Impacts of Urbanization on CO2 Emissions
April 21, 2010
Shinji Kaneko
Graduate School for International Cooperation and
Development (IDEC),
Hiroshima University
1
Japan„s 1st National Workshop on Economics of
Climate Change and Low Carbon Growth
Strategies in Northeast Asia
Significance of urbanization to GHG emissions
• Global and regional GHG emissions from urbanization
– IEA estimated that cities contributed to 67% of global
primary energy and 71% of global energy related CO2
emissions in 2006 (IEA, 2008).
– CO2 emission from cities in China, USA and Europe are
reported as 85%, 80%(76%) and 69%, respectively (Dhakal,
2009; IEA, 2008; Parshall et al, in press).
– Some 81% of the projected increase in energy use in cities
between 2006 and 2030 comes from non-OECD countries
(IEA, 2008).
• Methodological challenges:
– Definition of urban/cities: population census
– Allocation of CO2: electricity
– GHG other than CO2
2
if urbanization is so important
• Does it make sense to incorporate urbanization into projection models for global GHG emissions, which are not explicitly dealing with urbanization but mostly sectoral approaches?
• What key parameters in current projection models are sensitive to different urbanization scenarios, while urbanization take place with other socioeconomic changes?
• How can we consistently and systematically link between diversified individual city development models and collective impacts of those cities?
• To what extent, climate policy interventions are possible to alter the processes of urbanization and city development, while priorities are essentially local for cities?
3
4
Scale-merit of Cities,
Increase return to
Scale, “Evolution”
Inflow of resettlement to Urban areas
from rural for job opportunitiesPrimary
Industries
Secondary Industries:
Industrialization
Tertiary Industries:Services, Commerce
Promote ICT, Decrease
in Transaction Costs
Backward
linkage effect
Forward
Iinkage effect
Urban Development Patterns and Issues for Low Carbon Society
Energy-saving in the
Industrial SectorAdvance of the
Factories, Active
Investment
Factories Exit,
Move to the Sub-
urban, Overseas
Smart Growth,
Compact City
Introduction of New
Energy Resources in
Urban Areas
Dematerialization of
Urban Areas
Financial Inflows,
Advance of the
Financial Institution
Expansion of
Urban Areas
Urban
Infrastructure
Development
Urban industrialization
Poverty and energy
Lock-in Effects
Long-term cost, urban management
Urban development pattern of East Asian mega-cities
(Passenger vehicle ownership)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.01
90
8
19
12
19
16
19
20
19
24
19
28
19
32
19
36
19
40
19
44
19
48
19
52
19
56
19
60
19
64
19
68
19
72
19
76
19
80
19
84
19
88
19
92
19
96
20
00
20
04
20
08
20
12
million unit
1
10
100
1,000
10,000
100,000
1,000,000person per unit
person per unit(Tokyo2) person per unit(Seoul)
person per unit(Beijing) person per unit(Shanghai)
Tokyo(2) Seoul
Beijing Shanghai
Tokyo Olympic (1964) Seoul Olympic (1988) Beijing Olympic (2008)
Shanghai Expo (2010)
Gap of per capita CO2 between city and country
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Per
cap
ita C
O2
emis
sion
(t-
CO
2/pe
rson
)
Tokyo Japan(CDIAC) Japan
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
Per
cap
ita C
O2
emis
sion
(t-
CO
2/pe
rson
)
Seoul Korea
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Per
cap
ita C
O2
emis
sion
(t-
CO
2/pe
rson
)
Beijing Shanghai China(CDIAC) China
Tokyo Seoul Beijing and Shanghai
Source:UrbanTansformation and carbon footprint of mega-cities in Japan and China, S. Kaneko, S. Dhakal, M. Ichihashi
Dynamics of collective impacts of cities
Source: UN Population Division/DESA, World
Urbanization Prospects: The 2007 Revision
8
Literature review and problems1. Urbanization more energy use and emissions (Cole
& Neumayer, 2004; Parikh & Shukla, 1995; York, 2007)
– Problem 1: overgeneralized (development stages are
ignored)
– Problem 2: mixed explanation (industrialization and
rising income)
2. Urbanization reduce energy use and emissions (Chen et al., 2008; Jenks et al., 1996; Liddle, 2004; Williams et
al., 2000)
– Problem 1: excessive concentrations more energy
use and emissions (Breheny, 2001; Rudlin and
Falk,1999)
– Problem 2: little supporting evidence (wealthy cities)
• No comprehensive analysis (aggregate and disaggregate
data) urbanization impacts remains inconclusive!
