Figure 1-6: Range of global energy-related and industrial CO2 emissions for the 40 SRES scenarios. The dashed time-paths depict individual SRES scenarios and the shaded area the range of scenarios from the SRES database. The median (50th), 5th, and 95th percentiles of the frequency distribution are shown. The statistics associated with scenarios from the literature do not imply probability of occurrence (e.g., the frequency distribution of the scenarios may be influenced by the use of IS92a as a reference for many subsequent studies). The 40 SRES scenarios are classified into groups that constitute four scenario families. Jointly the scenarios span most of the range of the scenarios in the literature. The emissions profiles are dynamic, ranging from continuous increases to those that curve through a maximum and then decline. The colored vertical bars indicate the range of the four SRES scenario families in 2100. The black vertical bar shows the range of the IS92 scenarios. See also the note in Box 1.2.
The 40 SRES scenarios cover the full range of GHG and SO2 emissions consistent with the storylines and underlying ranges of driving forces from studies in the literature as documented in the SRES database. The four marker scenarios are characteristic of the four scenario families and jointly capture most of the ranges of emissions and driving forces spanned by the full set of scenarios. Figure 1-6 illustrates the range of global energy-related and industrial CO2 emissions for the 40 SRES scenarios against the background of all the emissions scenarios in the SRES scenario database shown in Figure 1-3. Figure 1-6 also shows a range of emissions of the four scenario families.
Figure 1-6 shows that the SRES scenarios cover most of the range of global energy-related CO2 emissions from the literature, from the 95th percentile at the high end of the distribution down to low emissions just above the 5th percentile of the distribution. Thus, they only exclude the most extreme emissions scenarios found in the literature - those situated in the tails of the distribution. What is perhaps more important is that each of the four scenario families covers a sizable part of this distribution, which implies that a similar quantification of driving forces can lead to a wide range of future emissions. More specifically, a given combination of the main driving forces is not sufficient to uniquely determine a future emissions path. There are too many uncertainties. The fact that each of the scenario families covers a substantial part of the literature range also leads to an overlap in the emissions ranges of the four families. This implies that a given level of future emissions can arise from very different combinations of driving forces. This result is of fundamental importance for the assessment of climate-change impacts and possible mitigation and adaptation strategies. Thus, it warrants some further discussion. The emissions paths of the A1 and B2 scenario families perhaps best illustrate these implications.
The A1 scenario family has explored variations in energy systems most explicitly and hence covers the largest part of the scenario distribution shown in Figure 1-6, from the 95th to just above the 10th percentile. The A1 marker (A1B) scenario represents a structure of the future energy mix, balanced in the sense that it does not rely too heavily on one particular energy source. The A1 scenario family includes different groups of scenarios that explore different specific structures of future energy systems, from carbon-intensive development paths to high rates of decarbonization as captured by the two illustrative scenarios that span most of the emissions range for the A1 family. All groups otherwise share the same assumptions about the main driving forces. This indicates that different structures of the energy system can lead to basically the same variation in future emissions as can be generated by different combinations of the other main driving forces - population, economic activities and energy consumption levels. The implication is that decarbonization of energy systems - the shift from carbon-intensive to less carbon-intensive and carbon-free sources of energy - is of similar importance in determining the future emissions paths as other driving forces. Sustained decarbonization requires the development and successful diffusion of new technologies. Thus investments in new technologies during the coming decades might have the same order of influence on future emissions as population growth, economic development and levels of energy consumption taken together.
For example, the comparison of the A1B and B2 marker scenarios indicates that they have similar emissions of about 13.5 and 13.7 GtC by 2100, respectively. The dynamics of the paths are different so that they have different cumulative CO2 emissions. To facilitate such comparisons, the scenarios were grouped into four categories of cumulative emissions between 1990 and 2100. This categorization can guide comparisons using either scenarios with different driving forces yet similar emissions, or scenarios with similar driving forces but different emissions. This characteristic of SRES scenarios also has very important implications for the assessment of climate-change impacts, mitigation and adaptation strategies. Two future worlds with fundamentally different characteristic features, such as A1B and B2 marker scenarios, also have different cumulative CO2 emissions and radiative forcing, but very similar CO2 emissions in 2100. In contrast, scenarios that are in the same category of cumulative emissions can have fundamentally different driving forces and different CO2 emissions in 2100, but very similar cumulative emissions and radiative forcing. Presumably, adverse impacts and effective adaptation measures would vary among the scenarios from different families that share similar cumulative emissions but have different demographic, socio-economic and technological driving forces. This is another reason for considering the entire range of future emissions in future assessments of climate change. There is no single "best guess" or central scenario.
The SRES emissions scenarios also have different emissions for other GHGs and chemically active species such as carbon monoxide, nitrogen oxides, and volatile organic hydrocarbons. The emissions of other gases follow dynamic patterns much like those shown in Figure 1-6 for CO2 emissions. Further details about GHG emissions are given in Chapter 5. Emissions of sulfur aerosol precursors portray even more dynamic patterns in time and space than the CO2 emissions shown in Figure 1-6. Factors other than climate change, namely regional and local air quality, and transformations in the structure of the energy system and end use intervene to limit future emissions. In view of the significant adverse impacts, SO2 emissions in the scenarios are increasingly controlled outside countries of the OECD. As such the SRES scenarios reflect both recent legislation in North America and in Europe and recent policy initiatives in a number of developing countries aimed at reducing SO2 emissions (reviewed in more detail in Chapters 3 and 5). As a result, in the second half of the 21 st century both the trends and regional patterns of SO2 emissions evolve differently from those of CO2 emissions in the SRES scenarios. Emissions outside OECD90 rise initially, most notably in ASIA, and compensate for declining OECD90 emissions. Over the long term, however, SO2 emissions decline throughout the world, but the timing and magnitude vary across the scenarios. One important implication of this varying pattern of SO2 emissions is that the historically important, but uncertain negative radiative forcing of sulfate aerosols may decline in the very long run.
An important feature of the SRES scenarios is their implications for radiative forcing. A vigorous increase of global SO2 emissions during the next few decades across most of the scenarios followed by a decline thereafter will lead to a cooling effect that will differ from the effect that results from the continuously increasing SO2 emissions in the IS92 scenarios. On one hand, the reduction in global SO2 emissions reduces the role of sulfate aerosols in determining future climate toward the end of the 21st century and therefore reduces one aspect of uncertainty about future climate change (because the precise forcing effect of sulfate aerosols is highly uncertain). On the other hand, uncertainty increases because of the diversity in spatial patterns of SO2 emissions in the scenarios. Future assessments of possible climate change need to account for these different spatial and temporal dynamics of GHG and SO2 emissions, and they need to cover the whole range of radiative forcing associated with the scenarios.
Figure 1-5: Schematic illustration of SRES scenarios. The set of scenarios consists of four scenario families: A1, A2, B1 and B2. Scenario family A1 is further subdivided into four scenario groups: A1C, A1G, A1B and A1T, (see also note below), resulting in seven scenario groups together with the other three scenario families. Each family and group consists of a number of scenarios. Some of them 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.
Note: During the approval process of the Summary for Policymakers at the 5th Session of WGIII of the IPCC from 8-11 March 2000 in Katmandu, Nepal, it was decided to combine the A1C and A1G groups into one "fossil intensive" group A1FI in contrast to the non-fossil group A1T, and to select two illustrative scenarios from these two A1 groups to facilitate use by modelers and policy makers. This leads to six scenario groups that constitute the four scenario families, three of which are in the A1 family. These six groups all have "illustrative scenarios," four of which are marker scenarios. All scenarios are equally sound. See also Figure SPM-1.
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