KIT – The Research University in the Helmholtz Association

INSTITUTE OF INDUSTRIAL PRODUCTION (IIP)Chair of Energy Economics (Prof. Dr. W. Fichtner)

www.kit.edu

THE EFFECTS OF URBANIZATION ON ENERGY CONSUMPTION AND GREENHOUSE GAS EMISSIONS IN ASEAN COUNTRIES: A DECOMPOSITION ANALYSISPhuong Khuong Minh, Russell McKenna, Wolf Fichtner15th IAEE European Conference 2017, Vienna, Austria.

Chair of Energy Economics2 27.09.2017

Contents

1. Introduction to ASEAN2. Motivation & Objectives3. Methodology4. Results5. Conclusion and Outlook

Chair of Energy Economics3 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

1. Introduction to ASEANASEAN – Association of Southeast Asian Nations consists of 10 countries

ASEAN EU World

Areamillion km2

4.4 4.4

Populationmillion people

625 508

GDP annual growth rate %

4.9 1.9 3.5

% Urban population 52.2 71.3 60.2

Urban population annual growth rate %

3.0 0.9 2.1

Energy intensitykoe/$

0.174 0.111 0.157

CO2 emission annual growth rate %

6.1 -5.6 0.8

Resources: World Bank database – 2016, IEA - 2016

Chair of Energy Economics4 27.09.20171. Introduction 2. Motivation +

Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

2. Motivation & Objectives

Level No. of

studies

year Results Method Variable

1989-

2000

2000-

2010

2010-

now+ - ~ Re De Other GDP EC Em EI

Other

s

Multi-country 16 4 4 8 9 2 5 13 0 3 17 15 6 3 1

Country/Sector 26 3 9 14 13 4 9 19 3 10 23 22 1 4 9

Issues:1. Comparison between countries & sectors2. Partly conflicting results3. Methodology limitations4. Variable selection : Urbanization definition,

Emission & Energy intensity

Literature review of the studies for relationship between Energy Consumption, Emission & Urbanization

Acronyms: “+”: increase effect, “-”: decrease effect, “~”: unclear effect. Re: Regression; De: Decomposition; EC: Energy consumption; Em: Emission, EI: Energy Intensity

Objectives:1. Estimate the urbanization effect and other

contributions effects on energy consumption & emission by new approach

2. Compare the effects in multi-level in ASEAN3. Propose some suggestions for policy makers

Chair of Energy Economics5 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

Effect Emission-factor Energy-mix Energy intensity Economicstructure

Activity Demographic

Symbol ∆𝐶𝐶𝑒𝑒𝑒𝑒𝑒𝑒 = ∆𝐶𝐶𝑖𝑖𝑖𝑖𝐸𝐸𝑖𝑖𝑖𝑖

∆𝐶𝐶𝑒𝑒𝑖𝑖𝑚𝑚 = ∆𝐸𝐸𝑖𝑖𝑖𝑖𝐸𝐸𝑖𝑖

∆𝐶𝐶𝑖𝑖𝑖𝑖𝑖𝑖 = ∆𝐸𝐸𝑖𝑖𝑉𝑉𝑉𝑉𝑖𝑖

∆𝐶𝐶𝑠𝑠𝑖𝑖𝑠𝑠 = ∆𝑉𝑉𝑉𝑉𝑖𝑖𝐺𝐺𝐺𝐺𝐺𝐺

∆𝐶𝐶𝑎𝑎𝑎𝑎𝑖𝑖 = ∆𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐷𝐷 ∆𝐶𝐶𝑑𝑑𝑒𝑒=∆De

3. MethodologyIDA – Index Decomposition Analysis

0%

20%

40%

60%

80%

100%Comparison the proportion of 2 types of urban

% Urban 1 % Urban 2

• C: Emission

• E: energy consumption

• VA: Value added

• De: Demographic

• i: fuel (oil, gas, coal)

• j: sector (commercial, industrial,

transportation, residential

1st - Population

2nd - Urban 1 –Population in urban areas

3rd - Urban 2 –No. of non-agriculture employees

Chair of Energy Economics6 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

4. Results: different effects

-200

-150

-100

-50

0

50

100

150

1996

2000

2005

2010

2013

Mill

ion

ton

CO

2

Philippines

∆Cemf ∆Cmix ∆Cint ∆Cstr ∆Cact ∆Cde

Emission-factor

Energy-mix

Energy intensity

Economicstructure

Activity Demographic

Brunei - - - - + +Cambodia + + + + + +Malaysia +/- +/- + -/+ + +Myanmar - - - + + +Philippines - - + + + -Thailand - +/- + -/+ + +Vietnam - + - + + +

“+”: increasing effect, “-”: decreasing effect, “+/-”: change from increasing to decreasing

“-/+”: change from decreasing to increasing

Different effects on CO2 emission from 1995-2013

Chair of Energy Economics7 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

4. Results: different effects by sector

Emission-factor Energy-mix Energy intensity Economicstructure

Activity Demographic

Commercial + + - + + -Industrial - - +/- + + -Transportation - + + + -Residential + - + + -

