance
(m)
2.5.1 Total energy
consumption
2.5.2 Total GHG
emissions
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Output variables
Level 1
Interim Report
Level 2
Unit
Values
MJ/MJ
0
gCO2eq/MJ
0
2.6.2.1
Combustion\land use
gCO2eq/MJ
0
2.6.2.2 VFF
gCO2eq/MJ
0
MJ/MJ
0
gCO2eq/MJ
0
MJ/MJ
0
gCO2eq/MJ
0
MJ/MJ
0.013
2.9.2 Total GHG
emissions
gCO2eq/MJ
0.94
2.9.3 Loss factor
NA
1
2.10 Other small
sources
gCO2eq/MJ
0.5
2.11 Offsite
emissions
credit/debit
gCO2eq/MJ
-0.61
MJ/MJ
0.071
gCO2eq/MJ
7.93
2.6 Waste disposal
(w)
2.6.1 Total energy
consumption
2.6.2 Total GHG
emissions
2.7 Diluent
2.7.1 Total energy
consumption
2.7.2 Total GHG
emissions
2.8 Non-integrated
upgrader
2.8.1 Total energy
consumption
2.8.2 Total GHG
emissions
2.9 Crude
transport (t)
2.9.1 Total energy
consumption
2.12 Lifecycle
energy
consumption
2.13 Lifecycle GHG
emissions
Table 4.2: Typical output of the OPGEE model
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4.1.5
Interim Report
Draft results
Based on the data gathered so far in Task b, it was possible to calculate the GHG
emissions of five major MCONs imported to the European refineries using the OPGEE
model. Figure 4.7 presents the draft results for Arab light, the Bonny light, the Siberia
light, the Urals and the Troll MCONs obtained with OPGEE. It has to be noted that
these are initial runs and that final results will take into account various pathways and
will presented in the form of a range with a minimum and a maximum.
The first MCON considered is the “Arab light” which is imported from Saudi Arabia. The
resulting GHG emissions of this specific MCON was found to be about 4.82 gr
CO2eq/MJ. The second one is the “Bonny light” MCON from Nigeria. The Nigerian
MCON has a carbon intensity of 12.59 gr CO2eq/MJ, which is significantly higher than
the Arab light. This increase is due to the much higher GHG emissions related with
VFF that are related with the Nigerian MCON. Further, the carbon intensity of the
“Siberian light”, imported from Russia, is calculated to be about 10.13 gr CO2eq/MJ.
Similarly, we observe that this Russian MCON shows a high carbon intensity
originating from the VFF process, even though the GHG emissions during the
processing stage are almost negligible. The picture is very similar regarding the “Urals”
MCON, also originating from Russia but from different oilfield, with a calculated carbon
intensity of 11.02 gr CO2eq/MJ. VFF related GHG emissions are also responsible for
more than half the overall carbon intensity of this particular MCON. The “Troll” MCON
which comes from Norway has significantly lower VFF emissions in comparison with
the Russian and the Nigerian MCONs, resulting in a carbon intensity of 7.09 gr
CO2eq/MJ. According to the OPGEE model, the transport related GHG emissions of
the “Troll” MCON are found to be significantly lower than the other four MCONs as the
transportation distance is relatively small. It is evident that the most significant
differences among the five MCONs considered are due to the VFF emissions.
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GHG emissions [gCO2eq/MJ]
14.00
12.00
10.00
8.00
6.00
4.00
2.00
0.00
-2.00
Offsite emissions
Transport
Misc.
Diluent
VFF
Waste
Maintenance
Upgrading
Processing
Production
Drilling
Exploration
Net lifecycle emissions
Arab
light
-0.44
0.73
0.50
0.0
1.96
0.00
0.00
0.00
0.20
0.54
1.33
0.00
4.82
Bonny
light
-0.17
0.63
0.50
0.0
8.79
0.00
0.00
0.00
0.59
0.92
1.33
0.00
12.59
Siberia
light
0.24
0.78
0.50
0.0
6.24
0.00
0.00
0.00
0.02
1.04
1.31
0.00
10.13
Urals
Troll
0.36
1.00
0.50
0.0
6.17
0.00
0.00
0.00
0.02
1.67
1.31
0.00
11.02
-0.58
0.30
0.50
0.0
1.82
0.00
0.00
0.00
0.88
2.89
1.29
0.00
7.09
Figure 4.7: Draft results on GHG emissions of five MCONs using the OPGEE
model (input data from Task b)
4.2
THE PRIMES-REFINERY MODEL
The present study takes into consideration the GHG emissions during the refining
stage of the crude oil in the European countries and the emissions associated to
imported final mineral oil fuels. The GHG emissions that take place during the refining
process are not included in the lifecycle analysis provided by the OPGEE model.
Therefore, for the purposes of the present study we use the PRIMES-Refinery model
for the estimation of GHG emissions resulting from the processing of petroleum in the
refineries of Europe. The current section presents an overview of the main features of
the PRIMES-Refinery model and a brief presentation of the main refining processes
considered, as well as the ongoing extensions and upgrades of the model required for
the purposes of the current study and some key required input data.
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Model rationale and structure
Coverage of the model
The PRIMES-Refinery supply model is an economic supply modelling tool developed
and maintained by E3MLab. The model takes demand for petroleum products as given,
either from statistics of past years or from projection to the future by the other submodels (demand models and power sector models) of PRIMES. The refinery submodel optimises economically the structure of stylised refineries, the use of processes,
the consumption of crude oil, feedstock and fossil fuels as needed to produce given
demand. The model endogenously estimates investment in processing and refining
capacity of needed to meet future demand. The model runs also for past years for data
calibration purposes and so it produces detailed (pseudo) data on the past in order to
estimate consumption of energy and emissions in detail. The refinery sub-model is
linked with the PRIMES large scale energy system model and can be used either as a
satellite model, thus forming a closed loop, or as a standalone model. The model is
designed to perform sensitivity analyses based on different demand estimations, crude
oil types and import-exports of refinery products, and includes representations to
handle legislative and policy regulations on the refinery processes.
The model covers all EU-28 Member States. It provides dynamic projections in 5-year
time periods with the time horizon of the model being 2050. Years 2000, 2005 and
2010 are reproduced by the model for calibration purposes a nd so the model is
updated until 2010. Alongside with the calculation of GHG emissions at the refinery
stage, the model seeks to minimise total cost so as to satisfy a fixed demand for
petroleum fuels, which is derived from the PRIMES core model. It therefore determines
the optimal use of resources and calculates the investment in technologies, the costs,
and the pre-tax prices of final refinery fuels. The total petroleum commodity supply
system cost includes annuity payments of capital cost, variable and energy costs, fixed
O&M costs, as well as the cost of imports. The cost optimization is performed for all EU
Member States in parallel and is inter-temporal thus having perfect foresight.
Model structure
In a nutshell, the refinery supply system is structured in the model as follows: the
primary energy commodity (i.e. crude oil and other feedstock) is transformed into final
commodities in a stepwise manner, via a variety of transformation processing
units/technologies included in the model. The final commodities are then distributed to
the fuel market of the EU Member States (final energy consumption) and to the EU
power or heat production plants. The schematic representation of the representative
refinery configuration is presented in Figure 4.8.
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Figure 4.8: Schematic representation of the main processes included in the
representative refinery structure of the PRIMES-Refinery model
The demand for petroleum products is met through domestic production in the EU
refineries and through trade (imports-exports), the latter determined endogenously in
the model based on relative prices and depending on elasticity parameters. Trading in
the model includes both final refinery fuels and refinery feedstock, which is
consequently used in the EU refineries, and is performed internally in the EU and
internationally. EU countries and extra EU locations are connected through a
transportation matrix that describes distances and transportation mean options. The
international trade mainly simulates trade between the EU, the Middle East region, the
North America region and a few other regions aggregated. The relation of imported
quantities to the respective import prices is described via non-linear cost-supply curves,
thus different market behaviours regarding import patterns can be simulated. The
minimization problem is subject to constraints associated with limitations of the
feedstock supply, as well as blending requirements on the crude oil and intermediate
streams, product specifications and capacities.
The refinery feedstock in the model is divided into 2 main categories: crude oil and
other feedstock. The feedstock supply is described by country specific cost-supply
curves. Feedstock produced internally in the EU is subject to resource limitations.
Given the large diversity of the various crude types imported at the European
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refineries, it was decided to improve the modelling and the resolution of the PRIMESRefinery model regarding the crude types imported. E3MLab is currently in the process
of upgrading the model to simulate three different crude oil types instead of the one
category previously implemented. The ongoing extensions of the model towards this
direction will be presented in more detail further in the current section.
The model includes a variety of refinery generic processing unit types used to separate
the distillates from the crude feedstock and convert the intermediate products into
lighter valuable products. Technology heat-rates (energy conversion factors) are
assumed to improve over time following technology developments. Additional
modelling work is also currently under way to include more refining processes in the
PRIMES-Refinery model. This extension is essential to account for the various actual
refining processes included in the European refineries; the main configuration types
have been derived from the refining survey of Oil and Gas Journal. The main refining
processes to be included in the model are presented further in the current section.
The model computes endogenously the investment in technologies and the respecting
processing capacities, derived as a result of investment accumulation. Available
capacity is a constraint to the petroleum commodities production. Technology vintages,
that define the time a processing capacity was installed, are used for the specification
of the technical characteristics of the processing units, as well as the decommissioning
of capacities. To determine the prices of the final petroleum products, the PRIMESRefinery model includes a pricing module. To this scope, the model formulates a
Ramsey-Boiteux pricing rule which consist of two parts, namely a marginal cost pricing
part and an average cost pricing one the latter being used to recover all fixed and
capital costs.
Allocation of GHG emissions per refined petroleum product
The key objective of using a model based analysis for simulating the European
refineries is to allocate the refinery GHG emissions to the following refined petroleum
products: petrol, diesel and kerosene (all refinery outputs are included in the model).
The allocation of the GHG emissions to the abovementioned petroleum products will be
based on marginal emission coefficients for each refinery product. The refined fuelspecific emission factors will be calculated by allocating total refinery emissions based
on the marginal emission content methodology (as developed by the Institut Francais
du Pétrole).
The marginal emission coefficients for each refinery product are derived by the
measuring of the variation of emissions after the marginal change of the demand for a
specific fuel. Marginal content refers to the additional emissions generated from one
additional unit of production of the specific product, which depends on refinery
configuration that varies in the EU countries. The resulting coefficients are
consequently applied to the average GHG emissions to receive an individual fuelspecific emission factor.
E3MLab will also provide estimates on the lifecycle GHG emissions of the major
refined products imported to EU, apart from the calculations of the GHG emissions
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resulting from petroleum products refined in European refineries. The evaluation of the
GHG emissions from the imported oil products, mainly from Russia and US, will be
based on the methodology followed for the calculation of emissions generated in
European refineries. To account for the GHG emissions of these imported fuels during
their refining process in Russia and US, E3MLab will derive proxy values for their
respective GHG emissions from other European countries with similar refinery
configuration. According to the study of Jacobs Consultancy, the US refined products
are derived from high conversion refineries, similar to European ones, while a
hydroskimming configuration (with no gas oil and residue conversion capacity) is
representative of Russian refineries that export finished products to Europe.
Ongoing extensions of the PRIMES-Refinery model related to crude oil types
For the purposes of the present study, E3MLab is currently performing modelling
upgrades to allow for a more enhanced simulation of the refineries configuration in the
EU. Drawing largely from data retrieved in Task b a number of different MCONs have
been identified that enter the refinery gates of the various European refineries. The key
characteristics of the various MCONs entering the EU refineries are related to the API
gravity and the sulphur content.
To account for the large diversity of the various MCONs used in the EU refineries,
E3MLab is currently extending the PRIMES-Refinery model to include three different
categories of crude types entering the representative refinery configuration. The
classification of the different crude types is based on the API gravity and sulphur, as
can be seen in Table 4.3. The differentiation of the crude types allows the different
handling and simulation of the respective processes, product yields and energy
consumption by the properties of crude oil.
Representative crude
oil types in PRIMESRefinery
Type 1 - Light
Type 2 - Medium
Type 3 - Heavy
Classification
by API gravity
Average
API
gravity
Classification by
sulphur content
(wt%)
>35
40.7
<0.8
Average
Sulphur
content
(wt%)
0.51
28-35
32.9
0.8-2
1.27
<28
22.3
>2
2.47
Table 4.3: Representative crude oil types considered in the PRIMES-Refinery
model: classification by API gravity and sulphur content
Heavier or lower quality crude oils (with lower API gravity) require energy intensive
processing to upgrade the higher volume of the ‘bottom of the barrel’. They go through
expanded carbon rejection and hydrogen addition processing, thus the energy required
for that additional processing increases the energy consumption of the refinery.
Vacuum distillation, catalytic cracking (including fluid catalytic cracking and
hydrocracking) and thermal cracking are the main processing units that are influenced
by the API gravity of the crude oil. Processing of crudes with high sulphur content
increases energy consumption as hydro-treating and desulphurization processes
require additional hydrogen consumption and, as a consequence, additional energy
use by the hydrogen production plant.
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In the modelling, the level of processing and the blending constraints for the input and
output of the various processes are differentiated by each type of crude. The three
types of crude oil have different volume distribution between the fractions derived from
the atmospheric distillation (i.e. naphtha, middle distillates and residue), different
processing capacities and product yields. The calibration of the model will be updated
in order to suite the scope of the study and determine the production level for each type
of crude oil.
Ongoing extensions of the PRIMES-Refinery model related to the refining
processes
This section presents the main refining processes that will be eventually considered in
the PRIMES-Refinery model. Partitioning of the refinery’s processes on a country basis
largely draws on the refining survey of Oil and Gas Journal. The modelling approach is
based on the fact that different products go through different processes within the
refinery, thus production flows are used to simulate the various streams leading to the
products of interest (petrol, diesel and kerosene). The typical refining processes
included in the PRIMES-Refinery model are presented in Table 4.4.
Refining Process
Short description
Atmospheric Distillation
First separation of crude into a series of boiling
point fractions
Vacuum Distillation
Separation of the bottom of the atmospheric
distillation under reduced pressure (vacuum)
Thermal Cracking (Visbreaking / Coking)
Thermal conversion of high-molecular weight
hydrocarbons into lighter products
Fluid Catalytic Cracking
Catalytic Conversion of high-molecular weight
hydrocarbons into lighter more valuable
products
Hydrocracking
Catalytic cracking of hydrocarbons under high
pressure in the presence of hydrogen
Catalytic Reforming
Low octane straight run naphtha is converted
into a high octane liquid reformate /Hydrogen
production
Isomerization/Alkylation
Conversion of low-octane n-paraffins to highoctane iso-paraffins and conversion of olefins to
highly branched iso-paraffins
Hydrotreating
Removal of contaminants (sulphur, nitrogen,
metals etc.) of the intermediate products through
their contact with hydrogen, aromatics saturation
Table 4.4: Main refining processes used in the PRIMES-Refinery model
The refining flow through the different processes is described as follows: the crude oil
feed (including the crude and the other feedstock components) is initially separated into
various fractions according to its boiling points in the atmospheric distillation unit. Light
fractions including gas to C5 molecules of hydrocarbons and light and heavy naphtha
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are used to produce LPG and gasoline blending components. Catalytic reforming
converts low octane straight run heavy naphtha into a high octane reformate. Middle
distillates including kerosene and light gas oil are processed to produce refined
products (kerosene and diesel).
Heavy fractions (atmospheric distillation residue) are further distilled under vacuum to
obtain vacuum gas oil (feed to fluid catalytic cracking or hydrocracking) and vacuum
residue. The Fluid Catalytic Cracking unit converts high-molecular weight hydrocarbons
into lighter products (light ends, naphtha, light cycle oil). Fluid catalytic cracking is
combined with an alkylation unit to convert light olefins into highly branched
isoparaffins (alkylates). Hydrocracking, similar to catalytic cracking, converts the heavy
fraction of vacuum gas oil into lighter saturated products under high hydrogen
pressure. Hydrocracking is considered to operate in competition with Fluid Catalytic
Cracking as both units convert vacuum gas oil. The vacuum residue is fed to a thermal
cracking unit; visbreaking is the most common process for the reduction of viscosity of
the residue and the production of lighter products. A part of vacuum residue may be
processed by coking in order to achieve higher conversion of heavy hydrocarbon
molecules and obtain petroleum coke as a final product. Hydrocracking and coking are
going to be selectively included in refining operations of EU countries that use these
units according to the data provided by the survey of Oil and Gas Journal.
Petrol and diesel are anticipated to be produced in accordance with Euro V fuel
specifications, requiring the sulphur content to be less than 10 ppm. In order to reach
the sulphur specifications for gasoline and gas oil pools, various hydro-treating units
are required. Three distinct hydro-treaters are considered in the model: naphtha hydrotreater, distillates (kerosene and diesel) hydro-treater and gas oil hydro-treater which
prepares the feed for fluid catalytic cracking. For simplicity, whenever hydro-treating
process is mentioned, it will refer to these three units.
Reforming produces high purity hydrogen to satisfy the needs of hydro-treating
processes. A hydrogen production unit via steam methane reforming is also considered
to supplement the requirements for hydrogen associated with hydro-treating and
hydrocracking processes.
4.2.2
Required Inputs and Outputs of the model
The key inputs required for the PRIMES-Refinery model are the capacities of the
refining processes within the refinery configuration per EU country. Oil and Gas Journal
Worldwide Refining Survey includes analytical data for the worldwide refineries and
their capacities. Valuable information is obtained regarding the number of active
refinery industries, the main operations of European refineries and the capacity of each
of them.
Apart from the crude oil capacity which is the main indicator of the size of the refinery,
Oil and Gas Journal database provides information on the charge and production
capacity in barrels per capital day (b/cd) for every single refinery worldwide. Production
related capacities provide data associated with aromatics, lubes, oxygenates,
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hydrogen, sulphur, coke and asphalt production. The following charge processing units
are included in the survey:







vacuum distillation,
coking,
thermal operations,
catalytic cracking,
catalytic reforming,
catalytic hydrocracking,
catalytic hydro-treating.
Further, data on the various MCONs entering the European refineries have been
collected within Task b. The various MCONs are further disaggregated by key
characteristics such as the API gravity and the sulphur content. This part is particularly
important for allocating the different MCONs entering the refinery gates of each EU
country with the representative crude type categories simulated in the PRIMESRefinery model. Feedstock supply for the refineries operations, as well as consumption
of electricity and gas are derived from the EUROSTAT energy balances.
Electricity and gas consumption needs to be further disaggregated into quantities
purchased directly from external sources and quantities produced within the refinery
boundary system. This split is important for the calculation of the GHG emissions
related to the electricity and gas consumed. Different emission factors will be used to
derive the GHG emissions from the electricity and natural gas imported from external
sources. For instance, in the case of electricity, the GHG emission factor assumed will
be related with the structure of the power generation sector of the country. As regards,
the electricity and gas produced within the refinery, the emission factor will be refinery
specific and data will be drawn from the EUROSTAT balances and the calibration of
PRIMES database to past years. The quantities of the refined petroleum products
imported in the EU by major exporting countries such as Russia and US have already
been identified during Task b. The total refined petroleum products that are produced
at a national level over the EU countries is also provided by the EUROSTAT balances.
Other techno-economic data regarding the heat-rates (conversion factors), utilization
rates of the processes, operating and investment costs as well as the respective
emission factors are also currently under update using sources from literature and
technical refinery reports.
4.2.3
Estimating the GHG emissions due to transportation from
refineries to filling stations
Methodology
The transportation of the refined petroleum products from the refineries to the filling
stations in the EU Member States usually takes place via road freight, freight rail and
inland waterways, which are currently operating mainly on fossil fuels. The use of fossil
fuels is responsible for GHG emissions which take place during the transportation of
the refined petroleum products and should be included in the lifecycle carbon
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emissions of diesel, petrol and kerosene. To calculate the carbon intensity 𝐶𝐼𝑐,𝑘 per
transport mode 𝑘 and country 𝑐 used to transport the refined petroleum products 𝑅𝑝𝑝
we use the formula in Eq 1. This formula is based on the activity of the transport mode,
usually measured in ton-kilometers (tkm), the emission factor of the mode (in
gCO2/tkm) and the total quantity of refined petroleum product transported (in MJ).
𝐶𝐼𝑐,𝑘 =
𝑔𝐶𝑂2
)
𝑡𝑘𝑚
𝑅𝑝𝑝 𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑒𝑑𝑐,𝑘 (𝑡𝑘𝑚)×𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑓𝑎𝑐𝑡𝑜𝑟𝑐,𝑘 (
Eq 1
𝑞𝑢𝑎𝑛𝑡𝑖𝑡𝑦 𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑒𝑑𝑐,𝑘 (𝑀𝐽)
To derive the average carbon intensity of the transportation of the refined petroleum
products from the refinery to the filling stations, the weighted average is calculated
based on the activity in tkm of each respective transport mode using the following
formula (Eq 2).
𝐶𝐼𝑐 =
∑𝑘 𝐶𝐼𝑐,𝑘 ×𝑅𝑝𝑝 𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑒𝑑𝑐,𝑘
∑𝑘 𝑅𝑝𝑝 𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑒𝑑𝑐,𝑘
Eq 2
Further, to account for the fugitive GHG emissions at the level of the filling stations, a
typical emission factor has been used from literature. As these emissions are relatively
small compared to the LCA GHG emissions, for simplicity, the same emission factor
has been assumed for the fugitive GHG emissions for all the EU countries. The most
recent emission factor found in the technical report published by the National
Environmental Research Institute has been utilized; the emission factor used is equal
to 0.46 kg NMVOC/ ton gasoline.
Input data
The required input for these calculations is the activity of each respective transport
mode transporting refined petroleum products, the amount of products transported, and
the emission factors per transport mode. The resolution of the data is at a national
level.
Data on the activity of road freight, freight rail and inland waterways transporting
refined petroleum products has been derived from EUROSTAT database. For road
freight the element “road_go_na_tgtt” has been used which includes statistics on both
the activity and the tons of refined petroleum products transported. As regards freight
rail, EUROSTAT did not provide the activity and the tons of refined oil products
transported at a national level. Therefore, shares were derived from the element
“rail_go_natdist” which only reported data until 2002 and applied these shares to the
total goods transported by rail at a national level in 2012 (element “rail_go_typeall”).
Regarding inland waterways, the values on activity and the tons of refined petroleum
products from the element “iww_go_atygo” were used from EUROSTAT. The emission
factors per transport mode used in our calculations are drawn from the PRIMESTREMOVE12 transport model, developed and maintained by E3MLab. The values used
12
http://www.e3mlab.ntua.gr/e3mlab/PRIMES%20Manual/PRIMES%20TREMOVE_v3.pdf
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have also been validated with the values reported in the TRACC13S database.
Draft results
The resulting values of the carbon intensity due to the transportation of refined
petroleum products from the refineries to the filling stations by EU country are
presented in Table 4.5. According to calculations we observe some variations are
observed in the resulting values which are attributed to the different shares of transport
modes used to transport refined petroleum products to the filling stations and different
emission factors per EU country. For the purposes of the present study an average
value for the carbon intensity at the EU level which is estimated to be about 0.29 gr
CO2/MJ.
Country
13
Carbon intensity
(grCO2/MJ)
Belgium
0.32
Bulgaria
0.26
Czech Republic
0.23
Denmark
0.50
Germany
0.18
Estonia
0.21
Ireland
0.50
Greece
0.33
Spain
0.37
France
0.29
Italy
0.46
Cyprus
0.53
Latvia
0.38
Lithuania
0.15
Luxembourg
0.66
Hungary
0.16
Netherlands
0.18
Austria
0.16
Poland
0.17
Portugal
0.32
Romania
0.42
Slovenia
0.19
Slovakia
0.11
Finland
0.31
Sweden
0.25
United Kingdom
0.42
Croatia
0.48
http://traccs.emisia.com/
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Country
EU average
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Carbon intensity
(grCO2/MJ)
0.29
Table 4.5: Estimated carbon intensity of refined petroleum products due to
transportation from refineries to filling stations (also including fugitive
emissions at the level of filling stations). Source: E3MLab calculations
THE GHGENIUS MODEL
4.3
4.3.1
Model rationale and structure
The GHGenius lifecycle model is a publicly available, Excel based, model that
considers the lifecycle energy use and emissions from transportation fuels and
vehicles. The model has been developed over the past 15 years by (S&T)2 Consultants
Inc. Most of the development work has been funded by Natural Resources Canada.
The model can perform a lifecycle assessment for specific regions (east, central or
west) of Canada, the United States and Mexico or for India as a whole. For Canada, it
is also possible to model many of the processes by province. It is also possible to
model regions of North America. It is the regional nature of GHGenius that makes it an
appropriate tool for studying the emissions of producing, processing, transporting and
transforming the gas for use in the transportation sector for Europe.
The spreadsheet structure of GHGenius makes it relatively easy to expand the model
to other regions of the world, in this case the European Union. The model is fully
transparent and users can easily trace all stages of the calculations.
There are over 200 vehicle and fuel combinations possible with the model. Although
the focus of this work is just the natural gas fuel supply chain up to the point that the
natural gas would be dispensed to a vehicle.
4.3.2
Model parameters and structure modification
The structure of GHGenius has been changed to provide the desired results of this
project. The number of regions that the model is capable of analysing has been
expanded with the addition of 4 more regions for Europe. The expansion of the model
has not resulted in any loss of functionality for any of the existing regions in the model.
The four new European regions are:


Northern Europe. The gas supply in the region is from the North Sea fields,
imported LNG, and some Russian gas.
Central Europe. Significant gas suppliers to the region are Russia, the
Netherland, and Norway. There are some indigenous supplies and imports of
LNG as well.
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South East Europe. This region has Russia and Algeria as the major suppliers
with a large number of smaller suppliers supplementing the two major suppliers.
South West Europe. The significant gas suppliers include Norway, Algeria, the
Netherlands, Russia and LNG from Qatar and Nigeria.
In addition to the four new consuming regions, new gas producers have been added to
the model. Some of these gas supply regions were already in the model but the data
was of very poor quality. That will be addressed as part of the project. The gas
suppliers that will be included in the revised model are:
Countries with existing quality information:




United States
Canada
Mexico
India
Existing Countries that need updated information:




Algeria
Norway
Russia
United Kingdom
New Countries added to the model:













Netherlands
Denmark
Libya
Germany
Belgium?
Generic shale gas
Other
Qatar LNG
Nigeria LNG
Algeria LNG
Trinidad and Tobago LNG
Indonesia LNG
Other LNG
Algeria will have two supply systems, pipeline gas and LNG. The model inputs for the
two types of gas will be slightly different with the extra energy required to liquefy the
gas included in the LNG supply options.
Not all of these LNG sources are currently gas suppliers to Europe, but they are large
global suppliers and space has been made for them in the model. The other LNG
suppliers will have average values so that the suppliers that contribute less than 1% of
the gas supply can be accounted for. We will also add a generic EU shale gas supplier
to the model so that can be considered as a future supply source as well. Data for this
supply option may have more uncertainty.
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Natural gas supply systems generally use mostly natural gas energy in the production
system but there can also be electricity consumed and a small amount of liquid fuels.
Electricity will also be used in the gas consuming regions for compression to CNG. The
GHGenius model structure has therefore been expanded to include the specific
regional electricity production data for the gas producing countries and the gas
consuming regions. This will include the mix of energy sources used to produce the
power, the efficiency of the thermal generating system, and the distribution losses in
the grids.
The contribution of the production of liquid fuels to the complete lifecycle emissions is
expected to be small and less effort will be expended to use regional specific data for
liquid fuel production for this work.
GHGenius currently allows for the input of energy used for well drilling, gas production,
and gas processing for gas production in Canada and the United States. The specific
energy inputs that can be input are crude oil, diesel fuel, residual fuel, natural gas, coal,
electricity, gasoline, and coke. Other gas producing regions are estimated on a total
quantity of energy consumed relative to energy consumed in the US. This same
structure used for Canada will be introduced for all of the other gas supply regions.
The model will be modified to include two tables of transportation distances from the
gas supplier to the gas consuming region. One table will have pipeline distances and
the other will have shipping distances for LNG. The average distance for each
consuming region will be used to calculate the energy consumed and the emissions
from the transmission and transport of the gas.
An important part of the natural gas supply chain is the rate of methane loss from the
system, this can be through venting, flaring, or equipment leaks. The new structure of
the model will accommodate separate inputs for all of these emissions for all gas
producers and for the gas consumers for the transmission losses.
The final emission source that is included in the model is the emission of carbon
dioxide that is removed from the gas during processing to bring the gas to pipeline
quality.
4.3.3
Required Inputs
In order to model the lifecycle GHG emissions from the supply of natural gas in Europe
a significant amount of data is required. The data required includes;




