3.3.2 Definition of a stabilization target
Mitigation scenarios explore the feasibility and costs of achieving specified climate change or emissions targets, often in comparison to a corresponding baseline scenario. The specified target itself is an important modelling and policy issue. Because Article 2 of United Nations Framework Convention on Climate Change (UNFCCC) states as its objective the ‘stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system’, most long-term mitigation studies have focused their efforts on GHG concentration stabilization scenarios. However, several other climate change targets may be chosen, for example the rate of temperature change, radiative forcing, or climate change impacts (see e.g. Richels et al., 2004; Van Vuuren et al., 2006b; Corfee-Morlot et al., 2005). In general, selecting a climate policy target early in the cause-effect chain of human activities to climate change impacts, such as emissions stabilization, increases the certainty of achieving required reduction measures, while increasing the uncertainty on climate change impacts (see Table 3.4). Selecting a climate target further down the cause-effect chain (e.g. temperature change, or even avoided climate impacts) provides for greater specification of a desired climate target, but decreases certainty of the emission reductions required to reach that target.
Table 3.4: Advantages and disadvantages of using different stabilization targets.
| Target | Advantages | Disadvantages |
|---|
| Mitigation costs | Lowest uncertainty on costs. | Very large uncertainty on global mean temperature increase and impacts. Very large uncertainty on global mean temperature increase and impacts. Either needs a different metric to allow for aggregating different gases (e.g. GWPs) or forfeits opportunity of substitution. |
| Emissions mitigation | Lower uncertainty on costs. | Does not allow for substitution among gases, thus losing the opportunity for multi-gas cost reductions. Indirect link to the objective of climate policy (e.g. impacts). |
| Concentrations of different greenhouse gases | Can be translated relatively easily into emission profiles (reducing uncertainty on costs). | Allows a wide range of CO2-only stabilization targets due to substitutability between CO2 and non-CO2 emissions. |
| Radiative forcing | Easy translation to emission targets, thus not including climate sensitivity in costs calculations. Does allow for full flexibility in substitution among gases. Connects well to earlier work on CO2 stabilization. Can be expressed in terms of CO2-eq concentration target, if preferred for communication with policymakers. | Indirect link to the objective of climate policy (e.g. impacts). |
| Global mean temperature | Metric is also used to organize impact literature; and as has shown to be a reasonable proxy for impacts | Large uncertainty on required emissions reduction as result of the uncertainty in climate sensitivity and thus costs. |
| Impacts | Direct link to objective of climate polices. | Very large uncertainties in required emission reductions and costs. |
A commonly used target has been the stabilization of the atmospheric CO2 concentration. If more than one GHG is included, most studies use the corresponding target of stabilizing radiative forcing, thereby weighting the concentrations of the different gases by their radiative properties. The advantage of radiative forcing targets over temperature targets is that the consequences for emission trajectories do not depend on climate sensitivity, which adds an important uncertainty. The disadvantage is that a wide range of temperature impacts is possible for each radiative forcing level. By contrast, temperature targets provide a more direct first-order indicator of potential climate change impacts, but are less practical to implement in the real world, because of the uncertainty about the required emissions reductions.
Another approach is to calculate risks or the probability of exceeding particular values of global annual mean temperature rise (see also Table 3.9). For example, Den Elzen and Meinshausen (2006) and Hare and Meinshausen (2006) used different probability density functions of climate sensitivity in the MAGICC simple climate model to estimate relationships between the probability of achieving climate targets and required emission reductions. Studies by Richels et al. (2004), Yohe et al. (2004), Den Elzen et al. (2006), Keppo et al. (2006), and Kypreos (2006) have used a similar probabilistic concept in an economic context. The studies analyze the relationship between potential mitigation costs and the increase in probability of meeting specific temperature targets.
The choice of different targets is not only relevant because it leads to different uncertainty ranges, but also because it leads to different strategies. Stabilization of one type of target, such as temperature, does not imply stabilization of other possible targets, such as rising sea levels, radiative forcing, concentrations or emissions. For instance, a cost-effective way to stabilize temperature is not radiative forcing stabilization, but rather to allow radiative forcing to peak at a certain concentration, and then decrease with additional emissions reductions so as to avoid (delayed) further warming and stabilize global mean temperature (see Meinshausen, 2006; Kheshgi et al., 2005; Den Elzen et al., 2006). Finally, targets can also be defined to limit a rate of change, such as the rate of temperature change. While such targets have the advantage of providing a link to impacts related to the rate of climate change, strategies to achieve them may be more sensitive to uncertainties and thus, require careful planning. The rate of temperature change targets, for instance, may be difficult to achieve in the short-term even, using multi-gas approaches (Manne and Richels, 2006; Van Vuuren et al., 2006a).