AIM approach on regional low carbon
development in Asian region, 2015

The 21th AIM International Workshop
November 14, 2015
Ohyama Memorial Hall, NIES
Tsukuba, Japan

Speaker: Yuzuru Matsuoka, Kyoto University, JapanThe 21th AIM International Workshop, 20151

Three important aspects of Low Carbon Development (LCD) study
1. Planning of Low Carbon Society and its realization cannot be
conducted without multi‐disciplinary, integrated andquantification methodologies.
2. Not only the planning of LCD Actions, but also themonitoring and improvement of the plans are crucial torealize LCSs. Integrated and quantification methodologies arealso useful to these stages.
3. Establishing the methodologies and apply them to thetarget regions, taking account of regional distinctive
diversified characteristics, is indispensable.
The 21th AIM International Workshop, 20152

Three special characteristics of LCS policies
Long‐term

Relate to whole socio‐
economic activities

Characteristics

Relate tomany policies
Note

1.

Long‐term horizon, 5 to 50
years from now, the worldof totally different from
historical trends

Drastic changes expected in the regional
economy, demography, transportation system,
technology, and lifestyle.
Difficult to project with simple extrapolation ofhistorical trends

2Strong and complex
relations to nearly wholesocio‐economic activities

Macro‐economy, Industry, Agriculture andForestry, Transportation, Energy Supply andConsumption, Land use, and people’s Lifestyle

3

Strong relations to many
policies. In other words, alarge rooms of enhancing
co‐benefits

Environment policies, Waste policy, Water
policy, Transportation management, Economic
and Industrial policies, and so on3

4

Necessity of integrated quantitative scenario approach
The previous characteristics restrict the methodology within the following:
Characteristics

How to deal with it ?

1. Drastically different socio‐
economies in future andhard to extrapolate from
historical trends

Based on sound and scientific principles withquantitative expressions, such as balances ofdemand and supply in monetary term (Social
Accounting Matrix), energy flow (Energy Balance
Table), and so on

2. Strong and complex relations Cross sector analysis, such as input‐output
to nearly whole socio‐
analysis, integration of sector specific modules,
economic activities
and so on
3. Strong relations to many
policies

Consideration of a bundle of quantitative targets,policies, and their interactions, not only the
direct reduction policies, but also related ones.

On top of the above, the methodology should be transparent, easy to operate andunderstand.

These are the necessity of integrated quantitative scenario
approach, which we are now adopting.
4Up to now, we have applied and are applying
our methodology to 8 nations and 14 regions in Asia regions
Malaysia
Japan

Putrajaya

Kyoto
Shiga

Cyberjaya
IskandarMalaysia

China

India
BhopalGuan Zhou
DalianAhmedabadThailand

Vietnam

KhonKaenHồ Chí MinhĐà Nẵng

S. KoreaHải Phòng

Kyonggi‐doStage of Study

BangladeshIndonesia
Cambodia

Preparing
study

ScenariomakingScenario
study
finished

PolicyImplementation and
Monitoring

Ex‐postevaluation5

Progress of Asian regional studies
after last AIM workshop (Jan. 2015‐Nov.2015)
regioncountry

IskandarMalaysia

Malaysia

Hồ Chí Minh

VietnamĐà Nẵng

stage
Scenario study
is finished

note
•
•
•

VietnamScenario making
is in the last
stage

•

Preparing stage

•

•

•

Hải Phòng

Vietnam

Preparing stage••

Cambodia
Kyoto

Cambodia
Japan

Scenario making
is in the last
stage

•

Interimevaluation isfinished•••

Project sponsored by JICA/JST is over by June
2016
Refinement to five local authorities
Conducting detailed documentation
Qualitative design of the cities’ Climate Change
Action Plan (CCAP)
Report to the city government in November, 2015
Preliminary analysis using ExSS and it’s
discussion with city government
Finish within this FY
Institutional arrangement for the collaborative
study
Finish within this FY
Finish the improvement of analysis of energy
related sector’s scenario
Extensions to AFOLU and waste sectors
Interim evaluation of on-going LCS policies
Reanalysis of present emission reduction target’s
feasibility

