Preliminary Research

The phenomenon of climate change in the last few decades has
become one of the strategic issues for all over the world, includingIndonesia. At the G20 Summit in Pittsburgh and COP15 in Copenhagen, Indonesia is committed to taking part in reducing greenhousegases (GHG) by 26% with domestic resources and 41% with international assistance in 2020. The commitments are then followed up by
the formulation of Presidential Regulation No. 61/2011 and No.
71/2011 on national action plans for GHG reduction. This regulation
provides the basis for ministries, institutions and local governments
to implement programs/activities aimed at reducing GHG emissions
from key development sectors. The Presidential Regulation has mandated local governments to develop Local Action Plans for Greenhouse Gas Emission Reduction. Moreover, Indonesia has set unconditional reduction target of 29% and conditional reduction target up
to 41 % of the business as usual scenario by 2030 in Intended Nationally Determined Contribution (INDC) in 2015.

plied for the projection of carbon dioxide (CO2) emission and designof LCS scenario. This preliminary research focuses on energy-related
CO2 emission.
Semarang City’s CO2 emission is estimated to be 5,282 ktCO2e in2015 based on collected data. The industry sector is a sector emitting the largest CO2 in Semarang City. This sector accounts for nearly
half of the total emission.
Two kinds of scenarios, namely Business as Usual (BaU) scenario
and Countermeasure (CM) scenario, are prepared to analyze reduction potential of CO2 emission in future. In BaU scenario, it is assumed that there is no policy or technology intervention to reducecarbon emission, while attempt to reduce carbon emission is assumed in CM scenario. In the CM scenario, Semarang City Government will promote five LCS actions and implement various LCS projects belonged to the actions. One of the action named “Sustainable
Transport”, which promotes energy efficient vehicle and modal shift,
will contribute to the reduction of 4,220 ktCO 2e. These actions andprojects help Semarang City to reduce total CO2 emission in 2030 by
29% compared to BaU scenario. CO2 emission per GDP, which is 39.4
tCO2e/bil. Rp in 2015, will be decreased to 26.9 tCO2e/bil. Rp in BaU
scenario and to 19.2 tCO2e/bil. Rp in CM scenario by 2030. Besides,
CO2 emission per capita is 3.3 tCO2e/person in 2015 and will be increased by more than 3 times from 2015 to 2030 in BaU scenario. On
the other hand, it will be reduced to 7.8 tCO 2e/person from BaU
scenario in CM scenario.

Following up the Presidential Regulation 61/2011 and 71/2011,
Semarang City as one of the cities in Indonesia has a liability in the
GHG reduction activities. This research on the low carbon society(LCS) scenario for Semarang City are carried out aiming to contribution to promoting climate change actions and policies in the city.
This study is one of the outcomes of the collaboration among Municipality of Semarang, Diponegoro University and Asia-Pacific Integrated Model (AIM) team in Japan.
The research are begun with collecting data and information
related to socioeconomic parameters and energy consumption. A lotof domestic and international sources are used to estimate bothcurrent and future status of Semarang City. The entire data is processed with the help of Extended Snapshot (ExSS) tool. ExSS is ap-

In conclusion, Semarang City has a potential to reduce CO2 emission corresponding to INDC of Indonesia. The city can be developed
more effectively and efficiently with contribution to the mitigation ofworld climate change.

Table 1. CO2 emission by sector
2015
CO2 emission (ktCO2e)
Industry
Commercial
Residential
Passenger transport
Freight transport
CO2 emission per GDP (tCO2e/bil. Rp)
CO2 emission per capita (tCO2e/person)

5,282
2,524
571
748
1,351
87
39.4
3.3

2030BaU
22,40914,577
4,042
1,174
2,093
523
26.9
10.9

1

2030CM
16,00910,826
2,665
862
1,246
410
19.2
7.8

2030BaU/2015
4.24
5.77
7.08
1.57
1.55
5.99
0.68
3.29

2030CM/2030BaU
0.71
0.74
0.66
0.73
0.60
0,78
0.71
0.71

SOCIOECONOMIC VISION
Table 2. Main socioeconomic indicators in Semarang City

Based on collected data of Semarang City in 2015 and information such as the national economic vision, “Masterplan for Acceleration and Expansion of Indonesia's Economic Development 20112025”, socioeconomic indicators for 2030 has been projected asshown in Table 2. There will have been an increase in the number of
each socioeconomic factor by 2030.

