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Technical Guidelines: Common terms, definitions and units used in GEA

ANNEX II

Technical Guidelines: Common terms, defi nitions and units used in GEA Annex II

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This document provides technical guidelines for common terms, defini-tions, and units used in various chapters of the Global Energy Assessment (GEA). Additionally, it covers the proposed spatial resolution (definition of regional aggregates), base year values, units and definition of energy, and sectorial definitions.

Definition and aggregation of GEA Regions

Three different levels of regional aggregations are used in GEA, each of which serves for different purposes and levels of analysis.

1. 5 regions : This aggregation is the common, consistent denomin-ator across the different models proposed to be used in GEA. Thus, it represents the minimum level of spatial disaggregation for all analyt-ical input/output data within GEA that involved modeling work. For instance, data for the GEA pathways are available systematically for the 5 GEA regions only. This is the highest (i.e., minimum) level of spatial disaggregation across all GEA chapters.

2. 11 Regions: This is the spatial resolution available for all IIASA mod-els used in GEA, which provided the backbone especially for the GEA scenario work for developing the pathways. Input data used in GEA modeling work (e.g., resource potentials, present energy use patterns, technology characteristics that are regionally different, etc.) have been provided at least at the level of these 11 world regions. The 11 regional

aggregations represent just an approximate denominator across all models used within GEA. Data for 11 regions are available for specific scenarios and for a limited set of models only. The results of the GEA pathways are documented in detail at the interactive web-based GEA scenario database hosted by IIASA: www.iiasa.ac.at/web-apps/ene/geadb.

Figure 1 | Minimum GEA regional detail (5 regions).

Table 1 | 5 Regions.

Regional acronyms Regional definition

OECD90 UNFCCC Annex I countries

REF Eastern Europe and Former Soviet Union

ASIA Asia excl. OECD90 countries

MAF Middle East and Africa

LAC Latin America and the Caribbean

OECD90 = Includes the OECD90 countries, therefore encompassing the countries included below (11 region) in the regions WEU, NAM and PAO.

REF = Countries undergoing economic reform, i.e. countries listed under the regions EEU and FSU below (11 regions).

ASIA = The countries included in the regions SAS, PAS and CPA are aggregated into this region.

MAF = This region includes the Middle East and African countries that make up the regions AFR and MEA above.

LAC = This region includes the Latin American countries that make up the LAC region above.

Technical Guidelines: Common terms, definitions and units used in GEA

Annex II Technical Guidelines: Common terms, defi nitions and units used in GEA

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Figure 3 | Detailed GEA Regions (18 regions).

Figure 2 | GEA Scenario Model Regions (11 regions).

3. 18 regions : This is the minimum spatial disaggregation needed to reconcile the regional definition differences across models used within GEA (e.g., including IMAGE models). This regional definition was used for all salient analytical work within GEA, e.g., for describing base year patterns of energy end-use and supply, energy access, resource poten-tials (fossil and renewable), technology deployment, policy implementa-tion, etc. When available data did not permit the representation of all 18 regions, the 11 regions defined above was used, or alternatively at least the 5 GEA Regions. Base year (2005) proportional scaling techniques are

suggested in cases where only 5-regional input data are available but finer regional detail is required.

Base Year: 2005

A common GEA base year is 2005. This is the year for which most critical energy statistics were available in time for GEA’s analytical work. More recent data where provided wherever available.


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USA United States of America

CAN Canada

WEU Western Europe, incl. Turkey

EEU Central and Eastern Europe

FSU Former Soviet Union

NAF Northern Africa

EAF Eastern Africa

WCA Western and Central Africa

SAF Southern Africa

MEE Middle East

CHN China

OEA Other East Asia

IND India

OSA Other South Asia

JPN Japan

PAS Other Pacifi c Asia

OCN Australia, New Zealand, and other Oceania


USA = Unites States (Guam, Puerto Rico, United States of America, British Virgin Islands)

CAN = Canada

WEU = Western Europe (Andorra, Austria, Belgium, Cyprus, Denmark, Finland, France, Germany, Greece, Greenland, Holy See, Iceland, Ireland, Italy, Liechtenstein, Luxembourg, Malta, Monaco, Netherlands, Norway, Portugal, San Marino, Spain, Sweden, Switzerland, Turkey, United Kingdom)

