Future AIM modeling Future AIM modeling ~Focused on global and - - PowerPoint PPT Presentation

Future direction of AIM, 2008 1

Future AIM modeling Future AIM modeling

~Focused on global and regional assessment tools~ ~Focused on global and regional assessment tools~

Yuzuru Matsuoka Yuzuru Matsuoka The 13th AIM International Workshop The 13th AIM International Workshop 17, 17, February February 2008 2008 At Conference Room in Climate Change Research Hall At Conference Room in Climate Change Research Hall (Not Ohyama Memorial Hall) (Not Ohyama Memorial Hall) National Institute for Environmental Studies, 305 National Institute for Environmental Studies, 305-

• 8506,Tsukuba, Japan

8506,Tsukuba, Japan

Future direction of AIM, 2008 2

Focused Focused points points

More 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, and spatial 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, 2008 3

• 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 of

climate feedback mechanism, 3) systematic and

• rganized methodology of impact assessment.
• AIM/Impact[Policy]

Future direction of AIM, 2008 4

Calibration 3：ＣＯ２ concentration

C4MIP (Friedlingstein et al.,2997), Plattner et al.(2007), WG1-7(2007) C4MIP (Friedlingstein et al.,2007), Plattner et al.(2007), WG1-7(2007)

Chemistry model （non-CO2,M2.1) Historical global temperature change

Global temperature model （IRF/UPDM)(M4) GHG concentration - RF model(M3.1)

Historical radiative forcing VOL, SOL, LAN Decay coefficient s

Climate sensitivit y

Chemistry model （TOZ,OH)(M2.2)

Carbon Cycle model

Vegetation carbon model(M1.2)

Oceanic carbon model(M1.3)

Atmospheric carbon balance model(M1.1)

Vegetation FB coefficient Ocean FB coefficient

Radiative Forcing ＳＯ２emission→DSU,ISU、 CFC and HC emission→ＳＯＺ CO emission→OC,BC ＡＦ coefficient

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

Global temperature

CH4 concentration→SH2O

Productivity and heterogeneous respiration: HRBM/CTBM/FBM/4box biosphere (Meyer et al. 1999) HILDA (Joos et al., 1996)

Calibration１：Vegetation carbon absorption Calibration 2： Oceanic carbon absorption

Historical emissions GHG NO2,CO,NMVOC SO2, Halocarbon

Joos et al. (2001), Eickhout et al.(2004) Calibration 4：Atmospheric non-CO

２ concentration

Radiative forcing in year 2000（IPCC WG1)

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

Calibration 5： Radiative Forcing

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

Calibration ６：Global temperature change

Vegetation absorption

Oceanic absorption

Calibration 5

Historical concentration

Including climate feedbacks

Future direction of AIM, 2008 5

0.0 1.0 2.0 3.0 4.0 1990 2010 2030 2050 2070 2090

Year Temperature increase from pre-industrial era （℃）

BaU (Case 1） Climate sensitivity: 4.5℃ (Case 5） 50％ reduction （Case 2) 50％ reduction at 2050, and continue reduction thereafter (Case 3) Climate sensitivity 2℃ （Case 4)

Effects of 50% GHG emission reduction in year 2050 on long-term temperature change

Temperature change (1) Case 1 BaU, climate sensitivity 3℃

5.7

Case 2 50% reduction of 1990 emission after year 2050, climate sensitivity 3℃

2.8

Case 3 Continuation of case 2's emission reduction speed till year 2100, keep 25%

• f year 1990 emission after then

2.0

Case 4 Same as case 2 except climate sensitivity is 2℃

1.9

Case 5 Same as case 2 except climate sensitivity is 4.5℃

4.2

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

Case

（２）Using same socio-economic assumptions as SRES B2. Compliance

with 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, 2008 6

Impacts of carbon cycle feedbacks on CO2 emission paths

1 2 3 4 5 6 7 8 9 10 1990 2010 2030 2050 2070 2090 2110 2130 2150 2170 2190 year CO2 emission (GtC/y)

(3) With land carbon storage feedback (2) With land carbon storage and climate feedback (1) Without land carbon storage and climate feedback (4) Feedback coefficients from HadCM3LC

