Drivers/Scenario drivers: Difference between revisions

From IMAGE
Jump to navigation Jump to search
No edit summary
mNo edit summary
 
(21 intermediate revisions by 4 users not shown)
Line 2: Line 2:
|PageLabel=Scenario drivers
|PageLabel=Scenario drivers
|Sequence=2
|Sequence=2
|Reference=PBL, 2010; PBL, 2011; OECD, 2008; Moss et al., 2010; IIASA, 2013; UN, 2013; Lutz and KC, 2010; Van Vuuren et al., 2007b; OECD, 2012;  
|Reference=PBL, 2010; PBL, 2011; OECD, 2008; Moss et al., 2010; IIASA, 2013; UN, 2013; Lutz and KC, 2010; Van Vuuren et al., 2007b; Chateau et al., 2013;
|Description={{DisplayFigureTemplate|Flowchart D}}
}}<div class="page_standard">
<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 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:
Based on 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]]);  
Line 14: Line 14:
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.  
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 based on 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.  
In addition to the 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 consumer 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 the 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]], [[Nutrient balances|nutrients]], [[Flood risks|flood risks]] and [[Human development|human health]].
Population data are used in the energy and agricultural economics models and other IMAGE modules, such as [[Water|water stress]], [[Nutrients|nutrients]], [[Flood risks|flood risks]] and [[Human development|human health]].
 
===Economy===
At the most aggregated level, economic activity is described in terms of [[GDP per capita|gross domestic product (GDP) per capita]]. Models outside the IMAGE 3.0 framework, such as the [[ENV-Linkages model|OECD ENV-Growth model]], project long-term GDP growth based on developments in crucial production factors (e.g., capital, labour, natural resources), and the sector composition of the economy. The various components of GDP on the production side (in particular [[Sector value added|value added (VA) per sector]]) and expenditures (in particular [[private consumption]]) are estimated with more detailed models that take account of inter-sector linkages, own- and cross-price responses, and other factors [[Chateau et al., 2013]].
 
In IMAGE 3.2, economic variables are used as model drivers for the [[energy demand]] model, food demand and non-agricultural water demand ([[Water|Water model]]). To meet the requirements of the household energy demand model, the average income is broken down into urban and rural population, and each population into quintiles of income levels. The latter is derived from the assumed uneven income distribution using the [[GINI coefficient|GINI]] factor, a measure of income disparity in a population. The macro indicator GDP per capita is also used directly in IMAGE components, such as [[Human development|human health]], [[flood risks]], and [[nutrients]] (for calculating urban wastewater). The agriculture model [[MAGNET model|MAGNET]] is an economy-wide computable general equilibrium ({{abbrTemplate|CGE}}) model that reproduces exogenous GDP growth projections made in less complex economic growth models, see [[Agricultural economy]].


===Policy and governance===
===Policy and governance===
Scenarios may differ considerably with regard to assumptions on implicit or explicit policies that reflect alternative future developments in human and natural systems, and assumptions on the evolution of governance structures and institutional settings. While policy thinking may vary, a key scenario split in IMAGE is more focus on the shorter term and/or on material wealth, or focus on longer term sustainability concerns. Based on this, inter-regional and/or inter-generational equity may be awarded more or less weight as an underlying future trend. As mentioned under culture and lifestyle, such assumed directions in overall policy have the potential to influence almost all relevant scenarios and model drivers.  
Scenarios may differ considerably with regard to assumptions on implicit or explicit policies that reflect alternative future developments in human and natural systems and assumptions on the evolution of governance structures and institutional settings. For instance, scenarios may emphasize the maximization of material consumption or long-term sustainability concerns. Based on this, inter-regional and inter-generational equity may be awarded more or less weight as an underlying future trend. As mentioned under culture and lifestyle, such assumed directions in overall policy can influence almost all relevant scenarios and model drivers. Other policy factors can be concern trade and technology preferences.  


In addition to alternative policy directions, other important factors are developments in governance structures and institutions in different world regions, or in groups of regions sharing certain characteristics. For instance, this may concern high-income industrialised countries, medium income emerging economies, or low-income developing countries.  
In addition to alternative policy directions, other essential factors are developments in governance structures and institutions in different world regions or groups of regions sharing specific characteristics. For instance, this may concern high-income industrialized countries, medium-income emerging economies, or low-income developing countries.


