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

== 12.2 Aggregation of Sectoral Costs and Potentials ==

<div id="h1-3-siblings" class="h1-siblings"></div>

The aim of this section is to provide a consolidated overview of the net emissions reduction potentials and costs for mitigation options available in the various sectors dealt with in the sectoral Chapters 6, 7, 9, 10 and 11 of this assessment report. This overview provides policymakers with an understanding of which options are more or less important in terms of mitigating emissions in the short term (here interpreted as 2030), and which ones are more or less costly. The intention is not to provide a high level of accuracy for each technology cost or potential, but rather to indicate relative importance on a global scale and whether costs are low, intermediate or high. The section starts with an introduction ( [[#12.2.1|Section 12.2.1]] ), providing definitions and the background. Next, ranges of net emission reduction potentials and the associated costs for the year 2030 are presented ( [[#12.2.2|Section 12.2.2]] ) and compared to earlier estimates and with the outputs of IAMs ( [[#12.2.3|Section 12.2.3]] ). Finally, an outlook to the year 2050 is provided ( [[#12.2.4|Section 12.2.4]] ).

<div id="12.2.1" class="h2-container"></div>

<span id="introduction-1"></span>
=== 12.2.1 Introduction ===

<div id="h2-4-siblings" class="h2-siblings"></div>

The term ‘mitigation potential’ is used here to report the quantity of net greenhouse gas emissions reductions that can be achieved by a given mitigation option relative to a specified reference scenario. The net greenhouse gas emission reduction is the sum of reduced emissions and enhanced sinks. Several types of potential can be distinguished. The technical potential is the mitigation potential constrained by theoretical limits in addition to the availability of technology and practices. Quantification of technical potentials primarily takes into account technical considerations, but social, economic and/or environmental considerations are sometimes also considered, if these represent strong barriers to the deployment of an option. The economic potential, being the potential reported in this section, is the proportion of the technical potential for which the social benefits exceed the social costs, taking into account a social discount rate and the value of externalities (see Annex I: Glossary). In this section, only externalities related to greenhouse gas emissions are taken into account. They are represented by using different cost cut-off levels of options in terms of USD per tonne of avoided CO 2 -eq emissions. Other potentials, such as market potentials, could also be considered, but they are not included in this section.

The analysis presented here is based, as far as possible, on information contained in Chapters 6, 7, 9, 10 and 11, where costs and potentials, referred to here as ‘sectoral mitigation potentials’ have been discussed for each individual sector. In the past, these were designated as bottom-up potentials, in contrast to the top-down potentials that are obtained from integrated energy-economic models and IAMs. However, IAMs increasingly include ‘bottom-up’ elements, which makes the distinction less clear. Still, sectoral studies often have more technical and economic detail than IAMs. They may also provide more up-to-date information on technology options and associated costs. However, aggregation of results from sectoral studies is more complex, and although interactions and overlap are corrected for as far as possible in this analysis, it is recognised that such systemic effects are much more rigorously taken into account in IAMs. A comparison is made between the sectoral results and the outcomes of the IAMs in [[#12.2.3|Section 12.2.3]] .

Costs of mitigation options will change over time. For many technologies, costs will reduce as a result of technological learning. An attempt has been made to take into account the average, implementation-weighted costs until 2030. However, the underlying literature did not always allow such costs to be presented. For the year 2030, the results are presented similarly to AR4, with a breakdown of the potential in ‘cost bins’. For the year 2050, a more qualitative approach is provided. The origins of the cost data in this section are mostly based on studies carried out in the period 2015–2020. Given the wide range of the cost bins that are used in this section it is not meaningful (and often not possible) to convert to USD values for one specific year. This may lead to some extra uncertainty, but this is expected to be relatively small.

As indicated previously, net emission reduction potentials are presented based on comparison with a reference scenario. Unfortunately, not all costs and potentials found in the literature are determined against the same reference scenarios. In this assessment, reference scenarios are based on what were assumed current-policy scenarios in the period 2015–2019. Typical reference scenarios are the Shared Socio-economic Pathway (SSP2) scenarios ( [[#Fricko--2017|Fricko et al. 2017]] ) and the Current Policies scenario from the World Energy Outlook (WEO) 2019 (IEA 2019). They can both be considered scenarios with middle-of-the-road expectations on population growth and economic development, but there are still some differences between the two (Table 12.2). The net emissions reduction potentials reported here were generally based on analyses carried out before 2020, so the impact of the COVID-19 pandemic was not taken into account. For comparison, the Stated Policies scenario of the World Energy Outlook 2020 ( [[#IEA--2020a|IEA 2020a]] ) is also shown, one of the scenarios in which the impact of COVID-19 was considered. Variations of up to 10% between the different reference scenarios exist with respect to macro-variables such as total primary energy use and total GHG emissions. The potential estimates presented below should be interpreted against this background. The total emissions under the reference scenarios in 2030 are expected to be in the range of 54 to 68 GtCO 2 -eq yr –1 with a median of 60 GtCO 2 -eq yr –1 (Table 4.1).

