TECHNICAL SUMMARY

I EA
Integrated Environmental Assessment

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

June 2004

APEIS-IEA Technical Summary

1.

What is APEIS-IEA?

The Integrated Environmental Assessment (IEA) sub-project of APEIS aims to address key environmental policy issues
at various levels of application using a set of integrated assessment models and a strategic database. These models anddatabase are part of the Asia–Pacific Integrated Model (AIM) family. Several AIM models have been developed to analyze
policy, from global to local geographical levels, and examine how they affect concerns ranging from stabilization ofgreenhouse gas (GHG) emissions to air pollution, wastes, human health, land-use change, and water resource depletion.
Triggered by opportunities of globalization and domestic economic reforms, a number of developing economies are
growing at a rapid pace while goals of a clean environment and sustainability stand threatened at both local and global
scales. Against this backdrop, policymakers are faced with multiple and complex issues often with mutually conflicting
objectives. The vast range of policy issues that AIM models and databases can jointly address, together with their userfriendly interfaces, make IEA potentially very useful to policymakers in various countries and international bodies. The
impacts of various policy intervention options—such as market-based policies (for example, emissions tax), regulatory
constraints, innovative technologies and systems, trade regimes, and bilateral technology transfer agreements—can beevaluated at the levels of city, country, region, and world.
The models and database include (i) the Strategic Database (SDB), used for storing data relating to socioeconomic
scenarios and innovation options, assessment of innovative technologies, and provision of data to other models; (ii) the
AIM/Energy model, used for local- and country-level assessment of technologies and emissions mitigation options; (iii) the
AIM/Material model, used for country-level assessment of environmental investments and recycling; (iv) the AIM/Trend
model, used for regional- and global-scale projections of future socioeconomic and environmental trends; (v) the set of
AIM/Ecosystem, AIM/Water and AIM/Agriculture models, used for assessment of impacts on water, agriculture, vegetation,and health.
All these models and database together cover both bottom-up and top-down features. AIM/Energy and SDB have bottomup frameworks, that is, they model detailed flows of energy through technology systems. AIM/Material and AIM/Trend are
top-down models. They model the relationships among aggregate economy-wide indicators. AIM/Ecosystem, AIM/Water
and AIM/Agriculture too have top-down features. A top-down representation of economy and its linkage with emissions, as
shown in Box1, is an integral part of AIM/Ecosystem. AIM/Material model includes similar top-down economy-environment
framework.
The IEA sub-project exchanges data and scenarios with the sub-projects “Integrated Environmental Monitoring” (IEM) and“Research on Innovative and Strategic Policy Options” (RISPO).

2.

What are the Expected Products, Scientific Contributions, and Current Progress?

The models and database developed by IEA are being used for addressing various environmental issues in selected
countries through collaboration with modeling and policy experts in each country (Table 1). Teams in each country havecollected current year data, projected future years’ data of driving forces, designed socioeconomic scenarios, and identified
abatement options for each country, in consultation with various domestic experts and policymakers. IEA model results and1analyses for each country have been used by the respective teams to contribute to domestic policymaking through various
projects and forums. Researchers in Japan have collected and estimated global data, too.

2.1 Technical Framework
The framework includes models—AIM/Energy, AIM/Material, Aim/Ecosystem, AIM/Water, AIM/Agriculture and AIM/Trend—
and the Strategic Database (SDB). Relevant results of one model are transferred as input to another. Each model isdesigned for a specific purpose, i.e. to address a specific set of policy issues. For instance, on the one hand, AIM/Energy
models significant technological and energy flow details in order to answer policy questions relating to emissions by sector,
technology, and fuel type, and to show the costs of intervention options for mitigating those emissions. The top-down
economy level representation in AIM/Ecosystem, on the other hand, dynamically models aggregate, economy-levelinteractions among prices, value outputs of sectors, and trade in a general equilibrium framework, in order to answer policyquestions relating to two-way impacts of economy-wide emissions and macroeconomic policies concerning trade,
production, and technological progress.
Input data and results of various models are also stored in the SDB. The SDB is designed to assess the environmental
impact of innovative technologies and systems, and to assess the suitability of such innovations in a local context.

