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Modeling LCS to Identify Modeling LCS to Identify Trend-Breaking OptionsTrend-Breaking Options
Junichi Fujino ([email protected])NIES (National Institute for Environmental Studies)
COP12 and COP/MOP2 Side Event, “Global Challenges
Toward a Low-Carbon Society (LCS) Through Sustainable Development (SD)”
November 8, 2006 in Nairobi, Kenya
脱温暖化2050
http://2050.nies.go.jp
Source: NASA
North Pole Ice in Sep.
1978
1998 Himalayan Glaciers
Back-casting from future target world
2020 20502000
Long
-term
targ
et y
ear
Rele
ase
of
AIM
resu
lt
Technology development,socio-economic change projected by historically trend
Forecasting
Back-casting
Normative target world
Reference future world
Service demand change
by changing social behavior,
lifestyles and institutions
Mitigation Technology
developmentRequired Policy intervention and Investment
required intervention policy and measures
En
vir
on
men
tal p
ress
ure
Check
ing
year(2
01
5)
Check
ing
year(2
02
5)
Req
uir
ed
in
terv
en
tion
3. We need“Trend Breaks”
to realize visions
2. We need“Visions”
1.Target may be tough
50% reductionsIn the world
Vision A Vision B
Vivid, Technology-driven Slow, Natural-oriented
Urban/Personal Decentralized/Community
Technology breakthroughCentralized production /recycle
Self-sufficientProduce locally, consume locally
Comfortable and Convenient
Social and Cultural Values
As for LCS visions, we prepared two As for LCS visions, we prepared two different but likely future societiesdifferent but likely future societies
2. We need “Visions”Akemi Imagawa
Efficient useNew energy
InfrastructureEco-lifestyle
Super high efficiency air-conditioner
Stand-by energy reduction
LED lightPV on roof
Fuel cell cogeneration
Heat insulation house
Hot water supply by heat pump or
solar heating
HEMS (Home Energy
Management System)
Eco-life Navigation
COP=8for cooling
EnvironmentEducation
10-20% reduction
66% reduction oflighting demand
60% reduction of heat demand
33% reduction COP=5 for warming10-20% reduction
3-4kW
Depict Future Image: Residential sector in 2050
3. We need “Trend Breaks”
-The “Top Runner Program” has -stimulated competition and innovation in the market, -diffused existing technologies, and -enhanced industrial competitiveness
-It created “win-win” situation and virtuous cycle.
Top Runner Program: Efficiency Improvement
(Source) JEMA (2002)
Annual electricity consumption
per volume (kWh/L)
Internal cubic volume (L)
1981 1991 2001
651.3 941.6 331.5Overall electricity consumption per
refrigerator (kWh)
Annual electricity consumption
per volume (kWh/L)
Internal cubic volume (L)
1981 1991 2001
651.3 941.6 331.5Overall electricity consumption per
refrigerator (kWh)
Fig: Energy efficiency of refrigerator
3. We need “Trend Breaks”
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055
CO
P (
Coe
ffic
ient
of
perf
orm
ance
)
Best
Average
Worst
Historical
Projected energy efficiency improvement: Projected energy efficiency improvement: Air-conditioners for cooling and heatingAir-conditioners for cooling and heating
AIST
MOE
METI METI
3. We need “Trend Breaks”
AIM (Asia-Pacific Integrated Model) for Japan LCS scenarios
Energy supply & demand
：Model
：Output of model
Macroeconomy
Stock Activity
Populationand
householdmodel
Residentialsector
Commercialsector
Transpor-tationsector
Industrialsector
Energybalance
table
Pop
ulat
ion
Labo
r
Service
Mat
eria
l sto
ck &
flow
mod
el
Energy supplysector E
nerg
ysu
pply
m
odel
Efficiency
Bui
ldin
g d
ynam
ic m
odel
Env
iron
men
tal o
ptio
n da
taba
se, B
otto
m-u
p en
gine
erin
g m
odel
Passenger Trns.demand model
Freight Trns.demand model
Inte
r-se
ctor
and
mac
ro e
cono
mic
mod
el
Household Prd.& lifestyle model
Residential energyservice model
Commercial energyservice model
Industrial production model
Stock
Preference of household
Production amount
Investment
EnergySnapshot
Tool：Data flow Check consistency!
