Low Carbon Society Scenario Toward 2050

INDONESIA
Energy Sector

NIES

October, 2010
Institut Teknologi Bandung (ITB) - Indonesia
Institute for Global Environmental Strategies (IGES) - Japan
Kyoto University - Japan
National Institute for Environmental Studies (NIES) - Japan
Mizuho Information & Research Institute - Japan

Authors
Dr. Retno Gumilang Dewi
ITB - Indonesia
Dr. Takuro Kobashi
IGES - Japan
Prof. Dr. Yuzuru Matsuoka
Dr. Kei Gomi
Kyoto University - Japan
Dr. Tomoki Ehara
Mizuho - Japan
Dr. Mikiko Kainuma
Dr. Junichiro Fujino
NIES - Japan

Preface
This report presents the results of an academic research in developing option of roadmaps ofenergy sector toward low carbon society (LCS) of Indonesia in 2050, which is carried out as anextension activity of the Asia Pacific Integrated Model (AIM) Workshop 2009 “Designing AsianScenarios Towards Low Carbon Society” held by NIES in August 2009 in Japan. The academic
contributors of the roadmap development are Institut Teknologi Bandung (Indonesia), IGES
(Japan), Kyoto University (Japan), NIES (Japan), and Mizuho Information and Research Institute(Japan).
The objective of this research is to obtain future visions and scenarios for achieving the goals
of LCS in Indonesia, particularly within the context of energy sector. The energy sector covers
supply side and demand side (industry, transportation, residential, and commercial sectors). The
report provides an overview of scenarios of visions of Indonesian LCS in energy sector and related actions needed to achieve the LCS visions. The scenario of visions includes socio-economic
development paths and the associated emissions. The discussion of actions to achieve LCS visions covers technology and policy options. The tool used in this research is ExSS (Extended
Snap Shot) using GAMS (General Algebraic Modeling System) 23.3 supported by various technical, economic, and social parameters.
The report is prepared by Retno G Dewi (Institut Teknologi Bandung – Indonesia), Takuro Kobashi (IGES – Japan), Yuzuru Matsuoka and Kei Gomi (Kyoto University – Japan), Tomoki
Ehara (Mizuho Information and Research Institute – Japan), Mikiko Kainuma and Junichi Fujino(NIES – Japan). We hope that the research results presented in this report could be used as areference in further discussion on LCS in Indonesia. We thank the following individuals for theirinvaluable contributions in this research, i.e. Farida Z and M. Saleh Abdurrahman (Ministry of Energy and Mineral Resources), Elly A Sinaga (Ministry of Transportation), Rizaldi Boer (Institute ofAgriculture Bogor – Indonesia), Ucok Siagian and M. Rozie (Institut Teknologi Bandung – Indonesia).
Bandung, November, 2010
Dr. Retno Gumilang DewiiAbbreviations
AIM

Asia Pacific Integrated Model

BAU

Business as Usual

BPS

Biro Pusat Statistik (National Statistical Bureau)

CCS

Carbon Capture and Storage

CM1

Counter Measure 1

CM2

Counter Measure 2

CNG

Compressed Natural Gas

ExSS

Extended Snap ShotGAMS

General Algebraic Modeling System

GHG

Green House Gas Emissions

GOI

Government of Indonesia

IGCC

Integrated Gasification Combined Cycle

IGES

Institute for Global Environmental Strategies

LPG

Liquefied Petroleum Gas

LCS

Loc Carbon Society

MMBOE

Million Barrels of Oil Equivalent

MEMR

Ministry of Energy and Mineral Resources

NIES

National Institute for Environmental Studies

PLN

National Electric Utility

PUSDATIN

Pusat Data dan Informasi (Center for Data and Information) - Ministry of Energy
and Mineral Resources

RUPTL PLN

Rencana Umum Pengembangan Tenaga Listrik (General Plan of The Development of Electric Power)Toe

Ton oil equivalent

Rp.

Rupiahii

Table of Contents
pagei

Preface
Abbreviationii

Table of Contentsiii

Executive Summaryiv

Background1

Socio-economic Scenario

3

GHG Emissions and Reductions

6

Five Actions Towards LCS

9

Research Methodology

15

Statistical Data Collection and Estimation

17

iii

Executive Summary
Low Carbon Society (LCS) is relatively new concept in Indonesia. Currently, there is no official document containing roadmaps to achieve LCS target.
However, there are several government initiatives thatare in line with and supportive to the LCS concept.
This report presents the results of an academic research assessing scenarios of LCS visions 2050 inIndonesia especially in energy sector and associatedactions and policies to achieve the LCS visions.

of the BAU but more efficient and less carbon energy
systems. In addition, the scenario assumes that Indonesia is to reduce significant emission to comply withworld‟s LCS target (0.5 ton-C per capita) in 2050. In
this scenario, the society is depicted as more active,
quick changing, and technology oriented. This scenario is regarded as high development path.

Three scenarios are developed to envision Indonesian development paths related to LCS including socioeconomic, energy, and associated carbon emissions.
The first scenario is designated as business as usual(BAU) scenario, which assumes that the current development trend and society orientation will continue until
2050. What is meant by orientation is peoples‟ lifestyles and activities that has implication to the generation of CO2 emissions.

₋BAU, CO2 emissions level is projected to increase
substantially from 81 Mton-C in 2005 to 1184 MtonC in 2050 (14.5 times).

₋CM1, CO2 emissions is projected to become 617 M
ton-C (7.6 times higher than 2005) or it is 48%
lower than the BAU.

₋

CM2: CO2 emissions would become 183 Mton-C(85% less than BAU) despite higher economic size.

Indonesia‟s future energy and associated emissions
projections (Table 1, Figure 1, 2) can be summarized:

It should be noted that increases of energy demandin freight transport is significant because growth infreight transport is correlated directly with industrial
export and commercial growths. Meanwhile the industrial and commercial sectors are assumed to grow significantly. Commercial sector also covers apartmentsthat is expected to become a trend in Indonesia.

The second scenario is designated as Countermeasure 1 (CM1), which assumes that economic development will be the same as BAU but the society ismore efficient in energy utilizations compared to the
BAU. The society is depicted as calmer, slower, andnature oriented. This scenario is regarded as moderate development path.

There are several actions considered to achieve LCS
target in reducing CO2 emission, which are grouped
into 5 Actions:

The third scenario is designated as Countermeasures 2 (CM2), which assumes that Indonesian economy will grow at much higher rate compared to those

Table 1. Estimation result of scenario quantification for base year (2005) and target year (2050)
Energy Emission Parameter
Energy Demand, ktoe
Passenger Transport
Freight Transport
Residential
Industry
Commercial
Total
Energy demand per capita, toe
Energy intensity, toe/million rupiah
CO2 Emissions
Total, million ton-C*
Per capita, ton-C
Total, million ton-CO2
Per capita, ton-CO2
Annual GDP Growth rate
Annual energy demand growth rate
Energy elasticity

2005
Base

2050
CM1

BaU

CM2

17,7986,562
42,832
39,224
3,704
110,1200.50
61.6

41,406
126,510
69,761
569,325
111,952
918,953
2.81
24.8

12,54345,62338,710471,039
68,039635,954
1.95
17.2

9,244
42,056
66,971
543,266
129,068
790,605
2.42
11.6

81
0.37
299
1.4
-

1,184
3.62
4,341
13.3
6.9%
4.8%
0.70

617
1.89
2,263
6.9
6.9%
4.0%
0.57

183
0.56
670
2.0
8.3%
4.5%
0.54

iv

(1) Introducing Clean Energy: utilization of renewable and less carbon emitting energy types andtechnology in residential/commercial sector;(2) Low Carbon Lifestyle: efficiency improvement
through appliances technology and society behavior in residential/commercial sector;(3) Low Carbon Electricity: more renewable energy,
efficient power generation (pulverized to subcritical, supercritical, and integrated gasification
combined cycle (IGCC) equipped with carbon capture and storage (CCS), and decreasing losses in
T&D of electricity grids;(4) Low Carbon Fuels in Industry: energy shift(toward renewable and less carbon emitting fuels),
efficiency improvement of industrial processes,
equipments, and appliances;(5) Sustainable transport: transport modal shift (moremass rapid transport utilization), fuel shift (to renewable and less carbon emitting fuels), reducing
trip generation and trip distance (improvement of
infrastructure, telecommunication, and information
access), traffic management, efficiency improvement of vehicles.

ures to support the implementations of these actions,i.e.:(1) Increasing share of new/renewable energy andless carbon emitting fuels (include less carbon
emitting technology) in energy supply mix to support implementation of Presidential Regulation
5/2006. On-going programs considered to meetenergy supply mix target are power generationcrash program I and II (which include clean coaland geothermal), kerosene to LPG, mandatory
biofuel in power plant, transportation, industry(MEMR 32/2008) ;(2) Increasing share of new/renewable (hydro, geothermal) and oil switch to natural gas as stated in
the National Plan of Electricity Development(RUPTL) PLN 2008 - 2018;(3) Regulations that lead to the formulation of national
master plan on energy efficiency;(4) Policies to support MRT (mass rapid transit) development, diversification of fuels (CNG/LPG, biofuel,electricity) in transportation, and emissions monitoring and control of local emission and combustion efficiency that has implication to the CO2 emissions.

