A STUDY ON

DA NANG LOW CARBON CITY

Source: ???

Recently, major ci es in Vietnam are required to localized the ini a‐ves of the Intended Na onally Determined Contribu ons (INDCs) to
the United Na ons Framework Conven on on Climate Change(UNFCCC). The aim of INDC is to reduce 8‐25% of total emissions in
2030 compared to Business as Usual (BaU). In line with the target, theVietnam Green Growth Strategy (Decision 1393/QD‐TTG) aims toensure eﬃcient and sustainable economic growth in Vietnam while
making signiﬁcant contribu ons towards implemen ng the na onal
climate change strategy. Moreover, the Na onal Target Program for
Climate Change Response (Decision 158/QD‐TTG) requires local gov‐
ernments to develop Climate Change Ac on Plans (CCAP). The CCAP
is necessary and should be integrated with the middle‐ and long‐term
master plan of socio‐economic development, speciﬁc sectoral devel‐
opment plans (such as transporta on, industry, power, agriculture,etc.) as well as water and waste management.

emission in energy‐related categories such as Residen al, Commercial,
Transporta on, and Industry. They are 2030BaU (Business as Usual) and
2030CM (CounterMeasures). The 2030BaU scenario, where counter‐measures for GHG emission reduc on are not introduced, reﬂects thesitua on in which both, the levels of commitments to climate‐friendly‐
energy produc on and technological breakthroughs are rela vely low.
Specially, countermeasures are assumed the same level as in 2013. On
the other hand, the 2030CM scenario, which addi onal low carbon
countermeasures are introduced in order to assess the reduc oneﬀects of GHG emissions. The socioeconomic assump ons about popu‐
la on, industrial structure, and economic growth are common to bothscenarios. Informa on from many domes c sources is used to calibrate
the parameters for base year 2013. In target year 2030, Extended Snap‐
shot Tool (ExSS) is applied for the projec on of future energy consump‐on and CO2 emission in energy‐related categories.

This study is one of the results of the research collabora on between
Asian‐Paciﬁc Integrated Model (AIM) team in Japan including Kyoto
University, E‐konzal, Na onal Ins tute for Environmental Studies(NIES), Mizuho Informa on and Research Ins tute (MHIR), Ins tutefor Global Environmental Strategy (IGES), and Ins tute of Strategy and
Policy on natural resources & environment (ISPONRE), Da Nang Cli‐
mate Change Coordina on Oﬃce (CCCO) in Vietnam. We expect thisbrochure is useful for researchers and policy‐makers who are interest‐
ed in developing the CCAP and can support the vision of building
green growth for Da Nang city.

In 2030BaU, Da Nang is expected under the rapid growth of driving
forces such as popula on, transport demand, and industrial ac vi es;
the total GHG emissions increases 4.01 mes, from 2,665 ktCO2eq in2013 to 13,563 ktCO2eq.
In 2030CM, the total GHG emissions reduc on is 16%, accoun ng for
2,226 ktCO2eq. Da Nang can reduce such emissions reduc ons by im‐
plemen ng 30 projects grouped in ﬁve ac ons.
By implemen ng ﬁve climate change ac ons, namely; Smart Building,
Smart Industry, Energy Eﬃciency, Smart Transport and Green Energy,
Da Nang can reduce 16% total GHG emissions in 2030CM (between the
10‐20% na onal reduc on target as declared in the Green Growthstrategy and within 8‐25% men oned in the Vietnam’s INDC).

Two scenarios are developed for the socio‐economic vision of Da
Nang by 2030, with the projec on of energy consump on and CO2
Table 1 GHG emissions by sectors (ktCO2eq) in Da Nang city

2030

2013
GHG emissions
Agricultural energy‐related
Industry
Commercial
Residen al
Passenger transport
Freight transport
Total GHG emissions

BaU

2030
BaU/2013
CM/BaUCM

ktCO2eq%ktCO2eq%ktCO2eq

%

2
880
151
459
546
626
2,665

0.1
33.0
5.7
17.2
20.5
23.5
100.0

12
5,779
1,169
1,235
1,838
3,531
13,563

0.1
42.6
8.6
9.1
13.5
26.0
100.0

12
4,950
961
1,000
1,537
2,878
11,338

0.1
43.7
8.5
8.8
13.6
25.4
100.0

5.67
6.56
7.73
2.69
3.37
5.64
5.09

1.00
0.86
0.82
0.81
0.84
0.82
0.84

GHG emissions per GDP (tCO2eq/bil.Dongs)

51.6

45.6

38.1

0.88

0.84

GHG emissions per capita (tCO2eq/person)

2.7

5.4

4.5

1.99

0.84

1

Socio‐economic scenario
Demography

Transport demands

Following the goal is to develop Da Nang into a major city for the
economy and to make Da Nang the socio‐economic centre of central
Vietnam. The es ma on of social and economic growth is based on
the Study on Integrated Development Strategy for Da Nang City and
Its Neighboring Area in the Socialist Republic of Vietnam (DaCRISS), .
Table 2 shows the results of main socio‐economic driving forces forbase year 2013 and target year 2030.

