Future AIM modeling~Focused on global and regional assessment tools~
Yuzuru Matsuoka
The 13th AIM International Workshop
17, February 2008
At Conference Room in Climate Change Research Hall
(Not Ohyama Memorial Hall)
National Institute for Environmental Studies, 3058506,Tsukuba, Japan

Future direction of AIM, 2008

1

FocusedpointsMore realistic and comprehensive modeling

1. Impact[Policy]
Climate feedback and economic uncertainties :Implication on 50%
reduction of world GHG emission

2. Enduse[global]

Inclusion of urbanization effects, household energy transition, andspatial emission distribution
Relative health impacts of environmental factors

3. Developing more consistent database for
global economy and environmental modeling
4. More comprehensive modeling for LCS study
Linkage of ESS,BCM, and Element models
Extension of ESS for long-term regional environment study
Future direction of AIM, 20082

AIM/Impact[Policy]- Global and Long-term climate-economic-energy integrated model
multi-regions (< 10), year 2000 to year 2200
- Dynamic global model consisted with;
Dynamic economic CGE module maximizing social utility+ Simplified climate module (global surface energy balance model)+ Carbon cycle module with feedback mechanism+ Simplified chemical reaction module+ Climate impact module- Gases : CO2, CH4, N2O, BC, SO2, and F gases- Now refining: 1)to multi-regional, 2) inclusion ofclimate feedback mechanism, 3) systematic andorganized methodology of impact assessment.
Future direction of AIM, 20083

Including climate feedbacks
Calibration 3：ＣＯ２
concentration

C4MIP (Friedlingstein et
Productivity and heterogeneous
respiration:
HRBM/CTBM/FBM/4box
biosphere (Meyer et al. 1999)

Carbon Cycle model
Atmospheric carbon balance
model(M1.1)
Vegetation carbon model(M1.2)

Historical emissions
GHG
NO2,CO,NMVOC
SO2, Halocarbon

al.,2997), Plattner et al.(2007),
al.,2007),
WG1-7(2007)

Vegetation
FB coefficient

Calibration1

Vegetation
absorption

Ocean FB
coefficient

Calibration2

Oceanic
absorption

Oceanic carbon
model(M1.3)
HILDA (Joos et al., 1996)

Calibration 2：
Oceanic carbon
absorption

Chemistry model（non-CO2,M2.1)

Calibration 4：Atmospheric non-CO
２ concentration

Joos et al. (2001),
Eickhout et al.(2004)

Calibration 5：
Radiative Forcing

ＳＯ２emission→DSU,ISU、
CFC and HC emission→ＳＯＺ
CO emission→OC,BC

CH4 concentration→SH2O

Chemistry model（TOZ,OH)(M2.2)

GHG: greenhouse gases
DSU: direct effect of tropospheric sulfates
ISU: indirect effect of tropospheric sulfates
VOL: volcanic stratospheric aerosols
SOL: solar irradiance
BCA: black carbon
TOZ: tropospheric ozone
SOZ: stratospheric ozone
IRF: impulse response function
UPDM: upwell-diffusion model
AF coefficient: Aerosol forcing coefficient
FB:feedback
LAN: landuse

Calibration１：Vegetation
carbon absorption

Decay
coefficients

Atmosphericconcentration

Calibration 3,4

Radiative forcing inyear 2000（IPCC
WG1)

GHG
concentration RF model(M3.1)
Calibration 5

Joos et al. (2001),
Eickhout et al.(2004)

Emissions of RF
related chemicals-RF
model（DSU,ISU,OC,BCS,OZ,SH2O)(M3.2)

Globaltemperature
model（IRF/UPDM)(M4)

Historicalconcentration

ＡＦ
coefficient

ClimatesensitivityFuture direction of AIM, 2008

Radiative Forcing

Globaltemperature

Calibration 6

Historical radiative
forcing
VOL, SOL, LAN

HistoricalglobaltemperaturechangeCalibration ６：Global
temperature change

4Effects of 50% GHG emission reduction in year 2050 on
long-term temperature change
Temperature increase from pre-industrial
era （℃）