For the energy sector the potentials are determined using the World Energy Outlook 2019 Current Policies Scenario as a reference (IEA 2019). However, for the economic assessment, more recent Levelised Costs of Electricity (LCOEs) for different electricity generating technologies were used ( [[#IEA--2020a|IEA 2020a]] ). For the AFOLU sector, the potentials were derived from a variety of studies. It may be expected that the best estimates, as averages, match with the reference in a middle-of-the-road scenario. For the buildings sector, the Current Policies scenario of World Energy Outlook 2019 (IEA 2019) was used as a reference. For the transport sector, the references of the underlying sources were used. For the industry sector, the scenarios used have emissions that are slightly higher than in the Current Policies scenario from the World Energy Outlook 2019 (IEA 2019).

'''Table 12.2 | Key characteristics of the scenarios used as a reference for determining costs and potentials.''' The values are for the year 2030.

{| class="wikitable"
|-
!
! SSP2 reference

(MESSAGE-GLOBIOM)

( [[#Fricko--2017|Fricko et al. 2017]] )

! All reference scenarios

median (25th–75th percentiles in parenthesis)

(AR6 scenarios database, [[#IIASA--2021|IIASA, 2021]] )

! WEO-2019

(Current Policies)

(IEA 2019)

! WEO-2020

(Stated Policies)

( [[#IEA--2020a|IEA 2020a]] )

! AR6 WG III Chapter 4

(Chapter 4, Table 4.1)

|-
| Real GDP (purchasing power parity, PPP) (10 12 USD)

| 158

(USD2010)

| 159

(154 '''–''' 171)

| 3.6% p.a. ↑

(2018 to 2030)

| 2.9% p.a. ↑

(2019 to 2030)

|
|-
| Population (billion)

| 8.30

| 8.30

(8.20–8.34)

| 8.60

|
|-
| Total primary energy use (EJ)

| 627

| 670 (635–718)

| 710

| 660

|
|-
| Total final energy use (EJ)

| 499

| 480

(457 '''–''' 508)

| 502

| 472

|
|-
| Energy-related CO 2 emissions (Gt)

| 33.0

| 37.9

(34.7 '''–''' 41.4)

| 37.4

| 33.2 a

| 37

(35 '''–''' 45)

|-
| CO 2 emissions energy and industry (Gt)

| 37.9

| 42.3

(39.0–45.8)

|
| 36.0

|
|-
| Total CO 2 emissions (Gt)

| 40.6

| 45.7

(41.8–49.4)

|
| 43

(38–51)

|-
| Total greenhouse gas emissions (GtCO 2 -eq)

| 52.7

| 59.7

(55.0–65.8)

|
| 60

(54–68)

|}

a The difference between WEO-2020 and WEO-2019 is partly explained by the fact that WEO-2019 had two different reference scenarios: Current Policies and Stated Policies. WEO-2020 has only one reference: the Stated Policies Scenario, which ‘is based on today’s policy settings’. The Stated Policies Scenario in WEO-2019 had energy-related emissions of 34.9 GtCO 2 . EJ, exajoules (1 x 1018 joules); p.a., per annum.

<div id="12.2.2" class="h2-container"></div>

<span id="costs-and-potentials-of-options-for-2030"></span>
=== 12.2.2 Costs and Potentials of Options for 2030 ===

<div id="h2-5-siblings" class="h2-siblings"></div>

In this section, we present an overview of mitigation options per sector. An overview of net emissions reduction potentials for different mitigation options is presented in Table 12.3.