The transport demand in 2030 increases drama cally from 8,642 to
26,770 million person per kilometer (mil.per.km) of passenger
transport and 2,563 to 14,201 million ton per kilometer (mil.ton.km)
of freight transport compared to 2013 due to the increasing popula‐on and industrial ac vi es.

With assump on of popula on growth rate of 3%, Da Nang’s popula‐on in 2030 is projected to be more than 2.53 million people, which
about 2.6 mes increase on the base year’s popula on 2013.

In passenger transport, there is a rapid increase of demand on car to
3.1 mes, even motorbike s ll dominates. The share of public
transport by trip increases from 0.6% in 2013 to 10.0% in 2030BaU
and reaches 24.5% in 2030CM due to the contribu on of public bus
system.

Household size in 2030 is assumed by 3 persons/household (smaller
than the calculated value for 2013, which is 3.4), the total number ofhouseholds increases 2.93 mes, reaching about 844 thousand house‐holds in 2030.

Freight transport relies predominantly on roads and followed by wa‐
terway. We assumed that the share of waterway by trip will increasein freight transport modes in 2030, in which road is s ll dominates ,followed by waterway.

Table 2: Main socio‐economic indicators in Da Nang city

Table 3: Transport demand in Da Nang city

Popula on
persons
No. of households household
GDP per capita
mil. Dongs
GDPbil. Dongs
Agriculture
Industry
Commercial
Outputsbil. Dongs
Agriculture
Industry
Commercial
Final consump on bil. Dongs
Gross ﬁxed capitalbil. Dongs
forma onExportbil. Dongs
Importbil. Dongs
Passenger
mil.per.km
transport demandFreight transport

mil.ton.km

2013

2030

2030/2013

992,849
288,620
52
51,624529
17,83133,264
124,446821
55,592
68,03339,2942,533,190
844,397117
297,542
2,620
100,813194,109715,160
4,066
314,093
397,001
222,536

2.55
2.93
2.26
5.76
4.95
5.65
5.84
5.75
4.95
5.65
5.84
5.66

25,895

146,657

5.66

47,94361,508271,520
343,171

5.66
5.58

8,642

26,770

3.10

2,563

14,201

5.54

2013 2030BaU 2030CM BaU/2013 CM/BaU
Passenger transport(mil.per.km)

8,642

26,77026,978

3.10

1.01

Walk

67

190

190

2.83

1.00

Bicycle

178

505

505

2.83

1.00

Motorbike

7,446

16,367

12,206

2.20

0.75

Car

891

6,935

7,281

7.78

1.05

Bus

60

2,774

6,796

46.09

2.45

2,563

14,201

13,919

5.54

0.98

2,168

12,227

12,227

5.64

1.00

395

1,974

1,692

5.00

0.86

Freight transport(mil.ton.km)
Car
Waterway100%
Modal share in passenger transport

Unit

Economy
Da Nang has recorded remarkable changes in economic development.
The economic structure of Da Nang city con nues to shi towards theindustries and sevices. According to the development targets in Da
Nang’s development master plan, it is es mated that the GDP in 2030
will increase 5.8 mes compared to 2013. In 2013, the commercial
sector dominates the GDP share with 64.4%, followed by industrial
sector with 34.5%. In 2030, due to the increase of growth rate in com‐
mercial compared to agricultural sectors, the share of commercial in
total GDP increase to 65.2%, while the share of industry decreases to
33.9%, with a small share of less than 1% of total GDP is from agricul‐
ture. This economic structure follows the current trend and future
vision of Vietnam towards the ter ary industrial economy.