4.0

BaU (Case 1）
Climate sensitivity: 4.5℃ (Case 5）

3.0
50％ reduction （Case 2)
50％ reduction at 2050, and continue
reduction thereafter (Case 3)

2.0

Climate sensitivity 2℃ （Case 4)

1.0

Case
Case 1Case 2
Case 3

0.0
1990

2010

2030

2050
Year

2070

2090

Case 4
Case 5Temperaturechange (1)BaU, climate sensitivity 3℃
50% reduction of 1990 emission after
year 2050, climate sensitivity 3℃
Continuation of case 2's emission
reduction speed till year 2100, keep 25%of year 1990 emission after thenSame as case 2 except climate
sensitivity is 2℃
Same as case 2 except climate
sensitivity is 4.5℃

5.7
2.8
2.0
1.9
4.2

（１）

Temperature increase in year 2200 above pre-industrial period（２）

Using same socio-economic assumptions as SRES B2. Compliancewith Kyoto target in year 2010 is assumed, and reduction will
start after year 2010. Controlled gases are those denoted in
Kyoto Protocol.

Future direction of AIM, 20085

Impacts of carbon cycle feedbacks on CO2 emission paths
10Land and ocean carbon storage sensitivity to CO2(GtC・ppm-1)
0
1
2
3
4

75

2.3 GtC/ppm(median)

50

25

50

96 GtC/℃(median)

25

Climate feedback
CO2 feedbback

CO2 emission (GtC/y)

Probability (%)757(2) With land carbon storage and climate feedback

6(1) Without land carbon storage and climate feedback

5
4

50% reduction in 2050

(4) Feedback coefficients from
HadCM3LC320(3) With land carbon storage feedback

8100

Probability (%)

100

936% reduction in 2050

0

-250

-200

-150

-100

-50

Land and ocean carbon storage sensitivity to climate(GtC・C-1)

Sensitivities of carbon cycle in
the C4MIP models

0101990 2010 2030 2050 2070 2090 2110 2130 2150 2170 2190
year
Target temperature = 2℃, Climate sensitivity =3℃, Discount rate = 1%/yLand carbon storage sensitivity = 0.6 GtC・GtC-1(=1.3 GtＣ/ppm) in (2), (3) and (4)Carbon storage sensitivity to climate = -96 GtC/℃ in (2), -199 GtC/℃ in (4)Future direction of AIM, 2008

6

Probability of temperature target compliance andemission reduction rate in year 2050
Temperaturetarget

2.0℃
2.6℃
3.6℃

Probability of compliance
10% 33% 50% 66% 90%
0
40
60
78
86
-4
43
64
87
97
-56
10
32
53
85
-64
8
34
56
95
-85 -54 -13
1655-79 -63 -21
15
59

Upper row is of six gases in Kyoto
Protocol, lower row is of CO 2 .
Temperature targets are increases above
pre-industrial period and reduction
rates are based on 1990 emissions.
Future direction of AIM, 20087

Countries' reduction rates for world 50% emission reduction
in year 2050
Equal emission
intensity
emission reduction ratio
reduction ratio
Mil.tC/y based on 1990
based on 1990
207
89%
49% ( 2%～63% )
2287%
61% ( 33%～65% )
5385%
35% ( -23%～44% )
1489%
66% ( 44%～73% )
3
89%
70% ( 51%～75% )
343
74%
50% ( 37%～62% )
4987%
83% ( 75%～92% )
55
94%
91% ( 75%～94% )
72
89%
90% ( 87%～93% )
2275%
36% ( -104%～75% )
728
34%
29% ( -69%～46% )
852-97%
48% ( -168%～66% )644-45%8% ( -27%～49% )
6852%
19% ( -13%～59% )
130
37%5% ( -23%～80% )
197
29%
12% ( -12%～71% )
232
35%
34% ( 20%～84% )
1028
-68%
51% ( 17%～92% )
4719
50%
50% ( 50%～50% )
705
87%
63% ( 37%～67% )
4014-2%
35% ( 29%～66% )Equal per capita

