TECHNICAL SUMMARY

I EA
Integrated Environmental Assessment

APEIS-IEA Web sites :http://www.nies.go.jp/social/aim/apeis/

June 2005

APEIS-IEA Technical Summary
1. What is APEIS-IEA?
The Integrated Environmental Assessment (IEA) sub-project of APEIS has the following objectives:
Development of IEA tools. IEA tools comprise several models and a strategic database (SDB)
developed for the purpose of assessing innovative options for managing environmental problems.
Diffusion of IEA tools to selected Asia-Pacific countries. IEA tools are passed to researchers andpolicy makers in selected Asia-Pacific countries, such as China, India, Thailand and Korea, via
research collaborations and capacity-building workshops.
Development of quantitative innovation scenarios. IEA tools are used to develop short- and long-term
quantified scenarios in various Asia-Pacific countries and regions for the purpose of assessing
environmental innovation options.
A set of IEA tools has been developed to enable comprehensive analyses of environmental problems in the
Asia-Pacific region. The tools include (i) the SDB, (ii) the AIM/Material model, (iii) the AIM/Energy and
AIM/Air models, (iv) the AIM/Trend model, and (v) the AIM/Ecosystem, AIM/Water and AIM/Agriculture
models. Figure 1 shows the connections between these tools. They have distinct utilities and are used inparticular combinations depending on the specific environmental issues being assessed and their spatial
scope.
AIM Models
AIM/ Ecosystem/Water/

AIM/ Energy/Air
A bottom-up
technology
selection model ofenergy use andemissions atcountry and local
levelsStrategic database
Agriculture

Emission Intensity of SO2 in China

Bottom-up
AIM/End-use
modeling
Country
Based
Technology
Model
fr ameworksTemper at ur e
Precipit
Pr ecipitaattionion

Sunshine
A set of models,
including vegetation
Land useW
Watater
er r esour
esourcece
dynamics, water
Cr
C rop
op
indicattor
oroduct ivity
indicaPPrroductivityr esource, agricultur alSocio-economic
productivity and healthdemandImpact on food demand
impactAdapt
ation
Adaptation strst r ategy

AIM Family

Institution, Management,
Technology, Adaptation
Database
Scenario
Assessment

Top-down
AIM/Top-down
modelingWorld
Economic
Model ks
fr amewor

Model Basebalance andr ecycling processmodules

Consumer
Envir onment Fund
Wast es

One countr y CGE model
An Cenvir
onmentwith
O2 andmater ial
economybalance,interinteracted
face wit h
envir
onm
ental
model with material
technology m odel

Envir onment albur denEnvironment al
Burden Envir onmenta l
Industr y
Gr een P ur chase
Industr y

R ecycle

AIM/Material

Environmental
Bur denEnvir onment al Industr y(waste management , r ecycle)
Technology assessment

Technology needs

AIM/Trend

Futtur
Fu
ure
e
econ
eco noom
omic
mic
ic ttrenrendd

An econometric
type model to
China
constr uct
countr y level
Thailandenvironment
outlooks

Fut ureenenvironenviroviro nmen
nment
menttalal
al ttren
rendd

Korea
India
Japan

Str ategy
Option Base

Index BaseR esearch on new t echnologies

Key Messages:
Environmental stress is substantial in the absence of innovative strategies
Innovations in technologies, institutions, and management systems are critical toresolving conflict between environment and development
Environmental actions need mainstreaming within development decisions

Figure 1. IEA Tools: AIM Models and SDB

1

The SDB is used to store data relating to innovative options for technological, institutional, and behavioral
systems in various sectors of a particular country or region. It is also used to assess the potential of such
options for reducing emissions or mitigating other environmental problems. AIM/Material is a top-down
model of economy–environment–energy linkages. It is used for analyzing macro-economic effects ofenvironmental interventions and impacts of economy-wide policies on the environment. It can effectively
assess environmental investments and recycling. AIM/Energy is a bottom-up optimization model oftechnology–energy–environment systems. It is used for assessing emission mitigation and technology
options. AIM/Trend is an econometric model that simulates relationships between emissions and socioeconomic indicators. It is used to project future socio-economic and environmental trends. The set of
AIM/Ecosystem, AIM/Water and AIM/Agriculture models is used to assess impacts on water, agriculture,
vegetation, and health. AIM/Air, a model for simulating air pollutant distribution within a city, takes emission
forecasts from AIM/Energy as input. It is used together with AIM/Water to assess health impacts. Table 1
summarizes the characteristics and scope of IEA tools.
Table 1. Characteristics and scope of IEA tools
IEA Tool
SDB
AIM/Trend
AIM/Material
AIM/Water
AIM/Energy
AIM/Air, AIM/Water
AIM/Agriculture
AIM/Ecosystem

Characteristics
Innovative options database
Econometric projection model
Combination of national economic modeland material balance model
Process-type water use and supply model
Bottom-up-type energy-emission model
Process-type models
Process-type crop productivity model
Combination of process-type eco-service
model and national-scale economic model

