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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. 339 340 Y. MATSUOKA et al. 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. Integrated Assessment Model of Climate Change: The AIM Approach 341 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 342 Y. MATSUOKA et al. 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 Integrated Assessment Model of Climate Change: The AIM Approach 343 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. 344 Y. MATSUOKA et al. 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. Integrated Assessment Model of Climate Change: The AIM Approach 345 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, 346 Y. MATSUOKA et al. 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 Integrated Assessment Model of Climate Change: The AIM Approach 347 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) 348 Y. MATSUOKA et al. Fig. 8. Change in potential productivity of winter wheat in 2100, IS92a scenario. Integrated Assessment Model of Climate Change: The AIM Approach 349 350 Y. MATSUOKA et al. Fig. 9. Framework of the malaria model. Fig. 10. Increase in area affected by malaria. Integrated Assessment Model of Climate Change: The AIM Approach 351 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). 352 Y. MATSUOKA et al. 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 Integrated Assessment Model of Climate Change: The AIM Approach 353 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 354 Y. MATSUOKA et al. 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. Integrated Assessment Model of Climate Change: The AIM Approach 355 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 356 Y. MATSUOKA et al. 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. Integrated Assessment Model of Climate Change: The AIM Approach 357 358 Y. MATSUOKA et al. 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 359 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 360 Y. MATSUOKA et al. 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. Bruce, J. P., H. Lee and E. F. Haites (eds.), 1996: Climate Change 1995, Economic and Social Dimensions of Climate Change, Intergovernmental Panel on Climate Change, Cambridge Univ. Press. Integrated Assessment Model of Climate Change: The AIM Approach 361 FAO, 1978–1981: Report on the Agro-Ecological Zones project, Vol. 1–4, World Soil Resource Report 48, Food and Agriculture Organization of the United Nations, Rome. FAO, 1992: Crop water requirements, Irrigation and Drainage Paper-24, Food and Agriculture Organization of the United Nations, Rome. Houghton, J. T. et al., 1996: Climate Change 1995, The Science of Climate Change Intergovernmental Panel on Climate Change, Cambridge Univ. Press. Matsuoka Y. and K. Kai, 1995: An estimation of climate change effects on malaria, J. of Global Environment Engineering, 1, 43–57. Matsuoka, Y., M. Kainuma and T. Morita, 1995: Scenario analysis of global warming using the Asian-Pacific Integrated Model (AIM), Energy Policy, 23(4/5), 357–371. Morita, T., Y. Matsuoka and M. Kainuma, 1994: An integrated model of global warming in the Asian-Pacific region (AIM)—Focus on emission modeling—. Proceedings of the 3rd JapanU.S. Workshop on Global Change Modeling and Assessment, 111–118, October 25–27, 1994, Honolulu, U.S.A. Nakicenovic, N. et al., 2000: Special Report on Emissions Scenarios, Intergovernmental Panel on Climate Change, Cambridge Univ. Press. Takahashi, K., H. Harasawa and Y. Matsuoka, 1996: Climate change impact on global crop production, J. of Global Environment Engineering, 2, 145–161. Takahashi, K., H. Harasawa and Y. Matsuoka, 1997a: Climate change impact on global crop production, J. of Global Environment Engineering, 3, 145–161. Takahashi, K., Y. Matsuoka and H. Harasawa, 1997b: Evaluation of climate change impacts on crop production considering effects of CO2 fertilization, Environmental Systems Research, 25, 121– 131. Takahashi, K., Y. Matsuoka and H. Harasawa, 1998: Impacts of climate change on water resources, crop production and natural ecosystem in the Asia and Pacific region, J. of Global Environment Engineering, 4, 91–103. Takahashi, K., H. Harasawa and Y. Matsuoka, 1999: Impacts of climate change on food production— An economic Assessment—, J. of Global Environment Engineering, 5, 1–8. Wigley, T. M. L. and S. C. B. Raper, 1993: (in) Climate and Sea Level Change: Observations, Projections and Implications, Cambridge Univ. Press, 111–133. Y. Matsuoka (e-mail: [email protected]), T. Morita and M. Kainuma