The 21th AIM International Workshop, 2015

6

Final evaluation of Iskandar Malaysia (IM) project
conducted by JICA Terminal Evaluation Team, October 15, 2015
• Project name: Development of Low Carbon Society Scenarios for Asia Regions(SATREPS*)• Research Team: Kyoto University (KU), National Institute for Environmental Studies(NIES), Okayama University (OU), University Technology Malaysia, Iskandar Regional
Development Authority (IRDA), etc.
• Objectives: Establish and utilize LCS scenarios for policy development in Iskandar
Malaysia, and disseminate the approach to Asian region• Evaluation by 5 criteria:
1) Relevance: Very High, 2) Effectiveness: Very High, 3) Efficiency: High,4) Impact: Very High,5) Sustainability: High• Conclusion of evaluation:
All indicators of the project purpose have been achieved. Moreover, various and many
positive impacts such as creation of LCS scenarios in other regions based on thisproject have been expanding from IM to other areas in Malaysia, and other Asian
countries. This project is identified as one of the best projects in the history of
SATREPS.
* SATREPS: “Science and Technology Research Partnership for Sustainable Development”, a project funding scheme by JICA and theJapan Science and Technology Agency (JST)The 21th AIM International Workshop, 20157

Documentation efforts of
AIM regional LCS scenario
approach

1. General
Procedure of
LCS Scenario
Development

2. Objective,
scopes andgoals of LCS
Policy3. PDCA cycleof LCS policy

4. Making plans
and their
improvement

The details of 5 step approach and supporting tools will be
explained in two forthcoming textbooks, i.e.
• “Technical Guide to Low Carbon Societies” and• “PDCA Textbook: Guidance on Planning and
Implementation of LCS Policy”.
The 21th AIM International Workshop, 2015

5. Assessment of GHG
and Non‐GHG effectsof the policies

8PDCA cycle of LCS policy (1)PDCA process of LCS policy: an iterative management procedure with continuous
improvement of the planning and implementation process of LCS policy.
1) “Planning and pledge” phase by regional authorities,2) Implementation phase (“Do”),
3) Evaluation phase (“Check”),
4) Improving phase based on the results of evaluation (“Act”).

Three levels of PDCA: In order to utilize the PDCA process of LCS policy, hierarchicalcharacteristics by the difference in level of implementation entities and the implemented.
Three levels of PDCA are existed from a view point of the lengths of cycling and levels ofdetail.
1) “Strategic” level, with a time frame of five to several ten years, may be vague, and themain entities related are organizational, board, or executive level.
2) “Managerial/tactical” level, with a year time frame, have a high level of detail, and aremanaged by the unit or department level.
3) “Operational” level, more short term and more detailed level.
The 21th AIM International Workshop, 2015

PDCA cycle of LCS policy (2)Strategic and Managerial levels
Strategic Level PDCAManagerial/Tactical Level PDCALCS Action
Every 5 to several ten year’s cycle

LCS Program/Measure
Every year’s cycle

Plan

Plan

• Design of the Actions> Set overarching target and each Action’s target> List‐up and disposition of programs (ABS)> Conceptual design of programs and Roadmaps• Ex‐ante evaluation of Actions/Programs• Dissemination of the planDo
• Management and adjustmentof Programs implementation

Check

P
D
C
A(P)
D

Act (Re‐Plan）• Amendment of the Actions> Modification of targets> Improvement of Action‐Program scheme> Re‐design of programs and Roadmaps

・・・• Integration of tracking indexes• Ex‐post evaluation of Actions/Programs• List up problems on the Action management• Detailed design of programs• Creating the enabling environment• Development of implementation/
monitoring plans

Do• Implementation and operation ofprograms

Check• Tracking of performance indexes• Review of program performance• List up problems on operation

