Technical annex

The quantitative results presented in this chapter were developed to illustrate the narrative scenarios and to provide an indication of their likely environmental implications. These results were derived using a range of analytical tools, in consultation with regional experts. They emphasize general trends and differences between scenarios, rather than precise levels of impact. This technical annex outlines the scenario development process followed for GEO-3, and presents summary descriptions of the analytical tools employed, and the indicators presented in the chapter. More extensive information, including more detailed data tables and figures, is presented in Raskin and Kemp-Benedict (2002) and in a separate technical report (RIVM and UNEP, in press).

The scenario development process

Drawing from previous work of the Global Scenario Group (see Raskin and Kemp-Benedict 2002), four global storylines were designed by a core scenario team of global and regional experts. An initial quantification for a small set of indicators was prepared at the level of the GEO sub-regions. Teams in each of the seven major GEO regions then elaborated the storylines at regional level and provided input to the quantitative analyses, particularly with respect to key driving forces. The results of the regional efforts were used to refine the global narratives and to undertake the subsequent quantitative analyses associated with the scenario narratives. Further refinement of both the narratives and the quantitative analyses was achieved through an iterative process involving the core scenario team and the modelling groups. During the development process the work underwent two formal rounds of review and was scrutinized at a special workshop with a group of scenario experts from around the world.

Quantitative analytical tools

AIM (Asian Pacific Integrated Model) is an integrated environment-economy model developed by the National Institute for Environmental Studies (NIES) and Kyoto University, Japan, to assess future scenarios of socio-economic development and environmental change in Asia and the Pacific as well as at global level. The set of AIM modules was developed primarily for assessing effects of climate change policies and climate change impacts, but it can also be applied to other environmental fields such as air pollution, water resources, land use change and ecosystem assessment. With externally derived socioeconomic data as input, the model estimates future environmental conditions of 42 countries in Asia and the Pacific. The ecosystem module uses a latitude-longitude grid with a spatial resolution of 2.5 x 2.5 minutes to facilitate policy analyses. The model has been extensively reviewed and frequently used by the IPCC. More information about AIM is available at

GLOBIO (Global methodology for mapping human impacts on the biosphere) is a simple transparent global model developed under the GLOBIO project, coordinated by the Norwegian Institute for Nature Research (NINA), UNEP-GRIDArendal, UNEP-WCMC and UNEP/DEWA. It is used to visualize, at a scale of 1 x 1 km, the cumulative impacts on biodiversity and ecosystem function of growth in human resource demand and associated infrastructure development. The model provides a statistical risk assessment of probability of human impacts using buffer zones from infrastructure that vary with type of human activity and density of infrastructure, region, vegetation, climate and sensitivity of species and ecosystems. Satellite imagery is used to derive overviews of cumulative impacts of ongoing development. Future scenario situations are derived from data on existing infrastructure, historic growth rates of infrastructure, availability of petroleum and mineral reserves, vegetation cover, population density, distance to coast and projected development. More information on GLOBIO can be found at and in UNEP 2001.

IMAGE 2.2 (Integrated Model to Assess the Global Environment) is a dynamic integrated assessment model for global change developed by the National Institute for Public Health and the Environment (RIVM), The Netherlands. IMAGE quantifies the consequences of different future developments for a broad range of environmental issues. Driving forces are modelled for 17 world regions, partly via the WorldScan general equilibrium model. Impacts are calculated over long time frames (typically 100 years), and with a high spatial resolution (0.5 x 0.5 degree latitude-longitude grid). Long historical series are used to calibrate the model and place future developments in perspective. The model has been extensively reviewed and frequently used by the IPCC. More information about IMAGE is available at and in Alcamo and others (1998) and IMAGE Team (2001a and 2001b).