9
Descriptive analysis
(c) Upper middle-income
-15
5
25
45
65
85
105
125
145
19751978
19811984
19871990
19931996
19992002
Re
lati
ve
ch
an
ge
(%
)
[19
75
= 0
]
(b) Lower middle-income
-20
10
40
70
100
130
160
190
220
250
280
310
19751978
19811984
19871990
19931996
19992002
Re
lati
ve
ch
an
ge
(%
)
[19
75
= 0
]
(a) Low-income
-20
10
40
70
100
130
160
190
220
250
280
310
19751978
19811984
19871990
19931996
19992002
Re
lati
ve
ch
an
ge
(%
)
[19
75
= 0
]
(d) High-income
-15
5
25
45
65
85
105
125
145
19751978
19811984
19871990
19931996
19992002
Re
lati
ve
ch
an
ge
(%
)
[19
75
= 0
]
GNP/cap in
2003≤$765$766≤GNP/cap in
2003≤$3035
$3036≤GNP/cap in
2003≤$9385 GNP/cap in 2003>$9385
Calculated using the data from World Bank (2007) and IEA (2008a, 2008b)
10
Estimation results for total energy use and emission models (1975-2003)
Variable Total energy (1) Total energy (2) Total CO2 (3) Total CO2 (4)
Constant-18.833 ***(-18.51)
-20.001 ***(-21.07)
-17.074 ***(-11.48)
-18.438 ***(-12.10)
lnP1.539 ***(23.47)
1.586 ***(24.71)
1.116 ***(10.94)
1.125 ***(10.26)
lnA0.495 ***(20.09)
0.443 ***(18.04)
1.038 ***(21.26)
1.092 ***(20.52)
lnEI― ―
0.594 ***(13.15)
0.657 **(13.84)
lnSV0.068 ***(2.67)
0.049 **(1.99)
― ―
lnIND0.036 **(2.18)
0.047 ***(2.93)
0.240 ***(5.05)
0.213 ***(4.46)
lnURB-0.212 ***(-3.61)
―0.157 (1.39)
―
lnURB_H0.519 **(2.16)
0.549 *(1.78)
lnURB_UM(reference)
0.761 ***(3.58)
-0.926 ***(-3.47)
lnURB_LM-0.709 ***(-3.45)
1.353 ***(5.39)
lnURB_L-1.241 ***(-6.11)
1.193 **(4.20)
Countries 98 98 98 98
R2 0.992 0.993 0.979 0.979
11
Empirical results (aggregate level)(a) Urbanization elasticity of energy use and
CO2 (without consideration of income levels)
-0.212
0.157
-0.5
0.0
0.5
1.0
1.5
Ela
sticity (
%)
TPES CO2
(c) Urbanization elasticiy of CO2
(with consideration of income levels)
0.2670.427
-0.926
-0.377
-1.0
-0.5
0.0
0.5
1.0
1.5
Ela
sticity (
%)
Low-income Lower middle-income
Upper middle-income High-income
(b) Urbanization elasticiy of energy use
(with consideration of income levels)
-0.480
0.052
0.761 1.280
-0.5
0.0
0.5
1.0
1.5
Ela
sticity (
%)
Low-income Lower middle-income
Upper middle-income High-income
Urbanization -->more energy use, but the elasticity varies across development stages
Urbanization --> lower emissions at a higher stage of development
Cities as open economy are production hubs or final
destination of commodities?
