EMF 22: Climate Policy Scenarios for Stabilization and in Transition,
Tsukuba International Congress Center (Epochal)
Tsukuba, Japan
December 12-14, 2006

Modeling inJapan “LCS toward 2050” project
Yuzuru Matsuoka
Kyoto University"EMF22 Tsukuba Workshop"

脱温暖化
2050

Dec. 13, 2006

1

Japan Low Carbon Society Scenarios toward 2050
[FY2004-2006(+2years), Global Environmental Research Program, MOE]
Study environmental options toward low carbon society in Japan
Techno-Socio Innovation Study

Green buildings
Self-sustained city
Decentralized services

Eco awareness
Effective communication
Dematerialization

Transportation
systemIT-society

EE improvement
Structure change
New energy
Life-stylechangeGHG reduction target

Middle-term
Target year

Loge-term
Target year

2010

2050

Intervention
scenario

2020（eg. 60-80% reduction by 1990 level）

2000

Long-term
Scenario
Development
Study

Next generation vehicles
Efficient transportation system
Advanced logistics

Energy saving Tech. innovationBaU scenario

1990

Development of socioeconomic scenarios,
evaluating countermeasures with socialeconomic-technology
models

GHG emission

Urban structure

Advisory board：
advice to project

Reduction
Target study

Effective

Valid
5
3
1
-1

EquitySuitable

Evaluate feasibility of
GHG reduction target

5 teams
60 Researchers

Propose options of long-term global warming policy"EMF22 Tsukuba Workshop"

Dec. 13, 2006

2

Focusing points of LCS modeling study
1. Support to develop LCS scenarios which satisfy theprescribed emission targets as well as the related
environmental, economical and social targets.
targets
2. The scenarios are concrete, plausible, quantitative andconsistent with technology, economy and sociality.
3. However, the LCS may be far from the current trend, andin order to reach them, the models can be useful tosearch “Trend Breaking Interventions” and to estimate
their effects from the viewpoint of technological,
environmental, and economical aspects.
aspects"EMF22 Tsukuba Workshop"

Dec. 13, 20063

Models to support LCS study
Element models;
1) Snapshot models;Quasi steady Computable General Equilibrium (CGE) model
Energy technology bottom-up models, energy supply modelHousehold production/lifestyle modelTransportation demand model
2) Transition models;Population and household model
Building dynamics model
Econometric type macro-economic model
Integration models;Snapshot Integration Tool (SSI)
Backcasting Model for transient control (BCM)"EMF22 Tsukuba Workshop"

Dec. 13, 2006

4

Element models forJapan low carbon society project
Scenario,
Storyline

Transition ModelHousehold production/Lifestyle model(identify effects of consumer behavior
considering change of age/type ofhousehold/ environment-oriented
preferences on energy service demand,transportation trip demand byeconometric methods and estimate
impacts of intervention scenarios)

Energy supply and demand balance
model (adjusting seasonal/daily energybalance of electricity, heat, andhydrogen supply and demandconsidering infrastructuredevelopment)
Energy technology bottom-up model (technology
selection of energy supply, conversion,
consumption using
econometric/engineering/management methods)

General equilibrium model (investigate feasibility,
economic impacts considering generalequilibrium of approx. 40 services including
energy at service and labor market with supportof other models)Dec. 13, 2006

Trajectory

Passenger/Freight Transportation
demand model (parameter estimate oftrip generation, modal share using
statistics on person trip, traffic flow,
freight flow and others. Service
demand estimation assuming
technology and behavior change)

Archive data set of Energy Balance, Environmental Burden, and
Cost

Archive data set of Socio-economic change

Infrastructure/building dynamic model (econometric/engineering bottom-up approach forresidential/nonresidential housing, construction and retirement of energy supply facilities)

Macro-economic model (econometric model for parameter estimate of supply-side potential
productivity change, IS balance and calculation of BAU scenario)

Population dynamic model (cohort model including birth/death, inter-regional/national migration)

Archive data set of Technology development and diffusion

Technology development schedule for energy use, production, and consumption (R&D plan,
expert judgment)

Socio-economic scenario, Intervention scenario"EMF22 Tsukuba Workshop"

Snap shot model

5

Using these models, and in order to describe theplausible, feasible, and consistent future, we areproceeding the study in the following steps
1. Description of narrative scenarios and storylines,
supported by project members, the advisory board,interviews to experts.
2. Construction of socio-economic visions in 2050
quantitatively, which satisfy 60-80% reduction of CO2
emission constraints.
3. Identification and evaluation of required interventions(Trend Breaking Interventions) that induce the society to
LCS.
"EMF22 Tsukuba Workshop"

Dec. 13, 2006

6

As for LCS visions, we prepared two
different but likely future societies
Vision A “Doraemon”

Vision B “Satsuki and Mei”

Vivid, Technology-driven

Slow, Natural-oriented

Urban/Personal

Decentralized/Community

Technology breakthroughCentralized production/recycle

Self-sufficient
Produce locally, consume
locally

Comfortable and Convenient

Social and Cultural Values

Akemi
Imagawa"EMF22 Tsukuba Workshop"

Doraemon is a Japanese comicseries created by Fujiko F.
Fujio. The series is about arobotic cat named Doraemon,
who travels back in time fromthe 22nd century. He has apocket, which connects to thefourth dimension and acts likea wormhole.

