|Working Group III: Mitigation|
|Other reports in this collection|
22.214.171.124 Comparison of Quantified Stabilization Scenarios
Based on the storylines, 76 stabilization scenarios were quantified as shown in Table 2.6. The assessment of the post-SRES work in this section is restricted to the analysis of CO2 emissions and energy use in the different model runs. The detailed comparison of macroeconomic costs of reducing CO2 emissions costs is not dealt with here: Chapter 8 addresses this aspect of stabilization.
Figure 2.13 shows the CO2 emission trajectories of the 76 post-SRES mitigation scenarios along with the ranges of SRES and other published scenarios. Quantifications differ with respect to the baseline scenario including assumed storyline, the stabilization target, and the model that was used. As shown in Figure 2.13, the post-SRES scenarios cover a very wide range of emission trajectories, but the range is relatively below the SRES range, and they are apparently classified into groups according to the different stabilization targets. The figure shows the WRE late-response scenario and WGI early-action scenario for 550ppmv stabilization to compare with post-SRES scenarios, and it shows that the post-SRES range covers a much wider range than that between WRE and WGI.
Figure 2.14 shows the comparison of SRES and post-SRES scenario ranges in total global CO2 emissions. The post-SRES ranges are estimated based on the selected scenarios quantified by SRES participants in order to compare the formal SRES ranges in Nakicenovic et al. (2000). It is shown clearly in the figure that concentration stabilization requires much more reduction of CO2 emissions under development paths with high emissions such as A1FI and A2 than under development paths such as B1 and B2. These differences in reduction requirements result in selection of different technology and/or policy measures and, as a consequence, different costs to stabilize concentrations even at the same level. In the A1 scenario family, with its different scenarios in technological development (A1B, A1FI, and A1T), technological change is also a key component in bringing down the costs of mitigation options and their contribution to the emissions reduction. The A1FI stabilization scenarios, which are based on the highest baseline emissions, require much larger emission reductions than the A1T stabilization scenarios. The role of technology has been found to be crucial in the A1 scenario variants.
Morita et al. (2000a) compared all the stabilization variants in detail and
found several common characteristics among these scenarios. These findings are
In order to compare the scenarios in further detail, several indices were calculated for this review.
First, a CO2 reduction index was compared among stabilization levels as well as among SRES worlds. This index is calculated by subtracting baseline emissions from mitigation scenario emissions. In general, the lower the stabilization level that is required, as well as the higher the level of baseline emissions caused by the selected development path, the larger the CO2 divergence from the baseline that is needed in all the regions. However, it does not simply follow from the larger divergence in emissions that there is an earlier divergence from the baseline.
The impact on the timing of emission reduction of both the stabilization level and the baseline level of emissions is further elaborated in Figure 2.15. This figure shows when the reduction in energy-related CO2 emissions in each stabilization scenario would reach 20% of baseline emissions. This figure indicates that more stringent stabilization targets require earlier emission reductions from baseline levels. Higher emission worlds such as A1F1 and A2 also require earlier reduction than lower emission worlds such as A1T and B1.
A key policy question is what kind of emission reductions would be needed in the medium term, after the commitment period of the Kyoto Protocol (assuming that it will be implemented). Figure 2.16 shows the percent reduction in energy-related CO2 emissions in Annex I countries from 1990 for the various stabilization cases. Since the first commitment period of the Kyoto Protocol ends in 2012, this can give some indication of the extent to which emission reduction commitments after 2012 would be needed to achieve the various stabilization levels. It should be noted that about two thirds of the scenarios assume that developing countries have already diverged from their baseline emission trajectories in 2020. Another point is that the post-SRES scenarios were not developed specifically to include the Kyoto targets, so there is a range of Annex I emission reductions (from 1990 levels) in 2010, 2020 and 2030. The mid-course scenarios are indicated in Figure 2.16 as the range between the 25th and 75th percentiles of the frequency distribution of the scenarios.
