Emissions Scenarios - IPCC

174 An Overview of Scenarios
• The A2 storyhne and scenario family describes a very
heterogeneous world. The underlying theme is selfreliance
and preservation of local identities. Fertility
patterns across regions converge very slowly, which
results in high population growth. Economic
development is primarily regionally oriented and per
capita economic growth and technological change are
more fragmented and slower than in other storylines.
• The Bl storyline and scenario family describes a
convergent world with the same low population growth
as in the Al storyline, but with rapid changes in
economic structures toward a service and information
economy, with reductions in material intensity, and the
introduction of clean and resource-efficient
technologies. The emphasis is on global solutions to
economic, social, and environmental sustainability,
including improved equity, but without additional
climate initiatives.
• The B2 storyline and scenario family describes a world
in which the emphasis is on local solutions to
economic, social, and environmental sustainability. It is
a world with moderate population growdi, intennediate
levels of economic development, and less rapid and
more diverse technological change than in the В1 and
AI storylines. While the scenario is also oriented
toward environmental protection and social equity, it
focuses on local and regional levels.
These storylines are presented in more detail in Section 4.3,
which includes their original quantitative indicators that served
as input to the scenario quantification process.
42.2. Scenarios
All SRES scenarios were designed as quantitative
"interpretations" (quantifications) of the SRES qualitative
storylines. Each scenario is a particular quantification of one of
the four storylines. The quantitative inputs for each scenario
involved, for instance, regionalized measures of population,
economic development, and energy efficiency, the availability
of various forms of energy, agricultural productivity, and local
pollution controls. Each participating modeling group (see
above) used computer models and their experience in the
assessment of long-range development of economic,
technological, and environmental systems to generate
quantifications of the storylines. The models used to develop
the scenarios are:
• Asian Pacific Integrated Model (AIM) from the
National Institute of Environmental Studies (NIES) in
Japan (Morita et al, 1994).
• Atmospheric Stabilization Framework Model (ASF)
from ICF Consulting in the US (Lashof and Tirpak,
1990; Pepper et al, 1998; Sankovski et al., 2000).
• Integrated Model to Assess the Greenhouse Effect
(IMAGE) from the National Institute for Public Health
and Hygiene (RIVM) in the Netherlands (Alcamo et
al, 1998; de Vries et al., 1994, 1999, 2000), used in
connection with the Central Plarming Bureau (СРВ)
WortdScan model (de Jong and Zalm, 1991), the
Netherlands.
• Multiregional Approach for Resource and Industry
Allocation (MARIA) from the Science University of
Tokyo in Japan (Mori and Takahashi, 1999; Mori,
2000).
• Model for Energy Supply Strategy Alternatives and
their General Environmental Impact (MESSAGE) from
the International Institute of AppHed Systems Analysis
(IIASA) in Austria (Messner and Strubegger, 1995;
Riahi and Roehrl, 2000).
• The Mini Cfimate Assessment Model (MiniCAM) from
the Pacific Northwest National Laboratory (PNNL) in
the USA (Edmonds etal, 1994, 1996a, 1996b).
A more detailed description of the modeling approaches is
given in Appendix IV. Some modeling teams developed
scenarios that reflected all four storylines, while some
presented scenarios for fewer storylines. Some scenarios share
hannonized^ input assumptions of main scenario drivers, such
as population, economic growth, and final energy use, with
their respective designated marker scenarios of the four
scenario families and underlying storyhnes (see Section 4.4.1).
Others explore scenario sensitivities in titese driving forces
through alternative interpretations of the four scenario
storylines. Table 4-1 lists all SRES scenarios, by modeling
group and by scenario family, and indicates which scenarios
share harmonized input assumptions of important driving
forces of emissions at the global level and at the level of the
four SRES regions. Altogether, the six modeling teams
formulated 40 alternative SRES scenarios
All the qualitative and quantitative features of scenarios that
belong to the same family were set to conform to the
corresponding features of the underlying storyline.
Quantitative storyline targets recommended for use in all
scenarios within a given family included, in particular,
population and GDP growth assumptions. Most scenarios
developed within a given family follow these storyline
recommendations, but some scenarios offer alternative
interpretations. Scenarios within each family vary quite
substantially in such characteristics as the assumptions about
availability of fossil-fuel resources, the rate of energyefficiency
improvements, the extent of renewable-energy
development, and, hence, resultant GHG emissions. This
variation reflects the modeling teams' altemative views on the
plausible global and regional developments and also stems
from differences in the underlying modeling approaches. After
the modeling teams had quantified the key driving forces and
made an effort to harmonize them with the storylines by
' The harmonization criteria agreed by the writing team are indicated
in Table 4-1. The classification of scenarios is quite robust against
varying the percentage deviation harmonization criteria (see Section
4.4.1).