Satsuki and Mei’s House
reproduced in the 2005
World Expo. Satsuki and Mei
are daughters in the film "My
Neighbor Totoro". They lived
an old house in rural Japan,
near which many curious andmagical creatures inhabited.

Dec. 13, 2006

7

Narrative description of Scenario A
Technical progresses in the industrial sectors are considerably high because of vigorous
R&D investments by the government and business sectors. The economic activities as awhole are so dynamic that average annual per capita GDP growth rate is kept at the levelof 2%. The other reasons for such high economic growth are high rates of consumption inboth business and household sectors.
The employment system has been drastically changed from that in 2000 and equal
opportunities for the employment have been achieved. Since workers are employed basedon their abilities or talents regardless of their sex, nationality and age, the motivation of
the worker is quite high in general.
As many women work outside, the average time spent for housekeeping has decreased.
Most of the household works are replaced by housekeeping robots or services provided byprivate companies. Instead, the time used for personal career development has increased.
The new technologies, products, services are positively accepted in the society.
Therefore, purchasing power of the consumer is strong and upgrade cycles of thecommodities are short.
Household size becomes smaller and the number of single-member households has
increased. Multi-dwellings are preferred over detached houses, and the urban lifestyle ismore popular than the lifestyle of countryside.

"EMF22 Tsukuba Workshop"

Dec. 13, 2006

8

Narrative description of Scenario B
Although average annual growth rate of per capita GDP is approximately 1%, people
can receive adequate social services no matter where they live. Volunteer works orcommunity based mutual aid activities are the main provider of the services. Since
the levels of medical and educational service in the countryside have drastically
improved, continuous migration of population from city to countryside has been
observed.
The number of family who own detached dwellings has increased. The trend is
especially prominent in the countryside. The size of the houses and the floor area
per houses has also increased with the increasing share of detached houses.
The ways people work have also changed. The practice that husbands work outside
and wives work at home is not common anymore. In order to avoid the excessive workof the partner, the couples help each other and secure the income according to theirlife plan. Housework is shared mainly among family members, but free housekeeping
services provided by local community or social activity organizations are also available.
As a result of the changes in lifestyle, the time spent within family has increased.
The time spent on hobby, sports, cultural activities, volunteer activities, agricultural
works, and social activities has also increased.

"EMF22 Tsukuba Workshop"

Dec. 13, 2006

9

Quantify impacts of social economic changes to energy
service demand with models

Energy Snapshot Tool (t)"EMF22 Tsukuba Workshop"

Dec. 13, 200610

On these two scenarios, we allocate possible trend-breaking options"EMF22 Tsukuba Workshop"

Dec. 13, 2006

11

Population and Household Model• Drastic change is projected in Japan’s population structure by 2050.
Downturn in birthrate, depopulation and aging will continue until 2050, andthey affect greatly the future vision.
• A cohort component model for population, a household headship rate modelfor household types, with spatial resolution of provinces, land-use types
and climate zones and five family types was developed, and is used toanalyze effects of depopulation and changes in family composition on therealization of LCS.
Total population(Period T-1)
[Sex, Age]

Adjustment

Life table[Sex, Age]

Consistency

Province-wiselife table[Sex, Age]

Province-wise
Population(Period T-1)
[Sex, Age]

Adjustment

Fertility rate
[Age]
Consistency

International
Net-migration(Japanese)
Total population(Period T)[Sex, Age]International
net-migration(Outsider)

Adjustment
Consistency

Headship rate
[Sex, Age, Family]

Total number ofHousehold(Period T)[Family-wise]"EMF22 Tsukuba Workshop"

Province-wise
fertility rate
[Age]

: Data flow
: Exogenous variable: Endogenous variable

Province-wisenet-migration[Sex, Age]

Province-wiseheadship rate
[Sex, Age, Family]
Province-wiseclimatic division
share
Province-wiselanduse Cls.
share

Flowchart of PHM

Landuse Cls.-wise
Population(Period T)[Sex, Age]

Province-wise
Population(Period T)[Sex, Age]

Climatic zone
-wise household(Period T)[ Family]

Province-wisehousehold(Period T)[Family]Dec. 13, 2006

12

Projection Japan population and households in
scenario A

120

age

100

8060-79

80

40-59
20-39
0-19

60
40
20

100%

Type of household (%)

80%

Others60%

ParentChildren
One-Person

40%

Couple-Only

20%

0

CoupleChildren

year
Population (million)
Aged population ratio (%)
Average number of household
Single-person households (%)"EMF22 Tsukuba Workshop"

2000
126.9
17.4
2.71
27.6

A
94.5
53.7
2.19
42.6

2050

2045

2040

2035

2030

2025

2020

2015

2010

2000 2010 2020 2030 2040 2050

2005

0%
2000

Population(Million)(Thousand)

140

2050

B
100.3
35.8
2.38
35.1
Dec. 13, 2006

13

Projection of urbanization

Population (mill.)