EEU = Central and Eastern Europe (Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, The former Yugoslav Rep. of Macedonia, Hungary, Latvia, Lithuania, Montenegro, Poland, Romania, Serbia, Slovak Republic, Slovenia)

FSU = Newly independent states of the former Soviet Union (Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Republic of Moldova, Russian Federation, Tajikistan, Turkmenistan, Ukraine, Uzbekistan)

NAF = North Africa (Algeria, Egypt (Arab Republic), Libya/SPLAJ, Morocco, Sudan, Tunisia)

EAF = Eastern Africa (Burundi, Eritrea, Ethiopia, Kenya, Madagascar, Mauritius, Seychelles, Somalia, Uganda)

WCA = Western and Central Africa (Benin, Burkina Faso, Cameroon, Cape Verde, Central African Republic, Chad, Comoros, Cote d’Ivoire, Congo (DR), Djibouti, Equatorial Guinea, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, Sao Tome and Principe, Senegal, Sierra Leone, Togo)

SAF = Southern Africa (Angola, Botswana, Burundi, Malawi, Mozambique, Namibia, Reunion, Rwanda, Saint Helena, South Africa, Swaziland, Tanzania, Zambia, Zimbabwe)

MEE = Middle East (Bahrain, Iraq, Iran (Islamic Republic), Israel, Jordan, Kuwait, Lebanon, Occupied Palastine Territory, Oman, Qatar, Saudi Arabia, Syria (Arab Republic), United Arab Emirates, Western Sahara, Yemen)

CHN = China (incl. Hong Kong and Macao)

OEA = Other East Asia (Cambodia, Korea (DPR), Laos (PDR), Mongolia, Viet Nam)



NAM North America

WEU Western Europe

PAO Pacifi c OECD

EEU Central and Eastern Europe

FSU Former Soviet Union

CPA Centrally Planned Asia and China

SAS South Asia

PAS Other Pacifi c Asia

MEA Middle East and North Africa


AFR Sub-Saharan Africa

NAM = North America (Canada, Guam, Puerto Rico, United States of America, British Virgin Islands)

WEU = Western Europe (Andorra, Austria, Belgium, Cyprus, Denmark, Finland, France, Germany, Greece, Greenland, Holy See, Iceland, Ireland, Italy, Liechtenstein, Luxembourg, Malta, Monaco, Netherlands, Norway, Portugal, San Marino, Spain, Sweden, Switzerland, Turkey, United Kingdom)

PAO = Pacifi c OECD (Australia, Japan, New Zealand)

EEU = Central and Eastern Europe (Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, The former Yugoslav Rep. of Macedonia, Hungary, Latvia, Lithuania, Montenegro, Poland, Romania, Serbia, Slovak Republic, Slovenia)

FSU = Newly independent states of the former Soviet Union (Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Republic of Moldova, Russian Federation, Tajikistan, Turkmenistan, Ukraine, Uzbekistan)

CPA = Centrally planned Asia and China (Cambodia, China (incl. Hong Kong and Macao), Korea (DPR), Laos (PDR), Mongolia, Viet Nam)

SAS = South Asia (Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, Sri Lanka)

PAS = Other Pacifi c Asia (American Samoa, Brunei Darussalam, Fiji, French Polynesia, Kiribati, Indonesia, Malaysia, Marshall Islands, Micronesia, Myanmar, Nauru, New Caledonia, Palau, Papua, New Guinea, Philippines, Republic of Korea, Samoa, Singapore, Solomon Islands, Taiwan (China), Thailand, Timor-Leste, Tonga, Tuvalu, Vanuatu)

MEA = Middle East and North Africa (Algeria, Bahrain, Egypt (Arab Republic), Iraq, Iran (Islamic Republic), Israel, Jordan, Kuwait, Lebanon, Libya/SPLAJ, Morocco, Occupied Palestine Territory, Oman, Qatar, Saudi Arabia, South Sudan, Syria (Arab Republic), Tunisia, United Arab Emirates, Western Sahara, Yemen)

LAC = Latin America and the Caribbean (Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Bermuda, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Miartinique, Mexico, Netherlands Antilles, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Santa Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela)

AFR = Sub-Saharan Africa (Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Comoros, Cote d’Ivoire, Congo (DR), Djibouti, Equatorial Guinea, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mozambique, Namibia, Niger, Nigeria, Reunion, Rwanda, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, Saint Helena, Swaziland, Tanzania, Togo, Uganda, Zambia, Zimbabwe)


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GDP at local currency ( 2005)GDP-PPP in nternation $

tt=( == 2005)

The relevant statistics are available from the World Development Indicators (World Bank, 2007).

