261

Integrated Assessment of Greenhouse Gas Stabilization
Concentrations, Emission Pathways, and Impact Threshold Values
for Control of Global Warming
Yasuaki HIJIOKA* and Kiyoshi TAKAHASHINational Institute for Environmental Studies
16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan*e-mail: hijioka@nies.go.jp

Abstract
To mitigate the dangerous impacts of global warming to the greatest extent possible, various greenhouse gas stabilization scenarios have been proposed. Integrated studies are proceeding on emission
pathways and the costs of achieving climate stabilization, as well as on the impact risks of global warming. This paper summarizes the existing knowledge on temperature rise, mitigation measures and impact
threshold values, with a particular emphasis on climate stabilization scenarios. It also gives an outline of
the AIM/Impact[Policy] policy support tool developed for integrated assessment of global warming, andreports on the results of analyses of global mean temperature increase, emission pathways, and global
warming impacts under GHG concentration stabilization constraints.
Key words: emission pathway, global warming impact, greenhouse gas stabilization scenario,
integrated assessment

1. Introduction
The concentration of carbon dioxide in the atmosphere reached approximately 370 ppm in the year
2000, compared to approximately 280 ppm prior to
the industrial revolution, and the global mean temperature is reported to have risen by 0.6 ± 0.2°C
through the 20th century up to the present time
(Folland et al., 2001). This increase in temperature has
been attributed mainly to greenhouse gases (GHGs)
emitted into the atmosphere as a result of humanactivity (Mitchell, 2001). The impacts of global
warming are already manifesting in various places
around the world (Folland et al., 2001), and withfurther progress of global warming in the future,significant impacts have been projected in diverse
areas including natural ecosystems, living environments, agriculture, water resources, and so on (Hitz &Smith, 2004; Hare, 2003). There is also concern overthe possibility of a shutdown of thermohaline circulation, which would result in instability of the climate
system; melting of the West Antarctic and Greenland
ice sheets, which would cause an irreversible sea level
rise; and melting of permafrost, which could lead to asudden release of GHGs (Church et al., 2001).
Efforts must be made for climate stabilization inorder to mitigate global warming to the greatest extent
Global Environmental Research
10(2)/2006: 261-270
printed in Japanpossible. The United Nations Framework Convention
on Climate Change (1992) sets forth the ultimate
objective of “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent
dangerous anthropogenic interference with the climate
system.” However, it has not been shown in concreteterms at what level GHG concentrations need to bestabilized, nor by how much and via what types ofpathways GHG emissions need to be reduced, in orderto achieve this objective. The European Union has
proposed that the rise in the global mean temperature
be limited to 2°C compared to that prior to the industrial revolution as the “level that would prevent dangerous anthropogenic interference (Commission of theEuropean Comunities, 2005).” To accomplish thislong-term goal, studies have been progressing on
targeted GHG stabilization concentrations, GHG
emission reduction plans (mitigation measures) andtheir costs, and global warming impact risks in various
sectors (WBGU, 2003; RCEP, 2000; MIES, 2004;
SEPA, 2002).
In this paper, we summarize the existing knowledge on mitigation measures, temperature rise andimpact threshold values, with particular emphasis on
climate stabilization scenarios. We also introduce anintegrated analysis method using AIM/Impact[Policy](Hijioka, 2005), a policy support tool for compre©2006 AIRIES262

Y. HIJIOKA and K. TAKAHASHI

hensive analysis and assessment of GHG stabilization
concentration targets and emission pathways forrealizing them, as well as impacts and risks undersuch targets.

