Research Methodology (Session 2)

State-of-the-art Energy-Environment Models and their Applications for Policy Formulation

P. R. ShuklaIndian Institute of Management, Ahmedabad

Presented in: Tianjin University of Finance and Economics, TianjinMay 2013

Indian Institute of Management, Ahmedabad

Presentation Agenda

1. Energy Models: Introduction and Model

Architecture Bottom-up (Techno-economic) Models (e.g. MARKAL)

Top-down (Macro-economic) Models (e.g. ERB/MINICAM)

2. Integrated Assessment Models Soft-Linked Model Systems (AIM, IPAC, SLIM)

Global Integrated Assessment Models

3. Model Inputs: Socio-economic Scenarios &

Databases1. Global Scenarios

2. National/Sector-level Scenarios

3. Model Database

• Conclusions

Bottom-up (Techno-economic) Models

MARKet ALlocation Model:MARKAL

MARKet ALlocation Model:

MARKAL Multi-period linear programming

formulation Decision variables in different time periods(e.g.): Energy consumption Electricity generation Capacity utilization Investment in technologies Emissions

MARKet ALlocation (MARKAL) Model: Overall Model Architecture

Techno-economic Database

Economic Scenario

EmissionScenarioMARKAL

• Consumption and production of energy• Marginal ‘values’ of energy resources & technologies• Shadow price of external constraints (e.g. emissions)• Introduction and retirement of technologies

Bottom-up 3E (Energy-Economy-Environment) Model System

MINING IMPORT COLLECTION RENEWABLE EXPORT

COALN. GAS

OILBIOMASSNUCLEAR

RENEWABLE

45

ENVIRONMENT

ELECTRICITY PRODUCTION

COAL GAS HYDRO

NUCLEAR SOLAR

ENERGY

FUEL PROCESSING

PETROLEUM REFINERY GAS PROCESSING

75

ENDUSE DEVICES

PUMP TRACTOR

FURNACE MOTOR

BUS TRAIN

CFLTVOVENAC

AGRICULTURE

INDUSTRY

TRANSPORT

COMMERCIAL

RESIDENTIAL

67

235

TECHNOLOGY CAPITAL

EMISSIONS

ENERGY

ECONOMY SECTORS

Agr

Ind

Tran

Bldg

Electricity Generation

Coal

Gas

Crude Oil

Renewable

Nuclear

OilRefinery

Lighting

Cooking

Transport

Irrigation

Water Supply

Heating

Drive

Light Bulb

Heater

Motor

Pump

Stove

Car

Resource Secondary Energy Technology End-Use

Reference Energy System: B/U Model

Model Formulation(Linear Programming)

Objective FunctionTo minimize the discounted sum, over up to 100 years, of investment, operating and maintenance cost of all technologies plus the cost of energy imports and carbon tax

Subject to1. Demand Constraints (one for each end use demand)

WhereDMD…end-use demand technologyGRD…set of grades technologies/energy sourcesDM….class of all end use demandsT…..set of time periodsCig(t)…capacity of technology i of grade G in period t

Objective Function (cntd)

1. Capacity transfer constraints (to account for technology vintage carry over time periods)

2. Energy carrier balance constraints (supply >= demand of fuel)

3. Cumulative reserve constraints (fuel extraction <= total reserves)

4. Electricity balance constraints(day and night time modeling for electricity system)

Model Constraints

5. Process technology capacity utilization constraints (process activity <= available capacity)

6. Electricity production capacity constraints (electricity generation <= available capacity)

7. Electricity peaking constraints (extra capacity to meet peak demand)

8. Total emissions constraints (Carbon, SO2 etc)

Model Constraints (cntd.)

Top-down (Macro-economic) Models

•SGM (Second Generation Model)CGE: Computational General Equilibrium Model

•ERB/MINICAMPE: Partial Equilibrium Model

Computational General Equilibrium (CGE) Model

AGRICULTUREgrains and oil seeds

animal productsforestry

food processingother agricultural services

HOUSEHOLDSdemographics

labor supplyENERGY land supply

oil production household savingsPRIMARY FACTORS gas production final product demands

OF PRODUCTION petroleum refiningland surface gas distribution

subsurface resources coke and coal productslabor biomass production

capital uranium productionhydro and solar electric power GOVERNMENT

electricity production general governmentnational defense

education

Other Sectorspaper and pulp manufacture

chemical manufacturecement manufacture

primary iron and steelprimary non-ferrous metals

other manufacturingpassenger transport

freight stransportother services

SGM: Second Generation Model is a Global CGE Model (PNL, USA)

Regional Fertility & Survival Rates

Regional Labor Force

Regional GDP

Regional Labor Productivity

Energy Technologies R

egio

nal

Ene

rgy

Dem

and

Regional Resource Bases

Regional Energy Supply Technologies R

egio

nal

Ene

rgy

Sup

ply

Regional Prices

World Prices and Quantities

GHG Emissions

ERB Model: Core Elements of Energy Markets

ERB: Edmonds, Reilly, Barnes, Pacific Northwest Lab, USAERB Model is a global energy partial equilibrium model

Oil Production

Synfuel Conversion

Electric Power Generation

Solids

Liquids Refining

Hydrogen

N. Gas Production

Coal Production

Biomass Production

Synfuel Conversion

Gas Processing

Nuclear/Fusion

Hydro

Solar

Liquids Market

Solids Market

Natural Gas Market

Hydrogen Market

Electricity Market

Energy Markets: Regional Supply and Conversion

Liquids Market

Hydrogen Market

Electricity Market

Residential Sector

Commercial Sector

Industrial Sector

Transport Sector

Industrial Technologies

Transport Technologies

Solids Market

Natural Gas Market

Residential Technologies

Commercial Technologies

Energy Markets: Regional End Uses

Residential Service Demands:Indexing to floor space

IP

PHFuD

H

H

HDDFHH

0,

Heating Degree Days Internal Gains

Price of Heating ServiceBuilding Shell

Area

Heat Transfer CoefficientCalibration

Parameter

CC

CDDFCC I

P

PCFuD

C

0,

L

L

LLL P

PFD

0,

WW

WWW

W

P

PFD

0,

AA

AAA

A

P

PFD

0,

Thermal Energy

Thermal Energy

Lumens

Thermal Energy

Unitless

Heating

Cooling

Lighting

HotWater

Appliances& Other

ResidentialBuildings

- daylighting

Saturation Factor

Building Design

Transport Technologies

Passenger Transport

Freight Transport

Rail

Automobile

Bus

Air

Air

Truck

Rail

Water

Pipeline

ICE

Hybrid

H2

Diesel

Electric

Natural Gas

Energy Markets: Transport Sector

Primary input variables by fuel, mode and sector:

• 1990 Energy used• Intensity / Efficiency• Load factor• Speed

20

Agriculture, Land-use and Energy

Energy Module Regional

demographics

Regional GDP Demand•Crops• Livestock and fish• Forests products• Urban land

Demand for Commercial

Biomass

Demand for Biomass Energy

Supply•Crops• Livestock and fish• Forests products• Urban land

Water

Fertilizer

CO 2

Climate

Markets•Land rent• Crop prices• Livestock prices• Forest product prices• Biomass prices

Production•Crops• Livestock and fish• Forests products• Biomass energy

Commercial Biomass

Land Use Change Emissions

Technology Land Use•Crops• Livestock and fish• Forests products•Urban• Unmanaged

Policies• Taxes• Subsidies•Parks• Regulation

Oil Production

Synfuel Conversion

Electric Power Generation

Solids

Liquids Refining

Hydrogen

N. Gas Production

Coal Production

Biomass Production

Synfuel Conversion

Gas Processing

Nuclear/Fusion

Hydro

Solar

Liquids Market

Solids Market

Natural Gas Market

Hydrogen Market

Electricity Market

CO2 Capture & Storage

AIM Family of ModelsAIM: Asia-Pacific Integrated

Model

AIM Family: Typology & Examples

Explanation AIM familly Other models/study

No explicit modelling structures; simply assess the costs

of different technological options to reduce GHG emissionsAIM/Enduse[MAC] McKinsey's ACC

Accounting type

Listing up externally prescribed GHG emission activities

and suming up the associated GHG emission caused by

the activities

AIM/Snapshot STAIR, LEAP

Sectoral

optimization type

Technology-oriented models which minimize the total

costs of the system,often applied to energy system

including all end-use sectors, and compute a partial

equilibrium for the markets. The costs include investment

and operation costs of all sectors based on a detailed

representation of factor costs and assumptions about

GHG emission taxes

AIM/Enduse,

AIM/AFOLU

MARKAL,

MESSAGE

Input-Output type

Describing complex interrelationships among economic

sectors using sets of simultaneous linear equations. The

coefficients of equations are generaly fixed, which means

that factor substitution, technological change, and

behavioural aspects related to climate change mitigation

policies cannot be assessed. However, recent models,

especially in ExSS, these restrictions are fully relaxed.

ExSS TEESE

Computable

General

Equilibrium

(CGE)

Considering simultaneously all the markets in an

economy,and calculating the conditions which permit their

simultaneous equilibriums. The models typically simulate

markets for factors of production (e.g., labour, capital,

energy),products, and foreign exchange, with equations

that specify supply and demand behaviour, under various

LCD policies.

AIM/CGE SGM, ENVISAGE

Coupling of Bottom-up type and top-down type module AIM/CGE[basic] MERGE, IMACLIM-R

Abatement Cost Curve analysis

Type of model

Bottom-up models

Top-down models

Hybrid of bottom-up and top-down

models

AIM: Asia-Pacific Integrated Model is a family of models

Top-down and Bottom-up Approach

Strengths/Weaknesses of MAC Curvese.g. AIM/End-use [MAC], McKinsey's ACC

　 Key Features and Assumptions

　 Strengths 　 Weaknesses

・To identify specific cost-efficient technologies and GHG abatement options

・Allow ranking of specific options according to cost-effectiveness criteria

・No consistent view of the energy and economic system

・Compare selected GHG abatement options (e.g. fuel substitution policies)

・Help setting priorities among GHG abatement options

・Fail to consider the timing and interaction of GHG abatement options

・Collect technology-specific data to evaluate mitigation options individually

・Have simple and transparent structures and input assumptions

・Ignore economic transaction costs, which can be significant

Modified based on "Mapping the energy

future", IEA, 1998

25

MAC Curves: Marginal Abatement Cost Curves (e.g. cost of abating CO2 emissions)

Strengths/Weaknesses of B/U models

　Key Features and Assumptions

　 Strengths 　 Weaknesses

・Choice of the most efficient mix of technologies to deliver services

・In case of energy sector, provide a comprehensive, coherent picture of the energy system (from primary energy to final energy and energy services use)

・Neglect feedback effects of emission reduction policies on the rest of the economy

・Rich collection of related data, abundant in detail on various technologies and countermeasures

・

Useful for assessing and identifying mitigation and efficiency potentials

・Do not capture demand-price interactions

・Perfect foresight· simulates perfect competition among technologies and energies

・Enable assessment of supply and demand-oriented policies to curb GHG emissions

・Undervalue the transaction costs of mitigation policies

　　 　　 ・Assume that markets react perfectly to price signals

Modified based on "Mapping the energy

future", IEA, 1998

26

• “Energy technology” refers to a device that provides a useful service by consuming energy

• “Energy service” refers to a measurable need that must be satisfied.

Structure of the AIM/End-Use Model

OutputsInputs

e.g. AIM/End-use, AIM/AFOLU, MARKAL, MESSAGE

End-use approach

AIM/Enduse model puts much focus on this part

World energy assessment: energy and the challenge of sustainability, 2000,UNDP

Energy Service Demand Conversion to Energy demand

Correspondence between Issues & models

Design target year’s societies by ExSS

One/multi- regional multi-sectoral analysis Check and analyze

quantitative consistency of future societies

Design target year’s societies by ExSS

One/multi- regional multi-sectoral analysis Check and analyze

quantitative consistency of future societies

Quantitative design of basic mechanisms by element models

• Energy enduse models (AIM/enduse)

• Energy supply model (ESM)• Traffic demand model (TDM)• Econometric type macro-economy

model (EME)• Population and household model

(PHM)• House and building dynamics

model (BDM)• Material stock dynamics model

(MSFM)• Household production and

lifestyle model (HPLM) • AFOLU model (AFOLU)

Quantitative design of basic mechanisms by element models

• Energy enduse models (AIM/enduse)

• Energy supply model (ESM)• Traffic demand model (TDM)• Econometric type macro-economy

model (EME)• Population and household model

(PHM)• House and building dynamics

model (BDM)• Material stock dynamics model

(MSFM)• Household production and

lifestyle model (HPLM) • AFOLU model (AFOLU)

Design target year’s social/economic/ energy

vision quantitatively

Major outputs of models are Policy portfolio, GHG emissions inventory, Energy balance table, IO table, Labor/population balance table, Transport demand and supply table, Household account, Macro economic account, Price, etc.

Design social, physical LCD’s details based on

more physically realistic mechanisms

RoadmapEconomic analysis Design of target society and

Reduction potential

Backcasting analysis by BCM/BCT

Design roadmaps towards future

designed societies

Backcasting analysis by BCM/BCT

Design roadmaps towards future

designed societies

LCD visions

and

LCDPolicies

• Economic instruments

• Regulation• Education• Public

investments• etc.

LCD visions

and

LCDPolicies

• Economic instruments

• Regulation• Education• Public

investments• etc.

Economic analysis by AIM/CGE

One/multi- regional multi-sectoral CGE analysis

Check and analyze quantitative economical consistency of future

societies

Economic analysis by AIM/CGE

One/multi- regional multi-sectoral CGE analysis

Check and analyze quantitative economical consistency of future

societies

Not all of them are applied. Depending on the situation, some are intensively applied.

Strengths/Weaknesses of T/D (input-output)

Models

29

　Key Features and

Assumptions　 Strengths 　 Weaknesses

・Systematic description of sectoral interrelationships in an economy

・Provide detailed analysis of inter-sectoral feedback effects for GHG abatement policies on a sectoral level

・External assumption of IO coefficients, macroeconomic structures

・Focus on statical snapshot status of emission reduction policies

・Easy to operate and interplete the results than CGE model

・Cannot consider price effects

　　 ・Well suited to look at recycling of carbon taxes (the "double-dividend" issue)

・Not well internalize to address issues of dynamic, technological, behavioral change

　　 　　 　　

Modified based on "Mapping the energy

future", IEA, 1998

Framework of Extended Snapshot Tool (ExSS)

e.g. ExSS

Strengths/Weaknesses of (CGE) models

Framework of AIM/CGE

　 Key Features and Assumptions

　 Strengths 　 Weaknesses

・Markets and the economy, as a whole, reach equilibrium, through price adjustments

・Present economy-wide costs of reduction policies, including trade effects

・Poor description of energy end uses and technologies

・Markets work efficiently (no market barriers, hidden costs or information barriers)

・Describe economic interactions among sectors in detail

・Assume that markets always work efficiently

・Able to analyze long-term resource allocation

・Able to assess long-term effects of GHG abatement policies on structural change in a coherent macro-setting

・Do not well reflect short-run economic adjustment costs

　　 　　 ・　

Have a weak statistical basis (usually models are calibrated on a single-year basis)

Modified based on "Mapping the energy

future", IEA, 1998

output matrix

energy balance table(output)

energy balance table(input)

input matrix

energ

yno

n-

energ

y

production sector final demand sector

value

adde

den

ergy

non

energ

y

output coefficienton energy

production and cost

production and income

comm

odity

supp

lyco

mmod

ity de

mand

fixed capital stockmatrix

production social

cap.

good

s

capital stock

labor

capital

comp

ensa

tion

of ca

p. go

ods

final

cons

inves

tmen

t

impo

rt&ex

port

input coefficienton non-energy

output coefficienton non-energy

capital profilein sector

SNA

tech&preference

IO tablein 2000

fixed capitalformation

matrix in 2000

tech

tech V matrixin 2000

economicgrowth

input data in2000 assumption balance condition

intermediatedemand

ext. trnsact.account

account ofinc. & expnd.

Input coefficient on energy

energy balancetable in 2000

①

①

②

②

③

④

⑤

⑥

⑥

⑥

⑦

⑧

⑩①

①

⑪

⑦

⑩

⑪

⑨

②

tech

tech

output

CO2⑫ ⑫

Macroeconomic module

CGE module

① production function

② commodity market

③ capital market④ labor market⑤ calculation of GDE⑥ expenditure and

income in production sector

⑦ expenditure and income in household and government

⑧ assumption of import and export

⑨ fixed capital stock matrix

⑩ investment goods market

⑪ capital stock ⑫ CO2 emissions

e.g. AIM/CGE, SGM, ENVISAGE

IPAC: Integrated Policy Model for

China

Framework of Integrated Policy Model for China (IPAC)

ERI, ChinaERI, China

IPAC-SGM

IPAC-Emission

IPAC-AIM/tech

IPAC/Tech(Power/Transport)IPAC/SE, IPAC/EAlarm

IPAC-TIMER

IPAC/AIM-Local

Energy demand and supplyPrice/investmentEconomic impactMedium/long-term analysis

Medium/short term analysis Technology assessmentDetailed technology flow

Region analysisMedium/short analysisEnergy demand and supplyTechnology policy

IPAC-AIM/MATERIAL

Energy demand and supplyFull range emissionPrice, resource, technologyMedium-long term analysisEconomic impact

Environment industryPollutant emissionMedium/long-term analysis

Technology developmentEnvironment impactTechnology policy

AIM-air IPAC-health

Energy demand and supplyPrice/investmentMedium/long-term analysis

Short term forecast/ energy early warning

Climate Model

IPAC/Gains-Asia

Future economic sector detailEnergy intensive industryReduction cost

China energy and emission scenariosEnergy demand by sectorsEnergy supply Reduction cost

Global ModelIPAC-Emission

Energy technology modelIPAC-AIM/technology

Energy economic modelIPAC-CGE

Global energy demand and supplyGlobal GHG EmissionGlobal TargetBurden sharingEnergy import/exportEnergy PriceReduction cost

Linked Economy-Energy Models (Global-China)

工业分部门投资

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

2005 2010 2020 2030 2040 2050年份

亿元

建筑业

自来水的生产和供应业

煤气的生产和供应业

蒸汽热水生产供应业

电力生产供应业

其他工业

仪器仪表文化办公用机械

电气机械及器材、 电子及通信设备制造业

交通运输设备制造业

普通机械、 专用设备制造业

金属制品业

有色金属

黑色金属冶炼及压延加工业

非金属矿物制品业

橡胶制品业, 塑料制品业

化学纤维制造业

医药制造业

化学原料及制品制造业

炼焦业

石油加工

印刷业记录媒介的复制, 文教体育用品制造业

造纸及纸制品业

木材加工及竹藤棕草制品业、家具制造业

服装皮革及其他纤维制品制造

纺织业

烟草加工业

食品饮料加工、 制造业

非金属矿采选业, 其他矿采选业, 木材及竹材采运业

有色金属矿采选业

黑色金属矿采选业

天然气开采业

石油

煤炭采选业

农业

Investment by industrial sectors (Example)

DATABASES

-Socio -Economic, Technologies, Energy Resources, Environmental Constrai nts

AIM CGE Model

ANSWER -MARKALModel

AIM SNAPSHOT ModelEnd

Use

Dem

and

Mod

el

AIM

Strategic Database

(SDB

)

DATABASES

AIM SNAPSHOT ModelEnd

Use

Dem

and

Mod

el

Socio-Economic, Technologies, Energy Resources, Environment

AIM CGE/GCAM-IIM

ANSWER-MARKALModel

AIM ExSSEnd-

Use

Dem

and

Mod

elScenario D

atabase

Soft-Linked Integrated Model System (SLIM)

Transport Demand Model Transport Database

Transport Model

Soft-Linked Integrated Model System

Sustainable Transport Indicators D

atabase

GCAM: Integrated Modeling Framework

ATMOSPHERIC COMPOSITION CLIMATE & SEA LEVEL

HUMAN ACTIVITIES ECOSYSTEMS

MAGICC

Atmospheric Chemistry

MAGICC

Ocean Carbon

Cycle

MAGICC

Climate

MAGICC--Ocean

· temperature

· sea level

ERB

Energy

System

ERB

Other Human

Systems

ALU

Ag., L'stock

& Forestry

(none)

Coastal

System

MAGICC

Terrestrial

Carbon Cyc.

ALU

Crops &

Forestry

Un-managed

Eco-system

& Animals

ALU

Hydrology

GCAM: Global Change Assessment Model (Application for Climate Change)

Integrated Assessment Model: GCAM

• Economy-Energy-Agriculture Market Equilibrium (Edmonds et al., 2004)

• 14 Global Regions Fully Integrated

• Explicit Representation of Energy Technologies

• Tracks 15 greenhouse gases

• Dynamic-recursive model

• Typically runs to 2095 in 5-year time steps

• Used extensively for energy and climate policy analyses conducted for DOE, EPA, IPCC, etc. (Clarke et al., 2007)

Labor Force

Labor Productivity

Energy Demand•Transportation•Buildings•Industry

Agricultural Demand•Crops•Livestock•Forest Products

Energy Demand

Technologies

Agricultural Technologies

Land Characteristics

Agricultural Supply•Crops•Livestock•Forest Products•Bioenergy

Energy Supply•Coal, Gas, Oil•Renewables•Electricity•Hydrogen

Energy Conversion

Technologies

Resource Bases

GCAM: Human & Natural System Integration

Energy Markets•Fossil fuel prices•Electricity prices•Hydrogen prices

Energy Markets•Fossil fuel prices•Electricity prices•Hydrogen prices

Agricultural Markets•Crops prices•Livestock prices•Forest Product prices•Bioenergy prices

Agricultural Markets•Crops prices•Livestock prices•Forest Product prices•Bioenergy prices

