Development of Multi-region and Multi-sector IAM - Project ... · Natural resources and Industry...

An Integrated Assessment of Global Warming Mitigation and Adaptation

and the Development of Multi-regional and Multi-sector IAM

- Project Phoenix -

Shunsuke MORI (RITE, Tokyo Univ. of Sci.)Toshimasa Tomoda, Hiromi Yamamoto, Keigo

Akimoto, Koji Tokimatsu, Takanobu Kosugi, Ayami Hayashi, Takashi Honma (RITE)

Integrated Assessment Models as a platform of the policy and technology assessments

• Integrated assessment models (IAMs) have been developed since 1990s as a powerful tool for this subject.

However,

• Economic models and technology assessments deal with near future (until 2020) while existing IAMs mainly talk about near 2100.

• Economic models and technology assessments mainly analyze country level while existing IAMs mainly aggregate the world into 10-15 regions.

• Globalization, civilization, penetration of IT, industrial structure changes etc. are not well discussed in the global environmental context.

Project Phoenix- Paths toward Harmony Of Environment, Natural resources and Industry complex –

• Developed by the RITE - Research Institute of Innovative Technology for the Earth

• Supported by the Ministry of Economy, Trade and Industry as a part of an “International Research Promotion Funds for the Global Environment”

• A project for 2002-2006 (five years)

Structure of Project Phoenix – three WGsMulti region and sector model GTAP

+ Easy to connect with GAMS- Dynamics- Aggregated energy technologies and sources

(Model development WG)

Energy demand, economic activities, structural changes

+ Data availability (trade andeconomic statistics)

- Societal structural change

(Warming factors WG)

Assessments of global warming

+ Availability on food, water, climate change studies

- Uncertainties of global warming damages

(Warming impacts WG)

A: Economic activities GTAP modelmulti regional and multi-sectoral

- CGE model- static model- energy flow and technologies

should be integrated

B: Energy flow modelexisting research activities in RITEDNE-21 and LDNE-21Energy demand scenarios should be provided based on the economic and societal story-lines.

H: Assessments of regional

optionsCGS, distributed energy systemsrenewable sourcesrecycling and waste managements

G：Energy demandtransportationpublic and householdlong-term growth patternsstructural changes

I: Regional structure change

civilizationsocial structuremodeling methods

C: Assessments of Global climate changesimple climate models(MAGICC, BERN)

D: Assessments of regional climate

changeGCM dataGIS

E：Assessments of global warming

water resourceocean, river and lakesland usefood productionvegetation etc.

J: Biospherehuman healthimpacts on biosphere

F: Food supply and demand

K: Mitigation investmentex-post expenditureex-ante investmentcost-benefit integrated assessments

subjects in 2004subjects after 2005

L: GHG emission scenariodetailed regional emission scenario

Tentative IAM structure and results• GTAP (Purdue Univ.) incorporates more than 60 regions and

sectors and is still being expanded.• GTAP is designed to assess the international trade and

production impacts of various policy options.• GTAP-EG includes energy flow subsystems.• GTAP provides comprehensive and consistent world economic

data base.

In Phoenix Project,• We aim at the assessments of the certain technologies such as

energy conversion technologies, carbon capture options, biomass production and utilization, etc.

• Dynamic model simulation is also needed. • We impose the bottoming up technology model into the GTAP

model simplifying the frame, if necessary.

Conceptual Frame of the Model Intermediate Inputs Final demand

Non-energy sectors Energy sectors trade

Investments

ConsumpTion Output

1 2 PrimarySecondary m I C Q

1

X11=Q1・a11

X12=Q2・a12 ００ｍ1 I1 C1 Q1

2

X21=Q1・a21

X22=Q2・a22 ００ｍ2 I2 C2 Q2

Primary ０００ Xpe ｍp ００EC_pre=PpS

Secondary

Xe1=PeE1

Xe2=PeE2 ００００

Ce=PeEc

EC=PeE

K Pk・K1 Pk・K2

L PL・L1 PL・L2

Output Q Q1 Q2EC_pre=PpS

EC=PeE Q

VA_pre VA_E

Y

ValueAdded

EnergySectors

Non-energySectors

Int.Inputs

V=f(K,L,E)-(secondary energy input costs)

VA_E=Σ(capital and labor costs of energy conversion

technologies )+(others)

VA_Epre=Σ(capital and labor costs of primary energy extraction and

production costs)+(others)

(Total secondary energy supply)=Σ(Conv. Eff.)＊(primary energy inputs)

Integration of energy flow

Trade Investment

Consumption

EIS Y AGR SER CRU OTR COL GAS OIL ELE M I C Q

YAGRSERCRU 0OTR 0COLGAS 0OIL 0ELE 0

capital Klabor L

Q

Intermediate inputs Final demand Output

Non energy sectors(j)