Population
No. of households
GRDP per capita
GRDP
Primary industry
Secondary industry
Tertiary industry
Final consumption
Gross capital formation
ExportImportCommercial floor area
Transport demand
Passenger transport
Freight transport

Population and Household
Population of Semarang City will grow by 464,733 people from2015 to 2030 or 1.29 times as much as population in 2015. This situation is similar to the number of households in Semarang City. The
number of households will also increase by 1.46 times compared to
the number in 2015. Growth of the number of households is a little
bit faster than population growth because household size will become smaller from the present to 2030.

Unit
persons
households
mil. Rpbil. Rpbil. Rpbil. Rpbil. Rpbil. Rp
thous. m2
mil. pass-km
mil. ton-km

2015
2030
2030/2015
1,595,267 2,060,000
1.29
471,327
686,667
1.46
84
405
4.81
134,207834,197
6.22
1,373
3,590
2.61
73,340440,906
6.01
59,493389,701
6.55
79,822
486,134
6.09
99,697607,179
6.09
37,563228,772
6.09
114,672
690,811
6.02
50,252330,043
6.57
18,342
3,391

28,422
20,3071.55
5.99

Macro Economy
As described in Table 2, the increase of macroeconomic indicators occurred by 2030 is about 6 times as much as the value in 2015.
There are three aspects underlying the macroeconomic conditions
which are gross regional domestic product (GRDP), GRDP per capita
and final consumption expenditure.

increase in GRDP in the secondary sector is not greater than that of
the tertiary sector. Growth rates of the primary, secondary and tertiary sectors between 2015 and 2030 are 2.61 times, 6.01 times and6.55 times.
Second is GRDP per capita. GRDP per capita in 2015 was 84 mil.
Rp and will have reached to 405 mil. Rp by 2030. GRDP per capita
will increase by 4.81 times compared with that in 2015.

First, the value of GRDP in 2015, which amounted to 134,207 bil.
Rp, will have increased to as big as 834,197 bil. Rp by 2030. Manufacturing of food, textile and transport equipment and Informationand communication technology (ICT) industry will lead the economic
growth of this area as written in the masterplan. The largest contributor to GRDP in Semarang City is the secondary sector. Table 3 andFigure 1 indicate the change of economic structure in Semarang City.
GRDP of Semarang City in 2030 will still be dominated by the secondary sector, especially the construction industry, followed by thetertiary sector, and the last is the primary sector. Nevertheless, theAs a result of population growth and income increase caused byeconomic growth, final consumption expenditure in the year 2030
will also have increased rapidly. The increase in the year 2030 equals
to 6.09 times as large as that in 2015. There is a connection between
consumption expenditure and GRDP, especially in the high increasein tertiary sectors, namely Transport and communications; Electricity,gas, water and waste; Wholesale and retail trade; and Financial, realestate and company services.

Table 3. GRDP by economic activity

100%

2030
/2015

2030

Primary industry
Secondary industry
Mining and quarrying
Foods, beverage and tobacco
Paper, paper products and printing

1,373
73,340261
17,885408

3,590
440,906
1,414
110,507
2,165

2.61
6.01
5.41
6.18
5.30

Chemicals and pharmaceuticals

6,785

35,783

5.27

Non-metal mineral products
Basic metals
Metal products, machinery and equipment
Other manufacturing
Construction
Tertiary industry
Electricity, gas, water and waste
Wholesale and retail trade
Transport and communications
Financial, real estate and company services
Other services

459
2,840
2,804
5,695
36,20159,493250
18,966
14,66910,45215,157

1,490
17,264
17,162
32,959222,162
389,701
1,658
124,395
99,352
67,70096,597

3.24
6.08
6.12
5.79
6.14
6.55
6.62
6.56
6.77
6.48
6.37

Total

134,207834,197

6.22

Other services

90%

Financial, real estate and company services

Transport and Communications

80%

Wholesale and retail trade70%

GRDP share (%)