140

Forest-rural

120

Forest-central city

100

Forest-Metropolitan
Agricultural-rural

80

Agricultural-central city
Agricultural-metropolitan

60

Urban-Regional

40

Urban-Central

20

Urban-Core

0

Urban-Metropolitan

2000

Rural

ABABABABABABABABABABAB
2010

year

2020

2030

2040

2050

2000

Population (million)
126.9
Urban population(%)
78.1
Agricultural area population(%) 8.2
Forest area population(%)
13.7"EMF22 Tsukuba Workshop"

Urban

A
94.5
84.2
7.1
8.7

2050

B
100.3
76.7
8.5
14.8
Dec. 13, 2006

14

Building Dynamics Model• Enhancement of building insulation is very effective countermeasures.
60% of the heating demand from the residential sector can be cut down,
if appropriate insulation systems are installed. Besides, configuration ofbuildings in urban and rural area affects social energy efficiency greatly.
• In order to take accountthese factors, a model ofbuilding dynamics (BDM)
was developed.

Number of dwelling stock(year T-1)

"EMF22 Tsukuba Workshop"

Number ofhouseholds

Population andHousehold Model

Number of new dwellings(year T)

Share by type ofbuilding

Survival rat• It is a cohort model with aspatial resolution ofclimate zones, four heatinsulation levels, four
residential building types,
and six commercial
building types.

Unoccupied rate

[Region, types of buildings,
construction material, insulation level,
construction year]

Share by region
Share byconstruction material

Survived number of dwellings(year T)
[Region, types of buildings,
construction material,
insulation level, construction year]

Share byinsulation level

Number of new dwellings(year T)
[Region, types of buildings,
construction material, insulation level]

Renovation rate

Number of dwelling stock(year T)
[Region, types of buildings,
construction material,
insulation level, construction year]

Householdproduction andlifestyle model
Bottom-up
engineeringmodel：endogenous variable：exogenous variable

Flowchart of BDM (residential)
Dec. 13, 2006

15

Projection of residential building stock byinsulation level60

1999 standard

Million houses

50

1992 standard
1980 standard

40

Projection
based onenhanced
policyWithout insulation

30

1999 standard

20

1992 standard

10

1980 standard

0

Projection
based onpresent
policyWithout insulation
2003

2008

2013

2018

"EMF22 Tsukuba Workshop"

2023

2028

2033

2038

2043

2048

Dec. 13, 2006

16

Passenger Transportation Demand Model• Many effective countermeasures exist related with transportation. Modal shift
from private motor vehicles to mass transit systems, urban planning towards
compact cities, transportation substitution with diffusions of teleworking andvirtual communication systems and so on.
• Passenger Transportation Demand
Model (PTDM) can simulatetransportation demand associatedwith changes in population
distribution, people’s activity
patterns, modal shares and average
trip distances.
• The demands in this model are
divided into two types,1)Intra-regional transportation
within the daily living area,2)Inter-region transportation
between the daily living areas,

Macro Economic Model

Employment[Attribute]
License[Attribute]

Population[Attribute, Area]

Population[Attribute]

Trip Generation Coefficient[Attribute, Day, Area, Objective]

Trip Generation Coefficient[Attribute, Objective, Mode]

Modal Share(%)[Day, Area, Mode]

Modal Share(%)[Attribute, Objective, Mode]

Average Trip Distance(km/Trip)[Day, Area, Mode]

Average Trip Distance(km/Trip)[Mode]
Intra-Area Transportation(person-km)[Mode]

Inter-Area Transportation(person-km)[Mode]：Data Flow

Net-Total
Conversion ratio：Endogenous Variables：Exogenous Variables
Passenger Transportation[Persons-km]

and they are calculated separately.
Intra-Area Transportation"EMF22 Tsukuba Workshop"

Population Dynamic Model

Population[Attribute, Area]

Inter-Area Transportation

Dec. 13, 2006

17

Passenger Transportation Demand Model (2)Scenario A
1,200,000

450,000
400,000

1,000,000

350,000
800,000

300,000
250,000

600,000

200,000
400,000

150,000
100,000

200,000

50,000
0

0
2000

2005

2010

2015

2020

2025

2030

2035

2040

2045

2050

2000

2005

2010

2015

2020

2025

2030

2035

2040

2045

2050

Inter-region transportation demand by mode Intra-region transportation demand by modeof transportation (mil. person-km)
Buses

Aviationof transportation (mil. person-km)
Pass.cars

Maritime

Railways

W alk&Bike• Coupled with population decrease, and intensive decreasing policy of average trip
distance, such as the compaction of neighborhood communities causes significant
decrease of intra-regional transportation demand.
• In addition, the share of railways transportation will increase rapidly due to thepromotion of modal shift from car to train.

"EMF22 Tsukuba Workshop"

Dec. 13, 2006

18

Freight Transportation Demand Model
This model simulates freight transportation volume associated withchanges in industrial structure, material density of commodities,
transportation distance, and modal share.
Inter-sector andmacro economic model“Air transport”“Surface transport”
Production and import[JPY](product)Transport generation ratio[tonne/JPY](product)
Modal share [%](product, mode,
distance)

Production and import ofhigh-value added products[JPY]

Distribution of transport distance[%](product, distance)

Representative transport distance[km](distance)

Transportation volume[tonne-km](product, mode)

Transportation volume[tonne-km]

Transportation volume[tonne-km](mode)"EMF22 Tsukuba Workshop"：Data Flow
：Endogenous Variables：Exogenous Variables