Energy sectors (e')

Int.inputs

Non-energysectors(i)

EIS

Energysectors 0

0

VADD

Output

tjijQa , teie ECb ,′ titi mx ,, − tiI , tiC , t,iQ

tOILCRUEC ,,

tMete EP ,,, ⋅ teEC ,tELEesEC ,,

tjsjtjs QeEC ,,, = tCsEC ,,

tjtjtj LKV ,,, += teV ,′

titj QQ ,, = tete ECEC ,, =′

EIS Y AGR SER CRU OTR COL GAS OIL ELECRU 0

OTR 0

COL

GAS 0

OIL

ELE 0

Non energy sectors (j) Energy flow Trade Consumption

Production

Prices

0

0

tOILCRUE ,,

tMeE ,,teE , teP ,tELEes

E ,,

tjsE ,, tCsE ,,

Energy flow in DNE-21 model:simplified structure will be imposed.

Natural Gas Splitting

Coal Gasification

Biomass Gasification

Coal Liquefaction

IGCC with CO Rec.2

Biomass Liquefaction(Fermentation)

Shift Reaction

CO2 Recovery

CO Liquefaction2

CO Compression2

CO Injection2

Methane Synthesis

Methanol Synthesis

EORGas WellAquifer

Ocean

Methanol Synthesis

CoalMethanolCO (pipeline)2

CO (tanker)2

Water Electrolysis

Water Electrolysis

H Liquefaction2 Hydrogen (tanker)

Methane (tanker)

Synthetic. Oil

Hydrogen (pipeline)

Methane (pipeline)

CH Liquefaction4

Methanol Upgrading (into Gasoline)

Oil Refinery(Distillation)

Oil Refinery (Gasoline)

Natural Gas

Methane

Crude Oil

Synthetic Oil

Oil

Coal

Coal

Energy Crops

Wind&O.R.E.

Photovoltaics

Nuclear

H2

CO

CH4

CO2

CO2

CH OH3

Methanol

Electricity

CO Disposal2

Hydrogen

From Other Regions

From Other Regions To Other Regions

To Other Regions

Hydro

Geothermal

Electricity

Gaseous Fuel

Light Fuel Oil

Solid Fuel

: Electricity Use

Gasoline

Heavy Fuel Oil

Modern Fuel WoodsWood Residues

Sawmill ResiduesTimber Scraps

Cereal Harvest ResiduesSugarcane Harvest Resid.

Bagasse

Paper Scraps

Black Liquor

Kitchen Wastes

Animal Wastes

Human Feces

Synthetic Oil

Crude Oil

SOx

Syn.Oil

Oil Refinery(Distillation)

Oil Refinery (Gasoline)

Biomass Liquefaction

Biomass Gasification(Anaerobic Digestion)

Crude Oil

EthanolCoal Cleaning

N.Gas power gen.

Meth. power gen.

Coal power gen.

H power gen.2

Biomasspower gen.

Oil power gen.

Oil power gen.

Photov. power gen.

Hydro power gen.Geoth. power gen.Nuclear power gen.

Sorbent InjectionWet limestone scrub.Wellman-Lord

Sorbent InjectionWet limestone scrub.Wellman-Lord

SOx Rec. in End Use

SOx Rec.in End Use

Aggregation of GTAP data into 18 regions and 18 non-energy sectors 18 regions

USA USA CAF Middle African countries

CAN Canada SAF South African countries

MCM Middle American countries JPN Japan

BRA Brazil CHN China, Hong kong, Taiwan

SAM Peru, Argentina, Chile, Uruguay and other south American countries

IND India

WEP West and middle European countries

ASN Asia NIES countries

EEP Hungary, Poland and other east European countries

TME Turkey and Middle-East countries

FSU Former USSR ANZ Australia, New Zealand and Pacific Island countries

NAF North and Middle African countries

XAP Other countries

Aggregation of GTAP data into 18 regions and 18 non-energy sectors 18 non-energy sectors

I_S Iron and steel LUM Wood, Pulp and printing

CRP Chemical industry CNS Construction

NFM Non-ferrous metals TWL Textiles, wearing, apparel and leather

NMM Non- metaric materials OMF Other manufacturings

TRN Transport equipments AGR Agricultural products

OME Other machinary T_T Transportation

OMN Minings ATP Aviation

FPR Food Products BSR Business services

PPP Paper, pulp and printings SSR Social services

Current Stage：

Two preliminarily dynamic models are developed.

(1)18-region and 18-sector model with 2 energy sectors (Primary and secondary)

(2) 1-region and 18-sector model with 6 energy sources and 4 power generation technologies

These two are being integrated.