Other elements may also make some policy measures and instruments more or less plausible. For example, a concerted and jointly implemented global climate mitigation strategy is less conceivable in a world with diverging regions primarily pre-occupied with short-term domestic interests and weak intergovernmental bodies.
Other elements may also make some policy measures and instruments more or less plausible. For example, a concerted and jointly implemented global climate mitigation strategy is less conceivable in a world with diverging regions primarily pre-occupied with short-term domestic interests and weak intergovernmental bodies.


===Technological development===
===Technological development===
At scenario level, the assumed technical progress is the key driver of economic growth. Given an effective labour force, the increase in labour productivity delineates the potential for economic growth. In scenarios, it is generally assumed that the degree of technical progress is reflected in all areas where technology plays a role. Thus, an assumed rapid growth in technology leading to high economic growth implies that technological options in specific sectors (e.g., energy and agriculture) will also develop relatively quickly. However, the directions of technological change may differ within and across sectors. For example, renewable energy technologies may improve more rapidly than fossil fuel based technology. Thus, this is an uncertain factor.
At the scenario level, the assumed technical progress is the key driver of economic growth. In scenarios, it is generally assumed that technical progress is reflected in all areas where technology plays a role. Thus, an assumed rapid growth in technology leading to high economic growth implies that technological options in specific sectors (e.g., energy and agriculture) will also develop relatively quickly. However, the directions of technological change may differ within and across sectors. For example, renewable energy technologies may improve more rapidly than fossil fuel-based technology. Thus, this is an uncertain factor.


In the energy sector (see [[Energy supply and demand]]), technology improvements over time are largely governed by an endogenous mechanism that links technology cost to the cumulative capacity, learning by doing. Technological factors in agriculture are estimated exogenously, based on historical data and projections from the literature on crop and livestock productivity, efficiency in water and fertiliser use, and performance of irrigation systems.
In the energy sector (see Energy supply and demand), technology improvements over time are primarily governed by an endogenous mechanism that links technology cost to the cumulative capacity, learning by doing. Technological factors in agriculture are estimated exogenously, based on historical data and projections from the literature on crop and livestock productivity, efficiency in water and fertilizer use, and performance of irrigation systems.


===Culture and lifestyle ===
===Culture and lifestyle ===
For comparable levels of affluence, observed consumption behaviour differs greatly between countries and regions, and to a lesser extent within countries. The modal split for passenger transport by walking, bicycle, car, bus, train, boat and aircraft depends on income, but also on engrained traditions and habits of social groups. Food preferences depend on availability and affordability, and also greatly on cultural factors, such as religion (e.g., no pork for Jewish and Islamic households, and no beef or no meat at all for Hindus), and on tradition, values and health concerns. In addition, behaviour may be influenced by concerns about environmental degradation, animal welfare, inter-regional and inter-generational equity, and other issues according to dominant social norms and values.  
For comparable levels of affluence, observed consumption behaviour differs significantly between countries and regions and to a lesser extent within countries. The modal split for passenger transport by walking, bicycle, car, bus, train, boat and aircraft depends on income and engrained traditions and habits of social groups. Food preferences depend on availability, affordability and cultural factors, such as religion (e.g., no pork for Jewish and Islamic households, no beef or meat at all for Hindus), and on tradition, values and health concerns. In addition, behaviour may be influenced by concerns about environmental degradation, animal welfare, inter-regional and inter-generational equity, and other issues according to dominant social norms and values.


Consumer preferences and lifestyles may change over time, as may norms and values. The direction and rates of change can be inferred from the underlying scenario storyline. Policies may be put in place to enable, encourage or even induce change, given sufficient public support.  
Consumer preferences and lifestyles may change over time, as may norms and values. The direction and rates of change can be inferred from the underlying scenario storyline. Policies may be put in place to enable, encourage or even induce change, given sufficient public support.