Dec. 13, 2006

19

Freight Transportation Demand Model (2)8,000,000

8,000,000

7,000,000

7,000,000

6,000,000

6,000,000

5,000,000

5,000,000

4,000,000

4,000,000

3,000,000

3,000,000

2,000,000

2,000,000

1,000,000

1,000,000
0

0
1980

1990

2000

A

1980

B

1990

2000

A
2050

2050
AG

MI

ME

CH

IL

IM

B

SP

OT

Freight Vehicle

Railway

Maritime

Transportation volume in tonnes by productTransportation volume in tonnes by mode

(1000 tonne)(1000 tonne)

8,000,000

700,000

7,000,000

600,000

6,000,000

500,000

5,000,000
400,000
4,000,000
300,000

3,000,000

200,000

2,000,000

100,000

1,000,000

0

0
1980

1990

2000

A

B

～100km100～300km

2050
300～500km

500～750km

750～1000km

1000km～

1980

1990

2000

A

B
2050

Small Freight Vehicle
Railway

Large Freight Vehicle
Maritime

Transportion volume in tonnes by transport

Transportion volume in tonne-km by mode

distance (1000 tonne)(mil. tonne-km)"EMF22 Tsukuba Workshop"• By year 2050, in
tonne-km, thevolumes of freighttransport are
0.91 and 0.79
times, because of
the decrease oflong-distancetransport of basic
materials.
• On the contrary.
short distancetransport does
not decrease somuch.

Dec. 13, 200620

Inter-sector and Macro Economic Model• Projecting macro economic activity, sectoral production, and also taking account thecountermeasures proposed in the individual models, we developed “Inter-sector and Macro
Economic Model (IMEM)”, which consists of a sequential dynamic general equilibrium
module and a macroeconomic module.
• The model can be used to estimate national and sectoral economic activities, the impactsof energy efficient and dematerialization technologies in industrial sectors, developmentof informatization, and increase of service sectors.
Macroeconomic module

energyoutput coefficient
on non-energy

input

data in
2000

commodity demand

import&export②⑪"EMF22 Tsukuba Workshop"

SNA

IO tablein 2000⑩⑥
production and income

outputext. trnsact.
account

input coefficient
on non-energy⑥

output matrix

assumption⑧①

V matrixin 2000

tech

account ofinc. & expnd.

tech&preference

input matrix

energy balance table(output)

nonenergy①

CO2⑥
production and cost

output coefficient ①
on energy
tech

⑫

⑦

balancecondition

fixed capitalformation
matrix in 2000
tech②

capital profile
in sector⑨
productionsocialfixed capital stock
matrix⑪
capital stock⑩

compensationof cap. goods

③

⑫

②

commodity supply

capitalintermediatedemand

cap.
goods

④

labor

final demand sector

energy balance table(input)value nonadded energy

energy balancetable in 2000⑤

investment

energytech⑦

economic
growthproduction sector①

final cons

Input coefficienton energy

CGE module① production function② commodity market③ capital market④ labor market⑤ calculation of GDE⑥ expenditure and income
in production sector⑦ expenditure and income
in household andgovernment⑧ assumption of import andexport⑨ fixed capital stock
matrix⑩ investment goods market⑪ capital stock⑫ CO2 emissions

Structure of Inter-sector Module
Dec. 13, 2006

21

300

0

<Sectors>

Agriculture
Forestry
Fishing
Coal mining
Crude oil & NG mining
Other mining
Food products & beverages
TextilesPulp, paper & paper products
Publishing & printing
Chemical materials
Chemical products
Petroleum products
Coal products
Non-metallic mineral
Pig iron & crude steel
Other steel products
Non-ferrous metal
Fabricated metal products
MachineryElec.machine, equip. & supplies
Transport equipment
Precision instruments
Other manufacturing
Construction
Thermal power plant
Non-thermal power plant
Town gas
Water supply
Wholesale & retail trade
Finance & insurance
Real estate
Railway transport
Road transport
Water transport
Air transport
Other transport
Communications
Public service activities
Other service activities

Tri. yen at 2000 price

Examples of the projected sector productions
in year 2050

350

2000
2050 A
2050 B

250

200

150

100

50

"EMF22 Tsukuba Workshop"
Dec. 13, 200622

Integration tools for quantitative,
transparent discussion toward a LCS
z Snapshot Integration Tool (SSI)･Reconciliation of the outputs of element models and technology
development･Calculation of energy balance table, CO2 emission table, as wellas various national social and economic accounts･Excel/GAMS based.
z Backcasting Model for transient control (BCM)･Combining the equations and parameters in the element models,and formulating the problem with an inter-temporal multisector optimum problem･Control variables: schedules of investment, necessary
technology development etc.
･With the model, required cost to reach the target world,
trade-off between the today’s effort, feasibility and thefuture burdens to attain target societies･GAMS based.
"EMF22 Tsukuba Workshop"

Dec. 13, 2006

23

Snapshot Integration Tool (SSI)- energy part <Base year><Target year><Base year><Target year>

Service demandService demand

Electricity demand

Electricity demandService share

Service share

Energy efficiency

Energy efficiency

Energyconsumption

Energyconsumption

CO2 emission

IND

RES

CO2 emission

COM TR_P TR_F

MixtureMixtureOwn useOwn use

Loss

Loss

Generation byenergy input

Generation byenergy input

Efficiency
Energyconsumption

Energy Balances
CO2 emission tables

Ctl
CO2 emission factor"EMF22 Tsukuba Workshop"

Energyconsumption

PWR

CO2 emission factor

EB
EB
EB
EB

Efficiency

Factor Analysis（D, E/D, C/E, C’/C）

Factors: Endogenous variables: Exogenous variables

Dec. 13, 200624

Quantification of Scenario A and B in 2050
year
Population
Household

unit

2000

Mil.
Mil.

