Looking Into the Future for Agriculture and AKST | 357

ary schooling, the ratio of female to male life expectancy at birth, and the percentage of the population with access to safe water (see also Rosegrant et al., 2001; Smith and Haddad, 2000). The model incorporates data from FAOSTAT (FAO, 2003); commodity, income, and population data and pro­jections from the World Bank (2000), the Millennium Eco­system Assessment (MA, 2005), and the UN (2000) and USDA (2000); a system of supply and demand elasticities from literature reviews and expert estimates (Rosegrant et al., 2001); and rates for malnutrition (UN ACC/SCN, 1996; WHO, 1997) and calorie-child malnutrition relationships developed by Smith and Haddad (2000).

A.5.1.3 Application
IMPACT has been used for analyzing the current and fu­ture roles of agricultural commodities and impacts on food security and rural livelihoods, including the future of fisher­ies (Delgado et al., 2003); the role of root and tuber crops (Scott et al., 2000a, 2000b); and the "livestock revolution" (Delgado et al., 1999). IMPACT has also been applied to regional analyses as well as selected country-level studies, for example, China (Huang et al., 1997), Indonesia (SEARCA/ IFPRI/CRESECENT 2004), sub-Saharan Africa (Rosegrant et al., 2005a) and Central Asia (Pandya-Lorch and Roseg­rant, 2000). IMPACT has also been used to analyze struc­tural changes, including the impact of the Asian economic and financial crisis (Rosegrant and Ringler, 2000); longer-term structural changes in rural Asia (Rosegrant and Hazell, 2000); as well as global dietary changes (Rosegrant et al., 1999). The model has also been used to describe the role of agriculture and water for achieving the Millennium De­velopment Goals (von Braun et al., 2004; Rosegrant et al., 2005b).
     Model runs have been carried out for individual centers of the CGIAR, the World Bank and the Asian Development Bank. The model has also been used for agricultural scenario analysis of the Millennium Ecosystem Assessment (Alcamo et al., 2005; MA, 2005), and is currently being used for the Global Environmental Outlook (GEO-4) assessment carried out by UNEP. Other work includes investigations into re­gional and global scale impacts of greenhouse gas mitiga­tion in agriculture and theoretical large-scale conversion to organic food production.

A.5.1.4 Uncertainty
In the following tables, the points related to uncertainty in the model are summarized, based on the level of agreement and amount of evidence.

A.5.2 The Integrated Model to Assess the Global Environment (IMAGE) 2.4

A.5.2.1Introduction
The IMAGE modelling framework had been developed origi­nally to study the causes and impacts of climate change within an integrated context. Now the IMAGE 2.4 is used to study a whole range of environmental and global change problems, in particular aspects of land use change, atmospheric pollu­tion and climate change. The model and its submodels have

 

been described in detail in several publications (Alcamo et al., 1998; IMAGE team 2001; Bouwman et al., 2006).

A.5.2.2 Model structure and data
The IMAGE 2.4 framework describes global environmen­tal change in terms of its cause-response chain, and belongs to the model family of integrated assessment models. The IMAGE model consists of two major parts: the socioeco-nomic system, elaborating on future changes in demograph­ics, economy, agriculture and the energy sector, and the bio­physical system, comprising land cover and land use, atmo­spheric composition and climate change. The IMAGE model focuses on linking those two parts through emissions and land allocation. Land allocation follows inputs from the IM­PACT model, allowing an assessment of the environmental consequences of changes in the agricultural sector. One of the crucial parts of the IMAGE 2.4 model is the energy mod­el, Targets IMage Energy Regional (TIMER). The TIMER model describes the chain, going from demand for energy services (useful energy) to the supply of energy itself through different primary energy sources and related emissions. The steps are connected by demand for energy and by feedbacks, mainly in the form of energy prices. The TIMER model has three types of sub-models: (1) a model for energy demand, (2) models for energy conversion (electricity and hydrogen production) and (3) models for primary energy supply. The final energy demand (for five sectors and eight energy car­riers) is modelled as a function of changes in population, economic activity and energy efficiency. The model for elec­tricity production simulates investments in various electric­ity production technologies and their use in response to elec­tricity demand and to changes in relative generation costs.
     Supply of all primary energy carriers is based on the interplay between resource depletion and technology de­velopment. Technology development is introduced either as learning curves (for most fuels and renewable options) or by exogenous technology change assumptions (for thermal power plants). To model resource depletion of fossil fuels and uranium, several resource categories that are depleted in order of their costs are defined. Production costs thus rise as each subsequent category is exploited. For renewable energy options, the production costs depend on the ratio between actual production levels and the maximum production level. Climate change mitigation policies can be implemented in the TIMER model, allowing assessing changes in the energy composition due to these policies (Van Vuuren et al., 2006; Van Vuuren et al., 2007).
     The TIMER model also simulates the potential impor­tance of biomass as an energy category. The structure of the biomass sub-model is similar to that of the fossil fuel supply models but with a few important differences (see also Hoog-wijk et al., 2005). First, in the bioenergy model, depletion is not governed by cumulative production but by the degree to which available land is being used for commercial energy crops. Available land is defined as abandoned agricultural land and part of the natural grasslands in divergent land use variants for the twenty-first century and is based on IMAGE alternative variant calculations. This assumption excludes any possible competition between bioenergy and food pro­duction, which is a simplification of reality. The potential available land is categorized according to productivity levels