Download Integrated Assessment Model of Climate Change: The AIM Approach Yuzuru M

Present and Future of Modeling Global Environmental Change: Toward Integrated Modeling,
Eds., T. Matsuno and H. Kida, pp. 339–361.
© by TERRAPUB, 2001.
Integrated Assessment Model of Climate Change:
The AIM Approach
Yuzuru M ATSUOKA1, Tsuneyuki MORITA2 and Mikiko KAINUMA2
1
Graduate School of Engineering, Kyoto University, Japan
2
National Institute for Environmental Studies, Japan
INTRODUCTION
It is predicted that global climate change will have significant impacts on the
society and economy of the Asian-Pacific region, and that the adoption of
measures to tackle global climate change will force the region to carry a very large
economic burden. Also, if the Asian-Pacific region fails to adopt such
countermeasures, it has been estimated that its greenhouse gas emissions will
increase to over one-half of total global emissions by the end of the next century.
In order to respond to such serious and long-term threats, it is essential to
establish communication and evaluation tools for policy makers and scientists in
the region. Integrated Assessment Model (IAM) provides a convenient framework
for combining knowledge from a wide range of disciplines, and is one of the most
effective tools to increase the interaction among these groups.
The Asian-Pacific Integrated Model (AIM) is a large scale computer
simulation model developed to promote the integrated assessment process in the
Asian-Pacific region. The main goal of this model is to assess policy options for
stabilizing global climate, particularly in the Asian-Pacific region, from the two
perspectives of reducing greenhouse gas emissions and avoiding the impacts of
climate change.
The AIM model has several distinct characteristics. The model:
1. integrates emission, climate and impact models,
2. prepares both country modules for detailed evaluation at the state and
national level and global modules to ensure consistency across individual
modules,
3. integrates bottom-up national modules with top-down global modules,
4. is designed to assess alternative policies,
5. contains a very detailed technology selection module to evaluate the effect
of introducing advanced technologies,
6. uses information from a detailed geographic information system to evaluate
and present the distribution of impacts at the local level,
7. focuses on the Asian-Pacific region and is based on a collaborative
network of international research institutes.
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Fig. 1. Framework of the AIM.
The AIM model has made many contributions to policy deliberations at the
national, regional and global levels. It has been used to provide global and
regional emission scenarios and regional impact assessments to the
Intergovernmental Panel on Climate Change (IPCC), the Stanford Energy
Modeling Forum (EMF) for the international comparison of emission scenarios
and impact assessments, as well as contributions to Eco-Asia (the Congress of
Asian Ministers for the Environment), the Global Environmental Outlook (GEO/
UNEP) and so on.
STRUCTURE OF THE AIM MODEL
The AIM comprises three main models—the greenhouse gas (GHG) emission
model (AIM/emission), the global climate change model (AIM/climate) and the
climate change impact model (AIM/impact). Figure 1 shows the relationships
among the main models.
The AIM/emission model consists of country level bottom-up energy models
and top-down type energy and land-use models of global level. A variety of global
and regional assumptions such as on population, economic trends, as well as
government policies, are entered into the model and they are interacted with the
regional and country models to provide estimates of energy consumption, landuse changes etc., and provide predictions of GHG emissions. Emissions of SO 2,
NO x and SPM are also calculated within the AIM/emission, and they are input in
the AIM/climate and a regional environmental model, which was developed in
order to reinforce the interaction with local atmospheric pollution problem.
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Fig. 2. Framework of the AIM/impact.
Except for CO2, GHGs emitted into the atmosphere are gradually transformed
by chemical reactions, which are calculated within the AIM/climate. We divided
these chemicals into two groups based on their reaction rates: long-life chemicals,
such as CFCs and halons, and short-life chemicals such as ozone and OH radicals.
