A commonly used target in the literature is stabilization of CO2 concentrations in the atmosphere. If more than one GHG is studied, a useful alternative is to formulate a GHG-concentration target in terms of CO2-equivalent concentration or radiative forcing, thereby weighting the concentrations of the different gases by their radiative properties. Another option is to stabilize or target global mean temperature. The advantage of radiative-forcing targets over temperature targets is that the calculation of radiative forcing does not depend on climate sensitivity. The disadvantage is that a wide range of temperature impacts is possible for each radiative-forcing level. Temperature targets, on the other hand, have the important advantage of being more directly linked to climate change impacts. Another approach is to calculate the risks or the probability of exceeding particular values of global annual mean temperature rise since pre-industrial times for specific stabilization or radiative-forcing targets.
There is a clear and strong correlation between the CO2-equivalent concentrations (or radiative forcing) and the CO2-only concentrations by 2100 in the published studies, because CO2 is the most important contributor to radiative forcing. Based on this relationship, to facilitate scenario comparison and assessment, stabilization scenarios (both multi-gas and CO2-only studies) have been grouped into different categories that vary in the stringency of the targets (Table TS.2).
Table TS.2: Classification of recent (Post-Third Assessment Report) stabilization scenarios according to different stabilization targets and alternative stabilization metrics [Table 3.5]. Errata
|Category ||Additional radiative forcing (W/m2) ||CO2 concentration (ppm) ||CO2-eq concentration (ppm) ||Global mean temperature increase above pre-industrial at equilibrium, using “best estimate” climate sensitivitya), b) (ºC) ||Peaking year for CO2 emissionsc) ||Change in global CO2 emissions in 2050 (% of 2000 emissions)c) ||No. of assessed scenarios |
|I ||2.5-3.0 ||350-400 ||445-490 ||2.0-2.4 ||2000 - 2015 ||-85 to -50 ||6 |
|II ||3.0-3.5 ||400-440 ||490-535 ||2.4-2.8 ||2000 - 2020 ||-60 to -30 ||18 |
|III ||3.5-4.0 ||440-485 ||535-590 ||2.8-3.2 ||2010 - 2030 ||-30 to +5 ||21 |
|IV ||4.0-5.0 ||485-570 ||590-710 ||3.2-4.0 ||2020 - 2060 ||+10 to +60 ||118 |
|V ||5.0-6.0 ||570-660 ||710-855 ||4.0-4.9 ||2050 - 2080 ||+25 to +85 ||9 |
|VI ||6.0-7.5 ||660-790 ||855-1130 ||4.9-6.1 ||2060 - 2090 ||+90 to +140 ||5 |
|Total ||177 |
Essentially, any specific concentration or radiative-forcing target requires emissions to fall to very low levels as the removal processes of the ocean and terrestrial systems saturate. Higher stabilization targets do push back the timing of this ultimate result beyond 2100. However, to reach a given stabilization target, emissions must ultimately be reduced well below current levels. For achievement of the stabilization categories I and II, negative net emissions are required towards the end of the century in many scenarios considered (Figure TS.8) (high agreement, much evidence) [3.3.5].
Figure TS.8: Emission pathways of mitigation scenarios for alternative categories of stabilization targets (Category I to VI as defined in the box in each panel). Lightbrown shaded areas give the CO2 emissions for the recent mitigation scenarios developed post-TAR. Green shaded and hatched areas depict the range of more than 80 TAR stabilization scenarios (Morita et al., 2001). Category I and II scenarios explore stabilization targets below the lowest of TAR. Base year emissions may differ between models due to differences in sector and industry coverage. To reach the lower stabilization levels some scenarios deploy removal of CO2 from the atmosphere (negative emissions) using technologies such as biomass energy production utilizing carbon capture and storage [Figure 3.17].
The timing of emission reductions depends on the stringency of the stabilization target. Stringent targets require an earlier peak in CO2 emissions (see Figure TS.8). In the majority of the scenarios in the most stringent stabilization category (I), emissions are required to decline before 2015 and be further reduced to less than 50% of today’s emissions by 2050. For category III, global emissions in the scenarios generally peak around 2010–2030, followed by a return to 2000 levels on average around 2040. For category IV, the median emissions peak around 2040 (Figure TS.9) (high agreement, much evidence).
Figure TS.9: Relationship between the cost of mitigation and long-term stabilization targets (radiative forcing compared with pre-industrial level, W/m2 and CO2-eq concentrations) [Figure 3.25].
Notes: Panels give costs measured as percentage loss of GDP (top), and carbon price (bottom). Left-hand panels for 2030, middle panels for 2050 and right-hand panels for 2100. Individual coloured lines denote selected studies with representative cost dynamics from very high to very low cost estimates. Scenarios from models sharing similar baseline assumptions are shown in the same colour. The grey shaded range represents the 80th percentile of TAR and post-TAR scenarios. Solid lines show representative scenarios considering all radiatively active gases. Dashed lines represent multi-gas scenarios where the target is defined by the six Kyoto gases (other multi-gas scenarios consider all radiatively active gases). CO2 stabilization scenarios are added based on the relationship between CO2 concentration and the radiative-forcing targets given in Figure 3.16.
The costs of stabilization depend on the stabilization target and level, the baseline and the portfolio of technologies considered, as well as the rate of technological change. Global mitigation costs rise with lower stabilization levels and with higher baseline emissions. Costs in 2050 for multi-gas stabilization at 650 ppm CO2-eq (cat IV) are between a 2% loss or a one procent increase of GDP in 2050. For 550 ppm CO2-eq (cat III) these costs are a range of a very small increase to 4% loss of GDP. For stabilization levels between 445 and 535 ppm CO2-eq. costs are lower than 5.5% loss of GDP, but the number of studies is limited and they generally use low baselines.
A multi-gas approach and inclusion of carbon sinks generally reduces costs substantially compared with CO2 emission abatement only. Global average costs of stabilization are uncertain, because assumptions on baselines and mitigation options in models vary a lot and have a major impact. For some countries, sectors or shorter time periods, costs could vary considerably from the global and long-term average (high agreement, much evidence) [3.3.5].
Figure TS.10: Cumulative emission reductions for alternative mitigation measures for 2000–2030 (left-hand panel) and for 2000–2100 (right-hand panel). The figure shows illustrative scenarios from four models (AIM, IMAGE, IPAC and MESSAGE) aiming at the stabilization at low (490–540 ppm CO2-eq) and intermediate levels (650 ppm CO2-eq) respectively. Dark bars denote reductions for a target of 650 ppm CO2-eq and light bars the additional reductions to achieve 490–540 ppm CO2-eq. Note that some models do not consider mitigation through forest sink enhancement (AIM and IPAC) or CCS (AIM) and that the share of low-carbon energy options in total energy supply is also determined by inclusion of these options in the baseline. CCS includes carbon capture and storage from biomass. Forest sinks include reducing emissions from deforestation [Figure 3.23].
Recent stabilization studies have found that land-use mitigation options (both non-CO2 and CO2) provide cost-effective abatement flexibility in achieving 2100 stabilization targets. In some scenarios, increased commercial biomass energy (solid and liquid fuel) is significant in stabilization, providing 5–30% of cumulative abatement and potentially 10–25% of total primary energy over the century, especially as a net negative emissions strategy that combines biomass energy with CO2 capture and storage.
The baseline choice is crucial in determining the nature and cost of stabilization. This influence is due mainly to different assumptions about technological change in the baseline scenarios.