127
47

2050
A
B
94 (74%)100 (79%)
43 (92%)42 (90%)

2.7

2.2

Average number of person
per household
GDP
Share of production
primary
secondarytertiary

2.4

Tril.JPY

538

1059 (197%)

693 (129%)

%
%
%

1.8%
39.9%
58.4%

1.0%
32.3%
66.7%

1.4%
35.4%
63.3%

model
Population and Household
modelInter-sector and Macro
Economic Model
Building dynamics Model &Office floor space

Mil.m

2

1654

2078 (126%)

1739 (105%)Inter-sector and Macro
Economic Model

Travel Passenger volume
Private car
Public transport
Walk/bycycle

bill. p・km
%
%
%

1297
53%
40%
8%

1016 (78%)
27%
62%
8%

794 (61%)
53%
34%
13%

Freight transport volume

bill. t・ km

578

525 (91%)458 (79%)100

142 (142%)

113 (113%)

Industrial production index
Steel production

Mil.t

107

40 (37%)40 (37%)

Etylen production

Mil.t

8

4 (50%)

4 (50%)

Cement production

Mil.t

82

40 (49%)40 (49%)Paper production

Mil.t

32

16 (50%)27 (85%)

Transportation demandmodel & Inter-sector andMacro Economic Model

Inter-sector and Macro
Economic Model( %) is a percentage compared with year 2000

"EMF22 Tsukuba Workshop"

Dec. 13, 2006

25

Energy and CO2 emission in 2050
year
Emission
CO2(MtC)

1990

2000

284.0

311.5

CCS

2050
Scenario A

Scenario B

97.7

(34%)

84.3

(30%)

-30.0

Generation

284.0

311.5

127.7

(45%)

84.3

(30%)

EnergyPrimary

446.0

520.7

388.3

(87%)

301.7

(68%)

(MTOE)

Final

292.0

380.2

205.5

(70%)

217.0

(74%)

Fossil fuel80.4%

dependency

49.9%

44.6%

GDP (tril.JPY)

467.9

537.5

1058.9(226%)

693.4(148%)

Population (Mill.)

123.6

126.9

94.4

(76%)

100.3

(81%)

( %) is a ratio with 1990

"EMF22 Tsukuba Workshop"

Dec. 13, 2006

26

Projected energy structures
0

100
100

-

2000
2000

200
200

400
400

500
500
Mtoe

Freight
Res. Serv. Pass.
Trans.Trans.

Industry

Final
2050
energy ScenarioA
2050 A (CM)demand2050
structure Scenario
B

300
300

Energy demand reduces
by structural change ofdemand, control
and efficiency
improvement

2050 B (CM)

-

2000
2000

Primary2050
energy Scenario
2050
A (CM)
A
supply2050
structureScenario
2050 B (CM)B

100 Residential
200
Industry

Coal

Oil

Freight
Passenger
400
500
Transportation
Transportation

Gas
Biomass

Solar/
Wind

Nuc

Hydro

Centralized style

Decentralized style
Micro grid
Coal

"EMF22 Tsukuba Workshop"

300
Service

Oil

Gas

Biomass

NuclearHydro Solar/Wind
Photo/Wind
Dec. 13, 2006

27

Projected CO2 emission structure0

By sector

50 100 150 200 250 300 350 MtC
Industry

2000
2050
Scenario A
2050
Scenario B

By fuel

2000

45%

16%

14% 14% 9%3%Others

70%

74%

Coal

28%
2050
Scenario A

Pass. FreightRes. Serv.Trans.Trans.

Oil

58%

Gas

14%

35% 44% 21%

2050
Scenario B
24% 35% 41%"EMF22 Tsukuba Workshop"

Dec. 13, 2006

28

Factor decomposition of CO2 emission reduction in 2050
E C′ CC = D× × ×
D E C′

C：CO
C：CO22 emissions
emissions
D：Activity
D：Activity
E：Energy
E：Energy demand
demandC：CO22 emissions
emissions (excluding(excluding energy
energyC’’：CO
conversion
conversion sector)
sector)ΔC ΔD Δ( E / D) Δ(C ′ / E ) Δ(C / C ′)
+
=
+
+
C
D
( E / D)(C ′ / E )(C / C ′)5%
Industry A

-5%
-5%

-15%
-7%

-2%

-25%
-10%

-9%
-5%
-6%
B
0%-5% -2% -7%
Residential A-14%-1%-2% -7%-3% -14%B
2% -6%
Commerce A 0%-8%-11%
B 1% -4% -3% -4% -10%
Passenger Transport A-1% -8% -1%-2% -13%-1% -5%-7% -1% -15%
B
Freight transport A
0%-5% -1%
-1%
-7%
-1%
-2% -6% 0%B-9%Total A
-3%
-31%
-10%
-18%
B

-35%

-45%

-55%

-65%

-75%

-14%

-69%
-73%

-24%
-5% -26%
Carbon intensity (energy conversion side change, C/C')
Carbon intensity (demand side change, C'/E)
Energy intensity (E/D)
Driving force (D)