90%

Bus

80%
70%

Car

60%
50%

Motorbike

40%
Bicycle

30%
20%

Walk

10%
0%
2013

2030BaU 2030CM

Modal share in freight transport

100%

The GDP per capita of Da Nang in 2013 is around 52 mil. Dongs , andincreases 2.3 mes by 2030. The GDP per capita in 2030 reaches 117
mil. Dongs due to the rapid GDP growth (9.7% per annual).
In 2030, export and import in Da Nang expected to increase 5.7 and5.6 mes compared to those in 2013, respec vely. Final consump on
increases 5.7 mes , in which main consump on is from households
for industrial commodi es and services while the government con‐sump on is mainly for science, technology, and other services.

90%
80%
70%
60%

Waterway

50%
Car

40%
30%
20%
10%
0%
2013

2030BaU 2030CM

Figure 1: Modal share of transporta on in Da Nang

2

Projec on of ﬁnal energy consump on and GHG emissions
Table 3: Final energy consump on by sectors (ktoe)

Final energy consump on

GHG emissions

The annual total ﬁnal energy consump on of residen al, commercial,industrial and transport sectors is expected to increase from 702 kilo
tonnes oil equivalent (ktoe) in 2013 to 2432 ktoe in 2030BaU scenario
and 2884 ktoe in 2030CM scenario.

Figure 2 and table 5 shows the emissions in Da Nang.
In the year 2013, es mated GHG emission is about 2.7 MtCO2eq. In
2030BaU, total GHG emission increased up to 13.6 MtCO2eq, morethan fourfold increase from 2013. In which, the major contributors to
GHG emission include industrial sector, followed by transport,commercial and residen al sectors

The share of energy consump on by residen al sector is projected tobe reduced substan ally from 11% in 2013 to 5.5% in 2030BaU and5.4% 2030CM scenarios, as a result of a reduc on of the tradi onal
biomass fuels for cooking. In transport sector, energy consump ons
are accoun ng for 53.0% and 52.0% in 2030BaU and 2030CM scenari‐os, respec vely.

In 2030CM, emissions es mated reduced by 16% from the 2030BaU
emissions. Breakdown of GHG emission redeuc on is shown in Figure
3. In which, highest reduc on is a ributes to transport sector (44%),
followed by industry (38%), commercial (8%) and residen al (10%).

The ﬁnding shows that the energy shares of industrial and commercial
sectors are expected to increase in future, while the share of residen‐
al and transport sectors decrease. This is because of con nued
trends of industrializa on.

In 2013, per capita GHG emissions in Da Nang was 2.7 tCO2eq, though,in BaU scenarios, it is projected to increase up to 5.4 CO2eq. In
2030CM scenario it can be reduced to 4.5 tCO2eq.
Table 1 shows the GHG emission intensity. In 2013, es mated GHG
emission intensity is 51.6 tCO2eq/bil.dongs. In 2030BaU, emission
intensity decreased to 45.6 tCO2eq/bil.dongs mainly because of
greater share of ter ary industry in GDP. In 2030CM scenario, which
introduces implementa on of the projects and ac ons, emission
intensity is es mated to 38.1 tCO2eq/bil.dongs. More details of the
projects and ac ons are described in the following pages of thisreport.

The energy intensity by GDP reduces from 13.6 toe/bil. Dongs in 2013
to 11.5 toe/bil. Dongs in 2030BaU and 9.7 toe/bil. Dongs in 2030CM
due to the lower increasing rate of energy consump on compared to
the rapid growth of GDP. This reduc on follows the target to reduce
1% to 1.5% per year as men oned in Decision 1393/QD‐TTg for“Na onal Green Growth Strategy”.