Economy

Energy System

Agriculture/Land Use

Other Markets•Emissions Permits•Portfolio Standards

Other Markets•Emissions Permits•Portfolio Standards

Fossil and Industrial Emissions

Fossil and Industrial Emissions

Land Use and Land Use Change

Emissions

Land Use and Land Use Change

Emissions

Ocean Carbon Cycle

Ocean Carbon Cycle

Atmospheric Composition,

Radiative Forcing, &

Climate

Atmospheric Composition,

Radiative Forcing, &

Climate

Terrestrial Carbon Cycle

Terrestrial Carbon Cycle

Land Use & Land Cover

Climate System

Regional GDP

3. Model Inputs: Socio-economic Scenarios & Databases

Global Scenarios

National/Sector-level Scenarios

Indicators

Model Database

Global Scenarios SRES: Non-climate intervention Scenarios Representative Concentration Pathways

(RCPs)

IPCC Scenarios: SRES Architecture

Economy

Environment

RegionalismGlobalism

A2: cultural pluralism

B1: recycle-based

B2: regional coexistence

population

Economic growthtechnology energy

Agriculture(land use)

Driving Forces

A1: high growth

(A1FI)

(A1T)A1B

• Scenarios: Images of future or alternate futures.

• Scenarios are not Predictions or Forecasts.• Used as a methodology in energy &

environmental analysis: Account for future uncertainties in energy planning and to study likely implications of current policy pathways.

Scenario Analysis

SRES Scenario Families

CO2 Emission Scenarios

Representative Concentration Pathways

Ref. Krieger et. al. 2010

IPCC Representative Concentration Pathways (RCPs)

Ref. Edmonds, 2010

Emission Paths for RCPs

Papers Available online (August 2011) in ‘Climatic Change’, Springer

National Scenario Architecture

Global & Regional Cooperation

High Low

Hig

h 9% Growth 8% Growth (Base)

Ref

orm

s

Low

7% Growth 6% Growth

Base

GDP- 8% CAGR (2005-30)Energy Reform (ER) - Moderate

Global Environ (GE) -CO2 650 ppm (CO2e)Local Environment (LE) -SO2 Moderate Regional Cooperation (RC) - Moderate

Globalization (G) - Moderate

RegionalCo-

operationReformsEnergy Reform

Environment Reform

6%

GDP- 6%ER - Low RC - LowG - Low

9%

GDP – 9%ER - HighRC- HighG – High

7 %

GDP- 7%RC - LowG – High

Coal Reform

ER – Improved Coal Supply

CBW

ER - Electricity Generation

Reform

Global Environment

GE - 550 ppmCO2e

Local Environment

LE – Year 2005 SO2 Emission =Year 2030

Regional Energy

Cooperation

RC - High

Base

GDP- 8% CAGR (2005-30)Energy Reform (ER) - Moderate

Global Environ (GE) -CO2 650 ppm (CO2e)Local Environment (LE) -SO2 Moderate Regional Cooperation (RC) - Moderate

Globalization (G) - Moderate

RegionalCo-

operationReformsEnergy Reform

Environment Reform

6%

GDP- 6%ER - Low RC - LowG - Low

9%

GDP – 9%ER - HighRC- HighG – High

7 %

GDP- 7%RC - LowG – High

Coal Reform

ER – Improved Coal Supply

CBW

ER - Electricity Generation

Reform

Global Environment

GE - 550 ppmCO2e

Local Environment

LE – Year 2005 SO2 Emission =Year 2030

Regional Energy

Cooperation

RC - High

Sector Scenarios: E.g. Trasnsport

Changes due to price of carbonChanges due to price of carbon

Changes due to targeted strategies + a carbon budget equivalent to conventional scenario

Changes due to targeted strategies + a carbon budget equivalent to conventional scenario

Passenger FreightPassenger & Freight

Strategic Model Database: AIM System

OutputsOutputs

OutputsOutputs

Outputs

CommonCommonDatabaseDatabase

Monitoring & Processing Data

from IEM

AIM-Trend

AIM-EnergyAIM-Top-down

AIM-Material AIM-Ecosystem

Policy making

Statistics

1. A variety of Energy Models are available

2. Choice of model depends on the purpose or the key questions to be addressed by the model (Horses for Courses)

3. Purposive modeling need strategic scenario databases.

4. Global Integrated Assessment Models (IAMs) are vital tools to assess log-term trends in energy and technology markets

5. Scenarios Assessments project, but not predict the future

6. Consistent geographic downscaling of scenarios is vital for policy assessment

Conclusions

Thank you