IMAGE framework summary/Description: Difference between revisions
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===Projections for driving forces, population and economic development=== | ===Projections for driving forces, population and economic development=== | ||
Key inputs for the model are projections describing direct and indirect drivers of global environmental change ([[ | Key inputs for the model are projections describing direct and indirect drivers of global environmental change ([[Scenario drivers]]). Most of these drivers (such as technology and lifestyle assumptions) are used as input in various subcomponents of IMAGE (see figure on the right). Clearly, the exogenous assumptions made on these factors need to be consistent. To ensure this, so-called storylines are used, brief stories about how the future may unfold, that can be used to derive internally consistent assumptions for main driving forces. Important categories of scenario drivers include demographic factors, economic development, lifestyle, and technology change. Among these, population and economic development form a special category as they can be dealt with in quantitative sense as exogenous model drivers. Other drivers mostly concern assumptions in different subcomponents of IMAGE, for examplee.g. both the yield assumptions in the crop growth model and the performance of solar power production in the energy model depend on a more generic description of the rate of technology change. | ||
For population, the IMAGE model mostly uses exogenous assumptions (total population per region, household size and urbanization rate). Also the population projections of the [[PBL]] [[GISMO model]] can be used, which allows, in principle, to also account for feedback of environmental factors (e.g. air pollution and undernourishment) on population growth (see [[Impacts]]). For that purpose, population can be downscaled to the grid level. For economic variables such as [[GDP]], usually also exogenous assumptions are used. In most studies the economic projections are developed by macro-economic models based on the same storylines as the rest of the IMAGE model to ensure consistency. Sector specific economics and household consumption can be derived directly by such models, in addition the latter can be broken down into income categories, reflecting the so-called [[GINI]] coefficient (a measure of the disparity in income distribution). | For population, the IMAGE model mostly uses exogenous assumptions (total population per region, household size and urbanization rate). Also the population projections of the [[PBL]] [[GISMO model]] can be used, which allows, in principle, to also account for feedback of environmental factors (e.g. air pollution and undernourishment) on population growth (see [[Impacts]]). For that purpose, population can be downscaled to the grid level. For economic variables such as [[GDP]], usually also exogenous assumptions are used. In most studies the economic projections are developed by macro-economic models based on the same storylines as the rest of the IMAGE model to ensure consistency. Sector specific economics and household consumption can be derived directly by such models, in addition the latter can be broken down into income categories, reflecting the so-called [[GINI]] coefficient (a measure of the disparity in income distribution). | ||
Revision as of 17:28, 11 December 2013
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