There are numerous energy-climate policy initiatives, regulations, and actions in energy sector that
could result in CO2 emission reduction. The latest policy initiative is non-binding emission reduction target of
26% lower than baseline in 2020 using domestic
budget and further increased to 41% with international
support. To implement non-binding commitment, GOI
prepares National Actions Plan 2010 -2020 to Reduce
CO2 Emissions. In addition to the policy initiatives,
most of the actions above will still need policy meas1,400

14

Passenger transport

13.3

Freight transport

1,200

Industry

800
600
400
200

Per capita emissions (ton-CO2 )Commercial

1,000
million ton-C

12

Residential

02005 Base

2050 BAU

2050 CM1

10
8

6.9

6
4

2
0

2005 Base

2050 CM2

Figure 1. CO2 emission by energy demand sector

2.0

1.4

2050 BAU

2050 CM1

2050 CM2

Figure 2. CO2 emission per capitav

Background
Geographical Features

Indonesian GHG EmissionsoIndonesia is located between 6 08‟ north latitude
and 11o15‟ south latitude, from 94o45‟ to 141o05‟ east
longitude. It is an archipelago with 5 big islands(Sumatera, Java, Kalimantan, Sulawesi, Papua) and13.7 thousand small islands. Among the small islands,
56% are nameless and 7% are inhabited. Indonesia
has 7.9 million-sq.km maritime area (81% total area,
1.86 million-sq. km land area, 81,000 km coastline,
0.220 million-sq.km arable land, 40% wet (rice fields),
40% dry, 15% shifting cultivation.

In Indonesia, the key sources of GHG emissions
are Land Use, Land Use Change and Forestry(LULUCF) and peat fires, combustion of fuels and fugitives in energy sector, industrial processes, waste sector, agriculture sector. In 2005, the total CO2 emissionsof these sectors reached almost 1.99 Gton-CO2e (0.55
Gton-C). Out of these emission, around 56% is from
LUCF and peat fires and 18.5% is from energy sector.
The rest are accounted by the previous mentioned
remaining sectors.

The country has two seasons: dry and rainy seasons with 3 rainfall peak patterns, namely monsoon(December), local (July-August), equatorial (Marchand October). Based on location , the pattern can befurther categorized into two groups indicated by aclear distinction between dry and wet throughout theyear, i.e. east part (East Nusa Tenggara) with drier
and longer period and west part (Java, South Sumatra, South Sulawesi). In general, rainfall variation islarger in dry season (April-September) compared tothose in wet (Oct-March).

Existing National Plan on Energy Sector and Climate Change Related Actions
In line with the world‟s commitment on climatechange, Government of Indonesia (GOI) announced
non-binding emission reduction target of 26% lower
intensity than the baseline of 2020 using domestic
budget. With international support, the reduction could
be further increased to 41%. To meet this target, GOI
is preparing National Action Plan on GHG Reduction(2010-2020). There are also several policy measures
relevant to climate change, primarily in energy sector.
The energy sector covered in the research study are
power generation, industry, transportation, residential,
and commercial sectors.

Demography
According to BPS [2008], the population in 2005 is
219 millions with an average growth of 1.3% per annum (2000-2005). Indonesian population is divided
into three age groups: 0-14 year old (28%), 14-65 year
old (66%), and > 65 year old (5.5%). About 58% of the
population lives in Java island, while the land area ofJava is only 7% of total area of Indonesia. Most ofthese people (60%) live in rural area. The remaining
40% live in urban and urban peripheral. On average,
member of a household is 3.65.

Share of renewable energy in the current mix ofprimary energy supply in Indonesia is still low. The
supply still relies on oil, which accounts for 54.8% of
total supply, followed by natural gas 22.2%, coal
16.7%, hydro 3.7%, and geothermal 2.49%. According
to National Energy Policy (President Regulation No
5/2006), share of oil is to be decreased and substituted by coal, natural gas, and new/renewable energy.
It is expected that in 2025 the energy supply mix willcomprise coal (33%), gas (30%), oil (20%), and new/renewable (17%). Renewable include hydro, geothermal, and biofuel. New energy includes coal liquefaction, coal bed methane, and nuclear.
Ongoing programs considered to meet supply mix
target are power generation crash program I (10,000
MW coal) and II (10,000 MW coal and geothermal),kerosene-to-LPG and biofuel. Share of biofuel in supply mix will be 5%.The primary consideration in setting
the supply mix target is energy security but theachievement of the target will also has impact to theCO2 emissions level. Current Indonesia power generation is dominated by coal, followed by natural gas, oil,

Economic Features and Trend
GDP of Indonesia in 2005 is 1786 trillion Rupiah.
The GDP is structured by agriculture (13.6%), mining(11.0%), manufacturing and construction (35.2%),
trade and services (40.1%). During 2000-2005, theGDP has grown at 5.6-6 % per year with inflation rate
at 6-7% and income per capita in 2005 is 11 million
Rupiah (1,300 USD). In the same year, Indonesia‟sexport value was 607 trillion Rupiah (mainly oil, gas,coal, copper and textile) while its import value was 522
trillion Rupiah (mainly food, chemical and consumer
goods).

1and renewable. The fuel mix composition of power
generation are coal 40.7%, oil 30.6%, natural gas
5.1%, hydro 8.4%, and geothermal 5.2% (2005). The
share of other renewable energy is not significant. To
achieve renewable energy target in the supply mix,
GOI has passed several regulations, one of them ismandatory biofuel utilization in transportation, power
generation, industry (MEMR -32/2008).
The fuel mix in power plant is expected to change
in the future. According to national electricity generation plan 2008–2018 of State Electricity Enterprises(RUPTL PLN), the fuel mix in 2018 will become coal
63%, oil 2%, natural gas 17%, hydro 6%, wind 12%,and biomass 1%. After 2018, the fuel mix will be different, where the dominant fuel to be used in power plant
is natural gas. Based on Blueprint National Energy
Management Plan 2009, the fuel mix in power sector(2025) is as follows: gas 48% followed by coal 36%, oil
3%, geothermal 8%, and hydro 5%.

Context of LCS scenario
During 2000-2005, GHG emissions in energy sector increased from 50.5 million ton-C (2000) to 67 million ton-C (2005). At this level, energy sector is thesecond contributor of national GHG emission after
forestry and peat fires. On average, level of country‟semission increased 5.9 % per year (2000-2005).
Concerning the CO2 emission/capita, energy sector
contributed 0.37 ton-C (1.4 ton-CO2) per capita in
2005. Key sources of CO2 emission are fuel combustions (90.3%) and fugitives from flaring/venting in oil
and gas production facilities (9.7%). In fuel combustion
activities, 33.2% of CO2 emissions is accounted byenergy transformation and losses in power generationand oil and gas processing, 25% manufacturing,
22.4% transportation, 15% residential and commercial,
4.3% agriculture, mining, construction.
LCS is a relatively new concept for Indonesia. All
the above mentioned government action plans are notdeveloped as roadmap to achieve Low Carbon Society(LCS) target of the country. However, all those actionplans actually are in line with and supportive to the
LCS concept.

Energy conservation program is formally stated in
Energy Law 30/2007, Presidential Regulation 5/2006
Presidential Instruction 10/2005, Ministerial Regulation
031/2005. These regulations lead to the formulation ofnational master plan on energy conservation, whichstate that there is 15-30% reduction potential. Basedon Presidential Regulation, energy conservation is tobe implemented so that in 2025 the energy elasticity(energy growth divided by GDP growth) will becomeless than 1.

