In Vietnam, ci es demand eco‐friendly and low‐carbon devel‐
opment approaches and solu ons, such as energy‐eﬃcientbuildings, public transport, innova ve environmental technol‐ogy, waste treatment, energy recycling, etc. The development
and applica on of science and technology innova on is one ofstrategic priori es. Being one of ﬁve central ci es, Can Tho city
has selected science and technology as a leverage for all socio‐
economic development aspects of city. Currently, the city isfacing environmental challenges like saliniza on, unexpected
weather events, lack of fresh water, etc., which aﬀects thequality of life and gradually loses investors’ a rac on. In that
context, promo ng technology applica on to strengthen ur‐
ban resilience has been emphasized by the city. Moreover,major ci es like Can Tho in Vietnam are required to localize
the ini a ves of the Na onally Determined Contribu ons(NDCs) to the United Na ons Framework Conven on on Cli‐
mate Change (UNFCCC). The aim of NDC is to reduce 8‐25% of
total emissions in 2030 compared to Business as Usual (BaU).
Based on the targets in master development plan of Can Tho
city, two scenarios, namely Business as Usual (BaU) and Coun‐termeasure (CM), are developed for the socio‐economic visionof Can Tho by 2030, with the projec on of energy consump‐on and CO2 emission in energy‐related categories such as
Power genera on, Transporta on, Residen al, Commercial,
and Industry. In which, in BaU scenario we do not consider the
GHG emissions reduc on target. Meanwhile, in CM scenario,
mi ga on projects in the above men oned categories will be
implemented in order to meet the GHG emissions reduc ontarget as declared in the Vietnam’s NDCs.

This study is one of the results of the research collabora on
between Ins tute of Strategy and Policy on natural resources &environment (ISPONRE), Can Tho Climate Change Coordina on
Oﬃce (CCCO) in Vietnam and the Asian‐Paciﬁc Integrated Model(AIM) team in Japan including Rirsumeikan University, E‐konzal,
Na onal Ins tute for Environmental Studies (NIES), Mizuho
Informa on and Research Ins tute (MHIR), Ins tute for Global
Environmental Strategy (IGES). The method and preliminary
results of this research, we hope, would be provided to a policy
making process as a star ng point of discussion as well as sup‐port the discussion among stakeholders. As a result, more real‐is c and acceptable scenario would be deﬁned from the discus‐sion, evalua on and modiﬁca on by various stakeholders.
Two scenarios are developed for the socio‐economic vision of
Can Tho city by 2030, with the projec on of energy consump‐on and CO2 emission in energy‐related categories such as Resi‐den al, Commercial, Transporta on, and Industry. The
2030BaU scenario (Business as Usual), where countermeasuresfor GHG emission reduc on are not introduced. On the other
hand, the 2030CM scenario (CounterMeasures), which addi on‐
al low carbon countermeasures are introduced in order to as‐
sess the reduc on eﬀects of GHG emissions. In 2030BaU, thetotal GHG emissions increases 3.96 mes, from 2,690 ktCO2 in2015 to 9,467 ktCO2. In 2030CM, the low‐carbon ac ons help
Can Tho to reduce is 15%, accoun ng for 1,434 ktCO2. Can Tho
can reduce such emissions reduc ons by implemen ng 30 pro‐jects grouped in ﬁve ac ons.

Table 1: GHG emissions by sectors (ktCO2) in Can Tho city
2015

Industry
Commercial
Residen al
Passenger transport
Freight transport
Total
CO2 emission per GDP (tCO2/bil. VND)
CO2 emission per capita (tCO2/person)

2030BaU

2030CM

Rate

AmountShareAmountShareAmountShare

2030BaU/2015

2030CM/2030BaU

1,578
253
542
204
113
2,690

58.7
9.4
20.1
7.6
4.2
100.0
33.7

6,258
1,017
1,214
598
380
9,467

66.1
10.7
12.8
6.3
4.0
100.0
36.9

5,443
805
992
492
301
8,033

67.8
10.0
12.4
6.1
3.7
100.0
31.3

3.96
4.02
2.24
2.93
3.37
3.52
1.10

0.87
0.79
0.82
0.82
0.79
0.85
0.85

3.8

2.10

0.85

2.1

4.5

1

Socio‐economic scenario
Table 2: Main socio‐economic indicators in Can Tho
The es ma on of social and economic growth in Can Tho city
is based on the master development plan (Decision number
1533/QD‐TTg). Table 2 shows the results of main socio‐
economic driving forces for base year 2015 and target year
2030.

