Of the GHGs, CO2 is the main contributor to anthropogenic radiative forcing because of changes in concentrations from pre-industrial times. According to Houghton et al. (1996) well-mixed GHGs (CO2 ,CH4 ,N2O, and the halocarbons) induced additional radiative forcing of around 2.5 W/m 2 on a global and annually averaged basis. CO2 accounted for 60% of the total, which indicates that the other GHGs are significant as well. Whereas CO2 emissions are by-and-large attributable to two major sources, energy consumption and land-use change, other emissions arise from many different sources and a large number of sectors and applications (e.g. see Table 5-3 in Chapter 5).
The SRES emissions scenarios also have different emissions for other GHGs and chemically active species such as carbon monoxide, nitrogen oxides, and non-methane volatile organic compounds. The uncertainties that surround the emissions sources of these gases, and the more complex set of driving forces behind them are considerable and unresolved. Hence, model projections of these gases are particularly uncertain and the scenarios presented here are no exception. Improved inventories and studies linking driving forces to changing emissions in order to improve the representation of these gases in global and regional emission models remain an important future research task. Therefore, the models and approaches 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 A1 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).
Anthropogenic CH4 emissions in the year 1990 are estimated at 375 ± 75 Mt CH4 in the second IPCC assessment (Prather et al., 1995). They arise from a variety of activities, dominated by biologic processes, each associated with considerable uncertainty. Future CH4 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 preferred diets and agricultural practices. For example, it is noted in Chapter 5 that the observed slowing of the rate of increase of CH4 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 CH4 emissions.
The resultant CH4 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 CH4 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 CH4 by 2100. The emissions level by 2100 for the B2 marker (600 Mt CH4) is about twice as high as in 1990 (310 Mt CH4) and ranges between 465 and 613 Mt CH4 for the other scenarios of the B2 family. In the A1B and B1 marker scenarios, the CH4 emissions level off and subsequently decline sooner or later in the 21st century. This phenomenon is most pronounced in the A1B 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 CH4 . The range of emissions in Table 6-2b indicate that alternative developments in energy technologies and resources could yield a higher range in CH4 emissions compared to the "balanced" technology A1 scenario group. In the two fossil fuel intensive scenario groups (A1C and A1G, combined into the non-fossil A1FI group in the Summary for Policymakers of this report), CH4 emissions could reach some 735 Mt CH4 by 2100, whereas in the post-fossil A1T scenario group emissions are correspondingly lower (some 300 Mt CH4 by 2100). Interestingly, the A1 scenarios generally have comparatively low CH4 emissions from non-energy sources because of a combination of low population growth 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 CH4 by 2100.
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