Emissions Scenarios - IPCC

304 Summaiy Discussions and Recommendations
characteristic of several models (e.g., AIM, IMAGE, MARIA,
and MiniCAM) used in SRES is the explicit modeling of landuse
changes caused by expanding biomass uses and hence
exploration of possible land-use conflicts between energy and
agricultural sectors. The corresponding scenarios of land-use
changes are illustrated in Figure 6-4 for all SRES scenarios. In
some contrast to the structural changes in energy systems
shown in Figure 6-3, different land-use scenarios in Figure 6-4
appear to be rather model specific, following the general trends
as indicated by the respective marker scenario developed with
a particular model.
6.3. Greenhouse Gases and Sulfur Emissions
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 CO,, CH4, and SO,. 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 CO, 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
CO, 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-inodal
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
N = 40 Scenarios
0 I 1 1 I I 1—
1990 2010 2030 2050 2070 2090
Relative Frequency (%)
Figure 6-5: Global energy-related and industrial CO2 emissions for the 40 SRES scenarios. The individual scenarios are shown
grouped into four scenario families. Marker scenarios are shown as bold continuous lines and the other 36 scenarios as dashed
lines. The emissions profiles are dynamic, ranging from continuous increases to those that curve through a maximum and then
decline. The relative positions of the scenarios change in time, with numerous cross-overs among the individual emissions
trajectories. The histogram on the right shows, for comparison, the frequency distribution of energy-related and industrial COj
emissions based on the scenario database. The histogram indicates the relative position of the four marker scenarios and the six
IS92 scenarios compared to the emissions in the literature. Jointly, the SRES scenarios span most of the range of scenarios in
the literature.