Editing IPCC:AR6/WGIII/SPM (section)

== C. System Transformations to Limit Global Warming ==

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

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

<div id="h2-8-siblings" class="h2-siblings"></div>

'''C.1 Global GHG emissions are projected to peak between 2020 and at the latest before 2025 in global modelled pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot and in those that limit warming to 2°C (&gt;67%) and assume immediate action (see Table SPM.2 footnote i). [[#footnote-039|37]] In both types of modelled pathways, rapid and deep GHG emissions reductions follow throughout 2030, 2040 and 2050 ( high confidence ). Without a strengthening of policies beyond those that are implemented by the end of 2020, GHG emissions are projected to rise beyond 2025, leading to a median global warming of 3.2 [2.2 to 3.5] °C by 2100 [[#footnote-038|38]] , [[#footnote-037|39]] ( medium confidence ). Expand [[#table-spm-2|Table SPM.2]] [[#figure-spm-4|Figure SPM.4]] [[#figure-spm-5|Figure SPM.5]] Links to chapters 3.3, 3.4'''
<div id="spmbulletcont-c1" class="spmbulletcont"></div>

'''C.1.1''' Net global GHG emissions are projected to fall from 2019 levels by 27% [13–45%] by 2030 and 63% [52–76%] [[#footnote-036|40]] by 2050 in global modelled pathways that limit warming to 2°C (&gt;67%) and assuming immediate action (category C3a, Table SPM.2). This compares with reductions of 43% [34–60%] by 2030 and 84% [73–98%] by 2050 in pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot (C1, Table SPM.2) ( ''high confidence'' ). [[#footnote-035|41]] In modelled pathways that return warming to 1.5°C (&gt;50%) after a high overshoot, [[#footnote-034|42]] GHG emissions are reduced by 23% [0–44%] in 2030 and by 75% [62–91%] in 2050 (C2, Table SPM.2) ( ''high confidence'' ). Modelled pathways that are consistent with NDCs announced prior to COP26 until 2030 and assume no increase in ambition thereafter have higher emissions, leading to a median global warming of 2.8 [2.1–3.4] °C by 2100 ( ''medium confidence'' ). 23 (Figure SPM.4) {3.3}

'''Table SPM.2 | Key characteristics of the modelled global emissions pathways.''' Summary of projected CO 2 and GHG emissions, projected net zero timings and the resulting global warming outcomes. Pathways are categorised (rows), according to their likelihood of limiting warming to different peak warming levels (if peak temperature occurs before 2100) and 2100 warming levels. Values shown are for the median [p50] and 5th–95th percentiles [p5–p95], noting that not all pathways achieve net zero CO 2 or GHGs.

{| class="wikitable"
|-
! colspan="3"| '''p50 [p5–p95]''' a

! colspan="3"| '''GHG emissions (''' '''GtCO''' 2 '''-eq''' '''y''' '''r''' –1 ''')''' g

! colspan="3"| '''GHG emissions reductions from 2019 (%)''' h

! colspan="4"| '''Emissions milestones''' i, j

! colspan="2"| '''Cumulative CO''' 2 '''emissions (GtCO''' 2 ''')''' m

! '''Cumulative''' '''net-negative''' '''CO''' 2 '''emissions (GtCO''' 2 ''')'''

! colspan="2"| '''Global mean temperature changes 50% probability''' '''(''' °C ''')''' n

! colspan="3"| '''Likelihood of peak global warming staying below (%)''' o

|-
! '''Categor''' '''y''' b, c, d '''[# pathways]'''

! '''Category/subset label'''

! '''WGI SSP &amp; WGIII IPs/IMPs''' '''alignmen''' '''t''' e, f

! '''2030'''

! '''2040'''

! '''2050'''

! '''2030'''

! '''2040'''

! '''2050'''

! '''Peak CO''' 2 '''emissions (% peak before 2100)'''

! '''Peak GHG emissions (% peak before 2100)'''

! '''Net zero''' '''CO''' 2 '''(%''' '''net zero''' '''pathways)'''

! '''Net zero''' '''GHGs (%''' '''net zero''' '''pathways)''' k, l

! '''2020 to''' '''net zero''' '''CO''' 2

! '''2020–2100'''

! '''Year of''' '''net zero''' '''CO''' 2 '''to 2100'''

! '''at peak warming'''

! '''2100'''

! '''&lt;1.5°C'''

! '''&lt;2.0°C'''

! '''&lt;3.0°C'''

|-
! colspan="3"| Modelled global emissions pathways categorised by projected global warming levels (GWL). Detailed likelihood definitions are provided in SPM Box 1.

The five illustrative scenarios ( SSPx-yy ) considered by AR6 WGI and the Illustrative (Mitigation) Pathways assessed in WGIII are aligned with the temperature categories and are indicated in a separate column. Global emission pathways contain regionally differentiated information. This assessment focuses on their global characteristics.

! colspan="3"| Projected median annual GHG emissions in the year across the scenarios, with the 5th–95th percentile in brackets.

Modelled GHG emissions in 2019: 55 [53–58] GtCO 2 -eq .

! colspan="3"| Projected median GHG emissions reductions of pathways in the year across the scenarios compared to modelled 2019, with the 5th–95th percentile in brackets. Negative numbers indicate increase in emissions compared to 2019.

! colspan="2"| Median 5-year intervals at which projected CO 2 &amp; GHG emissions peak, with the 5th–95th percentile interval in square brackets. Percentage of peaking pathways is denoted in round brackets.

Three dots (…) denotes emissions peak in 2100 or beyond for that percentile.

! colspan="2"| Median 5-year intervals at which projected CO 2 &amp; GHG emissions of pathways in this category reach net zero , with the 5th–95th percentile interval in square brackets. Percentage of net zero pathways is denoted in round brackets.

Three dots (…) denotes net zero not reached for that percentile.

! colspan="2"| Median cumulative net CO 2 emissions across the projected scenarios in this category until reaching net zero or until 2100, with the 5th–95th percentile interval in square brackets.

! Median cumulative net-negative CO 2 emissions between the year of net zero CO 2 and 2100. More net-negative results in greater temperature declines after peak.

! colspan="2"| Projected temperature change of pathways in this category (50% probability across the range of climate uncertainties), relative to 1850–1900, at peak warming and in 2100, for the median value across the scenarios and the 5th–95th percentile interval in square brackets.

