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Emissions Scenarios


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The six models have different regional aggregations. The writing team decided to group the various global regions into four "macro-regions" common to all different regional aggregations across the six models. The four macro-regions (see Appendix III) are broadly consistent with the allocation of countries in the United Nations Framework Convention on Climate Change (UNFCCC, 1997) although the correspondence is not exact because of changes in the countries listed in Annex I of UNFCCC.

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. Together, 26 scenarios were "harmonized" to share agreed common assumptions about population and gross domestic product (GDP) developments (a few that also share common final energy trajectories are called "fully harmonized," see Section 4.1. in Chapter 4). Thus, the harmonized scenarios are not independent of each other within each family, but they are independent across the four families. However, scenarios within each family vary quite substantially in characteristics such as the assumptions about availability of fossil-fuel resources, the rate of energy-efficiency improvements, the extent of renewable-energy development, and, hence, the resultant GHG emissions. Thus, after the modeling teams had quantified the key driving forces and made an effort to harmonize them with the storylines by adjusting control parameters, there still remained diversity in the assumptions about the driving forces and in the resultant emissions (see Chapter 4).

Box 6-2: SRES Modeling Teams

In all, six models were used to generate the 40 scenarios:

  • Asian Pacific Integrated Model (AIM) from the National Institute of Environmental Studies in Japan (Morita et al., 1994);
  • Atmospheric Stabilization Framework Model (ASF) from ICF Consulting in the USA (Lashof and Tirpak, 1990; Pepper et al., 1992, 1998; Sankovski et al., 2000);
  • Integrated Model to Assess the Greenhouse Effect (IMAGE) from the National Institute for Public Health and Environmental Hygiene (RIVM) (Alcamo et al., 1998; de Vries et al., 1994, 1999, 2000), used in connection with the Dutch Bureau for Economic Policy Analysis (CPB) WorldScan 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 Applied Systems Analysis (IIASA) in Austria (Messner and Strubegger, 1995; Riahi and Roehrl, 2000); and the
  • Mini Climate Assessment Model (MiniCAM) from the Pacific Northwest National Laboratory (PNNL) in the USA (Edmonds et al., 1994, 1996a, 1996b).

For a more detailed description of the modeling approaches see Appendix IV.

The remaining 14 scenarios adopted alternative interpretations of the four scenario storylines to explore additional scenario uncertainties beyond differences in methodologic approaches, such as different rates of economic growth and variations in population projections. These variations reflect the "modeling teams' choice" of alternative but plausible global and regional developments compared to those of the "harmonized" scenarios; they also stem from the differences in the underlying modeling approaches. This approach generated a large variation and richness in different scenario quantifications, often with overlapping ranges of main driving forces and GHG emissions across the four families.

In addition, the A1 scenario family branched out into different distinct scenario groups, based on alternative technological developments in future energy systems, from carbon-intensive development to decarbonization. Similar storyline variations were considered for other scenario families, but they did not result in genuine scenario groupings within the respective families. However, if future energy systems variations were applied fully to other storylines, they may evolve differently from those in A1. They have been introduced into the A1 storyline because of its "high growth with high technology" nature, for which differences in alternative technology developments translate into large differences in future GHG emission levels. The A1 groups further increased the richness in different GHG and SO2 emissions paths. Indeed, this variation in the structure of future energy systems in itself resulted in a range of emissions almost as large as that generated through the variation of other main driving forces, such as population and economic development. Altogether the 40 SRES scenarios fall into seven groups: the three scenario families A2, B1, and B2, plus four groups within the A1 scenario (see footnote 2).