Popula on
No. of households
GDP per capita
GDP
Agriculture
Industry
Commercial
Outputs
Agriculture
Industry
Commercial
Final consump on
Gross ﬁxed capitalforma onExportImportPassenger transport
Freight transport

Demography
As shown in Table 2, the registered popula on in Can Tho
increases 1.68 mes compared to 2015, reaching 2.1 million
people in 2030 (same as the projec on in Master plan ‐ Deci‐sion 1553/QD‐TTG).
By assuming the household size in 2030 is 3 persons/household, the total number of households increases 1.94
mes, reaching 700 thousand households in 2030.

EconomyFollowing the development targets in the master plan of Can
Tho, it is es mated that the GDP in 2030 will increase 3.21
mes compared to 2015. Secondary sector will s ll be mainindustry, though remarkable growth of ter ary sector. In
2015, the commercial sector dominates the GDP share with
47.9%, followed by industrial sector with 38.1%.

Unit
persons
householdmil. Dongs
bil. Dongs

bil. Dongs

bil. Dongs

2015
2030
2030/2015
1,251,809 2,100,000
1.68
357,660
700,000
1.96
64
122
1.92
79,864
256,660
3.21
11,125
18,8301.69
30,458107,859
3.54
38,281
129,971
3.40
185,422625,940
3.38
15,83826,807
1.69
107,260
387,529
3.61
62,324
211,604
3.40
53,405
181,562
3.40

bil. Dongs

32,533

110,605

3.40

bil. Dongs
bil. Dongs
mil.per.km
mil.ton.km

69,73175,8063,296
925

237,069
272,576
8,920
3,112

3.40
3.60
2.71
3.37

Transport demands
Due to the increasing popula on and industrial ac vi es, thetransport demand in 2030 also increases rapidly with 2.71
mes of passenger transport demand and 3.37 mes in‐crease of freight transport demand compared to 2015.

In 2030, due to the rapid growth rate in commercial com‐pared to other sectors, the share of commercial in total GDP
increases to 50.1%, and the share of industry grows to 42.0%.
This economic structure follows the current trend and future
vision of Vietnam towards the ter ary industrial economy.

In passenger transport, there is a rapid increase of demandon car (including taxi) to 8.23 mes, even motorbike s ll
dominates. The share of public transport (bus) increases
from 11% in 2015 to 15.0% in 2030BaU and reaches 20.0% in
2030CM due to the contribu on of bus system as urban
transport planning.

The GDP per capita of Can Tho in 2015 is around 64 mil.
Dongs , and increases 1.92 mes by 2030. The GDP per capita
in 2030 reaches 122 mil. Dongs due to the rapid GDP growth(8.1% per annual).

In freight transport, the demand increases mainly in truck
and waterway. Since we have no informa on about the planfor freight transport, we assume that the shares of freighttransport modes in 2030 are the same as in 2015, in which
truck contributes to about 48%, followed by waterway with52% contribu on.
Table 3: Transport demand in Can Tho city
2015
Passenger transport(mil.per.km)

3,296

8,920

9,037

2.71

1.01

Walk

7

17

31

2.47

1.82

Bicycle

82

203

268

2.47

1.32

2,434

5,097

4,446

2.09

0.87

Car

186

1,533

1,533

8.23

1.00

Bus

587

2,070

2,759

3.53

1.33

925

3,112

3,112

3.37

1.00

Truck

386

1,298

1,298

3.37

1.00

Waterway

539

1,814

1,814

3.37

1.00

Motorbike

Freight transport(mil.ton.km)

Figure 1: GRDP by secondary industry

22030BaU 2030CM BaU/2015 CM/BaU

Energy consump on and CO2 emissions
Table 3: Final energy consump on by sectors (ktoe)

Final energy consump on
In 2030BaU, the total energy consump on is 3.62 mes higher
than 2015 (Table 4), increasing from 730 ktoe to 2,379 ktoe. In
which, industry is s ll the main energy consumer with 55.0%(3.96 mes increase), followed by residen al sector with23.2%. Commercial has the highest speed of energy consump‐on with 4.02 mes increase and its share is 7.9%.

Table 4: Final energy consump on by sector (ktoe)
2015 2030BaU 2030CM BaU/2015 CM/2015
By sector

The energy intensity by GDP reduces from 9.1 toe/bil. Dongs in2015 to 8.1 toe/bil. Dongs in 2030CM due to the lower increas‐
ing rate of energy consump on compared to the rapid growthof 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”.