The gas production, imports and consumption for each of the EU countries.
The carbon intensity of the electric power used in each of the producing
countries, as some electricity can be used to produce and process the natural
gas in the producing country.
The carbon intensity of the electric power used in each of the EU countries as
electricity is used to compress the natural gas to CNG.
For each supplier of natural gas the data that will ideally be required are those
for three stages of gas production, well drilling, gas extraction, and gas
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processing. The data required will include the quantity and type of energy
required for each of the three stages, the methane loss rate of each stage, the
quantity of gas flared, and the quantity of carbon dioxide released to the
atmosphere to bring the field gas to pipeline specifications.
For each supply source the pipeline or shipping distance of gas to the EU
region will need to be identified so that the energy consumed in the gas
transmission/transportation stage can be determined. For each of these
activities the methane loss rate will be required.
Within each of the EU countries energy use in gas distribution (medium
pressure) and the relevant emissions will be assessed. Energy use in
distribution is very small as compression is not required, like it happens in
transmission; however the distribution gas loss as fugitive gas can be
substantial.On the other hand electricity requirements of gas distribution
systems are mostly related to compression of pipeline gas to CNG.
4.3.4
Parametric significance
There are three groups of GHG emissions in the natural gas supply chains. There are
CO2 emissions resulting from the purification of the raw gas to pipeline specifications.
Depending on the gas composition of the specific fields these can be zero or some
extreme cases these emissions might account for 4 or more gr CO2eq/MJ. In some gas
fields the CO2 may be re-injected into the reservoir to help maintain the field pressure.
This will lower the direct emissions of CO2, but the re-injection process will increase the
energy consumption and thus there will be some energy related emission increase that
will offset the savings from the re-injected gas.
The second category of emissions is energy related; those emissions resulting from the
use of energy in all stages of the supply chain. Field pressure, gas composition,
transmission distances, and pipeline characteristics can all influence the energy
consumed in the natural gas supply chain. Energy is used in the well drilling, gas
production, gas processing, gas liquefaction and regasification (for LNG supply), gas
transmission, but only in rare instances the gas distribution stage. The contribution of
energy related emissions is typically 5 to 10 gr CO2eq/MJ.
The third category of emissions is the leaks of methane from the system. Every stage
has the potential for some methane emissions, and since methane has a GWP of 25,
these emissions can become quite significant in “leaky” systems. In a few cases
methane leaks are deliberate such as using the natural gas to actuate control values
instead of using compressed air systems, but in most cases the methane emissions
are unintended and could be fugitive type emissions. Methane emissions are difficult to
quantify accurately since there can be literally thousands of individual points of
potential leaks in a supply chain. Every valve, meter, compressor, relief station, and
connection can be a source. Methane emissions from less than 0.5% to 1.5% can be
expected in most supply chains. These emissions are equivalent to 4 to 12 gr
CO2eq/MJ.
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Produced outputs
GHGenius can provide significant detail on the emissions for natural gas. The most
common form of the output is the GHG emissions by stage per GJ of fuel. For natural
gas systems the typical output is shown in Table 4.6. While the focus of the work is on
the emissions for CNG, the model will also provide the natural gas emissions for gas
supplied to power generators, fuel conversion facilities (e.g. methanol plants), and
other end users.
Stage
Compressed Natural Gas
Natural Gas for Industry
gr CO2eq/GJ (LHV)
Fuel dispensing
2,534
0
961
862
2,787
2,778
0
0
3,007
2,997
Feedstock Upgrading
0
0
Land-use changes,
cultivation
0
0
Fertilizer manufacture
0
0
Gas leaks and flares
3,214
1,605
CO2, H2S removed from NG
1,081
1,078
0
0
13,584
9,319
Fuel distribution and storage
Fuel production
Feedstock transmission
Feedstock recovery
Emissions displaced
Total
Table 4.6: Typical GHGenius Output on the emissions of natural gas
The information can also be supplied by the total emissions of the individual gases as
shown in Table 4.7. The emissions of these gases by stage can also be provided in a
series of tables for each gas.
GHGenius also can report on the primary energy consumed for each stage of the
process. Primary energy includes the energy required to produce the energy, it is the
lifecycle energy used. Total primary energy and fossil primary energy can be reported.
The typical energy use is shown in the Table 4.8. This output is only available on a
higher heating value basis.
Stage
Compressed Natural Gas
Natural Gas for Industry
gr CO2eq/GJ (LHV)
Carbon dioxide (CO2)
9,251.1
6,718.3
Non-methane organic
compounds (NMOCs)
3.7
3.0
170.6
102.2
Methane (CH4)
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Compressed Natural Gas
Natural Gas for Industry
Carbon monoxide (CO)
7.2
6.0
Nitrous oxide (N2O)
0.2
0.2
Nitrogen oxides (NO2)
52.7
44.6
Sulphur oxides (SOx)
15.9
7.0
Particulate matter (PM)
0.8
0.3
HFC-134a (mg)
0.0
0.0
13,583.6
9,318.8
CO2-equivalent GHG
emissions
Table 4.7: Typical GHGenius Output by Specific Gas
Stage
Compressed Natural Gas
Natural Gas for Industry
Joules consumed/Joule Produced
Fuel dispensing
0.0250
0.0000
Fuel distribution, storage
0.0143
0.0128
Fuel production
0.0392
0.0391
Feedstock transmission
0.0000
0.0000
Feedstock recovery
0.0416
0.0415
Feedstock Upgrading
0.0000
0.0000
Ag. chemical manufacture
0.0000
0.0000
Co-product credits
0.0000
0.0000
Total
0.1202
0.0935
EROEI (J delivered/J
consumed)
8.3186
10.7007
Table 4.8: Typical GHGenius Output for the Total Energy Consumption
The type of energy used can also be provided as shown in Table 4.9. This energy use
is reported as secondary energy. Secondary energy is the energy content of the
electric power, or diesel fuel, or coal at the point that it is used.
Energy Type
Compressed Natural Gas
Natural Gas for Industry
Joules consumed/Joule Produced
Coal
0.0000
0.0000
Crude
0.0000
0.0000
Natural Gas
0.0832
0.0817
Diesel
0.0006
0.0006
Gasoline
0.0000
0.0000
Biomass
0.0000
0.0000
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Compressed Natural Gas
Natural Gas for Industry
Electricity
0.0187
0.0017
Other
0.0000
0.0000
Total
0.10
0.08
Table 4.9: Typical GHGenius Output for the Secondary Energy Use by Type
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5
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TASK D: INDIRECT EMISSIONS
Regarding indirect emissions, the following activities have been conducted.





Articles reviewed and uploaded to database;
Method for calculation of indirect GHG emissions developed;
Information on indirect GHG emissions partly developed/identified;
Background data for calculation of average indirect GHG emissions established;
Preliminary results for some indirect GHG emissions calculated.
This section presents the method for estimating indirect emissions and reveals some
preliminary results regarding the magnitude of the indirect emissions.
5.1
SYSTEM BOUNDARY DEFINITION
Along with the direct GHG emissions from the life cycle (well-to-tank) of transport fossil
fuels (diesel, petrol, kerosene and natural gas); this study will also include the “indirect
emissions” in the analysis.
More precisely, the indirect emissions will be identified and assessed, and where
possible these emissions will be included in the total estimates of the GHG emissions
from the fuels.
The relevant stakeholders have not clearly defined indirect emissions. For the purpose
of the present study, the following definition will be used:
Direct emissions are emitted from the processes used to produce and transport the fuel
along the life cycle. Indirect emissions are those that are influenced or induced by
economic, geopolitical or behavioural factors, but which are not directly related
to extraction, processing, transportation and distribution of the fuels14.
In order to make sure that all relevant emission sources are covered by the project,
there is need to define clearly what is considered direct and indirect emission sources
respectively.
5.2
ATTRIBUTIONAL AND CONSEQUENTIAL EMISSIONS
Indirect emissions can be divided into two types:
14
Corresponding to the definition in the ICF report on Indirect Emissions (page 2)
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

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Attributional emissions: Emissions that can be said to be related to the
production of the fossil fuels and thus can be added to the direct emissions
estimated by the traditional LCA approach. An example of attributional
emissions is the case of emissions related to military activities to protect the
resources.
Consequential emissions: Emissions arising from changes at the level of the
production of fossil fuels. These are related to the forecasting of the future
emissions but not in terms of estimating the emissions from today's fuels. An
example of a consequential emissions source is “price effects”: Reduced
demand for fossil fuels for transportation due to substitution with alternative
fuels will lower fossil fuel prices, which in turn will tend to increase the demand
for fossil fuels used for other purposes. Thus, the full positive impact from the
fall in the demand for fossil fuels for transport will actually not occur.
Attributional emissions are associated with the full estimation of the actual lifecycle
emissions, whereas the consequential emissions are associated with the projections on
future GHG emissions. The study of indirect effects will focus on the attributional part,
especially when it comes to the estimation.
Following a literature review, the indirect emissions sources identified and included in
the study are listed below. These are described focusing on the boundaries to the
direct emissions, where relevant.


Attributional emissions sources:
- Induced land development
- Military involvement
- Accidents.
Consequential emission sources:
- Marginal effects
- Price effects
- Co-product production.
Figure 5.1 below illustrates the indirect emission sources (marked in red) and the
placement in the fossil fuel life cycle.
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Figure 5.1: Identification of indirect emission sources related to oil and gas
pathway from well to tank
MAIN INDIRECT EMISSIONS
5.3
5.3.1
Attributional emissions sources
Induced land development
This issue covers the induced land development caused by adjacent developments
that are facilitated by oil and gas production in remote areas.
It is important to distinguish between direct and indirect emissions from land
development:


The direct emission source arises from the need for land to produce and
transport fuels, thus the emissions related to clearing land for these purposes.
These can be compared with the ILUC emissions for biofuels, although the
impacts from fossil fuels are limited compared with the impacts from biofuels.
The direct impacts of land use change are considered a direct effect and not
covered in the study of indirect impacts.
The indirect emission source referred to as “induced land development”
covers the impacts caused by the access to remote areas. Extraction of the raw
materials requires access to areas that would possibly otherwise be left
untouched. The development of infrastructure will thereby cause disturbance to
the area. The magnitude of the emissions impact will, among other things,
depend on the type and location of the land involved. For example, it is
generally accepted that oil activities opened up new agricultural frontiers in the
northern Amazon region by building penetration roads into primary forest areas
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(ICF, p. 28). Therefore, the question is naturally whether the deforestation is
“additional” or whether a possible deforestation is just moved from one area to
another.
In the study, into the possible effects of induced land development will be investigated.
This will include, among other things, exploring the differences between various types
of raw materials and the geographic location, and considering whether the induced
land development is additional or a replacement.
Military involvement
This issue covers emissions from military activities to provide security and stability to
oil-producing regions and to protect international oil supply routes. The key issue is to
what extent military activities are motivated by efforts to secure petroleum and gas
reserves?
Emissions from military activities arise from fuel combustion from military means of
transport as well as from the energy used to construct military infrastructure and rebuild
states that have been affected by conflicts.
The emission sources can be divided into two categories: security-related emissions
(from long-term, sustained military presence in a geographic area) and conflict-related
operations emissions (such as the Gulf War).
Accidents
Accidents may occur throughout the pathways followed by the fossil fuels and may
have severe environmental impacts. Possible GHG emissions caused by accidents fall
within the following categories:


Blowouts (uncontrolled bursts or releases of oil and gas) during extraction.
These certainly have a severe environmental impact, but they are not GHG
emissions unless the oil is burnt or the blowouts involve release of methane.
Accidents during transportation or storage at the ocean: clean-up may include
surface burning of oil causing GHG emissions.
These possible impacts will be included in the analysis of indirect sources, where other
possible emission sources caused by accidents will also be investigated.
Fugitive emissions from sources such as sealing, well completions and work-overs (i.e.
retrofitting a well) are “engineered losses” that occur during normal operation. These
are considered direct emissions and are consequently not included in the analysis of
indirect emission sources.
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5.3.2
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Consequential emissions sources
Marginal impacts
This issue covers impacts on the fossil fuel lifecycle that would result from large-scale
economy-wide changes in the supply and demand of fossil fuels.
This may result in at least two different consequences:


Changes in demand will alter the marginal fossil fuel resource consumed. This
will change the types of fossil fuels extracted and the operation of refineries, all
affecting the GHG emission profile.
Increased demand for natural gas for transportation may reduce the use in the
electricity sector, resulting in changes in the mix of fuels used in electricity
production.
These impacts are expected to be modelled in the forecast models and are therefore
not included in this section of indirect emission sources.
Price impacts
Changes in the use of fossil fuels for transportation will affect the demand and thereby
the prices, which in turn will affect the demand for fossil fuels in other sectors. This
rebound effect is normally best modelled and assessed in economic models, especially
in the field of “general equilibrium modelling”.
Price impacts need to be taken into account in the forecasting. It is expected that the
models of E3M LAB will capture such impacts, and this issue will thus not be handled
within the area of indirect effects.
Production of co-products
The refinery process also results in various co-products besides the fossil fuels.
Without fossil fuels, these have to be produced in other ways or substituted by other
products in the use.
Two aspects of the production of co-products have to be considered in the LCA.
First, it could be argued that some of the emissions throughout the life cycle should be
assigned to the co-products, thus reducing the emissions from the fossil fuel part.
There are different methods for doing that, and it is assumed that these emissions will
be covered by the calculations of direct effects in the refinery model.
Secondly, changes in the production of fossil fuels will result in the need to find
alternative ways of producing the co-products or substituting the use of the co-products
with alternative products, which will affect the GHG emissions. This is an indirect and
consequential emission source, which may be considered in this study.
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5.4
Interim Report
METHODOLOGY FOR ASSESSMENT OF INDIRECT EMISSIONS
Oil and gas consumed in the EU come from different locations and are transported with
different technologies. The indirect emissions are relevant only for some of these
locations and technologies. For instance, induced land development will only be
relevant in areas where there is a potential for deforestation and maybe also later for
use of land for alternative purposes. Military CO₂ emissions may only be relevant in
areas with politically unstable conditions like in the Middle East. In order to include
these indirect GHG emissions, there is need to analyse which indirect GHG emissions
are relevant for each of the locations from which we get the oil and gas.
Table 5.1 shows how we suggest breaking down fossil fuel extraction and transport to
match specific, indirect emissions.
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Region
Country of
Origin
Iran
Iraq
Kuwait
Saudi
Arabia
Algeria
Angola
Africa
Libyan Arab
Jamahiriya
Nigeria
Azerbaijan
Kazakhstan
FSU
Russian
Federation
Denmark
Norway
Norway
Norway
UK
Mexico
Venezuela
Name
Gachsaran oil field
Rumaila (South)
West Qurna
Kirkuk
Burgan
Kurais
Manifa
Hassi Messaoud
Block 17/Dalia
Girassol
Greater Plutonio
Es Sider
El Sharara
Bonga
Forcados Yorki
Agbada
Caw Throne Channel
Escravos Beach
Azeri-Chirag-Gunashli (ACG) field
Tengiz
Azeri-Chirag-Gunashli (ACG) field
Tengiz
Povkhovskoye
Tevlinsko-Russkinskoye
Uryevskoye
Vat-Yeganskoye
Pamyatno-Sasovskoye
Unvinskoye
Tyra south east
Statfjord
Ekofisk
Troll B/C
Tyrihans
Oseberg
Gullfaks
Buzzard
Ninian
Captain
Cantarell
Boscan
Offshore
/Onshore
On
On
On
On
On
On
On
On
Off
Off
Off
Off
Off
Off
Off
On
On
On
Off
On
Off
On
On
On
On
On
On
On
Off
Off
Off
Off
Off
Off
Off
Off
Off
Off
Off
On
Interim Report
Transport
Pipeline / Tanker
Pipeline / Tanker
Pipeline / Tanker
Pipeline / Tanker
Pipeline / Tanker
Pipeline / Tanker
Pipeline / Tanker
Pipeline / Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Pipeline / Tanker
Tanker
Pipeline / Tanker
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Pipeline
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Tanker
Location
Political
Political issues
Political issues
Political issues
Political issues
Political issues
Political issues
Political issues
Political issues
Political issues
Political issues
Political issues
Political issues
Rain forrest
Rain forrest
Rain forrest
Political issues
Political issues
Political issues
Political issues
Rain forrest
Table 5.1: Potential indirect GHG emissions for oil consumed in the EU
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By combining the information from Table 5.1 with the amount of oil consumption from
these locations, it will be possible to calculate the share that is relevant for the specific
types of indirect GHG emissions. This is shown in Table 5.2.
Issues
Share of oil consumption in the EU (%)
Tanker transport
58 %
Rain forest
6%
Political issues
31 %
Table 5.2: Share of oil production affected by specific indirect GHG emissions
As can be seen, more than half of the oil consumed is transported to the EU by oil
tankers, with the potential risk of oil spills from oil tanker accidents. The rest is
transported by pipeline from Russia.
Only a very small fraction of 6% of the oil consumed in the EU comes from areas with
potential, induced land development effects in rain forest areas.
A percentage of 31% of the oil consumed comes from areas where politically unstable
situations may justify military presence to secure stable energy supply.
A similar picture can be drawn for natural gas, pipeline transported as well as LNG
transported by gas tankers.
The share of natural gas production of indirect GHG emissions is to be developed.
However, it is expected that the major source of indirect GHG emissions from natural
gas will be methane leaks from pipeline transport and tanker accidents and to a lesser
extent military GHG emissions from military activities in areas with politically instable
conditions.
DATA COLLECTION FOR INDIRECT EMISSIONS
5.5
The data collection for GHG emissions from different indirect GHG emissions is to be
based on the literature survey. The section below gives an assessment of the different
GHG emissions one by one. It contains a near-final description of induced land
development and a more preliminary handling of other effects.
5.5.1
Induced land GHG emissions
The Induced land effect contains two elements of GHG emissions.