'''Table 12.3 | Detailed overview of global net GHG emissions reduction potentials (GtCO''' 2 '''-eq) in the various cost categories for the year 2030.''' Note that potentials within and across sectors cannot be summed, as the adoption of some options may affect the mitigation potentials of other options. Only monetary costs and benefits of options are taken into account. Negative costs occur when the benefits are higher than the costs. For wind energy, for example, this is the case if production costs are lower than those of the fossil alternatives. Ranges are indicated for each option separately, or indicated for the sector as a whole (see Notes column); they reflect full ranges. Cost ranges are not cumulative, e.g., to obtain the full potential below USD50 tCO 2 -eq –1 , the potentials in the cost bins &lt;USD0, USD0–20 and USD20–50 tCO 2 -eq –1 need to be summed together.

{| class="wikitable"
|-
! rowspan="2"| '''Emissions reduction options (including carbon sequestration options)'''

! colspan="5"| '''Cost categories (USD tCO''' 2 '''-eq''' –1 ''')'''

! rowspan="2"| '''Notes'''

|-
! '''&lt;0'''

! '''0–20'''

! '''20–50'''

! '''50–100'''

! '''100–200'''

|-
| colspan="6"| '''Energy sector'''

| '''Cost ranges are derived as ranges of LCOEs for different electricity generating technologies and the potentials are updated from [[#UNEP--2017|UNEP (2017)]] .'''

|-
| Wind energy

| colspan="3"| 2.1–5.6

(majority in &lt;0 range)

|
| rowspan="2"| Costs for system integration of intermittent renewables are not included, but these are expected to have limited impact until 2030 and will depend on market design and cross-sectoral integration.

|-
| Solar energy

| colspan="4"| 2.0–7.0

(majority in &lt;0 range)

|
|-
| Nuclear energy

| colspan="5"| 0.88 ± 50%

|
|-
| Bioelectricity

|
| colspan="2"|
| colspan="2"| 0.86 ± 50%

| Biomass use for indoor heating and industrial heat is not included here. Currently, about 90% of renewable industrial heat consumption is bio-based, mainly in industries that can use their own biomass waste and residues (IEA, 2020).

|-
| Hydropower

|
| colspan="3"| 0.32 ± 50%

|
| Mitigation costs show large variation and may end up beyond these ranges.

|-
| Geothermal energy

|
| colspan="3"| 0.74 ± 50%

|
| Mitigation costs show large variation and may end up beyond these ranges.

|-
| Carbon capture and storage (CCS)

|
| colspan="2"| 0.54 ± 50%

|
|-
| Bioelectricity with CCS

|
| colspan="2"| 0.30 ± 50%

|
|-
| CH 4 emissions reduction from coal mining

| 0.04

(0.01–0.06)

| 0.41

(0.15–0.64)

| 0.03

(0.02–0.05)

| 0.02

(0.01–0.03)

|
|-
| CH 4 emissions reduction from oil and gas operations

| 0.31

(0.12–0.56)

| 0.61

(0.23–1.30)

| 0.07

(0.03–0.20)

| 0.06

(0.00–0.29)

| 0.10

(0–0.29)

|
|-
| colspan="6"| '''Land-based mitigation options (including agriculture and forestry)'''

| '''Potentials for AFOLU are averages for the period 2020–2050 and represent a proxy for mitigation in 2030.'''

'''Technical potentials listed below include the potentials already listed in the previous columns.'''

'''Note that in Table 7.3 the same potentials are listed, but they are cumulative over the cost bins.'''

|-
| Carbon sequestration in agriculture (soil carbon sequestration, agroforestry and biochar application)

|
| 0.50

(0.38–0.60)

| 0.73

(0.5–1.0)

| 2.21

(0.6–3.9)

|
| Technical potential: 9.5 (range 1.1–25.3).

|-
| CH 4 and N 2 O emissions reduction in agriculture (reduced enteric fermentation, improved manure management, nutrient management, rice cultivation)

|
| 0.35

(0.11–0.84)

| –

| 0.28

(0.19–0.46)

|
| Technical potential: 1.7 (range 0.5–3.2).

GWPs used from AR4 and AR5.

|-
| Protection of natural ecosystems (avoid deforestation, loss and degradation of peatlands, coastal wetlands and grasslands)

|
| 2.28

(1.7–2.9)

| 0.12

(0.06–0.18)

| 1.63

(1.3–4.2)

| 0.22

(0.09–0.45)

| Technical potential 6.2 (range 2.8–14.4).

|-
| Restoration (afforestation, reforestation, peatland restoration, coastal wetland restoration)

|
| 0.15

| 0.57

(0.2–1.5)

| 1.46

(0.6–2.3)

| 0.66

(0.4–1.1)

| Technical potential 5.0 (range 1.1–12.3).

|-
| Improved forest management, fire management

|
| 0.38

(0.32–0.44)

| –

| 0.78

(0.32–1.44)

|
| Technical potential 1.8 (range 1.1–2.8).

|-
| Reduction of food loss and food waste

|
| Feasible potential 0.5 (0.1–0.9).