Industry

331

1,310

1,144

3.96

0.87

Commercial

47

187

169

4.02

0.90

Residen al

246

551

523

2.24

0.95

Passenger transport

69

203

138

2.93

0.68

Freight transport

38

129

102

3.37

0.79

Coal

179

689

585

3.84

0.85

Oil

167

537

398

3.22

0.74

Natural gas

20

76

68

3.89

0.89

Solar

0

0

38

0.0

0.0

Biomass

178

436

419

2.45

0.96

Electricity

186

642

569

3.45

0.89

730

2,379

2,076

3.26

0.87

By energy type

In term of energy consump on mix, there is a switch from coaland oil consump on to electricity. However, coal is s ll one of
the main energy sources with the share of coal consump on
from 24.6% in 2015 to 29.0% in 2030BaU, especially for indus‐
trial ac vi es. Share of biomass consump on for some purpos‐
es in residen al and commercial sectors slightly reduces from
24.4% in 2015 to 18.3% in 2030BaU.

Total

CO2 emissions
Total GHG emission in 2030BaU is projected about 9.5 MtCO2,
accoun ng for 2.6 mes higher than base year 2015 (2.7
MtCO2).

Regarding to GHG emission intensity, in 2015, es matedGHG emission intensity is 33.7 tCO2/bil.dongs.
In 2030BaU, emission intensity increased to 36.9 tCO2/
bil.dongs.

Main contributors to GHG emissions in the 2030BaU scenario
are industrial sector (6.3 MtCO2), followed by residen al,commercial and transport, sectors which account for 1.2, 1.0
and 0.9 MtCO2, respec vely. GHG emissions in 2030CM, ises mated to reduce by 15% from the 2030BaU emissions.

In 2030CM scenario, which introduces implementa on of
the projects and ac ons, emission intensity is es matedto 31.3 tCO2/bil.dongs.
More details of the projects and ac ons are described in
the next pages.

As can be seen from table 1 that per capita GHG emissions in2015 in Can Tho was only 2.1 tCO2, though, in BaU scenarios, it
is projected to increase up to 4.5 tCO2. In 2030CM scenario it
can be reduced to 3.8 tCO2.
Table 5: CO2 emissions by sector and fuelYear

Sector

Coal

Oil

Gas

Electricity Total

2015

Industry

644.9

76.5

45.8

769.9

1,537.1

Commercial

30.0

47.3

0.0

175.8

253.0

Residen al

62.0

34.1

0.0

445.7

541.7

Passenger transport 0.0

203.8

0.0

0.0

203.8

Freight transport

0.0

113.0

0.0

0.0

113.0

Total

737.9

492.6

45.8

1,413.5

2,689.82030BaU Industry

2,572.9

306.1

178.1 3,124.8

6,181.9

Commercial

120.5

190.1

0.0

706.8

1,017.4

Residen al

138.8

76.3

0.0

998.8

1,214.0

Passenger transport 0.0

597.8

0.0

0.0

597.8

Freight transport

0.0

380.4

0.0

0.0

380.4

Total

2,834.1

1,583.7 178.1 4,871.2

9,467.2

2,167.7

273.3

158.6 2,774.0

5,373.6

Commercial

98.3

148.5

0.0

558.4

805.1

Residen al

138.1

68.6

0.0

785.7

992.4

Passenger transport 0.0

352.9

0.0

138.8

491.7

Freight transport

0.0

300.7

0.0

0.0

300.7

Total

2,405.8

1,174.7 158.6 4,293.7

2030CM Industry

8,032.7

Figure 2: CO2 emissions

3

CO2 emission reduc on by Ac ons[III] Reduc on in Transport: 816.0 ktCO2eq
Ac on 1. Green Industry

Ac on 4. Smart transport

Low carbon projects regarding promo on of energy eﬃcientequipment and fuel shi in the industry sector are included in
Ac on 1. Total reduc on of CO2 emissions is 808 ktCO2. Im‐
provement of kiln and furnace technology such as waste heatrecovery is one of the main project in Ac on 1.

It is es mated that projects in Ac on 4 can reduce 236 ktCO2
in total, which is the largest reduc on among all ac ons. Thisac on covers variety of projects regarding both passenger andfreight transporta on. Not only improvement of fuel eﬃcien‐
cy of vehicles but also promo on of modal shi to public
transporta on and deployment of EV bus are listed. Projects
for freight transport such as promo on of energy‐eﬃcient
trucks have large poten al to reduce GHG emissions. Mean‐
while, projects like introduc on of electric motorbike and EV
bus contribute to reduce GHG emission from passenger
transport.