GHG from harvesting rain forest
GHG from using the land after it was harvested.
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As defined, the indirect effect (or indirect emission source) termed induced land
development - in the present context - comprises land development that is induced by
developments in extraction of raw materials such as oil and gas for fossil fuel
production.
Such developments might open up access to remote, otherwise inaccessible, areas,
and besides the immediate deforestation they act as corridors and thereby open up for
new activities such as:


industrial forestry/logging, and subsequent
farming and/or ranching
The most characteristic case is related to the area of Amazon River.
Different types of fossil fuels result in varying degrees of land disturbance depending
on the type and location of land involved in the production of the fuel. Additionally,
concerning the drivers behind induced land development, factors including but not
limited to social changes, demographic shifts, political unrest, and economic incentives
must be examined.
For example, Unnash et. al (2009), based on other work by among others Perz,
Brilhante et al (2008) and Wunder (1997), argue that road construction and expansion
triggers logging on areas along the road, and when the areas are "harvested",
subsequent farming or ranching follows. Also, other infrastructure and derived
economic activity might follow.
However, regardless of how well induced land development can be concretised and
delimited, there are obviously difficulties in assessing the resulting GHG emissions, as:



It is very difficult to assess whether the actual, induced developments are
"additional" or alternatively would have occurred somewhere else,
without/regardless of the direct development in oil and/or gas production.
If part of the land development is actually "additional" in the sense that it would
not have occurred somewhere else, it will still be quite difficult to isolate
development of land that is specifically induced by oil and gas production in
affected areas from other facilitators of land use change and development in
those areas.
The size/intensity of resulting GHG emissions will obviously depend on the
geographical location of the induced land development – hereunder type of land
affected.
The only actual estimate of such induced land development seems to be calculated by
Unnasch et al. (2009).
Based on previously mentioned other work by among others Perz, Brilhante et al
(2008) and Wunder (1997), Unnash et. al (2009) presume that road building for
petroleum extraction and production, besides the initial relatively limited direct
deforestation, facilitates further and more considerable, induced deforestation caused
by industrial logging and/or subsequent agricultural activities.
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Based on available data from a study by Viña, Echavarria et al. (2004) concerning such
mechanisms along the border between Colombia and Ecuador, the extent of
deforestation associated with road building is estimated based on the proximity of
deforestation to the road network. The actual estimate obtained concerns a 5 km wide
zone along specific roads and amounts to approximately 32,710 hectares.
Assuming that all deforestation within a certain distance from roads built for petroleum
exploration and production in Ecuador is attributable to those roads during a certain
time period, and using a carbon loss factor for Latin American rainforests, estimated to
422 Mgr CO2eq/ha based on Searchinger, Heimlich et al. (2008), an estimate of the
quantity of CO2 released is calculated to approximately 13.8 Tgr CO2eq.
Comparing this estimate with an estimate of the total production of oil from this area,
during a related time period, Unnash et. al. (2009) estimated that the indirect emissions
related to induced land development amount to approximately 0.6 gr CO2eq /MJ to
approximately 1.0 gr CO2eq /MJ.15
This example clearly illustrates that it is not straightforward to estimate emissions from
induced land development, the emissions will largely depend on various assumptions
of the extent to which oil and gas development in an area facilities other indirect
deforestation activities such as




The extent to which road building in a given area is related to exploration and
production of fossil fuels – or rather to other facilitators.
The extent to which a certain activity such as deforestation, and eventually
subsequent farming, is related to that road building, hereunder the extent in
time.
The level of carbon losses related to this certain activity such as deforestation
The associated production of fossil fuels, hereunder the extent in time.
The above estimate of GHG emissions associated with induced land development – if
assumptions are accepted – might be considered an upper estimate depending on the
extent to which land development is additional. If not additional, the associated
emissions might be considered zero.
5.5.2
Accidents
Accidents may occur along the full lifecycle of the fossil fuels, from extraction to tank.
These accidents may have severe environmental impacts. The GHG emissions,
caused by accidents fall in the following categories:


Blowouts
Tanker accidents.
15
This estimate is obviously dependent on the underlying assumptions such as the fractions of the
deforestation attributed to petroleum extraction, or size of the buffer used, as the estimate will increase or
decrease accordingly to an increase or decrease in the aforementioned factors.
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Blowouts (uncontrolled bursts or releases of oil and gas) during extraction certainly
have a severe environmental impact, and they may require substantial clean-up
activities resulting in additional GHG emissions. The release of oil itself may not result
in GHG emissions, unless the oil is burnt or the blowouts concern release of methane.
Regarding GHG emissions related to outbursts, this effect should be calculated as
gram of GHG per extracted tonne of crude oil or natural gas.
Tanker accidents may result in GHG emissions during clean-up activities and burning
oil from the water surface.
The probability of tank ship accidents depends on the distance travelled. Therefore, it
would give the most accurate results to calculate the costs of tanker accidents as the
GHG for each km the oil is transported.
For pipeline natural gas and LNG, the major indirect GHG emissions in connection with
accidents are caused by methane evaporation.
According to Wuppertal (2005), there are substantial leaks of methane from the
compressor stations due to accidents. However, the question is whether these
emissions are considered indirect or direct emissions.
The major share of CO₂ emissions from pipeline transport is due to CO₂ emissions
from compressor stations. These emissions are parallel to for instance fuel emissions
from tanker transport, which is assumed a traditional, upstream direct emission.
However, there is also a substantial GHG emission due to leakages in the compressor
stations.
In the Wuppertal study, the indirect emissions due to leakages amount to
approximately 20% of 11 to 19 tonnes of CO2eq. per TJ natural gas, amounting to 2.23.8 tonnes of CO2eq per TJ. Still, a significant amount since the emissions from
combustion of natural gas amounts to approximately 56 tonnes of CO2eq per TJ
Natural gas.
The total amount of leakages in compressor stations will depend on the distance and
number of compressor stations. Therefore, it would be reasonable to calculate the
emissions from natural gas relative to the length of the pipeline.
5.5.3
Military GHG emissions
The emissions from military activities arise from fuel combustion by military means of
transport as well as from the energy used to construct military infrastructure and rebuild
states that have been affected by conflicts.
There are two types of military effects.


Military intervention in politically unstable areas
Military enforcement to secure safe transportation of fuels.
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The first type may be estimated by looking at the military GHG emissions from military
interventions, like for instance the Iraq War. Based on literature studies, this effect is
estimated to be at the level of 1gr CO2eq/MJ oil produced in the Persian Gulf. This type
of GHG emissions should only be applied in regions with politically unstable situation.
The other effect is due to military presence to secure safe transport of fossil fuels for
instance from the Persian Gulf. This effect is also in the order of magnitude of
approximately 1 gr CO2eq/MJ fossil fuel.
In both cases, there is uncertainty for instance about the extent to which the military
presence is solely due to secure safe fossil fuel deliveries. In the context of the Iraq
War, there might be other purposes. Consequently, this argument would point to an
overestimation of the indirect GHG emissions. On the other hand, the estimate referred
to above only includes GHG emissions from the US military forces. Since other
countries may also have contributed, this might lead to an underestimation of the GHG
emissions here.
Considering the potential biases, it seems reasonable to assume an indirect GHG
emission of approx. 1 gr CO2eq/MJ for both presence in the area and transport of fossil
fuels.
5.6
PRELIMINARY RESULTS
The average indirect GHG emissions are calculated by weighing the unit values for
specific indirect GHG emissions with the share of oil and gas flow relevant for each
type of indirect effect.
For instance, the induced land development may have a GHG emission of
approximately 1 gram of CO₂ per MJ. However, since the induced land development
effect is only relevant for oil and gas extracted in rain forest areas, this effect will only
contribute with 6% of the 1 gr CO2eq when we calculate the average indirect GHG
emission.
This section will illustrate the idea and preliminary results of these calculations. In the
final version, this section will be further developed with more explanations, numbers
and discussions of the validity of the results.
The following Table 5.3 shows the unit GHG emissions for specific types of indirect
GHG emissions.
Issues
Induced land development
Estimate
≈ 1 grCO₂ /MJ
Oil tanker accidents
LNG Bunker accidents
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Issues
Estimate
0 – 4.5 gram CO₂ /MJ
LNG Bunker leaks
Military GHG emissions locations
≈ 1 gram CO₂ /MJ
Military GHG emissions transport
≈ 1 gram CO₂ /MJ
Table 5.3: Unit GHG emissions for specific indirect effects
Combining the above unit emissions with the share of total oil consumption in EU
where the issue is relevant, the following total indirect GHG emissions are calculated
from oil consumption in the EU. The relevant results for oil are presented in Table 5.4
Issues
Induced land development
Estimate
(gr / MJ)
Weight
Avg. indirect GHG
emissions (gr / MJ)
0.6 - 1
6%
0.036 - 0.06
Oil tanker accidents
58%
Military GHG emissions
locations
0.5 – 1.5
31%
0.155 – 0.465
Military GHG emissions
transport
0.5 – 1.5
31%
0.155 - 0.465
Total
0.346 - 0.99
Table 5.4: Average indirect GHG emissions for oil consumption in EU
LNG amounts to 12% of the natural gas stream into Europe. It is assumed that LNG
extraction takes place in and is transported from politically unstable regions. Just for
illustrative purposes; to be further developed in the draft Interim report. Average
indirect GHG emissions in EU for natural gas are presented in Table 5.5.
Issues
Induced land development
Estimate
(gr / MJ)
Weight
Avg. indirect GHG
emissions (gr / MJ)
0.6 - 1
0
0-0
LNG Bunker accidents
0-0
0 – 4.5
12%
0 - 0.54
Military GHG emissions locations
0.5 – 1.5
12%
0.06 - 0.18
Military GHG emissions transport
0.5 – 1.5
12%
0.06 - 0.18
LNG Bunker leaks
Total
0.12 - 0.9
Table 5.5 Average indirect GHG emissions for natural gas consumption in EU
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6
Interim Report
TASK F: PROJECTIONS UP TO 2030
Within the context of Task f, the study focuses on emissions associated with fuels
projected to be consumed in the EU up to 2030, with particular emphasis on the period
up to year 2020. The projections on future demand for petroleum refined products will
be based on projections drawn from the PRIMES model. Two scenarios already
quantified using PRIMES will be used: the Reference scenario 201316 and the GHG40
scenario17 used for the Impact Assessment by the European Commission for the policy
framework for climate and energy in the period from 2010 up to 2030. This section
presents an introduction to the methodological aspects of Task f and a brief overview of
the PRIMES energy systems model.
6.1
INTRODUCTION TO THE METHODOLOGY
The current study will address the objective of Task f using the official projections
provided by E3M-Lab to the European Commission in 2013 using the PRIMES energy
systems model. Projections of demand and supply of oil fuels and natural gas will be
used for a Reference and a Decarbonisation scenario as quantified using the PRIMES
energy system model for the EC. The Reference scenario is based on the Reference
scenario 2013, while the decarbonisation scenario is based on the GHG40 policy
scenario.
Refineries inputs and outputs are also explicitly projected by the PRIMES model for
2020 and 2030. PRIMES also provides projections regarding net imports of refinery
feedstock, ready-to-use refinery products and natural gas. PRIMES model is linked
with the PRIMES-Refinery model; therefore the scenario projections of PRIMES
(demand projections for the refined petroleum fuels) will be conveyed to the PRIMESRefinery model. The PRIMES-Refinery model will therefore be used to project the EU
refinery system in terms of refinery feedstock processing unit types used to distil and
separate distillates from the crude feedstock and the respective capacities installed at
EU Member State level.
The estimation of the GHG emissions associated with the petroleum fuels and natural
gas WTT value chain will follow the methodology of Task c which will apply to the
demand projected for years 2020 and 2030. GHG emissions that occur during the
upstream, midstream and downstream sectors will be assessed with the use of the
enhanced and modified OPGEE and GHGenius emission accounting models, as
already presented in Task c. The projected net imports of refinery feedstock and readyto-use petroleum products by PRIMES will be analysed based on country of origin and
16
17
http://ec.europa.eu/energy/observatory/trends_2030/doc/trends_to_2050_update_2013.pdf
http://ec.europa.eu/energy/observatory/oil/doc/refining/20140522_3nd_meeting_dgenergy.pdf
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type, in order to obtain detailed commercial flows. The analysis for projection years will
be based on assumptions relevant to current trends and to future production/import
projections. These assumptions will be harmonized with latest IEA World Outlook
projection of global oil/gas trade flows and regional production.
Similarly to Task c, the output of the analysis will be a range of GHG emissions
resulting from the WTT supply chain due to the large uncertainty involved regarding the
credibility and the availability of data. The range of emissions will then specify minimum
and maximum emission factors of fuels.
THE PRIMES ENERGY SYSTEMS MODEL
6.2
6.2.1
Model structure
PRIMES is a modelling system that simulates a market equilibrium solution in the
European Union and its Member States involving economic decision making of various
stylised actors. It determines energy consumption, transformation and supply of various
sectors, the costs involved and market prices. The PRIMES model simulates the
response of energy consumers and the energy supply systems to different economic
developments, exogenous constraints and drivers.
The model determines the equilibrium by finding the prices of each energy form such
that the quantity producers find best to supply match the quantity consumers wish to
use. The equilibrium is forward looking and includes dynamic relationships for capital
accumulation and technology vintages. The model is behavioural, formulating agents’
decisions according to microeconomic theory, at the same time representing, in an
explicit and detailed way, the available energy demand and supply technologies as well
as pollution abatement technologies. The system reflects considerations about market
competition economics, industry structure, energy /environmental policies and
regulation. These are conceived so as to influence market behaviour of energy system
agents. The market integrating part of PRIMES simulates market clearing.
6.2.2
Model coverage
PRIMES is a partial equilibrium model simulating the entire energy system both in
demand and in supply; it contains mixed representations of bottom-up and top-down
elements. The PRIMES model covers the 28 EU Member States, as well as candidate
and neighbour states (Norway, Switzerland, Turkey, South East Europe). The
timeframe of the model is 2000 to 2050 by five-year periods; the years up to 2010 are
calibrated to Eurostat data. The level of detail of the model is large as it contains:

12 industrial sectors, subdivided into 26 sub-sectors using energy in 12 generic
processes (e.g. air compression, furnaces)
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