16.00

13.6
14.00

11.3

MtCO2eq

12.00
10.00

30%

38%

Industry

8.00

Commercial
Residential

6.00

14%
4.00

10%

2.7

8%

Passenger transport
Freight transport

2.00
0.00
2013

2030BaU

2030CM

Figure 3: Share of reduc ons by sector

Figure 2: GHG emissions in Da Nang
Table 4: Energy consump on
2013
Total

%

702 100.0

Table 5: GHG emissions and reduc on

Unit: ktoe

2030BaU%

3,432 100.0

2030CM

%

2,884 100.0

Year

BaU/2013 CM/BaU
4.89

0.84

By sector
Agriculture

1

0.1

3

0.1

1,268 37.0

3

0.1

5.39

1.00

1,088 37.7

Industry

205 29.2

6.18

0.86

Commercial

22

3.2

154

4.5

136

4.7

6.91

0.88

Residen al

77 11.0

188

5.5

156

5.4

2.43

0.83

Passenger transport

185 26.3

623 18.1

526 18.2

3.37

0.84

Freight transport

212 30.2

1,196 34.9

975 33.8

5.64

0.82

By energy type
Coal

100 14.3

584 17.0

448 15.5

5.84

0.77

Oil

434 61.8

1,989 57.9

1,584 54.9

4.59

0.80

Gas

15

2.1

91

2.6

132

4.6

6.19

1.46

Solar

0

0.0

0

0.0

15

0.5

Biomass

30

4.3

176

5.1

174

6.0

5.85

0.99

Electricity

124 17.6

530 18.4

4.79

0.89

593 17.3

Coal
0.1

Industry

372.9

49.0

34.4

0.0

0.0

0.0
38.7
0.0
0.0
411.6
0.3
2,307.7
0.0
94.1
0.0
0.0
2,402.2
0.3
1,773.1
0.0
70.9
0.0
0.0
1,844.3

11.5
46.5
545.9
626.1
1,280.1
6.4
301.9
79.6
113.1
1,837.8
3,530.8
5,869.6
6.4
265.8
62.0
73.6
1,387.8
2,877.8
4,673.4

0.0
0.0
0.0
0.0
34.4
0.0
213.2
0.0
0.0
0.0
0.0
213.2
0.0
186.6
0.0
0.0
123.9
0.0
310.5

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
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
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0

Commercial
2013 Residen al
Passenger transport
Freight transport
Total
Agriculture
Industry
Commercial
2030
Residen al
BaU
Passenger transport
Freight transport
Total
Agriculture
Industry
Commercial
2030
Residen al
CM
Passenger transport
Freight transport
Total

3

Oil

Unit: ktCO2eq

SectorAgriculture

Gas Solar Biomass Electricity Total
1.2
0.0 0.0
0.0
0.8
2.1
424.1

880.4

139.6
151.2
374.1
459.2
0.0
545.9
0.0
626.1
938.7 2,664.8
5.1
11.8
2,956.3 5,779.2
1,089.2 1,168.8
1,028.0 1,235.2
0.0 1,837.8
0.0 3,530.8
5,078.6 13,563.5
5.1
11.8
2,724.4 4,949.9
899.5
961.4
855.6 1,000.1
25.2 1,536.8
0.0 2,877.8
4,509.6 11,337.8

GHG emission reduc on by Ac ons[III] Reduc on in Transport: 816.0 ktCO2eq
Ac on 1. Smart Industry

Ac on 4. Smart transport

Low carbon projects regarding promo on of energy eﬃcient equip‐
ment and fuel shi in the industry sector is included in Ac on 1.
Total reduc on of GHG emissions by this ac on is 829 ktCO2eq. Im‐
provement of kiln and furnace technology such as waste heat recov‐
ery is one of the main project in Ac on 1. This project contributes toreduce 272 ktCO2eq (see next page).

It is es mated that projects in Ac on 4 can reduce 954 ktCO2eq in
total, which is the largest reduc on among all ac ons. This ac on
covers variety of projects regarding both passenger and freight trans‐
porta on. Not only improvement of fuel eﬃciency of vehicles but
also promo on of modal shi to public transporta on and deploy‐ment of CNG bus are listed. Projects for freight transport such as
promo on of energy‐eﬃcient trucks have large poten al to reduce
GHG emissions, because GHG emission from freight transport sector
is more than twice as high as that from passenger transport sector.
Development of water freight transport system is aimed to shi
freight transporta on from truck to ship. Meanwhile, projects likeintroduc on of electric motorbike and CNG bus contribute to reduce
GHG emission from passenger transport.

Ac on 2. Smart Building
Ac on 2 covers low carbon projects related with diﬀusion of low‐energy houses and buildings. This ac on reduce 106 ktCO2eq. Energy
demand in houses and buildings through projects such as diﬀusion ofenergy management system and installa on of insulated glasses.
Introduc on of insula ng material to houses is a project that reduce
the largest GHG emission in this ac on. Introduc on of solar water
heater to houses and buildings is also main projects in this ac on to
reduce fuel demand. CO2 emission from houses is reduced by 23
ktCO2eq through 20% diﬀusion of solar water heater.

Ac on 5. Green energy
This ac on covers projects for increasing electric power genera on
by renewable energy including photovoltaic power, wind power andsmall‐scale hydropower. Total reduc on of GHG emission by Ac on 5
is 39 ktCO2eq. Photovoltaic power genera on systems are assumed
to install on roo op of houses and buildings. Hydropower genera on
is introduced to public facili es such as water distribu on sta on.