-6%

-28%
-31%

% is a value compared with year 2000’s total emission"EMF22 Tsukuba Workshop"

Dec. 13, 2006

29

Possible trend-breaking options to achieve
70% reductions toward 2050 in Japan (Scenario A)

EE・Increase of natural gas use

CI・Use of high insulation system
・Control of home energy system

SD・High efficiency air-conditioner, hot water
heater, lighting system
・Fuel cell system, Photovoltaics on the roof

EE
CI

Transportation
Energy supply

・Replacement of working/living place・Public transportation

SD・Motor-driven mobiles: Electric Battery Vehicles,
Fuel Cell Battery Vehicles

EE
CI

・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

27MtC
16MtC
8MtC
21MtC
11MtC
9MtC
30MtC

* CO2 reduction amount compared with the emissions in 2000
"EMF22 Tsukuba Workshop"

11MtC

41MtC

30MtC

Demand side

・Production efficiency improvement

23MtC

Supply side

Residential

Activity

amountServiceDemand(SD) 40Soci Indusetytry・Reduce raw material production
・Decrease number of population

amount*Energy Efficiency(EE) 78

Category

CarbonIntensity (CI)79

Main driving forces to reduce CO2 emissions

CCS
30

CCS: Carbon Capture Storage

Dec. 13, 200630

Concluding my presentation…
What we are now doing;
1. Describing Japan’s social and economic structure
in 2050
2. Identifying CO2 emission reduction measures andquantifying their effects in order to realize 6080% reduction, which are consistent with the
future visions,And plan to do soon are;
1. Establishing Japan’s roadmaps toward LCS,
including social, economical and technologicalinnovation strategy,
2. Capacity building and supporting activity for Asian
countries on developing individual countries’ ownroadmaps toward LCS
脱温暖化
2050

"EMF22 Tsukuba Workshop"

Dec. 13, 200631

"EMF22 Tsukuba Workshop"

Dec. 13, 2006

32

Backcasting model (BCM) forJapan low carbon society project
Back-casting model

Element models
Description andquantification of
dynamic characteristics
and changing
mechanism of social /energy services with abottom-up approach
Road maps of Energy
technologies, andproduction / consumption
technology progressTransition models
z Population / household
dynamic modelz Macro-economic modelz Infrastructure / building
dynamic model
Snap shot modelsz Household production /lifestyle modelz Passenger / freighttransportation demandmodelz Energy supply anddemand balance modelzEnergy technology bottomup model"EMF22 Tsukuba Workshop"（multi-sector dynamic optimization model)
Identification of the optimization path of infrastructure andcapital investment in order to maximize cumulative social
utility （present discounted value, final consumption leveland social service level） from 2005 to 2050 under thefollowing balancing equations:
9Demand-and-supply balance of goods and services
9Balance of energy services and energy demand-and-supply
9Demand-and-supply balance of labor
9Balance of international payment
9Balance of infrastructure, buildings, and production capital stock
Aggregated transition dynamics of social/technological factors

Supported with the element models, we parameterize thefollowing dynamic characteristics as a pertinent investment
year, marginal abatement cost or indices of difficulty, anduse them as control variables for feasibility analysis.
Energy supply sector

Residential/commercial sectorz Distributed energy potential andacceptance levelz CCS potential and acceptance levelz Speed of technology progressz Speed of supply-infrastructuredevelopmentz Change of consumption propensity
z Speed of household production
efficiency improvementz Speed of energy technology efficiency
improvement

Goods/service production sectors

z Speed of transport service efficiency
improvementz Structure changing speed ofproduction sectorz Changing speed of input-output
coefficientz Changing speed of labor-input
coefficientz Speed of energy technology efficiency
improvement

Transportation sector

Quantify specificmeasures forrequiredtransition control
to achieve low
carbon society
Analyze requiredconditions for trend
breaks in eachsector, to identify
the feasibility ofachieving the CO2
reduction target

z Speed of trip generation and modalchangez Speed of technology efficiency
improvementz Speed of infrastructure development

Dec. 13, 2006

33

Passenger transport demand reduction by scenario
Transportation demand (billion person-km)
0200

AviationLight car

400

600

800

1,000

1,200

1,400

1,600

Maritime

Railways

2000

BaU

Scenario A

Trend
breaking

2000

BaU

Scenario B

Trend
breaking

Buses"EMF22 Tsukuba Workshop"

Small car

Large carCommercial vhc.

Dec. 13, 2006

34

Two types of models were required to support
scenario development(1) Snapshot model
The first group focuses on describing LCS in a certain future(e.g. year 2050), concretely, quantitatively, and consistently
with physical, economical, technological laws.
We call the models, “Snapshot models”. Examples are;• Household Production and Lifestyle model• Passenger and Freight transportation demandmodel• Energy supply and demand balance model• Energy technology bottom-up model• Inter-sector model• Simplified snapshot model"EMF22 Tsukuba Workshop"

Dec. 13, 2006

35

Two types of models were required to support
scenario development(2) Transition model
The second group focuses on the dynamics and trendtransition of the society, economic system, and thetechnological system. We call models of the group, “Transition
models”. Examples are;
• Population and household transition model• Material Stock and Flow model• Building Dynamics model• Macro Economic model
We link the “Snapshot models” and the “Transition
models” to construct future LCS visions, and to
identify/evaluate required interventions for realizing
LCS.