0
20
40
60
80
100
120
140
2000 2010 2020 2030 2040 2050
Pop
ulat
ion
(Tho
usan
d)
80-60-7940-5920-390-19
0
10
20
30
40
50
60
20
05
20
10
20
15
20
20
20
25
20
30
20
35
20
40
20
45
20
50
Millio
n
Wooden detached Non-wooden detached
Wooden apartment Non-wooden apartment
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
Number of Dwelling by typePopulation by age
Transportation demand by mode
Bus Aviation Pass.car Maritime Railway Walking & Bicycling
Main driving forces to reduce CO2 emissions Category
Society ・ reduce raw material production
・ decrease numbers of population/householdActivity
Industry
・ Production efficiency improvement EE
・ Increase rate of natural gas use CI
Residential
・ Use of high insulation system・ Control of home energy system
SD
・ High efficiency hair-conditioner, hot water heater, lighting system
・ Fuel cell system, Photovoltaics on the roof
EE
CI
Transportatio
n
・ Replacement of working/living place・ Public transportation
SD
・Motor-driven mobiles: Electric Battery Vehicles, Fuel Cell Battery Vehicles
EECI
Ene
rgy supply
・ Nuclear energy・ Use of electricity in night time, Electric storage・ CO2-free hydrogen supply
CI
・ Advanced fire plant + CCS・ Hydrogen supply using fossil fuel + CCS
CCS
23MtC
27MtC
16MtC
8MtC
21MtC
11MtC
9MtC
30MtC
41MtC
30MtC
11MtC
amount*
* CO2 reduction amount compared with the emissions in 2000
amount
ServiceDemand
(SD)40
EnergyEfficiency
(EE)78
CarbonIntensity
(CI)79
CCS30
Possible trend-breaking options Possible trend-breaking options to achieve to achieve 70% reductions toward 2050 in Japan (Scenario A)70% reductions toward 2050 in Japan (Scenario A)
Dem
and side
Supply
side
CCS: Carbon Capture Storage
Factor decomposition of CO2 emission reduction Factor decomposition of CO2 emission reduction in 2050 Japan using Kaya Identityin 2050 Japan using Kaya Identity
-4%
-30%
-7%
-28%
-69%
-11%
-18%
-30%
-14%
-73%
-80%-60%-40%-20%0%
D
E/D
C'/E
C/C'
Total
vs 2000's
2050 A 2050 B
C
C
E
C
D
EDC
C： CO2 emissions
D： Activity
E： Energy demand
C’： CO2 emissions (excluding energy conversion sector)
C： CO2 emissions
D： Activity
E： Energy demand
C’： CO2 emissions (excluding energy conversion sector)
Service demand improvement
Energy efficiency improvement in end-use sectors
Fuel mix change in end-use sectors
Fuel mix change inEnergy conversion
Cross
)/(
)/(
)/(
)/(
)/(
)/(
CC
CC
EC
EC
DE
DE
D
D
C
C
We support country-wise LCS modeling through SD for Asia-Pacific and the world
- We have continued AIM Training Workshops since 1995 -
India China Thailand Korea Malaysia Indonesia BrazilTaiwan,
China USA JapanRussiaSouth Africa
16-20 Oct 2006 at NIES
Vision A Vision B
Vivid, Technology-driven Slow, Natural-oriented
Urban/Personal Decentralized/Community
Technology breakthroughCentralized production /recycle
Self-sufficientProduce locally, consume locally
Comfortable and Convenient
Social and Cultural Values
We qualify and quantify possible future We qualify and quantify possible future
LCS visions using AIM modelsLCS visions using AIM models
Akemi Imagawa
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