Discount Rate

The discount rate represents the annual rate at which the effects of future events are reduced so as to be comparable to the effect of pre-sent events. Assumptions in regard to the discount rate adopted have important implications when considering medium- to long-term sce-narios. However, there is no rate universally accepted since it is laden with value judgment. For practical reasons, GEA adopted a uniform rate of 5% throughout. Other rates are used in specific cases (e.g. from the literature) whenever possible with a clear reference to the rate used is made in such instances.

Energy Flows (Joules)

Both final and primary energy use levels are reported systematically in GEA using SI units (i.e., Joules or multiples thereof, and to allow for additional units, e.g., kWh if so desired, but always keeping the Joules common denominator). Often alternative units from original sources in the literature are shown in addition to the SI units. For the sectorial end-use chapters, only final energy is reported to avoid the risk of double counting.

Table 5 | Units based on SI.

Physical quantity Unit Symbol

Length meter m

Mass kilogram kg

Time second s

Thermodynamic temperature Kelvin K

Energy Joule J

Power Watt W

Temperature Degree Celsius ºC

Economic data are expressed in 2005 US$. GDP at constant (2005) prices in US$ was calculated using the following equations:

price in national currencyGDP

i ( )t = at curreaa nt priceGDP deflator

GDP deflator

GD

i

irr

irr

( )t( )t

( )2005

P at constant (2005)PPprice in US$

GDP in con

i ( )t =

stantss (2005)price in national currency (t)

XRATEi ( )2005

Where, i = country indicator, t = year indicator, XRATE i (2005) = annual average market exchange rate in 2005 [Local currency / US$].

For example, 272 [billion 2007 Euro] GDP in Austria can be converted in 326 [billion 2005 US$] as follows:

262 [2005 Euro]272 [2007 Euro]

112.93 [GDP deflator (2007)=

]]108.51 [GDP deflator (2005)]

⎛⎝⎜⎛⎛⎝⎝

⎞⎠⎟⎞⎞⎠⎠

326 [2005 US$]262 [2005 Euro]

0 803 [XRATE (2005)]=

( )0.803 [XRATE (2005)]

All relevant data series for each country is from the World Economic Outlook (WEO) database by IMF at: www.imf.org/external/data.htm.

Depending on the specific context, economic indicators were presented in purchasing power parity (PPP) or market exchange rates (MER). In either case, the choice of PPP or MER should be clearly stated in the text and figures. The equations above are given for market exchange rates (XRATE). For using PPPs, above XRATE needs to be replaced by the following term:

Table 4 | Sample XRATE for major currencies.

Local Currency XRATE [Local Currency / US$] in 2005

Euro 0.803

British Pound 0.549

Japanese Yen 108.9

Chinese Yuan 8.195

Canadian Dollar 1.211

Australian Dollar 1.309

IND = India

OSA = Other South Asia (Afghanistan, Bangladesh, Bhutan, Maldives, Nepal, Pakistan, Sri Lanka)

JPN = Japan

OCN = Oceania (Australia, New Zealand)

PAS = Other Pacifi c Asia (American Samoa, Brunei Darussalam, Fiji, French Polynesia, Gilbert-Kiribati, Indonesia, Malaysia, Marshall Islands, Micronesia, Myanmar, Nauru, New Caledonia, Palau, Papua, New Guinea, Philippines, Republic of Korea, Singapore, Solomon Islands, Taiwan (China), Thailand, Timor-Leste, Tonga, Tuvalu, Vanuatu, Samoa)

LAC = Latin America and the Caribbean (Antigua and Barbuda, Argentina, Bahamas, Barbados, Belize, Bermuda, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominica, Dominican Republic, Ecuador, El Salvador, French Guiana, Grenada, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Netherlands Antilles, Nicaragua, Panama, Paraguay, Peru, Saint Kitts and Nevis, Santa Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Uruguay, Venezuela)

Table 3 | (cont.)


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Table 6 | Selected SI prefix.