As in the case of the storylines, no single scenario - whether it represents a modeler's choice or harmonized assumptions - was treated as being more or less "probable" than others belonging to the same family. However, one preliminary harmonized scenario from each family, referred to as a "marker," was used in 1998 to solicit comments during the "open process" and as input for climate modelers in accordance with a decision of the IPCC Bureau. The four marker scenarios were posted on the IPCC web site (sres.ciesin.org) in June 1998, and the open scenario review process through the IPCC web site lasted until January 1999. The choice of markers was based on extensive discussion of:

  • Range of emissions across all of marker scenarios.
  • Which of the initial quantifications (by the modelers) reflected the storyline.
  • Preference of some of the modeling teams and features of specific models.
  • Use of different models for the four markers.

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 matched 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 particular storyline. These scenarios have received much closer scrutiny, not only from the entire writing team, but also via the SRES open process, than other scenario quantifications. The marker scenarios are also the 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 scenario groups that constitute different interpretations of the A1 storyline with different models.

Figure 6-1: Schematic illustration of SRES scenarios. The set of
scenarios consists of the four scenario families A1, A2, B1, and
B2. Each family consists of a number of scenarios, some of which
have "harmonized" driving forces and share the same prespecified
population and gross world product (a few that also share common
final energy trajectories are called "fully harmonized"). These are
marked as "HS" for harmonized scenarios. One of the harmonized
scenarios, originally posted on the open-process web site, is called
a "marker scenario." All other scenarios of the same family based
on the quantification of the storyline chosen by the modeling team
are marked as "OS." Six modeling groups developed the set of 40
emissions scenarios. The GHG and SO2 emissions of the scenarios
were standardized to share the same data for 1990 and 2000 on
request of the user communities. The time-dependent standardized
emissions were also translated into geographic distributions. See
also footnote 2.

Additional scenarios using the same harmonized assumptions as the marker scenarios developed by different modeling teams and other scenarios that give alternative quantitative interpretations of the four storylines constitute the final set of 40 SRES scenarios. However, differences in modeling approaches mean that not all the scenarios provide estimates for all the direct and indirect GHG emissions for all the sources and sectors. The four SRES marker scenarios 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 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, be used to capture the range of uncertainties of driving forces and in addition, the two additional illustrative scenarios in A1 be used to capture the range of GHG emissions, and these should always be used together, and that no individual scenario should be singled out for any purpose. Multiple baselines and overlapping emissions ranges have important implications for making policy analysis (e.g., similar policies might have different impacts in different scenarios). Combinations of policies might shape the future development in the direction of certain scenarios. Box 6-4 (see later) summarizes the recommendations of the writing team for consideration by the user communities within and outside the IPCC.

Thus, there are three different types of scenarios within each family - one marker (and two illustrative scenarios in the A1 family), a set of harmonized scenarios, and a set of other (non-harmonized) scenarios. In addition, the A1 family of scenarios is subdivided into groups that describe alternative technological developments in the energy system. Together with the other three scenario families the SRES scenarios build seven distinct scenario groups (see footnote 2). Figure 6-1 illustrates this scenario terminology schematically. The detailed descriptions of inputs and outputs (other than GHG emissions) of the SRES marker scenarios, other harmonized scenarios, and all other scenarios are presented in Chapter 4 and the Appendices, while the emissions of GHGs and other radiatively important species of gases are described in Chapter 5 and Appendices.

The writing team considers that the SRES scenario set (in all the richness of scenario families, groups, markers, and illustrative and harmonized scenarios) is based on a "neutral" choice of scenario drivers; no driver is unduly emphasized as being more important than others. The scenarios do not suggest that future population growth alone is the driver of future emissions, nor do they suggest that technological change alone in any one sector could drive future emissions in one way or the other. While recognizing the importance of any of these driving forces per se, this report illustrates the critical role of relationships and interdependencies between scenario driving forces. To an extent it is the nature of these relationships that drives the future more than the possible evolution of any individual driving forces by itself. In other words, the uncertainty of the future is not simply parametric, but deeply functional; uncertainties and incomplete understanding exist for both. Qualitative scenario storylines add transparency and consistency to the relationships assumed in any particular scenario. The storylines also allow for additional interpretation of scenario results by different user communities.


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