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| {{FrameworkSummaryPartTemplate | | {{FrameworkSummaryPartTemplate |
| |Status=On hold
| | |PageLabel=Introduction model description |
| |PageLabel=Detailed description | |
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| |Reference=PBL, 2012;
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| |Description={{DisplayFigureTemplate|IMAGE framework scheme}}
| | <div class="page_standard"> |
| ==The IMAGE framework== | | <p>The IMAGE framework is structured according to the causal chain of key global sustainability issues (see the figure below). IMAGE comprises two main systems. The Human or socio-economic system describes the long-term development of human activities relevant for sustainable development. The Earth system describes changes in the The |
| The IMAGE integrated assessment framework is structured around the chain of key global sustainability problems (see figure on the right) . Similar to other integrated assessment models, it contains two main subcomponents: | | IMAGE framework is structured according to the causal chain of key global sustainability issues (see below). IMAGE comprises two main systems. The Human or socio-economic system describes the long-term development of human activities relevant for sustainable development. The Earth system describes changes in the natural environment. The two systems are linked by the impacts of human activities on the Earth system, and by the impacts of environmental change in the Earth system on the Human system.</p> |
| #the human system, describing the long-term development of human activities relevant for sustainable development issues;
| | {{DisplayFigureLeftOptimalTemplate|IMAGE framework schematic}} |
| # the earth system, describing changes in the natural environment.
| | ==Key features of IMAGE== |
| The two systems are coupled in two directions: via the impact of human activities on the environmental system, and via the impacts of environmental change back on the human system. | | ===Spatial scale=== |
| Now we briefly describe the various components of the IMAGE system, following the structure of the IMAGE framework. Each of these will be described in far more detail in the IMAGE framwork component pages. The IMAGE model can be used to explore the possible consequences of policy inaction (so-called baseline or reference scenarios) and to study the potential impact of different policy interventions. Throughout this report, we will use the baseline scenario used in the Rio+20 study to illustrate main model output. Here, while introducing the IMAGE model – we illustrate the key outcomes of (sub-)components resulting from this scenario.
| | The Human system and the Earth system in IMAGE 3.0 are specified according to their key dynamics. The geographical resolution for socio-economic processes is 26 regions selected because of their relevance for global environmental and/or development issues, and the relatively high degree of coherence within these regions (the figure below). In the Earth system, land use and land-use changes are presented on a grid of 5x5 minutes, while the processes for plant growth, carbon and water cycles are modelled on a 30x30 minutes resolution. |
| | | {{DisplayFigureLeftOptimalTemplate|Region classification map}} |
| ===Projections for driving forces, population and economic development===
| | See [[Region classification map]] for a detailed overview of the IMAGE 3.0 regions. |
| 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.
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| 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).
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| Assumptions for future scenarios start from observed trends in recent decades and this is also the base for the baseline scenario used in the Rio+20 study ([[PBL, 2012]])). The global population is based on the UN medium projection and grows to about 9 billion people in 2050, the increase mostly occurring in developing countries. The economic projection shows that developing countries increasingly dominate the world economy in terms of total GDP. For the [[OECD]] countries, the baseline scenario assumes a long-term economic growth rate of 1-2% per year over the whole scenario period. In the short term, per capita growth rates in Asia and Latin America are much higher, but they start to converge gradually to a long-term growth rates of around 2% per year. Africa, in contrast, shows a later peak in economic growth.
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| [[File:007g img13.png|thumb|500px|right|alt=Figure1_IF_summary|link=Trends in population and income.|Trends in population and income.]]
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| ===Human activities in relation to environmental change: the energy and land use system ===
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| Two key areas of human activity play a key role in many environmental and sustainable development issues:
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| # energy use and supply ([[Energy supply and demand]])
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| # food consumption and supply ([[Agriculture and land use]]).
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| Hence, in the IMAGE model, these human activities are the centers of attention.
