Editing IPCC:AR6/WGIII/Chapter-12 (section)

=== 12.2.3 Aggregation of Sectoral Results and Comparison with Earlier Analyses and Integrated Assessment Models ===

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In this section, the mitigation potentials are aggregated per sector, and then to the global economy. These potentials, which are based on sectoral analysis, are then compared to the results from earlier assessments and the results from IAMs. Given the incompleteness of data on the mitigation potential at mitigation costs larger than USD100 tCO 2 –1 , the focus will be on options with mitigation costs below USD100 tCO 2 –1 .

As suggested previously, the overview presented in Table 12.3 should be interpreted with care, as the implementation of one option may affect the mitigation potential of another option. Most sectoral chapters have supplied mitigation potentials that were already adjusted for overlap and mutual influences (industry, buildings, AFOLU). For the energy sector, interactions between the options will occur, but parallel implementation of all the options seems to be possible; if all options at costs levels below USD100 tCO 2 –1 were implemented, this would lead to an additional power generation with no direct CO 2 emissions of 41% of the total projected generation in 2030. This seems to be possible, but as higher penetrations are relatively unexplored, we apply a smaller uncertainty range at the high end. For the calculation of the aggregate potentials in the energy sector, error propagation rules were applied. For the transport sector, there will be interaction between the technical measures on the one hand and the modal shift measures on the other hand. Given the small mitigation contribution of the modal shift options, these interactions will be negligible. The resulting aggregate mitigation potentials and their uncertainty ranges per (sub)sector are given in Table 12.4 (columns indicated ‘AR6’). This overview confirms the large potentials per sector, even when taking the uncertainty ranges into account.

Calculating aggregated mitigation potentials for the global economy requires that interactions between sectors also need to be taken into account ( [[#12.6|Section 12.6]] ). First of all, there may be overlap between the electricity supply sector and the electricity demand sectors: if the electricity sector is extensively decarbonised, the avoided emissions due to electricity efficiency measures and local electricity production will be significantly reduced. Therefore, this demand-side mitigation potential is only taken into account for 25% (reflecting the degree of further decarbonisation of the power sector) in the cross-sectoral aggregation. For the other demand sectors, this problem does not arise. The industry sector did not provide estimates for electricity efficiency improvement and in the transport sector the utilisation of electricity to date is very low. Electrification options may occur in all sectors, but this enhances the mitigation potential in combination with a decreased carbon intensity of the power sector. For other energy sector options, such as methane emissions reduction from coal, oil and natural gas operations, the situation is more complex. The total emissions reduction potential for fossil fuels in the other sectors is high. Should this potential be realised, this would lead to a reduction of the potential reported here. However, reducing fossil fuel use also leads to a reduction in the upstream CH 4 (methane) emissions, so in the case of reducing fossil fuel use, these upstream emissions will also be avoided, so no overestimate of the aggregate emissions reduction potential occurs.

The total potential, given these corrections for overlap, leads to a mid-range value for the total mitigation potential at costs below USD100 tCO 2 -eq –1 of 38 GtCO 2 -eq. Given the fact that it is not to be expected that mitigation potentials of the various sectors are mutually correlated, that is, it is not to be expected that mitigation potentials are all on the high side or all on the low side, the ranges are aggregated using error propagation rules, which leads to a range for the mitigation potential of 32 to 44 GtCO 2 -eq.

Mitigation costs and potentials for 2030 have been presented previously, notably in AR4 [[IPCC:Wg3:Chapter:Chapter-11|Chapter 11]] on Mitigation from a Cross-sectoral Perspective ( [[#Barker--2007|Barker et al. 2007]] ) and the Emissions Gap Report ( [[#UNEP--2017|UNEP 2017]] ). Note that AR5 did not provide emissions reduction potentials in this form. The aggregated potentials reported here are higher than those estimated in AR4. Note, however, that AR4 suggested the potentials were underestimated by 10 to 15%, but a higher potential still remains in the current assessment. In a sector-by-sector comparison, higher potentials than in AR4 can be observed especially for the energy sector and the forestry sector, and to a more limited extent for the industry sector and the transport sector. For the energy sector, the change can largely be explained by the higher estimates for wind and solar energy and the improved understanding of how to integrate high shares of intermittent renewable energy sources into power systems. For industry and transport, the higher potentials can be partly explained by the inclusion of more options, like recycling and material efficiency (for industry) and electric transportation and modal shifts for transport. For buildings, a lower potential can be observed compared to AR4, one reason is that the 2030 reference direct and indirect emissions were estimated as 45% and 11% higher in AR4 than they were in AR6 (signalling a much quicker actual switch to electricity than was thought 15 to 20 years ago, among other reasons). The other reason for a difference is that the scenarios considered in AR4 had 25 to 30 years between their start year until the target year of 2030 and the scenarios reviewed in AR6 have only 10 to 15 years before 2030. The current retrofitting rates of existing buildings and penetration rates of nearly zero-energy buildings do not allow for decarbonisation of the sector over 10 to 15 years, but they do over a longer time period. A much larger potential than reported here for 2030 can still be realised in the timeframe up to 2050 ( [[IPCC:Wg3:Chapter:Chapter-9#9.6.2|Section 9.6.2]] ).

