Emissions Scenarios - IPCC

36 Technical Summary
Figure TS-5 illustrates that land-use patterns are also diverging
over time. It shows the main land-use categories - the
percentages of total land area use that constitute the forests, the
joint shares of cropland and energy biomass, and all the other
categories including grasslands. As for the energy triangle in
Figure TS-4, in Figure TS-5 each comer coiTesponds to a
hypothetical situation in which land use is dedicated to a much
greater extent than today to two of the three land-use categories
- 40% to cropland and energy biomass and 20% to forests at
the top, 60% to forests and 40% to other categories (including
grasslands) to the left, and 80% to other categories (including
grasslands) to the right.
In most scenarios, the current trend of shrinking forests is
eventually reversed because of slower population growth and
increased agricultural productivity. Reversals of deforestation
trends are strongest in the В1 and Al families. In the В1 family
pasture lands decrease significantly because of increased
productivity in livestock management and dietary shifts away
from meat, thus illustrating the importance of both
technological and social developments.
The main driving forces for land-use changes are related to
increasing demands for food because of a growing population
and changing diets. In addition, numerous other social,
economic, and institutional factors govern land-use changes
such as deforestation, expansion of cropland areas, or their
reconversion back to forest cover (see Chapter 3). Global food
production can be increased, either through intensification (by
multi-cropping, raising cropping intensity, applying fertilizers,
new seeds, improved farming technology) or through land
expansion (cultivating land, converting forests). Especially in
developing countries, there are many examples of the potential
to intensify food production in a more or less ecological way
(e.g. multi-cropping; agroforestry) that may not lead to higher
GHG emissions.
Different assumptions on these processes translate into
alternative scenarios of future land-use changes and GHG
emissions, most notably CO^, methane (CH^), and nitrous
oxide (NjO). A distinguishing characteristic of several models
(e.g., AIM, IMAGE, MARIA, and MiniCAM) used in SRES is
the explicit modeling of land-use changes caused by expanding
biomass uses and hence exploration of possible land-use
conflicts between energy and agricuhural sectors. The
corresponding scenarios of land-use changes are illustrated in
Figure TS-5 for all SRES scenarios. In some contrast to the
structural changes in energy systems shown in Figure TS-4,
different land-use scenarios in Figure TS-5 appear to be rather
model specific, following the general trends as indicated by the
respective marker scenario developed with a particular model.
9. 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 CO2, CH^, and SO,. For
simplicity, only these three important gases are presented
separately, following the more detailed exposition in Chapter 5
(see Table TS-4 for a summary of the ranges of emissions
across the scenario groups).
9,1. Carbon Dioxide Emissions
9.1.1. Carbon Dioxide Emissions and Their Driving Forces
Figure TS-6 illustrates the CO2 emissions across the SRES
scenarios in relation to each of the thi-ee main scenario driving
forces - global population, gross world product and primary
energy requirements. The general tendencies across the driving
forces are consistent with the underlying literature. All else
being equal, the higher future global populations, higher gross
world product, or higher primary energy requirements would
be associated with higher emissions. However, it is important
to note that the range of emissions is large across the whole
range of driving forces considered in SRES, indicating the
magnitude of the uncertainty associated with emission
scenarios. For instance, emissions can range widely for any
given level of future population (e.g. between 5 to 20 GtC in
case of a low population scenario of seven billion by 2100).
Conversely, emissions in the range of 20 GtC are possible with
global population levels ranging from seven to 15 billion by
2100. While the SRES scenarios do not map all possibilities,
they do indicate general tendencies, with an uncertainty range
consistent with the underlying literature. This emphasizes an
important SRES conclusion: alternative combinations of main
scenario driving forces can lead to similar levels of GHGs
emissions by the end of the 2P' century. Alternatively, similar
future worlds with respect to socio-economic developments
can result in wide differences in future GHGs emissions,
primarily as a result of alternative technological developments.
This suggests that technology is at least as important a driving
force of future GHG emissions as population and economic
development across the set of 40 SRES scenarios.
9.1.2. Carbon Dioxide Emissions from Energy, Industry, and
Land Use
Figure TS-7 illustrates the range of COj emissions of the SRES
scenarios against the background of all the IS92 scenaiios and
other emissions scenarios from the literature documented in the
SRES scenario database (blue shaded area). The range of
future emissions is very large so that the highest scenarios
envisage a tenfold 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