Target temperature = 2℃, Climate sensitivity =3℃, Discount rate = 1%/y Land 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)

25 50 75 100

• 250
• 200
• 150
• 100
• 50

Land and ocean carbon storage sensitivity to climate (GtC・C-1) Probability (%) 25 50 75 100 1 2 3 4 Land and ocean carbon storage sensitivity to CO2 (GtC・ppm-1) Probability (%) Climate feedback CO2 feedbback

96 GtC/℃ (median) 2.3 GtC/ppm (median)

Sensitivities of carbon cycle in the C4MIP models 50% reduction in 2050 36% reduction in 2050

Future direction of AIM, 2008 7

Probability of temperature target compliance and emission reduction rate in year 2050

10% 33% 50% 66% 90% 40 60 78 86

• 4

43 64 87 97

• 56

10 32 53 85

• 64

8 34 56 95

• 85
• 54
• 13

16 55

• 79
• 63
• 21

15 59 Probability of compliance

Temperature target

2.0℃ 2.6℃ 3.6℃

Upper row is of six gases in Kyoto Protocol, lower row is of CO2. Temperature targets are increases above pre-industrial period and reduction rates are based on 1990 emissions.

Future direction of AIM, 2008 8

Countries' reduction rates for world 50% emission reduction in year 2050

Equal emission intensity Equal velocity of intensity reduction emission reduction ratio reduction ratio reduction ratio Mil.tC/y based on 1990 based on 1990 based on 1990 United States 207 89% 49% ( 2%～63% ) 85% ( 75%～88% ) Canada 22 87% 61% ( 33%～65% ) 87% ( 77%～89% ) Japan 53 85% 35% ( -23%～44% ) 91% ( 87%～93% ) Australia 14 89% 66% ( 44%～73% ) 80% ( 65%～83% ) New Zealand 3 89% 70% ( 51%～75% ) 83% ( 70%～87% ) Western Europe 343 74% 50% ( 37%～62% ) 88% ( 87%～92% ) Eastern Europe 49 87% 83% ( 75%～92% ) 72% ( 64%～82% ) Russia 55 94% 91% ( 75%～94% ) 69% ( 60%～77% ) Other CIS 72 89% 90% ( 87%～93% ) 59% ( 49%～67% ) South Korea 22 75% 36% ( -104%～75% ) 68% ( 62%～78% ) China 728 34% 29% ( -69%～46% )

• 1% ( -46%～12% )

India 852

• 97%

48% ( -168%～66% )

• 36% ( -57%～2% )

Other Asia 644

• 45%

8% ( -27%～49% )

• 8% ( -15%～22% )

Mexico 68 52% 19% ( -13%～59% ) 57% ( 44%～60% ) Brazil 130 37% 5% ( -23%～80% ) 40% ( 33%～49% ) Other Latin America 197 29% 12% ( -12%～71% ) 40% ( 38%～44% ) Middle East 232 35% 34% ( 20%～84% ) 26% ( 22%～48% ) Africa 1028

• 68%

51% ( 17%～92% )

• 18% ( -49%～37% )

World 4719 50% 50% ( 50%～50% ) 50% ( 50%～50% ) Annex B 705 87% 63% ( 37%～67% ) 82% ( 78%～84% ) Non-annex B 4014

• 2%

35% ( 29%～66% ) 12% ( 9%～16% ) Country/Region Equal per capita 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, 2008 9

Relation of reduction rates between different sharing schemes

USA Canada Japan Australia New Zealand West Europe East Europe Russia Other CIS Korea China India Other Asia Mexico Brazil Other LA Middle East Africa World Annex B Non Annex B

0% 20% 40% 60% 80% 100%

• 100% -80%
• 60%
• 40%
• 20%

0% 20% 40% 60% 80% 100% Reduction rate with equal per capita emission Reduction rate with equal emission intensity

Future direction of AIM, 2008 10

• 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 among

stocks of energy devices, energy efficiency, energy services, and energy consumption

• Gases: CO2, CH4, N2O, BC, OC, SO2, and F gases
• Compatibility with national AIM enduse modeling activity

using same methodology and classification of energy/device/service

• AIM/Enduse[Global]

Future direction of AIM, 2008 11

Trade Balance Module of Energy, Materials and Food Database World Trade

Database

transportation cost and trade barrier

Regional macro-economy and energy service demand module Energy transformation sector Industrial sector Residential and commercial sector Transport sector agriculture sector

Non-agriculture CH4・N2O emission sector

F gases emission sector

Technology Database Regional energy production and supply module Resources-Cost database

23 regions Regional technology bottom-up module

Production and extraction amount of energy Trades of Energy, BMs and Food Energy service demand and energy price Energy demand and Supply Final energy demand

Energy price and emission coefficient World energy and BM price

AIM/Enduse[Global]

Trade module

• Oil, Gas, Coal, Energy biomass
• Iron and Steel,
• Chemical products
• Wood and wood products
• Crop and diary products

Key modeling issue 1

Macro-economy module

• Econometric production-

side model coupled with detailed module of energy and material service demand generation mechanism

Key modeling issue 2

Modules of material demand generation and its reduction mechanism

• Iron and Steel,
• Chemical products
• Wood and wood products
• Crop and diary products

Key modeling issue 3

Modeling of residential energy transition

Dynamism among Electrification, household fuel choice and poverty

Key modeling issue 4

Regional reality of modeling

• Spatial migration of

emission activity

• Building and household

dynamics

Key modeling issue 5

Modeling of ancillary benefit and neighboring policy effects

• Regional air quality

management

• Other environmental policy

Key modeling issue 6

Future direction of AIM, 2008 12

Regional reality of Modeling: Population distribution and its relationship with CO2 emission activity

( from county level information of year 2000 China population census)

10 20 30 40 50 60 70 80 90 100 0.1 1 10 100 1000 10000 100000 Population density (person/km2) Employed population ratio in 1st, 2nd and 3rd industry (%) 1st 2nd 3rd 2 3 4 5 6 7 0.1 1 10 100 1000 10000 100000 Population density (person/km2) Average persons per household

• 10
• 5

5 10 15 0.1 1 10 100 1000 10000 100000 Population density (person/km2) Internal migration rate (‰/year) 50 100 150 200 250 0.1 1 10 100 1000 10000 100000 Population density (person/km2) Average floor space (m2)

Types of industrial activities are strongly correlated with population distribution Household size is strongly correlated with population distribution House size is also strongly correlated with population distribution People migrates toward more dense populated region

Future direction of AIM, 2008 13

Bobo Dioulasso, B.F Xiushui, China Livingstone, Zambia Koudougou, B.F. Ouagadougou, B.F. Ouahigouya, B.F. Davao, Phil. Cagayan, Phil. Kitwe, Zambia Luanshya, Zambia Kiffa, Mt.

• Lusaka. Zambia

Kaedi, Mt. Port au Prince, Haiti Atar, Mt. Nouadhibou, Mt. Nouakchott, Mt. Surakarta, Ind. Yogyakarta, Ind. Surabaya, Ind. Semarange, Ind. Bandung, Ind. Jianyang, China Jakarta, Ind. Changshu, China Kezuo, China Huantai, China Bacolod, Phil. Cebu City, Phil. Hodeidah, Yemen Harare, Zim. Trinidad, Bolivia. Bulawayo, Zim Manila, Phil. Mindelo, C.V. Tarija, Bol.

• Praia. C.V.

Quillacollo, Bol. Oruro, Bol. La Paz, Bol. Tiaz, Yemen Sanaa, Yemen Ayutthaya, Thai. Chiengmai, Thai. Bangkok, Thai. I n c

• m

e U S $ / c a p / m

• n

t h F i r e w

• d

C h a r c

• a

l C

• a

l K e r

• s

e n e L P G E l e c t r i c i t y 20 40 60 80 100

Modeling of energy transition: Household energy transition in urban area

(from ESMAP household energy surveys, from 1984-2002)

Stage 1: Utilization

• f Biomass fuels

Stage 2a: Utilization

• f Transition fuels,

High Charcoal use Stage 2b: Utilization

• f Transition fuels,

High Coal or Kerosene use Stage 2c: Utilization

• f Transition fuels,

Diversified Transition fuel use Stage 3: Transition to LPG and Electricity

Transition :historical inevitability?

Future direction of AIM, 2008 14 T

• t

a l U n s a f e w a t e r a n d s a n i t a t i

• n

I n d

• r

a i r p

• l

l u t i

• n

U r b a n a i r p

• l

l u t i

• n

C l i m a t e c h a n g e

1380 653 522 132 73 939 77 503 356 3 117 46 37 33 1 18 1 18 500 1000 1500 2000 2500 Mortality (000s)

Factors

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 year 2000

Excess mortality attributed to 1) Unsafe water and insufficient sanitation 2) Indoor air pollution 3) Urban air pollution, and 4) Climate change

Modeling of ancillary benefit and neighboring policy effects :

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

Direct effects of heat and cold →Cardiovascular disease Foodborne and waterborne diseases→Diarrhoea Vector-borne diseases→Malaria

Future direction of AIM, 2008 15

Total Unsafe water and sanitation Indoor air pollution Urban air pollution Climate change

1849 602 887 224 137 1225 56 682 482 5 149 39 58 51 2 20 19 500 1000 1500 2000 2500 Mortality (000s)

Factors

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 year 2030

1) Unsafe water and insufficient sanitation : decrease 10- 20%, far from eradication 2) Indoor and urban air pollution : 40-70% increase mainly caused by population and emission increase 3) Climate change : 50-90% increase caused by the escalation of climate change

B2 scenario keeping current investments for next 30 years

Future direction of AIM, 2008 16 T

• t

a l U n s a f e w a t e r a n d s a n i t a t i

• n

I n d

• r

a i r p

• l

l u t i

• n

U r b a n a i r p

• l

l u t i

• n

C l i m a t e c h a n g e

520 38 301 76 105 402 4 231 163 4 41 2 20 17 1 7 7 500 1000 1500 2000 2500 Mortality (000s)

Factors

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 year 2030

Excess mortality attributed to 1) Unsafe water and insufficient sanitation 2) Indoor air pollution 3) Urban air pollution, and 4) Climate change

B2+550ppm Scenario Doubling of regional Investment/GDP ratio for next 30 years

1) Unsafe water and insufficient sanitation : nearly eradicated 2) Indoor and urban air pollution : 50% decrease 3) Climate change : intensive adaptation suppresses increase by 10-40%

Future direction of AIM, 2008 17

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

LPSs by electricity generation (Oil) LPSs by electricity generation (Gas) LPSs by electricity generation (Coal) LPSs by Steel Production LPSs by Cement Production

Future direction of AIM, 2008 18

More consistent database for global economy and environmental modeling

Supporting database

• f AIM

modeling activity

GAMMA (Global Accounting table for Money and Material )

SAM

(Social Accounting Matrix)

Price PIOT

(Physical IO Table) GAMMAF (Flow Account) GAMMAS (Stock Account)

Supplemental Activity Information

Monetary Flow Commodity Price Service Price Wage Energy Basic Material Energy Land Use Water

Population Labor Transportation Floor Area

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

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

• Demonstrating low carbon &

sustainable societies

• Designing roadmaps toward them

AIM global modeling activity

Future direction of AIM, 2008 19 GAMMA (Global Accounting table for Money and MAterial)

SAM

(Social Accounting Matrix)

Price PIOT

(Physical IO Table)

GAMMAF (Flow Account) GAMMAS (Stock Account)

Supplemental Activity Information

Supporting database of AIM modeling activity

Monetary Flow Commodity Price Service Price Wage Energy Basic Material Energy Land Use Water

Population Labor Transportation Floor Area

Statistics Name Publisher National Accounts Database UN World Development Indicators World Bank International Historical Statistics (Mitchell, 2003) GTAP Databse GTAP OECD Input-Output Tables OECD Asian International Input-Output Table IDE Asean International Input-Output Table IDE Balance of Payments IMF Commodity Trade Statistics Database UN International Trade by Commodity statistics OECD OECD Statistics on International Trade in Services OECD General Industrial Statistics Database UN Industrial Demand-Supply Balance Database at the 4-digit level of ISIC code UNIDO Industrial Statistics Database at the 4-digit level

• f ISIC code

UNIDO Asian Long-term Statistics -Industrial Development- Takushoku University FAOSTAT FAO Structural Statistics for Industry and Services OECD The OECD STAN database for Industrial Analysis OECD Statistics Name Publisher Commodity Trade Statistics Database UN FAOSTAT FAO Energy Price and Tax IEA Eenerdata Eenerdata LABORSTA ILO International Financial Statistics IMF Statistics Name Publisher International Historical Statistics (Mitchell, 2003) Industrial Commodity Production Statistics Databse UN Commodity Trade Statistics Database UN FAOSTAT FAO Energy Price and Tax IEA Eenerdata Eenerdata Energy Infromation EIA Iron and Steel Statistiscs IISI Statistics Name Publisher International Historical Statistics (Mitchell, 2003) LABORSTA ILO UN Population Prospects UN

Compiler Compiler Compiler Compiler

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

• Period: 1970 – latest
• Regionalization: 153 countries and regions ( covers

more than 99% of global GDP)

• Reconciliation methodology: Flow balancing, cross-

sectional and temporal aggregation constrains

Future direction of AIM, 2008 20

Stage 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 each policy option

• 3. Analysis of robustness of the roadmap caused

by societal, economical and institutional acceptability and uncertainties Stage 1: Design of a Low Carbon Society

• 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 and

packaging them

More comprehensive modeling for LCS study: More comprehensive modeling for LCS study: Two stages and three model groups of LCS Two stages and three model groups of LCS’ ’s study: s study:

Group 3: Backcasting Model for transient control (BCM) Group 2: Extended Snapshot Tool (ESS) Group 1: Element models;

1) 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 model

Future direction of AIM, 2008 21

Extended SnapShot (ESS)

SITUATION

• Excel and GAMS versions were

prepared

• Developing multi-regional version
• Linking with element models

Macro-economy model AIM/econometric, AIM/Material

Labor Time budget Population Residential Building Food production Input/Output model Energy consumption Forest Passenger Transportation MSW/ISW

GHG emissions Total energy consumption Other environmental load generation

Freight Transportation Industrial production Commercial Building Residential Service Commercial Service Sectoral final demand Changes of Input and import coefficient

Employment coefficient

Demographic and time budget scenarios

Aggregated energy and emission calculation in final sectors Aggregated energy and emission calculation in final sectors Energy supply

AIM/enduse model Population and household model

Final demand converter

Building model Passenger transportation model Freight transportation model

REMAINING AND REQUIRED IMPROVEMENT

• Linking with BCM
• Friendly interface and good operationality
• Systematic extension to other environmental loads

APPLICATION

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

Future direction of AIM, 2008 22

Linkage among ESS, BCM, and Element models

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.

Extended Snapshot Tool (ESS)

Check and analyze quantitative consistency of future societies

Backcasting Model (BCM)

Design roadmaps toward future visions

Sequential CGE type model such

as AIM/ material

Element models

• Macro-economy

model

• Population and

household model

• Building model
• Passenger

transportation model

• Freight

transportation model

• Energy supply

model

• Material stock

dynamics model

• Energy enduse

models

Supply transient and dynamic parameters based on more physically realistic mechanisms Supply social, physical parameters based on more physically realistic mechanisms Supply target vision quantitatively Supply values of parameters based on more physically realistic mechanisms Check and verify the future visions and transient paths from the points of economic reality

Future direction of AIM, 2008 23

Job creation Offshore procureme nt L

• c

a l p r

• c

u r e m e n t Working outside

• f region

Local government

Offshore procureme nt Offshore procureme nt L

• c

a l p r

• c

u r e m e n t Tax Investment

Purchase

Job creation Export Local procuremen t

Offshore market Industry

Agriculture Manufacturi ng industry Service industry

Investment Retail

• Convenienc

e goods

• Shopping

goods

• Specialty

goods Investment

Regional People

Public projects

Public service I n v e s t m e n t

Outside of region Outside of region

Internal market Industry

Agriculture Manufacturi ng industry Service industry

Fate of basic export industry Ratio of investment from

• utside of the region

Ratio of local product consumption Remaining ratio of value-add within the region Fate of non- basic local industry

Material and service flow Job creation Money flow Economic activity

GHG emission activity

Key factors for regional economy considered in ESS

More comprehensive model for regional LCS study: Key modeling parameters in regional ESS from a view point of regional development

Future direction of AIM, 2008 24

AIM model family, FY2008 AIM model family, FY2008

Category Name Category Objective Model type Target year Ecosystem Conservation of ecosystem/ water stress/ landuse/ pollution in developing countries Modeling of relationship among economic activities, land use and ecosystem Multi-regional CGE + various environmental process models ～2100 Global/CGE Energy, GHG Control Projection of long-term GHGs emission Multi-regional CGE model ～2100-2150 Material CO2 reduction, energy consumption, waste management. environmental industry Economic and material flow impact by climate and

• ther environmental policy

One regional national CGE model ～2030-2050 Econometric Forecasting macro-economic frame Quantification and analysis of macroeconomic and energy variables Country-level econometric model ～2050 Backcasting GHG, Energy, Low carbon society Establishing scenarios toward saustainable society from view points of environment and economy Country-level dynamic optimization model ～2050 Population/Household Population, household Establishing scenarios toward saustainable society from view points of environment and economy Cohort-component model, houshold transition matrix model ～2050 Building Residential, non-residential building Estimation of building demands related to houshold change, economic change and so on Stock dynamics model ～2050 Transport Passenger and Freight transport demand Estimation of transport demand related to national/regional/urban land planning Trip generation, modal share modeling ～2050 Quantitative shinario making tools for mid-term Stocks Infrastracture, capital, buildings Estimation of raw material needs, waste generation related to recycling and economic activity Stock dynamics model ～2050 Extended Snapshot Integrating tool of element models Comprehension of economic activity and environmental loadings with Social Accounting Matrix and energy balancing approach Accounting tool ～2050 Energy supply and demand regulation Temporal and spatial regulation

• f electlicity, heat and

hydrogen Adjustment among temporal and spatial fluctuation of energy demand and supply Simulation and optimization type model ～2050 Enduse[global] GHG,SO2,NOX,PM abatement technology Technology selection for global warming, regional air pollution Country-level or regional-level bottom-up model ～2050 Enduse[country] GHG,SO2,NOX,PM abatement technology Technology selection for global warming, regional air pollution Country-level or regional-level bottom-up model ～2050 Enduse[local] GHG,SO2,NOX,PM abatement technology Technology selection for global warming, regional air pollution Country-level or regional-level bottom-up model ～2030 Impact Impact assessment of climate change Impact assessment at global scale Process model based on raster GIS data ～2100 Impact[Country] Impact assessment of climate change Impact assessment at country scale Process model based on raster GIS data ～2100 Impact[policy] Integration of mitigation policy evaluation and impact assessment Investigation of stabilization level and mitigation policy with considering consequent impacts Calculating global GHGs paths ～2200 Water Impact assessment Integrated assessment of water supply and demand focusing on urban area Coupling process model with and statistics ～2050 Enduse[Air] Environmental Assesment Regional and country scale atmospheric environmental analysis Atmospheric quality model + GIS ～2050 FY 2006-2007 activity Top-down models Impact Assessment Coupling with AIM/GBDB(Global basin database) Coupling with AIM/Enduse[local], for assessing long-range and urban air pollution issues. Still developing. Estimation of feasibility and economic burdens

• f low carbon world

Models /Tools for scenario making Merge and extend to one global/CGE model as a plat home of AR5 scenario activity Connecting with stock models, houshold models, transport models and so on. Extend to a multi-regional world model Implementation and Operation Keep maintainance Keeping maintainance and reinforcement ? Anyway, it is necessary to reconfirm the developing policy, to review and to reorganize it. Change to multi-regional emission model, improve climate and carbon cycle modules End-use, Energy, Technology Bottom-up

→Dr.Masui →Dr.Ashina →Mr.Hibino

Mr.Gomi

→Mｓ.Kawase →Dr.Hanaoka

Dr.Kanamori Mr.Akashi

→Dr.Hijioka