2. Stabilization Concentrations, Emission
Pathways, and Impact Threshold Values
2.1 Climate stabilization scenarios and emission
pathways
In order to mitigate the impacts of global warming,
it will be necessary to establish targets that incorporatestabilization concentrations, temperature rises, andmitigation measures in an integrated way, taking impact threshold values into consideration. Discussionsof these issues have continued since the 1980s(Harasawa, 2005a). At a symposium on the stabilization of greenhouse gases held at the Hadley Centre in
the United Kingdom in 2005, scientific knowledge on
the most recent impacts of climate change, the possibility of achieving stabilization targets and concrete
mitigation measures for achieving these targets(Cramer et al., 2006) were discussed and summarized.
Various stabilization scenarios have been developed thus far (Meinshausen et al., 2004) for use instudies on GHG stabilization concentration targets andmitigation measures for achieving them. These can bebroadly classified into scenarios under which only
carbon dioxide (CO2) concentrations are stabilized(S profile (Houghton et al., 1994), WRE profile(Wigley et al., 1996), Post-SRES (Swart et al., 2002),
etc.) and scenarios under which all GHGs arestabilized by converting them into CO2 equivalentconcentrations (EMF-21 (De la Chesnaye, 2003),
EQW (Meinshausen et al, 2004), etc.). In the CO2
concentration stabilization scenarios, no stabilization
constraints are imposed on the scenarios of GHGs
other than CO2 and aerosols that have a cooling effect,
so the relationship between the global mean temperature and CO2 stabilization concentration is notstandardized among the scenarios. Attention must
therefore be paid to this point when establishing target
values for temperature rise using CO2 concentration

Fig. 1 S and WRE profiles. (IPCC, 1996)

stabilization scenarios.
Representative stabilization scenarios are outlined
below.
(1) S profile (Houghton et al., 1994) and WRE profile(Wigley et al., 1996) (Fig. 1)
S profile scenarios are CO2 concentration stabilization scenarios released by the Intergovernmental Panelon Climate Change (IPCC) in its Second Assessment
Report (Houghton et al., 1994), describing CO2 emission pathways when CO2 concentrations are stabilized
at 450, 550, 650, 750 and 1,000 ppm. In the case of
the S profile, when a low stabilization concentration
target is established, the IPCC concludes that early
reduction of CO2 emissions and continued strengthening of reductions are necessary.
WRE profile scenarios, whose name was takenfrom the initials of authors Wigley, Richels andEdmonds, are also CO2 concentration stabilization
scenarios like those of the S profile. However, theydescribe economically efficient emission pathways,
and compared with the S profile, CO2 emissions continue on an upward trend for a time, followed by a
drastic reduction, implemented at a certain stage. In
the WRE scenarios, although there is room for further
discussion on the setting of discount rates, technological innovations, energy-saving promotion effects, andso on, these scenarios indicate that it is possible forvarious different emission pathways to achieve thesame concentration stabilization target.
(2) Post-SRES (Swart et al., 2002) (Fig. 2)
Post-SRES CO2 stabilization scenarios are mitigation scenarios formulated based on the Special Reporton Emissions Scenarios (SRES) (Nakicenovic et al.,2000) released in 2000 by the IPCC. In the Post-SRES
scenarios, atmospheric CO2 stabilization concentrations are set at 450, 550, 650 and 750 ppm, and thetiming and degree of the necessary mitigation measures are quantitatively shown under six future development assumptions described by the SRES (A1B,
A1FI, A1T, A2, B1 and B2). Figure 2 shows anthropogenic CO2 emission pathways according to future
development pathways described by the SRES, andCO2 emission pathways when CO2 concentration

Integrated Assessment of Greenhouse Gas Stabilization Concentrations

263

Fig. 2 Comparison of SRES and post-SRES scenario ranges in total global CO2 emissions. (Morita et al., 2001)

stabilization constraints are imposed. The CO2 emission pathways obtained when CO2 concentration
stabilization constraints are imposed clearly show
larger differentiations due more to the differences inconstraints than to the differences in future world scenarios. On the other hand, when these results are compared with the case in which no concentration stabilization constraints are imposed, the amounts of reduction show large variations according to different futureworld trends, suggesting that the degree of difficultyof achieving climate stabilization will depend greatly
on the circumstances in the future world.
(3) Equal Quantile Walk (EQW) (Meinshausen et al.,
2004; Meinshausen, 2005) (Fig. 3)
In EQW, which is targeted at GHGs and aerosols,
detailed studies are conducted on the relationships
between stabilization concentrations and emission
pathways. Figure 3 shows changes in GHG concentrations and emission pathways for three GHG stabilization concentration targets (GHG concentrations of 550,
475 and 400 ppm). In the case of the 550 ppm stabilization scenario, it is estimated that emissions in 2050of the gases targeted for reduction under the Kyoto
Protocol (hereafter referred as “Kyoto gases”) willneed to be reduced by approximately 10% from the1990 levels. In the case of the 475 ppm and 400 ppm(peak concentration 475 ppm) stabilization scenarios,on the other hand, a considerable reduction of approximately 50% in Kyoto gas emissions in 2050
compared to the 1990 levels is estimated to be necessary. Under these scenarios, CO2 emissions originatingfrom land use change are assumed to have a negativevalue (i.e., they are absorption sources). Hence, when
CO2 emissions originating from land use change havea high value, as in the present situation, even moreglobally