2015

Electricity, gas, water and waste

Construction

60%

Other manufacturing

50%

Metal products, machinery and equipment
Basic metals

40%

Non-metal mineral products

30%

Chemicals and pharmaceuticals
Paper, paper products and printing

20%

Foods, beverage and tobacco

10%

Mining and quarrying
Agriculture, forestry, and fisheries

0%

2015
2030
Figure 1. GRDP share by economic activity

Transportation
In connection with the increasing socioeconomic aspects ofSemarang City, transport demand will also grow by 2030. Freighttransport volume will increase by 5.99 times from 2015, while growthrate of passenger transport volume between 2015 and 2030 is 1.55.
Freight transport demand will change rapidly leaded by the growing
manufacturing output.

2015
2030BaU
2030CM

Figure 2 describes modal share in passenger transport . In BaU
scenario, modal share is assumed not to be changed from 2015. On
the other hand, modal shift from motorbikes and private cars topublic transportation such us buses, bus rapid transits (BRTs) andrailways are expected in CM scenario. Modal share of public transportation will have reached to 25% by 2030 in CM scenario.

0%

20%

40%

60%

80%

100%

Modal share in passenger transport
Walk, Bicycle Motorbike Car Bus, BRT Railway, MRT
Figure 2. Modal share in passenger transport

2

ENERGY DEMAND AND SUPPLY
Under BaU scenario, final energy consumption will increase by
2,22 times in 2030 compared to 2015. The amount of energy consumed, which was 1,682.8 ktoe in 2015, will have increased to
6,149.6 ktoe in 2030. Table 4 describes that the industry sector will
still be the highest energy consumer with the increase in 2030. However, the most rapid growth of energy consumption does not occur
in the industry sector, but in the commercial sector instead. Energy
consumption of the commercial sector in 2030 will be 7.08 times asmuch as that in 2015.

ing water in the residential and commercial sector in CM scenario
though the share in total energy demand is still small.
Regarding energy mix in power generation, share of renewablesource such as solar, wind, geothermal and biomass energy will haveincreased to 17% in CM scenario as the national power development
plan is implemented (Figure 4). CO2 emission factor will be improved
from 10.07 tCO2/toe in 2015 to 7.74 tCO2/toe in 2030 CM scenario.
Table 4. Final energy consumption by sector (ktoe)
SectorIn contrast, energy consumption in CM scenario will be 27%
lower than that in BaU scenario owing to implementation of LCS
projects. Energy consumption will be reduced significantly in thepassenger transport sector. The reduction rate compared with BaU
scenario is 41%. According to Figure 3, oil will still dominate share ofenergy source in 2030, but it will have begun to switch from coal andoil to natural gas and electricity as a source of energy especially in
CM scenario. Furthermore, use of solar energy will increase for heat-

2015

2030BaU 2030CM BaU/2015 CM/BaU

Industry

731.6

4,139.9

3,483.6

5.66

0.84

Commercial

71.7

507.6

442.5

7.08

0.87

Residential

392.2

615.8

605.1

1.57

0.98

Passenger transport

457.7

709.2

421.0

1.55

0.59

Freight transport

29.6

177.2

138.8

5.99

0.78

1,682.8

6,149.6

5,091.0

3.65

0.83

Total

2015

2015

2030BaU

2030BaU

2030CM

2030CM

0%

0%

20%
40%
60%
80%
100%
Fuel share in final energy consumption

Coal

Oil

Gas

Solar

Biomass

Electricity

Coal

20%
40%
60%
80%
Energy mix in power generation
Oil

Figure 3. Fuel share in final energy demand

Gas

Hydro

Solar, Wind, Geothermal

100%
Biomass

Figure 4. Energy mix in power generation

CO2 EMISSION
Table 5 and Figure 5 describe estimated CO2 emission. In BaU
scenario, total CO2 emission will increase by 4.24 times from 2015 andwill have reached to 22,409 ktCO2e in 2030. On the other hand, CO2
emission in CM scenario will become 16,009 ktCO2e, which is equivalent to 29% reduction compared with BaU scenario.

have increased by 7.08 times compared to 2015, followed by thefreight transport sector (5.99 times) and the industry sector (5.77
times).
In CM scenario, the passenger transport sector and the commercial sector will lead emission reduction. The passenger transport
sector will have achieved 40% reduction of CO2 emission comparedwith BaU scenario, while CO2 emission will be reduced by 34% in thecommercial sector.