Ac on 3. Energy Eﬃciency
Projects about promo ng energy eﬃcient device and appliance likeligh ng and air condi oners for houses and buildings are covered in
Ac on 3. Total reduc on of GHG emission by this ac on is 298
ktCO2eq. For instance, replacement of conven onal ligh ng by higheﬃcient one such as LED ligh ng in houses and buildings contributes
to reduce about 87 ktCO2eq.
Table 1: Climate change ac ons (ktCO2) for Da Nang city
Climate change ac ons

Industry

Ac on 1. Smart Industry
Promo on of energy eﬃcient equipment and fuel shi

Commercial Residen al

Passenger
Transport

Freight
Transport

Total(ktCO2eq)829

829

Ac on 2. Smart BuildingDiﬀusion of low‐energy building (EMS, Insula on, Fuel shi )

55

51

106

Ac on 3. Energy Eﬃciency
Promo on of energy eﬃcient device/appliance

118

180

298

Ac on 4. Smart Transport
Energy eﬃcient vehicle and modal shi

301

Ac on 5. Green Energy
deployment of renewable electricity
Total (ktCO2eq)

829

4

34

5

207

235

653

954
39

301

653

2,226

Mi ga on projects in Da Nang LCC’s study
Table 6: Detail emission reduc on by projects in each category (ktCO2eq)

Action1 Smart Industry

Project

Sector

1-01

ESCO (Energy Saving COmpany) project for industries

Industry

225.8

1-02

Installation high energy efficiency facilities (such as compressors and motors)

Industry

204.3

1-03

Regional energy supply system

Industry

127.1

1-04

Improvement of kiln and furnace technology

Industry

272.0

Total
2 Smart Building

829.3

2-01

Installation of insulated glasses to commetcial buildings

Commercial

6.6

2-02

Installation of insulated glasses to households

Residential

7.0

2-03

Introduction of incentive to low energy buildings

Commercial

2.1

2-04

Introduction of insulating material to houses

Residential

28.6

2-05

Energy efficiency technology applied to buildings

Commercial

5.7

2-06

Introduction of solar water heater to commercial buildings

Commercial

18.9

2-07

Introduction of solar water heater to households

Residential

36.8

2-06

ESCO (Energy Saving COmpany) project for commercial buildings

Commercial

33.1

Total
3 Energy Efficiency 3-01

138.8

ESCO (Energy Saving COmpany) project for commercial buildings

Commercial

33.1

3-02

High efficiency lighting in public lighting

Commercial

4.3

3-03

High efficiency lighting in commercial buildings

Commercial

50.5

3-04

High efficiency lighting in households

Residential

36.1

3-05

High efficiency air conditioners (such as air conditioners with inverter controllers) incommercial buildings

Commercial

37.1

3-06

High efficiency air conditioners (such as air conditioners with inverter controllers) incommercial households

Residential

37.2

3-07

Promotion of energy-efficient appliances

Residential

99.7

Total
4 Smart Transport

298.1

4-01

Promotion of eco-driving with digital tachographs

Transport

46.6

4-02

Wide-range traffic control

Transport

4.9

4-03

Expansion of frequencies and routes of bus transportation

Transport

10.5

4-04

Development of Bus Rapid Transit (BRT)

Transport

5.2

4-05

Shift to CNG bus

Transport

11.9

4-06

Introduction of electric motorbikes

Transport

62.6

4-07

Promotion of energy-efficient vehicles (cars for passenger)

Transport

102.5

4-08

Promotion of energy-efficient vehicles (motorbikes)

Transport

143.5

4-09

Promotion of energy-efficient vehicles (trucks)

Transport

566.2

Total
5 Green Energy

Emission
reduction(ktCO2eq)

954.0

5-01

Introduction of photovoltaic power generation to commercial buildings

Commercial

32.4

5-02

Introduction of photovoltaic power generation to households

Residential

4.6

5-03

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

Commercial

1.6

Total

38.7

Total

2,258.8

5

Work procedure

ExSS tool

In order to iden fy the necessary ac ons, an “integrated modeling”
based on “back‐cas ng” approach is used.
The back‐cas ng approach sets a vision of the future society as a goal,
and then seeks a pathway towards achieving that goal.
We used ExSS (Extended Snapshot tool) for socio‐economic indicators,
energy related sectors. Informa on collec on is the ﬁrst step in themodeling work.
Socio‐economic informa on as well as environmental informa on forthe base year (2013) was collected and analyzed in order to es matecurrent carbon emissions. Besides this, feasible low carbon measuresfor Da Nang low carbon 2030 were also collected.
For the future projec on, informa on is based on planned develop‐
ments, as the model es mates socio‐economic ac vity levels including
popula on, number of households, land area, transport demand andother variables. Based on the collected informa on, GHG emissions
are calculated with or without countermeasures.