In this report, a scenario of energy sector in Indonesia towards LCS was developed. The objective is todescribe future visions for achieving the goals of LCS.
In developing the roadmap, there are 5 important
steps:- Depicting socio economic visions of Indonesia toward 2050;- Estimating current energy service demand-supply
and resulting CO2 emission that cover quantifying
society behavior on energy utilization, analyzing theimpact of city and transport infrastructure (include
travel behavior) and industrial structure to energy
consumption and resulting CO2 emission;- Exploring innovations for energy demand-supply;- Estimating energy service demand and supply in
BAU and two countemeasure scenarios and theamount of resulting CO2 emissions; and- Analysis of domestic potential to achieve energyrelated CO2 emission reduction.

There are several actions in transportation sector
relevant to energy and climate change are to be implemented in Jakarta and other big cities, i.e. decreasingof traffic jam through the reduction of private vehicles
by development of MRT (mass rapid transit) or BRT(bus rapid transit) in 6 cities, development of several
new toll roads, application of transport demand management, electronic road pricing, and intelligent transport system. Other actions to be implemented are diversification of fuels such as CNG and LPG for taxi
and bus-ways, biofuel for public as well as private car,and in the future, those are development of fuel cell,methanol and electricity in transportation. In addition,
GOI implements emissions monitoring in transportation (mobile source) and industrial flue gas (stationery
source) to control local emission as well as combustion efficiency in accordance to GHG emission.

2

Socio-economic scenarios in 2050
5.5% (2005–2010), 6.6% (2010-2014), 7.2% (20152030), 6% (2030-2050). On average, the GDP growthin 2005-2050 will be 6.9% per year. At this rate, theGDP will be 36998 trillion rupiah in 2050 (20.7 times
higher than 2005). The GDP per capita increases from
8 million (2005) to 113 million (2050) rupiah. For highgrowth scenario (CM2), GDP growth rate is assumed
to be 5.5% (2005-2010), 7.0% (2011-2015), 9% (20162030), 8% (2030-2050). As a result, It is estimated thatin 2050, the GDP will be 68252 trillion rupiah (40 times
higher than 2005) and GDP per capita will increase
from 8 million rupiah (2005) to 209 million rupiah(2050). As comparison, GDP projection developed by
Bapenas is also presented in the Figure 4. Comparedto Asian developed countries (Figure 5), the estimated
GDP per capita in 2050 for BAU and CM1 scenarios isrelatively low while in CM2 scenario the estimated of
GDP per capita is as high as Hongkong.

Depictive Scenario
Three scenarios are used to figure the direction of
future socio economic visions for achieving LCS goals
toward 2050, i.e. BAU (business as usual) and two
countermeasure (CM) scenarios. BAU assumes thatthe existing society orientation will continue until 2050.
The two countermeasures assume that there will bechanges in society orientation in the future.
The CM1, which is regarded as a moderate scenario, assumes that the society behavior is depicted
as calmer, slower, and nature oriented ones. The CM2that is regarded as high growth scenario, assumes
that the society is depicted as more active, quickchanging, and technology oriented. This scenario has
two long-term objectives, i.e. „realizing full socioeconomic potential of the country‟ and „creating a sustainable LCS.

Estimated Socio Economic Indicators

As for the industrial structure, countries with highGDP per capita such as most developed countries in
the world are usually has tertiary industry as the main
contributor of the country‟s GDP while other countries
with low GDP per capita will still rely on primary andsecondary sector. The share of tertiary industry inmost developed countries is around 70% while incountries with low GDP per capita only 40-50%. The

All scenarios (BAU, CM1 and CM2) use the same
estimate of population, 327 million in 2050. For number of household, BaU and CM1 assumed that population per household will not change from 2005 while
CM2 assumed the size will be reduced to 3.00.
For future projection (Figure 4) in BaU and CM1
scenario, it is assumed that the GDP will grow with

Population (million)

0-14

GDP (trillion rupiah)

250

15-64

200
150

100
50

80,000BAU and CM1

60,000CM240,000BAPENAS Projection

20,000
0

0

2005

2030

2050

Figure 3. Projection of Indonesian Population

Figure 4. GDP projection 2005-2050

Table 2 Estimated socio economic indicators in the base year (2005) and the target year(2050)
Socio Economic Parameter
Population, Million
No. of households. Million
GDP, trillion rupiah
GDP per capita, million rupiah
Gross output, trillion rupiah
Primary
Secondary
Tertiary
P-transport demand, billion psg km
F-transport demand, million ton km

2005
219
60
1,787
8.2
3,533
329
1,953
1,251
1,763
1.07

BaU
327
89
36,998113
72,406
6,516
37,50528,384
3,407
20.64

2050
CM1
327
89
36,998113
72,406
6,516
37,50528,384
2,965
20.64

3

CM2
327
109
68,252
209
126,791
9,610
39,62577,556
2,195
23.08

BaU
1.5
1.5
20.7
13.9
20.5
19.8
19.2
22.7
1.9
19.3

2050/2005
CM1
1.5
1.5
20.7
13.9
20.5
19.8
19.2
22.7
1.7
19.3

CM2
1.5
1.8
38.2
25.6
35.9
29.2
20.3
62.0
1.2
21.6

consumption of the country since industry sector is thelargest energy consumer in Indonesia.

350
300
250
200

In passenger transport, trip generation (number oftrips per parson per day) is assumed constant in BaU(3.6), slightly decrease in CM1 (3.3) and CM2 (3.0)
due to telecommunication. Though, in BaU scenario, it
is assumed that the distance of one trip will be longer
than 2005, and total passenger transport demand isabout twice of the base year. In CM1 and CM2 case,trip distance is assumed shorter than BaU due to infrastructure development, and total passenger transportvolume is reduced by 13% and 36% respectively.
Structure of freight transport is assumed similar withbase year, though, driven by growth of manufacturingindustries (export oriented), transport volume is increased significantly in all scenarios.

150
100
50

na
(2
00
-B
5)
aU
(2
05
-C
0)
M
1
(
- C 2 05
0)
M
2
(2
05
0)

Ch
i

as
e

-B

Si

Ja
pa
n
ng
ap
or
e
Br
un
Ho
ei
ng
So Ko n
g
ut
h
Ko
re
a
M
al
ay
sia

0

Figure 5. GDP per capita of Asian countries(2005)
and Indonesian scenarios.
GDP per capita of BAU and CM1 scenarios (in 2050)
is still relatively low, therefore, it is assumed that GDP
structure of the scenarios in 2050 will slightly different
compared to those in 2005. The share of tertiary industry is assumed to increase from 40 % to 45 % andshare of other sectors are relatively similar with that in2005. In CM2 scenario, share of tertiary industry is
assumed to increase to 65% in 2050. Shift of share ofindustry in the GDP structure will determine energy

Gross output (trillion rupiah)

140,000

In addition, floor space of commercial sector(including apartments) is increased by 23 times (BAU
and CM1) and 62 times (CM2) compared to base year
due to high growth of tertiary industry.
45

Commercial

120,000

100,000

Cement40

Iron and Stel

35

Other Industries
80,000Construction

60,000Chemicals
Textile, Wood, Paper

40,000Food and Beverage

BaU

30

CM1

25

CM2

20
15

5

Agriculture

0

Base

10

Mining and Quarying

20,000

Value of 2005 = 1

GDP per capita (million Rp.)

400

0

Population2005 2050 2050 2050
BAU CM1 CM2GDP

Final energy
GHG
demandemissionsFigure 7. Economy, Energy, Emissions

Figure 6. Economic structure of Indonesia in 2005 and 2050

Table 3 Quantitative assumptions of socio-economic indicators (input parameters to ExSS)
Population
Composition of population by age
Number of population per house holdPassenger Trip Generation (Ptg), trips
Final demand formation (trillion rupiah)- Export of Primary Industry- Export of Secondary Industry- Export of Tertiary Industry- Private consumption- Government consumption- Private investment

2005 Base
219,204,700
0-14 (28%),
15-64 (67%)>65 (5%)
3.68
3.6
11
471
125
1,109
140
453

4

2050 BaU
326,933,718

3.68
3.6
222
9,117
3,113
22,7552,867
9,294

2050 CM1
326,933,718
0-14 (23%)
15-64 (69%)>65 (9%)
3.68
3.3
222
9,117
3,113
22,7552,867
9,294

2050 CM2
326,933,718

3.00
3.0
213
6,973
4,791
40,572
15,336
16,572

GHG emissions & reductions
fuels and energy technology in line with the GOI energy planning. Final energy demand will be reduced to
636 million toe due to efficient energy system and mitigation measures as described later.