Scope
Innovative technology, institutional andmanagement options
Socio-economic framework
Macro-economy, environmental
investments and material recycling
Water
EnergyHealthAgriculture
Biodiversity

The motivation behind the IEA sub-project is to assess the potential for innovative strategies to resolvepressing environmental problems and simultaneously circumvent the trade-offs between economic
development and environmental improvement. Conventional approaches assume rigid trade-offs, as shownin the left panel of Figure 2. These approaches are based on the belief that any action toward environmental
improvement has a cost to the economy, and conversely, strategies toward economic development will
necessarily affect the environment adversely. The alternative approach, however, begins by looking at
innovative strategic options that can overcome the trade-offs and result in win–win solutions for both theenvironment and the economy. It is rooted in the proposition that innovative strategies, by definition, push
the frontiers of technological, institutional or behavioral systems, and enable the crossover to a superior
economy–environment relationship. Thus, they offer improvement in both dimensions simultaneously.

2Economic/social Indicator

National Economic
Targets

Economic/social Indicator

Innovational
strategies

Environmental Quality

Environmental Quality

National Environment Goals

Figure 2. Circumventing economy–environment trade-off with innovative strategies
The IEA sub-project identifies and analyses such innovative options to manage local, regional, and global
environmental problems. Problems relating to climate change, local air pollution, waste, water, health, andother issues have been analyzed. Such problems are complex by virtue of having multiple interlinkages
among themselves as well as with the larger economic, institutional, societal, and technological systems.
They also have a temporal dimension that makes them dynamic and gives them several uncertainties. The
combinations of IEA tools have proved effective in dealing with such complexities.
2. What has APEIS-IEA achieved?
2.1 Enhancement and application of IEA tools
The SDB has been enhanced as a tool to comprehensively assess environmental innovations. It is now anadvanced interactive tool that (i) stores an extensive database of country-level inventories of existing andnew innovative countermeasures in technological, social, institutional, and management systems, and (ii)assesses the cost and environmental effectiveness of specific innovations. It provides a framework thatallows policy makers and other stakeholders to conveniently build scenarios and evaluate options.
The SDB involves the setting up of an innovational countermeasures database and a country-specificdatabase in continuous collaboration with stakeholders such as policy makers and research institutions.
Development of the SDB is an iterative process that involves identification of innovative options; simulation,assessment, and design of environmental innovation strategies; development of quantitative
countermeasure scenarios; and revision of the set of innovative options for assessment (Figure 3).

3Collect & process dataof environmental options

Design environmental
innovation strategies

Develop quantitative
scenarioof future drivers
and countermeasure

Combine data cards

Simulate effect ofenvironmental innovation
strategies

Assess environmental
innovation strategies

Figure 3. Process of development of the SDB
Figure 4 shows the SDB flow diagram developed for the transportation sector. Several options in the realmsof technology, institutions, and management have been identified. These options have been quantified andused for environmental assessment. The SDB has also been used in a complementary relationship with the
AIM/Material model to enable more integrative assessments. The development and use of the Water
Management Model, explained in Section 2.3, is such an example.
The bottom-up modeling framework of IEA has been enriched by the development of AIM/Air, which takes
emissions forecasts from the AIM/Energy model as input and simulates the extremely disaggregateddistribution of air pollutants within a city. For instance, it can estimate the impact of road traffic on air quality
through a mathematical simulation using a GIS framework that considers disaggregated factors such as
land use and distribution of traffic on roads.
Specific combinations of IEA tools have been used for integrated studies of various issues of environment,
energy, health, and sustainability in selected Asia-Pacific countries, as summarized in Table 2. The
following sections discuss some of these applications and their results.
Table 2. Issues addressed using IEA tools
Issues Considered
Integration of millennium development
goals, global environmental problems, andsustainability
MDG, water, and sanitation
Renewable energy, rural electrification,and municipal solid waste management
City air pollution management

IEA Tools
AIM/Material
AIM/Energy
AIM/Agriculture
AIM/Water
AIM/Material
SDB
AIM/Energy
AIM/Trend
SDB
AIM/Air

4

ExamplesIndia's assessment of innovative options
for meeting both millennium development
goals and climate change objectives
Asia-Pacific countries' water and sanitation
developments and national healthimprovements
Thailand’s and Korea's environmentallysound energy innovations
Beijing city air management

Eco educationbudgetEco-driving
License system

Subsidy for
Eco-Nav. Sys.