Fig. 3 Global Kyoto-gas emissions for stabilization at 550,
475 and 400 ppm CO2 eq. (Meinshausen, 2005)

severe reductions in emissions are found to be required. Moreover, studies of various mitigation measures under the 400 ppm GHG concentration stabilization target (peak concentration of 475 ppm) have concluded that considerable efforts will be required if
mitigation is delayed.
Under the EQW approach, therefore, quantitative
analyses of various GHG concentration stabilization
targets have been conducted taking differences in reduction starting times into consideration in order todetermine the future course that should be taken, particularly in terms of mitigation measures.
2.2 Stabilization concentrations and temperaturerise
Meinshausen has studied the relationship between
GHG stabilization concentrations and global mean
temperature increases taking uncertainty into consideration (Meinshausen, 2005). The temperature rise at
the time of GHG concentration stabilization is esti-

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Y. HIJIOKA and K. TAKAHASHI

mated by Eq. (1) and (2) below:∆Q = α*ln(C/C0)(1)∆T = ∆Q*(∆T2xCO2/α*ln(2))

(2)

-1

Probability Density (°C )where ∆Q: radiative forcing, α: coefficient, C: CO2
equivalent concentration,
C0: CO2 concentration prior to the industrial revolution, ∆T: global mean temperature increase (compared to that prior to the industrial revolution), and∆T2xCO2: climate sensitivity.
As shown in Eq. (2), the global mean temperature
increase is determined by radiative forcing and climate sensitivity. Climate sensitivity indicates longterm (equilibrium) variations in the global mean temperature when atmospheric CO2 concentration doubles.
The global mean temperature increase, a parameterthat comprehensively indicates the uncertainty ofphysical processes and interactions contained in a climate model, is estimated at 1.7°C to 4.2°C in the
IPCC’s Third Assessment Report (Cubacsch et al.,2001). With regard to the uncertainties in climate
sensitivity, a probability density distribution approachhas been proposed using various methods (Forest
et al., 2002; Gregory et al., 2002; Kerr, 2004; Murphy
et al., 2004; Wigley & Raper, 2001).
Using the probability density distribution functionof climate sensitivity reported in the existing studies
shown in Fig. 4, Meinshausen clarified the relationship between stabilization concentration (radiative
forcing) and global mean temperature increase interms of the probability of overshooting the target values for global mean temperature increase (1.5°C,
2.0°C, 2.5°C, 3.0°C and 4.0°C), with the temperature
prior to the industrial revolution as the base (Fig. 5).
According to Fig. 5, for example, it can be seen that in
the case of 450 ppm GHG concentration stabilization,
the probability of overshooting 2°C is 47% on average,
with minimum and maximum values of 26% and 78%,
respectively. In this way, Meinshausen has attemptedto achieve analysis with a higher degree of reliability
by using the probability distribution of climate
sensitivity to express targeted GHG stabilization

