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Non-CO2 GHGs (CH4 ,N2O, and halocarbons) account for about 40% of the total induced additional radiative forcing compared to pre-industrial times (Houghton et al., 1996). Whereas CO2 emissions are largely attributable to two major sources (energy and land use), other gases arise from many different sectors and applications as shown in Table 5-3. Consequently, their emission levels are more uncertain. Also the base-year emissions of non-CO2 GHGs are subject to considerable uncertainty, in particular when it comes to regional and sectoral breakdowns.
Emissions of non-CO2 radiatively important gases are subject to considerable and unresolved uncertainties and are driven by a more complex set of forces than CO2 emissions. Therefore, the types of models employed for the SRES analyses are not expected to produce unambiguous and widely approved estimates of emissions of these gases for a period of over a century. Despite the limited knowledge, at some point in time causal relationships between driving forces and non-CO2 emissions need to be crafted into the models for the sake of completeness. Even if new insights are generated by specialist researchers in certain fields of environmental science, and these become accepted as the mainstream view, their adoption in the models is often far from straightforward, as appropriate links to drivers may not be readily available in the underlying structure. Limited manpower 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 abilities to capture major trends at a more aggregate level, the main purpose of these models.
In the following sections emission trajectories generated in the SRES scenarios are presented and discussed. However, model structures and properties, and exogenous assumptions made by the modelers involved, may give rise to systematic deviations within scenario families that may prove very significant compared to average inter-family differences. Further investigation and analysis is required to understand these issues more fully.
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