2.2 Expected Products
2.2.1 AIM/Energy
AIM/Energy is a bottom-up optimization model of technology selection that simulates flows of energy and materials throughcomplex technological systems, and the resultant emissions, at local or country levels. It selects technologies that minimize
system cost. It is useful for analyzing several policy concerns at local and country levels, such as reduction potentials of
specific emission removal technologies; and impacts of specific emissions taxes, emissions constraints, or end-use level
improvement measures on emission levels, marginal costs, technology mix, and fuel mix. Emissions covered by
AIM/Energy include CO2, CH4, N2O, SO2, and NOx, and Suspended Particulate Matter (SPM). Its strength is the ability tomodel technology–energy systems in detail (Fig. 2).
AIM/Energy simulations for China indicate that the economic potential for CO2 emission mitigation is the highest in theindustrial sector, where a reduction of over 200 Mt C can be achieved in 2010 at less than US$50/t C. A significant portionof this reduction potential lies in the power, steel, and cement industries. Of this, a reduction of over 60 Mt C can beachieved by no-regret options alone (Fig. 3). The majority of CO2 emissions in China arise from particular industrial–
residential areas (Fig. 4a). Simulations show that CO2 mitigation measures in the power and residential sectors will inducea shift away from coal, thus resulting in significant co-benefits of both CO2 and SO2 reduction (Fig. 4b).
AIM/Energy simulation results for India show that the scenario of 550 ppmv CO2 stabilization will be characterized by asignificant switch from coal- to gas-based power generation, especially in the coastal areas (Fig. 5). This switch arises
primarily because of the relatively low delivery cost of domestically produced and imported natural gas in coastal areas,
and the declining capital cost of gas turbines, making it the preferred option to meet GHG mitigation targets.

22.2.2 AIM/Trend
AIM/Trend is an econometric model used for projecting environmental trends in different countries. Compared to theprevious year, AIM/Trend has been expanded from Asia-Pacific region to the world. Indices of economy, energy, andenvironment calculated by AIM/Trend are used for other AIM models. Non-CO2 gas projections have been revised.

2.2.3 AIM/Material
AIM/Material is an environment–economy interaction model with special representations of economy-wide materialbalances and recycling processes. It is useful for analyzing policies relating to recycling industries and their impacts on
economy-wide emissions and macroeconomic performance.
Effects of economy-wide CO2 emission constraints (increase in emissions restricted to 2% per annum) and policies
promoting recycled biomass goods and technology innovations in India were analyzed with AIM/Material. Loss of GDP in
2030 under CO2 emissions constraint is about 2% of the reference scenario. Recycling and technology innovation
scenarios are expected to mitigate this loss by up to about half a percentage point in 2030 (Fig. 6).

2.2.4 AIM/Ecosystem, AIM/Water and AIM/Agriculture
These are a set of models focusing on different aspects of the interaction between natural and social environments. These
include a vegetation dynamics, water resources, agriculture productivity, and health impact. These are useful for analyzing
the impacts of long-term socioeconomic scenarios on vegetation, water resource depletion, agricultural productivity, andthe health of people, in various regions of the globe.
Four long-term scenarios of natural and social environment were analyzed using AIM/Ecosystem. The simulations indicatethat forest area will decrease at the beginning of the 21st century in all regions under all scenarios. While regional
scenarios (AM and OS), characterized by pressure from general food demand, show this decline to continue until 2050 for
Asia, global scenarios (GO and TG) show recovery of forest area in later periods due to pressures of globalization (Fig. 7).
AIM/Water results indicate that water demand per unit area will increase throughout the 21st century in China and Eastern
Europe owing to high economic growth under the GO scenario. Under the OS scenario, high population growth in Africa,
the Middle East, and South Asia will cause an increase in water demand per unit area (Fig. 8).
As described earlier, AIM/Ecosystem and AIM/Material contain explicit linkage with economy which is modeled in a topdown framework. This framework has a long-term, general equilibrium type global representation with recursive dynamics.
It has representations of 18 regions of the world, 13 economic sectors, and multiple gases. It models the interactions
among the economy’s production sectors, government, and households, with an implicit representation of prices, trading,and emissions (Box 1). The 13 economic sectors represented in the model include natural gas, electricity, crude oil, refined
oil products, coal transformation, agriculture, livestock, forestry, fishing, transport, services, energy-intensive industries, andother industries. The model represents allocation of emission rights among users in various sectors. It is useful for
analyzing global-level policy interventions like free trade agreements among different regions, bilateral technology transfer
agreements, and economic and trade impacts of global GHG stabilization scenarios.

