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{{FrameworkSummaryPartTemplate
{{FrameworkSummaryPartTemplate
|PageLabel=Interaction Human - Earth system
|PageLabel=Impacts
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|Sequence=7
|Description=<h2>Interaction between the Human system and the Earth system</h2>
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''Land cover/land use''  and ''emissions'' comprise the interaction.
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<h2>Impacts of environmental change</h2>
The Human system influences the Earth system in various ways, such as land use and atmospheric emissions, but also water extraction, and water and soil pollution. The representation of key factors of land use and atmospheric emissions in the IMAGE model are discussed below.
Several impacts of global environmental change are calculated in IMAGE (Component [[Impacts]]). Here we describe biodiversity loss and impacts on human development.
 
===Land cover and land use ===
Using demand for agricultural products, including food, feed and bioenergy, the Land-use allocation model locates production areas on a 5 x 5 minute grid (Component [[Agricultural systems]]). A region-specific regression based suitability assessment and an iterative allocation procedure are used. Alternatively, the land-use model can also integrate CLUMondo (using a more complex allocation procedure). In most regions, the main determinants of suitability for agricultural expansion are population density, accessibility, topography, and agricultural productivity. In the model, suitability is used in combination with regional preferences for different types of production systems (determined from historical calibration) to allocate land use to the grid. In addition, the IMAGE land use and land cover module (Component [[Land cover and use]]) collects and combines information from the agricultural system and the Earth system to provide maps of land-use and land-cover parameters, including fertiliser input, livestock densities, rain-fed and irrigated crop fractions, bioenergy crops, and forest management.


===Biodiversity loss ===
Biodiversity loss is assessed by the impact model GLOBIO (Component [[Terrestrial biodiversity]]) as calculated changes in mean species abundance ({{abbrTemplate|MSA}}). The MSA indicator maps the effect of direct and indirect drivers of biodiversity loss provided by IMAGE, including climate, land-use change, ecosystem fragmentation, expansion of infrastructure, disturbance of habitats, and acid and reactive nitrogen deposition. Their compound effect on biodiversity is computed with the [[GLOBIO model|GLOBIO3 model]] for terrestrial ecosystems. As IMAGE and GLOBIO3 models are spatially explicit, the impacts on MSA can be analysed on a grid by region, main biome and pressure factor. A similar model has been developed to map biodiversity in fresh water (Component [[Aquatic biodiversity]]).
<BlockQuote>
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Example: In most baseline scenarios, increased agricultural production in tropical regions leads to loss of natural ecosystems and associated biodiversity loss. Most expansion is projected to occur in highly productive ecosystems close to agricultural areas, including tropical forests and woodland, and other high nature value savannah and grassland areas. The agricultural area is contracting in temperate zones and the grid cells least suitable for production potential are abandoned. The resulting changes in land use are depicted in Figure below.
Example: A further decline in biodiversity is projected in the Rio+20 baseline at an almost historical rate. While historically habitat loss has been the key driver of biodiversity loss, more important pressures in the coming decades are projected to be climate change, forestry and infrastructure (the figure below).
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{{DisplayFigureLeftOptimalTemplate|Baseline figure AS}}
{{DisplayFigureLeftOptimalTemplate|Policy intervention figure Land and biodiversity policies II}}
===Emissions===
===Human development===
In IMAGE, emissions are described as a function of activity levels in the energy system, in industry, in agriculture and land-cover and land-use change, and they are also influenced by assumed abatement actions (Component [[Emissions]]). The model describes emissions of major greenhouse gases, and many air pollutants, calibrated to current international emission inventories. In some cases, the emission calculation uses detailed process representation on a grid (e.g., emissions from cultivated land and land-cover change) but in most cases, exogenous emission factors are used. Change in emission factors over time is estimated according to the storyline, sometimes assuming constant emission factors, but often assuming emission factors decrease over time along with economic development (consistent with the environmental Kuznets curve). Abatement of greenhouse gas emissions reflects estimates per region, sector and gas often optimised in the FAIR model (Component [[Climate policy]]).
Changes in the global environmental impact on 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 Millennium Development Goals (MDGs; see Component [[Human development]]). The health module describes the burden of disease per gender and age, including communicable diseases, and also health impacts of air pollution and undernourishment, and interactions between these factors.  