===Natural resource availability===
===Natural resource availability===
The term, ultimate natural resources, refers to the amount of resources theoretically available if not affected by human activity. For non-renewable resources, such as coal and iron ore, this concerns the accumulated amount before human extraction began. For renewable resources, such as solar energy, it represents the solar radiation intercepted on Earth in a given time period. As the ultimate quantities of these natural resources cannot be changed by humans, they cannot be considered as scenario drivers in IMAGE. Similarly, the global land area is fixed, except for relatively limited reclaimed areas in shallow coastal waters and natural processes by which land area is increased (e.g., volcanic islands) and land area is reduced (e.g., coastal erosion).
The term ultimate natural resource availability refers to the amount of resources theoretically available. For non-renewable resources, such as coal and iron ore, this concerns the total amount of fossil fuel stored underground. For renewable resources, such as solar energy, it represents the solar radiation intercepted on Earth in a given time period. However, these ultimate quantities of these natural resources are less relevant as, in reality, extraction is limited to technical and economic factors.   
 
The quantity of a resource available in the future depends on exogenous assumptions for the scenarios. The estimated quantities depend on the assumed future technology capabilities, policies and human preferences. Higher estimates of non-conventional fossil fuels and nuclear fuel reserves are associated with technology optimism, for example, estimates of natural gas reserves depend on whether the extraction of deep seabed methane is considered a viable option. Nature conservation and other issues may limit the potential for natural land conversion for agriculture, but may also impose limits on hydroelectricity generation.
 
In IMAGE 3.0, renewable and non-renewable energy resources are modelled by volume and price, see Component [[Energy supply]]. Similarly, the potential land for agriculture ranked according to suitability and is subject to nature conservation policies, limits future land conversion, see Component [[Agricultural systems]].
 
 
 
 
 
When considering how the world might unfold in the longer term, six key scenario drivers are distinguished:
* demographics;
* economics;
* culture and lifestyle;
* natural resources;
* technological development;
* policy and governance environment.
To a large degree these scenario drivers are interdependent, and their future direction is often inferred from a simple to very elaborate ‘storyline’ or narrative. Such storylines describe the type and function of the scenario at hand: a reference projection with no new policies, a single ‘best-guess’ projection combining trends from the past with assumptions about how they might unfold in the future, multiple contrasting scenarios that span a range of uncertainty about the future, or a specific or broad policy scenario aiming to improve future outcomes. For examples, see ([[PBL, 2010]]; [[OECD, 2008]]; [[OECD, 2012]]; [[UNEP, 2011]]; [[PBL, 2011]])
 
==Demographics==
The future state of the world will depend on how many people are expected to populate the world, as all –average- per capita activities scales with the number of people to obtain regional and global demands for goods and services. Typically the population projections that are used as input to drive the IMAGE model are adopted from published sources such as [[UN]] and [[IIASA]]. Behind these numerical projections are economic, technical, educational and policy assumptions that  influence the estimated future population as the net outcome of fertility and mortality, adjusted for migration flows. This provides internally consistent, or at least plausible, overall population scenarios on the basis of underlying demographic trends. At the level of model drivers, besides the total population size the breakdown over gender, income classes, urban/ rural split, and the level of education matter for such issues as consumption preferences and patterns, and access to goods and services. With use of a downscaling procedure, the population at country or regional level is also available at the grid level; see [[IMAGE_framework_summary|IMAGE_framework summary reference to downscale****]]. Population data are used in the energy- and agricultural economics modeling, but also directly in various other modules of IMAGE such as water stress, nutrients, flood risks and human health.
 
==Economics==
At the most aggregate level, the level of economic activity is typically described in terms of GDP (Gross Domestic Product) per capita. Models outside the IMAGE 3.0 framework estimate long-term GDP growth perspectives, following from development of the key production factors (e.g. capital, labour, natural resources) and the sectoral composition of the economy; such as the [[ENV-Growth model]] of the OECD. The overall GDP is composed of Value Added (VA) per relevant sector and private consumption, estimated with more detailed models accounting for intersectoral linkages, responses to prices, and others ([[Chateau et al., 2013]]). Economic variables are used as model drivers for the [[energy demand]] model , and the non-agricultural water demand contributing to water stress (model component [[Water]]). For the household energy demand model, the average income is broken down into urban and rural population, and for each into quintiles of income levels. The latter is derived from the assumed, uneven income distribution by means of the so-called [[GINI coefficient|GINI factor]]. The GINI factor is a measure of income disparity in a population. If all enjoy the same income, GINI equals unity. The lower the GINI is, the wider is the gap between the lowest and highest income groups. The agricultural economy model [[MAGNET model|MAGNET]] is in fact an economy-wide Computable General Equilibrium (CGE) model, that is able to reproduce the exogenous GDP growth projections made with the less complex economic growth models; see model component [[Agricultural economy and forestry]] . The macro indicator GDP/capita is also used directly in various other IMAGE components, such as [[nutrient balances]] in urban wastewater, [[Human development|human health]], and [[flood risks]] .
 