Pseudo-equilibrium state is assumed for the latter group and the oxidation and
photochemical reactions of CH4 and other molecules are represented by simple
kinetic equations. The absorption of CO2 and heat to ocean is calculated using a
upwelling-diffusion (UD) model (part of the AIM/climate) with the oceans
divided into a surface mixed layer and an intermediate layer which extends down
to about the 1000 meters.
Global averaged temperature changes are calculated with an energy balance/
upwelling-diffusion ocean model, and used for input into the regional models.
Data from the GCM experiments are used in order to estimate regional distribution
of climate parameters. They are coupled with global averaged temperature
change calculated in the AIM/climate. The interpolated climate distribution are
used in the AIM/impact, which calculates global and regional climatic impacts.
The AIM/impact treats mainly the impact on primary production industries, such
as water supply, agriculture, forest products and human health. It can also be used
to assess higher-order impacts on the regional economy. Figure 2 shows the
relationships among the sub-modules of the AIM/impact.
Environmental and socio-economic data of the region have been gathered
and filed in a geographical information system (GIS). Models to estimate water
resource changes, vegetation changes and malaria spread caused by global
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Fig. 3. Framework of the AIM/emission.
warming have been developed on this database. The resolution of the database is
county or province level.
THE AIM/EMISSION
The AIM/emission consists of two types of models, i.e. country level
bottom-up energy models and global level top-down type energy and land-use
model (Fig. 3). In the bottom-up type energy model, energy demand is calculated
by multiplying the amount of energy service and energy efficiency factors. The
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Fig. 4. CO 2 emissions based on SRES storylines, the AIM/emission.
factor is calculated with the energy efficiency sub-module, and depends on
assumptions about the R & D, diffusion of new energy technologies, and energy
prices. Detailed mechanism of energy technology renewal processes is described
in the bottom-up model. Costs and performances of more than 200 energy service
technologies are listed, from which consumers and industrial managers choose
best ones which fulfill their needs. The energy demands of the devices are
summed up, and the country/regional total of energy demand is estimated.
The energy demand is a function of the people’s socio-economic activity. In
the bottom-up model, the causal relationship between microscopic people’s
activity and energy consumption can be described, however, the macroscopic
consistency among the country activities and energy supply conditions are not
considered. To complement this drawback, a global level top-down model was
developed. It is an energy-economic model with regional and global markets of
energy, and the demand and supply of energy goods are balanced. GHG emission
activities besides energy consumption are also considered in the top-down model.
In order to calculate GHG emissions from land-use changes, a global land-use
model is developed, which also describes the interaction between land-use
changes and biomass energy production.
The AIM/emission has 9 regions for the top-down type energy-economic
model and 17 regions for the bottom-up and land-use models. Its time horizon is
from 1990 to 2100. The calculated GHGs and related gases include:
•
Carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), carbon
monoxide (CO), non-methane volatile organic compounds (NMVOCs), nitrogen
oxides (NOx), and sulfur dioxide (SO2) emissions from energy combustionproduction processes.
•
CO2 from deforestation.
•
CH4 and N2O from agricultural production.
•
NMVOCs and SO2 from biomass combustion.
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Fig. 5. Outline of the AIM/climate.
•
CO2, CH4, N 2O, NOx, CO, NMVOCs, and SO2 emissions from industrial
processes, waste management, and land-use changes.
Emissions of CFCs and other GHGs are provided exogenously based on related
protocols and regulations. Figure 4 presents CO2 emission projections by the
AIM/emission based on SRES storylines (Nakicenovic et al., 2000), which will
be used as reference scenarios in the Third Assessment Report of IPCC.
THE AIM/CLIMATE
Several types of simplified climate models were developed to represent the
CO2 and heat absorption processes to the ocean, and the sea level rise. The basic
structures of the models are common, and alternative formulations of submodules are prepared. The basic structure of the AIM/climate is shown in Fig. 5.