Energy demand
Future energy demand and the corresponding CO2
emissions are estimated using socio-economic data
described previously. Estimated energy demand isshown in Table 4 and Figure 8-10. Primary energy
demand in BAU is expected to increase 10.6 times,
from 120 to 1,273 million toe, while in CM1 and CM2
the demand will increase 6.5 and 10.9 times compared
to 2005. In the BAU, final energy demand is projected
to increase 8.3 times from 110 million toe (2005) to
919 million toe (2050) while CM1 and CM2 will increase 5.8 and 7.2 times. Share of industry sector will
increase from 36% (2005) to 62% (2050 BaU). In
countermeasure scenarios, share of final energy demand by type of fuel will shifts toward „move awayfrom oil‟. Oil decreases from 39% (2005) to 20.8%(CM1) and 3% (CM2),The CM2 has higher final energy demand (781 million toe) than CM1, but still lower than BaU despite its
greater economic size. It occurs due to higher energy
efficiency in CM2 with better financial availability.

CO2 emissions
CO2 emissions varied related to the economic size
and the way energy system is structured (Figure 11).
BAU has the largest CO2 emission, i.e. 1,184 million
ton-C in 2050 (14.4 times higher than in 2005). The
second is CM1 i.e. 617 million ton-C (7.6 times higher
than 2005 emission). Although the economic size of
CM1 is similar with BAU, however, energy system isstructured to be more energy efficient and low-carbon.
CM2 result in the lowest emission (183 million tons

In CM1 scenario, which assumed socioeconomic
structure will similar to BAU but considers low-carbon

1,000

1,500

Electricity

Clean coal (IGCC + CCS)
biomass (+biofuel)1,200

Biomass

800

Solar & Wind

900

million toe

million toe

solar wind geothermal
nuclear
hydro

600

600

Natural gas
Oil

400

Coal

natural gas

300

200

oil

coal

0

2005
Base

2050
BaU

2050
CM1

0

2050
CM2

2005
Base

Figure 8 Primary energy demand by type of energy

2050
CM1

2050
CM2

Figure 9 Final energy demand by type of energy

1,400

1,000

Passenger transport

Passenger Transport

800

1,200
Freight transport

Freight Transport

1,000

Residential

600

million ton-C

million toe

2050
Bau

Commercial

400

Industry

200

Residential

800

Commercial

600

Industry

400
200
0

0

2005

2050
BaU

2050
CM1

2005
Base

2050
CM2

2050
BAU

2050
CM1

2050
CM2

Figure 11 CO2 emissions by sector, million ton-C

Figure 10 Final energy demand by sector

5carbon). The energy demand and CO2 emission inthis scenario are lower than in BAU. The emissions
reductions from BAU emission are 48% and 85% respectively in CM1 and CM2 scenarios. Concerning
future final energy demand, in CM1 and CM2, share ofcarbon intensive energy (coal, oil, and gas) in final
energy demand is decreased. However, clean coal
power generation (equipped with CCS) increases its
share in CM2.
The CO2 emission per capita (Figure 2) in BAU
substantially increase from 0.37 ton-C (1.4 ton-CO2)
per capita (2005) to become 3.6 ton-C (13.3 ton-CO2)
per capita (2050). Emission per capita in CM1 is about
half of BAU and in CM2 it is about one sixth of BAU.

Owing to higher growth of the CM2, energy efficiency
improves more than CM1 and fuel use are expected toshift toward more electricity, renewable, nuclear, clean
coal power plant (IGCC) equipped with carbon capture
sequestration (CCS). It covers exploration of appropriate combination of energy services demand, end-use
technology, types of energy supply and technology.
The BAU projection is based on existing planningwithout mitigation actions for reducing CO2 emissions,moderate projection (CM1) follows the existing plan ofactions of the government, institutions, industries, association, etc. The above described results clearly
demonstrate that with appropriate policy it is possible

Table 4. Final energy demand by sector, ktoe
Coal

Oil

Solar, Wind,
Hydrogen

Gas

Biomass

Electricity

Total

2005
P-Transport
F-Transport
Residential

00017,788
6,562
7,876

6
0
836

0
0
0

0
0
30,6745
0
3,446

17,7986,562
42,832

Industry
Commercial
Total
Share

8,975
0
8,975
8.2%

8,925
1,223
42,374
38.5%

11,777207
12,825
11.6%

0
0
0
0.0%

5,995
193
36,863
33.5%

3,552
2,081
9,084
8.2%

39,224
3,704
110,120100%

2050 BAU
P-Transport
F-Transport
Residential
Industry
Commercial
Total
Share

0
0
0
133,904
0
133,904
14.6%

41,394
126,510
14,416204,622
39,561
426,503
46.4%

10
0
4,660
153,487
4,689
162,846
17.7%

0
0
0
0
0
0
0.0%

0
0
5,606
21,045
4,385
31,0373.4%

2
045,07856,26663,317
164,663
17.9%

41,406
126,510
69,761
569,325
111,952
918,953100%

2050 CM1
P-Transport
F-Transport
Residential
Industry
Commercial
Total
Share

0
0
0
94,7580
94,75814.9%

8,526
39,174
0
66,071
18,603132,37420.8%

0013,761
223,445
14,265
251,471
39.5%

0
0
9
0
0
9
0.0%

4,001
6,449
0
62,690073,14011.5%

15
024,94024,07635,171
84,202
13.2%

12,54345,62338,710471,039
68,039635,954100%

2050 CM2
P-Transport
F-Transport
Residential
Industry
Commercial
Total
Share

0
0
0
55,649055,649
7.0%

304
574
0
22,980023,857
3.0%

0
0
2,248
22,958
4,872
30,079
3.8%

0
5,403
0
0
0
5,403
0.7%

5,366
12,086
326
102,556
20,121
140,454
17.8%

3,573
23,99464,397339,124
104,075
535,163
67.7%

9,244
42,056
66,971
543,266
129,068
790,605100%

6

to direct the society toward low carbon development.
CM2 shows that higher economic growth may not always mean higher emissions. It can apply more costly
mitigation options and could reduce emission morethan lower economic growth scenario like CM1.

Residential sector
Energy demand in the sector will increase in linewith increasing population and GDP per capita. In
2050, it is assumed that energy service consumption
per capita increase by 1.2 ~ 7 times (varies by energy
service) compared to 2005 (BAU and CM1) and by 1.7
to 14 times in CM2. These assumptions are taken
based on energy demand and GDP trend data of several countries. However, because of higher efficiency
of equipments and more share of low-carbon fuels,
CO2 emissions from residential sector decreased by
54% (CM1) and 93% (in CM2) from BAU scenario.

CO2 emission reductions potential
Figure 12 presents CO2 emissions and reduction
potential of energy demand side. CO2 emission of
BAU will be reduced in demand side by 488 million ton-C 2050 under the CM1 scenario and by 385 million
ton-C in 2050 under the CM2 scenario. In both scenarios, largest reduction potential is found in industry sector.
. Figure 13 presents the breakdown of emission
reduction potential of energy supply side (broke downby the sectors which consumes electricity). It is possible to reduce emissions by 195 million ton-C in CM1
with appropriate policies. Largest reduction comesfrom industry and commercial sector. The reduction
potential of supply side is particularly high In CM2, 986
million ton-C in total, since large part of final energy
demand is shifted to electricity and power sector assumes very advanced technology in the scenario. As aresult, with higher efficiency and low carbon energy
sources can be implemented and its CO2 emissions
can be 85% less than BAU despite its greater economic size.

In BAU scenario, highest growth rate of CO2
emissions is found in commercial sector, 34 times
greater than year 2005. This is due to high growth oftertiary industry and more energy service demand per
floor area of commercial buildings. Though, in CM1
scenario, the rate is reduced to 16 times and in CM2,
only 2.8 times. In CM1, large part of emission reduction is contribution of energy efficiency improvement inbuildings while in CM2 power supply sector has
greater contribution as shown in Figure 13.

0

50

50

100

100

150

150

200

200

250

250

300

300

350

350

400

400

450

450

F-Transport

P-Transport

Industry

Commercial

Residential

F-Transport

2050CM2

P-Transport

Commercial

Residential

F-Transport

P-Transport

Industry

Commercial

Residential

F-Transport

0

Industry

2050CM1

2050CM2

P-Transport

Industry

Commercial

Residential

2050CM1

Commercial sector

Figure13 Potential of GHG emission reduction of
supply side by energy demand sector

Figure12 Potential of GHG emission reduction ofdemand side by energy demand sector

7ing transport distance, changing transport structure).
Fuel change to less CO2 emitting fuels could be implemented by introducing biofuel and natural gas toreplace oil fuels.