"EMF22 Tsukuba Workshop"

Dec. 13, 2006

36

Relationship among element models"EMF22 Tsukuba Workshop"

Dec. 13, 200637

Forecasting from now and Backcasting fromfuture prescribed/normative world

RequiredSufficient calibrationin order to reflect
historical trends

Mitigation
Technology
development"EMF22 Tsukuba Workshop"

Backcasting2020

Long-term target year

Service demandchangeby changing social
behavior, lifestyles
and institutions

Checking
year

2000

Reference
futureworld(BaU)

Trend breaking
Intervention and
Investment

Identification ofrequired intervention by
iterative method or
dynamic optimization
model
Release of
the study
resultEnvironmental pressure

Projection with expected
technology development,socio-economic change

Forecasting

Normative
target world

2050

Dec. 13, 2006

38

Besides these models, we prepared
Menoco Tool
• “Menoco” means “back of theenvelope” type calculation in
Japanese. It was developed on MS
Excel, and calculates an energybalance table, a CO2 emission table
It is suitable for communication
among stakeholders to design LCS.

Service Demand[Service]

Share of Energy[Service, Energy]

EnergyImprovement[Service, Energy]

Energy consumption
in Industrial sector[Service, Energy]
Energy consumption
in Residential sector[Service, Energy]

Environmental Options Database (EDB)・A database system which stores information ofrelated activities.
・Activity includes energy technology, institution,
infrastructure, lifestyle, and other aspects, andnarrative description and quantitative value areentered in the database.
・An engineering bottom-up type energy andemission calculator is attached to this database.
・The EDB serves as an exchange platform between
the each sectors experts and the scenario team.

Energy Balance
Table[Sector, Energy]

Energy consumption
in Commercial sector[Service, Energy]

CO2 Emission
Factor[Energy]

Energy consumptionin Transportation sector[Service, Energy]
Electricity
demandEnergy consumptionin Transformation andPower Generation[Energy]

CO2 Emission
Table[Sector, Energy]: Data flow
: Exogenous variable: Endogenous variable

Flowchart of the “Menoco”"EMF22 Tsukuba Workshop"

Dec. 13, 2006

39

図９． 70％削減を実現する対策オプションの検討［シナリオ B： 2050 年］
削減量 *・Reduce of final demand by material saturation
活動量変化
・ Reduce raw material production
・Decrease numbers of population and houshold

54MtC

Residential

・Production efficiency improvement

エネ効率改善・Increase of natural gas and biomass use

炭素強度改善・High insulation building
・ Efficient energy control by HEMS

サービス需要
削減

16MtC

36MtC

炭素強度改善・HSolar electricity 戸建住宅を中心とした太陽光発電による電力自立
・燃焼系暖房・厨房機器でのバイオマス利用拡大
・太陽熱温水器の普及

8MtC
6MtC

Transport- Energy
supplyation

・歩いて暮らせるコンパクトなまちづくりの促進
・歩行者や自転車利用促進のためのインフラ整備（駐輪場・自転車専用通路）
・バイオマスハイブリッド自動車の普及
・電力負荷調整のための IT技術の発達
・バイオマス発電
・電力需要の低下

サービス需要削減
エネ効率改善炭素強度改善

需要
削減
65
エネ
効率
改善
37

28MtC
3MtC
15MtC
28MtC

炭素
強度
改善
126

炭素強度改善主に供給部門の対策

エネ効率改善・Air conditionar and hot water heater
・照明の普及with heat pump

削減量

主に需要部門の対策

Indus
Society try

Main driving forces to reduce CO2 emissions

34MtC* CO2削減量は2000年における排出量からの削減量を示している。

"EMF22 Tsukuba Workshop"

Dec. 13, 200640

Household Production and Lifestyle Model• CO2 emissions from the residential sector have been increasing with the growing numberof households and people’s lifestyle changes. The trend is expected to continue with the
spreading use of ICT appliances and housekeeping robots.
• People’s preference of goods and service, the efficiency improvements of householdproduction are greatly affects the realization of the LCS.
• The Household
Time use
Production and Lifestyle
DisposalHistorical trend
income:Data flow
scenario
Model(HPLM) simulates:Exogenous variable
Liner Expenditure Systemenergy service demand,:Endogenous variablewaste generation, andHouseholdGoods and service preference module
Stock Capitalwater consumption forhousehold production by
four household types,
Amusement
Clothing
Food
Education
Housework
HealthResidence
Sleep
Other
under prescribedscenarios of household
type composition, age
Nesting structure of household production
composition, income
Material and energy balance module
budget, and time budget
in the future.
Revealed
Revealed
Revealed
Energy service
demandWaterdemandMaterial
demandFlowchart of HPLM
"EMF22 Tsukuba Workshop"

Dec. 13, 200641

Household Production and Lifestyle Model（２）•The model can consider demographic and socioeconomic trends
with consistency, together with Population and Household
Dynamics Model, Building Dynamics Model, and Inter-sector andMacro Economic Model.
Population and household
Dynamic model

Building
Dynamic model

Demographic information

Linking among
Household production
and lifestyle model andrelated models →Macroeconomic model

Building
characteristics

Disposal income
Interest rate, Good priceHousehold production and lifestylemodel

Revealed demands:Data flow

Endusemodel:Endogenous variable:ModelCO2emission"EMF22 Tsukuba Workshop"

Energycomsumption

Solid
Waste

Water
pollutantsAir
pollutants

Dec. 13, 200642

Material Stock and Flow Model
Material Stock and Flow Model (MSFM) estimates the change of material
stocks and flow in the society. Factors considered in the model are final
consumption and investments which are affected by capital stocks, material
densities of goods, physical input output coefficients of production sectors,
and recycling rate of wastes.