GHG emissions calculated in AIM/emission are pored into one or several
boxes which represent the hemispherical and altitudinal partitions of the
atmosphere. Carbon dioxide is assumed not to decay, but is absorbed to ocean and
terrestrial ecosystems. Ocean absorption is estimated by a simple upwelling
diffusion model or convolution approximations of OGCMs experiments. In our
model, carbon dioxide fertilization effect and temperature effect on net primary
production are attributed to the missing sink of the carbon cycle. Regarding the
first effect, the β coefficient (the sensitivity of net primary production to CO2
concentration) is assumed in order to balance the global carbon balance. As for
the other GHGs, the decaying processes are modeled with the first order reactions.
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Table 1. Concentrations, temperature and sea level rise projections based on SRES marker
scenarios.
The kinetic coefficients in the equations were calibrated by comparison with the
outputs of more complex, but realistic models. The relation between radiative
forcing and GHG concentration is calculated with the equations summarized in
the IPCC report (Houghton et al., 1996). The direct and indirect effects of 29
GHGs, SO2 and NO2 are calculated. The effect of moisture in the stratosphere and
the cooling effect of lower stratospheric ozone decrease and aerosol sulfates are
also calculated with the simplified radiation model.
The relationship between radiative forcing ∆Q and hemisphere land/ocean
temperature rise is formulated with an energy balance/upwelling-diffusion (EB/
UD) ocean model.
Sea level rise is calculated from the expansion of seawater due to temperature
increase, the melting of the continental glaciers, and changes in the ice sheets of
Greenland and Antarctica. The contribution of ice-melting is calculated using the
equations by Wigley et al. (1993). To estimate the expansion, we divided the
oceans into 20 degree latitude belts and calculated the increased volume of seawater. Table 1 presents the projected temperature and sea-level rise under SRES
scenarios calculated with the AIM/climate.
Research on climate change impact requires spatial data of future climate. To
consider the spatial distribution of future climate, we use the outputs from the
climate model which were calculated using various General Circulation Models
(GCMs). Since the spatial resolution of GCMs is not fine enough for direct use
in impact studies, the output is interpolated spatially to generate values at a finer
resolution. GCM outputs can thus generate spatial future climate data using the
global mean temperature increase in the following equations. For temperature,
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T (t ) = T ( base) + ∆T2 × CO 2 ×
Tmean (t ) − Tmean ( base)
.
Tmean (2 × CO 2 ) − Tmean (1 × CO 2 )
(1)
For precipitation,
log P(t ) = log P( base) +
P(2 × CO 2 )
Tmean (t ) − Tmean ( base)
× log
. (2 )
Tmean (2 × CO 2 ) − Tmean (1 × CO 2 )
P(1 × CO 2 )
Here, T(t) and P(t) are the temperature and the precipitation in year t, respectively.
∆T2 ×CO 2 is the temperature difference and P(2×CO2)/P(1×CO2) is the precipitation
ratio between 2×CO2 and 1×CO2 values for each cell of the spatial grid as
calculated by GCMs. T mean(t) – Tmean(base) is the global annual mean temperature
increase between the base year and year t, which is calculated in the AIM/climate.
THE AIM/IMPACT
Climate change has direct or potential impact on water resources, agricultural
production, natural ecosystems and human health, even if we do not consider the
socio-economic interaction. In actual world, global trade, immigration, measures
of adaptation modify direct impacts. In this way, there are two stages of impact
study, i.e. direct and indirect stage, and in this model, we are preparing two kinds
of modules, which correspond to them.
As for direct impact analysis, four models have been developed. They are
surface water runoff/transport model, crop productivity model, vegetation model
and infectious disease model. They are linked to indirect impact models such as
world agriculture trade model and a macro-economy model of country level.
They are economical general equilibrium type models, which can evaluate socioeconomic linkage effect of the direct impacts of climate change.