Environmental/
energy tax scenario

Subsidy for
driving monitor

Eco-driving
educationat school

Eco-driving
education
via TV program

Eco-driving
education
via Web site

Distribution of
eco-driving
leafletEco-driving
licenseEco-navigation
systemDriving
monitor[Tax/Subsidy]

Priority to highEff. vehicle
by voluntary plan

AG

Voluntary planof rail company

AB(Increase of inflow price)

Eco-drivercommendation[Eco education](Decrease of initial / O&M priceof high efficiency transportation )(Priority to high Eff. vehicle)

Priority to highEff. train
by voluntary plan

AH
A. Activation of new environmental markets

Priority to
publictransportation

Maintaining
Economical
speedsAir conditioner
Reduction of
Correct tiretemperatureillegal parking
pressureadjustment

Correct
laden weight

Air conditionerSuppression oftemperaturesuddenadjustment accelerationRev
control

Timelyshifting up

T(Decrease ofpassenger transportation)

U

PM emission
regulation

PM removal
budgetAC(Improve of efficiencyof passenger vehicle)of freight vehicle)

and GHG emission of freightvehicle)(reduction of air pollutant
and GHG emission of passenger
vehicle)AJ[Voluntary planof private company]

Road capital
informationbudgetFreight facilities
Capital information
Budget(Priority to high Eff. airplane)

Public Trns.
capital formationbudgetB. R & D of new environmental technologies
Marine container term.

NOx removal
catalyst

Joint delivery Large freightfacilities
stationStrengthen
road/bridge

Priority
bus lane

Paved Road

Bicycle Road

LRT

[Road infrastructure]
L

K(Priority to train/ship)

Subway[Public transportation]
O

M

Q(Improve of efficiency (Priority to Bus)of passenger vehicle)(Priority to large (Improve of efficiencyof freight vehicle)
freight vehicle)

N

R(Decrease ofpassenger transportation)

S(Priority to Train)P(reduction of air pollutant(reduction of air pollutant
and GHG emission of freight and GHG emission of passenger
vehicle)vehicle)J(reduction of air pollutantof passenger transportation)

Bio refinery
R&D budget

Biomass
Constraint

Bio refinery
Tech. Imp.

Biomass

Bio fuel
ImportFC Technology
Improvement

IC cardticket

AHS *1TDM

AHS *2*1

VICS
AHS *1*4AHS
ETC *3*1

HydrogenImportHydrogen(Biomass)PTPS
AHS *5*1

C(Priority to public transportation)

D(improvement of energy efficiencyof freight transportation)E(reduction of air pollutant
and GHG emission of freightvehicle)

J
I
D

AC

V

M

AD

W

AA

G

AB

P

Y

AF
O
F

N

E

Small-size
VehicleHybridVehicleNatural Gas
VehicleBio-fuel

Natural Gas
Vehicle

AE

Gas

AH

Train

Train

VehiclePassenger
Transportation

Large-size
VehicleR
C

Existing Oil
VehicleHybridVehicleTrain(Diesel)Fuel cell
VehicleShip

Passenger
Transportation

Train

Train

AI

CO2

SO2

Air
(Low EFF.)
Air

T

Train
(High eff.)

Train(High EFF.)

AJ

Air

Passenger
Transportation

S

AH

Train
(Diesel)Electricity

Q

J

Train
(High eff.)

Train(Electricity)

Bus

Bus

Natural Gas
VehicleAI

Ship

Large- size
VehicleH2

Train(Electricity)

Ship(Low EFF.)

VehicleFuel cell
VehicleNatural Gas
VehicleI
K

HybridVehicleNatural Gas
VehicleB

Fuel cell
VehicleFreight

Small-size
VehicleExisting Oil
VehicleHybridVehicleLarge-size
VehicleAG

Small- size
VehicleOil

Existing Oil
VehicleLarge-size
Vehicle(reduction of air pollutant
and GHG emission of passenger
vehicle)H

Fuel cell
VehicleFuel cell
VehicleVehiclePassenger
Transportation

H(Priority to high efficiency vehicle)

G

HybridVehicleExisting Oil
VehicleSmall- size
VehicleF(improvement of energy efficiencyof passenger transportation)X

Existing Oil
VehicleA

AG

VehicleCar sharing
system[ICT application]

B

L

Teleworking/ SOHOMOCS
AHS *1*6

Decrease ofCongestion

HydrogenConstraintA

Car sharing
preferential
tax system

C. Development of new environmental infrastructure

Hydrogen
(Gas)

Gas

ITS capital
informationbudgetIC cardpreferential
treatment system

FC
R&D budget

BiofuelConstraint

Freight
Transportation

Priority to highEff. shipby voluntary planand GHG emission of passenger
vehicle)NOx emission
regulation

S contentof oil

Bio fuel
RefineryAI(Priority to high Eff. ship)

Voluntary planof air company

AE (Improve of efficiency

AD (reduction of air pollutant AF(reduction of air pollutant[Flue gas
purification]

I

Priority to highEff. shipby voluntary planY

(Improve of efficiencyof passenger vehicle)[Freight facilities](reduction of air pollutant
of freight transportation)(Priority to high Eff. rail)

Voluntary planof ship company

X

NOx removal
budgetPM removal
air filter

Low sulfur
oil refinery

Air pollutant
regulation
by governmentV(reduction of air pollutant
and GHG emission of freightvehicle)SO2 emission
regulation

Air poluution
regulation

Energy Eff.
regulation
by government

W(Improve of efficiencyof freight vehicle)(Priority to
public transportation)

Energy Eff.
regulation[Regulation][Eco driving]

Low S oilrefinery plantbudgetSubsidy forhigh Eff. vehicle

Subsidy forhigh train/ship/air

GHG tax

AA

Priority to
walking/ bicycle

Voluntary planof auto company

Budget of subsidy
Tax benefit forhigh Eff. vehicle

Air pollutant
tax

Energy tax

Ship(Low EFF.)
Train(High EFF.)