Technical potential 0.7 (0.1–1.6).

Estimates reflect direct mitigation from diverted agricultural production only, not including land use effects.

|-
| Shift to sustainable healthy diets

|
| Feasible potential 1.7 (1.0–2.7).

Technical potential 3.5 (2.1–5.5).

Estimates reflect direct mitigation from diverted agricultural production only, not including land-use effects.

|-
| '''Buildings'''

|
| '''To avoid double-counting, the numbers were corrected for the potential overlap between options in the order sufficiency, efficiency, renewable measures and they could be therefore added up. In 2050, much larger and cheaper potential is available (see [[IPCC:Wg3:Chapter:Chapter-9#9.6|Section 9.6]] ); the potential in 2030 is lower and more expensive, mostly due to various feasibility constraints.'''

|-
| Sufficiency to avoid demand for energy services (e.g., efficient building use and increased inhabitancy and density)

| 0.56

(0.28–0.84)

|
|-
| Efficient lighting, appliances and equipment, including information and communications technologies, water heating and cooking technologies

| 0.73

(0.54–0.91)

|
|-
| New buildings with very high energy performance (change in construction methods, management and operation of buildings, efficient heating, ventilation and air conditioning)

|
| colspan="3"| 0.35

(0.26–0.53)

| 0.83

(0.62–1.24)

|
|-
| Onsite renewable production and use (often backed-up with demand-side flexibility and digitalisation measures, typically installed in very new high energy performance buildings)

|
| colspan="3"| 0.20

(0.15–0.30)

| 0.27

(0.20–0.40)

|
|-
| Improvement of existing building stock (thermal efficiency of building envelopes, management and operation of buildings, and efficient heating, ventilation and air conditioning leading to ‘deep’ energy savings)

|
| colspan="4"| 0.27

(0.20–0.34)

| Additionally, there is 0.50 (range 0.37–0.62) GtCO 2 -eq of potential above a price of USD200 tCO 2 -eq –1 .

|-
| Enhanced use of wood products

|
| Technical potential 1.0 (range 0.04–3.7).

Economic potential 0.38 (range 0.3–0.5) (varying carbon prices). Potential is mainly in the construction sector.

|-
| '''Transport'''

|
| '''Options for the transportation sector have an uncertainty of ±50%.'''

|-
| Light duty vehicles – fuel efficiency

| 0.6

|
|-
| Light duty vehicles – electric vehicles

|
| Estimated potential is 0.5-0.7 GtCO 2 -eq, depending on the carbon intensity of the electricity supplied to the vehicles. Mitigation costs are variable.

|-
| Light duty vehicles – shift to public transport

| 0.5

|
|-
| Light duty vehicles – shift to bikes and e-bikes

| 0.2

|
|-
| Heavy duty vehicles – fuel efficiency

| 0.4

|
|-
| Heavy duty vehicles – electric vehicles

|
| Estimated potential is 0.2 GtCO 2 -eq. Mitigation costs are variable.

|-
| Heavy duty vehicles – shift to rail

|
| No data available.

|-
| Shipping – efficiency, optimisation, biofuels

| 0.5

(0.4–0.7)

|
|-
| Aviation – energy efficiency

| 0.12–0.32

|
| Limited evidence.

|-
| Biofuels

|
| colspan="3"| 0.6–0.8

|
|-
| '''Industry'''

|
| '''The numbers for the industry sector typically have an uncertainty of ±25%, unless indicated differently.'''

'''The numbers are corrected for overlap between the options, except for the 0.15 GtCO''' 2 '''potential in the highest cost bin. For the rest they can be aggregated to provide full potentials.'''

|-
| Energy efficiency

|
| 1.14

|
| This only applies to more efficient use of fuels. More efficient use of electricity is not included.