DIRECT IMPACT MODELS
The surface water runoff/transport model is the basic part of the direct
impact models (AIM Project Team, 1996). It creates high-resolution grid data
sets of surface runoff, soil moisture, evapotranspiration, and river discharge. Soil
moisture capacities are estimated using current vegetation classes and soil
textures by a one-layer soil water model. To estimate potential evapotranspiration
(PET), two optional modules were prepared. They are the FAO24 (FAO, 1992)
method and Thornthewaite methods respectively, depending on data availability.
Crop productivity is estimated with a framework shown in Fig. 6. Days
suitable for crop cultivation (GP) are counted using climate data, and the crop
growth during the growing period is simulated using the growth characteristic
parameters of each crop. This model requires daily mean temperature, mean
daytime temperature, precipitation, PET, photo-synthetically active radiation
(PAR), and soil characteristics. Most of them are calculated by the AIM/climate
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Fig. 6. Outline of the crop productivity model.
and the surface water runoff model. Fertilizing effect of carbon dioxide
concentration on crop growth is optionally included in the model. Four properties
of soil are taken into account to represent a suitability of land resource: soil units,
soil phase, soil texture and soil slope. To consider the high spatial variability of
these constraints, soil data of a 5-minute resolution grid are used. Potential
productivities of rice, winter wheat, maize and other crops are selected as
representative indices of crop production. Plant/variety specific parameters of
the model are prepared from FAO study (FAO, 1978) or estimated by comparing
with reported and calculated crop production. Figures 7 and 8 show the productivity
changes caused by the climate change in the East Asia.
Potential vegetation is assessed with the Holdridge method (Takahashi et al.,
1998). This model uses a climate classification scheme that relates the distribution
of ecosystem complexes to the climate variables of bio-temperature (cumulative
temperature), precipitation, and the ratio of PET to precipitation. Two climate
variables, bio-temperature and annual precipitation, determine the classification.
Maps produced by the Holdridge model represent potential distributions of
vegetation depended on the climate. The changes in temperature and precipitation
projected by Eqs. (1) and (2) are used to estimate the changes in the climate zones,
which shows the potential impacts on natural ecosystems.
Malarial risk change is also estimate with climate and soil moisture changes
(Matsuoka and Kai, 1995). Figure 9 shows the framework of the estimation. The
major components of the model are the relationship between sporogony and
temperature, and the eco-climatic index model that shows the climatic response
of vectors. Figure 10 shows the calculated malaria potential under current and 4C
global temperature rise. The yellow indicates areas where the risk of malaria is
meso-endemic and the red highlighted areas are where it is hyper-endemic.
Fig. 7. Change in potential productivity of rice in 2100, IS92a scenario.
-2000
0
+2000
(kg/ha)
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Fig. 8. Change in potential productivity of winter wheat in 2100, IS92a scenario.
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Fig. 9. Framework of the malaria model.
Fig. 10. Increase in area affected by malaria.
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Fig. 11. Country averaged temperature change, global averaged temperature increase: 2°C.
POTENTIAL CLIMATE IMPACTS IN THE ASIAN-PACIFIC REGION
The AIM/impact estimates the potential climate impacts in the Asian-Pacific
region. Regional variation of GCM outputs is so large that 11 different GCM
outputs* were used and they were coupled with the AIM/climate in order to get
the representative responses to climate change. Also, in this section, we prescribed
global temperature increase between 0.5–4.0°C, and calculated country aggregated
responses to those changes.
Changes in temperature and precipitation averaged in the countries are
shown in Figs. 11 and 12. These are the cases in which global averaged
temperature change is 2°C, and 䊉 corresponds to a 3 month average of DJF
(December, January and February) and 䊊 to JJA (June, July and August). These
circles indicate the median values of all GCMs. Maximum and minimum values
for these GCMs are shown as the edges of horizontal error-bars. The median
temperature changes in Asian countries range from 1.25 to 2.76°C, but they might
range from 0.06 to 3.59°C according to the error-bars in Fig. 11. While the median
precipitation changes range from +1–34% in Asian countries, there is uncertainty
because of the difference of spatial distribution among GCMs.