Act (Re‐Plan)• Improvement, modification orsuspension of programs

Do

Do
10
The 21th AIM International Workshop, 2015

Quantification tools
supporting PDCA process of LCS policy

Planning

Stage

Task

Tools and their role of supporting PDCA process

Design of the Actions
Organize/Construct Action scheme
Set overarching target and each Action’s
targetList-up and disposition of programs
Preliminary design of programs
Ex-ante evaluation of Actions

Act (Re-Plan）

Check

Doing

Rough design of action roadmap

Organize and construct Action scheme with "Action Breakdown Structure" (ABS)
Analysis of action and program structure with "Action Design Structure Matrix"(ADSM, DSM of actors, measures and emission mechanisms)
Quantitative assessment of target feasibility, and contribution of each program(ExSS)
Cost-Effectiveness-Resource affordability analysis of actions and programs
Quantitative feasibility assessment of the action roadmap with "BackCasting Tool"(BCT)

Dissemination of the plan
Programs implementation, management and adjustment of operation
Monitoring and reporting of operational indexes
Monitoring and integration of tracking indexes

Improvement of quantification tools, recalibration of system parameters, andexternal factors

Ex-post assessment of Actions/Programs

Quantification of action's progress

Listing up of problems on action management,
progress and their quantitative assessment

Attribution of the discrepancies between plans and real progresses, to programs
and implementers

Feasibility check/Modification of targets
Improvement/Re-design of Action-Program
schemeReassessment of target feasibility
Re-analysis of cost-effectiveness-resource affordability of actions and programs

Reallocation of resources for actions
Re-design of Roadmaps

Revision of the action roadmap with "BackCasting Tool" (BCT)The 21th AIM International Workshop, 201511

Modeling of “Emission structure”
and “Counter measure structure”
In order to analyze the PDCA process, quantitatively and transparently, we need to have operationalmodels of “Emission structure” and “Counter measure structure” of the LCS system
Schematic diagram of “Counter measure
structure” and “Emission structure” models

Generic equations of “Counter measure structure
model” and “Emission structure model”
Four sets of variables
Exogenous variables discribing
environment and constraints

: ZX  ZX z | z  Z 

Exogenous variables discribing countermeasure (action/measure)'s intensity:RX  RX pm | pm  PM 

Endogenous variables describing
system behavior, including emissions
and quantified targets

: SX  SX st | st  ST 

Endogenous variables connecting countermeasure structure and emission structure(Direct Measure), which are a part of SX
: MX DM  MX dm | dm  DM 

Two sets of system equations   Equation of counter: MX DM  GDM ZX , RXmeasure structureEquation ofemission structure
The 21th AIM International Workshop, 2015   : SX  GSM ( ZX , MX DM )12

A model of emission structure (1)Simple emission model “S‐model”
Consider a typical emission structure of gas g emission from sector c :where:



 

 
Gg ,c  Ac   iss ,c     id 2d ,s  sd 2d ,s      id 1d ,s  sd 1d ,s     iee,d  igeg ,e   sS ( c ) 
 e
 
 dD 2( s )  dD1( s )


Gg,c
Ac

: Emission of Gas g in sector c: Activity of sector c. Depending to ZX

iss,c: Service demand intensity of service s in sector c

id1d,s: Production rate of service s by d (∊D1)

sd1d,s: Share ratio of service production device d (∊D1) in service s

id2d,s: Changing rate of service s by d (∊D2)

sd2d,s: Share ratio of service economizing device d (∊D2) in service s

iee,d: Energy intensity of d for energy e. In case of e='ne' (non-energy), ie'ne',d=1
Direct gas emission intensity of gas g by operating d. In this formulation, it is replaced by:igeg,'ne',digdg,digeg,e,d:

Emission coefficient of gas g from d and energy e. In case of e='ne'(non-energy), it is sameas igdg,dAlso, aliasing a set of variables with IVEg,e,d1,d2 as:

SX

iveIVEg , e , d 1, d 2

   A , is , id1 , sd1 , id 2 , sd 2 , ie , ige 
c

s ,c

d 1,s

d 1, sd 2,sd 2, se ,d 1g , e ,d 1

Considering s and c are specified by d1 or d2, gas g emission from energy e, technology d1 coupled with d2 is:Gg ,e ,d 1,d 2 iveIVE g , e , d 1, d 2

SX iveThe 21th AIM International Workshop, 2015

(S1)
13

A model of emission structure (2)Simple emission model “S‐model”
Denoting the divergence of SX ive from baseline B by MX ive , with a exception of Ac,;
(B)
MX ive  SX ive  SX ive,

ive  IVE g ,e ,d 1,d 2 \ Ac

Where

MX

iveIVE g , e , d 1, d 2 \ Ac

  mis , mid1 , msd1 , mid 2 , msd 2 , mie , mige s ,cd 1, sd 1, sd 2, sd 2, se ,d 1

Direct interventions
to emission structure
MXive

Converter matrix
DG
Emission and their
reduction
G and ΔG

S‐model(B)g ,e ,d 1,d 2 , is decomposed using a decomposing formula (see appendix);Gg ,e,d 1,d 2  Gg ,e,d 1,d 2  Gg( B,e),d 1,d 2  DG( g ,e,d 1,d 2), Ac   Ac  Ac( B )  

Driving force of sector
activity: Ac

g ,e ,d 1

Corresponding to these MX ive , the Gg ,e ,d 1,d 2 : divergence of Gg ,e ,d 1,d 2 fromG

Programs of LCS
actions

A Schematic diagram of S‐model

iveIVEg , e , d 1, d 2 \ Ac

DG( g ,e ,d 1,d 2),ive  MX ive(S2)

Where, DG( g ,e ,d 1,d 2),ive are coefficients describing a first order dependency of Gg ,e ,d 1,d 2 to

 A  A  and
c

(B)
c

MX ive , which are analytically derived from equation (S1)
We name this emission model “S-model”
14
The 21th AIM International Workshop, 2015

A model of counter measure structure (1)Simple counter measure model: “M‐model”
The model differentiates counter measures into the following three types


A measure is an intended intervention to reduce GHG emissions originally controlled by actors
outside of the system. A set of measures is written by “M”, and the element of the set is written
by “m”.



M is divided into three groups (sets), Direct Measures (DM), Consolidated Measures (CM)and Program measures (PM).

M  DM  CM  PM


Direct measure (DM) : Directly intervene emission mechanisms (e.g. improvement of energy
efficiency or service efficiency) and reduce GHG emissions.
Program measures (PM) : measures planned/programed by policies.
Consolidated measure (CM) : a combined measure convenient to connect DM and PM from aview point of intervention mechanisms.
DM and CM are consequences of one or multiple PMs.
15
The 21th AIM International Workshop, 2015

A model of counter measure structure (2)Simple counter measure model: “M‐model”
Direct measures : DM  dmg ,e,d 1,d 2 Interventions corresponding to the elements of IVE except Ac in S-model, ordm

g ,e ,d 1,d 2

  ive  IVE

g ,e ,d 1,d 2

\ Ac  .

7 types of DM are identified. They are;16
The 21th AIM International Workshop, 2015

A model of counter measure structure (3)Simple counter measure model: “M‐model”
Program measures : PM   pm , directly reflect of implementation programs. From aview point of interventions to gas emission mechanism, often duplicating, reflecting territories of
implementation agencies, confusing, and difficult to set straight
Example of Program measures : Climate Change Action Programs proposed in the HCMC study
Sectorcode
I
I