Country/Region
United States
CanadaJapan
Australia
New ZealandWestern Europe
Eastern Europe
RussiaOther CISSouth Korea
China
India
Other Asia
MexicoBrazilOther Latin America
Middle East
AfricaWorld
Annex B
Non-annex B

Equal velocity ofintensity reduction
reduction ratio
based on 1990
85% ( 75%～88% )
87% ( 77%～89% )
91% ( 87%～93% )
80% ( 65%～83% )
83% ( 70%～87% )
88% ( 87%～92% )
72% ( 64%～82% )
69% ( 60%～77% )
59% ( 49%～67% )
68% ( 62%～78% )-1% ( -46%～12% )-36% ( -57%～2% )-8% ( -15%～22% )
57% ( 44%～60% )
40% ( 33%～49% )
40% ( 38%～44% )
26% ( 22%～48% )-18% ( -49%～37% )
50% ( 50%～50% )
82% ( 78%～84% )
12% ( 9%～16% )Projections of GDP in 2050. We used 6 SRES scenarios of AIM (IPCC, 2001), A2r scenario(Grubler et al., 2006), Wilson and Purushothaman (2003), and Poncet (2006).

Future direction of AIM, 20088

Reduction rate with equal emission
intensity

Relation of reduction rates between different sharing
schemes
100%

RussiaOther CIS
East Europe

80%
New ZealandAnnex B60%
India

Africa

World

40%

Korea
Middle East
China

Non Annex B

20%
Other Asia

0%West Europe

Australia
CanadaUSA

Japan

MexicoOther LA
Brazil-100% -80% -60% -40% -20% 0%
20% 40% 60%
Reduction rate with equal per capita emission

Future direction of AIM, 2008

80% 100%

9

AIM/Enduse[Global]- Regional bottom-up type model
23 regions (same as AIM/Global[CGE]), year 2000 to year 2050
- Regional energy enduse module coupled with
Regional energy resource module
International energy, basic materials balance module
Regional macro-economy and energy service demand module- Emission sectors (activities)
Industrial, residential and commercial, transport, agriculture,
non-agricultural non CO2 emission sectors, F gases- Systematic reconciliation of base year information amongstocks of energy devices, energy efficiency, energy services, andenergy consumption- Gases: CO2, CH4, N2O, BC, OC, SO2, and F gases- Compatibility with national AIM enduse modeling activity
using same methodology and classification ofenergy/device/service
Future direction of AIM, 200810

AIM/Enduse[Global]

Key modeling issue 3

Key modeling issue 2

Key modeling issue 1

Macro-economy module

Trade module•Econometric productionside model coupled withdetailed module of energy
and material service demand
generation mechanism• Oil, Gas, Coal, Energy biomass• Iron and Steel,• Chemical products• Wood and wood products• Crop and diary products

Modules of material
demand generation andits reduction mechanism• Iron and Steel,• Chemical products• Wood and wood products• Crop and diary products

Key modeling issue 4
Database

Trades of Energy, BMs
and Foods

Database
World Tradetransportation cost and tradebarrierWorld energy and
BM price

2
re 3
gi
on

Trade Balance Module ofEnergy, Materials and Food

Production and extraction
amount of energy

Dynamism among
Electrification, household fuelchoice and poverty

Energydemand andSupplyKey modeling issue 5

Regional macro-economy and energy
service demand module

Energy service demand andenergy priceRegional technology
bottom-up module

Energy transformation
sectorModeling of residential
energy transition

Regional energy
production and supply
moduleFinal energy demand

F gasesemission
sectorNon-agriculture
CH4・N2O
emission sector

agriculture
sectorTransport
sectorResidential
andcommercial
sectorIndustrial
sectorEnergy price andemission coefficient