Based on the outputs of these national climate changes, potential crop
production changes are shown in Fig. 13 for rice, maize, and wheat, where global
*CCC (Boer et al., 1989), GISS (Hansen et al., 1984), GFDL (Wetherald and Manabe, 1986),
GFDL R30 (Wetherald and Manabe, 1989), GFDL Q-flux (Wetherald and Manabe, 1989), OSU
(Schlesinger and Zhao, 1989), Ukmet (Wilson and Mitchell, 1987), UIUC (Schlesinger, 1996), MRI
(Tokioka et al., 1995), GISS (Miller and Russell, 1995), and GFDL 100 (Manabe et al., 1992).
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Fig. 12. Country averaged precipitation change, global averaged temperature increase: 2°C.
Fig. 13. Country averaged productivity change of rice, maize, and wheat, global averaged
temperature increase: 2°C.
averaged temperature increase is 2°C. A little decrease of rice production is
expected in most countries, while slight increase is expected in Bhutan and
Taiwan. The productivity of wheat will decrease significantly in Bangladesh,
India and other tropical countries. China may not be affected seriously by this
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Fig. 14. Potential production change of rice.
Fig. 15. Potential production change of winter wheat.
climate change. As for maize (tropical variety), Bangladesh is expected to have
a large productivity increase. The impacts on other countries are within ±5%. The
variance in the productivity change among GCMs is large. However, the tendencies
toward productivity gain or loss are roughly the same for each country, showing
that such trends are in close agreement for different GCMs.
Figures 14, 15 and 16 show temperature dependencies of crop productivities
in some countries with error-bars. Potential productivity in some countries
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Fig. 16. Potential production change of maize.
Fig. 17. Decrease in temperate/boreal forest.
decreases monotonously in proportion to the global temperature increase, while
a threshold of temperature increase can be found in other non-sensitive countries.
Moreover, there are countries where productivity increases first with the
temperature increase of 1–2°C, and then it begins to decrease with the more
severe temperature increase.
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Table 2. Direct climate change impacts in the Asia and Pacific Region.
As for natural ecosystems, changes in present forest regions were analyzed.
Figure 17 shows changes in the forest area. The forests in some countries in
Fig. 17 are presently temperate/boreal and change to other classifications under
future conditions. In Japan and China, 35% of forest area is expected to change
by 2°C global temperature increase, and more than a 50% by 4°C. Most of the
changes take place toward tropical forest. Table 2 summarizes the impacts for
2°C global temperature increase, in which the significance of the impacts was
evaluated subjectively. According to Table 2, the Indian subcontinent seems to
suffer from various direct impacts of climate change, such as losses of areas
suitable for wheat production and temperate forest. It can be concluded that the
Indian subcontinent should be studied more intensively. Other regions such as the
East Asia are affected less seriously compared with the Indian subcontinent.
Areas for suitable temperate and boreal forest will decrease by 40% in the East
Asia as a result of 2°C global temperature increase.
INDIRECT IMPACT OF CROP PRODUCTIVITY CHANGES
The above section concerns only direct impacts of climate change, and social
and economic effects of these impacts are not considered. The change of potential
crop productivity will modify the global crop trade, and consequently people’s
food condition of the world. In the AIM/impact, a general equilibrium global
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Table 3. 11 GCMs’ median of the potential productivity changes in the three crops in 2100 under
the IS92a scenario(%), calculated with AIM/impact.
Country
Australia
New Zealand
Japan
South Korea
Indonesia
Malaysia
Philippines
Singapore
Thailand
China
Hong Kong
Ta iwan
India
Other South Asia
Canada
U.S.A.