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| ====Energy supply and demand====
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| For energy use and supply, the IMAGE framework uses a detailed energy system model (The IMage Energy Regional model, [[TIMER model|TIMER]]) to describe the long-term dynamics of the energy system; see [[Energy supply and demand]]. This includes demand for energy services and end-use energy carriers, and the role of fossil fuels versus alternative supply options such as renewables and nuclear power to meet the demands . The model determines the demand for energy services on the basis of primary drivers and assumptions on lifestyle. This demand is fulfilled by final energy carriers, which are, in turn, produced from primary energy sources. Both the mix of final energy carriers and the technologies to produce them are chosen on the basis of their relative costs. Key processes that determine these costs include technology development and resource depletion, but also preferences, fuel trade assumptions and policies play a role. The output of the model demonstrates how energy intensity, fuel costs and competing non-fossil supply technologies develop over time. Implementation of emissions mitigation is generally modeled on the basis of price signals. A carbon tax (used as a generic measure of climate policy) induces additional investments in energy efficiency, in fossil-fuel substitution, bioenergy, nuclear power, solar power, wind power and carbon capture and storage. The energy model is linked to other parts of the IMAGE model via calculated emissions (see further) and demand for bio-energy production (generating input into the land use model).
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| ''The model can be used to make detailed projections of energy developments, for instance with and without climate policy. In the Rio+20 baseline scenario, the baseline scenario (without climate policy) projects a 65% increase in energy consumption in the 2010-2050 period, driven by continued population and economic growth. With no fundamental change in current policies, fossil fuels are expected to retain a large market share as their market price is expected, to stay below the alternative fuels for the vast majority of applications. In climate policy scenarios, the inclusion of a carbon price leads to a an increased share for of different technologies and resources, such as carbon-capture and storage, nuclear power and renewables; see Figure 2.4.''
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| [[File:009x img13.png|thumb|500px|left|alt=Figure2_IF_summary|link=Trends in world energy use, with and without climate policy.|Trends in world energy use, with and without climate policy.]]
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| ====Food consumption and agriculture====
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| Demand for and production of agricultural products are modeled by soft-coupled agro-economic models, mostly [[MAGNET model|MAGNET]] and [[IMPACT model|IMPACT]]. With the MAGNET model information can be exchanged in two ways: the IMAGE model supplies the MAGNET model with information on land-supply curves by region (using the IMAGE crop model). And MAGNET provides information on future agricultural production levels and intensity by region, matching regional demands through trade. The MAGNET model assesses the production of agricultural products on the basis of different combinations of primary production factors (land, labour, capital and natural resources) and intermediate production factors. For the livestock sector, IMAGE makes scenario-specific assumptions about the breakdown of livestock production over different systems. A key purpose of the agro-economy model is to determine regional production levels and the associated yields, taking changes in growing conditions into account. In that context, it should be noted that an increase in demand for agricultural production can be met via increased production based on a land expansion (using the regional land supply curves) and/or intensification of land use: increase in yields.
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| All baseline scenarios, including the [[Roads from Rio+20 (2012)|Rio+20]] baseline, project a strong increase in agricultural production, driven by population growth and changes in dietary patterns in line with increasing per capita income. Consistent with the historical trends, most of the increase will be met through on average higher production per hectare (intensification). Still, in the Rio+20 baseline a further slow expansion of the agricultural area in developing countries can be observed, especially for crops and much less for pastures. Alternative scenarios explore ways to mitigate this agricultural expansion, looking into the influence of enhanced yield increase, reduction of post-harvest losses or dietary changes.
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| ===Interaction between the human system and environmental system: land allocation and emissions=== | |
| There are several ways by which the human system directly influences the earth system. Land allocation and atmospheric emissions form two of the most important factors, others include water extraction, and water and soil pollution. The two main factors are described in IMAGE in separate sub-models.
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| See the background information on [[Downscaling|Downscaling as a tool to link different geographical scales]].
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| ====Land allocation====
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| Using the demand for land to produce agricultural food products and bio-energy, the Land Allocation model determines at a 5 min x 5 min grid where this production occurs using a set of allocation rules. For instance, grid cells with a high potential to produce agricultural products (in terms of climate, soil types), that are near water (for transport and irrigation) and near to existing urban or agricultural areas are considered to be most suitable for agricultural production. In the model these rules in combination with regional preferences for different types of production systems, determined from historical calibration, are used to allocated land use to the grid.
