11 Mitigation from a cross-sectoral perspective
Mitigation options across sectors
While many of the technological, behavioural and policy options mentioned in Chapters 4–10 concern specific sectors, some technologies and policies reach across many sectors; for example, the use of biomass and the switch from high-carbon fuels to gas affect energy supply, transport, industry and buildings. Apart from potentials for common technologies, these examples also highlight possible competition for resources, such as finance and R&D support [11.2.1].
The bottom-up compilation of mitigation potentials by sector is complicated by interactions and spill-overs between sectors, over time and over regions and markets. A series of formal procedures has been used to remove potential double counting, such as reduction of the capacity needed in the power sector due to electricity saving in industry and the buildings sector. An integration of sector potentials in this way is required to summarize the sectoral assessments of Chapters 4–10. The uncertainty of the outcome is influenced by issues of comparability of sector calculations, difference in coverage between the sectors (e.g., the transport sector) and the aggregation itself, in which only the main and direct sector interactions have been taken into account [11.3.1].
The top-down estimates were derived from stabilization scenarios, i.e., runs towards long-term stabilization of atmospheric GHG concentration [3.6].
Figure TS.26A and Table TS.15 show that the bottom-up assessments emphasize the opportunities for no-regrets options in many sectors, with a bottom-up estimate for all sectors by 2030 of about 6 GtCO2-eq at negative costs; that is, net benefits. A large share of the no-regrets options is in the building sector. The total for bottom-up low cost options (no-regrets and other options costing less than 20 US$/tCO2-eq) is around 13 GtCO2-eq (ranges are discussed below). There are additional bottom-up potentials of around 6 and 4 GtCO2-eq at additional costs of <50 and 100 US$/tCO2-eq respectively (medium agreement, medium evidence) [11.3.1].
Table TS.15: Global economic mitigation potential in 2030 estimated from bottom-up studies [11.3].
Carbon price (US$/tCO2-eq) | Economic potential (GtCO2-eq/yr) | Reduction relative to SRES A1 B (68 GtCO2-eq/yr) (%) | Reduction relative to SRES B2 (49 GtCO2-eq/yr) (%) |
---|
0 | 5-7 | 7-10 | 10-14 |
20 | 9-17 | 14-25 | 19-35 |
50 | 13-26 | 20-38 | 27-52 |
100 | 16-31 | 23-46 | 32-63 |
Table TS.16: Global economic mitigation potential in 2030 estimated from top-down studies [11.3].
Carbon price (US$/tCO2-eq) | Economic potential (GtCO2-eq/yr) | Reduction relative to SRES A1 B (68 GtCO2-eq/yr) (%) | Reduction relative to SRES B2 (49 GtCO2-eq/yr) (%) |
---|
20 | 9-18 | 13-27 | 18-37 |
50 | 14-23 | 21-34 | 29-47 |
100 | 17-26 | 25-38 | 35-53 |
There are several qualifications to these estimates in addition to those mentioned above. First, in the bottom-up estimates a set of emission-reduction options, mainly for co-generation, parts of the transport sector and non-technical options such as behavioural changes, are excluded because the available literature did not allow a reliable assessment. It is estimated that the bottom-up potentials are therefore underestimated by 10–15%. Second, the chapters identify a number of key sensitivities that have not been quantified, relating to energy prices, discount rates and the scaling-up of regional results for the agricultural and forestry options. Third, there is a lack of estimates for many EIT countries and substantial parts of the non-OECD/EIT region [11.3.1].
The estimates of potentials at carbon prices <20 US$/tCO2- eq are lower than the TAR bottom-up estimates that were evaluated for carbon prices <27 US$/tCO2-eq, due to better information in recent literature (high agreement, much evidence).
Figure TS.15 and Table TS.16 show that the overall bottom-up potentials are comparable with those of the 2030 results from top-down models, as reported in Chapter 3.
At the sectoral level, there are larger differences between bottom-up and top-down, mainly because the sector definitions in top-down models often differ from those in bottom-up assessments (Table TS.17). Although there are slight differences between the baselines assumed for top-down and bottom-up assessments, the results are close enough to provide a robust estimate of the overall economic mitigation potential by 2030. The mitigation potential at carbon prices of <100 US$/tCO2-eq is about 25–50% of 2030 baseline emissions (high agreement, much evidence).
Table TS.17 shows that for point-of-emission analysis a large part of the long-term mitigation potential is in the energy-supply sector. However, for an end-use sector analysis as used for the results in Figure TS.27, the highest potential lies in the building and agriculture sectors. For agriculture and forestry, top-down estimates are lower than those from bottom-up studies. This is because these sectors are generally not well covered in top-down models. The energy supply and industry estimates from top-down models are generally higher than those from bottom-up assessments (high agreement, medium evidence) [11.3.1].