Projectcode(151027)
I-1
I-1

Land-use planning
Land-use planning

I

I-2

Land-use planning

I
I
I
II
II
II

I-2
II-1
II-1
II-1

Land-use planning
Land-use planning
Land-use planning
EnergyEnergyEnergy

II
II
II
II
II
II

II-1
II-3
II-3
II-3
II-3
II-7

EnergyEnergyEnergyEnergyEnergyEnergyII

II-7

EnergyII

II-7

EnergyX-1

Agriculture
Agriculture
Tourism

IX
IX
X

SectorContent

StatusDevelopment of Land Use Regulations and its Operation
Current
Urban Development in Model Region (in a integrated manner of Planned
the 10 important sectors)
Afforestation and greening (parks, roads, pedestrian spaces,
Plannedriparian and coastal areas)
Appropriate Site Allocation of Venous Industry Infrastructure
Potential
Appropriate Management of Large-scale Green Lands
Potential
Build wind channels (green corridors)
Potential
Energy efficiency technology applied to buildings
Current
ESCO (Energy Saving COmpany) ProjectCurrent
ESCO (Energy Saving COmpany) Project for commercial buildings Current

Effort(151027)
Internal
External
Internal

External
Internal
External
External

ESCO (Energy Saving COmpany) Project for industries
High Efficiency LightingHigh Efficiency Lighting in public lightingHigh Efficiency Lighting in commercial buildings
High Efficiency Lighting in households
High Efficiency Air Conditioners (such as Air Conditioners with
Inverter Controllers)High Efficiency Air Conditioners (such as Air Conditioners with
Inverter Controllers) in commercial buildings
High Efficiency Air Conditioners (such as Air Conditioners with
Inverter Controllers) in households

Current
Current
PlannedCurrent
Current
Current

External
Internal
Internal
Internal
Internal
Internal

Current

Internal

Current

Internal

Reduction of Agricultural Chemicals and Fertilizers Usage
Photovoltaic Power Generation at Agricultural Communities
Improvement of Water Traffic Network

Potential
Potential
Current

External
External
Internal

17
The 21th AIM International Workshop, 2015

A model of counter measure structure (4)Simple counter measure model: “M‐model”
Dividing PM (program measure) into three groups, i.e. PM1, PM2, and PM3.
PM1 is a measure directly effecting DM, PM2 to CM(consolidated measure). PM3 is a measure
which controls the effectiveness/governance of CM.
Using this disaggregation of PM, impacts to DM by PM are modeled by the following formula.

 t
MX DM   miss ,c , mid 1d 1,s , msd 1d 1,s , mid 2d 2,s , msd 2d 2,s , miee ,d 1 , migeg ,e ,d 1 

 
(M1)

 AD3  I  RX PM 3   ACPM2  RX PM 2  AD1  RX PM 1  AD0






where AD3, ACPM2, AD1 and AD0 are constant parameter matrix/vector, and x1
  0I  x   00RXPM1: Direct
effects to DM

0 
0 
 0 

0 x 

0 0
x2 0
0
0

Programs of LCS actions andprograms: RX
RXPM2: Effects
to CM

Direct interventions toemission structure MXDM

RXPM3:
Effects to theefficiency andgovernanceof CM

M‐modelEmission structure model
S‐modelA Schematic diagram of M‐modelThis counter measure structure model is called “M-model”, which connects RX (variables ofprogram measures) to MXDM (variables of direct measure).

18
The 21th AIM International Workshop, 2015

Coupling of S‐model, M‐model and related
quantification models for supporting PDCA
process
Projection of driving forces
Technology selection

Bottom up type engineeringmodel for technology selection

Top down type socio‐
economic‐energy model for
projecting driving forces

e.g. AIM/enduse, AFOLUB

e.g. ExSS, AIM/CGE
sd: Share rate oftechnology dInfluential factors to Sharerate of technology dM‐modelS‐model

Simple counter measure
structure model, whichconnects policy actions to
direct interventions onemission structure

Simple emission structure
model, which connects
interventions to emission
structure

Ac: Driving force ofsector c

Emission reduction: ΔG
Policy intervention: RX

Programs of LCS
actions andmeasures: RX

Feedback,
evaluationof actions,etc.