3The scenario of a free trade agreement among Asian countries, analyzed using top-down economy framework without the
non-CO2 GHG module, shows a significant change in both GDP and emissions in 2010 relative to the reference scenario.
Free trade will increase GDP as well as SO2 emissions in Korea and seven ASEAN countries owing to the rise inproduction from energy-intensive industries. However, free trade may induce a decline in SO2 emissions in other countries,
due to either the growth of industries supplying environmental processes/equipment (Japan) or a drop in production fromenergy-intensive industries (India) (Fig. 9).

2.2.5 Strategic Database
The APEIS Strategic Database (SDB) is designed to analyze strategies for innovative technologies and social systems
required for a shift toward environmentally sound industries and lifestyles. Various innovative technologies in the fields ofnanotechnology, biotechnology, and information technology, and innovative social systems, such as environmental fundschemes and awareness campaigns, can be analyzed for their impacts on reducing soil/water contamination soil/water
purification, waste reduction, and climate change.
In the SDB, descriptive information on innovative strategies and socioeconomic scenarios is quantified, and the impacts of
the innovations under different scenarios are analyzed. These strategies include innovative technological, management,
and institutional systems that have the potential to significantly improve an environmental effect. The potential acceptanceand implantation of such systems could be specific to the context of a country or region. Firstly, the user compiles a list ofinnovative environmental strategies based on various inputs such as interviews with experts, literature surveys, andexisting data from bottom-up models like AIM/Energy. This information is compiled as ‘narrative description cards’, each ofwhich presents the social, economic, technical, and environmental characteristics of a specific innovation in both
descriptive and quantitative terms. The user also draws up storylines describing future socioeconomic scenarios of interest
for a given country or region. These descriptive storylines are subsequently converted into quantified socioeconomic
scenarios. Finally, through a user-friendly interface, the quantified information about scenarios and innovative strategies iscombined to estimate the impacts of specific innovative systems under specific socioeconomic scenarios (Box 2). Several
innovative technologies and systems have been identified in the process of building the innovations database for the SDB(Box 3). Analysis of innovations using the SDB is in progress for Japan, China, and India.

2.3 Contributions to Scientific and Technological Progress
The set of AIM models and the strategic database shown in Figure 1—adjusted for mutual consistency and applied
together to address a wide range of environmental policy concerns—is at the cutting edge of development and applicationof Integrated Assessment Modeling. Each model itself has certain features that lend it an advantage over other similar
models available in the literature. The set of AIM models for IEA utilizes cutting-edge modeling methods in optimization,
economic equilibrium, and ecosystem simulation, and applies them innovatively for environmental policy analysis.

2.4 Current Progress on Major Tool Development
IEA has completed advanced versions of AIM/Energy, AIM/Material and AIM/Water, and a preliminary version of theintegrated AIM/Ecosystem models. It has also completed an advanced version of the Strategic Database with indicators

4

focusing on environmental efficiency. It has carried out projections of environmental trends and assessments of innovation
options for selected countries.

2.5 Messages from IEA
Integrated analysis with the IEA models and strategic database suggests that (i) the potentials of technological innovations
for the environment are very large but differ among countries, pointing to immense opportunities for regional collaboration;(ii) technological innovations are most effective if integrated with social innovations; (iii) policy options effective for the
global environment can reduce local environmental burdens as well; (iv) investments in the recycling industry and intechnological innovations can partly mitigate the loss of GDP due to environmental constraints; (v) globalization would
introduce innovations mainly in emission reduction while adversely affecting the incentives to sustain ecosystems; and (vi)free trade agreements would have varied economic and environmental impacts on different Asian countries.