Different effects on CO2 emission by sectorial in Philippines from 1995-2013

“+”: increasing “-”: decreasing “+/-”: change from increasing to decreasing “-/+”: change from decreasing to increasing

Chair of Energy Economics8 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

4. Results: Normalized effect of Urban 1 on Energy Consumption

EC Brunei Cambodia Malaysia Myanmar Philippines Thailand Vietnam

Commercial + + + + + + ++

Industrial ++ ++ +++ ++ ++++ ++ +++

Residential ++++ ++++ ++++ ++++ ++ +++ ++++

Transportation +++ +++ ++ +++ +++ ++++ +

Chair of Energy Economics9 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

4. Results: demographic effects

Population Urban 1 Urban 2

Brunei 1.00 1.33 1.40

Cam 1.00 1.48 3.53

Malay 1.00 1.81 1.55

Myan 1.00 2.24 3.41

Phil 1.00 0.82 1.86

Thai 1.00 3.49 3.25

Viet 1.00 2.57 4.66

Average demographic effect on Energy Consumptionfrom 1995-2013

Multi-country comparison

- Urban 1 & 2 effect more than Population

0

1

2

3

4

5

6

7

10% 20% 30% 40% 50% 60% 70% 80%

Rat

e of

urb

an 1

impa

ct o

n en

ergy

co

nsum

ptio

n %

Rate of urban 1 - %

Brunei Myanmar Viet Malay Thai Phil Cam

Sectorial comparison across countries

On Energy consumption- Strongest effect in residential sector- Weakest effect in commercial sector

On CO2 Emission- Strongest effect in transportation- Weakest effect in residential sector

- Notable effect in Cambodia & Philippines- Constant effect in Vietnam & Malaysia

- Urban 1 & 2 increase their effects in the first phrase and decrease gradually after that

- Urban factors co-variate with energy consumption

Chair of Energy Economics10 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

4. Critique of the methodology

-300%

-200%

-100%

0%

100%

200%

300%

-50% -30% -10% 10% 30% 50%

Demographic change

Eint change E act change E de change

Sen

sitiv

ity a

naly

sis

y = 282.56x + 67.373R² = 0.1652

0

50

100

150

200

250

0.17 0.19 0.21 0.23 0.25 0.27 0.29 0.31 0.33

Urb

an 1

Energy consumption

Energy & Urban 1 relationship

Linear (Energy & Urban 1 relationship)

Every 1% variation in the input could change- Activity effect: about -5.5%- Demographic effect: 5.5%- Energy intensity effect: 0%

Regression example Advantages of decomposition:- Deal with non-linear relationship- Comparison in multi-level across countries- Assess the hidden effects as energy structure & economic

structure

Disadvantages of decomposition:- Collecting & synchronizing data- Choosing appropriate decomposition analysis- Problem with 0 value in datasets

Pro

s &

Con

of t

he m

etho

d

Chair of Energy Economics11 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

5. Conclusion & OutlookDemographic effect:

The effects on Energy Consumption & Emissions: Urban 2 > Urban 1 > population Urbanization increases Energy Consumption & EmissionsUrbanization has the greatest impact on

Transportation emissionResidential energy consumption

Other effects on Energy & Emissions:Increasing factors: Activity, Economic StructureDecreasing factors: Energy intensity: most progress in industrial

Suggestions for Policy-makers:Consider urbanization instead of population as a energy consumption & emission problemFocus efforts on finding an optimal solution to decentralized, efficient energy system for urban citiesFocus efforts on decreasing transportation emission

Outlook:Consider different urbanization indicators (population and/or urban density)Improve database by applying bottom-up approaches Using decomposition combined with regression to forecast energy demand

Chair of Energy Economics12 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

1. Introduction to ASEANASEAN – Association of Southeast Asian Nations consists of 10 countries

ASEAN EU World

Areamillion km2

4.4 4.4

Populationmillion people

625 508

GDP annual growth rate %

4.9 1.9 3.5

% Urban population 52.2 71.3 60.2

Urban population annual growth rate %

3.0 0.9 2.1

Energy intensitykoe/$

0.174 0.111 0.157

CO2 emission annual growth rate %

6.1 -5.6 0.8

Resources: World Bank database – 2016, IEA - 2016

Chair of Energy Economics13 27.09.2017

Thank you for attention

Feedback & Questions Phuong, Khuong Minh. IIP - KIT

Contact: Email: Khuong.phuong@partner.kit.edu

Tel: +49 721 608 – 44400

Chair of Energy Economics14 27.09.2017 Phuong, Khuong Minh IIP - KIT

Chair of Energy Economics15 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

1. Introduction to ASEAN

CO2 emission from 1995 to 2013. Unit: million ton CO2

CO2 – Commercial

CO2 – Industrial

CO2 – Transportation

CO2 - Residential

Urban percentage

21

22-34

35-38

39-44

45-54

55-77

78-100

0102030405060

0

50

100

150

mill

ion

ton

CO

2

mill

ion

TOE

Vietnam

CO2 EC

20

22

24

26

050

100150200

mill

ion

ton

CO

2

mill

ion

TOE

Philippines

CO2 EC

Chair of Energy Economics16 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