Emissionsand their reductions:
G, ΔG
19

The 21th AIM International Workshop, 2015

Clarification of various emission projections forevaluating the performance of Action’s andmeasures
Combinations of Environmental variables andcounter measures for calculation
Environmental variables ZX
e.g . Economic growth rate, Grid power
emission coefficient, etc

Baseline, planned and adjusted emissions
Situation
B

Explanation
Baseline
Updated baseline, orProjected situation based on planned RX
and realized ZX
Imaginary status with realized intervention
and assumed environment situation, or
projected situation based on planned RX
and realized ZX
Realized
PlannedBR
RB
R
P

Actions andmeasures

RX

Emission orState variables
Variousconcepts ofreduction
evaluated at eBaseline (B )Baseline (B )(B)

Realized (R )Planned (P )SXSX (RB)SX (P)

B: Baseline

Realized (R )(BR)

SX
SX (R)SX (PR)

SX(f,B)

Evaluatedsituation

SX(e,B)
BR: Updated baseline
RB: Realized policy+ assumed
environment
at s

Various definitions of emission reduction
Formula ofemission reduction

SX

(B)

-SX

SX

(B)

SX

(BR)

SX

-SX

(B)

(P)

(RB)

-SX

-SX

(R)

(R)

SX(s,B)

SX(s,B)
Explanation

R: Realized

SX(e,R): Planned reduction
Adjusted realized reduction with ex:
ante external conditions
Adjusted realized reduction with:realized external conditions
Realized reduction based on baseline:
emission

P: Planned

SX(e,P)

X: Updated plan
P: Planned

SX(f,X)
SX(f,P)

point of times
Project starte
Evaluationf
Project end

Various emission projections
The 21th AIM International Workshop, 201520

Case study on ex‐post evaluationof a reduction action plan
Chronicle of our Kyoto study
Year

NationKyoto City

Research activity

2004

Es tablis hment of Ordinanc e on
" M eas ures agains t global
warming in Ky oto City ", the firs t
climate change ordinance in
Japan

2006

Construction andim plem entation of the firstround of "Ac tions for
Com bating Global Warming in
Ky oto"Start of a s tudy on "Ky oto LCS
Scenario" with Ex SS, andpropos ed 40% em is s ion
reduction target by y ear 2030

Selec ted as "Environmental
Model City " by the c abinet
offic ePropos al of "A roadm ap
towards Low Carbon Kyoto"with WBS methodology and"Bac kc as ting tool"

2007
2009

2010

2011
2013

(continue)

National GHG em iss ion Rev is ion of the global warming
reduc tion target: 25%
ordinanc e, and s et cityfrom y ear 1990
mitigation targets as 25%
em iss ion reduc tion by y ear
2020, 40% reduction by year
2030, from y ear 1990
Shutdown of all nuc lear The s ec ond round of "Actions
power plants in J apan
for Com bating Global Warmingin Ky oto" was s tarted
National GHG em iss ion
reduc tion target: 3.5%
from y ear 2005

2014
2015

An image of “Environmental model city
Kyoto” presented by Kyoto city to theselection committee, Cabinet OfficeStart revie w stu dy of th eaction s and targe ts, c onside rin g
rec e nt soc io- ec onomice n vironme nt
Rev iew and performance
ev aluation of the ac tions
considering recent national,
soc ial, and ec onomic
circ ums tanc e

The 21th AIM International Workshop, 2015

A roadmap proposed to Kyoto city for“Environmental model city Kyoto” andsetting mitigation targets”

21Review of the Ordinance of “Measures against global
warming in Kyoto City” and re‐analysis of future
reduction targets•

The ordinance was established in year 2004,
and fully revised in year 2010 which includes the following quantified targets.
GHG emission reduction targets compared with FY1990:
FY2010: 10% , FY2020: 25%, FY2030: 40%, FY2050: Realization of Low Carbon Society with a drastic
cut of GHG emission•

The actions and programs in the current policy was based on our previous study (base year 2005), andafter 8 years of implementation, ex-post analysis of performance and re-analysis of future reduction
targets are required, especially because of the following drastic changes of external conditions..