concentrations and the global mean temperature
increase in terms of a range of probabilities.
2.3 Impact threshold values
Classifications such as the following have been
proposed (Harasawa, 2005b) to define thresholdvalues for the impacts of global warming.
(1) Type 1: When the amount of damage shows linear or other smooth changes with the degree of climate change, this type of threshold value indicatesa point at which such damage is judged to be impermissible by certain decision makers. The targeted sectors are WEHAB (water, energy, health,agriculture, biodiversity), and others. For example,
permissible upper limits can be cited for populations at risk of food shortages, water shortages,
health deterioration, etc., or permissible degree of
reduction in biodiversity.
(2) Type 2: This type of threshold value is directly
connected to the main processes of the climate system itself, and indicates a point that should not be
exceeded in order to maintain the stability of oneof the processes. Examples that can be cited are a
shutdown of thermohaline circulation, which
would result in instability of the climate system;
melting of the West Antarctic and Greenland ice
sheets, which would cause an irreversible sea level
rise; and melting of permafrost, which could leadto a sudden release of GHGs.
Since the impacts of global warming affect various
fields, there have been many studies assessing individual sectors. There are far fewer studies, however, inwhich different sectors have been assessed in an integrated manner. Examples of studies that comprehensively summarize the results of research on global
warming impacts in various sectors include those by
Hitz & Smith (2004), Hare (2003), Parry et al. (2001)
and Leemans & van Vliet (2004). Parry et al.
summarized the relationship between temperature
increase and CO2 concentration, and risk populations(from hunger, malaria, flooding, water shortages) withthe global mean temperature increase as the predictor

Andronova and Schlesinger (2001) - with sol. & aer. forcing
Forest et al. (2002) - Expert priors
Forest et al. (2002) - Uniform priors
Gregory et al. (2002)
Knutti et al. (2003)
Murphy et al. (2004)
Schneider et al. (in prep.) - trop. SST 2.5°C - 3°C
Wigley and Raper (2001) - IPCC lognormal

Climate Sensitivity (°C)
Equilibrium warming at 556 ppm CO2 equivalence concentrations.

Fig. 4 Probability density functions of climate sensitivity. (Meinshausen, 2005)

Integrated Assessment of Greenhouse Gas Stabilization Concentrations

1.5°C

265

Andronova and Schlesinger (2001) - with sol. & aer. forcing
Forest et al. (2002) - Expert priors
Forest et al. (2002) - Uniform priors
Gregory et al. (2002)
Knutti et al. (2003)
Murphy et al. (2004)
Schneider et al. (in prep.) - trop. SST 2.5°C - 3°C
Wigley and Raper (2001) - IPCC lognormal

3.0°C

Probability of staying below indicated level(IPCC Terminology)

4.0°C

2.0°C
2.0°C

Andronova and Schlesinger (2001) - with sol. & aer. forcing
Forest et al. (2002) - Expert priors
Forest et al. (2002) - Uniform priors
Gregory et al. (2002)
Knutti et al. (2003)
Murphy et al. (2004)
Schneider et al. (in prep.) - trop. SST 2.5°C - 3°C
Wigley and Raper (2001) - IPCC lognormal

Probability of staying below indicated level(IPCC Terminology)

Probability of staying below indicated level(IPCC Terminology)

2.5°C

CO2 equivalence concentrations (ppm)Fig. 5 The risk of overshooting 1.5°C, 2.0°C, 2.5°C, 3.0°C and 4.0°C global mean equilibrium warming for different CO2
equivalent stabilization levels. (Meinshausen, 2005)
Hunger,malaria,flooding

Water
shortages

Hunger,malaria,flooding

350

3,500

350

3,500

300

3,000

300

3,000

250

2,500

250

2,500

200

2,000

200

2,000

150

1,500

150

1,500

100

1,000

100

1,000

50

500

50

500

0

0

Millions at risk in the 2050s

0
0

0.5

1
1.5
2
2.5
Global temperature increase (°C)
LegendRisk of water shortages

3

Risk of malaria

0

Water
shortages

Millions at risk in the 2080s

0.5

Risk of hunger

1
1.5
2
2.5
Global temperature increase (°C)

30

Risk of coastal flooding

Fig. 6 Additional millions at risk due to climate change in the 2050s and 2080s from hunger, coastal flooding,water shortages and malaria. (Parry, 2001)

variable, thereby providing knowledge for discussionof values at which the temperature increase should bestabilized (Fig. 6). From now on, it will be necessary
to further refine global warming studies, taking uncertainty into consideration, and to integrate knowledge of impacts in various sectors, of which there
have been many reports recently, so as to provide
scientific information with high reliability for discussing climate stabilization targets.