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5 tertiary sectors, using energy in 6 processes (e.g. air conditioning, office
equipment)
4 dwelling types using energy in 5 processes (e.g. water heating, cooking) and
12 types of electrical durable goods (e.g. refrigerator, washing machine,
television)
14 transport means including private passenger road (cars, light duty vehicles,
powered two-wheelers), public passenger road (buses and coaches), road
freight (heavy duty vehicles, light duty vehicles) rail passenger and freight,
inland navigation and aviation) and vehicle technologies (e.g. internal
combustion engine by euro class, conventional hybrids by euro class, plug-in
hybrids, electric vehicles, fuel cells and others)18.
14 fossil fuel types, new fuel carriers (hydrogen, biofuels) 10 renewable energy
types
Main Supply System: power and steam generation with 150 power and steam
technologies and 240 grid interconnections
Other sub-systems: refineries, gas supply, biomass supply, hydrogen supply,
primary energy production
7 types of emissions from energy processing (e.g. SO2, NOx, PM)
CO2 emissions from all energy-related processes and from industrial processes.
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ANNEX A: COORDINATES
ANNEX A.1: OIL FIELDS
Oil field Name
Latitude
Longitude
Offshore/Onshore
Gachsaran
30,350
50,800
On
Rumaila (South)
30,156
47,408
On
West Qurna
31,051
47,423
On
Kirkuk
35,467
44,317
On
Burgan
29,111
47,967
On
Gwahar
25,430
49,620
On
Kurais
25,263
48,170
On
Manifa
27,711
48,971
On
Hassi Messaoud
31,661
6,055
On
Block 17/Dalia
-7,630
11,760
Off
Girassol
-7,633
11,683
Off
Greater Plutonio
-7,810
12,110
Off
Es Sider
30,613
18,282
On
El Sharara
26,510
12,260
On
Bonga
5,100
5,100
Off
Forcados Yokri
5,346
5,349
On
Agbada
5,010
7,037
On
Caw Thorne Channel
4,604
7,017
On
Escravos Beach
5,589
5,178
On
Azeri-Chirag-Gunashli (ACG)
40,018
51,266
Off
Azeri-Chirag-Gunashli (ACG)
40,018
51,266
Off
Tengiz
46,153
53,383
On
Tengiz
46,153
53,383
On
Tevlinsko-Russkinskoye
62,266
73,708
On
Uryevskoye
62,270
74,752
On
Samotlor
61,186
76,655
On
Vat-Yeganskoye
62,164
75,014
On
Povkhovskoye
57,246
66,793
On
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Latitude
Longitude
Offshore/Onshore
Romashkino
56,014
53,673
On
Unvinskoye
59,218
56,758
On
Pamyatno-Sasovskoye
50,663
45,131
On
Halfdan
55,710
4,800
Off
Statfjord
61,256
1,854
Off
Ekofisk
56,549
3,210
Off
Troll B/C
60,646
3,726
Off
Tyrihans
64,900
7,000
Off
Oseberg
60,500
2,500
Off
Gullfaks
61,100
2,100
Off
Buzzard
57,783
-1,248
Off
Ninian
60,860
1,450
Off
Captain
58,200
-1,900
Off
Cantarell
19,753
-92,516
Off
Boscan
10,456
-72,041
On
Table A.0.1: Geographical coordinates of representative oil fields (source: own
elaboration)
ANNEX A.2: TERMINALS
Oil field
Terminal
Name
Name
Latitude
Longitude
Gachsaran
Kharg Island
29,25
50,31
Rumaila (South)
Al Basrah Oil Terminal
29,68
48,81
West Qurna
Al Basrah Oil Terminal
29,68
48,81
Kirkuk
Ceyhan
36,86
35,94
Burgan
Mina al Ahmadi
29,06
48,15
Gwahar
Ras Tanura
26,64
50,16
Kurais
Ras Tanura
26,64
50,16
Manifa
Ras Tanura
26,64
50,16
Hassi Messaoud
Algiers
36,79
2,99
Block 17/Dalia
Dalia FPSO
-7,63
11,76
Girassol
Girassol FPSO
-7,63
11,68
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Terminal
Name
Name
Latitude
Longitude
Greater Plutonio
Greater Plutonio FPSO
-7,81
12,11
Es Sider
Es Sider
30,64
18,37
El Sharara
Zawiya
32,79
12,70
Bonga
Bonga FPSO
5,10
5,10
Forcados Yokri
Forcados Terminal
5,35
5,35
Agbada
Bonny Terminal
4,40
7,17
Caw Thorne Channel
Bonny Terminal
4,40
7,17
Escravos Beach
Escravos Terminal
5,59
5,18
Azeri-Chirag-Gunashli (ACG)
Supsa
42,02
41,77
Azeri-Chirag-Gunashli (ACG)
Ceyhan
36,86
35,94
Tengiz
Ceyhan
36,86
35,94
Tengiz
Novorossiysk
44,78
37,72
Tevlinsko-Russkinskoye
Novorossiysk, Primorsk, Ventspills
Uryevskoye
Novorossiysk, Primorsk, Ventspills
Samotlor
Novorossiysk, Primorsk, Ventspills
Vat-Yeganskoye
Novorossiysk, Primorsk, Ventspills
Povkhovskoye
Novorossiysk, Primorsk, Ventspills
Romashkino
Novorossiysk, Primorsk, Ventspills
Unvinskoye
Novorossiysk, Primorsk, Ventspills
Pamyatno-Sasovskoye
Novorossiysk, Primorsk, Ventspills
Halfdan
Fredericia
55,56
9,74
Statfjord
Statford
61,26
1,85
Ekofisk
Teeside
54,61
-1,17
Troll B/C
Mongstad
60,81
5,02
Tyrihans
Trondheim
63,44
10,35
Oseberg
Sture
60,62
4,84
Gullfaks
Mongstad
60,81
5,02
Buzzard
Hound Point
56,04
-3,31
Ninian
Sullom Voe
60,46
-1,29
Captain
FPSO
58,200
-1,900
Cantarell
Caya Arcas
20,20
-91,96
Boscan
Punta Cardon
10,37
-70,13
Table A.0.2: Geographical coordinates of representative oil field terminals
(source: own elaboration)
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ANNEX A.3 PORTS
Port
Country
Aberdeen(GBR)
United Kingdom
Agioi Theodoroi
Greece
Algeciras
Spain
Amsterdam
Netherlands
Antwerp
Belgium
Argostoli
Latitude
Longitude
57.1526
-2.11
37.916667
23.083333
36.1275
-5.453889
52.366667
4.9
51.27
4.336667
Greece
38.183333
20.483333
Asnaesvaerkets Havn
Denmark
55.655213
11.097193
Aspropyrgos
Greece
38.066667
23.583333
Augusta
Italy
37.25
15.216667
Avonmouth
United Kingdom
51.501
-2.699
Barcelona
Spain
41.383333
2.183333
Bilbao
Spain
43.256944
-2.923611
Bourgas
Bulgaria
42.495278
27.471667
Brest
France
48.39
-4.49
Brofjorden
Sweden
58.348056
11.416667
Brunsbuttel
Germany
53.896389
9.138611
Cartagena(ESP)
Spain
37.6
-0.983333
Castellon
Spain
40.166667
-0.166667
Civitavecchia
Italy
42.1
11.8
Constantza
Romania
44.173333
28.638333
Copenhagen
Denmark
55.676111
12.568333
Corunna
Spain
43.365
-8.41
Coryton
United Kingdom
51.513
0.521
Cromarty Anch.
United Kingdom
57.681628
-4.037008
Donges
France
47.3242
-2.075
Dundee
United Kingdom
56.464
-2.97
Dunkirk
France
51.0383
2.3775
Eleusis
Greece
38.033333
23.533333
Enstedvaerkets Havn
Denmark
55.021283
9.442330
Escombreras
Spain
37.6
-0.983333
Falconara
Italy
43.633333
13.4
Fawley
United Kingdom
50.828
-1.352
Finnart
United Kingdom
56.115
-4.832
Fiumicino
Italy
41.766667
12.233333
Flushing
Netherlands
51.45
3.566667
Fos
France
43.2031
5.201
Fredericia
Denmark
55.566667
9.75
Frederikshavn
Denmark
57.441111
10.539722
Gela
Italy
37.066667
14.25
Genoa
Italy
44.411111
8.932778
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Port
Country
Gothenburg
Sweden
Hamble
United Kingdom
Hamburg
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Latitude
Longitude
57.7
11.966667
50.85694
-1.32084
Germany
53.565278
10.001389
Hook of Holland
Netherlands
51.981111
4.128611
Hound Point
United Kingdom
56.036117
-3.31225
Huelva
Spain
37.25
-6.95
Hvalfjordur
Iceland
64.383333
-21.666667
Immingham
United Kingdom
53.6139
-0.2183
Isle of Grain
United Kingdom
51.46
0.73
Kalamata
Greece
37.033333
22.116667
Kali Limenes
Greece
34.916667
24.8
Kalundborg
Denmark
55.681389
11.085
Karlshamn
Sweden
56.166667
14.85
La Pallice
France
46.158333
-1.227778
La Spezia
Italy
44.1
9.816667
Le Havre
France
49.49
0.1
Leghorn
Italy
43.55
10.316667
Leixoes
Portugal
41.183
-8.7
Liverpool
United Kingdom
53.4
-2.983333
Malta Anch.
Malta
35.818
14.54
Marsaxlokk
Malta
35.841667
14.544722
Megara
Greece
38
23.333333
Midia
Romania
44°05'.1N
028°43'.1E
Milazzo
Italy
38.216667
15.233333
Milford Haven
United Kingdom
51.71418
-5.04274
Naantali
Finland
60.466667
22.033333
Nigg Terminal
United Kingdom
57.705558
-4.029685
Nynashamn
Sweden
58.9
17.95
Oxelosund
Sweden
58.666667
17.116667
Pachi
Greece
37.974443
23.362741
Petit Couronne
France
49.3864
1.0283
Piraeus
Greece
Portbury
United Kingdom
Rostock
37.95
23.633333
51.4699
-2.7163
Germany
54.083333
12.133333
Rotterdam
Netherlands
51.916667
4.5
Rouen
France
49.44
1.1
Santa Panagia
Italy
37.122640
15.216326
Sarroch
Italy
39.066667
9.016667
Savona
Italy
44.3
8.483333
Setubal
Portugal
38.533333
-8.883333
Shell Haven
United Kingdom
51.5052
0.4902
Sines
Portugal
37.93
-8.77
Skoldvik
Finland
60.311737
25.541684
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Port
Country
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Latitude
Longitude
Stenungsund
Sweden
58.083333
11.816667
Sullom Voe
United Kingdom
60.451733
-1.310805
Taranto
Italy
40.466667
17.233333
Tarragona
Spain
41.115697
1.249594
Teesport
United Kingdom
54.604
-1.158
Terneuzen
Netherlands
51.333333
3.833333
Tetney Terminal
United Kingdom
53.499933
0.000533
Thessaloniki
Greece
40.646749
22.882513
Trapani
Italy
38.016667
12.516667
Trieste
Italy
45.633333
13.8
Tyne
United Kingdom
54.989907
-1.465280
Vassiliko Bay
Cyprus
34.724084
33.310287
Vasto
Italy
42.1118
14.7082
Venice
Italy
45.4375
12.335833
Wilhelmshaven
Germany
53.516667
8.133333
Table A.0.3: Geographical coordinates of major European oil importing ports
(source: own elaboration)
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ANNEX B: MAPS
ANNEX B.1: OIL FIELDS MAPS
Figure B.1: Nigerian pipelines oil and gas fields map
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Figure B.2: Algerian pipelines, oil and gas fields map (source: Ministère de
l’Energie et des Mines)
Figure B.3: Iraq’s pipelines, oil and gas fields map (source: Platts)
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Figure B.4: Arabian oil and gas pipeline system
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Figure B.5: Libyan pipelines, and oil fields map (source: Goldman Sachs)
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ANNEX B.2: OIL PIPELINE MAPS
Figure B.6: Major Caspian oil and gas pipeline system (source: EIA)
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Figure B.7: Russian oil and gas pipeline system (source: Theodora Maps)
Figure B.8: Balkan oil and gas pipeline system (source: Theodora Maps)
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Figure B.9: Oil and gas pipeline system of Central Europe (source: Theodora
Maps)
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Figure B.10: Oil and gas pipeline system of North Africa (source: Theodora
Maps)
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Figure B.11: Oil and gas pipeline system of Middle East (source: EIA)
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ANNEX C: LITERATURE DATABASE EXTRACT
Date
Publishing Organisation
Author(s)
Document Type
Key points
1/1/2008
Greenhouse Gas Protocol
Greenhouse Gas
Protocol
Datasheet
1/1/2010
Global Gas Flaring
Reduction, A PublicPrivate Partnership
The World Bank Group,
Oil & Gas Policy
Division
Report/Study
1/1/2013
Organization of the
Petroleum Exporting
Countries (OPEC)
Organization of the
Petroleum Exporting
Countries (OPEC)
Datasheet
11/6/2013
Society of Chemical
Industry and John Wiley &
Sons, Ltd - Biofuels,
Bioprod. Bioref.
Björn Pieprzyk, Paula
Rojas Hilje and Norbert
Kortlüke
In this document, a table with the direct (except for CH4) 100-year time horizon global
warming potentials (GWP) relative to CO2 is included. This table is adapted from table
2.14 of the IPCC Fourth Assessment Report, 2007. The 4th assessment report values are
the most recent (2007), but the second assessment report values (1995) are also listed.
A technical glossary of terms was commissioned by the Oil & Gas Methodology
Workgroup1 (WG) to compile and explain how specific oil and gas terms found and/or
required in relevant CDM/JI Methodologies, are understood and applied by industry, and
how the concepts should be interpreted in the context of project activities. The document
is intended to help reduce possible misinterpretations that can lead to delay and
additional transactions costs during the formulation, validation, registration and
verification of CDM/JI projects. The glossary features industry references as appropriate,
and is meant to serve as a useful guide when suggesting improvement and/or requests
for clarification and/or revisions of the approved methodologies.
This is the 48th edition of the Annual Statistical Bulletin (ASB), one of OPEC’s principal
publications and an increasingly important source of data for the oil industry. The aim of
this report is to make available reliable and timely historical data on the global oil and gas
industry. It is a useful and frequently cited reference tool for those working in the energy
industry. OPEC’s 12 Member Countries — namely Algeria, Angola, Ecuador, the Islamic
Republic of Iran, Iraq, Kuwait, Libya, Nigeria, Qatar, Saudi Arabia, the United Arab
Emirates and Venezuela — are the central focus of the ASB. However, as in previous
editions, the ASB also provides information and statistical data about non-OPEC oil
producing countries, bringing together data on exports, imports, pipelines and shipping,
as well as the petroleum industry in general. It has collected statistical information about
exploration and production, as well as transportation and refining, and has made this
available to other energy stakeholders.
In this report, the substitution of marginal oil with biofuels is analysed. For that, the effects
that influence the substitution process in the short, mid and long term are evaluated.
OPEC, resource nationalism, and geopolitical issues are identified as important influence
factors. It is concluded that in the short term biofuels will replace mainly OPEC oil but not
the most expensive petroleum.
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Date
Publishing Organisation
Author(s)
Document Type
Key points
22/9/2013
InLCA/LCM 2003
Paul Worhach, Robert
E. Abbott
Presentation
1/1/2014
IPCC WGIII AR5
Leon Clarke and Kejun
Jiang
Report/Study
1/1/2014
IPCC WGIII AR5
Ralph Sims, Roberto
Schaeffer
Report/Study
An important component of Life Cycle Assessment (LCA) is the methodology by which
energy and emissions in multi-product production systems, such as petroleum refining,
are attributed to the production of the different products. In this presentation, an
alternative methodology called Co-Product Function Expansion (CFE) is proposed. CFE
is an incremental approach in which selected co-products and a selected set of coproduct functions are placed within the product system boundary, and the energy and
emissions for upstream stages and co-product production are accounted for in the LCA.
The downstream functions of the co-products are compared with alternative products
serving the same functions, and the net energy and emissions, as either debits or credits,
are assigned to the primary system products.
Stabilizing greenhouse gas (GHG) concentrations will require large‐scale transformations
in human societies, from the way that we produce and consume energy to how we use
the land surface. A natural question in this context is what will be the ‘transformation
pathway’ towards stabilization; that is, how do we get from here to there? The Document
is primarily motivated by three questions: What are the near‐term and future choices that
define transformation pathways, including the goal itself, the emissions pathway to the
goal, technologies used for and sectors contributing to mitigation, the nature of
international coordination, and mitigation policies? What are the key characteristics of
different transformation pathways, including the rates of emissions reduction sand
deployment of low‐carbon energy, the magnitude and timing of aggregate economic
costs, and the implications for other policy objectives such as those generally associated
with sustainable development? How will actions taken today influence the options that
might be available in the future?
Reducing global transport greenhouse gas emissions will be challenging since the
continuing growth in passenger and freight activity could outweigh all mitigation measures
unless transport emissions can be strongly decoupled from GDP growth. Direct (tank‐to‐
wheel) GHG emissions from passenger and freight transport can be reduced by: avoiding
journeys where possible, modal shift to lower‐carbon transport systems, lowering energy
intensity (MJ/passenger km or MJ/tonne km) and reducing carbon intensity of fuels. Both
short‐ and long‐term transport mitigation strategies are essential if deep greenhouse gas
emissions reduction ambitions are to be achieved. Barriers to decarbonizing transport for
all modes differ across regions, but can be overcome in part by reducing the marginal
mitigation costs (medium evidence, medium agreement). There are regional differences
in transport mitigation pathways with major opportunities to shape transport systems and
infrastructure around low‐carbon options. A range of strong and mutually‐supportive
policies will be needed for the transport sector to decarbonize and for the co‐benefits to
be exploited.
Table C.0.1: Extract from the generic literature database until the interim report delivery
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Title
Date
Publishing
Organisation
Author(s)
Document
Type
Interim Report
Content
Lifecycle stage
UK Production
Data Release
1/10/2014
Department of
Energy and
Climate Change
(DECC) - Energy
Group
Department
of Energy
and Climate
Change
(DECC) Energy
Group
Datasheet
 Oil
 Upstream
Life Cycle
Greenhouse
Gas
Perspective on
Exporting
Liquefied
Natural Gas
from the United
States
29/5/2014
United States
Department of
Energy (DOE),
National Energy
Technology
Laboratory
(NETL)
Timothy J.
Skone,
Gregory
Cooney,
Matthew
Jamieson,
James
Littlefield,
Joe Marriott
Report/Study
 Direct GHG
Emissions;
 Modelling;
 Natural Gas;
 Unconvention
al Gas