==Culture and lifestyle==
For comparable levels of affluence, the observed behaviour of societies with respect to consumption differs strongly between countries and regions, and to a lesser extent also within  countries. The modal split of passenger transport between walking, cycling, cars, buses, trains, boats and planes depend on income, but also on traditions and habits engrained in social groups. Preference for different foodstuffs depends on availability and affordability, but also strongly on cultural factors. These may be inspired by religion (no pork for Jewish and Islamic households; no beef or no meat at all for Hindus; etc.), but also by tradition, public moral and health concerns. In addition, concerns over environmental degradation, animal welfare, inter-regional and intergenerational equity and other issues can influence actual behavior, in accordance with dominant societal norms and values. Consumer preferences and lifestyles can change over time, as norms and values can change. The direction and rate of such changes can be inferred from the underlying scenario storyline. Policies may be put in place to enable, encourage or even enforce such changes, given sufficient public support.
 
==Natural resource availability==
Ultimate natural resources are considered a given and are not subject to adjustment by human activities, other than depletion of non-renewable resources by transforming them. For example extracting coal from underground deposits to burn them to generate thermal energy and a range of -mostly gaseous-substances- including carbon dioxide. Similarly, the total land surface is fixed, except for relatively limited man-made expansion of land into shallow coastal waters. Human activities such as agriculture and forestry, however, transform the land-cover and land-use and thereby alter the quantity of suitable land for agriculture.
 
What can be assumed as exogenous scenario drivers are assumptions about how much of the ultimate resource is available in future. This depends on assumptions about future technological capabilities and assumed policies reflecting human preferences. Technological optimism is associated with higher end estimates of non-conventional fossil and nuclear fuel reserves. Nature conservation and other concerns can limit the potential for conversion of natural land for agriculture, but may also impose limits to hydro-electricity generation.
 
In IMAGE 3.0 renewable and non-renewable energy resource by volume and price are explicitly modeled; see component [[energy supply]]. Similarly the potential for land to be used for agriculture, ranked by suitability and subject to nature conservation policies, sets boundaries on future land conversion; see component [[Agricultural systems]].
 
==Technological change==
At the overall scenario level, assumptions about technological progress are the all-important drivers of economic growth. Given an effective labour force, the increase in labour productivity delineates the potential for economic growth. It is generally assumed that the degree of technological progress at the scenario level is bound to be reflected in all instances where technology plays a role. In other words: rapid technological growth assumptions behind high economic growth rates imply that technologies in specific sectors (energy, agriculture) will also improve relatively quickly. Across and within sectors the directions of technological change may differ, however. For example, renewable energy technologies may improve much more rapidly than fossil fuel based technology, an uncertain factor.
 
In the energy sector, see component [[Energy supply and demand]], the improvement in technologies over time is largely governed by an endogenous mechanism that links technology cost to the cumulative installed capacity: learning-by-doing. In agriculture technological factors are estimated exogenously, based on historical data and published projections of crop and livestock productivity, water and fertilizer use efficiency, irrigation systems performance, etc.


