Emissions Scenarios - IPCC

310 Summary Discussions and Recommendations
employed for the SRES analyses cannot produce unambiguous
and generally approved estimates for different sources and
world regions over a century. Despite the limited knowledge, at
some point in time causal relationships between driving forces
and emissions need to be crafted into the models for the sake
of completeness. Even if new insights are generated by
research specialists in certain fields of environmental science,
and these become accepted as mainstream view, adopting them
in the models is often far from straightforward as appropriate
links to drivers may not be readily available in the underlying
model structures. Limited personnel and resources imply that
priorities must be assigned when deciding on further model
development, and as a consequence the models lag behind
"common wisdom" in certain areas. Of course, this does not
necessarily limit their capabilities to capture major trends at a
more aggregate level, which is the main purpose of these
models.
Keeping the caveats above in mind. Table 6-2b (see later)
shows the emissions in 2100 of all relevant direct and indirect
GHGs for the four marker scenarios and, in brackets, the range
of the other scenarios in the same family (or scenario groups
for the Al family). Chapter 5 gives further detail about the full
range of GHG emissions across the SRES scenarios. Table 6-
2b also compares the SRES scenarios emissions range to that
of the IS92 scenario series (Pepper et al.. 1992).
6.3.2.1. Methane Emissions
Anthropogenic CH^ emissions in the year 1990 are estimated
at 375 ± 75 Mt CH^ in the second IPCC assessment (Prather et
ai, 1995). They arise from a variety of activities, dominated by
biologic processes, each associated with considerable
uncertainty. Future CH^ emissions in the scenarios depend in
part on the consumption of fossil fuels, adjusted for assumed
changes in technology and operational practices, but more
strongly on scenario-specific, regional demographic and
affluence developments, together with assumptions on
prefeiTcd diets and agricultural practices. For example, it is
noted in Chapter 5 that the observed slowing of the rate of
increase of CH^ concentrations in recent years might indicate
that the emission factors that link emissions to changes in their
drivers could be changing. The writing team recommends
further research into the sources and modeling approaches to
capture large uncertainties surrounding future CH^ emissions.
The resultant CH^ emissions trajectories for the four SRES
markers and other scenarios in the four families portray
complex patterns (as displayed in Figure 5-5 in Chapter 5). For
example, the emissions in A2 and B2 marker scenarios increase
throughout the whole time horizon to the year 2100. This
increase is most pronounced in the A2 marker scenario, in
which emissions reach about 900 Mt CH^ by 2100 (about a
three-fold increase since 1990). The range for other scenarios
in the A2 scenario family is between 549 and 1069 Mt CH^ by
2100. The emissions level by 2100 for the B2 marker (600 Mt
СЩ) is about twice as high as in 1990 (310 Mt CH^) and
ranges between 465 and 613 Mt CH, for the other scenarios of
the B2 family. In the AlB and Bl marker scenarios, the CH4
emissions level off and subsequently decline sooner or later in
the 2V^ century. This phenomenon is most pronounced in the
AlB marker, in which the fastest growth in the first few
decades is followed by the steepest decline; the 2100 level ends
up slightly below the current emission of 310 Mt CH^. The
range of emissions in Table 6-2b indicate that alternative
developments in energy technologies and resources could yield
a higher range in CH^ emissions compared to the "balanced"
technology Al scenario group. In the two fossil fuel intensive
scenario groups (AlC and AIG, combined into the non-fossil
AlFI group in the Summary for Policymakers of this report),
CH4 emissions could reach some 735 Mt CH^ by 2100,
whereas in the post-fossil AIT scenario group emissions are
correspondingly lower (some 300 Mt CH^ by 2100).
Interestingly, the Al scenarios generally have comparadvely
low CH4 emissions from non-energy sources because of a
combination of low population gfowth and rapid advances in
agricultural productivity. Hence the SRES scenarios extend the
uncertainty range of the IS92 scenario series somewhat toward
lower emissions. However, both scenario sets indicate an upper
bound of emissions of some 1000 Mt CH^ by 2100.
6.3.2.2. Nitrous Oxide Emissions
Even more than for CH^, the assumed future food supply will
be a key determinant of future N,0 emissions. Size, age
structure, and regional spread of the global population will be
reflected in the emissions trajectories, together with
assumptions on diets and improvements in agricultural
practices. Again, as for CH^ in the SRES scenarios (see Section
5.4.1 in Chapter 5), continued growth of NjO emissions
emerges only in the A2 scenario, largely because of high
population growth. In the other three marker scenarios,
emissions peak and then decline sooner or later in the course of
the 2P' century. Importantiy, as the largest anthropogenic
source of NjO (cultivated soils) is already very uncertain in the
base year, all future emissions trajectories are affected by large
uncertainties, especially if calculated with different models, as
is the case in this SRES report. Therefore, the writing team
recommends further research into the souices and modeling of
long-term N,0 emissions. Uncertainty ranges are
correspondingly large, and are sometimes asymmetric. For
example, while the range in 2100 reported in all Al scenarios
is between 5 and 10 MtN (7 MtN in the AlB marker), the A2
marker reports 17 MtN in 2100. Other A2 scenarios report
emissions that fall within the range reported for Al (from 8 to
19 MtN in 2100). Thus, different model representations of
processes that lead to NjO emissions and uncertainties in
source strength can outweigh easily any underlying differences
between individual scenarios in terms of population growth,
economic development, etc. Different assumptions with
respect to future crop productivity, agricultural practices, and
associated emission factors, especially in the very populous
regions of the world, explain the very different global emission
levels even for otherwise shared main scenario drivers. Hence,
the SRES scenarios extend the uncertainty range of future
emissions significantly toward higher emissions (4.8 to 20,2