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| ''As observed in other baseline scenarios, in the Rio+20 baseline the expansion of agricultural production in tropical regions leads to a loss of natural ecosystems, and an associated loss of biodiversity. In fact, most of the expansion is projected to occur in highly productive ecosystems near existing agricultural areas, thus including tropical forests and woodland, other high nature value savanna and grassland area. At the same time, in the temperate zones there is actually a contraction of the agricultural area. Here, the grid cells least suitable for production potential are abandoned. The resulting changes in agricultural area are depicted in Figure 2.5.''
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| ====Emissions====
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| Emissions are described in IMAGE as a function of activity levels in the energy system, in industry, in agriculture, and of the assumed abatement actions ([[Emissions]]). The model describes the emissions of all major greenhouse gases, and many air pollutants (calibrated to current international emission inventories). In some cases, the calculation of emissions is done using detailed process representation (e.g. emissions from cultivated land and land-cover change) but, in most cases, exogenous emission factors are used. The development of emission factors over time has been estimated based on relevant hypothesis, sometimes assuming constant emission factors, but often assuming that emission factors decrease over time along with economic development (consistent with the so-called environmental Kuznets curve). Emissions factors of greenhouse gases reflect estimates per region, sector and gas from the [[FAIR model]] ([[Climate policy]]).
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| ''In the Rio+20 baseline, increasing energy and agricultural production levels lead to an increase of associated greenhouse gas emissions. For air pollutants, the emission trends are more diverse: a decrease is projected in high-income countries, as emission factors drop faster than activity levels increase). In most developing country regions, however, increasing energy production is projected to be associated with more air pollution. The model can also be used to design scenarios that are consistent with different climate targets. For reaching the 2oC target, global [[GHG]] emissions would need to be reduced by around 50% in 2050.''
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| [[File:013x img13.png|thumb|500px|left|alt=Global geenhouse gas emissions and temperature changes|link=Changes in emissions under baseline (trend scenario) and 2ºC scenario (challenge pathways)|Changes in emissions under baseline (trend scenario) and 2ºC scenario (challenge pathways)]]
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| ===The earth system===
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| ====Land cover and carbon cycle====
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| A key component of the IMAGE model is formed by the detailed characterization of land cover and the associated impacts on the carbon cycle. This sub-model determines the productivity at the level of grids cells for both natural ecosystems and crops on the basis of so-called plant functional types. Key inputs to determine the productivity include climate conditions, soil types and assumed technology/management levels. The model iterates with the agricultural production components described earlier as it provides input on potential productivity, while the land used for agriculture and forestry forms a key input here. The changes in land cover, driven by changes in land use or climate, obviously have major consequences for the carbon cycle at grid cell level. In addition to these terrestrial carbon fluxes, the model also describes the uptake of carbon by oceans.
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| ''The land-use trends in the Rio+20 baseline described earlier lead to a net expansion of agricultural land, and thus a net loss of forest,(in particular tropical). These deforestation trends imply that the terrestrial system is a net source of carbon over the next decades. The net emissions from land, however, decline over time as a result of regrowth in the temperate zone. As a result, in the second half of the 21st century there is even a small net uptake. The emission from the energy system imply that all-in-all there is a rapid increase in atmospheric CO2 concentration.''
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| ====Nutrient cycle====
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| The Global Nutrient Model describes the fate of nitrogen (N) and phosphorus (P) emerging from concentrated point sources such as human settlements, and from dispersed or non-point sources such as agricultural and natural land. Through rivers and lakes, the nutrient surplus eventually enters coastal water bodies. Key drivers that demine the nutrient emissions of concentrated and point sources include the agricultural production with its fertilizer application, urban and rural population by sanitation system and level of wastewater treatment. For example, the model calculates the annual surface nitrogen balance from inputs such as biological nitrogen fixation, atmospheric nitrogen deposition and the application of synthetic nitrogen fertilizer and animal manure, and outputs such as nitrogen removal from the field by crop harvesting, hay and grass-cutting and grazing. The outflow of nutrients from the soil in combination with emissions from point sources and direct atmospheric deposition also determine the loading of nutrients to the surface water.