Prefix Symbol 10 n

exa- E 10 18

peta P 10 15

tera T 10 12

giga G 10 9

mega M 10 6

kilo k 10 3

hector h 10 2

deca da 10

- - 10 0

deci d 10– 1

centi c 10– 2

milli m 10– 3

micro μ 10– 6

nano n 10– 9

pico p 10– 12

femto f 10– 15

Accounting of Primary Energy

A consistent methodology was used for converting non-combustible and non-fossil energy (e.g., renewable and nuclear energy for electri-city generation) to primary energy equivalent across the assessment. A widely accepted method for the accounting of primary energy from these sources does not exist. Studies in the past have either used the substitution equivalent method, assuming specific efficiencies for renewable sources, or they have applied the direct equivalent method, which accounts the energy output (e.g., electricity) of above energy sources as their primary energy. The SRES (IPCC, 2000 ) have used the direct equivalent method, while e.g., Nakicenovic et al. ( 1998 ) and the IPCC ( 2007 ) have applied uniform conversion efficiencies across differ-ent sources (38.6% and 33%, respectively). Other assessments, such as the World Energy Assessment (UNDP, 2004 ) or the World Energy Outlook (IEA, 2007a ), combine both methods, and assume different conversion factors for different conversion technologies (in the WEA, for instance, nuclear: 3, hydro, wind and solar: 1, geothermal: 10).

It was decided to keep the accounting methodology transparent and as simple as possible in GEA given that a widely accepted and consistent

method across different studies does not exist. As a guide for the selec-tion of the conversion efficiency, a global average efficiency of electri-city and heat generation for the year 2005 was used. This corresponds to an average efficiency of 35% for electricity generation, and 85% for heat generation (IEA, 2007b ). For example, 1[EJ] of electricity generated by wind or nuclear at the secondary energy level is accounted as 2.86 [EJ] (i.e., 1/0.35) at the primary energy level. Likewise, 1[EJ] of heat gen-erated (and used as heat) by solar or geothermal is accounted as 1.17 [EJ] at the primary energy level (i.e., 1/0.85). See Chapter 1 for further discussion of primary energy accounting methods.

Accounting of Heating Values

To maintain clarity and consistency throughout the report, the heating value of a substance, i.e., the amount of heat released during combus-tion of a specified amount, is expressed in J/kg.

Heating values are clearly defined in the text as either HHV (Higher Heating Value) or LHV (Lower Heating Value). It is assumed that heating values are given as LHV unless explicitly noted in the text as HHV. The difference is that HHV includes the energy of condensation of the water vapor contained in the combustion products.

Sectorial Definitions

The reporting and analysis within GEA’s sectorial chapters adheres strictly to the principle of mutual exclusiveness.

Therefore, efficiency improvement (or carbon reduction) potentials for end-use sectors (e.g., industry) are always strictly separated from cor-responding “upstream” energy systems/sectors (e.g., electricity gen-eration). For example, emissions reductions (e.g., from the electricity generation sector) at the supply side need to be discussed/accounted in the “upstream” GEA chapter, while the end-use demand chapters should report emission/energy reduction potentials due to fuel substitu-tion and energy conservation in that end-use sector only. Thus, sectorial assessments were not “inflated” by accounting for (often unrelated) “upstream” energy systems changes that should be reported separ-ately. The GEA energy modeling framework enabled a rigorous and con-sistent accounting across sectors and the impacts of policy measures at the sector level.


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References

IEA , 2007a : World Energy Outlook 2007: China and India Insights . International

Energy Agency (IEA) , Paris .

IEA, 2007b : Energy Balances, 2007 Edition . International Energy Agency (IEA) , Paris .

IPCC , 2000 : Emissions Scenarios . Special Report of Working Group III of the

International Panel on Climate Change (IPCC), Cambridge University Press ,

Cambridge .

IPCC, 2007 : Fourth Assessment Report: Climate Change 2007 . International Panel on

Climate Change (IPCC), Cambridge University Press , Cambridge .

Nakicenovic , N. , A. Grubler and A. McDonald (eds.), 1998 : Global Energy

Perspectives . International Institute for Applied System Analysis (IIASA), World

Energy Council .

UNDP , 2004 : World Energy Assessment: 2004 Update . United Nations Development

Programme (UNDP), United Nations Department of Economic and Social Affairs

(UNDESA), World Energy Council .

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