Tae Yong Jung
IGES, Japan
Dong Kun Lee
Seoul National University, Korea
So Won YoonSeoul National University, Korea
Eun Young KimSeoul National University, Korea
The The 1010th AIM International Workshopth AIM International Workshop
Activities in the Fiscal Year 2005 in Korea
March 10-12, 2005 ,NIES, Tsukuba, Japan
<2>
Table of Contents
I. AIM/Korea local Model: Transport
Sector in Seoul
- Introduction
- Input data projection
- Scenario (setting/Results)
- Policy Implication
II. AIM/Enduse (MAC) Model
- Introduction
- Analysis Results
- Policy Implication
1. Introduction
2. Input data projection
3. Scenario (setting/Results)
4. Policy Implication
AIM/Korea local ModelAIM/Korea local Model
<4>
1. Introduction I . AIM/Korea local Model
The Ministry of Environment (MoE) of Republic of Korea (ROK) enacted the Special Act on Metropolitan Air Quality Improvement in December 2003
The new legislation of the Special Act on Metropolitan Air Quality Improvement is expected to affect the whole emission profiles of air pollutants in this area with the introduction ofdiesel passenger cars.
To discuss the possible impact of this Special Act on emissions of sulfur-dioxide (SO2), nitrogen-oxide (NOx), carbon monoxide (CO), particulate matter (PM), and carbon dioxide (CO2) from the transport sector in Seoul.
To analyzes the various policy scenarios along with projections of key determinants in the transport sector in this area.
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2. Input Data Projection I . AIM/Korea local Model
0
2000000
4000000
6000000
8000000
10000000
12000000
1970
1973
1976
1979
1982
1985
1988
1991
1994
1997
2000
2003
2006
2009
2012
2015
2018
2021
2024
2027
2030
man woman
PopulationPopulation
0
100
200
300
400
500
600
0-4
age
5-9a
ge10
-14a
ge15
-19a
ge20
-24a
ge25
-29a
ge30
-34a
ge35
-39a
ge40
-44a
ge45
-49a
ge50
-54a
ge55
-59a
ge60
-64a
ge65
-69a
ge70
-74a
ge75
-79a
ge
abov
e 80
age
1980 man 1980 woman 2030 man 2030 woman
(thousand pop.)
<6>
2. Input Data Projection I . AIM/Korea local Model
GRDPGRDP VehicleVehicle
<7>
2. Input Data Comparison I . AIM/Korea local Model
Tokyo/Seoul/BeijingTokyo/Seoul/Beijing Vehicle(Seoul)Vehicle(Seoul)
0
100
200
300
400
500
600
1940 1950 1960 1970 1980 1990 2000
Vehi
cles
per
100
0 pe
ople
Japan
Tokyo
Tokyo Ward area
Korea
Seoul
China
Beijing
9
72
317
557
226
356
216
0
100
200
300
400
500
2002 2005 2008 2011 2014 2017 2020 2023 2026 2029
359.5
423.5
<8>
3. Scenario (Setting/Results) I . AIM/Korea local Model
Scenario Description
BAU Business-As-Usual (BAU) Scenario
BAU_IMP Scenario that the new emission standard is applied
D10Scenario that diesel passenger cars will take 10 %
shares in 2030
H30Scenario that new advanced technology vehicles will
take 30% shares in 2030
D10H30 (D10 + H30) Combined Scenario
<9>
Energy useEnergy use
3. Scenario (Setting/Results) I . AIM/Korea local Model
4,000
4,100
4,200
4,300
4,400
4,500
4,600
4,700
2001 2005 2009 2013 2017 2021 2025 2029
10^3TOE
BAU BAU_IMP D10 H30 D10H30
Energy use
<10>
NOxNOx
3. Scenario (Setting/Results) I . AIM/Korea local Model
10,000
12,000
14,000
16,000
18,000
20,000
22,000
24,000
26,000
28,000
2001 2005 2009 2013 2017 2021 2025 2029
TO N
BAU BAU_IMP D10 H30 D10H30
NOx
<11>
SO2SO2
3. Scenario (Setting/Results) I . AIM/Korea local Model
2,150.0
2,200.0
2,250.0
2,300.0
2,350.0
2,400.0
2,450.0
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
2027
2029
BAU BAU_IMP D10 H30 D10H30
TON SO 2
<12>
CO2CO2
3. Scenario (Setting/Results) I . AIM/Korea local Model
3,100,000
3,200,000
3,300,000
3,400,000
3,500,000
3,600,000
3,700,000
2001 2004 2007 2010 2013 2016 2019 2022 2025 2028
TON
BAU BAU_IMP D10 H30 D10H30
CO 2
<13>
4. Policy Implication I . AIM/Korea local Model
The new legislation of the Special Act on Metropolitan Air Quality Improvement will affect the emission profiles of air pollutants in this area especially with the introduction of diesel passenger cars.