Mexico
Central America and
Caribbean
Argentina
Brazil
Chile
Other South America
EU
Austria, Finland, Sweden
Europian Free Tra de Area
Central Europian Associates
Former USSR
Middle East and North Africa
South Africa
Rest of the world
Rice
Wint er wheat
Maize
IS92a IS92a* IS92a IS92a* IS92a IS92a*
27
9
18
- 15
42
8
14
-2
36
-1
40
7
17
0
31
-5
26
-4
13
-2
29
-7
26
-4
13
- 2 - 22
- 44
30
-1
11
-4
28
-3
12
-4
29
-2
10
-5
37
4
18
1
28
-7
30
-1
26
9
24
- 10
28
-2
4
- 11 - 24
- 45
31
0
14
- 2 - 12
- 36
51
15
105
76
72
25
140
83
17
0
33
-4
33
1
11
- 4 - 19
- 41
24
-5
14
- 2 - 42
- 58
29
-2
12
13
50
14
22
109
55
20
-3
-3
29
-2
5
80
34
3
27
- 21
37
0
27
74
66
29
-8
- 43
-1
- 27
-8
26
21
-6
30
29
72
31
35
166
84
29
-1
-2
31
0
3
102
41
-2
85
25
12
17
59
9
-3
1
66
24
- 19
26
20
- 10
- 41
-9
74
43
28
44
33
9
-3
10
* : without fertilization
trade model is prepared in order to assess the economic impact of crop productivity
changes (Takahashi et al., 1999). The potential crop productivity changes under
IS92a emission scenario shown in Table 3 were coupled with this model, and the
changes of several agro-economic indices were calculated. Table 4 shows some
extracts of them. Without CO2 fertilization effect, in Canada, the productivity of
crops increase (Table 3), causing a significant decrease in the producer price of
crops. The amount of crop production increases, while the production of
manufactured goods and services decreases. Although the consumer price index
increases, reflecting the price increases in non-agricultural sectors, the increase
Table 4. Impact of climate change on economy through the change in crop productivity in 6 regions.
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in income exceeds the increase in prices, and social welfare increases by 0.3%.
Canada is found to be the country gaining the most benefit of these listed in
Table 4. In India, the producer price of wheat becomes more than double, and the
amount of production decreases in all sectors. Since the consumption of agricultural
products and processed agricultural commodities accounts for a large part of
private expenditure in India, social welfare decreases by 4.8%. Considering the
poor people in India, a decrease in agricultural consumption could cause a severe
hunger problem. In Japan, the anticipated decrease in crop productivity causes an
increase in the price of wheat and other grains and a decrease in the production
of the crops, however, the effect is not so large and social welfare increases by
0.02%. The same tendency is found for the U.S.A. The world social welfare
decreases 0.046%, or 9.5 $US billion under the climate condition in 2100, unless
we consider CO2 fertilization effect.
THE AIM APPROACH AND ITS POLICY NEED
In the previous sections, we introduced the AIM structure and some examples
of the outputs. The model has been developed in order to comprehend and assess
the relationship between human society and the natural environment especially
in the field of climate change. Recently, such kind of models, called Integrated
Assessment Model (IAM), is developed intensively. The need of integrated
assessment on climate change issues is required on many occasions. Some needs
are quite clear, while others are not so obvious. However, these needs increase
quickly. Three major needs were identified and the AIM has been designed with
a unique structure so that it can be used to meet these needs:
To identify incentives for policy measures of climate change
Many of the countries in the region need concrete examples of climate
change damage, short-term co-benefits and small economic impacts of policies
in order to increase the incentives for policy adoption. To meet this need requires
integration of emission and impact models, global warming and local
environmental models, and emission and economic models. Some topics belong
to this category are:
•
To compare costs and benefits of introducing global warming abatement
policies.
•
To identify vulnerable regions and sectors to climate change.
•
To identify and estimate secondary effects of global warming abatement
policies on regional and local environments.