Industry Sector“Industry sector” in this report means primary andsecondary industries as energy consumer. Currently It
is the largest GHG emitter and also the highest contributor to Indonesia‟s GDP. In the future, energy consumption of this sector will be still higher compared toothers. Energy demand of industry sector is expected
to grow from 39 (2005) to 569 million toe (2050). Sinceenergy consumed by the industry is mainly coal, oiland gas, this sector will remain the main contributorsof CO2 emission. However, the share of CO2 emissionof industry sector also changes substantially. The
share of emissions from industry increase from 45% in2005 to 53%, 62%, 80% in 2050 for BAU, CM1, andCM2, respectively.

Energy systems, both demand and supply side, in
CM1 and CM2 are progressively efficient and more
electrified. Central power systems utilize low carbon
energy source such as renewable energy, nuclear,and other less CO2 emitting fuels. Particularly theCM2, clean coal technology such as IGCC equippedwith CCS is included.

Process technologies and types of equipments
used in this sector determine the type and quantity ofenergy used by the sector and the amount of resulting
CO2 emissions. Energy technology intervention, goodhouse keeping, changes of behavior and lifestyle ofworkers could be implemented to achieve the LCS
target. Energy technology intervention is implemented
through efficiency improvement (high efficient equipments and processes). Energy efficiency potential varies upon type of equipments and visions of each scenario (BAU, CM1, CM2). BAU assumes that existing
low efficiency equipment and processes will continue
to be used until 2050. Countermeasures scenarios
assume that in 2050, there should be changes in technology processes orientation. CM1 (moderate scenario), assumes that the level of efficiency of mostequipment and processes in the manufacturing sector
is lower than those in CM2 (high growth scenario),
which assumed that the behavior of the society is depicted as “technology oriented”.

Transportation Sector
Transportation sector is the second largest (after
industry) energy consumer in Indonesia. This sector
consumes almost 80% of oil product in the country.
CO2 emissions of the transport sector is mainly fromoil combustion. Reduction of CO2 emission from fuelcombustion activities could be achieved through efficient use of fuel and fuel change to less CO2 emitting
fuels. Efficient use of fuel can be achieved throughefficient vehicles, efficient transportation system(increasing the share of mass transport mode, reduc-8

Five “Actions” towards LCS
ciency improvement of processes, equipments, andappliances;
5. Sustainable Transport: Developing sustainabletransportation, including modal shift (more public andmass transport), fuel shift to renewable and lesscarbon-emitting energy, reducing trip generation andpassenger trip distance through improvement of urban
infrastructure, telecommunication, information access,transport demand management, and energy efficiency
improvement of vehicles.

Based on the result of the scenarios, a set of actions in energy sector was developed (Figure 14). The
countermeasures were grouped into following five actions.
1. Introducing Clean Energy: Utilizing clean energy
in residential and commercial sector, for example,
switch from oil to gas or electricity ;2. Low Carbon Lifestyle: Promoting low carbon lifestyle in residential and commercial sectors throughenergy efficiency campaign (i.e. energy efficiency improvement of technology appliances and behavior
change in buildings);
3. Low Carbon Electricity: Introducing low carbon
electricity in power sector involves the use of new andrenewable energy, efficient power generation, reduction of transmission and distribution (T&D) losses inelectricity grids, and CCS (carbon capture and storage) technology in coal power plants;
4. Low Carbon Fuels in Industry: Introducing low
carbon energy in industry, which covers energy shift torenewable and less carbon emitting fuels, energy effi-

The implementation of those actions needs several policies and regulations to provide appropriate
incentives. Several regulations and policy initiatives
regarding energy and climate change related issues
have been passed by the GOI (see page 8-9). To
boost the implementation of those actions, more technical regulations and policies initiatives (i.e. economic
incentives) are still needed.

Renewable energy and less CO 2 intensive energy

1. Introducing Clean Energy(Residential and Commercial)

Less CO2 intensive energy technology

Behavior in residential/commercial sector

2. Low Carbon LIfestyle(Residential and Commercial)

Energy-efficient appliances
Renewable energy & Less CO 2 intensive energy

LCS Actions

Energy-efficient technology of power generation

3. Low Carbon Electricity

Less CO2 intensive energy of power generation
Increasing efficiency of T&D

Renewable energy & Less CO 2 intensive energy
4. Low Carbon Fuels in Industry

Energy-efficient appliances
Energy efficient process and processing technology

Renewable energy & Less CO 2 intensive energy
5. Sustainable Transport

Modal shift (public/mass rapid transport utilization)
Energy efficiency improvement
Reduce trip genreration and distance (improve infrastructure,telecommunication, new urban design, traffice management)

Figure 14 Integrated Chart of Five Options

9

Action1: Introducing Clean Energy
Utilization of renewable energy and less carbon emitting energy in residential and commercial (Figure 15)
are considered as “Introducing clean energy”. In CM1
and CM2 scenarios, the actions cover replacing oil
products (kerosene and LPG, 17% in the base year)
by increasing the utilization of electricity.

(b) Commercial sector(a) Residential sector
100%

100%

Electricity
Biomass

80%

80%

Solar & Wind
60%

Natural gas

60%

Oil
40%

40%

Coal

20%

20%

0%

0%
2005

2050
BaU

2050
CM1

2005
Base

2050
CM2

2050
Bau

2050
CM1

Figure 15 Share of energy in (a) residential and (b) commercial sectors
40

Value in 2005 = 1

2005
30

2050 BAU

2050 CM1
202050 CM2

100Energy in
Residential
sectorEmissions from
Residential
sectorEnergy inCommercial
sectorEmissions from
Commercial
sectorFigure 16 Energy demand and CO2 emissions inresidential and commercial sectors

10

2050
CM2

Action 2: Low Carbon Lifestyle“Low carbon lifestyle” is implemented through efficiency improvement of electric appliances and otherdevices in residential and commercial sectors and also
behavior change in the buildings.

Implementing actions on clean energy and low carbon lifestyle in residential and commercial sectors willneed support from the government such as;Assuming share and efficiency of the appliances inresidential and commercial sectors, it was found that
total energy demand of residential sector in BaU, CM1
and CM2 are 70, 39, 67 million toe, respectively.
Those of commercial sector are 112, 68, 129million
toe, respectively (Figure 17 and 18). Energy demandin CM2 is similar level with BaU because CM2 hasgreater economic size and therefore consumes moreenergy service. Emission form these sectors in CM2 issubstantially reduced by supply side. (See Action 3).

Lighting
Kitchen
Hot water

20

Government regulations and policies that willencourage the development and utilization of energy efficient buildins;₋

Reducing barriers to access information and installation of energy efficient appliances and equipments.

Electricity

Ref rigerator

40

₋

80

Other electric
equipments

60

ITax incentives for efficient electric appliances andother electric machines will reduce the price of thisappliances and equipment and in turn will lead to
reduction of energy use;

Energy demand (milliion toe)

Energy demand (million toe)80₋Cooling0

Biomass

60

Solar & Wind

40
Gas

Oil

20

0

2005

2050
BaU

2050
CM1

2050
CM2

2005

2050
BaU

2050
CM1

2050
CM2

Figure 17 Final energy demand by service (left) and by fuel (right) in residential sector
140

100

Lighting

8060

Kitchen40

Hot water

20

Cooling

0

2005

2050
BaU

2050
CM1

Electricity

120

Energy demand (million toe)

Energy demand (million toe)140

Other electric
equipments
Ref rigerator

120

2050
CM2

100

Biomass

80

Solar

60

Gas

40

Oil

20
0
2005

2050
BaU

2050
CM1

2050
CM2

Figure 18 Final energy demand by service (left) and by fuel (right) in commercial sector

11Action3: Low Carbon Electricity“Low carbon electricity” can be implemented byincreasing the use of renewable energy in energy supply mix of the power generation, developing more efficient power generation (from pulverized to supercriticalor IGCC), reducing losses in transmission and distribution (T&D) of electricity grids, and CCS (carbon capture and storage) application.
Figure 19 presents energy efficiency level while
Figure 20 presents share of the type of energy supply
in power plant. In CM2, share of efficient power plantand more renewable energy (hydro, geothermal, etc)
and less CO2 emitting technology (clean coal, i.e.
IGCC equipped with CCS and nuclear power plant) in

CM2 is higher than those inCM1. Fuel consumption of
power generation and CO2
emission reduction is shownin Figure 21. For more detailof electricity supply , see
Table 9 in page 19.