12
Methodological framework: Carbon footprint
analysis with regional input-output energy model
City
Country
World
Import
Export
City
Country
World
Import
ExportEmbodied energy in import for final
consumption
Embodied energy in
import of intermediate
products
Embodied energy in import for
capital formation
Production
Consumers
Capital Stock
Embodied energy
in Export
Imported products
Local productsEnergy supply
from the earth
Industry j
Industry 1
Industry 2Industry 3 Industry n-2
Industry n-1
Industry n
1
n
i ij
i
X
jE
1
n
j ji
i
X
1
n
j j j ji
i
Q X
• Embodied energy and embodied CO2 emissions
• Indirect energy and CO2 emissions• Embodied energy and embodied CO2 emissions
• Indirect energy and CO2 emissions
CO2 Balance, million t-CO2
• Carbon footprint in Tokyo
– 6.54 (1990), 6.10 (1995), 4.92 (2000)
• Share of export in Tokyo
– 56.6% (1990), 55.0% (1995), 55.5% (2000)
• Change in total carbon emissions in Tokyo
– -6.26% (1990-1995), -17.46% (1995-2000)
0
200
400
600
800
1,000
1,200
Inflow Outflow Inflow Outflow Inflow Outflow
1990 1995 2000
Indirect Coal Oil Gas Consumption Capital Formation Export
0
20
40
60
80
100
120
140
Inflow Outflow Inflow Outflow Inflow Outflow
1990 1995 2000
Indirect Coal Oil Gas Consumption Capital Formation Export
Tokyo
Source: UrbanTansformation and carbon footprint of mega-cities in Japan and China, S. Kaneko, S. Dhakal, M. Ichihashi
CO2 Balance, million t-CO2
• Carbon footprint in Beijing
– 1.66 (1992), 1.88 (1997), 2.93 (2002)
• Share of export in Beijing
– 49.2% (1992), 29.8% (1997), 56.9% (2002)
• Change in total carbon emissions in Beijing
– +19.27% (1992-1997), +74.5% (1997-2002)
0
20
40
60
80
100
120
140
160
180
200
Inflow Outflow Inflow Outflow Inflow Outflow
1992 1997 2002
Indirect Coal Oil Gas Consumption Capital Formation Export
0
500
1,000
1,500
2,000
2,500
3,000
3,500
Inflow Outflow Inflow Outflow Inflow Outflow
1992 1997 2002
Indirect Coal Oil Gas Consumption Capital Formation Export
Beijing
Source: UrbanTansformation and carbon footprint of mega-cities in Japan and China, S. Kaneko, S. Dhakal, M. Ichihashi
Mitigation opportunities of cities
Indirect CO2 emissions/Direct CO2 emissions
– Tokyo: 6.54 (1990), 6.10 (1995), 4.92 (2000)
– Beijing: 1.66 (1992), 1.88 (1997), 2.93 (2002)
– London: 2.05 (London Sustainable Development
Commission, 2009)
– Sydney (households): 2.3 (Lenzen, et al, 2004)
– Brazilian cities (households): 1.6-1.9 (Cohen et al,
2005)
• Shifting from direct emissions to embodied
emissions15
Social benefits and virtual water for Beijing:
Water production and recycling cost and wastewater
treatment cost are considered.
16
VR (International): Imported virtual re-used water through imports from international regions;
VF(International): Imported virtual re-used water through imports from international regions;
VR (China): Imported virtual water through imports from nationalwide:
VF (China): Imported virtual freshwater through imports from nationwide:
RW: Physical re-used water use; and
FW: Physical freshwater use.
Note: 2004/2005’ is the water use estimated in 2004/2005 but based onwater input coefficients in 1996/1997.
0
100
200
300
400
500Billion m3
VR(International) 6.206286122 47.22182421 28.06825643
VF (International) 7.746790209 57.37808472 30.3972457
VR (China) 31.49205975 146.0746984 79.57781411
VF (China) 45.13206159 168.8260478 85.72245917
RW 3.676962341 10.16432826 5.244750504
FW 3.116605919 6.611075838 2.069892148
1996/1997 2004/2005' 2004/2005
17
Hanoi(Vietnam)Jakarta
(Indonesia)
Dhaka
(Bangladesh)
Survey Time Sep. 2009 Dec. 2009 Feb. 2010
Method Household Survey (Face to Face Survey)
Sample SizeMigrants:475
Non-migrants: 459
Migrants: 446
Non-migrants: 418
Migrants: 503
Non-migrants:502
(Note) Survey conducted for slum dwellers in Jakarta and Dhaka.