! colspan="3"| Median likelihood that the projected pathways in this category stay below a given global warming level, with the 5th–95th percentile interval in square brackets.

|-
| '''C1 [97]'''

| '''limit warming to 1.5°C (&gt;50%) with no or limited overshoot'''

|
| 31

[21–36]

| 17

[6–23]

| 9

[1–15]

| 43

[34–60]

| 69

[58–90]

| 84

[73–98]

| rowspan="4" colspan="2"| 2020–2025 (100%)

[2020–2025]

| rowspan="4"| 2050–2055 (100%)

[2035–2070]

| 2095–2100 (52%)

[2050–...]

| 510

[330–710]

| 320

[–210 to 570]

| –220

[–660 to –20]

| 1.6

[1.4–1.6]

| 1.3

[1.1–1.5]

| 38

[33–58]

| 90

[86–97]

| 100

[99–100]

|-
| '''C1a [50]'''

| '''… with''' '''net zero''' '''GHGs'''

| SSP1–1.9,

SP

LD

| 33

[22–37]

| 18

[6–24]

| 8

[0–15]

| 41

[31–59]

| 66

[58–89]

| 85

[72–100]

| 2070–2075 (100%)

[2050–2090]

| 550

[340–760]

| 160

[–220 to 620]

| –360

[–680 to –140]

| 1.6

[1.4–1.6]

| 1.2

[1.1–1.4]

| 38

[34–60]

| 90

[85–98]

| 100

[99–100]

|-
| rowspan="2"| '''C1b [47]'''

| rowspan="2"| '''… without''' '''net zero''' '''GHGs'''

| rowspan="2"| Ren

| rowspan="2"| 29

[21–36]

| rowspan="2"| 16

[7–21]

| rowspan="2"| 9

[4–13]

| rowspan="2"| 48

[35–61]

| rowspan="2"| 70

[62–87]

| rowspan="2"| 84

[76–93]

| …–… [0%]

| rowspan="2"| 460

[320–590]

| rowspan="2"| 360

[10–540]

| rowspan="2"| –60

[–440 to 0]

| rowspan="2"| 1.6

[1.5–1.6]

| rowspan="2"| 1.4

[1.3–1.5]

| rowspan="2"| 37

[33–56]

| rowspan="2"| 89

[87–96]

| rowspan="2"| 100

[99–100]

|-
| […–…]

|-
| rowspan="2"| '''C2 [133]'''

| rowspan="2"| '''return warming to 1.5°C (&gt;50%) after a high overshoot'''

| rowspan="2"| Neg

| rowspan="2"| 42

[31–55]

| rowspan="2"| 25

[17–34]

| rowspan="2"| 14

[5–21]

| rowspan="2"| 23

[0–44]

| rowspan="2"| 55

[40–71]

| rowspan="2"| 75

[62–91]

| colspan="2"| 2020–2025 (100%)

| rowspan="2"| 2055–2060 (100%)

[2045–2070]

| rowspan="2"| 2070–2075 (87%)

[2055–...]

| rowspan="2"| 720

[530–930]

| rowspan="2"| 400

[–90 to 620]

| rowspan="2"| –360

[–680 to –60]

| rowspan="2"| 1.7

[1.5–1.8]

| rowspan="2"| 1.4

[1.2–1.5]

| rowspan="2"| 24

[15–42]

| rowspan="2"| 82

[71–93]

| rowspan="2"| 100

[99–100]

|-
| [2020–2030]

| [2020–2025]

|-
| rowspan="2"| '''C3 [311]'''

| rowspan="2"| '''limit warming to 2°C (&gt;67%)'''

| rowspan="2"|
| rowspan="2"| 44

[32–55]

| rowspan="2"| 29

[20–36]

| rowspan="2"| 20

[13–26]

| rowspan="2"| 21

[1–42]

| rowspan="2"| 46

[34–63]

| rowspan="2"| 64

[53–77]

| colspan="2"| 2020–2025 (100%)

| rowspan="2"| 2070–2075 (93%)

[2055–...]

| rowspan="2"| ...–... (30%)

[2075–...]

| rowspan="2"| 890

[640–1160]

| rowspan="2"| 800

[510–1140]

| rowspan="2"| –40

[–290 to 0]

| rowspan="2"| 1.7

[1.6–1.8]

| rowspan="2"| 1.6

[1.5–1.8]

| rowspan="2"| 20

[13–41]

| rowspan="2"| 76

[68–91]

| rowspan="2"| 99

[98–100]

|-
| [2020–2030]

| [2020–2025]

|-
| '''C3a [204]'''

| '''… with action starting in 2020'''

| SSP1–2.6

| 40

[30–49]

| 29

[21–36]

| 20

[14–27]

| 27

[13–45]

| 47

[35–63]

| 63

[52–76]

| colspan="2"| 2020–2025 (100%)

[2020–2025]

| 2070–2075 (91%)

[2055–...]

| ...–... (24%)

[2080–...]

| 860

[640–1180]

| 790

[480–1150]

| –30

[–280 to 0]

| 1.7

[1.6–1.8]

| 1.6

[1.5–1.8]

| 21

[14–42]

| 78

[69–91]

| 100

[98–100]

|-
| '''C3b [97]'''

| '''… NDCs until 2030'''

| GS

| 52

[47–56]

| 29

[20–36]

| 18

[10–25]

| 5

[0–14]

| 46

[34–63]

| 68

[56–82]

| rowspan="3" colspan="2"| 2020–2025 (100%)

[2020–2030]

| 2065–2070 (97%)

[2055–2090]

| ...–... (41%)

[2075–...]

| 910

[720–1150]

| 800

[560–1050]

| –60

[–300 to 0]

| 1.8

[1.6–1.8]

| 1.6

[1.5–1.7]

| 17

[12–35]

| 73

[67–87]

| 99

[98–99]

|-
| '''C4 [159]'''

| '''limit warming to 2°C (&gt;50%)'''

|
| 50

[41–56]

| 38

[28–44]

| 28

[19–35]

| 10

[0–27]

| 31

[20–50]

| 49

[35–65]

| 2080–2085 (86%)

[2065–...]

| ...–... (31%)

[2075–...]

| 1210

[970–1490]

| 1160

[700–1490]

| –30

[–390 to 0]

| 1.9

[1.7–2.0]

| 1.8

[1.5–2.0]

| 11

[7–22]

| 59

[50–77]

| 98

[95–99]

|-
| '''C5 [212]'''

| '''limit warming to 2.5°C (&gt;50%)'''

|
| 52

[46–56]

| 45

[37–53]

| 39

[30–49]

| 6

[–1 to 18]

| 18

[4–33]

| 29

[11–48]

| ...–... (41%)

[2080–...]

| ...–... (12%)

[2090–...]

| 1780

[1400–2360]

| 1780

[1260–2360]

| 0

[–160 to 0]

| 2.2

[1.9–2.5]

| 2.1

[1.9–2.5]

| 4

[0–10]

| 37

[18–59]

| 91

[83–98]

|-
| rowspan="2"| '''C6 [97]'''

| rowspan="2"| '''limit warming to 3°C (&gt;50%)'''

| rowspan="2"| SSP2–4.5

ModAct

| rowspan="2"| 54

[50–62]

| rowspan="2"| 53

[48–61]

| rowspan="2"| 52

[45–57]

| rowspan="2"| 2

[–10 to 11]

| rowspan="2"| 3

[–14 to 14]

| rowspan="2"| 5

[–2 to 18]

| 2030–2035 (96%)

| 2020–2025 (97%)

| rowspan="6" colspan="2"| no net zero

| rowspan="6"| no net zero

| rowspan="2"| 2790

[2440–3520]

| rowspan="6"| no net zero

| rowspan="6"| temperature does not peak by 2100

| rowspan="2"| 2.7

[2.4–2.9]

| rowspan="2"| 0

[0–0]

| rowspan="2"| 8

[2–18]

| rowspan="2"| 71

[53–88]

|-
| colspan="2"| [2020–2090]

|-
| rowspan="2"| '''C7 [164]'''

| rowspan="2"| '''limit warming to 4°C (&gt;50%)'''

| rowspan="2"| SSP3–7.0

CurPol

| rowspan="2"| 62

[53–69]

| rowspan="2"| 67

[56–76]

| rowspan="2"| 70

[58–83]

| rowspan="2"| –11

[–18 to 3]

| rowspan="2"| –19

[–31 to 1]

| rowspan="2"| –24

[–41 to –2]

| 2085–2090 (57%)

| 2090–2095 (56%)

| rowspan="2"| 4220

[3160–5000]

| rowspan="2"| 3.5

[2.8–3.9]

| rowspan="2"| 0

[0–0]

| rowspan="2"| 0

[0–2]

| rowspan="2"| 22

[7–60]

|-
| colspan="2"| [2040–...]