NOx

Air
(High EFF.)

Ship

Ship

AJ
Air
(Low EFF.)
Air(High EFF.)*1 TDM: Traffic Demand Management*2 AHS: Advanced Cruise-Assist Highway System*3 ETC: Electronic Toll Collection*4 VICS: Vehicle Information and Communication System*5 PTPS: Public Transportation Priority Systems*6 MOCS: Mobile Operation Control Systems

Air

Air

DemandScenario

Confluence

Trend/Policy
Scenario

Activity(Innovation)
Activity(Conventional)

Constraint
Scenario
Flow

Figure 4. SDB flow diagram for the transportation sector

5

Activity
with stock
Influence2.2 Assessment of innovative options for meeting both millennium development goals and climatechange objectives
Millennium development goals (MDGs) comprise eight socio-economic developmental goals which all 191
United Nations member states have pledged to meet by the year 2015. United Nations Development
Programme (UNDP) links and coordinates global and national efforts to reach these goals. It helps countries
integrate the MDGs into their national development frameworks. Global and national MDGs have direct
implications for the environment and climate change, since they involve changes in the drivers of socioeconomic development and sustainability. Table 3 illustrates these relationships for India. IEA tools arebeing used to carry out analyses of such interactions to assess the impacts of MDGs on the environment
and, conversely, the potential for meeting MDGs under various scenarios.
Table 3. Illustration of linkages among MDGs, India’s national targets, and climate change
MDGs and global targets
Goal 1: Eradicate extreme poverty
and hunger
Targets: Halve, between 1990 and2015, the proportion of people withincome below $1 a day and those
who suffer from hunger.
Goal 7: Ensure environmental
sustainability
Targets: Integrate sustainable
development principles in country
policies and programs to reverse lossof environmental resources.
Target: Halve by 2015 the proportionof people without sustainable accessto safe drinking water.

India’s national plan targets
Double the per capita income by 2012.
Reduce the proportion of people withincome below $1 a day by 15% by 2012.
Contain total population growth between
2001 and 2011 to 16.2%.

Interface with climate change
Income effect would enhancechoices for cleaner fuels andadaptive capacity.
GHG emissions would be
reduced due to lower population.

Increase forest cover to 25% by 2007 and
33% by 2012 (from 23% in 2001).
Enable sustained access to potabledrinking water to all villages by 2007.
Electrify 80,000 additional villages by
2012 via decentralized sources.
Clean all major polluted rivers by 2007
and other notified stretches by 2012.

Enhanced sink capacity; reduced
GHG and local emissions;
reduced fossil fuel imports;
reduced pressure on land,
resources, and ecosystems.
Higher adaptive capacity fromenhanced supply of water,
health, and education in rural
areas.

Figure 5 illustrates such an analysis at global and country (India) scales. Global emissions scenarios
developed for the purpose of climate change analysis are used as references in analyzing the potential for
meeting global MDGs. For instance, the IPCC’s A2 scenario will not leave reasonable scope for meeting the
MDG of the number of people suffering from hunger in 2012. This target can be met under the B2 scenario,
but only with additional economic support for hunger alleviation programs. Different emissions scenarios,translated for India, signify different trajectories for water consumption and other parameters critical for MDG.
Since different emissions scenarios correspond to different socio-economic developmental pathways, this
implies that the future development path of a country determines the scope and effort required for meeting
MDGs and environmental and climate targets. Thus, environmental improvement actions need to be
integrated within the development decisions of various countries. Elements of innovative strategies, such as
financial budgeting or investment plans, must be designed for multiple dividends to development and theenvironment.

6

Indian Scenar ios

Global Scenar ios
1800

(A1T)

A2: cultura l plura lism

A1: high growth(A1F I)

Globalism

Regionalism

B1: recycle-based

B2: regiona l coexistence

Envir onment
Population
Economic growthTechnology

IA2

1600

EconomyCarbon Emissions (MT)

A1B

1400

IB 2

1200

IA1

1000
IA1T
800

IB1

600
400

Agriculture (land use)
Energy200
2000

Driving F orces

550 ppmv
2020

2040

2060

2080

2100

Number of people suffering from hunger

Number of people(Global Million)