100%

60%

IGCC+CCS

2005,
2050BaU

Biomass

Energy efficiency (%)

80%
2050CM1

Solar, wind,geothermal
Nuclear

40%
60%

2050CM2

Hydro
40%

20%

Gas
Oil

20%

Coal

0%
Coal

Oil

Gas

0%

Biomass IGCC
+CCS

2005

2050
BaU

2050
CM1

2050
CM2

Figure 19 Energy efficiency level of power generation Figure 20 Share of power supply by energy type inin each scenarioeach scenario
700

500

Coal with
CCS

600

Gas

400
CO2 emission (million ton-C)

Energy demand (milion toe)

Gas
500
Oil

400

Coal

300
200
100

0
2005

2050
BaU

2050
CM1

2050
CM2

Oil

300

Coal

200
100
0
2005

2050
BaU

2050
CM1

2050
CM2

Figure 21 Fuel consumption and CO2 emission of power generation sector in each scenario

12Action4: Low Carbon Energy System in Industry“Low carbon energy system in industry” can be
implemented through utilization of more renewable
and less carbon emitting fuels, efficiency improvementof processes, equipments, and appliances. Implementing low carbon fuels in industrial sector will reduce
CO2 emissions level significantly. Figure 22 presents
CO2 emission reduction potential of industry in CM1
and CM2 scenarios.
The level of emission and energy demand in bothscenarios CM1 and CM2 is affected by economic conditions of each scenario. Figure 23 shows the impactof economic output to energy demand in industry sector of each scenario. Figure 24 and 25 present energy
demand by service and by fuel.

500

Supplyside

60Demand
side

50

2005

400

Value in 2005 = 1

300
200

40

2050
BaU

30

2050
CM1

20

2050
CM2

100

10

0

0
2050
CM1

Gross output

2050
CM2

Energy demand (million toe)

600

Kiln
Steal

400

Motor
300

BoylerFurnace

200

Emission

600

Others500

Final Energy
DemandFigure 23 Impact of economic output to energy andCO2 emissions in primary and secondary industry

Figure 22 CO2 emissions reduction potential inindustrial sector by supply and demand side

Energy demand (million toe)

Emission reduction (million ton-C)

600

100
0

Electricity

500

Biomass
Gas

400

Oil
300

Coal

200
100
0

2005

2050
BaU

2050
CM1

2050
CM2

2005

2050
BaU

2050
CM1

2050
CM2

Figure 25 Energy demand in Industry by fuelFigure 24 Energy demand in Industry by energy service

13

Action 5: Sustainable Transport“Sustainable transport” is to be achieved throughmodal shift (more public and mass rapid transport), fuelswitch (more renewable and less GHG emitting fuel),
reducing trip generation and passenger trip distancethrough the improvement of city infrastructure, telecommunication, information access, traffic management,
and energy efficiency improvement.

Bike
Walk
Air
Ship
Two wheeler
Train
Bus
Large vehicle
Small vehicle

Transport demand(million passenger-km)

3,500
3,000
2,500

2,000
1,500
1,000

25

Transport demand(million t-km)

4,000

Air

Ship

20

Train

Large vehicle

15

Small vehicle

10
5

500

0

0
2005

2050
BAU

2050
CM1

2005

2050
CM2

2050
BAU

2050
CM1

2050
CM2

Figure 26 Transport demand by transport mode in passenger (right) and freight (left) transport
2.5

2050
BaU

1.5

2050
CM1

1

2050
CM2

0.5

20
Value in 2005 = 1

2
Value in 2005 = 1

25

2005

15

10
5

0

0

Passenger Transport Energy
DemandDemandGHG Emissions

Freight Transport
DemandEnergyDemandGHG Emissions

Figure 27 Effect of passenger and freight transport demand to energy demand and CO 2 emissions
14000

80000
Modal shift

70000

12000

milion ton-C

Fuel shift

50000

8000

40000
6000

4000
2000
0

2050CM1

Efficiency
improvement(vehicle)

30000

Efficiency
improvement(others)

10000

2050CM2

milion ton-C

60000

10000

20000

0
2050CM1

2050CM2

Figure 28 CO2 emissions reduction potential by means in passenger (right) and freight (left) transport

14

Methodology
A Procedure to create a local LCS scenario
In order to create a local low-carbon society scenario, We developed a method based on the idea of"back casting", which sets a desirable goal first, andthen seek the way to achieve it. Figure 28 shows
overview of the method.

(1) Setting Framework(1) Setting framework
Framework of a LCS scenario includes; target
area, base year, target year, environmental target,
number of scenarios. Among them, the base year iscompared with target year. The target year should
be far enough to realize required change, and nearenough to image the vision for the people in theregion. In this study, we set the target year of Indonesia, 2050. This is also a suitable time span for a
LCS study for the reasons above.

(2) Description of socioeconomic assumptions(4) Collection of low carbon
measures(3) Quantification of socioeconomic assumptions(5) Setting introduction of
measures in target year(6) Estimation of GHG
emissions in the target year

(2) Assumptions of socio-economic situations
Before conducting quantitative estimation, qualitative future image should be written. It is an imageof lifestyle, economy and industry, land use and soon. We could use the assumptions showed in the
CDP.

(7) Confirming measures set andsuggestion of policy recommendations
Figure 28. Procedure to create a local LCS scenario
priate criteria. For example, cost minimization, acceptance to the stakeholders, or probability of technological development.

(3) Quantification of socio-economic assumptions
To estimate Snapshot based on future image of(2), values of exogenous variables and parameters
are set. Using those input, ExSS calculates socioeconomic indices of the target year such as population, GDP, output by industry, transport demand,and so on.

(6)Estimation of GHG emission in the target year
Based on socio-economic indices and assumption of measures' introduction, GHG emissions arecalculated.
(7)Proposal of policies
Propose policy set to introduce the measures
defined. Available policies depend on the situationof the municipality or the country which it belongs.
ExSS can calculate emission reduction of eachcounter measure.
Therefore, it can show reduction potential ofmeasures which especially needs local policy. It
can also identify measures which have high reduction potential and therefore important.

(4) Collection of low-carbon measures
To collect counter measures which are thought
to be available in the target year. For example, highenergy-efficiency devices, transport structurechange such as public transport, use of renewableenergy, energy saving behavior and carbon sink.
Technical data is required to estimate their effect toreduce GHG emissions. In this research we employed the measure collected by AIM group in preceding studies.
(5)Setting introduction of counter measures
Technological parameters related to energy demand and CO2 emissions, in short energy efficiency, are defined. Since there can be various
portfolios of the measures, one must choose appro-

15

Quantitative estimation tool “Extended Snapshot Tool”

Figure 29 shows the structure of the Extended
Snapshot Tool (ExSS); seven blocks with input parameters, exogenous variables and variables between modules. ExSS is a system of simultaneous
equations. Given a set of exogenous variables andparameters, solution is uniquely defined. In thissimulation model, only CO2 emission from energy
consumption is calculated, even though, ExSS canbe used to estimate other GHG and environmentalloads such as air quality. In many LCS scenarios,
exogenously fixed population data are used. However, people migrate more easily, when the target
region is relatively a smaller area such as a state,
district, city or town. Population is decided by demand from outside of the region, labor participation
ratio, demographic composition and relationship ofcommuting with outside of the region. To determine
output of industries, input-output approach with“export-base approach” is combined in line with thetheory of regional economics.
Industries producing export goods are called"basic industry". Production of basic industries induces other industries i.e. non-basic industries,•Export•Government expenditure•Import ratio •Labor productivity

Macro-economy andIndustry Module•Commuting OD

Labor ModuleLabordemandWage

Averageworking time

Privateconsumption

Outputthrough demand of intermediate input and consumption of their employees. Number of workers
must fulfill labor demand of those productions.
Given assumptions of where those workers live andlabor participation ratio, population living in the region is computed. This model enables us to consider viewpoints of regional economic development
to estimate energy demand and CO2 emissions. For
future estimation, assumption of export value is especially important if the target region is thought to(or, desired to) develop led by particular industry,
such as automotive manufacturing.
Passenger transport demand is estimated fromthe population and freight transport demand
whereby it is a function of output by manufacturingindustries. Floor area of commerce is determinedfrom output of tertiary industries. Other than driving
force, activity level of each sector, energy demandby fuels determined with three parameters. One isenergy service demand per driving force, energy
efficiency and fuel share. Diffusion of counter measures changes the value of these parameters, and so
GHG emissions.