3. Methodology & Database

Phuong, Khuong Minh IIP - KIT

Sector Activity Energy data Emission data Demographic

Residential Number of

households – National

population censuses

report

Fuel, renewable,

electricity - IEA 2015

CO2 emission from fuel

combustion - IEA, 2016

Population,

Urban 1,

Urban 2 – World Bank

2015

Commercial Added Value, GDP –

World Bank 2015 &

ADB database 2015Industrial

Transportation Fuel – IEA 2015

Database: 7 countries from 1995 - 2013

Chair of Energy Economics17 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

4. Results: Normalized effect of Urban 1 on Emissions

Brunei Cambodia Malaysia Myanmar Philippines Thailand Vietnam

Commercial +++ ++ ++ + +++ ++ +

Industrial ++++ + ++++ +++ + +++ ++++

Residential ++ +++ + ++ ++ + ++

Transportation + ++++ +++ ++++ ++++ ++++ +++

Chair of Energy Economics18 27.09.2017

Energy consumption

Phuong, Khuong Minh IIP - KIT

EC Brunei Cambodia Malaysia Myanmar Philippines Thailand Vietnam

Commercial + + + + + + ++Industrial ++ ++ +++ ++ ++++ ++ +++Residential ++++ ++++ ++++ ++++ ++ +++ ++++Transportation +++ +++ ++ +++ +++ ++++ +

Chair of Energy Economics19 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

ASEAN status

Phuong, Khuong Minh IIP - KIT

0.02.04.06.08.0

10.012.014.0

BRN IDN KHM LAO MMR MYS PHL SGP THA TMN VNM

%

Average GDP growth rate in ASEANs

95-00 00-05 05-10 10-14

0

2

4

6

8

95-99 00-04 05-09 10-14 AVERAGE

3.77 3.89 3.99 3.32 3.744.71

6.10 5.91 5.85 5.54

%

Average GDP growth rate over the World & ASEAN from 1995-2014

World ASEAN

World Bank, 2015

86.5 51.8 33.6 19.1

2.4

3.3 3.32.9

0.00.51.01.52.02.53.03.5

020406080

100

high income Upper middleincome

Lower middleincome

Low income

%%

ASEAN

% urban population urban growth rate

73.28 58.56 39.16 31.20

1.251.83

2.45

4.01

0.01.02.03.04.05.0

high income Upper middleincome

Lower middleincome

low income0

20

40

60

80

% %

The World

% urban population urban growth rateWorld Bank, 2015

Chair of Energy Economics20 27.09.2017 Phuong, Khuong Minh IIP - KIT

Chair of Energy Economics21 27.09.2017 Phuong, Khuong Minh IIP - KIT

1995 2000 2005 2010 20131995 2000 2005 2010 2013

1995 2000 2005 2010 2013

1995 2000 2005 2010 2013

1995 2000 2005 2010 2013

1995 2000 2005 2010 2013

1995 2000 2005 2010 2013

Chair of Energy Economics22 27.09.2017Phuong, Khuong Minh IIP - KIT

- IEA -

0

2

4

6

8

elec oil gas

0123456

elec coal oil gas

02468

10121416

elec coal oil gas

0

1

2

3

4

5

6

elec coal oil gas

CO2 intensity 1995-2013. Unit: kgCo2/Toe

Chair of Energy Economics23 27.09.2017

Urbanization effect on Energy Consumption

Phuong, Khuong Minh IIP - KIT

0

2

4

6

8

10

12

1 1.1 1.2 1.3 1.4

Rat

e of

impa

ct %

Population (1996 = 1)

Brunei Myanmar Viet Malay Thai Phil Cam

0

1

2

3

4

5

6

7

8

9

0% 20% 40% 60% 80% 100%

Rat

e of

impa

ct %

Rate of urban 1 - %

Brunei Myanmar Viet Malay

Thai Phil Cam

0

2

4

6

8

10

12

14

16

18

20

0% 20% 40% 60% 80% 100%

Rat

e of

impa

ct %

Rate of urban 2 - %

Brunei Myanmar Viet Malay Thai Phil Cam

Population Urban 1 Urban 2

Brunei 1.00 1.33 1.40

Cam 1.00 1.48 3.53

Malay 1.00 1.81 1.55

Myan 1.00 2.24 3.41

Phil 1.00 0.82 1.86

Thai 1.00 3.49 3.25

Viet 1.00 2.57 4.66

Chair of Energy Economics24 27.09.20171. Introduction 2. Motivation + Objectives 3. Methodology 4. Results 5. Conclusion + Outlook

Effect Emissionintensity

Energy mix Energy intensity Economicstructure

Activity Demographic

Symbol

3. Methodology selection

Phuong, Khuong Minh IIP - KIT

IDA – Index Decomposition Analysis

Limitation RegressionData Require large data sets

Difficult to deal with unbalanced data (missing data & different criterial)

Method Complex in defining & considering the relationship between dependent and independent variablesNot a strong tool in comparisonOverlooks the effect of structure (i.e. energy structure & economic structure)