1200
1000
800
600
400
Target200
01997 2000 2003 2006 2009 2012 2015

B2

A2

B2+Economic Support

Figure 5. Linking global scenarios, Indian scenarios, and MDGs
2.3 Water management model linking the SDB and AIM/Material
The water management model has been developed within a framework that externally links the SDB and the
AIM/Material model (Figure 6). Salient features of this framework are as follows:
Water demand is estimated in the SDB on the basis of water supply and sanitation conditions
Services with a safe piped water supply are distinguished from those without a safe water supply
Services with sanitation are distinguished from those without sanitation
Unaccounted for water and efficiency of water management are distinguished from actual water use
by households and commercial users served by piped water
A decision to install facilities for improved water supply and sanitation is linked to investment bygovernment and households in the AIM/Material model
Dynamics of inter-temporal decisions, such as investments, are considered
Urban and rural areas are treated separately
Potential health impacts and impacts on costs of strategies to increase water supply, improve
sanitation, reduce unaccounted for water, and improve water management efficiency can be
estimated using the SDB

7

AIM/Material

Other investment

Household
Government

Facility
construction

Investment
T
Decrease?

Water
availability

Increase?

T+1

Borehole

Water
availability

Publicstandpipe

Simple pit
latrineSepticsystemHouseholdconnection

SDB
Labor loss

Publicsewer

Supply services

Supply services

Water demand

Water demand

Sanitation services

Sanitation services

Without
safe waterWithout
sanitation

Labor loss

Watersavings

Figure 6. Water management model linking the SDB and AIM/Material
The water management model has been applied to India, China, and Thailand. Figures 7 and 8 show someof the results. For all three countries, the greatest decline in the relative risk of diarrhea mortality over the
2000–2025 period will come when all households are supplied with safe piped water and have a centralized
sewer connection (Case 2). However, the increase in the annual cost of supplying water and sanitation is
the highest in this case. For Case 3, where water is supplied to new households by cheap options such aswells, ponds, or boreholes, and cheap sanitation options are provided, such as ventilated improved pits
(VIP) or simple pit latrines, annual costs will be lower but the risk of diarrhea mortality will decline less thanin Case 1, where there is no change in the technology mix of water supply and sanitation systems. Thailand
is not expected to witness any decline in diarrhea mortality risk in Case 3. This is because its population is
not likely to increase significantly from 2000 to 2025, and almost all of its existing households have septictank systems for treating waste water that have a similar impact on diarrhea mortality as cheaper sanitation
options (Figure 7).

4

10
2

5

m ort al it yy ea r)Rel at iv e ri s k of di arrh eal

2
0

2025

2015

2000

2025

2015

2000

2025

2015

2000

A nnual c os t (bi l li on $ per

4

India

China

ThailandPublic standpoint
Septic tank

6

15

4

10
2

5
0

Case 3

Well/Pond/Borehole
VIP/Simple pit latrine

0
2025
2015
2000

8

0

Case 2

0

20

2025
2015
2000

Household connection
Sewer connection
6

20
10

0

8
25

2025
2015
2000

Thailand

10

2

5
2025
2015
2000

2025
2015
2000

China

India

4

10

2025
2015
2000

2025
2015
2000

2025
2015
2000

Case 1

6

15

2025
2015
2000

0

20

10

30

Relative impact of diarrheal
mortality

15

8

25

35
Annual cost (billion $ per year)

6

20

10

30

Relative risk of diarrheal
mortality

8

25

Annual cost (billion $ per year)

30

0

30

35

10
Relative risk of diarrheal
mortality

Annual cost (billion $ per year)

35

India

China

ThailandRainwater
Diarreha

Figure 7. Annual cost of water supply and health risk in 2000, 2015, and 2025 in India, China, and Thailand
under three scenarios(Case 1: No change in technology mix. Case 2: Piped water and sewer connection to all households in 2025. Case 3: Provision ofcheap water/sanitation technologies to new households from 2000 onwards.)

8

For India, the annual cost of providing a centralized connection of piped water to households is expected to
decline more by improvement to the efficiency of water supply management than by reduction of
unaccounted for water. However, it is the other way round for Thailand. This is because the existing
manpower cost of supplying 1 m3 of piped water and the existing proportion of unaccounted for water areboth very high in India, whereas in Thailand, the former is very low and the latter is high. For the same
reason, the reduction in annual volume of piped water is expected to be higher in India than in Thailand in
scenarios where unaccounted for water is reduced. China is expected to witness a very low decline in bothannual cost of connected systems and annual volume of piped water supply because of its existing low unit
cost of piped water supply and low proportion of unaccounted for water (Figure 8).

