Emissions Scenarios - IPCC

100 An Overview of the Scenario Literature
2.4.12. Comparison of Indicators
Figure 2-13 illustrates the database distributions of COj,
population, gross world product, primary energy, and carbon
intensity of energy. The circles closest to the center denote the
minimum value of the distribution; the solid circles denote the
median value; and the shaded circles represml the maximum
database value for each variable. While the values are
connected in the form of a snowflake, it is important to note
that those of a given range (e.g., minimum, median, and
maximum), taken together, do not necessarily yield a
consistent or logically possible scenario. As is shown in
Chapter 4 (Figure 4-4), actual scenarios may fall into a median
range on some axes and into a higher or lower range on others.
Snowflake diagrams are useful because they allow the reader to
see at a glance the full range of values encompassed by the
database. Subsequent snowflake diagrams plot SRES scenario
values on the vaiious axes to illustrate where the scenarios fall
relative to the database minimum, median, and maximum
values. Snowflake diagrams should be used only for purposes
of scenario classification and interpretation and not for
scenario design, since the latter could lead to logical
inconsistencies.
2.5. Conclusions
In this chapter a brief overview and evaluation of the emissions
scenarios is presented. Much of the quantitative analysis of the
emissions scenarios is based on the unique scenario database
developed for SRES. This database, its structure, and the
process of assembling the data that it now contains are
described. The database provides a valuable overview of the
various emissions modeling approaches and scenarios in the
literature. It is the most comprehensive ESD available, and it
can be accessed tlirough a website (www-cger.nies.go.jp
/cger-e/db/ipcc.html).
The SRES database represents the basis for evaluations of
emissions scenarios, their main driving forces, and their
uncertainty ranges. The CO, emissions trajectories of the
scenarios in the SRES database are presented and their
distribution and the associated sample statistics assessed. In the
same way, the main driving forces of future emissions -
population, economic development and energy consumption -
are analyzed. Finally, the possible relationships among these
driving forces for the collection of emissions scenarios in the
database are considered.
Future levels of CO, emissions from the energy sector are a
function of population, gross world product, the structure and
efficiency of the economy, and the costs and availabihty of
different sources of energy.
The factor range for population increases by 2100 across the
scenarios is between 1.2 and 3.3 times 1990 levels (see Figure
2-4). This is the smallest factor increase of all the emissions
driving forces. This probably reflects a relatively high
consensus among demographers as to future population
growth. However, this observation is based on a relatively
small number of reported population projections in the
database (46). The range in projected gross world product
values is between 3.2 and 35 times the 1990 levels (see Figure
2-5). The range of the factor increase of primary energy
consumption is from 0.9 to 10 times 1990 levels (see Figure 2-
8). For energy intensity the range in 2100 is from 9.3 MJ/LJS$
down to 2.3 MJ/US$.
The range in carbon intensity of primary energy is the widest
range of all the driving forces considered here. It varies from
0.025 to l.I times 1990 levels (about a factor of 45) in the year
2100 (see Figure 2-11). Emissions trajectories are extremely
sensitive to a number of driving forces, which include
including population growth, economic growth, and energy
intensity improvement. Variation in carbon intensity is the
main indicator of the wide variation in energy-related COj.
However, it is important to recognize that this is a result of the
inputs, assumptions, methods, and types of models used to
calculate the scenarios.
The findings of the analysis of the scenarios in the literature
suggest the following general conclusions:
• the ranges over which the driving forces vary are large,
which contributes to the wide range of future
emissions;
• of these driving forces, gross world product and
population are often exogenous, while carbon and
energy intensity are not;
• the frequency distributions of driving forces and
emissions are asymmetric, with long tails and often
more than one peak;
• for many driving forces the median and mean are closer
to the minimum than to the maximum;
• lack of information as to whether climate intervention
policies and measures were included in the scenarios,
for about 40 scenarios, means that it is not possible to
distinguish between intervention and non-intervention
scenarios;
• it is hoped that IPCC or another international institution
will, in the futiu-e, maintain this or a similar .database so
as to assure a continuity of knowledge and scientific
progress in GHG emissions scenarios (an equivalent
database to document narrative and other qualitative
scenarios would also be very useful for future climatechange
assessments); and
• it would be useful in the future to evaluate the
consistency of the driving forces and results of all
scenarios included in the scenario database. In addition,
it would be helpful to extend the database to include
land-use change data where currentiy only land-use
emissions are presented. As noted above, only a small
percentage of scenarios contain information on land
use.