Facts 2014,
The Norwegian
Petroleum
Sector
5/5/2014
Yngvild
Tormodsgard,
Ministry of
Petroleum and
Energy
Yngvild
Tormodsgar
d, Ministry
of
Petroleum
and Energy
Report/Study
 Oil;
 Natural Gas
Comparing
GHG Intensity
of the Oil Sands
and the
Average US
Crude Oil
1/5/2014
IHS Energy
IHS Energy
Report/Study
 Direct GHG
Emissions;
 Modelling;
 Oil;
 Unconvention
al oil
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Geographical
coverage
Referenced Model
Key points
Europe
Production data regarding UK fields.
Monthly data for oil,
water, condensate and gas production are
provided for the period from July 2013 to June
2014.
Europe;
North America
A life cycle assessment of the greenhouse
gas emissions for regional coal and imported
natural gas power in Europe and Asia.
Exported LNG from the U.S.A. is compared
with regional coal for electric power
generation in Europe and Asia. Furthermore,
natural gas produced in Russia and delivered
to Europe and Asia via pipeline is also
evaluated.
 Upstream
Europe
A report on Norvegian petroleum industry. A
wide range of issues from Ekofisk, (the first
discovered Norwegian oil field) to current
industry status are analysed. Furthermore,
future challenges and strategies are also
provided.
 Upstream;
 Midstream;
 Downstream
North America
The purpose of this report is to inform the
dialogue surrounding the GHG emissions from
US crude oil supply and Canadian oil sands.
The origin of US oil supply since 2005 has
changed significantly. However, the GHG
intensity of the average crude oil consumed in
the United States did not materially change.
Common GHG intensity baselines—such as
the average crude consumed in the United
States—provide a useful reference point for
comparisons. However, they should be used
with caution. They are theoretical values to
enable comparisons, not absolute numbers.
There are simply too many crude oils
consumed in the United States to accurately
track and quantify emissions for each. The
almost 4% difference between the IHS and
DOE/NETL results indicates the possible
Upstream;
Midstream;
Downstream;
Combustion
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margin of error in estimating the GHG
emissions for the average crude oil.
The study uses a hybrid bottom-up method for
estimating the average GHG emissions for the
average US crude oil. It is followed by an
Appendix analysing the methodology, data
and calculations utilized.
Appendix to
IHS Special
Report:
Comparing
GHG Intensity
of Oil Sands to
the Average US
Crude
1/5/2014
IHS Energy
IHS Energy
Report/Study
 Direct GHG
Emissions;
 Modelling;
 Oil;
 Unconvention
al oil
 Upstream;
 Midstream;
 Downstream
North America
OPGEE
Documentation
version 1.1b
11/3/2014
California Air
Resources
Board
Hassan M.
El-Houjeiri,
Kourosh
Vafi, Scott
McNally,
Adam
Brandt
(Stanford
University),
James Duffy
(CARB)
User's
Manual
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Modelling;
 Oil;
 Unconvention
al oil
 Upstream;
 Midstream
Worldwide
An Overview of
Unconventional
Oil and Natural
Gas:
Resources and
Federal Actions
23/1/2014
Congressional
Research
Service (CRS)
Michael
Ratner,
Mary
Tiemann
Report/Study
 Policy;
 Unconvention
al oil;
 Unconvention
al Gas
 Upstream
North America
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Appendix to the referenced report including
the methodology, data and calculations
utilized.
OPGEE
Technical documentation to the Oil Production
Greenhouse gas Emissions Estimator
(OPGEE) explaining the calculations and data
sources in the model.
This report focuses on the growth in U.S. oil
and natural gas production driven primarily by
tight oil formations and shale gas formations.
It reviews as well selected federal
environmental regulatory and research
initiatives related to unconventional oil and
gas extraction.
The motive for this study has been the rapid
expansion of oil and gas extraction using
hydraulic fracturing, both in rural and more
densely populated areas. In general, this
production method has raised concerns about
its potential environmental and health impacts,
i.e. groundwater and surface water quality,
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public and private water supplies and air
quality.
Reduction of
Methane
Emissions in
The EU Natural
Gas Industry
1/1/2014
Marcogaz, Eni
S.p.A, E.ON
Ruhrgas AG
Jürgen
Vorgang
(E.ON
Ruhrgas
AG,
Germany),
Angelo Riva
(Eni S.p.A,
G&P Div.
G&P, Italy),
Alessandro
Cigni
(Marcogaz,
Belgium),
Daniel Hec
(Marcogaz,
Belgium)
Research
Paper
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Modelling;
 Natural Gas
 Midstream;
 Downstream
Europe
Upstream
emissions of
fossil fuel
feedstocks for
transport fuels
consumed in
the European
Union
30/11/2013
EC / DG CLIMA
Chris
Malins,
Sebastian
Galarza,
Anil Baral,
Drew
Kodjak
(Internationa
l Council on
Clean
Transportati
on (ICCT)),
Adam
Brandt,
Hassan ElHoujeiri
(Stanford
University),
Gary
Howorth
Report/Study
 Direct GHG
Emissions;
 Policy;
 Modelling;
 Oil
 Upstream;
 Midstream
Europe
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
In the natural gas transmission sector,
methane is released to the atmosphere. In this
paper, a methodology for evaluating methane
releases is proposed. Although the parameter
values used for calculating methane releases
vary from one transmission company to
another, a specified range for such values is
suggested. Furthermore data from seven
major western European transmission
companies are analysed. Finally suggestions
for redaction of the methane releases are
provided.
OPGEE
The report analyses the results of several
desk studies on the EU fossil fuel feedstock
market and associated empirical and modeled
data on GHG emissions. It presents a new
model for lifecycle analysis of crude oil
extraction and provides an estimate using that
model of the carbon intensity of crude oil
supplied to the European Union. The objective
is to calculate the carbon intensity (CI) for the
most important types of crude oil entering the
EU.
More specifically the study provides a
comprehensive Life Cycle Emissions analysis
using the OPGEE model for a large number of
crudes imported in Europe, using the DG
ENER list of crude imports. The analysis has
been done on oil-field basis by collecting key
data for each oil field. There can be found
detailed analyses about available data
sources (Chapter 7), as well as a
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coverage
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(Energy
Redefined),
Tim Grabiel
(Defense
Terre)
Key points
comprehensive summary of findings from
other LCA studies on crude oil (Chapter 4).
Environmental
Performance
Indicators 2012 Data
1/11/2013
International
Association of
Oil and Gas
Producers
(OGP)
OGP
Report/Study
 Direct GHG
Emissions;
 Oil;
 Unconvention
al oil
 Upstream
Worldwide
OGP has been collecting environmental data
from its member companies for the past 14
years on an annual basis. The present report
summarises information on activities related to
exploration and production (upstream) carried
out by OGP member companies in 2012. Data
coverage is relatively low – 32% of 2012 world
production – while regional coverage varies
from 96% in Europe to 8% in FSU. Overall,
data from 78 countries are represented in the
report.
Associated
Petroleum Gas
Flaring Study
for Russia,
Kazakhstan,
Turkmenistan
and Azerbaijan
1/11/2013
European Bank
for
Reconstruction
and
Development
Carbon
Limits AS
Report/Study
 Direct GHG
Emissions;
 Policy;
 Oil;
 Natural Gas
 Upstream
Former Soviet
Union
This report summarizes the findings of the
“Associated Petroleum Gas Flaring Study for
Russia, Kazakhstan, Turkmenistan and
Azerbaijan” which was initiated by the
European Bank for Reconstruction and
Development (EBRD) and co-managed by
EBRD and the Global Gas Flaring
Reduction Partnership (GGFR). The aim of
the Study has been to review and analyse
appropriate technical solutions for the use of
the associated petroleum gas (APG) and to
identify bankable projects in the four
countries covered. Flaring data from NOAA
and other sources are provided and analysed.
Independent
Assessment of
the European
Commission’s
Fuel Quality
Directive’s
“Conventional”
Default Value
9/10/2013
Natural
Resources
Canada
ICF
Consulting
Canada
Report/Study
 Direct GHG
Emissions;
 Modelling;
 Oil
 Upstream;
 Midstream;
 Downstream
Europe
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
OPGEE
Based on the new Fuel Quality Directive, this
report analyses the lifecycle GHG emissions
for diesel and petrol.
The objective of this study is two-fold:
1) analyse the methodology that has been
used in the JEC reports (JEC v3c and v4) to
determine the default conventional crude oil
gasoline and diesel GHG intensity values,
2) using that improved understanding, develop
a more accurate default GHG intensity range
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for gasoline and diesel from conventional
crude oils (using OPGEE).
Emphasis is given on data quality and
availability which is limited.
The study includes a number of MCONs
imported in the EU given in the table of
Appendix E.
Natural Gas
Information
2013
13/8/2013
IEA
IEA
Book
 Natural Gas




Upstream;
Midstream;
Downstream;
Combustion
Worldwide
A detailed reference work on gas supply and
demand covering not only the OECD
countries but also the rest of the world, this
publication contains essential information on
LNG and pipeline trade, gas reserves, storage
capacity and prices.
The main part of the book, however,
concentrates on OECD countries, showing a
detailed supply and demand balance for each
country and for the three OECD regions:
Americas, Asia-Oceania and Europe, as well
as a breakdown of gas consumption by enduser. Import and export data are reported by
source and destination.
Desk study on
indirect GHG
emissions from
Fossil Fuels
1/8/2013
DG Clima
ICF
International
Report/Study
 Indirect GHG
Emissions;
 Oil




Upstream;
Midstream;
Downstream;
Combustion
Worldwide
The overall objective of the study is to provide
an overview that enables the European
Commission to evaluate the indirect GHG
emissions from fossil fuel origin.
In the study the direct emissions are defined
as the ones emitted from the processes used
to produce, transport and combust the fuel
along the life cycle, whereas the indirect
emissions are those that are influenced or
induced by economic, geopolitical or
behavioural factors, but which are not directly
related to extraction, processing, distribution
or final combustion of the fuels.
The study identifies and evaluates six possible
sources of indirect GHG emissions from fossil
fuels: Induced land development, Military
involvement, Accidents, Marginal effect, Price
effects and Export of co-products.
It is based on a thorough literature review in
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
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the field of indirect emissions. Where possible,
estimates on the emissions are provided.
The study is a central source for analysing
and estimating indirect emission and will also
provide the basis for defining the boundaries
between direct and indirect sources in the
current project.
Oil Information
2013
23/7/2013
IEA
IEA
Datasheet
 Oil




WELL-TOTANK Report
Version 4.0
1/7/2013
JEC
Robert
EDWARDS
(JRC),
JeanFrançois
LARIVÉ
(CONCAWE
), David
RICKEARD
(CONCAWE
), Werner
WEINDORF
(LBST)
Report/Study
 Direct GHG
Emissions;
 Modelling;
 Oil;
 Unconvention
al oil
 Upstream;
 Midstream;
 Downstream
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Upstream;
Midstream;
Downstream;
Combustion
Worldwide
Europe
A comprehensive reference book on current
developments in oil supply and demand. The
first part of this publication contains key data
on world production, trade, prices and
consumption of major oil product groups, with
time series back to the early 1970s. The
second part gives a more detailed and
comprehensive picture of oil supply, demand,
trade, production and consumption by enduser for each OECD country individually and
for the OECD regions. Trade data are
reported extensively by origin and destination.
Other
This part of the study describes the process of
producing, transporting, manufacturing and
distributing a number of fuels suitable for road
transport powertrains. It covers all steps from
extracting, capturing or growing the primary
energy carrier to refuelling the vehicles with
the finished fuel.
As an energy carrier, a fuel must originate
from a form of primary energy which can be
either contained in a fossil feedstock
(hydrocarbons of fissile material) or directly
extracted from solar energy (biomass or wind
power). Generally a fuel can be produced
from a number of different primary energy
sources. In this study, we have included all
fuels and primary energy sources that appear
relevant within the timeframe considered
(which broadly speaking is the next decade)
and we have considered the issues and
established comparisons from both points of
view in order to assist the reader in answering
the questions:
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1) What are the alternative uses for a given
resource and how can it best be used?
2) What are the alternative pathways to
produce a certain fuel and which of these hold
the best prospects?
GHGenius
Model 4.03 Model
Background
and Structure Data and Data
Sources
15/6/2013
Natural
Resources
Canada
Don
O'Connor
User's
Manual
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Modelling;
 Oil;
 Natural Gas;
 Unconvention
al oil;
 Unconvention
al Gas




Upstream;
Midstream;
Downstream;
Combustion
Worldwide
BP Statistical
Review of world
energy
1/6/2013
BP
BP
Datasheet
 Oil;
 Natural Gas
 Upstream;
 Downstream;
 Combustion
Worldwide
It provides an annual opportunity to examine
the latest data, country-by-country and fuelby-fuel. This helps us discern the important
trends and assess the challenges and the
opportunities that lie before us. This edition of
the review highlights the flexibility with which
our global energy system adapts to rapid
global change.
BP Statistical
Review of
World Energy
June 2013
1/6/2013
BP
BP
Report/Study
 Oil;
 Natural Gas;
 Unconvention
al oil;
 Unconvention
al Gas
 Upstream;
 Downstream
Worldwide
Annual report providing data on oil and natural
gas reserves, prices, production and
consumption by country as well as trade
movements.
Oil and Gas
Production in
Denmark and
Subsoil Use,
2012
1/6/2013
Danish Energy
Agency (Energi
Styrelsen)
Danish
Energy
Agency
(Energi
Styrelsen)
Report/Study
 Oil;
 Natural Gas
 Upstream
Europe
A report on oil and gas production in Danish.
An overview of licences and exploration is
given. Other uses of subsoil, such as produce
salt, produce geothermal heat and store of
natural gas are mentioned. Production and
development as well as classification of
resources and economy are analysed. Health
and safety regulations by the Danish Offshore
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
GHGenius
Volume 1 of the report documents the
development of the model and provides the
user with an understanding of the primary
functions of the model. Volume 2 is focused
on the data that is used in the model, the
sources and where the data is used.
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Safety Act and Climate and environment
issues are provided. Furthermore detailed
actual data are given.
Crude Oil in
Europe:
Production,
Trade and
Refining
Outlook
1/3/2013
Wood
Mackenzie
Steve
Cooper
Presentation
 Oil