3. How Can the APEIS-IEA Products be Applied for Policy Formulation/Implementation Work?
IEA products have a wide range of applications to policy-making, as highlighted in Table 1. They can address a variety ofenvironmental policy concerns at the levels of:(i)city, country, region, and world(ii)

sector, economy, and ecosystem(iii)

short term (5–10 years), intermediate term (10–50 years), and long term (50–200 years)(iv)

technology innovations, management and institutional innovations, command and control interventions, andmarket-based interventions

Taken together, the IEA models and database can help policymakers at various levels of decision making to address awide range of environmental and allied issues in an integrative manner.
Each IEA product has a user-friendly interface especially designed to meet the needs of policymakers. For instance,
assumptions for scenarios can be specified on the basis of policymakers’ expert judgments. A user can run the models
without needing to access the models’ technical formulations, and can analyze the results using tables, graphs, and maps.
Analysis features of the models permit the user to view results on a wide range of policy criteria that are of relevance tovarious stakeholders typically involved in real-life contexts of environmental policy. The user can thus weigh various tradeoffs involved in a specific context, understand the underlying inter-linkages, and arrive at informed decisions by interactingwith the models.
For instance, AIM/Trend and top-down economy component of AIM/Ecosystem will enable policymakers to easily
comprehend complex dynamics of economy-wide environmental policies and the inter-relationships among multiple criticalelements, such as outputs of different economic sectors, prices of commodities, technological progress, trade flows,
macroeconomic indicators, and environmental emissions. AIM/Material will enhance the understanding of linkages between
those elements and recycling sectors. AIM/Energy will help in grasping technological details of energy extraction, energy

5conversion, supply systems and enduse systems and the flows of energy and materials through them, possible pollution
reduction technologies and their implications for emissions of various gases (including GHGs), and marginal abatement
costs in the process of satisfying specific enduse services in various sectors of a city, province, or country. AIM/Ecosystemenables integrative understanding of interdependent phenomena such as climate change, land-use change, water
availability, vegetation, crop productivity, and health impacts. The SDB guides the user through the definition andquantification of innovative systems and socioeconomic scenarios, and provides an evaluation of each innovation’s impact
on the environment, thus facilitating the awareness of underlying cause-and-effect relationships. Hence, regular interaction
and familiarity with the IEA models will in itself enhance policymakers’ awareness and appreciation of a specificenvironmental problem and policy context.
In the process of interaction with the IEA models and database, and by directly using these tools to address specificproblems, the policymakers would equip themselves with improved capability for policy formulation and implementation.
Because of the interactive and user-friendly features of the products, policymakers would be able to complement their own
expertise and judgment with the models’ analytical and scientific strengths.

3.

Other Relevant Information

Participating organizations and relevant Internet sites:

Energy Research Institute, Beijing, China
http://www.eri.org.cn/
Institute of Geographical Sciences and Natural Resources Research, Beijing, China
http://english/igsnrr.ac.cn/
Indian Institute of Management, Ahmedabad, India
http://www.iimahd.ernet.in/Seoul National University, Korea
http://www.snu.ac.kr/engsnu/
Korea Environment Institute, Seoul, Korea
http://www.kei.re.kr/eng/
Asian Institute of Technology, Pathumthani, Thailand
http://www.ait.ac.th/
Universiti Putra Malaysia, Serdang, Malaysia
http://www.upm.edu.my/WebsiteEnglish/

6

Kyoto University, Kyoto, Japan
http://www.kyoto-u.ac.jp/index-e.html
Fuji Research Institute Corporation, Tokyo, Japan
http://www.fuji-ric.co.jp/english/profile/
National Institute for Environmental Studies, Tsukuba, Japan
http://www.nies.go.jp/
Asia–Pacific Integrated Model
http://www.nies.go.jp/social/aim/index.htm

GlossaryAIM

Asia–Pacific Integrated Model

AM

Adapting Mosaic, a name of scenario for ecosystem assessment, characterized by regionally decentralized
and environmentally conscious societies

ASEAN

Association of Southeast Asian Nations

CDM

Clean Development Mechanism

GDP

Gross Domestic Product

GHG

Greenhouse Gases

GO

Global Orchestration, a name of scenario for ecosystem assessment, characterized by high degree of
globalization and economic growth

IEA

Integrated Environmental Assessment

MAC

Marginal Abatement Cost curveOS

Order from Strength, a name of scenario for ecosystem assessment, characterized by regional consolidation

SDB

Strategic Database

SPM

Suspended Particulate MattertC

Tonnes of Carbon (Mt C: million tonnes of carbon)

