3.6.2.2 Assessment of reduction levels at different marginal prices

To put these identified mitigation opportunities into context they will be compared with mitigation estimates from bottom-up models. Chapters 4 through 10 describe mitigation technologies available in specific economic sectors. Chapter 11, Section 11.3 compares the short-term mitigation estimates across all of the economic sectors for selected marginal costs levels (20, 50 and 100 US$/tCO₂-eq). For that purpose, we have plotted the permit price and (sectoral) reduction levels of the different studies. These plots have been used to explore whether the combination of the studies suggests certain likely reduction levels at the three target levels of 20, 50 and 100 US$/tCO₂-eq. As far more studies were available that reported economy-wide reduction levels than the ones that provided sectoral information, we were able to use a formal statistical method for the former. For the latter, a statistical method was also applied, but outcomes have been used with more care.

Economy-wide reduction levels

Figure 3.40 shows the available data from studies that report economy-wide reduction levels (multi-gas) and permit prices. The data has been taken from the emission scenario database (Hanaoka et al., 2006; Nakicenovic et al., 2006) – and information directly reported in the context of EMF-21 (De la Chesnaye and Weyant, 2006) and IMCP (Edenhofer et al., 2006). The total sets suggest some form of a relationship with studies reporting higher permit prices: also, in general, reporting higher reduction levels.

Figure 3.40: Permit price versus level of emission reduction – total economy in 2030 (the natural logarithm of the permit price is used for the x-axis). The uncertainty range indicated is the 68% interval.

Obviously, a considerable range of results is also found – this is a function of factors such as:

• Model uncertainties, including technology assumptions and inertia.
• Assumed baseline developments.
• The trajectory of the permit price prior to 2030.

The suggested relationship across the total is linear if permit prices are plotted on a logarithmic scale as shown in Figure 3.40. In other words, the relationship between the two variables is logarithmic, which is a form that is consistent with the general form of marginal abatement curves reported in literature: increasing reduction levels for higher prices, but diminishing returns at higher prices as the reduction tends to reach a theoretical maximum. The figure not only shows the best-guess regression line, but also 68% confidence interval. The latter can be used to derive the 68 percentile interval of the reduction potential for the 20 and 100 US$/tCO₂-eq price levels, which are 13.3 ± 4.6 GtCO₂-eq/yr and 21.5 ± 4.7 GtCO₂-eq/yr, respectively.

Figure 3.41: Permit price versus emission reduction level – several sectors in 2030 (vertical lines indicate levels at 20, 50 and 100 US$/tCO₂).

Sectoral estimates

A more limited set of studies reported sectoral reduction levels. The same plot as Figure 3.40 has been made for the sectoral data (see Figure 3.41), again plotting the logarithm of the permit price against emission reduction levels. The data here are directly taken from Table 3.13 and Table 3.14. As less data are available, the statistical analysis becomes less robust. Nevertheless, for most sectors, a similarly formed relationship was found across the set of studies as for the economy-wide potential (logarithmic relationship showing increasing reduction levels at relatively low prices, and a much slower increase at higher prices). As expected, in several sectors, the spread across models in the 2030 set is larger than in the economy-wide estimates.

In general, a relatively strong relationship is found in the sectors for energy supply, transport, and industrial energy consumption. The relationship between the price and emission reduction level is less clear in other sectors – and more-or-less absent for the limited reported data on the forestry sector. It should be noted here that definitions across studies may be less well-defined – and also, forest sector emissions may actually increase in mitigation scenarios as a result of net deforestation due to bio-energy production.

It should be noted that emission data (and thus also reduction levels) are reported on a ‘point of emission basis’ (emissions are reported for the sectors in which the emissions occur). For example, the efficiency improvements in end-use sectors for electricity lead to reductions in the energy supply sector. Likewise, using bio-energy leads to emission reductions in the end-use sectors, but at the same time (in some models) may lead to increases in emissions for forestry, due to associated land-use changes. The latter may explain differences in the way that data from top-down models are represented elsewhere in this report, as here (in most cases) only the emission changes from mitigation measures in the forestry sector itself are reported. It also explains why the potential in some of the end-use sectors is relatively small, as emission reductions from electricity savings are reported elsewhere.

Reported estimates

On the basis of the available data, the following ranges have been estimated for the reduction potential at a 20, 50 and 100 US$/tCO₂-eq price (Table 3.15). As estimates have been made independently, the total of the different sectors does not add up to the overall range (as expected, the sum of the sectors gives a slightly wider range).

Table 3.15: Reduction potential at various marginal prices, averages across different models (low and high indicate one standard deviation variation).

Note: 1) The overall potential has been estimated separately from the sectoral totals.

The largest potential is found in energy supply – covering both the electricity sector and energy supply – with a relatively high capability of responding to permit prices. Relatively high reduction levels are also found for the industry sector. Relatively small reduction levels are reported for the forestry sector and the waste management sector.