Ac on 2. Green Building
Ac on 2 covers low carbon projects related with diﬀusion of
low‐energy houses and buildings. This ac on reduce 104
ktCO2eq. Energy demand in houses and buildings throughprojects such as diﬀusion of energy management system andinstalla 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.

Ac on 5. Green energy
This ac on covers projects for increasing electric power gen‐era on by renewable energy including photovoltaic power,
wind power and small‐scale hydropower. Total reduc on of
GHG emission by Ac on 5 is 21 ktCO2. Photovoltaic power
genera on systems are assumed to install on roo op of hous‐es 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 appli‐
ance like ligh 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 265 ktCO2.

Table 6: Climate change ac ons (ktCO2)
Industry
Ac on 1. Green Industry
Promo on of energy eﬃcient equipment and fuel shi
Ac on 2. Green BuildingDiﬀusion of low‐energy building (EMS, Insula on, Fuel shi )Commercial Residen al

Passenger
Transport

Freight
Transport

Total(ktCO2)808

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

808
93

11

104

101

164

265

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

106

Ac on 5. Green Energy
Deployment of renewable electricity
Total (ktCO2)

808

18

3

194

175

130

236
21

106

130

1,434

References
Organiza on, Author
Popula on and macro
General Sta s cs Oﬃce of Vietnam
economyGeneral Sta s cs Oﬃce of Vietnam
Can Tho department of commerce
Prime Minister of Vietnam
Prime Minister of Vietnam
Can Tho People Commi ee
EnergyTitle
Vietnam Sta s cal Yearbook 2016
Can Tho Sta s cal Yearbook 2016
Project on trade development plan of Can Tho city 2015, and a vision to 2020
Decision number 1515/QD‐TTg on approval of development plan for Can Tho
2030 and vision up to 2050
Decision number 1533/QD‐TTg on approval of socio‐economic development
plan for Can Tho 2020 and vision up to 2030
Decision number 3814/QD‐UBND on approval of solu on to transfer eco‐nomic structure of Can Tho city 2020

CP TVXDD3 company

Master plan on development of power sector in Can Tho in period 2011‐2015

Interna onal Energy Agency

IEA Energy Balances of Non‐OECD in 2015
Decision number 2012/QD‐UBND on approval of public transport by bus in
Can Tho 2020 and vision to 2030

Transport

Can Tho People Commi ee

Environment

Can Tho department of transport, Center ofReport on development plan of transporta on in Can Tho 2030
research on transport development
Can Tho People Commi ee
Plan number 83/KH‐UBND on sustainable development of Can Tho 2016
Can Tho People Commi ee

Ac on plan on air quality management in Can Tho

4

Low carbon projects in Can Tho city
Table 6: Detail emission reduc on by projects in each category (ktCO2eq)

Ac on
1

Reduc‐
on(ktCO2)

Project

Sector

1‐01

Energy savings in factory

Industry

239.1

1‐02

Installa on high energy eﬃciency facili es

Industry

94.6

1‐03

Regional energy supply system

Industry

204.8

1‐04

Improvement of kiln and furnace technology

Industry

269.8

Green Industry

Total
2

Green Building

808.3

2‐01

Installa on of insulated glasses to commercial buildings

Commercial

8.5

2‐02

Installa on of insulated glasses to households

Residen al

10.1

2‐03

Introduc on of incen ve to low energy buildings

Commercial

2.0

2‐04

Introduc on of insula ng material to houses

Residen al

5.3

2‐05

Energy eﬃciency technology applied to buildings

Commercial

5.5

2‐06

Introduc on of solar water heater to commercial buildings

Commercial

27.9

2‐07

Introduc on of solar water heater to households

Residen al

44.9

Total
3

125.1

3‐01

Energy savings in commercial facili es

Commercial

25.2

3‐02

Conversion of street lights to LED ligh ng

Commercial

3.3

3‐03

High eﬃciency ligh ng in commercial buildings

Commercial

44.3

3‐04

High eﬃciency ligh ng in households

Residen al

26.2

3‐05

High eﬃciency air condi oners in commercial buildings

Commercial

21.1

3‐06

High eﬃciency air condi oners in households

Residen al

31.7

3‐07

Promo on of energy‐eﬃcient appliances (refrigerator and other appliances)