==Policy and governance==
The quantity of a resource available thus depends on exogenous assumptions that influence these factors. More concretely, this involves future technology capabilities, policies and human preferences. Higher estimates of non-conventional fossil fuels and nuclear fuel reserves are associated with technology optimism; for example, estimates of natural gas reserves depend on whether the extraction of deep seabed methane is considered a viable option. Nature conservation and other issues may limit the potential for natural land conversion for agriculture and impose limits on hydroelectricity generation.  
At the scenario level it can make a big difference if –implicit or explicit- policies are assumed that reflect alternative directions that shape future development of human and natural systems. And it matters also how governance structures and institutional settings are assumed to evolve. Overall policy thinking can vary in many ways, but in the context of IMAGE important scenario bifurcations include more focus on the shorter term and/or on material wealth, versus longer term sustainability concerns. But also inter-regional and/or intergenerational equity may gain more or less weight as underlying future trend. As mentioned under culture and lifestyle, such assumed overall policy directions have the potential to influence pretty much all relevant scenario drivers, and model drivers alike.  


In addition to the alternative policy directions, it matters how the governance structures and associated institutional arrangements develop over time in different regions of the world, or different groups of regions which share certain characteristics, such as high-income industrialized, medium income emerging or low income developing countries.  
In IMAGE 3.2, renewable and non-renewable energy resources are modelled by volume and price, see Component [[Energy supply]]. Similarly, the potential land for agriculture ranked according to suitability and is subject to nature conservation policies, limits future land conversion, see Component [[Land-use allocation]].


Besides the structural elements, the assumed policy and governance environment can also make certain policy measures and instruments more or less plausible. For example, a concerted and jointly implemented global climate mitigation strategy can hardly be imagined in a world of diverging regions primarily occupied with shorter term domestic interests, including barriers to international trade and weak intergovernmental bodies.
===Relationships between scenario drivers===
Assumptions made in one of the six scenario drivers depend, to a lesser or greater extent, on assumptions in one or more of the other scenario drivers. Thus, the plausibility of a set of drivers and an individual driver hinges on careful consideration of the nature and direction of these relationships. An overarching story or narrative has proven helpful in selecting meaningful combinations of scenario drivers ([[IPCC, 2000]]; [[MA, 2005]]).
==Relations between scenario drivers==
</div>
As mentioned in the descriptions of the six scenario drivers, assumptions for each tend to depend to a lesser or greater extent on what is assumed for one or several of the other scenario drivers. Plausibility of the set of drivers, over and above the plausibility of each driver in its own right, therefore hinges on a careful consideration of the nature and direction of these relationships. An overarching story or narrative is proven to be helpful in choosing meaningful combinations across each of the six domains ([[IPCC, 2000]]; [[MA, 2005]]).
}}

Latest revision as of 10:25, 7 April 2023

Link to framework components overview

Parts of Drivers/Scenario drivers

  1. Introduction page
  2. Scenario drivers
  3. Model drivers
  4. Policy issues
  5. Overview of references
Projects/Applications
Models/Databases
Relevant overviews
Key publications
References
Scenario development and model drivers for IMAGE 3.0
Flowchart Drivers. Model drives are inferred from scenario storylines taking into account external data sources, such as time series, cross-sector data, and literature sources.

Scenario drivers

Based on 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:

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 based on underlying demographic trends.

In addition to the 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 consumer 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 the grid level to account for trends in urbanisation and migration within countries and regions.

Population data are used in the energy and agricultural economics models and other IMAGE modules, such as water stress, nutrients, flood risks and human health.

Economy

At the most aggregated level, economic activity is described in terms of gross domestic product (GDP) per capita. Models outside the IMAGE 3.0 framework, such as the OECD ENV-Growth model, project long-term GDP growth based on developments in crucial production factors (e.g., capital, labour, natural resources), and the sector composition of the economy. The various components of GDP on the production side (in particular value added (VA) per sector) and expenditures (in particular private consumption) are estimated with more detailed models that take account of inter-sector linkages, own- and cross-price responses, and other factors Chateau et al., 2013.

In IMAGE 3.2, economic variables are used as model drivers for the energy demand model, food demand and non-agricultural water demand (Water model). To meet the requirements of the household energy demand model, the average income is broken down into urban and rural population, and each population into quintiles of income levels. The latter is derived from the assumed uneven income distribution using the GINI factor, a measure of income disparity in a population. The macro indicator GDP per capita is also used directly in IMAGE components, such as human health, flood risks, and nutrients (for calculating urban wastewater). The agriculture model MAGNET is an economy-wide computable general equilibrium (CGE) model that reproduces exogenous GDP growth projections made in less complex economic growth models, see Agricultural economy.