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| ''In the Rio+20 scenario, further increase of the global population and growth of agricultural production adds to pressures on the nutrient cycle. While increasing waste water treatment and improved agricultural practices mitigate some of the increased nutrient loading, these processes are insufficient to offset the increased fertilizer application to sustain intense agriculture. This leads to a significant further imbalance of both the nitrogen and phosphorus cycle, with consequences for water quality in rivers, lakes and coastal seas.''
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| ====Atmospheric composition and climate change====
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| Data on emissions of greenhouse gases and air pollutants are used in IMAGE to calculate changes in concentrations of greenhouse gases, ozone precursors and species involved in aerosol formation at a global scale ([[Atmospheric composition and climate]]). Climatic change is calculated as global mean temperature changes using a slightly adapted version of the [[MAGICC]]6 climate model. Climatic change does not manifest itself uniformly over the globe, and patterns of temperature and precipitation are uncertain and differ between complex climate models. Therefore, changes in temperature and precipitation in each 0.5 x 0.5 degree grid cell are derived from the global mean temperature using a pattern-scaling approach. The model accounts for important feedback mechanisms related to changing climate, notably growth characteristics in the crop model, carbon dioxide concentrations (carbon fertilization) and land cover (biome types).
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| ''In the Rio+20 baseline, increasing fossil fuel use leads to increasing [[GHG]] emissions and air pollution levels. For the 2010–2050 period, GHG emissions are projected to increase by about 60%. As a result global temperature is expected to increase to around 4°C above pre-industrial levels by 2100, most likely passing the 2°C level before 2050; see Figure 2.7.''
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| ====Water==== | | ===Temporal scale=== |
| The [[LPJmL model]] used for a description of vegetation and carbon cycle also includes a global hydrological model ([[Hydrological cycle]]). With this coupled hydrological model, IMAGE scenarios now also capture future changes in water availability, agricultural water use and water shortage.. Water demand for irrigated agriculture is calculated inLPJmL, based on requirements for evapotranspiration for the crop types grown on irrigated land. Water demand for other sectors (households, manufacturing, electricity and livestock) is currently adopted from exogenous scenarios. The most frequently used are WaterGap projections of the University of Kassel, adjusted to remain consistent with projections for households, livestock numbers, industrial value added, and for thermal electricity production as projected with IMAGE-TIMER. | | The Human system and the Earth system each run at annual or five-year time steps focusing on long-term trends to capture inertia aspects of global environmental issues. In some IMAGE model components, shorter time steps are also used, for example, in water, crop and vegetation modelling, and in electricity supply. The model is run up to 2050 or 2100 depending on the issues under consideration. For instance, a longer time horizon is often used for climate change (see [[Applications]]). IMAGE also runs over the historical period 1971-2005 in order to test model dynamics against key historical trends. |
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| ''The increases projected in agricultural , energy and industry production households lead to an increasing demand for water. At the same time, climate change also impacts the water cycle. While overall climate change is projected to lead to more precipitation, geographical patterns show changes to both dryer and wetter gridcells. As a result, the water balance improves in some regions, while it deteriorates in other regions. The pattern of these changes is very uncertain. In combination with increased demand, however, the number of people confronted with serious water stress is projected to increase significantly.''