Resources-Cost
database

Technology
Database

Regional reality ofmodeling• Spatial migration ofemission activity• Building and household
dynamics
Key modeling issue 6

Modeling of ancillary
benefit andneighboring policy
effects• Regional air quality
management• Other environmental policy

Future direction of AIM, 200811

Regional reality of Modeling: Population distribution
and its relationship with CO2 emission activity( from county level information of year 2000 China population
census)
7
1st
2nd
3rd

90

Types ofindustrial
activities
are strongly
correlatedwithpopulation
distribution

80
70
60
50
40
30
20

Householdsize isstrongly
correlatedwithpopulation
distribution

6
Average persons per household

Employed population ratio in 1st, 2nd and 3rd industry (%)

100

5

4

3

10

2
0.1

0
0.1

1

10

100

1000

1

10

100

1000

10000

100000

2

Population density (person/km )10000 100000

15
Population density (person/km2)

House size isalso strongly
correlatedwithpopulation
distribution

2

Average floor space (m )

200

150

100

Peoplemigrates
toward more
dense
populatedregion10Internal migration rate (‰/year)

250

5

0

-5

50
-10
0.1

0
0.1

1

10

100

1000

10000
2

Population density (person/km )100000Future direction of AIM, 2008

1

10

100

1000

10000 100000
2

Population density (person/km )12Modeling of energy transition:
Household energy transition in
urban area(from ESMAP household energy surveys, from
1984-2002)

a
r
T

io
t
i
ns

n

st
i
:h

ca
i
or

100
80
60
40
20
0
th
on
d
m
oo al
p/
w
a
co al
c
re
Fi har Co ne
$/
S
e
C
U
os LPGity
e
er
m
ic
K
o
c
tr
In
ec
l
E

y?
t
ili
b
a
it

Bob
Xius o Dioula
Livin hui , Ch sso, B.
FKou gstone i na
Oua dougou, , Zambi
g
a
B.F.
adou
Oua
g
Dav higouya ou, B. F.
aStage 1: Utilization
,
o
B.F.
, Ph
Cag
i l.
Kitw ayan, Ph
of Biomass fuelsil .
Lua e, Zam
Kiffa nshya, Z bi a
ambLusa , Mt.
ia
Kaed ka. Zam
bia
Port i, Mt.
au P
A ta
ri nceNou r, Mt.
, Ha
a
iti
d
hibo
Nou
Stage 2a: Utilization
u, M
a
k
c
t.
Sura
hott
,
k
M
a
rta,
t.
Yog
of Transition fuels,
I
Sura yakarta nd.
High Charcoal use
Sem baya, In , I nd.
Ban arange, d.
dJian ung, In Ind.
Jaka yang, C d.
Cha rta, Ind hina
Stage 2b: Utilization
Kezu ngshu, C .
o
h
,
i
na
Hua
Chin
of Transition fuels,
Bac ntai, Ch a
Ceb olod, Ph ina
High Coal or
Hod u City, P il.
e
hil.
idah
Kerosene use
Har,Y
Tri n are, Zim emen
id
.
a
d, B
Bul a
o
Man wayo, Z l ivia.
ilaStage 2c: Utilization,
Mind
Phil . i m
Tari elo, C.
jaV.
of Transition fuels,
, Bo
Prai
l.
Quil a. C.V.
laDiversified
collo
Orur
,
La P o, Bol. Bol.
Transition fuel use
Tiaz az, Bol.
San , Yemen
Ayu aa, YemenChie tthaya,Stage 3: Transition to LPG and Electricity
Ban ngmai, Thai.
gkok
Thai
, Th
.
ai.

ne
i
l

v

Future direction of AIM, 200813

Modeling of ancillary benefit andneighboring policy effects :year 2000

Health risks attributed to environmental
factors
year 2000 situation( estimated by WHO method)