Number ofworkers

IncomeTime-use andConsumption Module•Labor participation ratio•Demographic composition•Average number of family
occupants

Population and Household
Number Module
Population
Number ofhousehold•Breakdown ofconsumption•Population distribution•Floor area per
outputFloor area ofcommercial buildings

Energy demand

Transport
ModuleCommercial
Building Module•Trip per parson•Transport distance•Modal share

Passenger and freighttransport demand

Energy Demand & GHG
Emissions Module•Energy service demand generation unit
•Energy efficiency•Fuel share•Emission factor

Module

GHG emissions

Main endogenous
variables

Exogenous variables
and parameters

Flow of endogenous variables

Figure 29. Overview of calculation system of Extended Snapshot Tool

16

Input

1.3

0.0

Iron and Stel

Cement86329

Total Input

9.0

Textile, Wood, Paper

17

6516

Total Input

37.5

Iron and Stel

115.2

7103

9610

Total value added

Total Input

5367.8

Subsidy & Indirect tax

Operating surplus

2507

1620.0Intermediate input

Compensation for employee

545.8

Commercial Services

0.0

13.0

Other Industries

Cement78.7

Construction

13.2

Textile, Wood, Paper

483.6

399.3

Food and Beverage

Chemicals

0.0

936.0

Mining and Quarying

Agriculture

4816

Total value added

Agriculture

78.1

3639.5

Subsidy & Indirect tax

Operating surplus

1700

1098.4

Intermediate input

Compensation for employee

370.1

0.0

25.4

8.8

53.4

Commercial Services

CementIron and StelOther Industries

Construction

327.9

270.7

Food and Beverage

Chemicals

0.0

634.6

Mining and Quarying

Agriculture243

Total value added

Agriculture

3.9

183.6

55.4

Subsidy & Indirect tax

Operating surplus

Compensation for employee

Intermediate input

18.7

0.4

Other Industries

Commercial Services

2.7

Construction

0.5

Textile, Wood, Paper

16.5

13.7

Food and Beverage

Chemicals

0.0

32.0

Mining and Quarying

Agriculture

Agriculture

316

109

20.7

62.1

26.5

207

35.8

0.6

0.6

1.1

0.1

5.4

3.3

54.6

0.3

104.9

Food andBeverage

253

95

2.7

63.9

28.5

158

36.2

0.0

3.2

5.6

0.4

26.8

70.8

0.9

0.3

14.2

339

144

-30.5

132.4

42.0

195

25.0

0.4

2.8

2.4

0.4

56.5

2.5

1.1

90.6

13.8

Chemicals

359

128

4.6

76.1

47.7

231

63.3

12.3

70.8

0.6

0.4

43.9

14.1

0.0

19.6

5.7

Construction

165

60

-3.1

43.5

20.0

105

17.3

0.0

12.7

44.9

0.6

19.9

1.1

0.0

8.0

0.5

Other
Industries

265

86

4.0

57.2

25.2

178

42.2

0.0

83.8

5.9

0.5

25.2

2.5

0.0

18.3

0.0

Iron and Stel

14

6

0.7

3.5

1.8

8

1.5

0.0

0.0

1.1

0.1

0.5

0.2

0.0

4.3

0.0

Cement

1251

717

17.7

425.5

273.7

534

280.4

0.0

16.1

43.2

23.1

75.4

26.0

34.8

0.4

34.4

Commercial
Services

3532

1786

29

1209

548

1746

530

13

195

105

31

274

121

105

165

206

Intermediate
input

1,109

529.7

0.0

52.1

73.2

0.0

68.9

54.0

199.6

0.0

131.4

Privateconsumption

140

139.7

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Government
consumption

453

25.3

0.0

66.6

21.0

328.5

7.1

5.5

-3.6

3.9

-1.5

Fixed capitalformation

Table 5. Input-Output data in the base year (2005), trillion rupiah
Textile, Wood,and Paper

607

124.8

0.5

81.5

16.8

0.0

112.8

96.7

43.8

119.0

10.8

Export

-522

-99.0

-0.3

-130.4-50.9

0.0-123.4

-23.9

-28.9

-47.2

-17.6

Import

5711

1975

373.4

1123.1

478.5

3736

646.3

11.7

11.7

20.1

2.0

96.8

60.0

987.0

5.0

1895.5

Food andBeverage

4852

1820

51.8

1222.6

545.6

3032

692.2

0.0

62.1

107.3

7.0

512.3

1355.7

16.3

6.2

272.8

Textile, Wood,and Paper

6631

2813

-595.12586.6

821.3

3818

488.2

7.9

54.1

46.8

6.9

1104.048.7

22.3

1770.7269.0

Chemicals

7100

2539

91.9

1503.5

943.7

4561

1252.3243.2

1399.5

11.1

7.2

868.7

277.8

0.0

387.4

113.6

Construction

3168

1157

-58.8

833.9

382.3

2011

331.2

0.2

242.3

859.9

12.1

380.2

21.8

0.1

152.3

10.5

Other
Industries

5102

1665

76.8

1102.4

485.8

3437

811.8

0.1

1614.5

113.8

10.1

484.6

48.7

0.3

352.8

0.1

Iron and Stel

269

118

13.6

68.4

35.8

151

30.1

0.5

0.0

22.0

1.2

10.4

3.0

0.0

84.0

0.0

Cement

28384

16268

401.7

9654.96211.212117

6363.9

0.0

366.0

981.2

524.4

1710.8

590.2

789.9

10.2

779.9

Commercial
Services

72406

36998

592

24877

11529

35408

11183

264

3848

2175

673

5571

2418

2087

3214

3977

Intermediate
input

22,75512515.1

0.0

877.2

1232.80.01160.8909.1

3363.30.1

2696.5

Privateconsumption

2,867

2867.1

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Government
consumption

9,294

929.4

0.3

1304.2410.26427.1

139.9

107.9

-69.7

76.4

-31.2

Fixed capitalformation

12,4523113.010.2

1577.9324.7

0.0

2182.6

1870.6847.72303.5

221.7

Export

4498

3684

152.5

3024.4

507.3

814

189.2

0.0

70.2

3.4

46.6

72.2

3.2

0.0

428.6

4075

1409

266.5

801.5

341.4

2666

461.2

8.3

8.3

14.4

1.4

69.1

42.8

704.3

3.6

1352.7

Food andBeverage

4699

1763

50.2

1184.2

528.4

2937

670.5

0.0

60.2

103.9

6.7

496.2

1313.1

15.8

6.0

264.2

Textile, Wood,and Paper

7854

3331

-704.93063.6

972.7

4523

578.2

9.4

64.0

55.4

8.2

1307.657.7

26.4

2097.2

318.6

Chemicals

9264

3313

119.9

1961.81231.35951

1634.0317.4

1826.114.5

9.4

1133.5

362.4

0.0

505.5

148.2

Construction

3788

1384

-70.3

997.2

457.2

2404

396.0

0.3

289.7

1028.2

14.5

454.6

26.0

0.2

182.1

12.6

Other
Industries

5107

1667

76.9

1103.6

486.3

3441

812.7

0.1

1616.2

113.9

10.1

485.1

48.8

0.3

353.2

0.1

Iron and Stel

338

148

17.0

85.8

44.9

190

37.7

0.6

0.0

27.6

1.5

13.1

3.8

0.0

105.5

0.0

Cement

77556

44449

1097.526380.5

16971.2

33107

17388.5

0.0

1000.02681.11432.94674.51612.72158.327.8

2130.9Commercial
Services

126791

68252

1120

43970

23161

58539

22714

336

4972

4056

1610

9189

3484

3305

3709

5164

Intermediate
input

40,57234486.3

0.0

148.6

208.9

0.0

196.7

154.0

569.8

0.0

4807.8

Privateconsumption

15,33615336.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Government
consumption

16,5726628.90.3

1553.1488.5

7654.0

166.6

128.5

-83.0

91.0

-55.7

Fixed capitalformation

11,9784791.17.8

1206.9248.3

0.0

1669.41430.8648.4

1761.9213.3

ExportTable 7. Input-Output data in the target year (2050), CM2 Scenarios, trillion rupiah

0.6

Mining andQuarying

4673

3827

158.4

3141.7

526.9

846

196.6

0.0

72.9

3.5

48.4

75.0

3.4

0.0

445.2

0.6

Mining andQuarying-16,206-6400.3-6.5-2773.6-1212.8

0.0-3368.0-497.7-364.4-1064.1-519.0

Import-10,371-2222.8-5.1-2505.9-974.20.0-2422.6-453.9-517.1-921.3-347.6

ImportTable 6. Input-Output data in the target year (2050), BAU and CM1 Scenarios, trillion rupiah