<BlockQuote>
The model puts the impacts of global environmental change in perspective of other factors determining human health. For instance, hunger is defined as the proportion of the population with food consumption below the minimum dietary energy requirement. The model determined hunger on the basis of distribution of food intake over individuals calculated on the mean food availability per capita (from other parts of IMAGE), and a coefficient of variation.
Example: In the Rio+20 baseline, increasing energy and agricultural production levels lead to an increase of associated greenhouse gas emissions (Figure below). 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. However, in most developing country regions, increasing energy production is projected to be associated with more air pollution. In the policy scenarios, the target to keep global mean temperature change below 2 °C requires global greenhouse gas emissions to be reduced by about 50% in 2050. This is achieved in the model by structural changes in the energy system and by changes in emission and abatement factors.
Water supply levels and sanitation are modelled separately for urban and rural populations by applying an empirical regression model, depending on per capita GDP, urbanisation rate and population density.
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{{DisplayFigureLeftOptimalTemplate|Figure4 IF}}
Example: With regard to global hunger, the Rio+20 scenario shows improvement compared to the last few decades. This improvement is a consequence of rapid income growth in low-income regions and levelling off of population growth (the figure below). The baseline scenario also shows a decline in population without access to safe drinking water, sanitation and modern energy. In all cases, the improvement is too slow compared to policy ambitions.
[[Downscaling tool|Downscaling]] is used  as a tool to link different geographical scales
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{{DisplayFigureLeftOptimalTemplate|Figure6 IMAGE framework summary}}
===Other impacts===
Other impacts calculated in the IMAGE framework using separate impact models include flood risks (Component [[Flood risks]]), land degradation (Component [[Land degradation]]) and ecosystem services (Component [[Ecosystem services]]). Many impacts of global environmental change are an integral part of the modules in the Human system and the Earth system, such as water stress and climate change impact on crop yields (Component [[Impacts]]).
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Latest revision as of 15:48, 21 October 2021

Parts of IMAGE framework summary

  1. Introduction page
  2. Introduction model description
  3. Drivers
  4. The Human system
  5. Interaction Human - Earth system
  6. Earth system
  7. Impacts
  8. Policy issues
  9. Data, uncertainty and limitations
  10. Overview of references
Projects/Applications
Relevant overviews
Key publications


Impacts of environmental change

Several impacts of global environmental change are calculated in IMAGE (Component Impacts). Here we describe biodiversity loss and impacts on human development.

Biodiversity loss

Biodiversity loss is assessed by the impact model GLOBIO (Component Terrestrial biodiversity) as calculated changes in mean species abundance (MSA). The MSA indicator maps the effect of direct and indirect drivers of biodiversity loss provided by IMAGE, including climate, land-use change, ecosystem fragmentation, expansion of infrastructure, disturbance of habitats, and acid and reactive nitrogen deposition. Their compound effect on biodiversity is computed with the GLOBIO3 model for terrestrial ecosystems. As IMAGE and GLOBIO3 models are spatially explicit, the impacts on MSA can be analysed on a grid by region, main biome and pressure factor. A similar model has been developed to map biodiversity in fresh water (Component Aquatic biodiversity).

Example: A further decline in biodiversity is projected in the Rio+20 baseline at an almost historical rate. While historically habitat loss has been the key driver of biodiversity loss, more important pressures in the coming decades are projected to be climate change, forestry and infrastructure (the figure below).


Global biodiversity under baseline and sustainability scenarios to prevent biodiversity loss
Biodiversity is projected to decline further in the baseline scenario (left). Various measures in the demand system, the production system and in land-use regulation contribute to reducing biodiversity loss in the sustainability scenarios (right).

Human development

Changes in the global environmental impact on 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 Millennium Development Goals (MDGs; see Component Human development). The health module describes the burden of disease per gender and age, including communicable diseases, and also health impacts of air pollution and undernourishment, and interactions between these factors.

The model puts the impacts of global environmental change in perspective of other factors determining human health. For instance, hunger is defined as the proportion of the population with food consumption below the minimum dietary energy requirement. The model determined hunger on the basis of distribution of food intake over individuals calculated on the mean food availability per capita (from other parts of IMAGE), and a coefficient of variation. Water supply levels and sanitation are modelled separately for urban and rural populations by applying an empirical regression model, depending on per capita GDP, urbanisation rate and population density.

Example: With regard to global hunger, the Rio+20 scenario shows improvement compared to the last few decades. This improvement is a consequence of rapid income growth in low-income regions and levelling off of population growth (the figure below). The baseline scenario also shows a decline in population without access to safe drinking water, sanitation and modern energy. In all cases, the improvement is too slow compared to policy ambitions.


Human development indicators in baseline scenario
Human development indicators

Other impacts

Other impacts calculated in the IMAGE framework using separate impact models include flood risks (Component Flood risks), land degradation (Component Land degradation) and ecosystem services (Component Ecosystem services). Many impacts of global environmental change are an integral part of the modules in the Human system and the Earth system, such as water stress and climate change impact on crop yields (Component Impacts).

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