Emissions Scenarios - IPCC

Technical Summary 31
• range of emissions across all of marker scenarios;
• which of the initial quantifications (by the modelers)
reflected the storyline best;
• preference of some of the modeling teams and features
of specific models;
• use of four different models for the four markers.
As a result the markers were not intended to be the median or
mean scenarios from their respective families. Indeed, in general
it proved impossible to develop scenarios in which all relevant
characteristics match mean or median values. Thus, marker
scenarios are no more or less likely than any other scenarios, but
are those scenarios considered by the SRES writing team as
illustrative of a parficular storyline. These scenarios have
received the closest scrutiny of the entire writing team and via
the SRES open process compared to other scenario
quantifications. The marker scenarios are also those SRES
scenarios that have been most intensively tested in terms of
reproducibility. As a rule, different modeling teams have
attempted to replicate the model quantification of marker
scenarios. Available time and resources have not allowed a
similar exercise to be conducted for all SRES scenarios,
although some effort was devoted to reproduce the four scenario
groups (merged into three in the SPM) that constitute different
interpretations of the Al storyline with different models.
Additional scenarios using the same harmonized assumptions
as the marker scenarios developed by different modeling teams
and other scenarios that give alternative quantitative
inteфretations of the four storylines constitute the final set of
40 SRES scenarios. This also means that the 40 scenarios are
not independent of each other as they are all based on four
storylines and subdivided into seven scenario groups (after
merging two groups, six in the SPM) that share many common
assumptions. In addition to many revisions of the marker and
other harmonized scenarios, other ahemative scenarios were
foiTuulated by the six modeling teams within each of the four
scenario famiUes. The result is a more complete, refined set of
40 emissions scenarios that reflects the broad spectrum of
modeling approaches and regional perspectives. However,
differences in modeling approaches have meant that not all of
the scenarios provide estimates for all the direct and indirect
GHG emissions for all the sources and sectors. In addition to
the marker scenarios, two scenarios were also selected in the
SPM to illustrate the alternative energy systems developments
in the AI family. Hence, this report has an illustrative scenario
for each of the six scenario groups in the SPM. The four SRES
marker scenarios and the two illustrative scenarios (selected in
the SPM) cover all the relevant gas species and emission
categories comprehensively and thus constitute the smallest set
of independent and fully documented SRES scenarios.
The scenario groups and cumulative emissions categories were
developed as the smallest subsets of SRES scenarios that
capture the range of uncertainties associated with driving
forces and emissions. Together, the four markers and the two
additional illustrative scenarios selected in the SPM from the
AI scenario groups constitute the set of SRES scenarios that
reflects the uncertainty ranges in the emissions and their
driving forces. Furthermore, the writing team recommends
that, to the extent possible, these scenarios, but at least the four
markers and the two additional illustrative scenarios selected in
the SPM, should always be used together, and that, in general,
no individual scenario should be singled out for any puipose.
Multiple baselines and overlapping emissions ranges have
important implications for making policy analysis, e.g., similar
policies might have different impacts in different scenarios.
Combination of policies might shape the future development in
the direction of certain scenarios.
8. Main Scenario Driving Forces Based on the
Literature
The scenarios cover a wide range of driving forces, from
demographic to social and economic developments. This
section summarizes the assumptions on important scenario
drivers. For simplicity, only three of these are presented
separately here following the exposition in Chapters 2, 3, and
4. Nonetheless, it is important to keep in mind that the future
evolution of these and other main driving forces is interrelated
in the SRES scenarios (see Tables TS-2 and TS-3 for a
summary of the ranges of the main driving forces across the
scenario groups in 2100).
The SRES scenarios span a wide range of assumptions for the
most salient scenario drivers, and thus reflect the uncertainty of
the future. Evidently, views of the future are a time-specific
phenomenon, and this report and its scenarios are no exception.
However, it is important to emphasize that this is an explicit
part of the Terms of Reference for the SRES writing team - to
reflect a range of views, based on current knowledge and the
most recently available literature (see Appendix I). The
scenario quantification results reflect well the literature range,
except for extreme scenarios.
8.1. Population Projections
Three different population trajectories were chosen for SRES
scenarios to reflect future demographic uncertainties based on
published population projections (Lutz, 1996; UN, 1998; see
Chapter 3). The population projections are exogenous input to
all the models used to develop the SRES scenarios. The models
used do not develop population from other assumptions within
the model. Figure TS-3 shows the three population projections
in comparison with the three population projections used in the
IS92 scenarios. Global population ranges between seven and
15 billion people by 2100 across the scenarios, depending on
the rate and extent of the demographic transition. The insert in
Figure TS-3 shows population development in the developed
(industrialized) regions. The range of future populations is
smaller than in the IS92 scenarios, particularly in the
developed (industrialized) regions, for which the lowest
scenario indicates a very modest population decline compared
to IS92 scenarios. The greatest uncertainty about future growth