The environmental policies and measures would shift to more market-oriented approaches rather than the conventional ‘command-and-control’type.
The relative energy prices between gasoline and diesel should be re-examined (energy tax issues).
Policy balance among sectors and policy integration is considered in more systematic way to achieve multi-targets and goals.
To boost the R&D of advanced technologies in the transport sector with financial and tax incentives will contribute to the formulation of overall framework for environmentally sustainable society .
1. Introduction
2. Analysis Results
3. Policy Implication
AIM/Enduse (MAC) ModelAIM/Enduse (MAC) Model
<15>
1. Introduction
Modeling the cost of abating greenhouse gases (GHGs) is crucial to demonstrate an economy’s ability to reduce GHG emissions cost-effectively with specific options.
The results of the analysis are presented as marginal abatement cost curves for 2030 in transport and residential sector.
Starting year : 2001
Ending year : 2030
Sector : transport sector, residential sector
Area : Korea
II . AIM/Enduse (MAC) Model
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Marginal Abatement Cost CurveMarginal Abatement Cost Curve
-15
-10
-5
0
5
10
15
0.0E+00 1.0E+12 2.0E+12 3.0E+12 4.0E+12 5.0E+12 6.0E+12
Reduction Potential
Mar
gina
l Cos
t
kg-CO2
Won/kg-CO2
- Transport sector
2. Analysis Results II . AIM/Enduse (MAC) Model
<17>
2. Analysis Results
Marginal CostMarginal Cost
- Transport sector
Won/kg-CO2
Technology_name
CPP(New) compact private passenger Cars(New)
SPP(CNG) small private passenger Cars(CNG)
JEEP(LPG_New) Jeeps(LPG_New)
BL15P(LPG_New) Buses less than 15 persons(LPG_New)
CPP(electricity) compact private passenger Cars(electricity)
CPP(fuel cell-meth)compact private passenger Cars(fuel cell-meth)
LPP(gasoline hybird)Large private passenger Cars(gasoline hybird)
LPP(full cell-meth)Large private passenger Cars(full cell-meth)
TL1(LPG_New) Trucks less than 1.0 tons(LPG_New)
MPP(CNG) Medium private passenger Cars(CNG)
MPP(gasoline hybrid)Medium private passenger Cars(gasoline hybrid)
MPP(electricity) Medium private passenger Cars(electricity)
BL15P(CNG) Buses less than 15 persons(CNG)
SPP(electricity) small private passenger Cars(electricity)
BM25P(CNG) Buses more than 25 persons(CNG)
Jeep(gasoline_New) Jeeps(gasoline_New)
BM15P(Electricity) Buses more than 15 persons(Electricity)
BM15P(gasoline_New)Buses more than 15 persons(gasoline_New)
SPP(full cell-meth) small private passenger Cars(full cell-meth)
Marginal_Cost
0.0000
2.0000
4.0000
6.0000
8.0000
10.0000
12.0000
CPP
(New
)SP
P(CNG
)
JEEP
(LPG
_Ne w)
BL15
P(LP
G_N
ew)
CPP
(ele
c tric
ity)
CPP
(fue l c
e ll-
meth
)
LPP(
gaso
line h
ybird
)
LPP(
full
c e ll-m
eth )
TL1(
LPG
_Ne w)
MPP
(CNG
)
MPP
(ga so
line
hybrid
)
MPP
(ele
c tric ity
)BL
15P(
CNG
)
SPP(
e lec tri
c ity
)
BM25
P(C
NG)
Jee p (g
a solin
e_Ne w)
BM15
P(El
ectri
c ity)
BM15
P(g a so
line_N
ew)
SPP(
full
c e ll-m
e th)
Won/kg-CO2
II . AIM/Enduse (MAC) Model
<18>
2. Analysis Results
Marginal CostMarginal Cost
- Transport sector
Won/kg-CO2
Marginal_Cost
-16.0000
-14.0000
-12.0000
-10.0000
-8.0000
-6.0000
-4.0000
-2.0000
0.0000
LPP(d
iesel_
New)
SPP(Dies
el)MPP(D
iese l)
CPP(LPG_N
ew)
SPP(LPG _N
ew)
LPP(L
PG_New
)MPP(L
PG_New
)TL
5 (New
)TM
5(New
)MPT(
New)
MPT(New
)BM25(
New)
SPP(New
)BM16P
(New
)MPP(N
ew)
Technology name
LPP(diesel_New) Large private passenger Cars(diesel_New)