ExSS is a simpliﬁed simula on model for low carbon study and projects
socio‐economic ac vity, energy demand and supply, GHG emissions
and emission reduc on by measures. While each part of the tool isrela vely simple, it can describe whole picture of future society as a LCS
in a quan ta ve and consistent manner with a greater ﬂexibility thanmany other models. It also can consider most of the low carbon
measures exis ng and expected in near future. In this simula onmodel, popula on is decided by demand from outside of the region,
labor par cipa on ra o, demographic composi on and rela onship ofcommu ng with outside of the region. To determine output ofindustries, input‐output approach is applied. Passenger transportdemand is es mated from the popula on and freight transportdemand whereby it is a func on of output by manufacturing industries.
Floor area of commerce is determined from output of ter ary
industries. Other than driving force, ac vity level of each sector, energy
demand by fuels determined with three parameters. One is energy
service demand per driving force, energy eﬃciency and fuel share.
Diﬀusion of counter measures changes the value of these parameters,
and so GHG emissions.
Export by goods
Government expenditure
Import ratio
Input coefficient matrix
Private consumptions
Fixed capital formation

Output byindustry

IO
analysis
Output ofcommercial
industry

Energy service demand
per driving force
Energy end‐use device
share
Energy end‐use device
energy efficiency
Dispersed power
generation (DPG)

Household size

Output ofmanufacturingindustry

Population

Freighttransport
demandPassenger
transport
demandNumber ofhousehold

Trip per person
Trip distance
Modal share

Energy service
demandFuel share
Energy efficiency

Central power
generation (CPG)
Energy demand(CPG)

Team Informa on

Freight generation
per output
Transport distance

Final energy demand

Energy demand(DPG)

Energy efficiency DPG

KYOTO UNIVERSITY (KU)

Population

Modal share
Energy efficiency (CPG)
Fuel share (CPG)
Transmission loss (CPG)

Primary energy
supplyOwn use (CPG)

CO2 emissions

CO2 emission factor

Acronyms and Abbrevia ons

Yuzuru MATSUOKANGUYEN Thai Hoa*
DA NANG CLIMATE CHANGE COORDINATION OFFICE (CCCO)DINH Quang Cuong
VU Thi Mai Huong
Phu Chi Thinh
INSTITUTE OF STRATEGY AND POLICY ON NATURAL RESOURCES &ENVIRONMENT (ISPONRE)

AIM
BaU
CC
CCAP
CCCO
EBT
ExSS
GDP
IEA
IGES
INDCs
IOT
ktCO2eq
KU
LCC
MHIR
NIES
SYB
toe

NGUYEN Tung Lam
NATIONAL INSTITUTE FOR ENVIRONMENTAL STUDIES, JAPAN(NIES)
Junichi FUJINO
Toshihiko MASUI
E‐KONZAL
Yuki OCHI*
Tomoki EHARAINSTITUTE FOR GLOBAL ENVIRONMENTAL STRATEGIES (IGES)

Asia‐Paciﬁc Integrated ModelingBusiness as Usual scenario
Climate Change
Climate Change Ac on Plan scenario
Da Nang Climate Change Coordina on Oﬃce
Energy Balance Table
Extended Snapshot Tool
Gross Domes c ProductInterna onal Energy Agency
Ins tute for Global Environmental Strategies
Intended Na onally Determined Contribu ons
Input‐Output Tablekilo‐ton Carbon dioxide
Kyoto University
Low Carbon City
Mizuho Informa on and Research Ins tute
Na onal Ins tute for Environmental Studies
Sta s cal Yearbook
ton of oil equivalent

Shuzo NISHIOKATomoko ISHIKAWAMIZUHO INFORMATION AND RESEARCH INSTITUTE (MHIR)
Kazuya FUJIWARA

Acknowledgement*Contact address:

This research is supported by the Ministry of the Environment, Japan.

NGUYEN Thai Hoa: envi.jp@gmail.com
Yuki OCHI: ochi.ekonzal@gmail.com

Oct, 20166