(Jakarta: 100 households for migrants, 100 for non-migrants. Dhaka: 100
for migrants, 101 for non-migrants.)
Questionnaire Item
Migration Original residential place, reasons for migration, time of migration, desire to future migration
Household
AttributesHousehold Income, Household size, House size, Housing type
Energy Electricity, Gas(LPG), Water, Kerosene, Brown coal briquettes, Gasoline etc.
Electric Appliance Refrigerator, Air Conditioner, Laundry Machine, Mobile phone, Car, Motorcycle etc.
Personal Attributes Sex, Age, Occupation, Education, Commuting mode/time, Personal Income
Collecting micro evidences on household GHG
emissions before and after migration to the cities
Dhaka and Hanoi
18
0
50
100
150
200
250
300
350
400
450
Dhaka Hanoi
Household monthly income (USD/month)
Before
After
0
20
40
60
80
100
120
140
Dhaka Hanoi
Monthly GHG emission (CO2-equiv)
Before
After
0
1
2
3
4
5
6
Dhaka Hanoi
Family size (persons)
Before
After
Estimating Elasticity, Marginal Effect (dummy)
• If household moved to megacities, their household GHGs emissions
increases at 89.91 kg CO2-equiv. in Hanoi, 71.88kg CO2-equiv. in Dhaka.
• When household income increases at 1%, GHGs increases at 0.31% in
Hanoi, 8.86*10-2% in Dhaka.
• (Hanoi) When the number of household member increases at 1%, the GHGs
emissions increases at 0.22% 19
Total Household Income (Taka,
2009 price/year)8.86*10
-2 ***
Number of Household Members
(number)7.10*10
-2
Number of Rooms in House
(numbers)0.74 ***
Dummy (Dhaka=1, Non-
Dhaka=0)71.88 ***
*discrete change of dummy variable from 0 to 1
Dhaka
Total Household Income (VND,
2009 price/year)0.31 ***
Number of Household Members
(number)0.22 ***
Size of the House (m3) 0.28 ***
Dummy (Hanoi=1, Non-
Hanoi=0)*89.91 ***
*discrete change of dummy variable from 0 to 1
Hanoi
Hanoi
Penetration of Home Appliances in Dhaka, Hanoi and Jakarta.
Jakarta
Dhaka• Examine how the resettled households change the
diffusion rate of home appliances before and after the resettlement;• Overall, the ownership ratio has increased after the
migration. Sharp increase is observed in Dhaka.
• Diffusion rate is highest in Hanoi, followed by Jakarta, and Dhaka. Since the Indonesia is higher in terms of per capita GDP than Hanoi, the rate is lower.
• The Urban-rural migration accelerates the ownership of home appliances, but that trend differs among cities.
0%
20%
40%
60%
80%
100%
ElectricLights
TV Refre-gerator
Washingmachine
PC Electricfan
Aircondi-tioner
Mobilephone
Before
Now
0%
20%
40%
60%
80%
100%
ElectricLights
TV Refre-gerator
Washingmachine
PC Electricfan
Aircondi-tioner
Mobilephone
Before
Now
0%
20%
40%
60%
80%
100%
ElectricLights
TV Refre-gerator
Washingmachine
PC Electricfan
Aircondi-tioner
Mobilephone
Before
Now
Some concluding remarks
• Little is known the relation between urbanization/urban growth and GHG emissions and therefore more researches needs to be accumulated.
• Classification and typology of urbanization and/or urban development processes from climate change perspectives is necessary: i.e. urban form, industrial structure and transformation, population density, geographical location and local climate, existing energy system and buildings etc.
• Development stages are important element to consider dynamic relation between urban development processes and GHG emissions.
• Careful examinations might be needed:
– on the possibility of leap frogs
– optimal range of urban densities for both each urban system (transportation, housing, energy supply etc) and their integrated system.
21
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