3. Development of a Global Warming
Impact Assessment Method for Climate
Stabilization
3.1 AIM/Impact[Policy]
In the present study, we are developing AIM/
Impact[Policy] (Hijioka, 2005), a policy support tool

to assist in achieving climate stabilization targets bycomprehensively analyzing and assessing GHG concentration stabilization and mitigation measures aswell as impacts and risks under the targets (Fig. 7).
AIM/Impact[Policy] is being developed and applied in a study entitled “Comprehensive assessmentof climate change impacts to determine the dangerous
level of global warming and appropriate stabilization
target of atmospheric GHG concentration” (hereafterreferred to as “S-4”), which is a research topic of the
Global Environmental Research Fund (GERF) of
Japan’s Ministry of the Environment. The objective of
S-4 is to promote comprehensive assessment of climate change impacts in Japan and the Asia region.
The objective of the development of AIM/Impact[Policy] is to provide an integrated approach for the
analysis of dangerous levels of global warming

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Y. HIJIOKA and K. TAKAHASHI

impacts by connecting the knowledge obtained fromsectoral climate change impact studies with GHG
stabilization targets.
In establishing future targets for the global mean
temperature, sea level rise, atmospheric GHG concentrations, and so on, AIM/Impact[Policy] functions to(1) project the optimal GHG emissions path and GHG
reduction burden by region, and (2) show the scale ofthe impact of warming by country and sector under
this GHG emissions path, and provide materials toinvestigate whether or not the established future targets are sufficient to avoid “dangerous impacts” (i.e.,
to determine the validity of future targets). This will
be highly useful for formulating specific future targets
for global warming response policies.
AIM/Impact[Policy] consists of multiple models.
These are classified into models to simulate GHG
emissions under the global warming control targets(an energy economic model, a burden sharing model
to estimate the GHG reduction burden by country, anda global economic model to assess economic impacts
resulting from the implementation of global warming
response policies), and a model to simulate the global
warming impact anticipated to occur under the global
warming control targets (an impact assessment andadaptation model) (Fig. 7).
3.2 Outline of energy economic model
The energy economy model (Hijioka, 2005) contained in Fig. 7 is used to simulate the optimum GHG
emission pathway in terms of economic efficiency for
an assumed climate stabilization target, and to quantiStabilization target of
GHG concentrations and/or
global temperature increasetatively assess the impacts of global climate change
and sea level rise. This model consolidates the world
into a single region, and consists of four basic modules (an economic/energy module, greenhouse gas
emissions module, climate module and sea level rise
module). It allows policy targets to be quantitatively
assessed by identifying optimal paths of economic
development under various constraints; namely,(1) GHG concentration constraints, (2) global mean
temperature constraints, (3) temperature change rate
constraints and (4) sea level constraints. These constraints can be set simultaneously, and the time thatthe constraints are applied can also be set freely, froma single point to multiple points in time.
In this model, in addition to changes in radiative
forcing resulting from GHG and SO2 emissions, thosedue to ozone (stratospheric and tropospheric), variations in stratospheric water vapor, soot originatingfrom fossil fuels, and soot originating from biomass
combustion are also modeled. Values for GHG concentration are expressed by converting the sum ofthese radiative forcing values into CO2 concentration.
3.3 Outline of impact assessment and adaptation
model
By quantitatively showing country-level and sector-level global warming impacts under the GHG concentration stabilization targets, the impact assessment
and adaptation model provides materials to investigate
whether or not the established future targets are sufficiently low to avoid “dangerous impacts” (i.e., todetermine the validity of future targets).

Intolerable level ofclimate change impact

Choice oflong-term target

Trajectory of sector /country-wise impact

Impact assessment model for global climate change（multi-region/sector, database type model）
Energy economic model for
global multi-GHG emission constraint（single-region, economic and simplified climate model）

Trajectory of global
temperature

Flexibility scheme for
GHG emission constraint

Economically optimal path ofglobal GHG emissions

Global CGE model for global
multi-GHG emission constraint（multi-region/sector）

Burden-sharing scheme

GHG emission permit path atcountry level and economic
cost of emission reduction

Fig. 7 Outline of AIM/Impact[Policy].