|-
| Material efficiency

|
| 0.93

|
|-
| Circularity (enhanced recycling)

|
| 0.48

|
|-
| Fuel switching

|
| 1.28

| 0.67

| 0.15

|
|-
| Feedstock decarbonisation, process change

|
| 0.38

|
|-
| Carbon capture, utilisation and storage (CCU and CCS)

|
| 0.15

(0.08–0.36)

|
|-
| Cementitious material substitution

|
| 0.28

|
|-
| Reduction of non-CO 2 emissions

|
| 0.2

|
|-
| '''Cross-sectorial'''

|
|-
| Emission reduction of fluorinated gases

| 0.26

(0.01–0.50)

| 0.68

(0.55–0.90)

| 0.18

(0.01–0.42)

| 0.09

(0–0.20)

| 0.03

(0–0.05)

| GWPs not updated.

|-
| Reduction of CH 4 emissions from solid waste

| 0.33

(0.24–0.43)

| 0.11

(0.03–0.15)

| 0.06

(0.03–0.08)

| 0.04

(0.01–0.10)

| 0.08

(0.02–0.12)

|
|-
| Reduction of CH 4 emissions from wastewater

| 0.02

(0–0.05)

| 0.03

(0.01–0.05)

| 0.04

(0.01–0.07)

| 0.03

(0.02–0.04)

| 0.07

(0.01–0.16)

|
|-
| Direct air carbon capture and storage (DACCS)

|
| very small

| rowspan="2"| There is potential in these categories, but given the current technology readiness levels, for 2030 the potential is limited. Also, it is not certain whether the costs will have dropped below 200 USD tCO 2 –1 before 2030. In the longer term, much larger potentials are projected, see [[#12.3.1|Section 12.3.1]] .

|-
| Enhanced weathering

|
| very small

|}

Firstly, a brief overview of the process of data collection is presented, with a more detailed overview being found in Supplementary Material 12.SM.1.2. For the energy sector, the starting point for the determination of the emissions reduction potentials was the Emissions Gap Report ( [[#UNEP--2017|UNEP 2017]] ), but new literature was also assessed, and a few studies that provide updated estimates of the mitigation potentials were included. It was found that higher mitigation potentials than in the UNEP report are now reported for solar and wind energy, but at the same time electricity production by solar and wind energy in the reference scenario has increased, compared to earlier versions of the World Energy Outlook. The net effect is a modest increase in the average value of the potential, and a wider uncertainty range. Costs of electricity-generating technologies are discussed in [[IPCC:Wg3:Chapter:Chapter-6#6.4.7|Section 6.4.7]] , with a summary of LCOEs from the literature being presented in [[IPCC:Wg3:Chapter:Chapter-6#6.4.7|Section 6.4.7]] . Mitigation costs of electricity production technology depend on local conditions and on the baseline technology being displaced, and it is difficult to determine the distribution over the cost ranges used in this assessment. However, it is possible to indicate a broad cost range for these technologies. These cost ranges are presented in Table 12.3. For onshore wind and utility-scale solar energy, there is strong evidence that despite regional differences in resource potential and cost, a large part of the mitigation potential can be found in the negative cost category or at cost parity with fossil fuel-based options. This is also the case for nuclear energy in some regions. Other technologies show mostly positive mitigation costs, the highest mitigation costs are for CCS and bioelectricity with CCS, for details see Supplementary Material 12.SM.1.2.

For the AFOLU sector, assessments of global net emissions reduction studies were provided in Table 7.3. The number of studies depends on the type of mitigation action, but ranges from five to nine. Each of these studies relies on a much larger number of underlying data sources. From these studies, emissions reduction ranges and best estimates were derived. The studies presented refer to different years in the period 2020 to 2050, and the mitigation potential presented for AFOLU primarily refers to the average over the period 2020 to 2050. However, because most of the activities involve storage of carbon in stocks that accumulate carbon, or conversely decay over time (e.g., forests, mangroves, peatland soils, agricultural soils, wood products), the 2020 to 2050 average provides a good approximation of the amount of permanent atmospheric CO 2 mitigation that could be available at a given price in 2030. The exception is BECCS, which is in an early upscaling phase, so the potential estimated by [[IPCC:Wg3:Chapter:Chapter-7|Chapter 7]] as an average for the 2020 to 2050 period is not included in Table 12.3. Note that for the energy sector a mitigation potential for BECCS is provided in Table 12.3.