240

197

8.2

161.7

27.1

44

10.1

0.0

3.8

0.2

2.5

3.9

0.2

0.0

22.9

0.0

Mining andQuarying

68252

54842

2

135

-267

7654

-1335

1216

771

789

4446

Total final
demand

36998

17202

5

1253

993

6427

1061

2434

3624

1459

2539

Total final
demand

1786

720

0

70

60

328

65

132

211

76

123

Total final
demand126791

77556

338

5107

3788

9264

7854

4699

4075

4498

9610

Total output

72406

28384

269

5102

3168

7100

6631

4852

5711

4673

6516

Total output

3532

1251

14

265

165

359

339

253

316

240

329

Total output

Data tables

Table 8 Final energy demand of base year (2005) and target year (2050BAU, CM1, CM2), ktoe
2005 Base
Passenger Transport
Freight Transport
Residential
Agriculture
Mining and Quarying
Food and Beverage
Textile, Wood, Paper
Chemicals
Construction
Other Industries
Iron and Stel
CementCommercial
TOTAL

Coal
0
0
0
0
0
0
1,068
17
0
4,461
254
3,175
0
8,975

Oil
17,788
6,562
7,876
204
901
321
1,122
650
210
2,256
1,510
1,750
1,223
42,3742050 BaU

Coal

Oil

Passenger Transport
Freight Transport
Residential
Agriculture
Mining and Quarying
Food and Beverage
Textile, Wood, Paper
Chemicals
Construction
Other Industries
Iron and Stel
CementCommercial
TOTAL

0
0
0
0
0
0
14,026332
051,254
4,891
63,4010
133,904

41,394
126,510
14,416
11,453
9,335
9,853
52,722
18,5384,157
57,51029,072
11,981
39,561
426,5032050 CM1

Coal

Oil

Passenger Transport
Freight Transport
Residential
Agriculture
Mining and Quarying
Food and Beverage
Textile, Wood, Paper
Chemicals
Construction
Other Industries
Iron and Stel
CementCommercial
TOTAL
2050 CM2
Passenger Transport
Freight Transport
Residential
Agriculture
Mining and Quarying
Food and Beverage
Textile, Wood, Paper
Chemicals
Construction
Other Industries
Iron and Stel
CementCommercial
TOTAL

0
0
0
0
2,141
682
4,422
1,023
0
12,40931,247
42,8350
94,758
Coal
0
0
0
0
627
77
0
0
0
0
1,996
52,948055,6498,526
39,174
0
1,960
6,351
1,670
6,835
15,606917
20,751
0
11,981
18,603132,374
Oil
304
574
0
525
1,168
246
1,460
3,826
289
3,618
0
11,848023,857Natural gas

Solar & Wind

6
0
836
0
500
2,500
1,500
3,000
0
1,277
1,500
1,500
207
12,825Natural gas

Solar & Wind

10
0
4,660
421
28,5740
072,542
0
23,06628,885
0
4,689
162,846Natural gas

Solar & Wind

HydrogenSolar & Wind

18

0
0
0
0
0
0
0
0
0
0
0
0
0
5,403

0
0
30,674
500
150
300
2,650
0
150
745
0
1,500
193
36,863
Biomass

0
0
0
0
0
0
0
0
0
0
0
0
0
0
Hydrogen

0
0
9
0
0
0
0
0
0
0
0
0
0
9

0
0
2,248
328
2,426
417
4,660
6,249
289
8,591
0
0
4,872
30,079Biomass
0
0
0
0
0
0
0
0
0
0
0
0
0
0

0
0
0
0
0
0
0
0
0
0
0
0
0
0

0
0
13,761
4,865
22,753
3,313
44,617
65,168582
82,1460014,265
251,471Natural gas

Hydrogen

0
0
0
0
0
0
0
0
0
0
0
0
0
0

0
0
5,606
0
0
0
16,191
0
0
4,854
0
0
4,385
31,037
Biomass

Electricity
5
0
3,446
32
350
150
800
500
50
470
700
500
2,081
9,084
Electricity
2045,078
4,811
2,915
3,105
4,790
4,437
329
20,401
13,4801,997
63,317
164,663
Electricity

total
17,7986,562
42,832
736
1,901
3,271
7,140
4,167
410
9,209
3,964
8,425
3,704
110,120
total
41,406
126,510
69,761
16,68640,824
12,95887,73095,850
4,487
157,084
76,327
77,379111,952
918,953
total

0
0
0
0
0
0
0
0
0
0
0
0
0
0

4,001
6,449
0
5,234
4,313
2,503
25,7283,741
1,584
19,58600073,14015
024,940
2,064
1,657
2,825
1,057
596
329
13,5510
1,997
35,171
84,202

12,54345,62338,71014,124
37,214
10,99382,66086,134
3,411
148,443
31,24756,81368,039635,954

0
5,403
0
0
0
0
0
0
0
0
0
0
0
0

Biomass&H2
5,366
12,086
326
6,069
5,579
1,349
16,20921,112686
51,5520020,121
140,454

Electricity
3,573
23,99464,397
13,031
26,186
6,247
59,662
69,561
4,512
146,746
11,205
1,975
104,075
535,163

total
9,244
42,056
66,971
19,95235,985
8,335
81,990100,748
5,776
210,507
13,202
66,771129,068
790,605

HydrogenTable 9. Power supply table in Base year, BaU, CM1 and CM2 scenarios, ktoe
Coal
(conventional)(IGCC with CCS)

Fuel consumption

12,382

0

7,966

3,252

824

Power generation

3,979

0

2,992

1,481

166

0

125

62

2005 BaseOwn useTransmission loss

Coal

Naturalgas

Oil

Solaer& windBiomass

0507

624,937

824

0

507

2

9,785

34

0

21

0

407

Hydro

Nuclear

Total

445

0

334

166

92

0

57

0

1,094

3,368

0

2,533

1,254

697

0

429

1

8,284

Coal
(conventional)(IGCC with CCS)

Solaer& windBiomass

Fuel consumption

368,941

Power generation

Power supply

Oil

Natural
gas

Hydro

0

20,716

106,726

11,670

0

7,196

3,890

519,139

118,061

0

7,780

48,625

11,670

0

7,196

1,167

194,499

Own use

4,915

0

324

2,024

486

0

300

49

8,097

Transmission loss

13,196

0

870

5,435

1,304

0

804

130

21,740Power supply

99,9500

6,587

41,166

9,880

0

6,093

988

164,663

Coal(conventional)(IGCC with CCS)

Solaer& windBiomass

Fuel consumption

147,788

0

9,762

48,811

7,810

0

5,857

8,135

228,163

Power generation

53,2040

3,905

24,405

7,810

0

5,857

2,441

97,622

Own use

2,215

0

163

1,016

325

0

244

102

4,064

Transmission loss

5,099

0

374

2,339

748

0

561

234

9,356

Power supply

45,8900

3,368

21,050

6,736

0

5,052

2,105

84,202

Coal(conventional)(IGCC with CCS)

NuclearSolaer& windBiomass

Total

Fuel consumption

45,448514,934

28,78434,54180,59598,08357,568

191,893

1,051,845

Power generation

2050 BaU

2050 CM1

2050 CM2

Coal

Coal

Coal

Naturalgas

OilNatural
gas

Oil

Hydro

Hydro

Nuclear

Nuclear

Total

Total

17,270257,467

11,514

17,27080,59598,08357,56857,568597,335

Own use719

25,747

479

719

3,355

9,808

2,396

2,396

45,620Transmission loss

497

6,952

331

497

2,317

2,648

1,655

1,655

16,551

16,055

224,769

10,703

16,05574,92385,62653,51653,516535,163

Power supply

Table 10. Sources for the statistical data
Statistics
Indonesian Input-Output table
Indonesian population census
Indonesian population projection
Other indonesian economic data
National energy balance
Energy balance table of several countries
Other energy information
Transportation statistics
Industrial statistics

Sources
BPS-Indonesia
BPS-Indonesia
UN statisitcs
Bank of Indonesia publications
Pusdatin-MEMR
US-department of energy
DGEEU-MEMR publications
Ministry of transportation
BPS-Indonesia

19

Year
FY2000-2005
2005-2025
2005-2050
2000-2005
2005
2005
2005

NIES

Indonesia Low Carbon Society Vision of 2050 In Energy Sector
Institut Teknologi Bandung (ITB) - Indonesia
Retno Gumilang Dewi
Institute for Global Environmental Strategies (IGES) - Japan
Takuro Kobashi
Kyoto University - Japan
Yuzuru Matsuoka
Kei Gomi
Mizuho Information & Research Institute - Japan
Tomoki Ehara
National Institute for Environmental Studies (NIES) - Japan
Mikiko Kainuma
Junichiro Fujino