The industry sector will still be the largest CO2 emitter in both
BaU and CM scenario. The biggest increase in CO2 emission in BaU
scenario will occur in the commercial sector, where CO2 emission will
Table 5. CO2 emission by sector and fuel (ktCO2e)
Oil

Gas

497.0

492.5

586.8

948.2

2,524.5

Commercial

0.0

45.3

5.7

520.0

571.0

Residential

0.0

173.5

0.3

574.2

748.0

Passenger transport

0.0

1,350.7

0.0

0.0

1,350.7

Freight transport

0.0

87.3

0.0

0.0

87.3

Total

497.0

2,149.3592.7

2,042.5

5,281.5

Industry

5,694.5 14,576.9

Industry

2015

Coal

Electricity

2,738.9

2,820.5

3,322.9

Commercial

0.0

320.8

40.3

3,680.7

4,041.72030 Residential
BaU Passenger transport

0.0

272.4

0.4

901.5

1,174.4

0.0

2,093.0

0.0

0.0

2,093.0

Freight transport

0.0

522.8

0.0

0.0

522.8

Total

2,738.9

6,029.5

3,363.7 10,276.8 22,408.9

Industry

1,905.2

2,140.8

3,137.6

Commercial

0.0

208.9

105.7

2,350.82030 Residential
CM Passenger transport

0.0

272.4

0.4

588.8

861.7

0.0

1,182.6

40.6

23.2

1,246.3

Freight transport

0.0

409.7

0.0

0.0

409.7

1,905.2

4,214.5

3,284.3

Total

25,000Total

22,40920,000CO2 emission (ktCO2e)

Sector

16,009
Freight transport

15,000

Passenger transport

Residential
10,000Commercial
Industry
5,282

5,000

3,642.7 10,826.3
2,665.302015

2030BaU 2030CM

Figure 5. CO2 emission

6,605.5 16,009.4

3

CO2 EMISSION REDUCTION BY LCS ACTIONS/PROJECTSA variety of LCS projects shown in Table 8 are assumed to be
implemented to achieve CO2 emission reduction in CM scenario.
These projects are aggregated into five LCS actions from the perspective of fields and similarities. The actions are “Green Industry”,“Smart Building”, “Smart Device”, Sustainable Transport” and “Green
Energy”. These actions can help to reduce CO2 emission by 4,220.3
ktCO2e. In addition, 2,179.3 ktCO2e of CO2 emission are reduced by
improvement of CO2 emission factor of electricity due to the national
power policy to promote switching from coal to renewable energy.

gas and solar water heater are main projects in the action. For instance, Introduction of solar water heater to houses and buildings
can reduce CO2 emission by 76.2 ktCO2e.

Action 3: Smart Device
Action 3 is a group of LCS projects promoting energy efficientdevices and equipment used in houses and offices. Total GHG emission reduction by projects of the action is 434.1 ktCO 2e. Projects forthe commercial sector has a large potential to reduce CO 2 emission
reduction. Energy saving support scheme is a project that reduceenergy consumption and 150.6 ktCO2e of CO2 emission.

Action 1: Green Industry
Action 1 covers LCS projects for reducing energy consumption or
CO2 emission especially factories in industries. CO2 emission reduction equivalent to 2,552.0 ktCO2e by this action is largest among all
actions, because the industry sector emit more CO2 than any othersectors and has large room to reduce emission. Energy saving support scheme such as energy service company (ESCO) projects is adominant project in this action. This project contributes to reduce
964.6 ktCO2e of CO2 emission.