SPP(Diesel) small private passenger Cars(Diesel)
MPP(Diesel) Medium private passenger Cars(Diesel)
CPP(LPG_New) compact private passenger Cars(LPG_New)
SPP(LPG_New) small private passenger Cars(LPG_New)
LPP(LPG_New) Large private passenger Cars(LPG_New)
MPP(LPG_New) Medium private passenger Cars(LPG_New)
TL5(New) Trucks less than 5.0 tons(New)
TM5(New) Trucks more than 5.0 tons(New)
MPT(New) Medium private Taxi(New)
MPT(New) Medium company Taxi(New)
BM25(New) Buses more than 25persons(New)
SPP(New) small private passenger Cars(New)
BM16P(New) Buses more than 16persons(New)
MPP(New) Medium private passenger Cars(New)
Won/kg-CO2
II . AIM/Enduse (MAC) Model
<19>
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
1,800,000
2,000,000
TM
5(N
ew
)
MP
Ta
xi(Ne
w)
TL
5(N
ew
)
SP
P(N
ew
)
MC
T(N
ew
)
MP
P(N
ew
)
MP
P(L
PG
_N
ew
)
MP
P(D
ies
el)
BM
25
P(N
ew
)
SP
P(D
ies
el)
SP
P(L
PG
_N
ew
)
BM
16
P(N
ew
)
CP
P(L
PG
_N
ew
)
LP
P(L
PG
_N
ew
)
LP
P(d
ies
el_
Ne
w)
10 6̂kg-CO2
2. Analysis Results
Reduction PotentialReduction Potential
- Transport sector
Technology_name
TM5(New) Trucks more than 5.0 tons(New)
MPTaxi(New) Medium private Taxi(New)
TL5(New) Trucks less than 5.0 tons(New)
SPP(New) small private passenger Cars(New)
MCT(New) Medium company Taxi(New)
MPP(New) Medium private passenger Cars(New)
MPP(LPG_New) Medium private passenger Cars(LPG_New)
MPP(Diesel) Medium private passenger Cars(Diesel)
BM25P(New) Buses more than 25persons(New)
SPP(Diesel) small private passenger Cars(Diesel)
SPP(LPG_New) small private passenger Cars(LPG_New)
BM16P(New) Buses more than 16persons(New)
CPP(LPG_New) compact private passenger Cars(LPG_New)
LPP(LPG_New) Large private passenger Cars(LPG_New)
LPP(diesel_New) Large private passenger Cars(diesel_New)
II . AIM/Enduse (MAC) Model
<20>
2. Analysis Results
Reduction PotentialReduction Potential
- Transport sector
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
BL15P
(CN
G)
MP
P(g
aso
line h
ybrid
)
TL1(L
PG
_N
ew
)
Jeep
(LP
G_N
ew
)
SP
P(e
lectric
ity)
SP
P(C
NG
)
SP
P(fu
ll cell-
meth
)
Jeep
(gaso
line_N
ew
)
MP
P(C
NG
)
BM
25P
(CN
G)
BL15P
(LP
G_N
ew
)
CP
P(N
ew
)
CP
P(fu
el c
ell-
meth
)
BM
15P
(gaso
line_N
ew
)
CP
P(e
lectric
ity)
LP
P(fu
ll cell-
meth
)
LP
P(g
aso
line h
ybird
)
MP
P(e
lectric
ity)
BM
15P
(Ele
ctric
ity)
10 6̂kg-CO2
Technology_name
BL15P(CNG) Buses less than 15 persons(CNG)
MPP(gasoline hybrid)
Medium private passenger Cars(gasoline hybrid)
TL1(LPG_New) Trucks less than 1.0 tons(LPG_New)
Jeep(LPG_New) Jeeps(LPG_New)
SPP(electricity) small private passenger Cars(electricity)
SPP(CNG) small private passenger Cars(CNG)
SPP(full cell-meth)small private passenger Cars(full cell-meth)
Jeep(gasoline_New) Jeeps(gasoline_New)
MPP(CNG) Medium private passenger Cars(CNG)
BM25P(CNG) Buses more than 25 persons(CNG)
BL15P(LPG_New) Buses less than 15 persons(LPG_New)
CPP(New) compact private passenger Cars(New)
CPP(fuel cell-meth)compact private passenger Cars(fuel cell-meth)
BM15P(gasoline_New)
Buses more than 15 persons(gasoline_New)
CPP(electricity)compact private passenger Cars(electricity)
LPP(full cell-meth)Large private passenger Cars(full cell-meth)
LPP(gasoline hybird)Large private passenger Cars(gasoline hybird)
MPP(electricity) Medium private passenger Cars(electricity)
BM15P(Electricity) Buses more than 15 persons(Electricity)
II . AIM/Enduse (MAC) Model
<21>