Guidance
Document Flaring
Estimates
Produced by
Satellite
Observations
1/1/2013
The World Bank
/ NOAA
Global Gas
Flaring
Reduction
Report/Study
 Direct GHG
Emissions;
 Modelling;
 Oil;
 Natural Gas
2012 Annual
Statistical
Bulletin of
Nigerian oil and
gas sector
1/1/2013
National
Nigerian
Petroleum
Corporation
Corporate
Planning &
Strategy
Division
(CP&S)
Datasheet
HANDBOOK
ON THE
ENERGY
SECTOR
Fugitive
Emissions
1/1/2013
UNFCCC
Consultative
Group of
Experts
(CGE) –
National
GHG
Inventory
Report/Study
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Upstream;
Midstream;
Downstream;
Combustion
Europe
Production, Trade and Refining Outlook of
2013 for Crude Oil in Europe by Wood
Mackenzie.
 Upstream
Worldwide
This report provides general guidelines on the
utilisation of satellite images in order to
estimate the GHG emissions due to
Associated Petroleum Gas (AGP) - flaring and
venting emissions.
 Oil;
 Natural Gas
 Upstream
Africa
The specific datasheet contains detailed
information regarding the Nigerian oil and gas
sector published by the national responsible
authority for the oil and gas sector (NNPC).
Specifically, it contains information on the
quantity of oil and produced, quantity of water
produced, number of wells, API gravity, gas to
oil ratio per oil field and operator.
Furthermore, it contains information regarding
quantities of gas produced, gas re-injected
and flared per oil field and operator.
 Direct GHG
Emissions
 Upstream
Worldwide
The aim of this handbook is to improve skills
and knowledge regarding the preparation of
greenhouse gas inventories. Specifically, this
handbook focuses on the fugitives portion of
the energy sector, in keeping with the Revised
1996 IPCC Guidelines for National
Greenhouse Gas Inventories and taking into
consideration the Good Practice Guidance
and Uncertainty Management in National
Greenhouse Gas Inventories.
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Nexen
Petroleum U.K.
Limited
Environmental
Statement 2012
1/1/2013
Nexen
Nexen
Report/Study
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Policy;
 Oil;
 Natural Gas
 Upstream
Europe
Nexen is an upstream oil and gas company.
The environmental performance of Nexen’s
UK offshore operations during 2012 are
reported. Actual data regarding atmospheric
emissions, produced water, waste generation,
production chemical usage, unplanned
releases and emissions associated with
drilling operations are analysed. Finally
environmental objectives of 2012 and 3013
are provided.
Environmental
Report, The
Environmental
Efforts of the
Oil and Gas
Industry with
Facts and
Figures, 2013
1/1/2013
Norwegian Oil
and Gas
Association
(Norsk
olje&gass)
Norwegian
Oil and Gas
Association
(Norsk
olje&gass)
Report/Study
 Direct GHG
Emissions;
 Policy;
 Oil;
 Natural Gas
 Upstream
Europe
The annual environmental report of the
Norwegian Oil and Gas Association. Data on
emissions/discharges are
recorded continuously in Environment Web, a
joint database for Norwegian Oil and Gas, Klif
and the Norwegian Petroleum Directorate
(NPD). Based on information from
Environment Web, the Norwegian Oil and Gas
environmental report provides an updated
overview of reporting in 2012 on emissions to
the air and discharges to the sea as well as
waste generation from NCS operations. The
report also contains data and research results
from long-term projects related to the marine
environment and
environmental monitoring. All fields with
production facilities on the NCS are included.
Emissions/discharges from the
construction and installation phase, maritime
support services and helicopter traffic are
excluded.
UK Operations,
Environmental
Performance,
Annual Report
2012
1/1/2013
CNR
International
CNR
International
Report/Study
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Policy;
 Oil;
 Natural Gas
 Upstream;
 Combustion
Europe
The annual environmental report of the CNR
International. CNRI operations and
environmental aspects are provided.
Significant environmental aspects of CNRI are
Carbon dioxide emissions from power
generation and flaring, oil discharged in
produced water, oil and chemical spills, solid
waste generation and disposal and chemical
use and discharge.
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
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BP in
Azerbaijan,
Sustainability
Report 2012
1/1/2013
BP Caspian
BP Caspian
Report/Study
 Direct GHG
Emissions;
 Oil;
 Natural Gas
 Upstream;
 Midstream
Former Soviet
Union
An annual report of BP in Azerbaijan for 2012.
Business performance, environmental record,
safety requirements and impact on Society
are covered. Furthermore detailed actual data
regarding performance are provided.
Oil Sands,
Greenhouse
Gases, and US
Oil Supply
1/11/2012
IHS CERA
IHS CERA
Report/Study
 Policy;
 Oil;
 Unconvention
al oil
 Upstream;
 Midstream;
 Downstream
North America
The purpose of this report is to generate a
broad set of crude oil GHG emissions data to
help inform the dialogue on GHG emissions
from US crude supply. In these types of
discussions, it is important that GHG
estimates represent average values.
It provides a meta-analysis of various GHG
emissions estimates for crude oil, with a focus
on oil sands, and concludes that differences
between the carbon intensities calculated
within each study depends on the unique
assumptions made in each case.
It is followed by an Appendix summarizing the
method and data used for the meta-analysis.
Appendixes to
IHS CERA
Special Report,
Oil Sands,
Greenhouse
Gases, and US
Oil Supply—
2012 Update
1/11/2012
IHS CERA
IHS CERA
Report/Study
 Policy;
 Oil;
 Unconvention
al oil
 Upstream;
 Midstream;
 Downstream
North America
Appendixes summarizing the method and
data used for the meta-analysis provided
within the report entitled "Oil Sands,
Greenhouse Gases, and US Oil Supply".
Life Cycle
Greenhouse
Gas Emissions
of Natural Gas
1/10/2012
CNGI
ICF
Consulting
Canada
Report/Study
 Direct GHG
Emissions;
 Natural Gas




Worldwide
The goal of this paper is to review the recent
scientific literature on life-cycle GHG
emissions from coal and conventional and
shale gas production and their use for
electricity generation.
The motivation of the study was the rapid
increase in production of shale gas in North
America in recent years, which has focused
attention on the increased role that low-priced,
abundant natural gas can play throughout the
economy.
The results show that all of the research other
than the Howarth study finds that lifecycle
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Upstream;
Midstream;
Downstream;
Combustion
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Key points
GHGs are less from gas than from coal and
that there is relatively little difference between
conventional and shale gas in life-cycle GHG
emissions.
Lifecycle
Assessment of
Crude Oil
Production
within the LOW
CARBON FUEL
STANDARD
12/7/2012
California Air
resources Board
John
Courtis,
Manager
Alternative
Fuels
Section, Jim
Duffy Air
Resources
Engineer
Alternative
Fuels
Section
Presentation
 Modelling;
 Oil
 Upstream;
 Midstream
From Ground to
Gate: A
lifecycle
assessment of
petroleum
processing
activities in the
United Kingdom
1/6/2012
NTNUTrondheim
Reyn OBorn
Report/Study
 Direct GHG
Emissions;
 Oil




EU Pathway
Study: Life
Cycle
Assessment of
Crude Oils in a
European
1/3/2012
Alberta
Petroleum
Marketing
Commission
Bill Keesom,
John
Blieszner
(Jacobs
Consultnacy
), Stefan
Unnasch
Report/Study
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Oil;
 Unconvention




EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
North America
OPGEE
Presentation within public meeting concerning
the status of the methodology under
development for determining the carbon
intensity of crude oil, according to newly
developed policy.
Updates to OPGEE and modelling methods
are being presented.
Upstream;
Midstream;
Downstream;
Combustion
Europe
GREET
The scope of the study is to introduce a
lifecycle analysis on the UK petroleum refining
sector and clarify where emissions occur
along the process chain and which fuels
cause the most pollution on a per unit basis.
The motivation of the study has been the
complexity of the petroleum process chain
and the fact that the environmental impacts
within the process chain are not always well
understood. So, it is believed that a deeper
understanding of where emissions come from
along the process chain will help policy
makers in the path towards a less carbon
intensive society. Concluding, the results of
the study show that the UK refining industry is
typically more environmentally efficient than
the average refinery in Europe according to
Eco Invent data.
Upstream;
Midstream;
Downstream;
Combustion
Europe;
North America
GREET
The goal of this Study is to evaluate the LCA
GHG for potential pathways to Europe for
producing gasoline and diesel from
representative heavy crude oils from Alberta,
Canada. Another goal was to evaluate the
LCA GHG emissions of representative crude
oils refined in representative refineries and
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Indirect Land
Use Change how good are
the models?
Author(s)
Document
Type
(Life Cycle
Associates)
28/2/2012
Biorefinery
Conference
2012
Don
O'Connor
Interim Report
Content
Lifecycle stage
Geographical
coverage
al oil
Presentation
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
 Indirect GHG
Emissions;
 Modelling
Referenced Model
Key points
thereby gain a better understanding of the
variability in LCA GHG emissions for different
pathways for producing gasoline and diesel
for the EU market.
The intent of this work is to better understand
the carbon intensity of pathways for gasoline
and diesel from individual crude oils.
Determining the carbon intensities of gasoline
and diesel from an average crude oil refined in
an average refinery risks losing some of the
granularity that helps explain the range in
carbon intensities for gasoline and diesel from
different crude oils produced in different
regions and refined in different refineries.
Representative crude oils ranging from light to
heavy crude oils from the major supply
regions were selected for the Study. Therefore
the Study does not cover all crude oils
imported in Europe, but only the ones treated
in 3 representative refineries:
FCC-Coking refinery – situated in Germany,
FCC-Visbreaking refinery – situated in France,
Hydrocracking-Visbreaking refinery – situated
in Italy.
 Downstream
Worldwide
The scope of the presentation is a discussion
of the indirect land use related to biofuels.
Further the presentation looks at the issue of
indirect impacts related to fossil fuel
production, namely the issue of the production
of co-products from fossil fuel production. The
substitution of these products will result in
emissions, and the magnitude depends of the
source of substitution.
For the purpose of the current project the
presentation provides figures on the volume of
the co-products and it refers to an European
LCA study that have looked into to issue of
taking into account alternative production of
co-products.
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Type
Interim Report
Date
Variability and
Uncertainty in
Life Cycle
Assessment
Models for
Greenhouse
Gas Emissions
from Canadian
Oil Sands
Production
14/12/2011
Environmental
Science and
Technology
Adam R.
Brandt
Research
Paper
 Direct GHG
Emissions;
 Oil;
 Unconvention
al oil




Upstream;
Midstream;
Downstream;
Combustion
North America
GHGenius;
GREET;
Other
The scope of this paper is to review factors
affecting energy consumption and GHG
emissions from oil sands extraction. For this
purpose, the author uses publicly available
data to analyse the assumptions made in the
LCA models to better understand the causes
of variability in emissions estimates.
The motive of this paper has been the raising
interest in greenhouse gas (GHG) emissions
from transportation fuels production. A
number of recent life cycle assessment (LCA)
studies have calculated GHG emissions from
oil sands extraction, upgrading, and refining
pathways, but the results from these studies
vary considerably.
Concluding, it is found that the variation in oil
sands GHG estimates is due to many causes,
e.g. scope of modelling and choice of projects
analysed, differences in assumed energy
intensities of extraction and upgrading,
differences in the fuel mix assumptions,
treatment of secondary non combustion
emissions sources, such as venting, flaring,
and fugitive emissions and treatment of
ecological emissions sources, such as landuse change-associated emissions.
Lifecycle
analysis of
Shale Gas and
Natural Gas
1/12/2011
Argonne
C.E. Clark,
J. Han, A.
Burnham,
J.B. Dunn,
M. Wang
Report/Study
 Direct GHG
Emissions;
 Modelling;
 Natural Gas;
 Unconvention
al Gas




Upstream;
Midstream;
Downstream;
Combustion
Worldwide
GREET
The scope of this study is to examine the size
of the environmental impacts of shale gas
production, by comparing it to natural gas.
The motivation has been the technologies and
practices that have enabled the recent boom
in shale gas production and the fact that shale
gas will provide the largest source of growth in
the U.S. natural gas supply through 2035.
The results of the base case scenario show
that shale gas life-cycle emissions are 6%
lower than those of conventional natural gas.
However, the range in values for shale and
conventional gas overlap, so there is a
statistical uncertainty regarding whether shale
gas emissions are indeed lower than
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Content
Lifecycle stage
Geographical
coverage
Title
Referenced Model
Key points
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Content
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coverage
Referenced Model
Key points
conventional gas emissions.
Life Cycle
Greenhouse
Gas Inventory
of Natural Gas
Extraction,
Delivery and
Electricity
Production
24/10/2011
U.S. Department
of Energy /
NETL
Timothy J.
Skone
(NETL),
James
Littlefield,
Dr. Joe
Marriott
(Booz Allen
Hamilton,
Inc.)
Report/Study
 Direct GHG
Emissions;
 Natural Gas;
 Unconvention
al Gas
 Upstream;
 Midstream;
 Downstream
North America
Upstream
greenhouse
gas (GHG)
emissions from
Canadian oil
sands as a
feedstock for
18/1/2011
Stanford
University
Adam R.
Brandt
Report/Study
 Direct GHG
Emissions;
 Oil;
 Unconvention
al oil
 Upstream;
 Midstream
Europe;
North America
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
This report expands upon previous life cycle
assessments (LCA) performed by the National
Energy Technology Laboratory (NETL) of
natural gas power generation technologies by
describing in detail the greenhouse gas
emissions due to extracting, processing and
transporting various sources of natural gas to
large end users, and the combustion of that
natural gas to produce electricity.
The results show that average coal, across a
wide range of variability, and compared
across different assumptions of climate impact
timing, has lower greenhouse gas emissions
than domestically produced natural gas when
compared as a delivered energy feedstock—
over 50 percent less than natural gas per unit
of energy.
The extraction and delivery of the gas has a
large climate impact —32 percent of U.S.
methane emissions and 3 percent of U.S.
greenhouse gases. There are significant
emissions and use of natural gas—13 percent
at the city or plant gate—even without
considering final distribution to small endusers. The vast majority of the reduction in
extracted natural gas —70 percent cradle-togate—are not emitted to the atmosphere, but
can be attributed to the use of the natural gas
as fuel for extraction and transport processes
such as compressor operations.
OPGEE
The report focuses on the following issues:
First, it provides an overview and description
of oil sands extraction, upgrading, SCO and
bitumen, non-combustion process emissions
and land use change associated emissions.
Second, it compares a variety of recent
estimates of GHG emissions from oil sands
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Type
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Content
Lifecycle stage
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coverage
European
refineries
Petroleum
industry
guidelines for
reporting
greenhouse
gas emissions
Referenced Model
Key points
and outlines the reasons for variations
between the estimates in surface mining, in
situ production, upgrading, refining and VFF.
Finally, it outlines low, high and “most likely”
estimates of GHG emissions from oil sands,
given results from previously produced
estimates, and compare these emissions to
those of conventional EU refinery feedstock.
This report focuses on the European context,
and therefore uses EU-specific emissions
factors for transport and refining of fuels.
It results that, while the highest emissions
conventional oil has higher upstream
emissions than the lowest emissions oil sands
estimate, the production-weighted emissions
profiles are significantly different.
The most important uncertainties mentioned
are treatment of cogenerated electric power,
treatment of refining and the interaction of
markets with LCA results.
1/1/2011
IPIECA, Energy
API, OGP
IPIECA,
Energy API,
OGP
Legislation
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Policy
 Upstream;
 Midstream;
 Downstream
North America
This report's objective is to fulfil the need for
industry guidance focused specifically on the
accounting and reporting of GHG emissions at
the facility through to the corporate level, for
member companies of the American
Petroleum Institute. They have been
developed as a complement to the
Compendium and the IPIECA Sustainability
Guidance
The Compendium has been written and
published in order to meet the need of the
petroleum industry for GHG accounting and
reporting guidance, specifically focused
on operations. The member companies of
the American Petroleum Institute first
published the Compendium of Greenhouse
Gas Emissions Estimation Methodologies for
the Oil and Gas Industry in April 2001, with a
third edition released in August 2009.
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Type
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Content
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coverage
Referenced Model
Key points
LCA of the
European Gas
Chain:
Challenges and
Results
1/1/2011
International Gas
Union Research
Conference
2011
A. PrieurVernat
(GDF Suez
– France),
P. Pacitto
(GDF Suez
– France),
D. Hec
(Marcogaz –
BELGIUM),
V. Bichler
(GDF Suez
– France)
Research
Paper
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Modelling;
 Natural Gas