Action 4: Sustainable Transport
LCS projects regarding transportation are included in Action 4.
CO2 emission reduction by the action amounts to 950.1 ktCO2e.
Modal shift to public transportation as well as promotion of fuelefficient vehicles are listed in this action. promoting high efficient
motor bike is a project which have the largest potential to reduce
CO2 emission (452.3 ktCO2e) in the action.

Action 2: Smart Building

Action 5: Green Energy

LCS projects related with housing and building are categorizedin Action2. Reduction of CO2 emission reaches 248.4 ktCO2e in Action 2. Not only energy saving technology like insulated materials
applied to buildings but also installation of infrastructure for natural

Action 5 is a category for projects regarding electric power generation from renewable energy. 35.7 ktCO2e of emission can be reduced by photovoltaic power generation systems and small-scalehydropower generation facilities are introduced in Semarang City.

Table 6. Contribution to CO2 emission reduction by action and sector (ktCO2e)
Industry
Action 1: Green Industry
Promotion of energy efficient equipment and fuel shift

Commercial

Residential

Passenger
Transport

Freight
Transport

2,552

Total
2,552

Action 2: Smart Building
Diffusion of low-energy building (Insulation, fuel shift)

215

33

248

Action 3: Smart Device
Promotion of energy efficient device/appliance

357

77

434

Action 4: Sustainable Transport
Energy efficient vehicle and modal shift

837

Action 5: Green Energy
deployment of renewable electricity
Total

2,552

26

10

598

120

113

950
36

837

113

4,220

REFERENCES
Table 7. Main references of this research
SourcePopulation and ■ Badan Pusat Statistik, Kota Semarang (2016): Kota Semarang dalam Angka Tahun 2016.
household■ Demographia (2010): Demographia World Urban Areas Population Projections (From 6th Edition of World Urban Areas).
Macro economy ■ Badan Pusat Statistik, Kota Semarang (Website): [2010 Version] GRDP At Current Market Prices by Industrial Origin Per Sector-Sub Sector
in Semarang Municipality, 2008 - 2016.
■ Badan Pusat Statistik, Kota Semarang (Website): [2010 Version] GRDP of Semarang Municipality at Current Market Prices [2010] by Typeof Expenditure (Million Rupiahs), 2010 - 2016.
■ Bappeda, Provinsi Jawa Tengah and Badan Pusat Statistik, Provinsi Jawa Tengah (2015): Table Input Output Jawa Tengah 2013.
■ Kota Semarang (2004): Rencana Detail Tata Ruang Kota - Kota Semarang Tahun 2000 - 2010 (Bagian Wilayah Kota I - X).
■ Coordinating Ministry for Economic Affairs, Indonesia (2011): Masterplan for Acceleration and Expansion of Indonesia's Economic
Development 2011-2025.
Transport■ Kecamatan Dalam Angka Kota Semarang Tahun 2016 dan.
■ Badan Pusat Statistik, Kota Semarang (Website): Kind of Vehicles in Semarang City, 2005-2014.
■ Sugiono, A (2012): Prakiraan Kebutuhan Energi Untuk Kendaraan Bermotor di Perkotaan: Aspek Permodelan. Jurnal Sains dan Teknologi
Indonesia Vol. 14, No. 2, Agustus 2012, Hlm. 104-109.
■ Badan Pusat Statistik, Indonesia (2017): Statistik Indonesia 2017.
■ Indonesia 2050 Pathway Calculator – Panduan Pengguna untuk Sektor Transportasi –.
Energy■ Pemerintah Kota Semarang (2012): Profil emisi GRK Kota Semarang Tahun 2010 - 2020.
■ Pemerintah Kota Semarang (2014): Inventarisasi Emisi Gas Rumah Kaca Kota Semarang Tahun 2009-2014.
■ Ministry of Energy and Mineral Resources, Indonesia (2017): Handbook of Energy & Economic Statistics of Indonesia 2017.
■ International Energy Agency (2017): World Energy Balance 2017.
■ Bandung Institute of Technology & Kyoto University (2013): Technical Report of Low Carbon Society Scenarios Indonesia 2020 and 2050.
■ Ministry of Energy and Mineral Resources, Indonesia (2015): Power Policy and National Development Plan in Indonesia.