Table TS.17: Economic potential for sectoral mitigation by 2030: comparison of bottom-up (from Table 11.3) and top-down estimates (from Section 3.6) [Table 11.5].
Chapter of report | Sectors | Sector-based (‘bottom-up’) potential by 2030 (GtCO2-eq/yr) | Economy-wide model (‘top-down’) snapshot of mitigation by 2030 (GtCO2-eq/yr) |
---|
End-use sector allocation (allocation of electricity savings to end-use sectors) | Point-of-emissions allocation (emission reductions from end-use electricity savings allocated to energy supply sector) |
---|
Carbon price <20 US$/tCO2-eq |
---|
| Low | High | Low | High | Low | High |
---|
4 | Energy supply & conversion | 1.2 | 2.4 | 4.4 | 6.4 | 3.9 | 9.7 |
5 | Transport | 1.3 | 2.1 | 1.3 | 2.1 | 0.1 | 1.6 |
6 | Buildings | 4.9 | 6.1 | 1.9 | 2.3 | 0.3 | 1.1 |
7 | Industry | 0.7 | 1.5 | 0.5 | 1.3 | 1.2 | 3.2 |
8 | Agriculture | 0.3 | 2.4 | 0.3 | 2.4 | 0..6 | 1.2 |
9 | Forestry | 0.6 | 1.9 | 0.6 | 1.9 | 0.2 | 0.8 |
10 | Waste | 0.3 | 0.8 | 0.3 | 0.8 | 0.7 | 0.9 |
11 | Total | 9.3 | 17.1 | 9.1 | 17.9 | 8.7 | 17.9 |
| | Carbon price <50 US$/tCO2-eq |
---|
4 | Energy supply & conversion | 2.2 | 4.2 | 5.6 | 8.4 | 6.7 | 12.4 |
5 | Transport | 1.5 | 2.3 | 1.5 | 2.3 | 0.5 | 1.9 |
6 | Buildings | 4.9 | 6.1 | 1.9 | 2.3 | 0.4 | 1.3 |
7 | Industry | 2.2 | 4.7 | 1.6 | 4.5 | 2.2 | 4.3 |
8 | Agriculture | 1.4 | 3.9 | 1.4 | 3.9 | 0.8 | 1.4 |
9 | Forestry | 1.0 | 3.2 | 1.0 | 3.2 | 0.2 | 0.8 |
10 | Waste | 0.4 | 1.0 | 0.4 | 1.0 | 0.8 | 1.0 |
11 | Total | 13.3 | 25.7 | 13.2 | 25.8 | 13.7 | 22.6 |
| | Carbon price <100 US$/tCO2-eq |
---|
4 | Energy supply & conversion | 2.4 | 4.7 | 6.3 | 9.3 | 8.7 | 14.5 |
5 | Transport | 1.6 | 2.5 | 1.6 | 2.5 | 0.8 | 2.5 |
6 | Buildings | 5.4 | 6.7 | 2.3 | 2.9 | 0.6 | 1.5 |
7 | Industry | 2.5 | 5.5 | 1.7 | 4.7 | 3.0 | 5.0 |
8 | Agriculture | 2.3 | 6.4 | 2.3 | 6.4 | 0.9 | 1.5 |
9 | Forestry | 1.3 | 4.2 | 1.3 | 4.2 | 0.2 | 0.8 |
10 | Waste | 0.4 | 1.0 | 0.4 | 1.0 | 0.9 | 1.1 |
11 | Total | 15.8 | 31.1 | 15.8 | 31.1 | 16.8 | 26.2 |
Bioenergy options are important for many sectors by 2030, with substantial growth potential beyond, although no complete integrated studies are available for supply-demand balances. Key preconditions for such contributions are the development of biomass capacity (energy crops) in balance with investments in agricultural practices, logistic capacity and markets, together with commercialization of second-generation biofuel production. Sustainable biomass production and use could ensure that issues in relation to competition for land and food, water resources, biodiversity and socio-economic impacts are not creating obstacles (high agreement, limited evidence) [11.3.1.4].
Apart from the mitigation options mentioned in the sectoral Chapters 4–10, geo-engineering solutions to the enhanced greenhouse effect have been proposed. However, options to remove CO2 directly from the air, for example, by iron fertilization of the oceans, or to block sunlight, remain largely speculative and may have a risk of unknown side effects. Blocking sunlight does not affect the expected escalation in atmospheric CO2 levels, but could reduce or eliminate the associated warming. This disconnection of the link between CO2 concentration and global temperature could have beneficial consequences, for example, in increasing the productivity of agriculture and forestry (in as far as CO2 fertilization is effective), but they do not mitigate or address other impacts such as further acidification of the oceans. Detailed cost estimates for these options have not been published and they are without a clear institutional framework for implementation (medium agreement, limited evidence) [11.2.2].