Input (target)
Model/Scheme
OutputIntegrated Assessment of Greenhouse Gas Stabilization Concentrations

In investigating the validity of future targets, ahighly simplified impact cost estimation equation (e.g.,
an equation for estimating the global impact cost as afunction of global mean temperature change) for
endogenous use in the economic model is insufficientbecause it cannot grasp regional deviations in impacts
and it has low accuracy in impact estimation. On theother hand, impact assessment models that segment
the world into lattice points and give detailed
estimates of the impact for each lattice point entail alarge computational burden and are not suited totrial-and-error investigations of the validity of various
future targets. In the present study, therefore, using
existing detailed sector-level impact assessment models, we estimated the impact on each lattice point using sensitivity analysis with two climate factors, temperature and precipitation, and we spatially averaged
them to prepare country-level and sector-level impact
functions (the predictor variables were change in temperature and change in precipitation from the present
conditions) to estimate the scale of the warming
impact by country and sector.
Figure 8 gives an outline of the impact assessment
and adaptation model used to assess sector-level impacts, with the global mean temperature estimatedusing the energy and economic model as input data.
3.3.1 Global mean temperature
Annual changes in global mean temperature (compared to the base year) are calculated using the climate
module integrated into the energy economic model. As
mentioned above, it is possible to set various stabilization concentration constraints. Moreover, it is possible

for users to arbitrarily set the climate sensitivity,
which has the greatest impact on the estimation oftemperature rise.
3.3.2 Country-level normal climate change
database
Country-level normal climate change databases areprepared in order to estimate country-level climatechanges. Here, General Circulation Model (GCM)
experimental output is aggregated by country meanvalue according to the following equations, and thecountry mean values (spatial pattern) of climatechange (temperature change and precipitation change)
are stored as a table type database.
Country-level normal temperature change [°C/°C]= (Future average year country mean temperature− Present average year country mean temperature)/ (Future average year global mean temperature −Present average year global mean temperature)(3)
Country-level normal precipitation [% / °C] = (100× Future average year country mean precipitation /Present average year country mean precipitation –100) / (Future average year global mean temperature − Present average year global mean temperature)(4)Here, the years 2071 to 2100 are used for the
future average years, the base years (1961 to 1990) areused for the present average years, and the average isadopted when there are multiple emission scenario
calculation results from the same GCM.

Economic-energy model for global multiGHG emission constraint(dynamic optimization model, singleregion, simplified climate model )Normal climate change DB bycountry

AO-GCMs

Policy selection,
Assumption of international affairs,
Equity criteria,
Assumption of technologicalchanges, etc．

Climate sensitivity

Global averagetemperature

Pattern scaling
Climate scenario bycountyCountry averaged potential impact
by field

Potential impact byinterpolated estimation

GCM selection
Japanese climate
scenarioParameters foradaptation
capacity equation

Other impact
studies

Equation foradaptation
capacity estimation
Adaptation
capacity

Potential impact by
field

AIM/Impact

267

Agri., Water, Health, Biodiversity

Impact assessment modelfor global climate change(multi-region/sector,
database type model)

Equation for risk
assessment of climatechange impact

Parameters for risk assessment
equation by field

Sectoral risk by climatechange impact
Agri., Water, Health, Biodiversity

Synopsis of risk indicators by
climate change impact

Criteria for integrated
judgement

Integrated judgment of success or failure of
avoidance of risk from climate change

Fig. 8 Outline of the impact assessment and adaptation model (database type model).