Residen al

111.8

3‐08

Promo on of energy‐eﬃcient appliances (cooking appliances)

Residen al

1.4

Energy Eﬃciency

Total
4

Clean Transport

265.1

4‐01

Promo on of eco‐driving with digital tachographs

Transport

8.6

4‐02

Smart traﬃc management

Transport

11.4

4‐03

Expansion of frequencies and routes of bus transporta on

Transport

3.2

4‐04

Development of Bus Rapid Transit (BRT)

Transport

1.6

4‐05

Introduc on of EV buses

Transport

10.3

4‐06

Introduc on of electric motorbikes

Transport

23.4

4‐07

Promo on of energy‐eﬃcient vehicles (cars for passenger)

Transport

26.3

4‐08

Promo on of energy‐eﬃcient vehicles (motorbikes)

Transport

63.9

4‐09

Promo on of energy‐eﬃcient vehicles (trucks)

Transport

87.1

Total
5

235.9

5‐01

Introduc on of photovoltaic power genera on to commercial buildings

Commercial

18.3

5‐02

Introduc on of photovoltaic power genera on to households

Residen al

2.6

Green Energy
Total

20.9

Total

1,434.55

Work procedure

ExSS tool

In order to iden fy the necessary ac ons, an “integrated mod‐eling” based on “back‐cas ng” approach is used.
The back‐cas ng approach sets a vision of the future society asa 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 theﬁrst step in the modeling work.
Socio‐economic informa on as well as environmental infor‐
ma on for the base year (2015) was collected and analyzed inorder to es mate current carbon emissions. Besides this, feasi‐
ble low carbon measures for Can Tho low carbon 2030 werealso collected.
For the future projec on, informa on is based on planneddevelopments, as the model es mates socio‐economic ac vity
levels including popula on, number of households, land area,transport demand and other 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 andprojects socio‐economic ac vity, energy demand and supply,
GHG emissions and emission reduc on by measures. Whileeach part of the tool is rela vely simple, it can describe whole
picture of future society as a LCS in a quan ta ve and con‐sistent manner with a greater ﬂexibility than many other mod‐els. In this simula on model, popula on is decided by demand
from outside of the region and rela onship of commu ng
with outside of the region. To determine output of industries,
input‐output approach is applied.
Passenger transportdemand is es mated from the popula on and freighttransport demand whereby it is a func on of output by
manufacturing industries. Other than driving force, ac vity
level of each sector, energy demand by fuels determined withthree parameters. One is energy service demand per driving
force, energy eﬃciency and fuel share. Diﬀusion of countermeasures changes the value of these parameters, and so GHG
emissions.

Team Informa on

Acronyms and Abbrevia ons

CAN THO PEOPLE COMMITTEEDAO Anh Dung
CAN THO CLIMATE CHANGE COORDINATION OFFICE (CCCO)CHAU Thi Kim Thoa
LUU Tan Tai
DUONG Thanh Van
RITSUMEIKAN UNIVERSITY (RU)

AIM
BaU
CC
CCAP
CCCO
EBT
ExSS
GDP
IEA
IGES
NDCs
IOT
ktCO2
RU
LCC
MHIR
NIES
SYB
toe

Koji SHIMADANGUYEN Thai Hoa*
INSTITUTE OF STRATEGY AND POLICY ON NATURAL RESOURCES& ENVIRONMENT (ISPONRE)NGUYEN Tung Lam
NATIONAL INSTITUTE FOR ENVIRONMENTAL STUDIES, JAPAN(NIES) & INSTITUTE FOR GLOBAL ENVIRONMENTAL STRATEGIES(IGES)
Junichi FUJINOMIZUHO INFORMATION AND RESEARCH INSTITUTE (MHIR)
Kazuya FUJIWARA

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

Feb 2018

6

Asia‐Paciﬁc Integrated ModelingBusiness as Usual scenario
Climate Change
Climate Change Ac on Plan scenario
Can Tho Climate Change Coordina on Oﬃce
Energy Balance Table
Extended Snapshot Tool
Gross Domes c ProductInterna onal Energy Agency
Ins tute for Global Environmental Strategies
Na onally Determined Contribu ons
Input‐Output Tablekilo‐ton Carbon dioxide
Ritsumeikan 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*Contact address:
NGUYEN Thai Hoa*: envi.jp@gmail.com
Chau Thi Kim Thoa: chauthoa@cantho.gov.vn
Junichi FUJINO: jfuji55@gmail.com