| | ==Modular structure== |
| | IMAGE has been set-up as an integrated assessment framework in a modular structure, with some components linked directly to the model code of IMAGE, and others connected through soft links (the models run independently with data exchange via data files). This architecture provides more flexibility to develop components separately and to perform sensitivity analyses, recognising that feedback may not always be strong enough to warrant full integration. For example, the various components of the Earth system are fully linked on a daily or annual basis. However, components of the Human system, such as the TIMER energy model and the agro-economic model MAGNET, are linked via a soft link, and can also be run independently. |
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| [[File:015g img13.png|thumb|400px|left|alt=Framework summary figure 5.|link=Biodiversity impacts (baseline and alternative scenarios)|Biodiversity impacts (baseline and alternative scenarios)]]
| | The IMAGE core model comprises most parts of the Human system and the Earth system, including the energy system, land-use and plant growth, carbon and water cycle model LPJmL. The IMAGE framework includes soft-linked models, such as the agro-economic model MAGNET, and PBL policy and impact models, such as FAIR (climate policy), GLOBIO (biodiversity), GLOFRIS (flood risks) and GISMO (human development). |
| === Impacts of environmental change===
| | See [[Computer models overview]]. |
| ====Biodiversity loss==== | | <BlockQuote> |
| Biodiversity loss is described in the impact model [[GLOBIO model|GLOBIO]] in the form of calculated changes in MSA (mean species abundance). The MSA indicator maps the effect of a suite of direct and indirect drivers of biodiversity loss provided by IMAGE. GLOBIO 3 takes into account the impacts of climate, land-use change, ecosystem fragmentation, expansion of infrastructure, disturbance of habitats, and acid and reactive nitrogen deposition ([[Terrestrial biodiversity]]). Their compound effect on biodiversity is computed using the GLOBIO3 model for terrestrial ecosystems. As the IMAGE and the GLOBIO3 models are spatially explicit, the impacts on MSA can be analysed by region, main biome and pressure factor. Recently, a similar model was developed to map biodiversity in fresh water; see [[Aquatic biodiversity]].
| | ===The Rio+20 study=== |
| | Using the IMAGE model, the PBL study Rio+20 ([[PBL, 2012]]) assessed pathways to achieve ambitious global sustainability targets in 2050, including limiting climate change to 2 °C, stabilising biodiversity loss and providing full access to energy, water and food. The baseline scenario assessed possible development without major changes in current policies. Three alternative scenarios assessed possible routes to achieving the sustainability targets. The first scenario (Global Technology) was directed to achieving the target mainly through large-scale introduction of advanced technologies. The second scenario (Decentralised Solutions) assessed achieving the long-term targets by introducing small-scale technologies and emphasising local-scale solutions. The third scenario (Consumption Change) focused on the role of lifestyle changes in achieving the targets. In this chapter, the [[PBL, 2012|Rio+20]] study is used to illustrate potential assessments with IMAGE. |
| | </BlockQuote> |
| | ''{{#show:PBL, 2012|? HasFormattedReference}}'' |
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| ''For biodiversity, a further decline is projected in the Rio+20 baseline at an almost unchanged rate as in the past century. While historically, habitat loss has been the most important driver of biodiversity loss, in the future decades climate change, forestry and infrastructure expansion are projected to become the more important pressure factors.''
| | In the subsequent pages of the summary, the various components of the IMAGE system are described briefly, and in further detail in the model component pages. Results from the Rio+20 study (PBL, 2012, see above) and some other studies are used in this chapter to illustrate the main model output. |
| | | </div> |
| ====Human development====
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| Global environmental change impacts human development in many ways. Via the link to the [[GISMO model]], the IMAGE framework describes impacts on human health, and the achievement of human development goals such as the [[MDG|MDGs]]. The health model describes the burden of disease per gender and age ([[Human development]]). The GISMO model allows to describe health impacts from communicable diseases, but also from air pollution and undernourishment, and the interactions between these factors. The model is thus able to put the impacts of global environmental change factors in perspective of other factors determining human health.
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| Hunger, defined as the proportion of the population with food consumption below the minimum dietary energy requirement, is determined using an assumed distribution of food intake over individuals on the basis of the mean food availability per capita (from other parts of IMAGE) and a coefficient of variation. Water supply levels and sanitation were modelled separately for urban and rural populations by applying regressions based on available data for 1990 and 2000. The explanatory variables include GDP per capita, urbanisation rate and population density.
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| ''As far as global hunger is concerned, the Rio+20 scenario shows some clear improvement, in contrast to the last few decades. This improvement is a consequence of a rapid income growth in low-income regions and leveling-off of population growth.''
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| [[File:017x img13.png|thumb|500px|right|alt=Human development indicators in baseline scenario|Human development indicators]]
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| ====Other impacts====
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| Other impacts calculated by the IMAGE framework are not described here, including flood risks ([[Flood risks]]), land degradation ([[Soil degradation]]) and ecological goods and services ([[Ecosystem goods and services]]).
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