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Y. HIJIOKA and K. TAKAHASHI

3.3.3 Country-level climate scenarios
The climate scenarios of targeted countries are prepared using the stored country-level normal climatechange database. This involves preparing countrylevel annual mean temperature scenarios using a country-level pattern scaling method. Specifically, an arbitrary GCM is selected from the spatial pattern of the
GCM (country-level mean climate change) containedin the country-level normal climate change database,and future country-level annual mean temperature
scenarios and country-level annual mean precipitation
scenarios are calculated using the following equations:
Country-level annual mean temperature [°C] =Global temperature change × Country-level normal
temperature change + Country-level base year
annual mean temperature(5)Country-level annual mean precipitation [mm] =(Global temperature change × Country-level normal precipitation change / 100 + 1.0) × Country-level base year annual precipitation(6)
3.3.4 Sector-level country-mean potential impact
database
Detailed impact assessments which place a large
calculation burden on the computer are not carried out
in AIM/Impact[Policy]. Rather, the results of assessments performed outside the tool are stored as a database. The impact assessment results are stored afterconverting presently observed climate data into unitsof 0.5°C for mean temperature and 5% for precipitation using an already developed impact assessment
model, then impact estimation is performed by sensitivity analysis of the mesh that is created. The results
are aggregated by country-mean values, and input into
the database. This database can also contain knowledge obtained by other impact studies.
3.3.5 Sector-level potential impact
The sector-level potential impact is estimated byinterpolation, combining the country-level climatechange (annual mean temperature change and annual
precipitation change) with the sector-level country-mean potential impact database. The impact estimated here is not a risk estimation taking adaptation
into consideration, but the physical potential impact tobe used as material for damage estimation.
3.3.6 Adaptive capacity
Although cumulative assessment of the cost-effectiveness of individual adaptation measures would be
an ideal method of studying adaptive capacity, inorder to study the effects of introducing individual
adaptation measures – where localized effects are seen
in many cases – on a global scale or at the regional orcountry levels, enormous amounts of data and detailed
case studies become necessary. At the first step of thedevelopment process, therefore, this problem is handled by dealing with adaptive capacity in simple terms.
Concretely, by combining socioeconomic factors, aparameter to determine adaptive capacity is incorporated into a function for estimating sector-level impact
risk (described below), providing a mechanism thatallows users to determine the relationship between
socioeconomic scenarios and adaptive capacity. As
regards the socioeconomic factors to be combined,
different factors are used according to the sector.
3.3.7 Sector-level impact risk
Sector-level impact risk can be obtained using afunction with potential impact and adaptive capacity
as variables. For impact risk, we are planning to prepare various physical quantities, risk indexes for performing integrated assessment, and economic losses
by sector.
3.3.8 Comprehensive judgment of global warming
impact
It is difficult to summarize the risk of impacts invarious sectors and express the degree of impact interms of a single numerical index. Indicating the degree of impact in each sector in the form of a graphic
chart in both a sector-parallel and time-series manner
can therefore assist comprehensive judgment. Moreover, a comprehensive judgment criteria module isbeing developed. This module judges whether or not
the sector-level impact risk set by the user can be
avoided under various emission and socioeconomic
scenarios and levels of adaptive capacity.
3.4 Global warming impact assessment using
GHG concentration stabilization scenarios
We performed calculations under business as usual(BaU) conditions and the following two constraints toassess the impacts of global warming under GHG
stabilization conditions.
• BaU: Business as usual• GHG-475 ppm: a 475 ppm cap on total GHG concentration• GHG-550 ppm: a 550 ppm cap on total GHG concentration
Constraints were calculated so that GHG concentrations not exceeding the constraint could be maintained from 1990 to 2200. The SRES B2 scenario prepared by IPCC was used for estimating figures on
future population and future economic development. A
discount rate of 4%, an annual reduction ratio of GHG
emissions/primary energy supply of 0.85, and a climate sensitivity of 2.6°C were applied. Figure 9shows the results obtained.
In the BaU case, GHG emissions would continue
to increase until 2050 (Fig. 9 (a)), and by 2150 GHG
concentrations (Fig. 9 (b)) would have increased toapproximately three times the 1990 level. The global
mean temperature (Fig. 9 (c)) would rise 3.5°C by
2100 and 4.5°C by 2150, and would also continue toincrease thereafter. Judging from the projected temperature change in 2150, when the GHG concentration
constraint is 550 ppm, the increase (2.5°C) exceeds
the 2°C level seen in the case of the 475 ppm constraint. Focusing on GHG emissions (Fig. 9 (a)), in theIntegrated Assessment of Greenhouse Gas Stabilization Concentrations