Another global analysis was done by [[#McKinsey--2009|McKinsey (2009)]] , which presents a marginal abatement cost curve for 2030, suggesting a total potential of 38 GtCO 2 -eq (note that the reference for that study is 70 GtCO 2 -eq, which is at the high end of the reference range used in this assessment).

The potentials reported here are comparable with [[#UNEP--2017|UNEP (2017)]] . Note that material for the energy sector from the UNEP report was partly reused in this analysis. Furthermore, some options for the transport sector (aviation and biofuels) were identical to the estimates in the UNEP report. The remaining mitigation potentials are all based on new – and much more extended – assessment. There are some notable changes. The AR6 mitigation potential for forestry is substantially larger. For buildings the potential is smaller, mainly related to the smaller mitigation potential for electric appliances than in the UNEP report. But overall, the estimates of the total mitigation potential are well aligned, which confirms there is substantial consistency across various emissions reduction estimates.

The results of the sectoral mitigation potentials are also compared with mitigation impacts as calculated by IAMs. To this end, cumulative sectoral potentials over cost ranges were determined, based on the information in Table 12.3. For options that are in various cost ranges, we assumed that they are evenly distributed over these cost ranges. The only exception is wind and solar energy, for which it is indicated that the majority of the mitigation potential is in the negative cost range. It was assumed that the fraction in the negative cost range was 60%; the remainder is evenly distributed over the other cost ranges. These cumulative potentials were compared with emissions reductions realised in IAMs at certain price levels for CO 2 . Note that these price levels selected in IAMs are average price levels – not all IAMs use globally uniform carbon prices, so underlying these cost levels, there may be regional differentiation. Data were taken from the AR6 scenarios database. Note that, strictly speaking, not all models in the database are IAMs; in this analysis all models in the database were used, but the term IAMs is used as shorthand in the text that follows. All scenarios that limit warming to 2°C (&gt;67%) or lower are included for the comparison (i.e., the categories of scenarios C1 to C3 in Chapter 3). A comparison per sector is provided in Figure 12.1. It is important to note that two different things are compared in this figure: on the one hand emissions reduction potentials and on the other hand realisations of (part of) the potential within the context of a certain scenario. Having said that, a number of lessons can be learned from the comparison of both.

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'''Figure 12.1 | Comparison of sectoral estimates for emissions reduction potential with the emissions reductions calculated using IAMs.''' Emission reductions calculated using IAMs are given as box plots of global emissions reductions for each sector (dark blue and brown) at different global carbon cost levels (horizontal axis) for 2030, based on all scenarios that limit warming to 2°C (&gt;67%) or lower (see Chapter 3) in the AR6 scenarios database ( [[#IIASA--2021|IIASA 2021]] ). For IAMs, the cost levels correspond to the levels of the carbon price. Hinges in the dark blue box plots represent the interquartile ranges and whiskers extend to 5th and 95th percentiles while the hinges in the brown box plots describe the full range, and the middle point indicates the mean, not the median. In yellow, the estimates from the sectoral analysis are given. In all cases, only direct emissions reductions are presented, except for the light-blue boxes (for buildings), which include indirect emissions reductions. The light-blue boxes are only given for reasons of completeness. For buildings the dark-blue boxes should be compared with the yellow boxes. Light-blue and yellow boxes represent the full ranges of estimates. For IAMs, global carbon prices are applied, which are subject to significant uncertainty.