TG

Technogarden, a name of scenario for ecosystem assessment, characterized by rapid increase inenvironmental industries supported by globalization

7

Table 1. Current status of IEA applications
Model/Database Application

Policy Needs

Countries/Regions ofapplication (until 2003)

AIM/Energy

Clean air for major cities

China, India

AIM/Material

Assessment of air pollution
reduction policies and healthimpacts

Assessment of technology options Strategy for climate change
mitigation/adaptation
for GHG mitigation

Japan, China, India,
Korea, Thailand

CDM assessment

China, India

Assessment of effects ofenvironmental constraints andinvestments
Trade-off between air pollution
and health impacts

Strategies for environmental
Japan, China, India
industry, waste treatment, waterpollution, climate change, andhealth policy
China

AIM/Ecosystem Assessment of natural capital,
Strategy for ecosystemland-use change, water resource conservation
AIM/Water
depletion, crop productivity, and
AIM/Agriculture energy supply
Top-down
Assessment of free tradeeconomyagreementscomponent of
GHG stabilization scenarios
AIM/Ecosystem

World

Strategy for environmental policy Worldthrough trade
Strategy for climate change
mitigationWorld
Asia–Pacific (7 regions),
World (14 regions)

AIM/Trend

Projection of GHG emissions,water supply and demand, andwastesCommunication tool forpolicymakers

Strategic
Database

Assessment of innovation
technologies under different
socioeconomic scenarios

Strategies for environmental
Japan, China, India,
industry, waste treatment, water Thailand
pollution, and climate change8AIM Models
AIM/ Energy
A bottom-up
technology
selection modelof energy use
and e missions atcountry andlocal level

AIM/ Ecosystem/Water/
Agriculture
A set of models,
including vegetati on
dynamics, water
resource, agricultural
producti vi ty andhealth i mpact

Emiss ion I ntensity of SO2 in China

Land use

Water
Waterresour
resourcece

AIM Family

Scenario
Assessment

modelingWorld
Economic
Model
frame
works

WastesEnv ironmental
BurdenEnviro nmenta l Industry(waste management, r ecycl e)
Technology needs

Research on new techno logies

Model Base

FutureFutureecono
economic
mic trend
trend
FutureFutureenvironenvironmenta
menta lltren
trenddKorea

An econometric
China
type model toconstruct
Thailandcountry le vel
environment
outl ooks

Co nsumer
Enviro nment Fund

Technology assessment

Top-down
AIM/Top-down

AIM/Trend

Environmental
Enviro nburden
mentalBurden Environmental
Industry
Green Purchase
Industry

RecycleOne countr y CG E model
An e nvironmentwith CO2 and material
economyactedbalance,interfinterace withenvironmental
model wi th material
technology model

Crop
Productivity
ity
Productiv

Impact on
on foofoodd dema
demandnd
ImpactAdaptatio n strategy

modeling
Country
Based
Technology
Modelframe works

AIM/Material

Institution, Management,
Technology, Adaptation
Database

Temp era ture
Prec
Precipitatio
ipitationn
Sunshine

Socio
Socio -economic
indicator
indicator

Bottom-up
AIM/End-usebalance andrecycling processmodules

Strategic database

India
Japan

Strategy
Option Base

Figure 1. AIM Models and Strategic Database for APEIS

Purchased
coke

Limestone

Blast furnace
Casting
machineCoke oven

Slabs

Coal
Coke

SinterPig ironRolledsteel
products

Crude
steel
Basic oxygen
furnace

Iron ore
SinteringmachineReheating &annealingCokeoven gasOpen hearth
furnaceBlast
furnacegas

Smelting
reduction
furnaceUtility

Electricity: External energy: Energy device: Internal energy/service: External service

Electricarc
furnace

Heat

Scrap

Purchased
electricity

Figure 2. Example of the technology system of the steel industry in the AIM/Energy model for India