case of GHG of 475 ppm, reductions of approximately
10% and 50% in GHG emissions need to be achievedby 2020 and 2050, respectively, compared to the 1990
level, indicating an urgent need for a full-scale reduction system. GHG emissions after 2010 are consistently lower than the 1990 level when the GHG concentration is capped at 475 ppm, confirming the needfor a strict emissions control policy.
As shown in Fig. 9(d), the projected rises in sea
level in the case of GHG of 475 ppm are 0.16 m by2100 and 0.22 m by 2150. These rises are respectively
0.64 and 0.55 times those projected for the BaU scenario. Under the condition of GHG of 550 ppm, on theother hand, the rise in sea level by 2150 is 0.26 m,
about 1.2 times that projected in the case of GHG of
475 ppm. Since the sea level continues to show arising tendency even after the GHG concentration isstabilized, a more severe constraint can be inferred
when considering the stabilization target in terms ofsea level rise.
When the change in potential rice productivity(India) is examined in comparison with the average-year conditions from 1961 to 1990 (Fig. 9(e)), a
very slight decrease is seen in all cases including the
BaU case in the first half of the 21st century. In thelatter half of the 21st century, however, the decrease inpotential productivity gradually progresses in the BaU
case, with the level of decrease expected to reach almost 25% by the end of the century. Although the adverse impact of decreased productivity is less in the
GHG of 550 ppm case than in the BaU case, a moderate decreasing trend continues from 2040 onward. In
the GHG of 475 ppm case, however, the situation in
the first half of the 21st century is projected to be

virtually maintained in the years after 2040. With regard to the potential productivity of wheat in India(Fig. 9(f)), a decreasing tendency during the 21st century cannot be avoided even in the case of GHG of
475 ppm, but the rate of decrease is gentle comparedto the BaU case.
To summarize the analysis results, temperaturerises and adverse impacts are mitigated in the cases of
GHG of 475 ppm and GHG of 550 ppm in comparison
with the BaU case. However, even in the case of GHG
of 475 ppm, which requires severe reductions in emissions (approximately 10% reduction in 2020 and 50%
reduction in 2050 compared to 1990), climate change
impacts cannot be avoided. Measures against global
warming integrating both mitigation and adaptation
measures are therefore essential.

4. Conclusion
In this paper, we have summarized the existing
GHG stabilization scenarios and reported the resultsof analyses of global mean temperature increase and
GHG emission pathways as well as global warming
impacts under GHG concentration stabilization constraints using the AIM/Impact[Policy] policy support
tool. Our results indicate that (1) a GHG concentration
stabilization target not exceeding 475 ppm is necessary to limit the rise in global mean temperature to
2°C compared to the level prior to the industrial revolution, requiring a significant reduction in emissions at
an early stage; and (2) global warming impacts cannot
be avoided even if GHG concentrations are stabilizedat 475 ppm or less, making global warming response
measures integrating both mitigation and adaptation
4.0

900

(b)

(c)
Temperature increase(1990=0.6)

700

500

2070

2080

2090

2100

2090

2100

2050

2080

-20

(e)

-25

-10
-15
-20

(f)

-25

2050

2030

2100

2090

2080

2070

2060

2050

2030

2020

2010

2040

Year

2020

-30
2000

2100

2090

2080

2070

2060

2050

2040

2030

2020

2010

2000

1990

Year

2060

-15

-30

0.0

2070

-10

-5

2010

0.1

-5

2000

0.2

0
Change in potential wheat
productivity (India) (%)

Change in potential riceproductivity (India) (%)

(d)

2040

1990

2100

2090

2080

2070

2060

Year

0

0.3

Sea level rise (m)

2050

Year

2060

Year

2040

2030

2020

2010

2000

0.0
1990

2100

2090

2080

2070

2060

2050

2040

2030

2020

2010

2000

1990

300

2030

0

1.0

2020

5

2.0

2040

10

3.0

2010

15

2000

(a)

CO 2 equivalent concentration(ppmv)

CO 2 equivalent emission(GtCeq/yr)

20

269

Year

Fig. 9 Effects of two GHG concentration constraints on (a) GHG emissions, (b) GHG concentrations, (c) Global
mean temperature increase, (d) Sea level rise, (e) Change in potential rice productivity (India), and (f) Change
in potential wheat productivity (India).

270

Y. HIJIOKA and K. TAKAHASHI

measures essential.
As regards future tasks, integrated studies taking
uncertainty into consideration need to be promoted in
the areas of stabilization targets, mitigation measuresto achieve the targets, and adaptation measures to reduce impacts and risks under the targets.
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(Received 12 September 2006, Accepted 26 September 2006)