Drivers/Scenario drivers: Difference between revisions
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|Description={{DisplayFigureTemplate|Flowchart D}} | |Description={{DisplayFigureTemplate|Flowchart D}} | ||
<h2>Scenario drivers</h2> | <h2>Scenario drivers</h2> | ||
On the basis of how the world may develop in the longer term, the following six key scenario drivers are distinguished: demography, economy, culture and lifestyle, natural resource availability, technological development, and policy and governance, see | On the basis of how the world may develop in the longer term, the following six key scenario drivers are distinguished: demography, economy, culture and lifestyle, natural resource availability, technological development, and policy and governance, see flowchart. The future direction of these drivers is often inferred from the storyline or narrative, which may range from brief to very detailed. The storyline describes the following scenario types and functions: | ||
*reference projection with no new policies (OECD, 2008); | *reference projection with no new policies ([[OECD, 2008]]); | ||
*single ‘best guess’ projection combining past trends with assumptions on how they may develop ([[PBL, 2010]]; [[PBL, 2011]]); | *single ‘best guess’ projection combining past trends with assumptions on how they may develop ([[PBL, 2010]]; [[PBL, 2011]]); | ||
*multiple contrasting scenarios that span a range of uncertainties about the future ([[IPCC, 2000]]; [[MA, 2005]]; [[Moss, 2010]]; [[IIASA, 2013]]); | *multiple contrasting scenarios that span a range of uncertainties about the future ([[IPCC, 2000]]; [[MA, 2005]]; [[Moss et al.,, 2010]]; [[IIASA, 2013]]); | ||
*specific or broad policy scenarios directed to improving future outcomes ([[OECD, 2012]]; [[PBL, 2012]]). | *specific or broad policy scenarios directed to improving future outcomes ([[OECD, 2012]]; [[PBL, 2012]]). | ||
===Demography=== | ===Demography=== | ||
The future state of the world depends on the population because total demand for goods and services equals the number of people times demand per capita. | The future state of the world depends on the population because total demand for goods and services equals the number of people times demand per capita. | ||
Most population projections used as input to the IMAGE model have been adopted from published sources, such as data from the United Nations (UN, 2013) and projections by the International Institute for Applied Systems Analysis (IIASA) (Lutz and KC, 2010). Behind these numerical projections are economic, technical, educational and policy assumptions that determine the estimated future population as the net outcome of fertility and mortality, adjusted for migration flows. This has provided internally consistent, overall population scenarios on the basis of underlying demographic trends. | |||
In addition to total number of people, the population is broken down into gender, income classes, urban and rural, and educational level. These attributes are relevant for issues such as consumption preferences and patterns, and access to goods and services. Using a downscaling procedure (Van Vuuren et al., 2007b), national and regional population can be projected at grid level to account for trends in urbanisation and migration within countries and regions. | Most population projections used as input to the IMAGE model have been adopted from published sources, such as data from the United Nations ([[UN, 2013]]) and projections by the International Institute for Applied Systems Analysis ({{abbrTemplate|IIASA}}) ([[Lutz and KC, 2010]]). Behind these numerical projections are economic, technical, educational and policy assumptions that determine the estimated future population as the net outcome of fertility and mortality, adjusted for migration flows. This has provided internally consistent, overall population scenarios on the basis of underlying demographic trends. | ||
Population data are used in energy and agricultural economics modelling, and in other IMAGE modules, such as water stress, nutrients, flood risks and human health. | |||
In addition to total number of people, the population is broken down into gender, income classes, urban and rural, and educational level. These attributes are relevant for issues such as consumption preferences and patterns, and access to goods and services. Using a downscaling procedure ([[Van Vuuren et al., 2007b]]), national and regional population can be projected at grid level to account for trends in urbanisation and migration within countries and regions. | |||
Population data are used in energy and agricultural economics modelling, and in other IMAGE modules, such as [[Water|water stress]], [[Nutrients|nutrients]], {{Flood Risks|flood risks]] and [[Human development|human health]]. | |||
Revision as of 12:11, 9 May 2014
{{DriverPartTemplate |PageLabel=Scenario drivers |Sequence=2 |Reference=PBL, 2010; OECD, 2008; UNEP, 2011; PBL, 2011; Chateau et al., 2013; IPCC, 2000; MA, 2005; |Description=
Scenario drivers
On the basis of how the world may develop in the longer term, the following six key scenario drivers are distinguished: demography, economy, culture and lifestyle, natural resource availability, technological development, and policy and governance, see flowchart. The future direction of these drivers is often inferred from the storyline or narrative, which may range from brief to very detailed. The storyline describes the following scenario types and functions:
- reference projection with no new policies (OECD, 2008);
- single ‘best guess’ projection combining past trends with assumptions on how they may develop (PBL, 2010; PBL, 2011);
- multiple contrasting scenarios that span a range of uncertainties about the future (IPCC, 2000; MA, 2005; Moss et al.,, 2010; IIASA, 2013);
- specific or broad policy scenarios directed to improving future outcomes (OECD, 2012; PBL, 2012).
Demography
The future state of the world depends on the population because total demand for goods and services equals the number of people times demand per capita.
Most population projections used as input to the IMAGE model have been adopted from published sources, such as data from the United Nations (UN, 2013) and projections by the International Institute for Applied Systems Analysis (IIASA) (Lutz and KC, 2010). Behind these numerical projections are economic, technical, educational and policy assumptions that determine the estimated future population as the net outcome of fertility and mortality, adjusted for migration flows. This has provided internally consistent, overall population scenarios on the basis of underlying demographic trends.
In addition to total number of people, the population is broken down into gender, income classes, urban and rural, and educational level. These attributes are relevant for issues such as consumption preferences and patterns, and access to goods and services. Using a downscaling procedure (Van Vuuren et al., 2007b), national and regional population can be projected at grid level to account for trends in urbanisation and migration within countries and regions.
Population data are used in energy and agricultural economics modelling, and in other IMAGE modules, such as water stress, nutrients, Template:Flood Risks