2. Analysis Results
Reduction PotentialReduction Potential
- Transport sector
0
10,000,000
20,000,000
30,000,000
40,000,000
50,000,000
60,000,000
2001 2030
GH
G E
mis
sion
Emission Reduction
10^6Kg-CO2 ▶ GHG Emission - 2001 : 29.998.45010^6- 2030 : 45,884,380 10^6
▶ Reduction 5,276,466 10^6kg-CO2
II . AIM/Enduse (MAC) Model
<22>
Marginal Abatement Cost CurveMarginal Abatement Cost Curve
kg-CO2
Won/kg-CO2
- Residential sector
2. Analysis Results
-10
-5
0
5
10
15
20
0.0E+00 1.0E+12 2.0E+12 3.0E+12 4.0E+12 5.0E+12
Reduction Potential
Mar
gina
l Cos
t
Won/kg-CO2
kg-CO2
II . AIM/Enduse (MAC) Model
<23>
2. Analysis Results
Marginal CostMarginal Cost
Won/kg-CO2
Won/kg-CO2
Marginal_Cost
-10
-5
0
5
10
15
20
WA
SH
IN
DH
ETW
1
DH
EA
T2
DB
OIL
4
TE
LE
V1
DH
EA
T1
DLIG
I2
DC
OM
2
DLIG
I5
DB
OIL
6
DLIG
I4
WA
SH
I2
TE
LE
V2
DH
EA
T3
DS
OR
AR
DZ
ISN
2
RE
FR
I2
DC
OO
L2
Won/Kg-CO2
Technology_name
WASHIN Regular washing mashine
DHETW1 LPG oven range(LPG)
DHEAT2 LNG heater(LNG)
DBOIL4 Boiler(LNG)
TELEV1 Regular Television
DHEAT1 Kerosene pan heater
DLIGI2 Fluorescent lamp(luminous)
DCOM2 Efficient computer
DLIGI5 Compact Fluoresen lamp(saving 2)
DBOIL6 Condensing Boiler
DLIGI4 Efficient fluorescent lamp(saving)
WASHI2 Efficient washing mashine
TELEV2 Efficient Television
DHEAT3 LPG heater(LPG)
DSORAR Solar energy
DZISN2 Insulation
REFRI2 Efficient Refrigeration
DCOOL2 High efficient air conditioner
- Residential sector
II . AIM/Enduse (MAC) Model
<24>
2. Analysis Results
Reduction PotentialReduction Potential
Reduction_Potential
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
DS
OR
AR
DZ
ISN
2
DB
OIL
6
RE
FR
I2
DLIG
I2
DC
OM
2
DLIG
I4
DLIG
I5
TE
LE
V2
DH
EA
T3
DH
EA
T2
DB
OIL
4
DH
ETW
1
WA
SH
I2
DC
OO
L2
DH
EA
T1
TE
LE
V1
WA
SH
IN
10 6̂kg-CO2
Technology_name
DSORAR Solar energy
DZISN2 Insulation
DBOIL6 Condensing Boiler
REFRI2 Efficient Refrigeration
DLIGI2 Fluorescent lamp(luminous)
DCOM2 Efficient computer
DLIGI4 Efficient fluorescent lamp(saving)
DLIGI5 Compact Fluoresen lamp(saving 2)
TELEV2 Efficient Television
DHEAT3 LPG heater(LPG)
DHEAT2 LNG heater(LNG)
DBOIL4 Boiler(LNG)
DHETW1 LPG oven range(LPG)
WASHI2 Efficient washing mashine
DCOOL2 High effiecient air conditionaer
DHEAT1 Kerosene pan heater
TELEV1 Regular Television
WASHIN Regular washing mashine
- Residential sector
II . AIM/Enduse (MAC) Model
<25>
2. Analysis Results II . AIM/Enduse (MAC) Model
Reduction PotentialReduction Potential
0
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
2001 2030
GH
G E
mis
sion
Emission Reduction
10^6Kg-CO2
▶ GHG Emission - 2001 : 14,396,73010^6- 2030 : 16,109,950 10^6
▶ Reduction 3,933,938 10^6kg-CO2
- Residential sector
<26>
3. Policy Implication II . AIM/Enduse (MAC) Model
Negative cost of reduction options implies that such options arefeasible without extra cost of implementation, The list of such options will be a good information for policy makers to launch specific action programs to mitigate GHG emissions in a specificsector.
In transport sector, most of options are to improve the energy efficiency in various vehicles. If high advanced technologies in this sector is considered, the potential of GHG reduction will be much bigger with much higher MAC.
Even if the potential of GHG reduction in transport sector is bigger, relatively, it is easier to do it in residential sector. This finding implies that some policies will be implemented in residential sector.