The emissions reduction potentials for the buildings sector were based on the analysis by [[IPCC:Wg3:Chapter:Chapter-9|Chapter 9]] authors of a large number of sectoral studies for individual countries or regions. In total, the chapter analysed the results of 67 studies that assess the potential of technological energy efficiency and onsite renewable energy production and use, and the results of 11 studies that assess the potential of sufficiency measures helping avoid demand for energy and materials. The sufficiency measures were included in models by reorganisation of human activities; efficient design, planning, and use of building space; higher density of building and settlement inhabitancy; redefining and downsizing goods and equipment, limiting their use to health, living, and working standards, and their sharing. Most of these studies targeted 2050 for the decarbonisation of buildings; the potentials in 2030 reported here rely on the estimates for 2030 provided by these studies or on the interpolated estimates targeting these 2050 figures. Based on these individual country studies, regional aggregate emissions reduction percentages were found. The potential estimates were assembled in the order sufficiency, efficiency, renewable options, correcting the amount of the potential at each step for the interaction with preceding measures. Note that the option ‘Enhanced use of wood products’ was analysed by Chapter 7, but is listed under the buildings sector in Table 12.3, as such enhanced use of wood takes place predominantly in the construction sector.

For the transport sector, [[IPCC:Wg3:Chapter:Chapter-10|Chapter 10]] provided data on the emissions reduction potential for shipping. For the other transportation modes, additional sources were used to achieve a complete overview of emissions reduction potentials (for further details, see Supplementary Material 12.SM.1.2). A limited number of estimates for global emissions reduction potential is available: the total number of sources is about 10, and some estimates rely on just one source. The data have been coordinated with [[IPCC:Wg3:Chapter:Chapter-10|Chapter 10]] authors.

For the industrial sector, global emissions reduction potentials per technology class per sector were derived by [[IPCC:Wg3:Chapter:Chapter-11|Chapter 11]] authors, using primarily sectoral or technology-oriented literature. The analysis is based on about 75 studies, including sectoral assessments (Sections 11.4.1 and 11.4.2 and Figure 11.13).

For methane emissions reduction from oil and gas operations, coal mining, waste treatment and wastewater, an analysis was done, based on three major data sources in this area ( [[#Harmsen--2019|Harmsen et al. 2019]] ; [[#US%20EPA--2019|US EPA 2019]] ; [[#Höglund-Isaksson--2020|Höglund-Isaksson et al. 2020]] ); for oil and gas operations this was complemented by [[#IEA--2021a|IEA (2021a)]] . A similar analysis for reductions of emissions of fluorinated gases was carried out based on analysis by the same institutes ( [[#Purohit--2017|Purohit and Höglund-Isaksson 2017]] ; [[#Harmsen--2019|Harmsen et al. 2019]] ; [[#US%20EPA--2019|US EPA 2019]] ). Data for CDR options not discussed previously (such as DACCS and enhanced weathering) were taken from [[#12.3|Section 12.3]] . For more details about data sources and data processing, see Supplementary Material 12.SM.1.2.

In Table 12.4 mitigation potentials for all gases are presented in GtCO 2 -eq. For most sectors the mitigation potentials (notably for methane emissions reductions from coal, oil and gas, waste and wastewater) have been converted to CO 2 -eq using global warming potential (GWP) values as presented in AR6 WGIII (Cross-Chapter Box 2 in Chapter 2). However, the underlying literature did not always accommodate this, in which cases older GWP values apply. Given the uncertainty ranges in the mitigation potentials in Table 12.3, the impact on the results of using different GWP values is considered to be very small.

'''Table 12.4 | Overview of aggregate sectoral net GHG emissions reduction potentials (GtCO''' 2 '''-eq) for the year 2030 at costs below USD100 tCO''' 2 '''-eq''' –1 '''.''' Comparisons with earlier assessments are also provided. Note that sectors are not entirely comparable across the three different estimates.

{| class="wikitable"
|-
! rowspan="2"| '''Sector'''

! colspan="5"| '''Mitigation potentials at costs less than USD100 tCO''' 2 '''-eq''' –1

|-
! AR6

best estimate

! AR6

range

! AR4

( [[#Barker--2007|Barker et al. 2007]] )

! UNEP2017

best estimate

( [[#UNEP--2017|UNEP 2017]] )

! [[#UNEP--2017|UNEP 2017]]

range

( [[#UNEP--2017|UNEP 2017]] )

|-
| Electricity sector

| 11.0

| 7.9–12.5

| rowspan="2"| 6.2–9.3

| 10.3

| 9.5–11.0

|-
| Other energy sector (methane)

| 1.6

| 1.1–2.1

| 2.2

| 1.7–2.6

|-
| Agriculture

| 4.1

| 1.7–6.7

| 2.3–6.4

| 4.8

| 3.6–6.0

|-
| Forestry and other land use-related options

| 7.3

| 3.9–13.1

| 1.3–4.2

| 5.3

| 4.1–6.5

|-
| AFOLU demand-side options (estimates reflect direct mitigation from '''diverted agricultural production only, not including land-use effects)'''

| 2.2

| 1.1–3.6

|
| 1.3–3.4

|-
| Buildings (potentials up to

USD200 '''tCO''' 2 '''-eq''' –1 '''in parentheses)'''

| Dir 0.7

(1.1)

Ind 1.3

(2.1)

Tot 2.0

(3.2)

| 0.5–1.0

(0.7–1.5)

0.9–1.8

(1.5–3.1)

1.4–2.9

(2.3–4.6)

| Dir 2.3–2.9

Ind 3.0–3.8

Tot 5.4–6.7

| Dir 1.9

Ind 4.0

Tot 5.9

| Dir 1.6–2.1

|-
| Transport

| 3.8

| 1.9–5.7

| 1.6–2.5

| 4.7

| 4.1–5.3

|-
| Industry

| Dir 5.4

| 4.0–6.7

| Dir 2.3–4.9

Ind 0.83

Tot 3.1–5.7

| Dir 3.9

Ind 1.9

Tot 5.8

| Dir 3.0–4.8

|-
| Fluorinated gases (all sectors)

| 1.2

| 0.7–1.5

| NE

| 1.5

| 1.2–1.8

|-
| Waste and wastewater

| 0.7

| 0.6–0.8

| 0.4–1.0

| 0.4

| 0.3–0.5

|-
| Enhanced weathering

| –

| –

| –

| 1.0

| 0.7–1.2

|-
| '''Total of all sectors'''

| '''38'''

| '''32–44'''

| '''15.8–31.1'''

| '''38'''

| '''35–41'''

|}

Note: Dir = reduction of direct emissions, Ind = reduction of indirect emissions (related to electricity production), Tot = reduction of total emissions, NE = not estimated, AR4: Table 11.3, UNEP-2017: Chapter 4.

For all options, uncertainty ranges of the mitigation potentials are given in Table 12.3. As far as possible, the ranges represent the variation in assessments found in the literature. This is the case for wind and solar energy, for the AFOLU options, for the methane mitigation options (coal, oil and gas, waste and wastewater) and for fluorinated gas mitigation. For the latter options, some variability exists for each cost bin, but aggregated over cost ranges the variation is much smaller, typically ±50%. For the buildings sector and the industrial sector options, the uncertainty in the mitigation potential is estimated by the lead authors of those chapters. For options for which only limited sources were available, an uncertainty range of ±50% was used. Overall, the uncertainty range per option is typically in the range of ±20% to ±60%.

Despite these uncertainties, clearly a number of options with high potentials can be identified, including solar energy, wind energy, reducing conversion of forests and other natural ecosystems, and restoration of forests and other natural ecosystems. As mid-range values, they each represent 4 to 7% of total reference emissions for 2030. Soil carbon sequestration in agriculture and fuel switching in industry can also be considered as options with high potential, although it should be noted that these options consist of a number of discernible sub-options, see Table 12.3. It can be observed that for each sector, a variety of options is available. Many of the smaller options each make up 1 to 2% of the reference emissions for 2030. Within this group of smaller options there are some categories that, summed together, stand out as substantial: the energy efficiency options and the methane mitigations options.

Costs are highly variable across the options. All sectors have several options for which at least part of the potential has mitigation costs below USD20 tCO 2 –1 . The only exception is the industrial sector, in which only energy efficiency is available below this cost level. At the same time, a substantial part of the emissions reduction potential comes at higher cost, much being in the USD20 to 100 tCO 2 –1 cost ranges. All sectors have substantial additional potential in these cost ranges; only for transportation is this limited. Aggregation of the potentials per cost bin shows that the potential in these cost bins is marginally smaller than in the two cheapest cost bins. For some options, potential was identified in the 100 to 200 tCO 2 –1 cost bin. The mitigation potentials identified in this cost range make up only a small part of the total mitigation potential. It could be that there is limited potential in this range; however, a more plausible explanation, supported by several authors of sectoral chapters, is that this cost range is relatively unexplored.

In this assessment, the emphasis is on the specific mitigation costs of the various options, and these are often considered as an indicator to prioritise options. However, in such a prioritisation, other elements will also play a role, like the development of technology for the longer term ( [[#12.2.4|Section 12.2.4]] ) and the need to optimise investments over longer time periods, see for example [[#Vogt-Schilb--2018|Vogt-Schilb et al. (2018)]] who argue that sometimes it makes sense to start with implementing the most expensive option.