PoleStar is a comprehensive and flexible software tool for sustainability studies developed by the Stockholm Environment Institute (SEI), Boston Centre, USA. Rather than being a rigid model, the software provides an adaptable accounting framework and modelling environment for mounting economic, resource and environmental information and for examining alternative development scenarios. PoleStar has been used in a number of international assessments, including quantification of the scenarios of the Global Scenario Group (GSG). Technical documentation on PoleStar and details of the GSG scenarios can be found online at and

WaterGAP 2.1 model (Water — Global Assessment and Prognosis) is the first global model that computes both water availability and water use on the river basin scale. WaterGAP, developed by the Center for Environmental Systems Research (CESR), University of Kassel, Germany, has two main components, a Global Hydrology Model and a Global Water Use Model. The Global Hydrology Model simulates the characteristic macro-scale behaviour of the terrestrial water cycle to estimate water availability. The Global Water Use Model consists of three main sub-models that compute water use for the domestic, industry and agriculture sectors. All computations cover the entire land surface of the globe on a 0.5 x 0.5 degree latitude-longitude grid. A global drainage direction map then allows the analysis of the water resources situation in all large drainage basins worldwide. For a more detailed description of the model see Alcamo and others (2000) and Center for Environmental Systems Research (2002).

Note: Any discrepancies between the GEO-3 regions and sub-regions and the regions represented in data sets used to generate charts and other figures are noted with the individual graphics.


Variables charted or mapped in the Outlook section of GEO-3 are (in alphabetical order) as follows.

Area with high risk of water-induced soil degradation indicates the land area that is at high risk from water erosion under a specific form of land use. The sensitivity to water erosion is computed from the soil and terrain characteristics, rainfall erosivity and land cover. In global terms, water erosion is the most serious form of land degradation and it is irreversible. Whether erosion actually occurs depends on implementation of soil conservation measures at farm and landscape levels.

Source: IMAGE 2.2; Hootsmans and others 2001. For definition of erosion risk see UNEP/ISRIC 1991

Atmospheric concentrations of carbon dioxide presents the global CO2 concentration in the atmosphere as the net balance between CO2 emissions from fossil fuel combustion, industrial production, deforestation and CO2 uptake by mature and regrowing vegetation, and by the oceans.

Source: AIM for Asia and the Pacific; IMAGE 2.2 for other regions and global chart; De Vries and others 2001

Carbon dioxide emissions covers emissions from land use, industrial production and energy use. Emissions from industrial sources include the emissions from non-energy use of fossil fuels (mainly feedstocks) and industrial activities. Land-use sources of carbon dioxide include burning forest biomass (after deforestation) and fuelwood, and releases by waste processes after disposal of consumer goods such as paper, furniture and building materials.

Source: AIM for Asia and the Pacific; IMAGE 2.2 for other regions and global chart; De Vries and others 2001

Change in average temperature, 2002–32. Given the uncertainties in the regional distribution of temperature increase, this graph is based on results from four different Global Circulation Models (GCMs) in combination with IMAGE 2.2. For each of the GCMs, the spatially differentiated pattern of temperature change for a reference scenario (1 per cent per annum growth in equivalent greenhouse gas concentration from 1990 onwards) was taken, north of 66°N and south of 66°S latitude. This pattern was then scaled on the basis of global average temperature changes for each of the scenarios as calculated by IMAGE 2.2. Finally, the average temperature change for the Arctic and Antarctic was calculated. The GCMs used are HadCM2, ECHAM4, CSIRO Mk2 and CGCM1. The GCM results were taken from the IPCC Data Distribution Centre for Climate Change and Related Scenarios for Impacts Assessment (IPCC-DCC 1999).

Source: four GCMs and IMAGE 2.2

Change in selected pressures on natural ecosystems 2002–32. For the ecosystem quality component, see the explanation of the Natural Capital Index. Values for the cumulative pressures were derived as described under Natural Capital Index. The maps show the relative increase or decrease in pressure between 2002 and 2032. ‘No change’ means less than 10 per cent change in pressure over the scenario period; small increase or decrease means between 10 and 50 per cent change; substantial increase or decrease means 50 to 100 per cent change; strong increase means more than doubling of pressure. Areas which switch between natural and domesticated land uses are recorded separately.

Source: IMAGE 2.2

Ecosystems impacted by infrastructure expansion reflects the probability of human impact on biodiversity based on distances to different types of infrastructure, such as roads, dams and other utilities. Impact zones vary according to climate, vegetation and political region.

Source: GLOBIO

Energy-related carbon dioxide emissions are total CO2 emissions from all energy uses.

Source: AIM for Asia and the Pacific; IMAGE 2.2 for other regions and global chart; De Vries and others 2001

Energy-related nitrogen oxide emissions are total NOx emissions from all energy uses.