9

Index BaseEmission reduction potential by sector in 201080
40

Market case

Other

Rural

Pow erUrban

Transport

Paper

Commerce

CopperAluminum

Brick

Glass

Fertilizer

Ethylene

Steel

Ammonia0

Cement20
Calcium

Mt-C

60

Less than US$50/t-C

Figure 3. CO2 mitigation potential in China in two selected scenarios as compared to reference scenario in 20100.00
0100.00100
200.00200
300.00300
400.00400
500.00500
600.00600
700.00700
800.00800
900.00900
1,000
1000.00
1,100
1100.00
1,200
1200.00
1,300
1300.00
1,400
1400.00
1,500
1500.00≧1,600>=1600.00<t-C/km2>

Figure 4a. CO2 emission intensity in China in 2010

Rateof reductionof SO2
Reduction
rate of SO2

1

Pollution re moval processes in power
plants and rural residential households

0.8

0.6

Pollution re moval inurban residential
households

0.4

0.2

Other Policy Cases
0
0

0.2

0.4

0.6

0.8

1

Reductrat e of CO2
Rate
of ionreductionof CO2

Figure 4b. Co-benefits of CO2 reduction in China in different sectors

10Figure 5. CO2 emissions from large power plants in India under the reference scenario in 2000 (left) and the 550 ppmv
stabilization scenario in 2030 (right)
2010

2015

2020

2025

2030

0
-10

Billion US$ 2000

-20
-30
-40
-50

COCO2
Constraint
2 constraint-60

Recycling
Recycling++CO
CO2
Constraint
2 constraint-70

Innovation
Innovation++CO
CO2
Constraint
2 constraint

-80
-90

Figure 6. Change in GDP in India under ‘CO2 emissions constraint’, ‘Recycling and emissions constraint’, and‘Technological innovation and emissions constraint’ scenarios
400000OECD

840000Forest (1000ha)

Forest (1000ha)

880000800000760000720000
2000

2025
Year

2050

Global Orchestration (GO)Order from Strength (OS)Asia

350000300000250000
2000

2025
Year

2050

Technogarden (TG)
Adapting Mosaic (AM)Figure 7. Estimation of forest area in selected regions under different long-term scenarios of natural and social
environment

11

Global Orchestration

Order from Strength

Technogarden

Adapting Mosaic

2000

2100

100 101 102 103 (mm/year)

0

ROW

FSU

EUR

-2. 0%

NAM

0. 0%

ANZ

2. 0%
Wor l dW orld

RO W

FS U

EU R

NAM

A S EA N 7

CHN

KO R

‑1.0%

JP N

0.0%

ANZ

1.0%

4. 0%

I DI

2.0%

6. 0%

ASEAN73.0%

SO2 emissions change in 2010

8. 0%

CHN

4.0%

ID I

G D P difference (%)

5.0%

10. 0%KOR

GDP change in 2010

JPN

6.0%

SO 2 emi ssi ons di f f er ence ( %)Figure 8. Estimation of water withdrawal per unit area under different long-term scenarios of natural and social
environment-4. 0%

Figure 9. Impact of free trade agreement among Asian countries in 2010 relative to reference scenario (JPN: Japan, KOR:
South Korea, CHN: China, ASEAN7: Seven ASEAN countries (Indonesia, Malaysia, Thailand, Philippines, Singapore,
Burma, and Vietnam), IDI: India, ANZ: Australia & New Zealand, NAM: USA and Canada, EUR: West-European countries,
FSU: Former Soviet Union, ROW: Rest of World)

12

Box 1. Structure of Top-down Framework of Economy-Environment Linkage as a part of AIM/Ecosystemnon- MAC
CO2

non- MAC
CO2Electricity

Fuels

generation
mix
input

CO2

input

Electricity

Non-energy
goods

CO2
input

CO2

MAC
nonCO2Government
primaryfactors

Note: MAC stands for Marginal Abatement Cost curve

13

MAC
nonCO2

input

Production Sectors

multi-gas emission
rightconsumption

rent

emissionrightsCO2
Households

investment

input

consumption

Energyresource
depletionnon- MAC
CO2

Box 2. Framework of the Strategic Database (SDB)

Sales Campaign for Hybrid Vehicle
Hybrid type gasoline vehicle- Literature search- Interviews with experts