15
10
5

Case 2
Case 2.1
Case 2.2

150
100
50

0
Year

Unit cost for HC ($/m3)

200

Case 2
Case 2.1
Case 2.2

HC water supply(million m3/yr)

Annual cost for HC(billion$/yr)

20

02000 2005 2010 2015 2020 2025

Year

2000 2005 2010 2015 2020 2025

0.10
0.09
0.08

Case 2
Case 2.1
Case 2.2

0.07
0.06

Unaccountd for water (%)

India

0.05
Year
2000 2005 2010 2015 2020 2025 Year

60
50
40
30
20

Case 2
Case 2.1
Case 2.2

1002000 2005 2010 2015 2020 2025

10
Case 2
Case 2.1
Case 2.2

5

250
200
150

Case 2
Case 2.1
Case 2.2

100
50

0

0

2000 2005 2010 2015 2020 2025 Year

Year

Unit cost for HC ($/m3)

300

15

HC water supply(million m3/yr)

Annual cost for HC(billion$/yr)

20

2000 2005 2010 2015 2020 2025

0.10
0.09
0.08

Case 2
Case 2.1
Case 2.2

0.07
0.06

Unaccountd for water (%)

China

0.05
Year
2000 2005 2010 2015 2020 2025 Year

60
Case 2
Case 2.1
Case 2.2

50
40
30
20
10

0
2000 2005 2010 2015 2020 2025

0.9

25
Case 2
Case 2.1
Case 2.2

0.6
0.3
0.0

Year

2000 2005 2010 2015 2020 2025

Annual costfor HCYear

20

Unit cost for HC ($/m3)

1.2

HC water supply(million m3/yr)

Annual cost for HC(billion$/yr)

1.5

Case 2
Case 2.1
Case 2.2

15
10
5

0.10
0.09
0.08

Case 2
Case 2.1
Case 2.2

0.07
0.06

Unaccountd for water (%)

Thailand00.05
2000 2005 2010 2015 2020 2025 Year
2000 2005 2010 2015 2020 2025 Year

Annual HC
water

Unit cost for
HC

60
Case 2
Case 2.1
Case 2.2

50
40
30
20
10

0
2000 2005 2010 2015 2020 2025

Unaccounted
for w ater

Figure 8. Comparison of three water management scenarios in India, China, and Thailand(Case 2: Same as Case 2 in Fig. 7. Case 2.1: Improved water supply efficiency over Case 2 as measured by an increase inmanpower productivity of 5% per year. Case 2.2: Reduction in unaccounted for water of 3% per year over Case 2 due to improved
management, up to a minimum limit of 10% of total water supply. HC: Household connection of centralized piped water and sewer
system.)

2.4 Use of the SDB to assess innovative options in Thailand and Korea
The SDB has been used extensively to assess multiple innovation options in the transportation, residential,
and commercial sectors of Thailand and Korea. Figure 9 illustrates the concepts of innovations consideredin various sectors, and the interlinkages among them, for urban Thailand. The SDB was used to analyze thebiofuel program in Thailand, covering bio-diesel and gasohol options (Figure 10). It was found that bio-diesel
is competitive in road transport but not in water transport in Thailand. Gasohol is not competitive at current
production costs. At existing costs, the biofuel program in Thailand has the potential for reducing CO2

9emissions by 1.6 Mt and SO2 by 1.9 kt in 2011. With additional policy and institutional support, its impact
could be significant.

3

4, 5
4A

Biofuel Plant

8A

8
8

13

1A

5A
1, 4

MSW

Biogas
4, 5

6, 7

9

2, 4

Biomass
Power Plant 11

2A

RETs Knowledge &Database Center

3A

9A

10

6A, 7A
12

Grid
Other
Renewable E.
Applications
Thermal Energy Flow
Electricity Flow

14

Existing Innovations:

Future Innovations:

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.

1A. Solar Street Lighting Project
2A. Solar thermal for w ater
purification
3A. Solar PV in commercial andmanufacturing sector
4A. Regional Biogas Pipeline &Netw ork
5A. Fuel cell & Hybrid Technology
6A. Renewable Portfolio Standard
7A. IT Based technology to control
demand/supply
8A. Large scale Energy Plantation
9A. Renewable Energy Fund

Solar Home System Project
Solar PV Power System for Rural Schools
Solar Power plant
Solar Water Heater
Solar Dryer
Green Fuel & Cook stoves
Rice Husk for Mushroom Drying Kiln
Biogas in Livestock Farms & fertilizer
Biogas from Landfill MSW
Biogas in Tapioca Starch/Palm oil Plant/Slaughter houses
Rice Husk & Paraw ood Power Plant
Hybrid Power System for National Parks
Biodiesel and Gasohol Program
Renewable Map, Database and Museum & TEENET

Re du ct ion in em ission s in tran sport
sect or com pared t o case w ith n o bio
fu els con sidered (% )Figure 9. Existing and future innovations assessed in SDB for Thailand

2.5
2

1.5
1

0.5
0

-0.5

2006

2010

2020

2030

-1

CO2 Em sision s

SO2 Em sision s

NOx Emsision s

Figure 10. Assessment of the Thai biofuel program with the SDB
Several innovations have been analyzed using the SDB for the residential and transport sectors of Korea.
Figure 11 shows the SDB card and result of a scenario where green roofs are installed on 30% of Koreanhouses. Green roof is a light weight roof garden system involving layers of volcanic stone mulching, artificial

10lighting soil, filtration non-woven fabric, drain insulating bricks, PVC water proof sheet, slope control EPS
panel and insulating board. The green roof technology saves about 9.8% of the energy requirement of ahouse. This scenario is expected to result in an approximately 2.5% reduction in energy consumption in
Korea.