4PROJECTS TO ACHIEVE LOW CARBON SOCIETY
Table 8. CO2 emission reduction by project
Action1 Green Industry

Project

Sector

1-01

Energy saving support scheme such as ESCO (Energy Saving Company) project for
Industryindustries

964.6

1-02

Installation high energy efficiency facilities

Industry

346.6

1-03

Regional energy supply system

Industry

489.7

1-04

Improvement of kiln and furnace technology

Industry

692.3

1-05

Promotion of fuel shift of furnaces and boilers from coal to natural gas

Industry

58.8

Total
2 Smart Building

3 Smart Device

2,552.0

2-01

Installation of insulated glasses to commercial buildings

Commercial

84.1

2-02

Installation of insulated glasses to houses

Residential

12.2

2-03

Introduction of incentive to low energy buildings

Commercial

15.9

2-04

Introduction of insulating material to houses

Residential

7.0

2-05

Energy efficiency technology applied to buildings

Commercial

35.8

2-06

Shift to natural gas in buildings

Commercial

17.1

2-07

Introduction of solar water heater to commercial buildings

Commercial

52.3

2-08

Introduction of solar water heater to households

Residential

23.9

Total

248.4

3-01

Energy saving support scheme such as ESCO (Energy Saving Company) project forCommercial
commercial buildings

150.6

3-02

High efficiency lighting in commercial buildings

Commercial

66.5

3-03

High efficiency lighting in households

Residential

22.8

3-04
3-05
3-06

High efficiency air conditioners (such as air conditioners with inverter controllers)Commercial
in commercial buildings
High efficiency air conditioners (such as air conditioners with inverter controllers)
Residential
in households
Promotion of energy-efficient appliances

Residential

Total
4 Sustainable Transport

137.3
33.7
23.1
434.1

4-01

Promotion of eco-driving with digital tachographs

Transport

7.2

4-02

Wide-range traffic control

Transport

28.8

4-03

Expansion of frequencies and routes of bus and BRT

Transport

96.2

4-04

Development of public transportation like railway and MRT

Transport

98.6

4-05

Shift to CNG bus

Transport

6.1

4-06

Introduction of electric motorbikes

Transport

61.5

4-07

Promotion of energy-efficient vehicles (cars for passenger)

Transport

452.3

4-08

Promotion of energy-efficient vehicles (motorbikes)

Transport

86.7

4-09

Promotion of energy-efficient vehicles (trucks)

Transport

112.8

Total
5 Green Energy

Emission
reduction(ktCO2e)

950.1

5-01

Introduction of photovoltaic power generation to commercial buildings

Commercial

24.3

5-02

Introduction of photovoltaic power generation to households

Residential

9.7

5-03

Introduction of small-scale hydropower generation (at water distribution stations)

Commercial

1.7

Total

35.7

Improvement of CO2 emission factor of electricity

2,179.1

Total

6,399.55METHODOLOGY
1. Start of the Storytarget year, and calculate GHG emission reduction by each projectfrom bottom up based on assumption of degree of implementation.
Then, ExSS is used again to estimate GHG emission and reduction
from a macro perspective in CM scenario to remove duplication of
GHG reduction among projects and to keep consistency.

First, we authorize a task force to develop LCS scenario and allocate human resource and budget for the research. We also make aschedule based on needs and situation of a local government.
2. Framework Setting

5. Bridging the Output to Real World

Background research is important to set an effective framework
suited with the target region. We determine framework of the scenario (the target year, the base year, types of greenhouse gases, thetarget activities and the number of scenarios) by reference to thebackground. The base year should be decided with consideration fordata availability. More than one scenarios such as BaU scenario andCM scenario should be set to analyze effects of LCS actions to reduce GHG emissions.