Macroeconomic
Model

Investmentof Goods

Investment Shareof Material

Initial Material
StocksStock, Flows

Physicalstock

Material Flow among
Domestic Sectors

Generated Waste

Material Import
RecycleExtraction fromthe Environment
Recycling Ratekocs t a teof n rse io
ea lat
cr mu
De cu
ac

Waste

Production including
reproduction
Decommissioning
Inputs of virgin material

Material Input for Construction
and Rehabilitation of Building
Physical Input Output
Coefficient for Production

Lifetime

Increase of service efficiency

Recycling

Material Densityof Goods

Material Demandfor Products

Material Stocks

Service producedby the stock

Import / Exportof Goods
Building Dynamics
Model

Stock dynamics greatly affects social
energy/material efficiency
Saturation ofservice demand

Final Consumptionof Goods

These factors
affect energy
consumption，
consumption，
greatly

Final Disposal: Data flow
: Exogenous variable: Endogenous variable

Flowchart of MSFM

year

"EMF22 Tsukuba Workshop"

Dec. 13, 2006

43

Shiga Prefecture (area: 4017km2,
population: 1.37 million) is at the center ofJapan. It has the largest lake in Japan,
Lake Biwa, and is surrounded by mountains
clad in fresh greenery, and has many
fertile plains.

Shiga Prefecture

CO2 emission
in 1990 level=100
1990年の二酸化炭素排出量=100

Application to local society -A Case Study in Shiga, JapanCO2 Emission Transitions

Electricity’s
Emission Factor
Reduction
EfficientTechnology
Introduction
Reconstruction toCompact City &Modal Shift

130
130

BaU(+20%)120
120

Supply Side Measure

110
110
100
100

Demand Side Measure

90
90

80
80

Fuel Switching

70
70
60
60

Renewable Energy
Penetration

-50%

50
50

1990

2000

2010

2020

2030

Lifestyle
ChangeContributions to Total Reduction by
Demand-Side Measures
Compact City

16%

People in Shiga have been very
conscious about protecting their richenvironment, and now, the Shiga
government is start to design their longterm plan towards a Low Carbon Society.
The models in this presentation were used
to project quantitative aspects of theplanning.
.
"EMF22 Tsukuba Workshop"

Others15%

6%

Solar Energy

7%8%

Fuel Efficient
Automobile

Traffic Modal
Shift

9%
High EfficientIndustrial Furnace
High Efficient Motor

Dec. 13, 2006

44

Key concepts of two scenarios"EMF22 Tsukuba Workshop"

Dec. 13, 2006

45

Key concepts of two scenarios (2)"EMF22 Tsukuba Workshop"

Dec. 13, 200646

Modeled production sectors andcommodities in the inter-sector module
Commodities

Activities
Primary
industry

MiningManufacturing

Construction

Power plant

Town gas
Water supply
Service

Transport andcommunications

Agriculture / Forestry / Fishing
Coal mining / Crude oil andnatural gas mining / Other
miningFood products and beverages /Textiles / Pulp, paper and paper
products / Publishing andprinting / Chemical materials /Chemical products / Petroleum
products / Coal products /Non-metallic mineral products /Pig iron and crude steel / Other
steel products / Non-ferrous
metal / Fabricated metal
products / Machinery /Electrical machinery, equipment
and supplies / Transport
equipment / Precision
instruments / Other
manufacturing

Primary energy

SecondaryenergyPrimary
industry
Other mining

manufacturing

Nuclear power plant / Thermal
power plant / Hydro power plant/ Geothermal plant /Photovoltaic generation / Windpower plant / Waste power
plant / Biomass power plant
Wholesale and retail trade /Finance and insurance / Realestate / Public service
activities / Other service
activities
Railway transport / Road
transport / Water transport /Air transport / Other
transport / Communications"EMF22 Tsukuba Workshop"

Construction
Water supply
Service

Transport andcommunications

Coal / Crude oil / Natural gas/ Nuclear / Hydro /Geothermal / Photovoltaic /Wind / Waste / Biomass
Coaks / Other coal products /Gasoline / Naphtha / Jet fuel/ Kerosene / Light oil / Heavy
oil / LPG / Other petrorium
products / Town gas /Electricity / Hydrogen / Heat
Agriculture / Forestry /Fishing
Food products and beverages/ Textiles / Pulp, paper andpaper products / Publishingand printing / Chemicalmaterials / Chemical products/ Non-metallic mineralproducts / Pig iron and crude
steel / Other steel products /Non-ferrous metal /Fabricated metal products /Machinery / Electricalmachinery ,equipment andsupplies / Transport
equipment / Precision
instruments / Other
manufacturing
Wholesale and retail trade /Finance and insurance / Realestate / Public service
activities / Other service
activities
Railway transport / Road
transport / Water transport/ Air transport / Other
transport / Communications

Dec. 13, 2006

47