The hybrid system proven in Toyota's “PRIUS”, the world's first mass-produced
hybrid car, achieves its highly efficient operation through sophisticated energy
Sales Campaign for Electric Vehicle
management of a gasoline engine and secondary battery.
When the car stops, the gasoline engine stops too, instead of just idling and Reva: India’s First Electric Car
wasting energy. During start-up and at low speed, gasoline engine efficiency islow, so the car runs on its electric motor, which draws electricity from the
Reva isBut
the India’s first zero-polluting electric vehicle heralds a new
secondary battery. At faster speeds, the gasoline engine propels the vehicle.
of non-polluting, cost effective, quiet city transportation - A boon
the system gives priority to operating the engine only within its mostera
efficientfor cityAt
commuters. This elegant, light-yet rugged, two-door sedan
rpm range, so engine power may not be sufficient when the car accelerates.
such times, therefore, the motor provides assistance to make up for thecomfortably
shortage, seats 4 people. It has a range of 80 kilometers in stopand-go
drawing electricity from the secondary battery. If, on the other hand, thecar city driving, and a top speed of 65 km/h. Reva runs 80 Km
cruises at a steady speed, the engine, which operates with priority placedon aonsingle charge of 9 units of electricity. The cost of the vehicle isefficiency, may produce more energy than is needed. In this case, suchapproximately
excess$ 7000.
energy is used to generate electricity, which is stored
in the secondary battery. If
Eco-Friendly
the accelerator is let up on to slow down, the engine
stopsanautomaticallyto Reva
avoidis zero polluting and noiseless. It does not require
Being
Electric Vehicle,
wasting energy. And during deceleration through braking and other means, thefrequent oil changes. Moreover Reva has high recyclable content
car's forward momentum is used to generate electricity, which is stored in theHigh on Technology
secondary battery.
Two computers and the state-of-the-art electronics in the Reva provide an efficient
Price is 2,150,000 yen and higher by 300,000 yen than conventional type. Fuelenergy management system with advanced computerized vehicle diagnostics. The
efficiency is 30km/l………

Japan case

India case

► Compact Cities
Environmental-technology→ Increase of -leading
public transportation
scenario

CO2 Emission (MtC)

40
30
20

B2
Impact of Innovation
B1
Strategies under eachSocioeconomic Scenario► Remarkable technology innovation→ Bio-ethanol→ H2 fuel cell vehicle
H2 produced from NG and renewables

GeneralEco-drive
LicenseA2

50

Industrial

Economic growth rate
Pop ulation
Crude steel
CementEthy lene
Pap er and p ap erboards
Share of tertiary industry
Households
Heating service p erhousehold
Cooling service p erhouseholdInformation ap p liances p erhousehold
Fuel cell cogeneration

Virtual communication
systemAdvanced car
sharing system

Residential

Gasoline hybrid
vehicleT ransp ortation

Floor sp ace
Fuel cell cogeneration
Passenger transp ortation
Fuel cell vehicles
Freight transp ortation

Power generation Nuclear p ower p lants

0
1995

2000

2005

2010

2015

2020

2025

2030

2035

B2
► Regions coexist symbiotically with independent and sustainable production area.
→ Virtual communication system (Cyber
office)New Independent► Shift
to environmentally
harmonious lifestyle
Areas
Scenario→ Bikeway→ Eco-drive license► Decease of transportation distance by car→ Advanced car sharing system

2010
A2
0.9
126.3
9,860
8,194
701
3,311
64.1
49

(%/y ear)(million)(10,000 t)(10,000 t)(10,000 t)(10,000 t)(％)(million)

A1
2.1
127
8,887
8,398
668
3,052
65.9
49.6

(2000 = 100)

100

92

97

89

(2000 = 100)

145

137

145

133

Quantified Storylines forSocioeconomic Scenarios

Commercial

10► Stagnation of technological innovation

B1

Bikeway60► Suburban sprawl→ Increase of passenger vehicle trans.

► To achieve both economic development
and dematerialization through tech.
innovation

Fuel cell vehicle fueled by by-productH2 of industrial process

A1► High economic growth→ Increase of passenger transportation

Descriptive Storylinesfor► Without consumer ’s awareness regarding
environmental
issuesScenariofeaturing
Socioeconomicregions
Scenarios
and traditions

regenerative braking in the Reva recovers useful electricity by putting it back into thebatteries. Regenerative braking lets the motor act as a generator, converting thevehicle's momentum into electricity….