For the energy supply sector, the emissions reductions projected by the IAMs are for the higher cost levels comparable with the potentials found in the sectoral analysis. But at lower cost levels, the emissions reductions as projected by IAMs are smaller than for the sectoral analysis. This is likely due to the fact that high costs for solar energy and wind energy are assumed in IAM models ( [[#Krey--2019|Krey et al. 2019]] ; [[#Shiraki--2020|Shiraki and Sugiyama 2020]] ). This is not surprising, as the scenario database comprises studies dating back to 2015. A more detailed comparison for the power sector is given in Figure 12.2. Both the sectoral analysis and the IAMs find that both solar and wind energy in particular show strong growth potential, although there is a continuing role for other low-carbon technologies, like nuclear energy and hydropower.

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'''Figure 12.2 | Electricity production in 2030 as calculated by IAMs (dark blue), compared with electricity production potentials found in the sectoral analysis (yellow).''' Cost cut-offs at USD100 tCO 2 –1 are applied to both electricity production in 2030 as calculated by IAMs and electricity production potentials found in the sectoral analyses. Hinges in the dark-blue box plots represent the interquartile ranges and whiskers extend to the 5th and 95th percentiles, while the hinges in the yellow box plots describe the full range.

For the AFOLU sector, the sectoral studies provide net emissions reduction potentials comparable with projections from the IAMs at costs levels up to USD50 tCO 2 -eq –1 . However, beyond that level the mitigation potential found in the sectoral analysis is larger than in the IAMs. For agriculture, it can be explained by the fact that carbon sequestration options, like soil carbon, biochar and agroforestry, have little to no representation in IAMs. Similarly, for forestry and other land use-related options, the protection and restoration of other ecosystems than forests (peatland, coastal wetlands and savannas) are not represented in IAMs. Also note that some IAM baselines already have small carbon prices, which induce land-based mitigation, while in others, mitigation, particularly from reduced deforestation, is part of the storyline even without an implemented carbon price. Both of these effects dampen the mitigation potential available in the USD100 tCO 2 -eq –1 carbon price scenario from IAMs. Furthermore, estimates of mitigation through forestry and other land use-related options from the AR6 IAM scenario database represent the net emissions from A/R and deforestation, thus are likely to be lower than the sectoral estimates of A/R potential expressed as gross removals.

For the buildings and transport sectors, the sectoral mitigation potentials are higher than those projected by the IAMs. The difference in the transport sector is particularly significant. One possible explanation is that options with negative costs are already included in the reference. In addition, some options, like avoiding demand for energy services in the building sector and model shift in transportation, are less well represented in IAMs.

For the industry sector, the sectoral emissions reduction potentials are somewhat higher than those reported on average by IAMs. The difference can well be explained by the fact that most IAMs do not include circularity options like material efficiency and recycling; these options together account for 1.5 GtCO 2 -eq at costs levels from USD20 tCO 2 -eq –1 onwards.

For mitigation of emissions of methane and fluorinated gases, the comparability between the sectoral results and IAMs is good.

Overall, it is concluded that there are differences between the sectoral analyses and the IAM outcomes, but most of the differences can be explained by the exclusion of specific options in most IAMs. This comparability confirms the reliability of the sectoral analysis of emissions reduction potential. It also demonstrates the added value of sectoral analyses of mitigation potentials: they can more rapidly adapt to changes in price levels of technologies and adopt new options for emissions mitigation.

In this section, the information on individual options reported in [[#12.2.2|Section 12.2.2]] to sectoral and economy-wide totals has been aggregated. It is concluded that, based on the sectoral analysis, the global mitigation potential is in the range of 32 to 44 GtCO 2 -eq. This mitigation potential is substantially higher than that reported in AR4, but it is comparable to the more recent estimate by [[#UNEP--2017|UNEP (2017)]] . Differences exist with the results of IAMs, but most of these can be well explained. The conclusion that the global potential is in this range can be drawn with ''high agreement'' and ''r'' ''obust evidence'' .

Given the median projection of the reference emissions of 60 GtCO 2 -eq in 2030, the range of mitigation potentials presented here is sufficient to bring down global emissions in the year 2030 to a level of 16 to 28 GtCO 2 -eq. Taking into account that there is a range in reference projections for 2030 of 54 to 68 GtCO 2 -eq, the resulting emissions level shows a wider range: 12 to 31 GtCO 2 -eq. This is about, or below half, the most recent (2019) emissions value of 59 ± 6.6 GtCO 2 -eq ( ''hi'' ''gh confidence'' ).

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