••

Shutdown of nuclear power plants after
the Fukushima accident (National
government changed the target from 25%
reduction to 18% of 1990 emission
Stagnation of recent economic growth ofthe city. In the ex‐ante projection fortarget setting, we used 1.3%/y for real
growth rate assumption.

The 21th AIM International Workshop, 201522

Analysis of CO2 emissions by ex‐post analysis
Calculation of CO2 emissions by ex‐ante and ex‐post analysis in FY 2013
2013

B
Year

Reported by city
government
CO2
Ex-ante analysis inemission
2008(ktCO2)Ex-post analysis in
2015
Carbon intensity of gridelectricity (kgCO2/kWh)

1990

7,068

2005

7,051

RB

P

Realizedactions andBaseline ex-anteenvironment
situation

2010

BR

R

plannedactions andPlanned realized
Realized Baseline
environmental
situation

6,141

7,051

6,141

0.353

0.358

0.316

6,562
6,735

Formula ofCalculation of emission emission
reduction
reductions by ex‐ante and SX -SX
ex‐post analysis in FY 2013

(P)

SX

(B)

(RB)

1,373

SX

(BR)

(R)

1,542

(R)

574

-SX

(B)

-SX

-SX

1,551

The 21th AIM International Workshop, 2015

8,897
9,081

Reduction in
Realized/Planned
FY2013
reduction (%)(ktCO2)

(B)

SX

P

Planned

7,539
8,113

7,062

2030

B

4,586

7,539

2,294-5,478

0.522

0.076-0.398

Explanation

Planned reduction
Adjusted realized reduction
88.5% with ex-ante external
conditions
Adjusted realized reduction
99.4% with realized external
conditions
Realized reduction based
37.0%
on baseline emission

23

Emission reductions by ex‐ante and ex‐post analysis

Emission (ktCO2)

Adjusted baseline
emission with ex‐postenvironment (BR)9,081 ktCO2
Baseline emission(B)8,113 ktCO2
Realizedemission(R)7,539 ktCO2

Reference year
emission
7,051 ktCO2

Adjusted realized emission
with ex‐ante environment(RB) 6,735 ktCO2

Adjusted realized
reduction with ex‐post (realized)
Realized reduction external conditions
574 ktCO2
1,542 ktCO2 Adjusted realized
reduction with ex‐
ante (planned)
external conditions
1,378 ktCO2
Plannedreduction
1,551 ktCO2

Planned emission (P)6,562 ktCO2
Reference year
FY2005

Evaluation year
FY2013
The 21th AIM International Workshop, 2015

24

The 21th AIM International Workshop, 201525

Feasibility analysis of CO2 emission reduction target
Scenarios of Nuclear plants and energy demand side measures
Scenario

Three scenarios of Nuc. 60yr.,
one scenario of Nuc. 40yr., andone scenario of Nuc. CG
reach the 40% emission reduction
targetwo Nuc.
Nuc.40yr.
Nuc.60yr.
Nuc.CG

No.addi.
CG
Accel.

Content
Scenarios of Nuclear power plants
No nuclear plants operation in year 2030
No additional construction of nuclear power plants, and operating life span of existingones is 40 years. 2 plants, 13% of grid power supply in 2030, KEPCO area.
No additional construction of nuclear power plants, and operating life span of existingones is 60 years. 9 plants, 50% of grid power supply in 2030, KEPCO
Scenario of Agency for Natural Resources and Energy, Central Government (2015).
21% of grid power supply in 2030
Demand side measures
Introduction of no additional counter measure. Continuation of existing policy.
Interpolation of a scenario based on Agency for Natural Resources and Energy,
Central Government (2015).
Aggressive introduction of feasible counter measures