Flat roof (Application of insulating method of
construction)
Volcanic stone
Ar tificial lighting
mulching(Including or ganic
soil
Filtr
-woven fabr icbody)ation non
Dr ain insulatingSepar
br ick ating
PVC/PO
water proof
boar
Sloped control EPS
sheet
Insulating
panel
Pr
eventing
moistur e P .E
boar
d
Roof
Film

25

10^6G

20

15

10

50

0
200

201
heatincoolin202
reductio

Figure 11. Assessment of a green roof scenario in Korea with the SDB

2.5 Application of AIM/Air to China
The AIM/Air model has been used to simulate air pollution from various sources in Beijing. Figure 12 shows
the distribution of PM concentration estimated from the distribution of traffic volume in a winter night.
Significant seasonal variation was observed in the concentrations of SO2 and NO x, with very highconcentrations occurring in winter. On 63 days in a year, the SO 2 concentration in Beijing was above the 24hour standard of 0.15 mg/m3 for residential areas, and on 35 days it was above the standard of 0.25 mg/m3
for industrial areas. The NO x concentration crossed the residential area standard of 0.10 mg/m3 on 64 days,
and the industrial area standard of 0.15 mg/m3 on 11 days. Although the commercial and power sectors
were the main contributors of SO2, the power sector alone was primarily responsible for most of the NOx
emissions (Figure 13).

11

D aily averaged S O 2 concentration

1.2

1.0
PublicC om m erce
Transport
O thers
N onferrous
Iron & S teelC em ent
Pow er

0.8

0.6

0.4

0.2

D aily averaged N O x concentration (m g/m 3)

Figure 12. Simulation of PM concentration caused by traffic emission in Beijing in a winter night

0.30

0.25

PublicOthers0.15

Nonferrous
Iron & Steel
Cement

0.10

Power
0.05

0.00

0.0

1/1

1/1

3/1

5/1

7/1

9/1

3/1

5/1

7/1

9/1

11/1

11/1
100%

80%

PublicCommerce

60%

Transport
Others40%

Nonferrous
Iron & Steel
Cement20%

Power

C ontribution to N ox concentration

100%

C ontribution to SO 2 concentration

Commerce
Transport

0.20

80%
PublicCommerce
60%

Transport
OthersNonferrous
Iron & Steel40%

Cement
Power
20%

0%

0%

Jan. Feb. M ar. A pl. M ay Jun. Jul. A ug. S ep. O ct. Nov. D ec.

Jan. Feb. M ar. A pl. M ay Jun. Jul. A ug. S ep. O ct. N ov. D ec.

Figure 13. Seasonal variations in SO2 and NOx concentrations in Beijing

122.6 Capacity-building initiatives by the IEA sub-project in selected Asian countries
A capacity-building workshop was held in November 2004 to train researchers from China, India, andThailand in the use of the AIM/Material model for environmental policy analysis at the country level. After theworkshop, a team from each country carried out analysis using the model and presented its results. Figure
14 shows a result from the application of the AIM/Material model to China. Four scenarios to assess theimpacts of SO 2 policies were developed — business as usual with no special SO2 policy (BAU), investment
and sulfur tax imposition (INV), investment and emission cap imposition (INV+CAP), and enhanced
investment and emission cap imposition (EINV+CAP). For the majority of economic sectors, the minimum
decline in output is expected to occur under the last scenario involving enhanced investment and a cap on
SO 2 emissions. SO2 emissions are expected to decline more under the last two scenarios (i.e., the ones
involving investment together with an emission cap) than under the scenario with investment and sulfur tax.
This shows that an innovative policy involving a combination of regulations imposing a limit on emissions
together with enhanced supply-side investments in various sectors can achieve the dual objectives of
mitigating emissions and economic costs.

Figure 14. Assessment of SO2 policies in China using AIM/Material
3. Application of APEIS-IEA activities
3.1 How can the APEIS-IEA products be used for policy formulation / implementation work?
APEIS-IEA tools have been directly used for providing input to policy analysis and implementation in
selected Asia-Pacific countries. For instance, the use of IEA tools to analyze Beijing’s air pollution
contributed to the National Report on Climate Change in China. Local air pollution analyses carried out by
IEA collaborating teams in India and Thailand have also been providing inputs to their national policy forums.
Another key area in which IEA tools have contributed to policy is the assessment of clean development
mechanisms (CDM). CDM is one of the flexibility mechanisms of Kyoto Protocol that allows emission trading
reduction projects creating sustainable development in developing countries to generate certified emission
reductions for use by the investors. Analysis using IEA tools by collaborating teams in China, India, Thailand,
and Korea has provided robust estimates of marginal costs of mitigation in various sectors in thosecountries. These estimates have been useful in deciding benchmarks for CDM projects.