We formulate actions by grouping projects according to themes
and fields for implementation. The whole outputs are summarized toa brochure/report and reported to policy makers.
Export by goods
IO
analysis

Investment
Government
expenditure
Import rate
Input coefficient matrix

3. Data Preparation

Private consumption

Two kinds of data are needed. One is for the current status andthe other is for the future vision. We collect data and information
about population, No. of household, economic accounts, inputoutput tables, transport volume, energy balance tables and GHG
emission. If some data are unavailable in the target region, it can be
estimated based on other available regional and national data.

Floor area per output

Population

Output byindustry

Household size

Output ofcommercial
industry

Output ofmanufacturingindustry

Commercial
building floorarea

Freighttransport
demandNumber ofhousehold

Trip distance
Modal share

Passenger
transport
demandFreight generation
per output

Energy service demand
per driving force

Transport distance
Fuel share

Energy end-use device
share

Energy service demand

Modal share

Final energy demand

Energy efficiency in
CPG

Energy efficiency

Energy end-use device
energy efficiency

4. Design of LCS Projects and Projection of Future Scenario

Energy demand
to DPG

Dispersed power
generation (DPG)
Energy efficiency in
DPG

Based on the collected information, GHG emission for the baseyear and BaU scenario are estimated by the quantification tool, ExSS.
This model was developed by Kyoto University. We adopt both bottom-up approach and top-down to estimate CM scenario. First, welist LCS projects that can be implemented in the target region by the

Exogenous variables
Parameters

Trip per person

Central power
generation (CPG)

Energy demand to CPG

Fuel share in CPG
Transmission loss in
CPG
Own use in CPG
CO2 emission factor

Primary energy supply

Carbon sink

Endogenous
variables

CO2 emission

Figure 6. Structure of ExSSACRONYMS AND ABBREVIATIONS
AIM
Bappeda
BaU
BRT
CM
CNG
COP
CPG
DPG
ESCO
ExSS
G20

Asia-Pacific Integrated Model
Development Planning Agency
Business as UsualBus Rapid Transit
Countermeasure
Compressed Natural Gas
Conference of the Parties
Central Power Generation
Dispersed Power Generation
Energy Service Company
Extended Snapshot Tool
Group of Twenty

GHG
GRDP
LCS
IEA
IGES
INDC
MRT
NIES
pass-km
Rp
tCO2e
toe

Greenhouse Gasses
Gross Regional Domestic Product
Low Carbon SocietyInternational Energy Agency
Institute for Global Environmental Strategies
Intended Nationally Determined Contribution
Mass Rapid Transit
National Institute for Environmental Studies, Japan
Passenger-km
RupiahTons of Carbon Dioxide EquivalentTons of Oil Equivalent

TEAM INFORMATION
Name

Affiliation

Bambang Haryono

Director, Semarang Development Planning Agency (Bappeda)

M. Farchan

Deputy Director, Semarang Development Planning Agency (Bappeda)

Muhanmmad Luthfi Eko Nugroho

Head, Infrastructure and Environment Semarang R&D Section, Development Planning Agency (Bappeda)

MaryonoLecturer, Department of Urban and Regional Planning, Diponegoro University

Satria Utama

Master Student, Department of Urban and Regional Planning, Diponegoro University

Hadiyanto, ST., Msc.

Head, Master Program of Environmental Science, Postgraduate School, Diponegoro university

Tomoki Ehara

Representative Executive, E-Konzal Co. Ltd.

Yuki Ochi

Researcher, E-Konzal Co. Ltd.

Junichi Fujino

Programme Director, City Taskforce, Institute for Global Environmental Strategies (IGES) /Senior Researcher, National Institute for Environmental Studies, Japan (NIES)

Sudarmanto Budi Nugroho

Research Manager, City Taskforce, Institute for Global Environmental Strategies (IGES)

Kazuya Fujiwara

Chief Consultant, Mizuho Information and Research Institute, Inc.

We welcome feedback and suggestion. Please contact us.
Maryono: maryono@pwk.undip.ac.id
Yuki Ochi: ochi.ekonzal@gmail.com
Junichi Fujino: jfuji55@gmail.com

Acknowledgement
This research is supported by the Ministry of the Environment, Japan and the Ministryof Research, Technology and Higher Education of the Republic of Indonesia.
November, 20176