2500
1380

Mortality (000s)

2000

1500

939
653

1000

522
503

500

117

T

sa
Un

w
fe

at

er

an

an
ds

ita

do
In
Fa
cto
r

s

n
tio

or

ol
p
air

73
33

0

ion
t
lu

132

37

1

l
ota

356

46

18

0

77

1

18

ion
t
u
ll
po
ge
r
i
an
a
h
an
ec
t
b
a
Ur
m
Cl i

3

0

Bangladesh, Bhutan, N.Korea, India,
Maldives, Myanmar, Nepal

Indonesia, Sri Lanka, Thailand
China, Malaysia, Micronesia, Mongolia, Papua
New Guinea, Philippines, S.Korea, Viet Nam

Australia, Brunei, Japan, New Zealand, Singapore

Excess mortality attributed to1) Unsafe water and insufficient sanitation
Direct effects of heat and cold
→Cardiovascular disease2) Indoor air pollution
Foodborne and waterborne
Futuredirection of AIM, 2008143) Urban air pollution, anddiseases→Diarrhoea
Vector-borne diseases→Malaria
4) Climate changeB2 scenario
keeping current investments fornext 30 years

year 2030

2500

1849

Mortality (000s)

2000
1225
1500

1000

682
500

149

To

sa
Un

r
ate

an

39

an
s
d

ita

do
In
Fa
ct
or

s

n
tio

or

n
ba
r
U

137
51

0

t
l lu
o
p
air

t
llu
o
p
air

ion

5
2

19

ion

224

58

0

ta l

482

56

20

0

w
fe

887

602

0

Bangladesh, Bhutan, N.Korea, India,
Maldives, Myanmar, Nepal

Indonesia, Sri Lanka, Thailand
China, Malaysia, Micronesia, Mongolia, Papua
New Guinea, Philippines, S.Korea, Viet Nameng
Australia, Brunei, Japan, New Zealand, Singapore
a
ch
e
t
ma
1) Unsafe water and insufficient sanitation : decrease 10ilC20%, far from eradication
2) Indoor and urban air pollution : 40-70% increase mainly
caused by population and emission increase
FutureAIM, 20083) direction
Climate ofchange: 50-90% increase caused by the 15
escalation of climate changeB2+550ppm Scenario
Doubling of regional Investment/GDP
ratio for next 30 years

year 2030

2500

Excess mortality attributed to1) Unsafe water andinsufficient sanitation
2) Indoor air pollution
3) Urban air pollution, and
4) Climate change

Mortality (000s)

2000

1500
520
1000

402

41

sa
Un

w
fe

at

er

an

an
ds

ita

do
In
Fa
cto
r

s

n
tio

or

ol
p
air

163
20

0

l
ota

231

4
2

7

0

T

301

38

500

ion
t
lu

4

17

0

1

7
0

76

105

Bangladesh, Bhutan, N.Korea, India,
Maldives, Myanmar, Nepal

Indonesia, Sri Lanka, Thailand
China, Malaysia, Micronesia, Mongolia, Papua

New Guinea, Philippines, S.Korea, Viet Nam
ion
t
u
l
l
po
ge
Australia, Brunei, Japan, New Zealand, Singapore
ir
an
a
h
c
n
ba
ate
Ur
m
i
Cl
1) Unsafe water and insufficient sanitation : nearly eradicated2) Indoor and urban air pollution : 50% decrease3)Future
Climatechange: intensive
directionof AIM,
2008 adaptation suppresses increase
16 by
10-40%

Regional reality of modeling :Large point sources of CO2 SO2 and NOx emission in 2000

LPSs by electricity generation (Coal)
LPSs by electricity generation (Oil)LPSs by electricity generation (Gas)

LPSs by Steel Production
LPSs by Cement Production

Future direction of AIM, 200817

More consistent database for global economy and environmental modeling• Demonstrating low carbon &sustainable societies• Designing roadmaps toward them