133.2 What has APEIS contributed to the scientific community?
Each of the IEA tools is a new model developed to assess certain environmental issues and answer a
specific set of policy questions. These tools have been designed to be used both independently andcomplementarily. Various combinations of these tools provide a comprehensive framework to assess
multiple dimensions of environmental problems. Such dimensions could include technologies, institutions,policy instruments, regional scope, time horizon, GHG emissions and other environmental pollutants. For
instance, the SDB and AIM/Material can be used together to design business-as-usual and intervention
scenarios and assess their impacts on emissions of various gases, costs, macro-economic indicators suchas changes in GDP and capital formation, health and other developmental indicators. The AIM/Energy and
AIM/Material models can be used together to assess impacts of policy measures such as emission
constraints, carbon taxes, or permit trading, on technology mix, fuel mix, and macro-economic indicators.
Such analyses can be undertaken over short or long runs and at the level of city, country, or region.
The IEA models and database are especially suitable for application to developing countries where, on the
one hand, collecting extensive and reliable data is difficult but, on the other hand, innovative options are
expected to play an extremely critical role, since those countries are witnessing rapid socio-economictransitions. IEA tools are designed to facilitate estimation, storage, and use of relevant data forenvironmental assessment in such contexts. This characteristic is not adequately present in other existingmodels. This is one of the reasons why IEA tools are already being extensively used by researchers inmajor developing countries of the Asia-Pacific region, such as China, India, and Thailand, and are providing
inputs to their policy discussions. IEA tools have helped in the scenario development processes in thesecountries.
3.3 Cooperation with international organizations
The APEIS-IEA sub-project has been actively contributing to several international projects, such as
CAPaBLE, UNEP/SEFII, and UNEP/GEO3 & GEO4. APEIS-IEA tools are providing useful analyses in the
CAPaBLE project for assessing mitigation options and sustainable development opportunities in developing
countries. In the UNEP/SEFII Great Mekong project, IEA tools such as the SDB/Water Management Model
and AIM/Air are proving useful for contributing to the database and for analysis of countermeasures forassessing regional environmental problems of water, air, waste, and forests. IEA tools have also contributed
to the construction of future scenarios for emissions of CO2, SO2, and NOx and generation of municipal solid
waste in the UNEP/GEO3 project. Figure 15 shows the APEIS session in progress at the CAPaBLE
Workshop at Asian Institute of Technology, Bangkok, in 2004, and the participants of the UNEP/SEFIIWorkshop held in Hanoi in 2005.

14

Figure 15. The APEIS session at the CAPaBLE Workshop (top), and participants at the UNEP/SEFIIWorkshop (bottom)
APEIS-IEA has been continuously collaborating with a network of organizations in the Asia-Pacific region inorder to develop tools to suit the diverse social, institutional, and economic contexts of the region, and tocarry out assessments useful to its policy making processes. The list of participating organizations anddetails on the Asia-Pacific Integrated Model can be accessed at http://www-iam.nies.go.jp/aim/.
Plan of APEIS-IEA Phase II
In APEIS phase II, the IEA sub-project aims to continue its work of enhancing tools and their application toenvironmental assessment in the Asia-Pacific region. New work on tool enhancement and application is
expected to include:

15

(i)
(ii)
(iii)
(iv)
(v)
(vi)
(vii)

Building a comprehensive inventory of innovative institutional and management options in the
SDB.
Development of country-specific innovation scenarios supported by the SDB.
Extension of AIM/Material and other AIM tools to assess land use, material stock balance, andoptions to achieve national environmental and developmental goals.
Enhancement of feedback linkages between the SDB and AIM/Material for more integrative
assessment of environmental and national development goals.
Development of feedback between the SDB and other IEA models in order to make themodels more interactive and relevant for policy making processes in Asia-Pacific countries.
Extensive capacity building though use of IEA tools and making them accessible toresearchers and policy makers in the Asia-Pacific countries.
Continuation of contribution to international activities such as UNEP/GEO4, IPCC, andUNEP/SEFII.

Figure 16 shows the proposed interlinkages among the SDB, AIM/Material, and other IEA models to be
developed in APEIS phase II. The SDB engine will be developed to interface with other IEA models. For
instance, service demand drivers for SDB will be provided directly by AIM/Material. AIM/Material will, in turn,take relevant data from other IEA tools, such as efficiency, emissions, and cost parameters from the SDB
and the rate of technological improvement from AIM/Energy. The SDB engine will supply basic technology
characteristics and estimates of technology shares to AIM/Energy for calculation of optimal investment
trajectories in various sectors. Thus, the new interface enhancements will enable all IEA tools to be used
together for a more integrative environmental assessment and scenario development for a country.

Quantitative & formatted
data of innovation options:Technologies, Institutions
and Management

Driving force
Service demand

AIM/
Mater ial

SDB
engineParameters ofinnovative options

Raw data of environmental
innovation options specificto a country

Scenarios
for eachcountr y

Other AIMmodelsAPEIS/SDB
Figure 16. Proposed interlinkages between the SDB, AIM/Material model, and other IEA tools

16