Figure 2.16 shows that:
This suggests that achievement of stabilization at 450ppmv will require emissions reductions in Annex I countries by 2020 that go significantly beyond their Kyoto Protocol commitments for 2008 to 2012.15 It also suggests that it would not be necessary to go much beyond the Kyoto commitments for Annex I countries (assuming as indicated that developing countries diverge from their baselines by 2020) to achieve stabilization at 550ppmv or higher. However, it should be recognized that several scenarios do indicate the need for significant emission reductions by 2020 in order to achieve these stabilization levels. These findings should be interpreted in light of the facts that CO2 concentrations are assumed to reach one of the alternative fixed target levels in the year 2150, and unlike emission corridor analyses, these scenarios do not introduce other conditions such as a constraint on the rate of temperature increase.
Another important policy question concerns the participation of developing countries in emission mitigation. As a first step in addressing this question, the post-SRES scenarios were evaluated according to when per capita CO2 emissions in Annex I countries would fall below per capita emissions in non-Annex I countries, assuming that all CO2 emission reduction necessary for stabilization would occur in Annex I countries and that non-Annex I countries would emit CO2 without any controls. This hypothetical assumption permits the analysis of one of the determinants of when non-Annex I emissions might begin to diverge from baseline levels. The results are shown in Figure 2.17 for each stabilization level and for three groups of SRES baselines.
Figure 2.17 shows that:
In order to assess priority setting in energy intensity reduction or in carbon intensity reduction, a response index was calculated for all stabilization variants of post-SRES scenarios for the years 2020, 2050, and 2100, as shown in Figure 2.18. This index relates the impact on CO2 emission reduction of switching towards low-carbon or carbon free energy to the impact of energy intensity reduction. The response index is the ratio of the change in carbon intensity to the change in primary energy intensity16.
When energy intensity reduction is relatively larger than carbon intensity reduction, the index shows more than 1.0, and less than 1.0 in the opposite case.
It is clear from Figure 2.18 that the priority of response to reduce CO2 emissions would change over time. Energy intensity reduction would be relatively larger than carbon intensity reduction in the beginning of 21st century, but these would be of equal weight by the middle of the century. The impact of energy intensity reduction would be saturated towards the end of the 21st century, and the use of low-carbon or carbon-free energy sources would become relatively much larger. This pattern is generally consistent across the stabilization levels. The lower the stabilization target, the higher the relative importance of energy intensity reduction in the beginning of the 21st century, and the higher the relative importance of low-carbon or carbon free energy towards the end of the 21st century.
These trends are important, but it is necessary at the same time to understand the model assumptions behind them. Most of the models do not accommodate very well structural and consumption-pattern-related efficiency measures (e.g., advanced dematerialization, major structural change, and changes in consumption patterns and lifestyles). A few cases which incorporate drastic changes in social structure (e.g., some of the scenarios based on AIM and WorldScan) give relatively high priority to energy efficiency improvement even in the latter half of 21st century.
A per capita final energy index was calculated in order to analyze equity between North and South. Since one of the weak points of quantified scenario analysis concerns equity or burden sharing, the comparison of this kind of index is very important. Even though the per capita income is the most popular index to analyze equity, this index was not estimated by all the modelling teams. Therefore, final energy consumption per person in each region was adopted as an appropriate index for the equity analysis, because this index is closely related to per capita economic welfare. Figure 2.19 shows this index (in GJ/capita) among the OECD, EFSU, ASIA and ALM regions17 for all post-SRES and SRES variants over the period 1990 to 2100.
As shown in this figure, some interesting trends can be observed:
Though the analyses described above mainly focus on CO2 emissions from energy consumption, it is also important to consider non-CO2 emissions as well as non-energy-related CO2 emissions. However, very few scenarios that include these emissions have been quantified and therefore it was not possible to include this additional review in this report. Some of the nine modelling approaches used here do include other radiatively active gases. However, the mitigation and/or stabilization scenarios include explicit limitations only on CO2 emissions, and hence the reductions in other gases are indirect results (or ancillary benefits) of the CO2 reduction measures.
Other reports in this collection