70

A2► Economic development along the samelines as existing social system► Remarkable technology innovation→ H2 fuel cell vehicle
H2 produced
frommarket-based
fossil fuelGlobalscenario

Narrative Description Cards
containing Environmental
Innovations Strategies

80

A1► Market economy-based system thatemphasizes economical rationale.

Fuel cell vehicle fueled by
H2 from natural gas

Bio-ethanol

14

B1
1.6
128.4
9,120
8,264
640
3,010
65.4
49.4

B2
0.5
127.6
9,119
7,727
645
3,004
64.8
48.8

(2000 = 100)

128

116

122

116

(million kW)(million m2)(million kW)(mil. p ass.-km)(%)(million t-km)
(M W)

0
1,804
0
1,387
0
593
53,248

0
1,710
0
1,343
0
544
57,546

1
1,796
1
1,367
0
559
49,580

0
1,702
0
1,323
0
506
44,917

Box 3. Selected Examples of Innovations
SectorAgriculture,
Forestry &Fisheries

Objective ofenvironmental
burdenreduction
Agricultural
production
improvement

Innovation
classification

Innovation name

Biotechnology

High-efficiency organic farming with microorganisms
Fodder production from microorganism protein
Multifunctional and multi-effect natural food materials
Other technologies
Agricultural production improvement using insects
Biotechnology
Soil moisture fixing by grass plantation
Water
conservation
Other technologies
Drip irrigation, Micro irrigation
Manufacturing Monitoring
Information technology Monitoring and information dissemination for local pollution
Continuous flood monitoring of Himalayan river systems
Other technologies
Marine pollution status tracking by satellite radar
Tropical forest reduction status tracking by satellite
PolicyEstimation and public dissemination of environmental burden
Energy saving
Other technologies
Steel: Dry coke quenching facility
Steel: Direct current electric furnace
Cement: Vertical type millCement: High-efficiency clinker cooler
Brick: Vertical shaft brick kiln
Petrochemistry: Naphtha catalytic cracking
Paper and pulp: Press drying/impulse drying
High-speed switching-type regenerative burner
Air pollution
Other technologies
Activated carbon catalyst type desulfurization equipment
Fertilizer production from desulfurization byproduct
Soil and
Biotechnology
Elimination of mercury by microorganisms
groundwater
Bioremediation
pollution
Nanotechnology
Groundwater purification by photocatalysts
Other technologies
Low-temperature decomposition of pollutants by additives
Soil purification by colloidal iron
PolicySuperfund law
Removal of organic tin from seawater by microorganisms
Water pollution Biotechnology
Treatment of marine oil pollution by microorganisms
Water purification by microorganisms using carbon fiber
EnergyEnergyOther technologies
Ceramic gas turbine
industries
conversion
Superconducting generator
Energy storage Other technologies
Storage of electric power by superconducting flywheel
EnergyOther technologies
Low-loss material for pillar transformers
transportation
Energy networking using low-loss electric power elements
Photovoltaic
Nanotechnology
Efficient solar cell with thin-film layer controlled at nanolevel
power generation Other technologies
Crystal system solar cells
Amorphous system solar cells
Sunlight convergence and tracking system
Fuel production from waste materials
Biomass
Biotechnology
Production of vehicle fuel from waste cooking oil
Conversion of organic wastes to methane15SectorServiceindustries

Objective ofenvironmental
burdenreduction

Innovation
classification

Innovation name

Education

Information technology Decrease in building investment by e-learning
Decrease in movement of people by e-learning
Consulting
Other technologies
Environmental auditing
Environment risk management
Leasing industry Information technology Car sharing
Other technologies
Environmental venture business bond exchange market
Finance
Emission trading market
PolicyDuty-free measures for green money
Transportation Improvement of Information technology Delivery efficiency by integrated vehicle dispatching systemtransportation
Global Positioning System to determine vehicle location
efficiency
Space pricing
PolicyEco-driver's license
Nanotechnology
Hydrogen direct-loading fuel cell vehicle
Automobiles
Platinum catalyst for fuel cells using carbon nanotubes withuniform differential scattering function
Other technologies
Hybrid vehicle
Car lightening by use of aluminum

16

TECHNICAL SUMMARY

I EA
Integrated Environmental Assessment

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

June 2004