|-
| rowspan="2"| '''C8 [29]'''

| rowspan="2"| '''exceed warming of 4°C (≥50%)'''

| rowspan="2"| SSP5–8.5

| rowspan="2"| 71

[69–81]

| rowspan="2"| 80

[78–96]

| rowspan="2"| 88

[82–112]

| rowspan="2"| –20

[–34 to –17]

| rowspan="2"| –35

[–65 to –29]

| rowspan="2"| –46

[–92 to –36]

| rowspan="2" colspan="2"| 2080–2085 (90%)

[2070–...]

| 5600

| rowspan="2"| 4.2

[3.7–5.0]

| rowspan="2"| 0

[0–0]

| rowspan="2"| 0

[0–0]

| rowspan="2"| 4

[0–11]

|-
| [4910–7450]

|}

a Values in the table refer to the 50th and [5th–95th] percentile values across the pathways falling within a given category as defined in Box SPM.1. For emissions-related columns these values relate to the distribution of all the pathways in that category. Harmonised emissions values are given for consistency with projected global warming outcomes using climate emulators. Based on the assessment of climate emulators in AR6 WGI (WG1 Chapter 7, Box 7.1), two climate emulators are used for the probabilistic assessment of the resulting warming of the pathways. For the ‘Temperature change’ and ‘Likelihood’ columns, the single upper-row values represent the 50th percentile across the pathways in that category and the median [50th percentile] across the warming estimates of the probabilistic MAGICC climate model emulator. For the bracketed ranges, the median warming for every pathway in that category is calculated for each of the two climate model emulators (MAGICC and FaIR). Subsequently, the 5th and 95th percentile values across all pathways for each emulator are calculated. The coolest and warmest outcomes (i.e., the lowest p5 of two emulators, and the highest p95, respectively) are shown in square brackets. These ranges therefore cover both the uncertainty of the emissions pathways as well as the climate emulators’ uncertainty.

b For a description of pathways categories see Box SPM.1.

c All global warming levels are relative to 1850–1900. (See footnote n below and Box SPM.1 45 for more details.)

d C3 pathways are sub-categorised according to the timing of policy action to match the emissions pathways in Figure SPM.4. Two pathways derived from a cost-benefit analysis have been added to C3a, whilst 10 pathways with specifically designed near-term action until 2030, whose emissions fall below those implied by NDCs announced prior to COP26, are not included in either of the two subsets.

e Alignment with the categories of the illustrative SSP scenarios considered in AR6 WGI, and the Illustrative (Mitigation) Pathways (IPs/IMPs) of WGIII. The IMPs have common features such as deep and rapid emissions reductions, but also different combinations of sectoral mitigation strategies. See Box SPM.1 for an introduction of the IPs and IMPs, and [https://www.ipcc.ch/chapters/chapter-3 Chapter 3] for full descriptions. {3.2, 3.3, Annex III.II.4}

f The Illustrative Mitigation Pathway ‘Neg’ has extensive use of carbon dioxide removal (CDR) in the AFOLU, energy and the industry sectors to achieve net negative emissions. Warming peaks around 2060 and declines to below 1.5°C (50% likelihood) shortly after 2100. Whilst technically classified as C3, it strongly exhibits the characteristics of C2 high-overshoot pathways, hence it has been placed in the C2 category. See Box SPM.1 for an introduction of the IPs and IMPs.

g The 2019 range of harmonised GHG emissions across the pathways [53–58 GtCO 2 -eq] is within the uncertainty ranges of 2019 emissions assessed in [https://www.ipcc.ch/chapters/chapter-2 Chapter 2] [53–66 GtCO 2 -eq]. 49 (Figure SPM.1, Figure SPM.2, Box SPM.1)

h Rates of global emission reduction in mitigation pathways are reported on a pathway-by-pathway basis relative to harmonised modelled global emissions in 2019 rather than the global emissions reported in SPM Section B and Chapter 2; this ensures internal consistency in assumptions about emission sources and activities, as well as consistency with temperature projections based on the physical climate science assessment by WGI. 49 {Annex III.II.2.5} . Negative values (e.g., in C7, C8) represent an increase in emissions.

i Emissions milestones are provided for five-year intervals in order to be consistent with the underlying five-year time-step data of the modelled pathways. Peak emissions (CO 2 and GHGs) are assessed for five-year reporting intervals starting in 2020. The interval 2020–2025 signifies that projected emissions peak as soon as possible between 2020 and at latest before 2025. The upper five-year interval refers to the median interval within which the emissions peak or reach net zero. Ranges in square brackets underneath refer to the range across the pathways, comprising the lower bound of the 5th percentile five-year interval and the upper bound of the 95th percentile five-year interval. Numbers in round brackets signify the fraction of pathways that reach specific milestones.

j Percentiles reported across all pathways in that category include those that do not reach net zero before 2100 (fraction of pathways reaching net zero is given in round brackets). If the fraction of pathways that reach net zero before 2100 is lower than the fraction of pathways covered by a percentile (e.g., 0.95 for the 95th percentile), the percentile is not defined and denoted with ‘…’. The fraction of pathways reaching net zero includes all with reported non-harmonised, and/or harmonised emissions profiles that reach net zero. Pathways were counted when at least one of the two profiles fell below 100 MtCO 2 yr –1 until 2100.

k The timing of net zero is further discussed in SPM C2.4 and Cross-Chapter Box 3 in [https://www.ipcc.ch/chapters/chapter-3 Chapter 3] on net zero CO 2 and net zero GHG emissions.

l For cases where models do not report all GHGs, missing GHG species are infilled and aggregated into a Kyoto basket of GHG emissions in CO 2 -eq defined by the 100-year global warming potential. For each pathway, reporting of CO 2 , CH 4 , and N 2 O emissions was the minimum required for the assessment of the climate response and the assignment to a climate category. Emissions pathways without climate assessment are not included in the ranges presented here. {See Annex III.II.5}

m Cumulative emissions are calculated from the start of 2020 to the time of net zero and 2100, respectively. They are based on harmonised net CO 2 emissions, ensuring consistency with the WGI assessment of the remaining carbon budget. 50 {Box 3.4}

n Global mean temperature change for category (at peak, if peak temperature occurs before 2100, and in 2100) relative to 1850–1900, based on the median global warming for each pathway assessed using the probabilistic climate model emulators calibrated to the AR6 WGI assessment. 12 (See also Box SPM.1) {Annex III.II.2.5; WGI Cross-Chapter Box 7.1}

o Probability of staying below the temperature thresholds for the pathways in each category, taking into consideration the range of uncertainty from the climate model emulators consistent with the AR6 WGI assessment. The probabilities refer to the probability at peak temperature. Note that in the case of temperature overshoot (e.g., category C2 and some pathways in C1), the probabilities of staying below at the end of the century are higher than the probabilities at peak temperature.