AIM global
modeling

CGE[Global]Enduse[Global]Econometric[Global]Material[Global]activity

GAMMA(Global Accounting table for Money and Material )Supporting

GAMMAF(Flow Account)databaseof AIM
modeling

SAM(Social Accounting Matrix)

Price

Supplemental
Activity
Information

GAMMAS(Stock Account)

PIOT(Physical IO Table)

Reconciliation: 1) Outliers’ elimination, 2) Flow balancing, 3) Value and volume adjusting, 4) Dynamic adjustment

activity
Monetary Flow

Commodity Price
Service Price
Wage

EnergyBasic Material

Future direction of AIM, 2008

Population
Labor
Transportation
Floor Area

EnergyLand Use
Water

18

Supporting database of AIM modeling activity

GAMMA(Global Accounting table for Money and MAterial)
Supplemental
Activity
Information

GAMMAF(Flow Account)
SAM(Social Accounting Matrix)

GAMMAS(Stock Account)

PIOT

Price

(Physical IO Table)

Reconciliation: 1) Outliers’ elimination, 2) Flow balancing, 3) Value and volume adjusting, 4) Dynamic adjustment

Commodity Price
Service Price
Wage

Monetary Flow

Statistics Name
Commodity Trade Statistics
Database
FAOSTAT
Energy Price and Tax
Eenerdata
LABORSTA

Compiler
Publisher

Statistics Name

UN

International Historical Statistics

GTAP Databse
OECD Input-Output TablesCompiler
Publisher
UN
World Bank
(Mitchell,
2003)
GTAP
OECD

FAO
IEA
Eenerdata
ILO

Asian International Input-Output Table

IDE

International Financial Statistics

IMF

Asean International Input-Output Table

IDE

Industrial Commodity Production
Statistics Databse
Commodity Trade Statistics
Database
FAOSTAT
Energy Price and Tax
Eenerdata
Energy Infromation
Iron and Steel Statistiscs

Statistics Name
National Accounts Database
World Development Indicators
International Historical Statistics

Balance of Payments

IMF

Commodity Trade Statistics Database

UN

International Trade by Commodity statistics

OECD

OECD Statistics on International Trade inServices

OECD

General Industrial Statistics DatabaseUN

Industrial Demand-Supply Balance Database at
UNIDO
the 4-digit level of ISIC code
Industrial Statistics Database at the 4-digit levelof ISIC code
Asian Long-term Statistics -Industrial
DevelopmentFAOSTATUNIDOTakushoku
University
FAO

Structural Statistics for Industry and Services

OECD

The OECD STAN database for Industrial
AnalysisOECD

Population
Labor
Transportation
Floor Area

EnergyBasic Material
Compiler
Publisher(Mitchell,
2003)

UN
UN

Statistics Name
International Historical
Statistics
LABORSTAUN Population
Prospects

EnergyLand Use
Water

Compiler
Publisher(Mitchell,
2003)
ILO

UN

FAO
IEA
Eenerdata
EIA
IISI• Period: 1970 – latest• Regionalization: 153 countries and regions ( covers
more than 99% of global GDP)• Reconciliation methodology: Flow balancing, crosssectional and temporal aggregation constrains
Future direction of AIM, 200819

More comprehensive modeling for LCS study:
Two stages and three model groups of LCS’s study:
Stage 1: Design of a Low Carbon SocietyGroup 1: Element models;

1. Creation of narrative storylines of future Low
Carbon Societies
2. Description of sector-wise details of the future
LCSs.
3. Quantification of the Macro economic and social
aspects of the LCSs.
4. Identification of effective policy measures andpackaging them1) Snapshot models;- Quasi steady Computable General
Equilibrium (CGE) model- Energy technology bottom-up models- Energy supply model- Household production/lifestyle model- Transportation demand model
2) Transition models;- Population and household model- Building dynamics model- Econometric type macro-economy modelStage two : Putting them together and making
it happen
1. Design of policy roadmaps toward the Low
Carbon Society
2. Feasibility analysis of the roadmaps
considering uncertainties involved in eachpolicy option
3. Analysis of robustness of the roadmap causedby societal, economical and institutional
acceptability and uncertainties

Group 2: Extended Snapshot Tool
(ESS)Group 3: Backcasting Model fortransient control(BCM)

Future direction of AIM, 200820

Extended SnapShot (ESS)
Passenger transportation model
Building model
Freight transportation model
Population andhousehold model

Commercial
Building

Commercial
Service

Input/Output
model
Employment
coefficient

Final demand
converter

Macro-economy
model
AIM/econometric,
AIM/Material

Freight
Transportation

Industrial
production
Sectoralfinal demand
Food production

MSW/ISW

ForestAggregated energy and emission calculation in
final sectors Energy supply

Changes of Input
and import coefficient

Energy consumption

Residential
Service

Aggregated energy and emission calculation in final sectors

Residential
Building
Population

Labor•Excel and GAMS versions wereprepared•Developing multi-regional version•Linking with element models

Passenger
Transportation

Demographic andtime budget
scenarios

Time budget

SITUATION

AIM/enduse
model

APPLICATION•Japan 2050 LCS study•Shiga 2030 Sustainable Society study•Kyoto 2030 LCS study•Iskandar Sustainable Society study

GHG emissions
Total energy
consumption
Other
environmentalload generation

REMAINING AND REQUIRED IMPROVEMENT•Linking with BCM•Friendly interface and good operationality•Systematic extension to other environmental loads
Future direction of AIM, 200821

Linkage among ESS, BCM, and Element models
Element models•Macro-economy
model•Population andhousehold model•Building model•Passenger
transportation
model•Freight
transportation
model•Energy supply
model•Material stock
dynamics model•Energy enduse
modelsSupply transient and dynamic parameters based on
more physically realistic mechanisms

Supply social,physicalparameters
based on more
physicallyrealisticmechanisms

Supply target
visionquantitatively

ExtendedSnapshotTool (ESS)

Check and analyze
quantitative
consistency of
future societies

Backcasting
Model (BCM)
Design roadmaps
toward future
visions

Check and verify the future
visions and transient paths
from the points of economic
reality

Sequential CGE

Supply values of parameters based on more
type model suchphysically realistic mechanisms
as AIM/ material

We have completed most of element models, ESS and the 1st version of BCM.
Now preparing the operational version of BCM and also material stock model.
After completing them, we will assemble them to one Integrated Model for
Sustainable Society.
Future direction of AIM, 200822

More comprehensive model for regional LCS study:
Key modeling parameters in regional ESS from a view point of regional development
Ratio of investment fromoutside of the region

In

Agriculture

Publicprojects

Offshore market
Industry
In
ve
stm
en
t

Working outsideof region

Local
procurementoreOffsh mee
procurnt

ExportLocal
governmentrocu

Investmentcbli
Pu icerv
seServiceindustry

Manufacturi
ng industry

Tax

b
Jo n
io
at

Agriculture

Fate ofbasic exportindustry

Purchase

Regional
PeopleJobcreation

Retail• Convenienc
e goods• Shoppinggoods• Specialty
goods

lp

proc
urem
e

nt

Internal market
Industry

LocalOffshoreprocurementOffshoreprocurementServiceindustryecrRemainingratio ofvalue-add
within theregiontLo
ca

Manufacturi
ng industry

n
me
st
e
v

re
me
nt

Fate of nonbasic local
industry

Inv
est
me
nt

Outside of region
Future direction of AIM, 2008

Ratio of
local
product
consumption

Key factors forregional economy
considered in ESS

GHG emission
activity
Economic
activity
Material andservice flow
Job creation
Money flow 23

AIM model family, FY2008
Category

Name

Category
Conservation of ecosystem/

Ecosystem

water stress/ landuse/ pollution
in developing countries

Top-down models

Global/CGE

Energy, GHG Control
CO2 reduction, energy

Material

consumption, waste management.
environmental industry

Econometric
Backcasting
Population/Household
Building
Models /Tools for
scenario making

Transport

StocksExtended Snapshot

Energy supply anddemand regulation
End-use, Energy,
Technology

Enduse[global]

Bottom-up
Enduse[country]
Enduse[local]
ImpactImpact[Country]

Impact Assessment

Multi-regional CGE + various

land use and ecosystem

environmental process models

Projection of long-term GHGs emission
Economic and material flow impact by climate andother environmental policy
Quantification and analysis of macroeconomic andframeenergy variables

GHG, Energy, Low carbon

Establishing scenarios toward saustainable societysocietyfrom view points of environment and economy

Population, householdchange, economic change and so on

demandnational/regional/urban land planning

Infrastracture, capital,

Estimation of raw material needs, waste generationbuildings

related to recycling and economic activity

modelsMerge and extend to one
global/CGE model as a plathome of AR5 scenario activity～2030-2050 houshold models, transport models
and so on.

Country-level econometric model～2050

Country-level dynamic optimization model～2050

Extend to a multi-regional world
model
Implementation and Operation

Stock dynamics model～2050

Trip generation, modal share modeling～2050

Stock dynamics model～2050→Mｓ.Kawase～2050→Mr.Hibino

Quantitative shinario making
tools for mid-term

Comprehension of economic activity andenvironmental loadings with Social Accounting Matrix Accounting tooland energy balancing approachenergy demand and supply→Dr.Ashina～2050

Mr.GomiTemporal and spatial regulation Adjustment among temporal and spatial fluctuation ofof electlicity, heat and→Dr.MasuiConnecting with stock models,transition matrix model

Passenger and Freight transport Estimation of transport demand related to～2100

One regional national CGE modelfrom view points of environment and economy

building

FY 2006-2007 activity～2100-2150

Cohort-component model, houshold

Estimation of building demands related to houshold

Target year

Multi-regional CGE model

Establishing scenarios toward saustainable society

Residential, non-residential

Integrating tool of element

Model type

Modeling of relationship among economic activities,

Forecasting macro-economic

Simulation and optimization type model～2050

hydrogen
GHG,SO2,NOX ,PM abatement

Technology selection for global warming, regional air Country-level or regional-level bottom-up

technology

pollution

model

GHG,SO2,NOX ,PM abatement

Technology selection for global warming, regional air Country-level or regional-level bottom-up

technology

pollution

GHG,SO2,NOX ,PM abatement

Technology selection for global warming, regional air Country-level or regional-level bottom-up

technology

pollution

model

Impact assessment at global scale

Process model based on raster GIS data

Impact assessment of climatechangeImpact assessment of climatechangeIntegration of mitigation policy

Impact[policy]

Objective

evaluation and impact
assessment

Water

Impact assessment

Enduse[Air]

Environmental Assesment

model

Still developing. Estimation of～2050

feasibility and economic burdensof low carbon world～2050
Keep maintainance
～2030
～2100

→Dr.Hanaoka

Dr.Kanamori
Mr.Akashi

Keeping maintainance andreinforcement ? Anyway, it isnecessary to reconfirm the

Impact assessment at country scale

Process model based on raster GIS data

～2100

developing policy, to review
and to reorganize it.

Investigation of stabilization level and mitigation
policy with considering consequent impacts

Change to multi-regional emission
Calculating global GHGs paths
Coupling process model with andfocusing on urban area

statistics

analysismodel, improve climate and carbon
cycle modules

Integrated assessment of water supply and demand

Regional and country scale atmospheric environmental

～2200

～2050

→Dr.Hijioka

Coupling with AIM/GBDB(Global
basin database)
Coupling with AIM/Enduse[local],Atmospheric quality model + GIS～2050

for assessing long-range and urban
air pollution issues.

Future direction of AIM, 200824