Source: AIM for Asia and the Pacific; IMAGE 2.2 for other regions and global chart; De Vries and others 2001

Energy-related sulphur dioxide emissions are total SO2 emissions from all energy uses.

Source: AIM for Asia and the Pacific; IMAGE 2.2 for other regions and global chart; De Vries and others 2001

Extent of built-up areas includes land cleared and altered for businesses, residences, roads, parking lots, parks, landfills, burial grounds and other similar uses. A combination of different sources was used to arrive at regional estimates for built-up land.

Source: Polestar

Global temperature change is the average increase of global temperature, expressed in degrees per ten years. The rate of temperature change is important since sensitive ecosystems may not be able to adapt at high rates. Research has shown that, at rates larger than 0.1°C per ten years, extensive damage to ecosystems is probable (Vellinga and Swart 1991).

Source: IMAGE 2.2

Land area impacted by infrastructure expansion. See note under Ecosystems impacted by infrastructure expansion, above.

Source: GLOBIO

Municipal solid waste generation is an index of solid waste generation from household and commercial sources. Total solid waste generation in the Asia and Pacific region in the year 1995 has been allocated an index value of 1. Index values for 2032 under each scenario relate to the index for the base year.

Source: AIM

Natural Capital Index is a measure for terrestrial and aquatic biodiversity of natural ecosystems and agricultural land. The index is calculated as the product of habitat area times ecosystem quality, expressed as a percentage. The habitat area is taken as the percentage of remaining surface of natural ecosystems. Ecosystem quality is approximated from four pressure factors that are considered to have a major influence on biodiversity and for which global data are available. Based on literature, for each pressure factor a range is defined from no effect to complete deterioration of habitats if the maximum value is exceeded over a long time. Pressure factors are population density (min-max: 10–150 persons per km2), primary energy use (min-max: 0.5–100 peta Joules per km2), rate of temperature change (min-max: 0.2–2.0°C in a 20 year period) and restoration time for exhausted agricultural land, livestock area and deforested zones in re-conversion towards natural, lowimpacted ecosystems (min-max: 100–0 restoration time). The proxy for ecosystem quality is a reversed function of these pressures, calculated as a percentage of the low-impacted baseline state. The higher the pressure, the lower the quality. Finally, the percentages for habitat area and quality are multiplied, resulting in a pressure-based Natural Capital Index. The calculations were carried out on a detailed latitude-longitude grid, before aggregation to subregions and regions.

Source: IMAGE 2.2; ten Brink 2000 and 2001, ten Brink and others 2000

Natural forest, excluding regrowth is the area of mature forests (excluding plantations) that has not been harvested using clear cutting since 1972.

Source: IMAGE 2.2

Potential increase in nitrogen loading on coastal ecosystems. At the sub-regional aggregation level employed in GEO, nitrogen loading can be taken as a proxy for a wider range of land-based pollution on the coastal ecosystems. The potential growth of the subregional nitrogen load under each of the scenarios has been estimated by rating the change in determinants such as sewage inputs and level of treatment, fertilizer use and airborne emissions, on a ten-point scale.

Source: IMAGE 2.2; van Drecht and others (in press)

Percentage of 2002 cropland that is severely degraded by 2032 represents cropland so degraded that it is of little value for production. The degraded area is expressed as a percentage of land that was under crops in 2002.

Source: Polestar

Population living in areas with severe water stress. Water stress is measured by the ‘withdrawal-to-availability’ ratio (wta-ratio). This ratio captures how much of the average annual renewable water resources of a river basin are withdrawn for human purposes in the domestic, industry and agricultural sectors. In principle, the higher the ratio, the more intensively the water in a river is used; this reduces either water quantity or water quality or even both for downstream users. Commonly it is assumed that when the wtaratio in a river basin exceeds 0.4, or 40 per cent, the river basin experiences severe water stress.

Source: WaterGAP 2.1

Population living with hunger refers to the incidence of chronic under-nutrition in developing and transitional regions (using 1995 data based on FAO estimates), the incidence of food insecurity in the United States and estimates for other countries based on income distribution. Hunger patterns are determined in the scenarios by changes in income, income distribution and population.

Source: PoleStar