The SRES scenarios generally cover the full range of GHG and sulfur emissions consistent with the storylines and the underlying range of driving forces from studies in the literature, as documented in the SRES database. This section summarizes the emissions of CO₂, CH₄ and SO₂. For simplicity, only these three important gases are presented separately, following the more detailed exposition in Chapter 5 (see Table 6.2b for a summary of the ranges of emissions across the scenario groups in 2020, 2050, and 2100).

6.3.1. Carbon Dioxide Emissions

6.3.1.1. Emissions from Energy, Industry, and Land Use

Figure 6-5 illustrates the range of 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. For simplicity, only energy-related and industrial sources of CO₂ emissions are shown.

Figure 6-5 shows that the marker scenarios by themselves cover a large portion of the overall scenario distribution. This is one reason why the SRES writing team recommends the use of at least the four marker scenarios. Together, they cover a large range of future emissions, both with respect to the scenarios in the literature and the full SRES scenario set.

The SRES scenarios cover rather evenly the range of future emissions found in the literature, from high to low levels over the whole time horizon. In contrast, the distribution for emissions by 2100 of scenarios in the literature is very asymmetric. It has a structure that resembles a tri-modal frequency distribution - those showing emissions of more than 30 gigatons of carbon (GtC; 20 scenarios), those with emissions between 12 and 30 GtC (88 scenarios), and those showing emissions of less than 12 GtC (82 scenarios). As discussed in Chapter 2, the lowest cluster appears to include many of the intervention scenarios; the second and third clusters are most likely the non-intervention cases. The lowest cluster may have been influenced by many analyses of stabilizing atmospheric concentrations. The middle cluster echoes the many analyses that took IS92a as a reference and is testament to the enormous influence of the IS92 series on emissions assessments in general.

The range of CO₂ and other GHG emissions for the four marker scenarios is generally somewhat lower than that of the six IS92 scenarios.³ However, the IS92 scenarios do not cover the "middle" range of emissions where the median and the average of all scenarios in the literature are situated. Adding the other 36 scenarios to the four SRES markers increases the covered emissions range beyond the IS92 series at the high end of the distribution but not at the low end. SRES scenarios stop short of the lower literature emissions because they are scenarios without additional climate initiatives (as per the Terms of References, see Appendix I).

Figure 6-6 illustrates the range of CO₂ emissions of the SRES scenarios against the background of all the IS92 scenarios and other emissions scenarios from the literature documented in the SRES scenario database. The shaded areas depict the range of the scenarios in the database that exceeds the SRES emissions range. The range of future emissions is very large so that the highest scenarios envisage more than a sevenfold increase of global emissions by 2100, while the lowest have emissions lower than today.

The literature includes scenarios with additional climate initiatives and policies, which are also referred to as mitigation or intervention scenarios. As shown in Chapter 2, many ambiguities are associated with the classification of emissions scenarios into those that include additional climate initiatives and those that do not. Many cannot be classified in this way on basis of the information available from the SRES scenario database and the published literature.

Figure 6-6a indicates the ranges of emissions from energy and industry in 2100 from scenarios that apparently include additional climate initiatives (designated as intervention emissions range), those that do not (non-intervention), and those that cannot be assigned to either of these two categories (non-classified). This classification is based on the subjective evaluation of the scenarios in the database by the members of the writing team and is explained in Chapter 2. The range of the whole sample of scenarios has significant overlap with the range of those that cannot be classified and they share virtually the same median (15.7 and 15.2 GtC in 2100, respectively), but the non-classified scenarios do not cover the high part of the range. Also, the range of the scenarios that apparently do not include climate polices (non-intervention) has considerable overlap with the other two ranges (lower bound is slightly higher), but with a significantly higher median (of 21.3 GtC in 2100).

The median of all energy and industry emissions scenarios from the literature is 15.7 GtC by 2100. This is lower than the median of the IS92 set and is lower than the IS92a scenario often (inappropriately) considered as the "central" scenario. Again, the distribution of emissions is asymmetric (see the emissions histogram in Figure 6-5) and the thin tail that extends above 30 GtC includes only a few scenarios.

Figure 6-6 shows the range of emissions of the four families (vertical bars next to each of the four marker scenarios), which illustrate that the scenarios groups by themselves cover a large portion of the overall scenario distribution. Together, they cover much of the range of future emissions, both with respect to the scenarios in the literature and all SRES scenarios. Adding all other scenarios increases the covered range. For example, the SRES scenarios span jointly from the 95^th percentile to just above the 5^th percentile of the distribution of energy and industry emissions scenarios from the literature. This illustrates again that they only exclude the most extreme emissions scenarios found in the literature, which are situated out in the tails of the distribution. What is perhaps more important is that each of the four scenario families covers a substantial part of this distribution. This leads to a substantial overlap in the emissions ranges of the four scenario families. In other words, a similar quantification of driving forces can lead to a wide range of future emissions and a given level of future emissions can result from different combinations of driving forces. This result is of fundamental importance for the assessments of climate change impacts and possible mitigation and adaptation strategies. Thus, it warrants some further discussion.

Another interpretation is that a given combination of the main driving forces, such as population and economic growth, is not sufficient to determine the future emissions paths. Different modeling approaches and different specifications of other scenario assumptions overshadow the influence of the main driving forces. A particular combination of driving forces, such as specified in the A1 scenario family, is associated with a whole range of possible emission paths for energy and industry. The nature of climate change impacts and adaptation and mitigation strategies would be fundamentally different depending on whether emissions are high or low, given a particular combination of scenario driving forces. Thus, the implication is that the whole range needs to be considered in the assessments of climate change, from high emissions and driving forces to low ones.

The A1 scenario family explored variations in energy systems most explicitly and hence covers the largest part of the scenario distribution shown in Figures 6-5 and 6-6a, from the 95th to just above the 10th percentile. The A1 scenario family includes different groups of scenarios that explore different structures of future energy systems, from carbon-intensive development paths to high rates of decarbonization. All groups otherwise share the same assumptions about the main driving forces (see Section 6.2.3 and, for further detail, Chapters 4 and 5). This indicates that different structures of the energy system can lead to basically the same variation in future emissions as 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.

Figure 6-6b shows that CO₂ emissions from deforestation peak in many SRES scenarios after several decades and subsequently gradually decline. This pattern is consistent with many scenarios in the literature and can be associated with slowing population growth and increasing agricultural productivity. These allow a reversal of current deforestation trends, leading to eventual CO₂ sequestration. Emissions decline fastest in the B1 family. Only in the A2 family do net anthropogenic CO₂ emissions from land use remain positive through to 2100. As was the case for energy-related emissions, CO₂ emissions related to land-use in the A1 family cover the widest range. The range of land-use emissions across the IS92 scenarios is narrower in comparison.

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