Upstream;
Midstream;
Downstream;
Combustion
Europe
A life cycle assessment of the European gas
chain with respect to environmental
performance. Data validated by the European
Gas Industry are analysed. Additionally,
suggestions in order to improve the
environmental performance are provided.
Carbon
Intensity of
Crude Oil in
Europe
1/12/2010
ICCT
Energy
Redefined
LLC
Report/Study
 Direct GHG
Emissions;
 Modelling;
 Oil




Upstream;
Midstream;
Downstream;
Combustion
Europe
According to IEA projections in 2009, global
consumption of crude oil will increase by 27%
over the next two decades, from 83 million
barrels per day in 2009 to 105 MMbbl/d in
2030. Since extracting, transporting, and
refining crude oil on average account for
about 18% of well-to-wheels greenhouse gas
(GHG) emissions, on a global scale, that
equates to a very large amount of GHG
emissions: about 2.8 billion metric tonnes of
CO2 equivalent per year. Therefore,
improvements in the processes of extracting
and refining crude oil would mean substantial
progress toward reducing overall
transportation-sector GHG emissions.
The scope of the study is to accurately
quantify the GHG emissions from the
wellhead to the refinery output gate. For this
purpose, they have developed emission
factors for five components of
production: extraction, flaring and venting,
fugitive emissions, crude oil transport, and
refining, in order to highlight the greatest
potential opportunities for reducing or avoiding
GHG emissions from oil extraction. Based on
a life-cycle assessment of approximately 3100
oilfields in countries that supply oil to Europe,
the study develops GHG emission factors for
five elements of extraction-to-refining analysis:
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
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coverage
Referenced Model
Key points
crude oil extraction, flaring and venting,
fugitive emissions, crude oil transport, and
refining.
The focus of the study is on the European
market, as the European Commission seeks
the best way to address extraction-to-refining
emissions from petroleum fuels under the Fuel
Quality Directive.
Results of
Crude Oil
Marketing
Name Analysis
9/9/2010
California
Energy
Commission
Greenhouse
gas emissions
reporting from
the petroleum
and natural gas
industry
1/1/2010
EPA
DIRECTIVE
2009/30/EC OF
THE
EUROPEAN
PARLIAMENT
AND OF THE
COUNCIL of 23
April 2009
5/6/2009
European
Parliament
Gordon
Schremp
European
Parliament
Presentation
 Direct GHG
Emissions;
 Modelling;
 Oil
 Upstream;
 Midstream
Report/Study
 Direct GHG
Emissions;
 Oil;
 Natural Gas




Legislation
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Policy;
 Oil
 Natural Gas;
 Unconvention
al oil;
 Unconvention
al Gas
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Upstream;
Midstream;
Downstream;
Combustion
North America
OPGEE
Presentation on Marketable Crude Oil Names.
Provides critical information on available data
and information resources regarding crude oil
extraction and transport.
North America
A technical support document (TSD) that
contains legally-binding requirements. It offers
illustrative examples for complying with the
minimum requirements indicated by the
regulations, but it does not substitute for the
regulations cited in this TSD, nor is it a
regulation itself, so it does not impose legallybinding requirements on EPA or the regulated
community. The document describes the U.S.
petroleum and natural gas life cycle of raw
gas and crude oil from the wells to the delivery
of processed gas and petroleum products to
consumers. Since these segments use energy
and emit greenhouse gases (GHG), the
document provides information on the
calculation of minimum GHG emissions.
Europe
Fuel Quality Directive 2009/30/EC amending
Directive 98/70/EC as regards the
specification of petrol, diesel and gas-oil and
introducing a mechanism to monitor and
reduce greenhouse gas emissions and
amending Council Directive 1999/32/EC as
regards the specification of fuel used by inland
waterway vessels and repealing Directive
93/12/EEC. Specific attention should be given
to Article 7a.
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Document
Type
Interim Report
Content
Lifecycle stage
Geographical
coverage
Referenced Model
Key points
Life Cycle
Analysis of
GHG and Air
Pollutant
Emissions from
Renewable and
Conventional
Electricity,
Heating, and
Transport Fuel
Options in the
EU until 2030
1/6/2009
European Topic
Centre on Air
and Climate
Change
(ETC/ACC)
Uwe R.
Fritsche
(ÖkoInstitut),
Lothar
Rausch
(ÖkoInstitut)
Report/Study
 Oil;
 Natural Gas




Upstream;
Midstream;
Downstream;
Combustion
Europe
Life cycle emissions in Europe from fossil and
nuclear energies as well as from renewable
energies are identified. Furthermore,
electricity generation technologies are
compared. Future development prospects
until 2030 are also provided.
An Evaluation
of the
Extraction,
Transport and
Refining of
Imported Crude
Oils and the
Impact on Life
Cycle
Greenhouse
Gas Emissions
27/3/2009
Department of
Energy
National
Energy
Technology
Laboratory
Report/Study
 Direct GHG
Emissions;
 Modelling;
 Oil




Upstream;
Midstream;
Downstream;
Combustion
South America;
North America
The National Energy Technology Laboratory
(NETL) has analysed the full life cycle
greenhouse gas (GHG) emissions of
transportation fuels derived from domestic
crude oil and crude oil imported from specific
countries.
The study takes into account particularly the
impact of crude oil source on WTT GHG
emissions from:
1) flaring and/or venting of associated natural
gas during the crude oil extraction process,
2) alternative crude oil extraction techniques
and pre-processing requirements required for
oil sands and bitumen, (3) ocean transport
distances for delivery of crude oil and
(4) varying processing requirements within the
refinery for crude oils of different quality.
Methane
Emissions from
Natural Gas
Transport
1/3/2009
Open University
of the
Netherlands
S. Murrath
Report/Study
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Natural Gas
 Midstream;
 Downstream;
 Combustion
Worldwide
In the natural gas transport sector, methane is
released to the atmosphere. Quantify
methodologies for methane emissions on a
natural gas grid at high pressure are
analysed. Furthermore, several abatement
options to reduce the methane emissions are
studied.
Assessment of
the Direct and
Indirect GHG
Emissions
1/2/2009
New Fuels
Alliance
Life Cycle
Associates,
LLC
Report/Study
 Direct GHG
Emissions;
 Indirect GHG
 Upstream;
 Midstream;
 Downstream;
Worldwide
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
GREET
Assessment of the life cycle impact on GHG
emissions from petroleum fuels.
The estimation of the direct emissions is
heavily based on the GREET model and
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Date
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Type
Associated with
Petroleum
Fuels
Interim Report
Content
Emissions
European gas
imports: GHG
emissions from
the supply
chain
1/1/2009
Allocation of
CO2 Emissions
in Joint Product
Industries via
Linear
1/1/2007
Institut français
du pétrole (IFP)
Lifecycle stage
 Combustion
Antonio
Taglia,
Nicola Rossi
Report/Study
 Direct GHG
Emissions;
 Modelling;
 Natural Gas




A. Tehrani
Nejad M.
Report/Study
 Direct GHG
Emissions;
 Oil
 Midstream
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Geographical
coverage
Upstream;
Midstream;
Downstream;
Combustion
Referenced Model
Key points
includes the emissions from exploration,
production, flaring, refining and transportation.
Indirect emissions include emissions from:
Protection of supply, Land use and marketmediated impacts (economic impacts primarily
from price pressures) and refinery of coproducts.
The study will provide input to the current
project in regard to defining boundaries for
direct and indirect emissions and in regard to
the analysis of the indirect emissions.
Europe
The aim of this paper is to analyse from the
environmental and economical point of view
the global impact of the gas that enters into
Europe, investigating the contribution of all the
chain steps, starting from the production of the
gas until the consumption in a “combined
cycle gas turbine” (CCGT) plant for power
generation.
For this purpose, six different real cases are
studied: three regard a pipeline-based
transport and three regard LNG production,
transport through tankers and regasification.
These six real cases are compared to the
GHG emissions of a reference case: power
generated in a CCGT plant in North Africa and
imported to Europe.
The environmental impact of energy
production from gas must be evaluated from
the impact analysis of the supply chains, since
it can reach the 20% of the CO2 emissions
from gas combustion. Therefore, Europe,
which aims to cut GHG emissions, should
consider also the supply chain emissions,
given that a remarkable reduction of overall
emissions would be feasible.
Europe
The paper outlines the application of the
marginal allocation methodology to the oil
refinery LP model, to evaluate and compare
the CO2 emissions associated with different
oil products. Also, it distinguishes the
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Date
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Author(s)
Document
Type
Programming: a
Refinery
Example
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Interim Report
Content
Lifecycle stage
Geographical
coverage
Referenced Model
Key points
allocation procedures in retrospective
(accounting) and prospective (changeoriented) LCAs.
As mentioned in the report, the allocation in
joint product systems is among the most
critical issues specific to LCA and the
assumptions about the allocation procedures
influence considerably the results. In general,
allocation tools in LCA are based on linear
homogeneous and unconstrained models to
relate the environmental burdens associated
with a product system to its economic outputs.
Under particular conditions, the marginal
allocation data generated by LP can also be
applicable in retrospective LCA studies.
Contrary to the arbitrary physical
measurements (mass, volume, energy, etc.),
the allocation coefficients which emerge from
the LP model are based on realistic causal
relations between oil products and the whole
refinery system. In other words, the LP model
itself detects the real type of causality
between various inputs and outputs in the
refinery and allocates the CO2 emissions
accordingly without having to use any arbitrary
measurements.
The study uses an LP refinery model that
describes a typical European fluid catalytic
cracking refinery with predefined capacity.
The oil production level of the refinery
corresponds to the EU market structure of the
year 2000 and the model is calibrated
accordingly.
The parametric results of the
verification/calibration experiments confirmed
the capability of the IFP model to correctly
reproduce the logical evolution of the product
mix. The study concludes that the allocated
CO2 emissions that are calculated are not
fixed but change to reflect changes in the
system parameters, such as the evolution of
oil products demand and recommends to
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coverage
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Key points
perform a parametric analysis to fully compare
the evolution of the CO2 allocations of various
oil products.
Life Cycle
Assessment of
the European
Natural Gas
Chain, A
Eurogas–
Marcogaz
Study
1/1/2007
Eurogas–
Marcogaz
Marion
Papadopoul
o (GDF
SUEZ),
Salam
Kaddouh
(GDF
SUEZ),
Alessandro
Cigni
(Marcogaz),
Dirk
Gullentops
(Synergrid),
Stefania
Serina
(Snam Rete
Gas),
Juergen
Vorgang
(EONRuhrgas),
Tjerk
Veenstra
(Gasunie),
François
Dupin
(DVGW)
Report/Study
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Natural Gas




Fugitive
emissions
1/1/2006
IPCC
John N.
Carras
(Coal
Mining) et.
al., David
Picard (Oil
and Natural
Gas) et. al.
Research
Paper
 Direct GHG
Emissions;
 Oil;
 Natural Gas
 Upstream;
 Midstream;
 Downstream
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Upstream;
Midstream;
Downstream;
Combustion
Europe
A life cycle assessment of the European
Natural Gas Chain. Data for heat
and electricity production in Europe in 2004
are collected. Furthermore impact assessment
results and sensitivity analyses are provided.
It is concluded that transmission distance
affect the emissions significantly. Priorities to
improve the natural gas chain environmental
performances are suggested.
Worldwide
As part of the "2006 IPCC Guidelines for
National Greenhouse Gas Inventories Volume 4, Energy", the paper provides
specific recommendations for improvements
of the IPCC methodology for oil and gas
systems. Furthermore, it identifies relevant
new emission factors and methodological
advancements made since the last update of
the IPCC Guidelines.
The paper also provides a summary of the
Page 268
Study on actual GHG data for diesel, petrol, kerosene and natural gas
Title
Date
Publishing
Organisation
Author(s)
Document
Type
Interim Report
Content
Lifecycle stage
Geographical
coverage
Referenced Model
Key points
major oil and gas producers, a summary of
useful conversion factors for various common
oil and gas statistics and presents typical
compositions of processed natural gas and
liquefied petroleum gas.
Summarizing, an opportunity has been
provided to improve and build upon the
existing IPCC methodology and to establish
clearer directions on how to apply the IPCC
Guidelines for the oil and gas sector (Chapter
4.2).
The Natural
Gas Chain,
Toward a
Global Life
Cycle
Assessment
1/1/2006
CE Solutions for
environment,
economy and
technology
M.N.
Sevenster,
H.J.
Croezen
Report/Study
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Natural Gas




Upstream;
Midstream;
Downstream;
Combustion
Flaring &
venting in the
oil & gas
exploration &
production
industry
1/1/2000
OGP
John
Kearns, Kit
Armstrong,
Les Shirvill,
Emmanuel
Garland,
Carlos
Simon,
Jennifer
Monopolis
Report/Study
 Direct GHG
Emissions;
 Indirect GHG
Emissions;
 Oil;
 Natural Gas
 Upstream
Worldwide
A life cycle analysis of the entire gas chain
related to the costs and environmental impact
of natural gas. As opposed to venting and
flaring, fugitive emissions can be reduced
significantly. For the study high quality lifecycle data are used.
Worldwide
The option to release gas to the atmosphere
by flaring and venting is an essential practice
in oil and gas production, primarily for safety
reasons. The essential point is that no single
approach to dealing with associated gas will
be appropriate for all projects or locations.
Industry needs to be able to choose from
among a variety of creative and common
sense approaches to address flaring and
venting concerns in specific operations. To
achieve this, governments need to provide an
energy policy framework which will encourage
and allow companies to select from among
very different approaches in order to achieve
the best practicable outcome in particular
circumstances. The specific report discusses
various aspects of venting and flaring.
Table C.0.2: Extract from the specific literature database until the interim report delivery
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Page 269
Study on actual GHG data for diesel, petrol, kerosene and natural gas
Interim Report
ANNEX D: LETTER TEMPLATE FOR OIL AND GAS
DATA REQUEST
EXERGIA S.A. – E3M-Lab – COWI A/S, Members of COWI Consortium
Page 270
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