Projection of CO2 emission in FY2030
7,062

7,051

1,973

1,829

‐43.4%
5,478

1,196

1,696

523
693

947
2,273

‐59.5%‐67.5%

6,141
1,584

1,946

‐56.2%

Unit: ktCO2‐45.4%

1,995

1,124

1,836

5,152

5,105
495
645
972
1,863

521

4,270

4,799

4,975

493
624

521

671

438
460

1,048

780

1,701

1,560

4,000

908
1,721

659

436
440

3,092

735

513
532
568

484
492
506

849

819

630

562

1,433

2,863
2,294
427
316
451
628
473

1,007

4,633
492
613
874

1,628

1,643

1,161

1,011

3,854
435
429
711
1,364

1,447

1,754

1990

2005

現状取組
現状取組
現状取組
現状取組
2010 Noaddi. 国想定取組最⼤限取組
CGAccel. No
addi. 国想定取組最⼤限取組
CGAccel. No
addi. 国想定取組最⼤限取組
CGAccel. No
addi. 国想定取組最⼤限取組
CGAccel.

1990年

2005年

2010年

1,615

1,303

1,131

1,211

1,032

wo
Nuc.
原発ゼロ

1,053

956

Nuc.
40yr.
原発40年

2030
residential
家庭commercial
業務

industry
産業

Nuc. 60yr.
原発60年

914

Nuc.
CG
原発国発表

2030年
transport
運輸

passenger
旅客輸送
transport

freight
貨物輸送
transport

40% reduction level
40%削減ライン※ CO2 from energy consumption

30

Final remarks
1. In the past 15 years, we have developed and applied our LCD Scenario approachto many Asian nations and local regions. Now, they reached to 8 nations and 14
regions in Asia regions.
2. Related to this, in the past AIM workshops, I reported the followings:
16th WS: Coupling of AIM/CGE, AIM/enduse and ExSS for Pan‐Asian LCS studies
17th WS: Deployment and its explanation of our Asian regional LCS studies
18th WS: Introduction of Low Carbon Policy‐Action tools for regional LCS study
19th WS: Overall research procedure of the LC Development Scenario approach
20th WS: Importance of PDCA process and Ex‐ante/Ex‐post analysis
3. In this 21st WS, I focused on a PDCA process of regional LCS policy, and propose amethodology of systematic analysis of LCS actions/projects, and their couplingwith other quantification tools.
4. Not only planning stage, but also monitoring, auditing and improving the LCS
policies are crucial to make the LCS happen in the Asian region. They should bedesigned and managed with good rationale, efficiency, and transparency. As a next
generation study in LCS research, productive and valuable fields exist, here.
The 21th AIM International Workshop, 201531

Decomposition of the change of multiplies
Consider the change of following y caused by small changes of xis.

Appendixy   xi

(1)iI

Denoting the changes of xi and y by xi and y , we describe y as a quasi linear function of xi as following.

y    xi  xi    xi   DYi  xi
iI

iI

(2)

i

Expanding the above equation, we can get;



 
 
1 
y   xi   xl     x j1     x j 2  iIn 1,..,dim( I ) 1 n  1 
 J C  I \i ,n   j1J
  j 2I \ J \i   lI \i(3)

Where C  I \ i , n  is a set of any combination of n element sets extracted from I \ i . For example, in case ofI  1, 2, 3, 4,5 ,C  I \ i  1, n  3  2, 3, 4, 2, 3,5, 2, 4,5, 3, 4,5
The number of elements in C  I \ i , n  is;dim  C  I \ i , n    dim I 1 Cn  dim  I   1!
n !  dim  I   1  n !

(4)

And in case of C  I \ i , 3 , dim( I )  5 , it is 4.
By equation (3), DYi is;

DYi   xl lI \i


 
 
1 
    x j 1     x j 2  n 1,..,dim( I ) 1 n  1   j 2I \ J \i  
 J C  I \i ,n   j1JThe 21th AIM International Workshop, 2015(5)32