Total Value-added

0

2000

4000

6000

8000

10000

12000

14000

1997 2007 2017 2027 2037 2047 2057

Year

Total Value-added

USA CAN

MCM BRA

SAM WEP

EEP FSU

NAF CAF

SAF JPN

CHN IND

ASN TME

ANZ XAP

Preliminarily Simulation Results: GDP18 region - 18 sector with 2 energy input model

Energy Consumption

0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

400.0

1997 2007 2017 2027 2037 2047 2057

Year

Final Energy Consumption(EJ)

USA CAN

MCM BRA

SAM WEP

EEP FSU

NAF CAF

SAF JPN

CHN IND

ASN TME

ANZ XAP

Preliminarily Simulation Results: Final Energy Concumption

18 region - 18 sector with 2 energy input model

JPN　Sectoral Domestic Production

0

200

400

600

800

1000

1200

1400

1997 2007 2017 2027 2037 2047 2057

Year

Domestic Production

(10million US$)

I_S CRP

NFM NMM

TRN OME

OMN FPR

PPP LUM

CNS TWL

OMF AGR

ATP T_T

BSR SSR

Preliminarily Simulation Results: Outputs by sector (Japan)


WEP Sectoral Domestic Production

0

500

1000

1500

2000

2500

3000

3500

4000

4500

1997 2007 2017 2027 2037 2047 2057

Year

Domestic Production

(10million US$)

I_S CRP

NFM NMM

TRN OME

OMN FPR

PPP LUM

CNS TWL

OMF AGR

ATP T_T

BSR SSR

Preliminarily Simulation Results: Outputs by sector (WEP)


USA　Sectoral Domestic Production

0

1000

2000

3000

4000

5000

6000

1997 2007 2017 2027 2037 2047 2057

Year

Domestic Production

(10million US$)

I_S CRP

NFM NMM

TRN OME

OMN FPR

PPP LUM

CNS TWL

OMF AGR

ATP T_T

BSR SSR

Preliminarily Simulation Results: Outputs by sector (USA)


CHN　Sectoral Domestic Production

0

200

400

600

800

1000

1200

1400

1997 2007 2017 2027 2037 2047 2057

Year

Domestic Production

(10million US$)

I_S CRP

NFM NMM

TRN OME

OMN FPR

PPP LUM

CNS TWL

OMF AGR

ATP T_T

BSR SSR

Preliminarily Simulation Results: Outputs by sector (CHN)


IND　Sectoral Domestic Production

0

100

200

300

400

500

600

700

800

900

1000

1997 2007 2017 2027 2037 2047 2057

Year

Domestic Production

(10million US$)

I_S CRP

NFM NMM

TRN OME

OMN FPR

PPP LUM

CNS TWL

OMF AGR

ATP T_T

BSR SSR

Preliminarily Simulation Results: Outputs by sector (India)


0

500

1000

1500

2000

2500

1997 2007 2017 2027 2037 2047

西暦年

GDP (10 billion USD)

制約無し

制約有り

YEAR

With policy

Without policy

Preliminarily Simulation Results:GDP (USA)1 region - 18 sector with 6 energy input model

with and without carbon emission stabilization policy

0

20

40

60

80

100

1997 2007 2017 2027 2037 2047

西暦年

電力価格 (USD/MWh)

制約無し

制約有り

YEAR

With policy

Without policy

Ele

ctric

pow

er p

rice

(US

D/M

wh)

Preliminarily Simulation Results:electric power price (USA)1 region - 18 sector with 6 energy input model


0

1

2

3

4

5

1997 2007 2017 2027 2037 2047

西暦年

炭素排出量 (GtC)

制約無し

制約有り

YEAR

With policy

Without policyC

arbo

n em

issi

on (

GtC

)

Preliminarily Simulation Results:carbon emission (USA)1 region - 18 sector with 6 energy input model


0

100

200

300

400

500

600

700

1997 2007 2017 2027 2037 2047

西暦年

炭素潜在価格（USD/tC）

Preliminarily Simulation Results:

Shadow price of carbon emission (USA)1 region - 18 sector with 6 energy input model


YEARSha

dow

pric

e of

Car

bon

emis

sion

($/

tC)

0

2

4

6

8

10

12

14

1997 2007 2017 2027 2037 2047西暦年

送電端発電電力量（TkWh）

石油

天然ガス

石炭

その他


Power generation mix without carbon policy (USA)1 region - 18 sector with 6 energy input model


YEAR

Ele

ctric

pow

er s

uppl

y (T

kwh)

Oil

Gas

CoalOthers

0

1

2

3

4

5

6

7

8

9

1997 2007 2017 2027 2037 2047西暦年

送電端発電電力量（TkWh）

石油

天然ガス

石炭

その他


Power generation mix with carbon policy (USA)1 region - 18 sector with 6 energy input model