Policy and governance

Scenarios may differ considerably with regard to assumptions on implicit or explicit policies that reflect alternative future developments in human and natural systems and assumptions on the evolution of governance structures and institutional settings. For instance, scenarios may emphasize the maximization of material consumption or long-term sustainability concerns. Based on this, inter-regional and inter-generational equity may be awarded more or less weight as an underlying future trend. As mentioned under culture and lifestyle, such assumed directions in overall policy can influence almost all relevant scenarios and model drivers. Other policy factors can be concern trade and technology preferences.

In addition to alternative policy directions, other essential factors are developments in governance structures and institutions in different world regions or groups of regions sharing specific characteristics. For instance, this may concern high-income industrialized countries, medium-income emerging economies, or low-income developing countries.

Other elements may also make some policy measures and instruments more or less plausible. For example, a concerted and jointly implemented global climate mitigation strategy is less conceivable in a world with diverging regions primarily pre-occupied with short-term domestic interests and weak intergovernmental bodies.

Technological development

At the scenario level, the assumed technical progress is the key driver of economic growth. In scenarios, it is generally assumed that technical progress is reflected in all areas where technology plays a role. Thus, an assumed rapid growth in technology leading to high economic growth implies that technological options in specific sectors (e.g., energy and agriculture) will also develop relatively quickly. However, the directions of technological change may differ within and across sectors. For example, renewable energy technologies may improve more rapidly than fossil fuel-based technology. Thus, this is an uncertain factor.

In the energy sector (see Energy supply and demand), technology improvements over time are primarily governed by an endogenous mechanism that links technology cost to the cumulative capacity, learning by doing. Technological factors in agriculture are estimated exogenously, based on historical data and projections from the literature on crop and livestock productivity, efficiency in water and fertilizer use, and performance of irrigation systems.

Culture and lifestyle

For comparable levels of affluence, observed consumption behaviour differs significantly between countries and regions and to a lesser extent within countries. The modal split for passenger transport by walking, bicycle, car, bus, train, boat and aircraft depends on income and engrained traditions and habits of social groups. Food preferences depend on availability, affordability and cultural factors, such as religion (e.g., no pork for Jewish and Islamic households, no beef or meat at all for Hindus), and on tradition, values and health concerns. In addition, behaviour may be influenced by concerns about environmental degradation, animal welfare, inter-regional and inter-generational equity, and other issues according to dominant social norms and values.

Consumer preferences and lifestyles may change over time, as may norms and values. The direction and rates of change can be inferred from the underlying scenario storyline. Policies may be put in place to enable, encourage or even induce change, given sufficient public support.

Natural resource availability

The term ultimate natural resource availability refers to the amount of resources theoretically available. For non-renewable resources, such as coal and iron ore, this concerns the total amount of fossil fuel stored underground. For renewable resources, such as solar energy, it represents the solar radiation intercepted on Earth in a given time period. However, these ultimate quantities of these natural resources are less relevant as, in reality, extraction is limited to technical and economic factors.

The quantity of a resource available thus depends on exogenous assumptions that influence these factors. More concretely, this involves future technology capabilities, policies and human preferences. Higher estimates of non-conventional fossil fuels and nuclear fuel reserves are associated with technology optimism; for example, estimates of natural gas reserves depend on whether the extraction of deep seabed methane is considered a viable option. Nature conservation and other issues may limit the potential for natural land conversion for agriculture and impose limits on hydroelectricity generation.

In IMAGE 3.2, renewable and non-renewable energy resources are modelled by volume and price, see Component Energy supply. Similarly, the potential land for agriculture ranked according to suitability and is subject to nature conservation policies, limits future land conversion, see Component Land-use allocation.

Relationships between scenario drivers

Assumptions made in one of the six scenario drivers depend, to a lesser or greater extent, on assumptions in one or more of the other scenario drivers. Thus, the plausibility of a set of drivers and an individual driver hinges on careful consideration of the nature and direction of these relationships. An overarching story or narrative has proven helpful in selecting meaningful combinations of scenario drivers (IPCC, 2000; MA, 2005).

Retrieved from "https://models.pbl.nl/index.php?title=Drivers/Scenario_drivers&oldid=37100"