Systematic assessment of climate change mitigation policy
Systematic and consistent assessment of policy options is essential for
policy makers to be able to make sound decisions. Assessments need to be made
on the technical feasibility for GHG reductions, the combined effects of various
policies, the consistency of policy combinations and approaches to GHG
reductions. To meet these needs requires integration of technology and economic
Integrated Assessment Model of Climate Change: The AIM Approach
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models, top-down and bottom-up models, energy and land-use models and CO2
emission and other GHG emission models. Some topics belong to this category
are:
•
To assess technological and economical feasibility for GHG reduction
considering costs and markets.
•
To assess consistency of mitigation policies, such as increasing biomass
use and land availability.
•
To assess comprehensive approaches for GHG reduction including
energy saving, introduction of renewable energy, reforestation, methane emission
reduction and CO2 disposal.
Long-term policy option assessment
Consistent method to discuss on the atmospheric stabilization target is
needed. Compatible short and long-term policies are required, and their feedback
loops and interactions among energy-use changes and the social and economic
systems must be assessed. Some topics belong to this category are:
•
To prepare a common platform to discuss on long-term targets of
atmospheric stabilization.
•
To compare short-term mitigations with long-term adaptation policies.
•
To assess the long-term interaction among mitigation policies, natural
and socio-economical impacts of climate change, and other global issues, such as
economic development, food problem and so on.
CHALLENGE TO THE IAM STUDY
The natural and socio-economic systems stand between human activities and
global environment. In most cases, the effects of any of these systems cannot be
ignored, and the necessity of integrating them has been asserted many times.
Figure 18 shows an integrated framework especially on the climate change
problem (Bruce et al., 1996). Up to now, integrated models based more or less on
this framework have been constructed and various studies have been conducted.
Whether such work has developed to the level where it can serve as the basis for
judgments in formulating actual global environmental measures is, at present,
giving rise to many discussions, but it can be said that the framework itself has
for the most part been accepted. Integrated assessment on global environmental
issues from the natural and social perspectives is not a field of learning involving
the pursuit of truth. Rather, they are a practical science aimed at providing useful
guidance for various social rules and policies that can smoothen the relationships
among natural rule, the global environment and humanity.
Conventionally, it has been possible to encapsulate the relationships between
such practical scientific studies and the real world in a relatively simple framework.
Researchers could formulate policies for studies through their understanding of
policy needs or immediate needs, and with the basic science and various statistics
as a base, assess and analyze human and social activities and derive certain rules
and forecasts. The formulation of issues has been unsophisticated, with society
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Fig. 18. Integrated framework for climate change assessment.
referring to these rules and forecasts and proceeding with the process of policy
decisions, political negotiations, etc.
However, such a framework is incompetent in the case of issues having a
gigantic and uncertain structure such as global environmental issues. These
issues, consisting of myriad important factors that are also interrelated in a
complex manner, there are many cases in which it is extremely difficult not only
to gain a comprehensive understanding of the issue, but also to clarify what the
issue is. Moreover, the people and governments of the world are the interested
parties, so that obtaining agreements recognizing these issues is difficult. In many
cases the issues have a super long-term span, during which structural changes can
take place in socio-economic systems and even part of the natural system may
also undergo structural change. With regard to such issues, even in gaining a basic
understanding of an issue or in its formulation, it is impossible to have a one-sided
relationship of dependence from the study to the real world, or from the real world
to the study. Both must evolve interactively and in the course of this, the process
of understanding the issue toward solutions will simultaneously advance. In this
process, a logical, deductive formulation of the issue may be made, but its essence
should be sought in terms of practical significance. Moreover, the principles and
fundamental rules that are abstracted to individual basic sciences, such as natural
science, economic theory, psychology, law, and so on, also need to be fed back
during this process.
REFERENCES
AIM Project Team, 1996: Technical structure of AIM/impact model, AIM Interim Paper, IP-95-06,
Tsukuba, Japan.
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