YEAR

Ele

ctric

pow

er s

uppl

y (T

kwh)

Oil

Gas

CoalOthers

0 2 4 6 8 10 12 14 16 18

合計I_SCRPNFMNMMTRNOMEOMNFPRPPPLUMCNSTWLOMFAGRT_TATPBSRSSR

産業

付加価値生産額減少率（%）


Impacts of carbon policy; loss of sector products in 2047 (USA)1 region - 18 sector with 6 energy input model


Loss of product (%)

Indu

stry

Total

Integration : Scenario Generation and Simulations

Exogenous conditions

Lower warming factors & events

Upper warming factors & events

Lower warming factors & events

Upper warming factors & events

4:parameters, constraints, exogenous variables

5:Feedback:consistency

check

3:Scenario generation by X-I method

1:TAR-assumptions2:Structure Analysis among factors

Quantitative IAM- economy- technology- energy- natural resource- etc.

Structure Analysis for the Narrative Scenario Generation

Scenario Generation using X-I method -1

Originally developed by Gordon (1965) to see the complicated interactions among the events .

(1) Estimating the probability of occurrence of each technology

(2) Evaluate the degrees of impact among events

(3) Revise occurrence probabilities using Monte Carlo simulation.

Dalky pointed out the mathematical consistency in 1972.

Duperrin and Godet (Duperrin, 1975) proposed a new method to guarantee the mathematical consistency.

Kaya et. al. (Kaya, 1979) expanded their method；

(1)using causality probabilities instead of conditional probabilities based on the Markovian probability model.

(2)sequential linear programming method to assess the range of highdimensional state probabilities.

Dynamic expansion has been developed (Mori, 1984).

Scenario Generation using X-I method -21. Determine the set of events to be considered during the forecasting period.

2. Define the exogenous conditions affecting the event occurrences one-sidedly.

3. Estimate the occurrence probability of event i (i=1,2…n) at the end of the forecasting period P(i).

4. Estimate the “impact probability” P(i →j) : the occurrence probability of event j given the condition that the event i occurs solely in the beginning of the period.

5. Calculate the two-dimensional probability applying Markovian transition model.

6. Construct the mathematically consistent probabilities modifyingestimated two dimensional probability data set by

( ) ( ){ } ( ) ( ){ }∑ ∑ ≠−+−=

i ij

2*ij

2*i j,iPj,iPwiPiPwJ.min

where the consistent probabilities P*(i), P*(i,j) are the linear combinations of n-dimensional state probabilities {πk}.

Scenario Generation using X-I method -37. Calculate the ranges of {πk} using linear programming.

kπ.max.min

subject to ( ) ∑= k kkidiP π* , ( ) ∑= k k

kj

ki ddjiP π,* , 1=∑k kπ , 0≥kπ

kπ :n-dimensional probability ( ) ( )nkn

k2

k1 2,2,1kd,d,dP ΛΛ = .

kid =1 if even i occurs in the state k else k

id =0.

ex. Nuclear power technology forecasting for 1990-2010 (Mori and Kaya, 1984)

(1)FBR: some FBR(Fast Breeding Reactor)s are already developed.

(2)ATR: some ATR(Advanced Thermal Reactor)s are already developed.

(3)CAND: some CANDU-PHW reactors are developed.

(4)LWR-Pu: share of Plutonium recycling comes to 33% of total LWR fuel.

(5) Repro: some reprocessing systems for LWR-Pu or ATR are operating.

(6) Cent: some centrifugal separation plants are developed.

(7) Coal: the share of coal fired power generation comes to more than 20% of world electric power supply.

Example of X-I method - continued

1990 (0000000)0.688

1995 (0000001) (0000000) (0000010).22-.42 A: .25-.45

B: .27-.51.18-.37

2000 (0000011) (0001110).42-1.0 12-.93

2005 (0000011) (1001110).32-.81 .33-.82

2010 (1000111) (1001110).09-.17 .09-.12

Scenario A Scenario B

upper:occurrence state lower: range of probability

Scenario A: Coal-nuclear scenarioScenario B: Nuclear oriented scenario

Dynamic scenario sequences from 1990-2010

(1) FBR(2) ATR(3) CAND(4) LWR-Pu(5) Repro(6) Cent(7) Coal

Expected outcomes • The changes of the energy supply-demand systems,

industry structure changes and the international industry allocation scenarios will provide the basic information to assess the policy measures.

• The outcomes of the project will give the helpful information on the energy technology development strategies.

• The most preferable burden sharing scenario on the carbon emission reduction can be generated.

• Industry policies on the R&D on the energy and environmental technologies, technology transfer, and other industry strategies can be assessed under the global warming mitigation policies.

Development of Multi-region and Multi-sector IAM - Project ... · Natural resources and Industry...

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