'''C.1.2''' In modelled pathways that limit warming to 2°C (&gt;67%) assuming immediate action, global net CO 2 emissions are reduced compared to modelled 2019 emissions by 27% [11–46%] in 2030 and by 52% [36–70%] in 2040; and global CH 4 emissions are reduced by 24% [9–53%] in 2030 and by 37% [20–60%] in 2040. In pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot global net CO 2 emissions are reduced compared to modelled 2019 emissions by 48% [36–69%] in 2030 and by 80% [61–109%] in 2040; and global CH 4 emissions are reduced by 34% [21–57%] in 2030 and 44% [31–63%] in 2040. There are similar reductions of non-CO 2 emissions by 2050 in both types of pathways: CH 4 is reduced by 45% [25–70%]; N 2 O is reduced by 20% [–5 to +55%]; and F-gases are reduced by 85% [20–90%]. [[#footnote-033|43]] Across most modelled pathways, this is the maximum technical potential for anthropogenic CH 4 reductions in the underlying models ( ''high confidence'' ). Further emissions reductions, as illustrated by the IMP-SP pathway, may be achieved through changes in activity levels and/or technological innovations beyond those represented in the majority of the pathways ( ''medium confidence'' ). Higher emissions reductions of CH 4 could further reduce peak warming. ( ''high confidence'' ) (Figure SPM.5) {3.3}

'''C.1.3''' In modelled pathways consistent with the continuation of policies implemented by the end of 2020, GHG emissions continue to rise, leading to global warming of 3.2 [2.2–3.5] °C by 2100 (within C5–C7, Table SPM.2) ( ''medium confidence'' ). Pathways that exceed warming of &gt;4°C (≥50%) (C8, SSP5-8.5, Table SPM.2) would imply a reversal of current technology and/or mitigation policy trends ( ''medium confidence'' ). Such warming could occur in emission pathways consistent with policies implemented by the end of 2020 if climate sensitivity is higher than central estimates ( ''high confidence'' ). (Table SPM.2, Figure SPM.4) {3.3, Box 3.3}

'''C.1.4''' Global modelled pathways falling into the lowest temperature category of the assessed literature (C1, Table SPM.2) are on average associated with a higher median peak warming in AR6 compared to pathways in the same category in SR1.5. In the modelled pathways in AR6, the likelihood of limiting warming to 1.5°C has on average declined compared to SR1.5. This is because GHG emissions have risen since 2017, and many recent pathways have higher projected emissions by 2030, higher cumulative net CO 2 emissions and slightly later dates for reaching net zero CO 2 or net zero GHG emissions. High mitigation challenges, for example, due to assumptions of slow technological change, high levels of global population growth, and high fragmentation as in the Shared Socio-economic Pathway SSP3, may render modelled pathways that limit warming to 2°C (&gt;67%) or lower infeasible. ( ''medium confidence'' ) (Table SPM.2, Box SPM.1) {3.3, 3.8, Annex III Figure II.1, Annex III Figure II.3}

'''Box SPM.1 | Assessment of Modelled Global Emission Scenarios'''

A wide range of modelled global emission pathways and scenarios from the literature is assessed in this report, including pathways and scenarios with and without mitigation. [[#footnote-032|44]] Emissions pathways and scenarios project the evolution of GHG emissions based on a set of internally consistent assumptions about future socio-economic conditions and related mitigation measures. [[#footnote-031|45]] These are quantitative projections and are neither predictions nor forecasts. Around half of all modelled global emission scenarios assume cost-effective approaches that rely on least-cost emission abatement options globally. The other half look at existing policies and regionally and sectorally differentiated actions. Most do not make explicit assumptions about global equity, environmental justice or intra-regional income distribution. Global emission pathways, including those based on cost-effective approaches, contain regionally differentiated assumptions and outcomes, and have to be assessed with the careful recognition of these assumptions. This assessment focuses on their global characteristics. The majority of the assessed scenarios (about 80%) have become available since the SR1.5, but some were assessed in that report. Scenarios with and without mitigation were categorised based on their projected global warming over the 21st century, following the same scheme as in the SR1.5 for warming up to and including 2°C. {1.5, 3.2, 3.3, Annex III.II.2, Annex III.II.3}

Scenario categories are defined by their likelihood of exceeding global warming levels (at peak and in 2100) and referred to in this report as follows: [[#footnote-030|46]] , [[#footnote-029|47]]

'''•''' Category C1 comprises modelled scenarios that limit warming to 1.5°C in 2100 with a likelihood of greater than 50%, and reach or exceed warming of 1.5°C during the 21st century with a likelihood of 67% or less. In this report, these scenarios are referred to as scenarios that limit warming to 1.5°C (&gt;50%) with no or limited overshoot. Limited overshoot refers to exceeding 1.5°C global warming by up to about 0.1°C and for up to several decades. [[#footnote-028|48]]

'''•''' Category C2 comprises modelled scenarios that limit warming to 1.5°C in 2100 with a likelihood of greater than 50%, and exceed warming of 1.5°C during the 21st century with a likelihood of greater than 67%. In this report, these scenarios are also referred to as scenarios that return warming to 1.5°C (&gt;50%) after a high overshoot. High overshoot refers to temporarily exceeding 1.5°C global warming by 0.1°C–0.3°C for up to several decades.

'''•''' Category C3 comprises modelled scenarios that limit peak warming to 2°C throughout the 21st century with a likelihood of greater than 67%. In this report, these scenarios are also referred to as scenarios that limit warming to 2°C (&gt;67%) ''.''

'''•''' Categories C4, C5, C6 and C7 comprise modelled scenarios that limit warming to 2°C, 2.5°C, 3°C, 4°C, respectively, throughout the 21st century with a likelihood of greater than 50%. In some scenarios in C4 and many scenarios in C5–C7, warming continues beyond the 21st century.

'''•''' Category C8 comprises modelled scenarios that exceed warming of 4°C during the 21st century with a likelihood of 50% or greater. In these scenarios warming continues to rise beyond the 21st century.

Categories of modelled scenarios are distinct and do not overlap; they do not contain categories consistent with lower levels of global warming, for example, the category of C3 scenarios that limit warming to 2°C (&gt;67%) does not include the C1 and C2 scenarios that limit or return warming to 1.5°C (&gt;50%). Where relevant, scenarios belonging to the group of categories C1–C3 are referred to in this report as scenarios that limit warming to 2°C (&gt;67%) or lower.

Methods to project global warming associated with the scenarios were updated to ensure consistency with the AR6 WGI assessment of physical climate science. [[#footnote-027|49]] {3.2, Annex III.II.2.5; AR6 WGI Cross-Chapter Box 7.1}

These updated methods affect the categorisation of some scenarios. On average across scenarios, peak global warming is projected to be lower by up to about 0.05 [±0.1] °C than if the same scenarios were evaluated using the SR1.5 methodology, and global warming in 2100 is projected to be lower by about 0.1 [±0.1] °C. {Annex III.II.٢.٥.١, Annex III Figure II.٣}

Resulting changes to the emission characteristics of scenario categories described in Table SPM.2 interact with changes in the characteristics of the wider range of emission scenarios published since the SR1.5. Proportionally more scenarios assessed in AR6 are designed to limit temperature overshoot and more scenarios limit large-scale net negative CO 2 emissions than in SR1.5. As a result, AR6 scenarios in the lowest temperature category (C1) generally reach net zero GHG emissions later in the 21st century than scenarios in the same category assessed in SR1.5, and about half do not reach net zero GHG by 2100. The rate of decline of GHG emissions in the near term by 2030 in category C1 scenarios is very similar to the assessed rate in SR1.5, but absolute GHG emissions of category C1 scenarios in AR6 are slightly higher in 2030 than in SR1.5, since the reductions start from a higher emissions level in 2020. (Table SPM.2) {Annex III, 2.5, 3.2, 3.3}

The large number of global emissions scenarios assessed, including 1202 scenarios with projected global warming outcomes using climate emulators, come from a wide range of modelling approaches. They include the five illustrative scenarios (Shared Socio-economic Pathways; SSPs) assessed by WGI for their climate outcomes but cover a wider and more varied set in terms of assumptions and modelled outcomes. For this assessment, Illustrative Mitigation Pathways (IMPs) were selected from this larger set to illustrate a range of different mitigation strategies that would be consistent with different warming levels. The IMPs illustrate pathways that achieve deep and rapid emissions reductions through different combinations of mitigation strategies. The IMPs are not intended to be comprehensive and do not address all possible themes in the underlying report. They differ in terms of their focus, for example, placing greater emphasis on renewables (IMP-Ren), deployment of carbon dioxide removal that results in net negative global GHG emissions (IMP-Neg), and efficient resource use as well as shifts in consumption patterns globally, leading to low demand for resources, while ensuring a high level of services and satisfying basic needs (IMP-LD) (Figure SPM.5). Other IMPs illustrate the implications of a less rapid introduction of mitigation measures followed by a subsequent gradual strengthening (IMP-GS), and how shifting global pathways towards sustainable development, including by reducing inequality, can lead to mitigation (IMP-SP). The IMPs reach different climate goals as indicated in Table SPM.2 and Box SPM.1, Figure 1. {1.5, 3.1, 3.2, 3.3, 3.6, Figure 3.7, Figure 3.8, Box 3.4, Annex III.II.2.4}

<div id="_idContainer026" class="Body-copy_Boxes_Blue-Boxes_•-Box-body"></div>

[[File:ebe1d7ff4a7a0f1e1c00dc5d13003cfe IPCC_AR6_WGIII_Box_SPM_1_Figure_1.png]]

'''Box SPM.1, Figure 1 | Projected global mean warming of the ensemble of modelled scenarios included in the climate categories C1–C8 and IMPs (based on emulators calibrated to the WGI assessment), as well as five illustrative scenarios (SSPx-y) as considered by AR6 WGI.''' '''Panel a''' shows the p5–p95 range of projected median warming across global modelled pathways within a category, with the category medians (line). '''Panel b''' shows the peak and 2100 emulated temperature outcomes for the categories C1 to C8 and for IMPs, and the five illustrative scenarios (SSPx-y) as considered by AR6 WGI. The boxes show the p5–p95 range within each scenario category, as in panel a. The combined p5–p95 range across scenarios and the climate uncertainty for each category C1–C8 is also shown for 2100 warming (thin vertical lines). (Table SPM.2) {Figure 3.11; AR6 WGI Figure SPM.8}

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

<div id="h2-9-siblings" class="h2-siblings"></div>

'''C.2 Global net zero CO 2 emissions are reached in the early 2050s in modelled pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot, and around the early 2070s in modelled pathways that limit warming to 2°C (&gt;67%). Many of these pathways continue to net negative CO 2 emissions after the point of net zero. These pathways also include deep reductions in other GHG emissions. The level of peak warming depends on cumulative CO 2 emissions until the time of net zero CO 2 and the change in non-CO 2 climate forcers by the time of peaking. Deep GHG emissions reductions by 2030 and 2040, particularly reductions of methane emissions, lower peak warming, reduce the likelihood of overshooting warming limits and lead to less reliance on net negative CO 2 emissions that reverse warming in the latter half of the century. Reaching and sustaining global net zero GHG emissions results in a gradual decline in warming. ( high confidence ) Expand [[#table-spm-2|Table SPM.2]] Links to chapters 3.3, 3.5, Box 3.4, Cross-Chapter Box 3 in Chapter 3, AR6 WGI SPM D1.8'''
<div id="spmbulletcont-c2" class="spmbulletcont"></div>

'''C.2.1''' Modelled global pathways limiting warming to 1.5°C (&gt;50%) with no or limited overshoot are associated with projected cumulative net CO 2 emissions [[#footnote-026|50]] until the time of net zero CO 2 of 510 [330–710] GtCO 2 . Pathways limiting warming to 2°C (&gt;67%) are associated with 890 [640–1160] GtCO 2 (Table SPM.2). ( ''high confidence'' ) {3.3, Box 3.4}

'''C.2.2''' Modelled global pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot involve more rapid and deeper near-term GHG emissions reductions through to 2030, and are projected to have less net negative CO 2 emissions and less carbon dioxide removal (CDR) in the longer term, than pathways that return warming to 1.5°C (&gt;50%) after a high overshoot (C2 category). Modelled pathways that limit warming to 2°C (&gt;67%) have on average lower net negative CO 2 emissions compared to pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot and pathways that return warming to 1.5°C (&gt;50%) after a high overshoot (C1 and C2 categories respectively). Modelled pathways that return warming to 1.5°C (&gt;50%) after a high overshoot (C2 category) show near-term GHG emissions reductions similar to pathways that limit warming to 2°C (&gt;67%) (C3 category). For a given peak global warming level, greater and more rapid near-term GHG emissions reductions are associated with later net zero CO 2 dates. ( ''high confidence'' ) (Table SPM.2) {3.3, Table 3.5, Cross-Chapter Box 3 in Chapter 3, Annex I: Glossary}

'''C.2.3''' Future non-CO 2 warming depends on reductions in non-CO 2 GHGs, aerosols and their precursors, and ozone precursor emissions. In modelled global low-emission pathways, the projected reduction of cooling and warming aerosol emissions over time leads to net warming in the near- to mid-term. In these mitigation pathways, the projected reductions of cooling aerosols are mostly due to reduced fossil fuel combustion that was not equipped with effective air pollution controls. Non-CO 2 GHG emissions at the time of net zero CO 2 are projected to be of similar magnitude in modelled pathways that limit warming to 2°C (&gt;67%) or lower. These non-CO 2 GHG emissions are about 8 [5–11] GtCO 2 -eq yr –1 , with the largest fraction from CH 4 (60% [55–80%]), followed by N 2 O (30% [20–35%]) and F-gases (3% [2–20%]). [[#footnote-025|51]] Due to the short lifetime of CH 4 in the atmosphere, projected deep reduction of CH 4 emissions up until the time of net zero CO 2 in modelled mitigation pathways effectively reduces peak global warming. ( ''high confidence'' ) {3.3; AR6 WGI SPM D1.7}

'''C.2.4''' At the time of global net zero GHG emissions, net negative CO 2 emissions counterbalance metric-weighted non-CO 2 GHG emissions. Typical emissions pathways that reach and sustain global net zero GHG emissions based on the 100-year global warming potential (GWP-100) 7 are projected to result in a gradual decline of global warming. About half of the assessed pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot (C1 category) reach net zero GHG emissions during the second half of the 21st century. These pathways show greater reduction in global warming after the peak to 1.2 [1.1–1.4] °C by 2100 than modelled pathways in the same category that do not reach net zero GHG emissions before 2100 and that result in warming of 1.4 [1.3–1.5] °C by 2100. In modelled pathways that limit warming to 2°C (&gt;67%) (C3 category), there is no significant difference in warming by 2100 between those pathways that reach net zero GHGs (around 30%) and those that do not ( ''high confidence'' ). In pathways that limit warming to 2°C (&gt;67%) or lower and that do reach net zero GHG, net zero GHG occurs around 10–40 years later than net zero CO 2 emissions ( ''medium confidence'' ). {Cross-Chapter Box 2 in Chapter 2, 3.3, Cross-Chapter Box 3 in Chapter 3; AR6 WGI SPM D1.8}

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

<div id="h2-10-siblings" class="h2-siblings"></div>

'''C.3 All global modelled pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot, and those that limit warming to 2°C (&gt;67%), involve rapid and deep and in most cases immediate GHG emission reductions in all sectors. Modelled mitigation strategies to achieve these reductions include transitioning from fossil fuels without CCS to very low- or zero-carbon energy sources, such as renewables or fossil fuels with CCS, demand side measures and improving efficiency, reducing non-CO 2 emissions, and deploying carbon dioxide removal (CDR) methods to counterbalance residual GHG emissions. Illustrative Mitigation Pathways (IMPs) show different combinations of sectoral mitigation strategies consistent with a given warming level. ( high confidence ) Expand [[#figure-spm-5|Figure SPM.5]] Links to chapters 3.2, 3.3, 3.4, 6.4, 6.6'''
<div id="spmbulletcont-c3" class="spmbulletcont"></div>

'''C.3.1''' There is a variation in the contributions of different sectors in modelled mitigation pathways, as illustrated by the Illustrative Mitigation Pathways (IMPs). However, modelled pathways that limit warming to 2°C (&gt;67%) or lower share common characteristics, including rapid and deep GHG emission reductions. Doing less in one sector needs to be compensated by further reductions in other sectors if warming is to be limited. ( ''high confidence'' ) (Figure SPM.5) {3.2, 3.3, 3.4}

'''C.3.2''' In modelled pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot, the global use of coal, oil and gas in 2050 is projected to decline with median values of about 95%, 60% and 45% respectively, compared to 2019. The interquartile ranges are (80 to 100%), (40 to 75%) and (20 to 60%) and the p5–p95 ranges are [60 to 100%], [25 to 90%] and [–30 to +85%], respectively. In modelled pathways that limit warming to 2°C (&gt;67%), these projected declines have a median value and interquartile range of 85% (65 to 95%), 30% (15 to 50%) and 15% (–10 to +40%) respectively by 2050. The use of coal, oil and gas without CCS in modelled pathways that limit warming to 1.5°C (&gt;50%) with no or limited overshoot is projected to be reduced to a greater degree, with median values of about 100%, 60% and 70% in 2050 compared to 2019. The interquartile ranges are (95 to 100%), (45 to 75%) and (60 to 80%) and the p5–p95 ranges about [85 to 100%], [25 to 90%] and [35 to 90%] for coal, oil and gas respectively. In these global modelled pathways, in 2050 almost all electricity is supplied from zero- or low-carbon sources, such as renewables or fossil fuels with CCS, combined with increased electrification of energy demand. As indicated by the ranges, choices in one sector can be compensated for by choices in another while being consistent with assessed warming levels. [[#footnote-024|52]] ( ''high confidence'' ) {3.4, 3.5, Table 3.6, Figure 3.22, Figure 6.35}

'''C.3.3''' In modelled pathways that reach global net zero CO 2 emissions: at the point they reach net zero, 5–16 GtCO 2 of emissions from some sectors are compensated for by net negative CO 2 emissions in other sectors. In most global modelled pathways that limit warming to 2°C (&gt;67%) or lower, the AFOLU sector, via reforestation and reduced deforestation, and the energy supply sector reach net zero CO 2 emissions earlier than the buildings, industry and transport sectors. ( ''high confidence'' ) (Figure SPM.5e,f) {3.4}

'''C.3.4''' In modelled pathways that reach global net zero GHG emissions, at the point they reach net zero GHG, around 74% [54 to 90%] of global emissions reductions are achieved by CO 2 reductions in energy supply and demand, 13% [4 to 20%] by CO 2 mitigation options in the AFOLU sector, and 13% [10 to 18%] through the reduction of non-CO 2 emissions from land-use, energy and industry ( ''medium confidence'' ). (Figure SPM.5f) {3.3, 3.4}

'''C.3.5''' Methods and levels of CDR deployment in global modelled mitigation pathways vary depending on assumptions about costs, availability and constraints. [[#footnote-023|53]] In modelled pathways that report CDR and that limit warming to 1.5°C (&gt;50%) with no or limited overshoot, global cumulative CDR during 2020–2100 from bioenergy with carbon dioxide capture and storage (BECCS) and direct air carbon dioxide capture and storage (DACCS) is 30–780 GtCO 2 and 0–310 GtCO 2 , respectively. In these modelled pathways, the AFOLU sector contributes 20–400 GtCO 2 net negative emissions. Total cumulative net negative CO 2 emissions including CDR deployment across all options represented in these modelled pathways are 20–660 GtCO 2 . In modelled pathways that limit warming to 2°C (&gt;67%), global cumulative CDR during 2020–2100 from BECCS and DACCS is 170–650 GtCO 2 and 0–250 GtCO 2 respectively, the AFOLU sector contributes 10–250 GtCO 2 net negative emissions, and total cumulative net negative CO 2 emissions are around 40 [0–290] GtCO 2 . (Table SPM.2) ( ''high confidence'' ) {Table 3.2, 3.3, 3.4}

'''C.3.6''' All mitigation strategies face implementation challenges, including technology risks, scaling, and costs. Many challenges, such as dependence on CDR, pressure on land and biodiversity (e.g., bioenergy) and reliance on technologies with high upfront investments (e.g., nuclear), are significantly reduced in modelled pathways that assume using resources more efficiently (e.g., IMP-LD) or that shift global development towards sustainability (e.g., IMP-SP). ( ''high confidence'' ) (Figure SPM.5) {3.2, 3.4, 3.7, 3.8, 4.3, 5.1}

<div id="figure-spm-5" class="Basic-Text-Frame"></div>

[[File:a0179ccd3aef3d563e228beb16418606 IPCC_AR6_WGIII_FigureSPM5abcd.png]]

[[File:9a0c05dd78c09151b72c92d224b301ff IPCC_AR6_WGIII_FigureSPM5ef.png]]

'''Figure SPM.5: Illustrative Mitigation Pathways (IMPs) and net zero CO''' 2 '''and GHG emissions strategies.''' '''Panels a and b''' show the development of global GHG and CO 2 emissions in modelled global pathways (upper sub-panels) and the associated timing of when GHG and CO 2 emissions reach net zero (lower sub-panels). '''Panels c and d''' show the development of global CH 4 and N 2 O emissions, respectively. Coloured ranges denote the 5th to 95th percentile across pathways. The red ranges depict emissions pathways assuming policies that were implemented by the end of 2020 and pathways assuming implementation of NDCs (announced prior to COP26). Ranges of modelled pathways that limit warming to 1.5 '''°''' C (&gt;50%) with no or limited overshoot are shown in light blue (category C1) and pathways that limit warming to 2 '''°''' C (&gt;67%) are shown in light purple (category C3). The grey range comprises all assessed pathways (C1–C8) from the 5th percentile of the lowest warming category (C1) to the 95th percentile of the highest warming category (C8). The modelled pathway ranges are compared to the emissions from two pathways illustrative of high emissions (CurPol and ModAct) and five IMPs: IMP-LD, IMP-Ren, IMP-SP, IMP-Neg and IMP-GS. Emissions are harmonised to the same 2015 base year. The vertical error bars in 2015 show the 5–95th percentile uncertainty range of the non-harmonised emissions across the pathways, and the uncertainty range, and median value, in emission estimates for 2015 and 2019. The vertical error bars in 2030 (panel a) depict the assessed range of the NDCs, as announced prior to COP26 (Figure SPM.4). 23 '''Panel e''' shows the sectoral contributions of CO 2 and non-CO 2 emissions sources and sinks at the time when net zero CO 2 emissions are reached in the IMPs. Positive and negative emissions for different IMPs are compared to the GHG emissions from the year 2019. Energy supply (neg.) includes BECCS and DACCS. DACCS features in only two of the five IMPs (IMP-REN and IMP-GS) and contributes &lt;1% and 64%, respectively, to the net negative emissions in Energy Supply (neg.). '''Panel f''' shows the contribution of different sectors and sources to the emissions reductions from a 2019 baseline for reaching net zero GHG emissions. Bars denote the median emissions reductions for all pathways that reach net zero GHG emissions. The whiskers indicate the p5–p95 range. The contributions of the service sectors (transport, buildings, industry) are split into direct (demand-side) as well as indirect (supply-side) CO 2 emissions reductions. Direct emissions represent demand-side emissions due to the fuel use in the respective demand sector. Indirect emissions represent upstream emissions due to industrial processes and energy conversion, transmission and distribution. In addition, the contributions from the LULUCF sector and reductions from non-CO 2 emissions sources (green and grey bars) are displayed. {3.3, 3.4}

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

<div id="h2-11-siblings" class="h2-siblings"></div>

'''C.4 Reducing GHG emissions across the full energy sector requires major transitions, including a substantial reduction in overall fossil fuel use, the deployment of low-emission energy sources, switching to alternative energy carriers, and energy efficiency and conservation. The continued installation of unabated fossil fuel [[#footnote-022|54]] infrastructure will ‘lock-in’ GHG emissions. ( high confidence ) Expand Links to chapters 2.7, 6.6, 6.7, 16.4'''
<div id="spmbulletcont-c4" class="spmbulletcont"></div>

'''C.4.1''' Net-zero CO 2 energy systems entail: a substantial reduction in overall fossil fuel use, minimal use of unabated fossil fuels, and use of CCS in the remaining fossil fuel system; [[#footnote-022|54]] electricity systems that emit no net CO 2 ; widespread electrification of the energy system including end uses; energy carriers such as sustainable biofuels, low-emissions hydrogen, and derivatives in applications less amenable to electrification; energy conservation and efficiency; and greater physical, institutional, and operational integration across the energy system. CDR will be needed to counterbalance residual emissions in the energy sector. The most appropriate strategies depend on national and regional circumstances, including enabling conditions and technology availability. ( ''high confidence'' ) {3.4, 6.6, 11.3, 16.4}

'''C.4.2''' Unit cost reductions in key technologies, notably wind power, solar power, and storage, have increased the economic attractiveness of low-emission energy sector transitions through 2030. Maintaining emission-intensive systems may, in some regions and sectors, be more expensive than transitioning to low emission systems. Low-emission energy sector transitions will have multiple co-benefits, including improvements in air quality and health. The long-term economic attractiveness of deploying energy system mitigation options depends, ''inter alia'' , on policy design and implementation, technology availability and performance, institutional capacity, equity, access to finance, and public and political support. ( ''high confidence'' ) (Figure SPM.3) {3.4, 6.4, 6.6, 6.7, 13.7}

'''C.4.3''' Electricity systems powered predominantly by renewables are becoming increasingly viable. Electricity systems in some countries and regions are already predominantly powered by renewables. It will be more challenging to supply the entire energy system with renewable energy. Even though operational, technological, economic, regulatory, and social challenges remain, a variety of systemic solutions to accommodate large shares of renewables in the energy system have emerged. A broad portfolio of options, such as integrating systems, coupling sectors, energy storage, smart grids, demand-side management, sustainable biofuels, electrolytic hydrogen and derivatives, and others will ultimately be needed to accommodate large shares of renewables in energy systems. ( ''high confidence'' ) {Box 6.8, 6.4, 6.6}

'''C.4.4''' Limiting global warming to 2°C or below will leave a substantial amount of fossil fuels unburned and could strand considerable fossil fuel infrastructure ( ''high confidence'' ). Depending on its availability, CCS could allow fossil fuels to be used longer, reducing stranded assets ( ''high confidence'' ). The combined global discounted value of the unburned fossil fuels and stranded fossil fuel infrastructure has been projected to be around USD1–4 trillion from 2015 to 2050 to limit global warming to approximately 2°C, and it will be higher if global warming is limited to approximately 1.5°C ( ''medium confidence'' ). In this context, coal assets are projected to be at risk of being stranded before 2030, while oil and gas assets are projected to be more at risk of being stranded towards mid-century. A low-emission energy sector transition is projected to reduce international trade in fossil fuels. ( ''high confidence'' ) {6.7, Figure 6.35}

'''C.4.5''' Global methane emissions from energy supply, primarily fugitive emissions from production and transport of fossil fuels, accounted for about 18% [13–23%] of global GHG emissions from energy supply, 32% [22–42%] of global CH 4 emissions, and 6% [4–8%] of global GHG emissions in 2019 ( ''high confidence'' ). About 50–80% of CH 4 emissions from these fossil fuels could be avoided with currently available technologies at less than USD50 tCO 2 -eq –1 ( ''medium confidence'' ). {6.3, 6.4.2, Box 6.5, 11.3, 2.2.2, Table 2.1, Figure 2.5, Annex1: Glossary}

'''C.4.6''' CCS is an option to reduce emissions from large-scale fossil-based energy and industry sources, provided geological storage is available. When CO 2 is captured directly from the atmosphere (DACCS), or from biomass (BECCS), CCS provides the storage component of these CDR methods. CO 2 capture and subsurface injection is a mature technology for gas processing and enhanced oil recovery. In contrast to the oil and gas sector, CCS is less mature in the power sector, as well as in cement and chemicals production, where it is a critical mitigation option. The technical geological CO 2 storage capacity is estimated to be on the order of 1000 GtCO 2 , which is more than the CO 2 storage requirements through 2100 to limit global warming to 1.5°C, although the regional availability of geological storage could be a limiting factor. If the geological storage site is appropriately selected and managed, it is estimated that the CO 2 can be permanently isolated from the atmosphere. Implementation of CCS currently faces technological, economic, institutional, ecological-environmental and socio-cultural barriers. Currently, global rates of CCS deployment are far below those in modelled pathways limiting global warming to 1.5°C or 2°C. Enabling conditions such as policy instruments, greater public support and technological innovation could reduce these barriers. ( ''high confidence'' ) {2.5, 6.3, 6.4, 6.7, 11.3, 11.4, Cross-Chapter Box 8 in Chapter 12, Figure TS.31; SRCCL Chapter 5}

<div id="Net-zero-CO2" class="h2-container"></div>

<div id="h2-12-siblings" class="h2-siblings"></div>

'''C.5 Net zero CO <sub>2</sub> emissions from the industrial sector are challenging but possible. Reducing industry emissions will entail coordinated action throughout value chains to promote all mitigation options, including demand management, energy and materials efficiency, circular material flows, as well as abatement technologies and transformational changes in production processes. Progressing towards net zero GHG emissions from industry will be enabled by the adoption of new production processes using low- and zero-GHG electricity, hydrogen, fuels, and carbon management. ( high confidence ) Expand Links to chapters 11.2, 11.3, 11.4, Box TS.4'''
<div id="spmbulletcont-c5" class="spmbulletcont"></div>

'''C.5.1''' '''The use of steel, cement, plastics, and other materials is increasing globally, and in most regions. There are many sustainable options for demand management, materials efficiency, and circular material flows that can contribute to reduced emissions, but how these can be applied will vary across regions and different materials. These options have a potential for being more used in industrial practice and would need more attention from industrial policy. These options, as well as new production technologies, are generally not considered in recent global scenarios nor in national''' '''economy-wide''' '''scenarios due to relative newness. As a consequence, the mitigation potential in some scenarios is underestimated compared to''' '''bottom-up''' '''industry-specific''' '''models. (''' ''high confidence'' ''') {3.4, 5.3, Figure 5.7, 11.2, Box 11.2, 11.3, 11.4, 11.5.2, 11.6}'''

'''C.5.2''' For almost all basic materials – primary metals, [[#footnote-021|55]] building materials and chemicals – many low- to zero-GHG intensity production processes are at the ''pilot'' to ''near-commercial'' and in some cases ''commercial'' stage but they are not yet established industrial practice. Introducing new sustainable production processes for basic materials could increase production costs but, given that only a small fraction of consumer costs are based on materials, such new processes are expected to translate into minimal cost increases for final consumers. Hydrogen direct reduction for primary steelmaking is ''near-commercial'' in some regions. Until new chemistries are mastered, deep reduction of cement process emissions will rely on already commercialised cementitious material substitution and the availability of CCS. Reducing emissions from the production and use of chemicals would need to rely on a life cycle approach, including increased plastics recycling, fuel and feedstock switching, and carbon sourced through biogenic sources, and, depending on availability, carbon capture and use (CCU), direct air CO 2 capture, as well as CCS. Light industry, mining and manufacturing have the potential to be decarbonised through available abatement technologies (e.g., material efficiency, circularity), electrification (e.g., electrothermal heating, heat pumps) and low- or zero-GHG emitting fuels (e.g., hydrogen, ammonia, and bio-based and other synthetic fuels). ( ''high confidence'' ) {Table 11.4, Box 11.2, 11.3, 11.4}

'''C.5.3''' Action to reduce industry sector emissions may change the location of GHG-intensive industries and the organisation of value chains. Regions with abundant low-GHG energy and feedstocks have the potential to become exporters of hydrogen-based chemicals and materials processed using low-carbon electricity and hydrogen. Such reallocation will have global distributional effects on employment and economic structure. ( ''medium confidence'' ) {Box 11.1}

'''C.5.4''' Emissions-intensive and highly traded basic materials industries are exposed to international competition, and international cooperation and coordination may be particularly important in enabling change. For sustainable industrial transitions, broad and sequential national and sub-national policy strategies reflecting regional contexts will be required. These may combine policy packages including: transparent GHG accounting and standards; demand management; materials and energy efficiency policies; R&amp;D and niche markets for commercialisation of low-emission materials and products; economic and regulatory instruments to drive market uptake; high quality recycling, low-emissions energy and other abatement infrastructure (e.g., for CCS); and socially inclusive phase-out plans of emissions-intensive facilities within the context of just transitions. The coverage of mitigation policies could be expanded nationally and sub-nationally to include all industrial emission sources, and both available and emerging mitigation options. ( ''high confidence'' ) {11.6}

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

<div id="h2-13-siblings" class="h2-siblings"></div>

'''C.6 Urban areas can create opportunities to increase resource efficiency and significantly reduce GHG emissions through the systemic transition of infrastructure and urban form through low-emission development pathways towards net-zero emissions. Ambitious mitigation efforts for established, rapidly growing and emerging cities will encompass (i) reducing or changing energy and material consumption, (ii) electrification, and (iii) enhancing carbon uptake and storage in the urban environment. Cities can achieve net-zero emissions, but only if emissions are reduced within and outside of their administrative boundaries through supply chains, which will have beneficial cascading effects across other sectors. ( very high confidence ) Expand Links to sections 8.2, 8.3, 8.4, 8.5, 8.6, 13.2'''
<div id="spmbulletcont-c6" class="spmbulletcont"></div>

'''C.6.1''' In modelled scenarios, global consumption-based urban CO 2 and CH 4 emissions [[#footnote-020|15]] are projected to rise from 29 GtCO 2 -eq in 2020 to 34 GtCO 2 -eq in 2050 with moderate mitigation efforts (intermediate GHG emissions, SSP2-4.5), and up to 40 GtCO 2 -eq in 2050 with low mitigation efforts (high GHG emissions, SSP3-7.0). With ambitious and immediate mitigation efforts, including high levels of electrification and improved energy and material efficiency, global consumption-based urban CO 2 and CH 4 emissions could be reduced to 3 GtCO 2 -eq in 2050 in the modelled scenario with very low GHG emissions (SSP1-1.9). [[#footnote-020|56]] ( ''medium confidence'' ) {8.3}

'''C.6.2''' The potential and sequencing of mitigation strategies to reduce GHG emissions will vary depending on a city’s land use, spatial form, development level, and state of urbanisation ( ''high confidence'' ). Strategies for established cities to achieve large GHG emissions savings include efficiently improving, repurposing or retrofitting the building stock, targeted infilling, and supporting non-motorised (e.g., walking, bicycling) and public transport. Rapidly growing cities can avoid future emissions by co-locating jobs and housing to achieve compact urban form, and by leapfrogging or transitioning to low-emissions technologies. New and emerging cities will have significant infrastructure development needs to achieve high quality of life, which can be met through energy efficient infrastructures and services, and people-centred urban design ( ''high confidence'' ) ''.'' For cities, three broad mitigation strategies have been found to be effective when implemented concurrently: (i) reducing or changing energy and material use towards more sustainable production and consumption; (ii) electrification in combination with switching to low-emission energy sources; and (iii) enhancing carbon uptake and storage in the urban environment, for example through bio-based building materials, permeable surfaces, green roofs, trees, green spaces, rivers, ponds and lakes. [[#footnote-019|57]] ( ''very high confidence'' ) {5.3, Figure 5.7, