IPCC Fourth Assessment Report: Climate Change 2007
Climate Change 2007: Working Group III: Mitigation of Climate Change Non-CO2 greenhouse gas emissions

The emissions scenario chapter in the TAR (Morita et al., 2001) recommended that future research should include GHGs other than CO2 in new scenarios work. The reason was that, at that time, certainly regarding mitigation, most of the scenarios literature was still primarily focused on CO2 emissions from energy. Nevertheless, some multi-gas scenario work existed, including the SRES baseline scenarios, but also some other modelling efforts (Manne and Richels, 2001; Babiker et al., 2001; Tol, 1999). The most important non-CO2 gases include: methane (CH4), nitrous oxide (N2O), and a group of fluorinated compounds (F-gases, i.e., HFCs, PFCs, and SF6). Since the TAR, the number of modelling groups producing long-term emission scenarios for non-CO2 gases has dramatically increased. As a result, the quantity and quality of non-CO2 emissions scenarios has improved appreciably.

Unlike CO2 where the main emissions-related sectors are few (i.e. energy, industry, and land use), non-CO2 emissions originate from a larger and more diverse set of economic sectors. Table 3.2 provides a list of the major GHG emitting sectors and their corresponding emissions, estimated for 2000. Note that there is significant uncertainty concerning emissions from some sources of the non-CO2 gases, and the table summarizes the central values from Weyant et al. (2006) which has been used in long-term multi-gas scenario studies of the EMF-21. To make the non-CO2 emissions comparable to those of CO2, the common practice is to compare and aggregate emissions by using global warming potentials (GWPs).

Table 3.2: Global Anthropogenic GHG Emissions for 2000 at sector level, as used in EMF-21 studies (MtCO2-eq/yr).

Sector sub-total & percent of total Sub-sectors CO2 CH4 N2F-gases 
ENERGY  Coal  8,133  451      
 Natural gas 4,800 895     
25,098  Petroleum syst.  10,476 62      
67% Stationary/Mobile sources   59 224   
LUCFa and AGRICULTURE  LUCF and agriculture (net)  3,435       
 Soils     2,607   
 Biomass    491  187    
9,543  Enteric fermentationManure management    1,745224  -205    
25% Rice   649   
INDUSTRY Cement 829       
 Adipic & nitric acid productionHFC-23      158 95  
1,434 PFCsSF6        10655  
4% Substitution of ODSb       191 
WASTE Landfills   781     
1,448  Wastewater    565  81    
4% Other   11 11   
Total all GHG 37,524 27,671 5,933 3,472 447 
 Gas as percent of total 74% 16% 9% 1% 

Notes: a LUCF is Land-use change and forestry.

b HFCs are used as substitutes for ODSs in a range of applications

Sources: Weyant et al, 2006.

The most important work on non-CO2 GHG emissions scenarios has been done in the context of EMF-21 (De la Chesnaye and Weyant, 2006). The EMF-21 study updated the capability of long-term integrated assessment models for modelling non-CO2 GHG emissions. The results of the study are illustrated in Figure 3.11.

Figure 3.11

Figure 3.11: Development of baseline emissions in the EMF-21 scenarios (left) and comparison between EMF21 and SRES scenarios (right).

Source: De la Chesnaye and Weyant , 2006; see also Van Vuuren et al., 2006b

Evaluating the long-term projections of anthropogenic methane emissions from the EMF-21 data shows a significant range in the estimates, but this range is consistent with that found in the SRES. The methane emission differences in the SRES are due to the different storylines. The differences in the EMF-21 reference cases are mainly due to changes in the economic activity level projected in key sectors by each of the models[6]. This could include, for example, increased agriculture production or increased supply of natural gas and below-ground coal in the energy sector. In addition, different modelling groups employed various methods of representing methane emissions in their models and also made different assumptions about how specific methane emission factors for each economic sector change over time. Finally, the degree to which agricultural activities are represented in the models differs substantially. For example, some models represent all agricultural output as one large commodity, ‘agriculture’, while others have considerable disaggregation. Interestingly, the latter group of models tend to find slower emissions growth rates (see Van Vuuren et al., 2006b).

The range of long-term projections of anthropogenic nitrous oxide emissions is wider than for methane in the EMF-21 data. Note that for N2O, base year emissions of the different models differ substantially. Two factors may contribute to this. First, different definitions exist as to what should be regarded as human-induced and natural emissions in the case of N2O emissions from soils. Second, some models do not include all emission sources.

The last group of non-CO2 gases are fluorinated compounds, which include hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulphur hexafluoride (SF6). The total global emissions of these gases are almost 450 MtCO2-eq, or slightly over 1% of all GHG for 2000. While the emissions of some fluorinated compounds are projected to decrease, many are expected to grow substantially because of the rapid growth rate of some emitting industries (e.g. semiconductor manufacture and magnesium production and processing), and the replacement of ozone-depleting substances (ODSs) with HFCs. Long-term projections of these fluorinated GHGs are generated by a fewer number of models, but still show a wide range in the results over the century. Total emissions of non-CO2 GHGs are projected to increase, but somewhat less rapidly than CO2 emissions, due to agricultural activities growing less than energy use.

  1. ^  In the EMF-21 study, reference case scenarios were considered to be ‘modeller’s choice’, where harmonization of input parameters and exogenous assumptions was not sought.