In this section, an overview of emissions mitigation options for the year 2030 was presented. The overview of the mitigation potential is based on a variety of approaches, relying on a large number of sources, and the number of sources varied strongly from sector to sector. The main conclusions from this section are: (i) there is a variety of options per sector, (ii) per sector the options combined show significant mitigation potential, (iii) there are a few major options and a lot of smaller ones, and (iv) more than half of the potential comes at costs below USD20 tCO 2 –1 (between sectors: ''medium'' to ''robust evidence'' , ''h'' ''igh agreement'' ).

<div id="12.2.3" class="h2-container"></div>

<span id="aggregation-of-sectoral-results-and-comparison-with-earlier-analyses-and-integrated-assessment-models"></span>
=== 12.2.3 Aggregation of Sectoral Results and Comparison with Earlier Analyses and Integrated Assessment Models ===

<div id="h2-6-siblings" class="h2-siblings"></div>

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.

<div id="_idContainer009" class="_idGenObjectStyleOverride-1"></div>

[[File:e8e6d1bccbe881519c701a988236570e IPCC_AR6_WGIII_Figure_12_1.png]]

'''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.

<div id="_idContainer011" class="Basic-Text-Frame"></div>

[[File:741fade45336cc75db20488fc787b4e7 IPCC_AR6_WGIII_Figure_12_2.png]]

'''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'' ).

<div id="12.2.4" class="h2-container"></div>

<span id="sectoral-findings-on-emission-pathways-until-2050"></span>
=== 12.2.4 Sectoral Findings on Emission Pathways until 2050 ===

<div id="h2-7-siblings" class="h2-siblings"></div>

As noted previously, a more qualitative approach is followed and less quantitative information is presented for 2050. The sectoral results are summarised in Table 12.5. In addition to the many technologies that already play a role by 2030 (Table 12.3) additional technologies may be needed for deep decarbonisation, for example for managing power systems with high shares of intermittent renewable sources and for providing new fuels and associated infrastructure for sectors that are hard to decarbonise. New processes also play an important role, notably for industrial processes. In general, stronger sector coupling is needed, particularly increased integration of energy end use and supply sectors.

'''Table 12.5 | Mitigation options and their characteri''' '''stics for 2050.'''

{| class="wikitable"
|-
! Sector

! Major options

! Degree to which net zero-GHG is possible

|-
| Energy sector.

| Range of supply-side options possible (see 2030 overview).

Increased share of electricity in final energy use.

Potentially important role for hydrogen, ammonia, etc.

| Zero CO 2 energy system is possible.

|-
| Agriculture, forestry and other land use (AFOLU).

| Options comparable to those in 2030. Permanence is important.

| Some hard-to-abate activities will still have positive emissions, but for the sector as a whole, net negative emissions are possible through carbon sequestration in agriculture and forestry.

|-
| Buildings.

| Sufficiency, high performance new and existing buildings with efficient heating, ventilation, and air conditioning, especially heat pumps, building management and operation, efficient appliances, and onsite renewables backed up with demand flexibility and digitalisation measures.

| At least 8.2 GtCO 2 or 61% reduction, as compared to the baseline is possible with options on the demand side. This is a low estimate, because in some developing regions literature is not sufficient to derive a comprehensive estimate. Nearly net zero CO 2 emissions is possible if grid electricity will also be decarbonised. Carbon storage in buildings provides CDR.

|-
| Transport.

| Electrification can become a major option for many transport modes. For long-haul trucking, ships and aviation, in addition biofuels, hydrogen and potentially synthetic fuels can be applied.

| To a large extent if the electricity sector is fully decarbonised and the deployment of alternative fuels for long-haul trucking, aviation and shipping is successful.

|-
| Industry.

| Stronger role for material efficiency and recycling.

Full decarbonisation through new processes; CCS, CCU and hydrogen can become dominant.

| Approx. 85% reduction is possible. Net zero CO 2 emissions is possible with retrofitting and early retirement.

|-
| Cross-sectoral.

| Direct air carbon capture and storage.

Enhanced weathering.

Ocean-based methods.

| Contributes CDR to support net zero GHG by counterbalancing sectoral emissions.

|}

<div id="12.3" class="h1-container"></div>

<span id="carbon-dioxide-removal"></span>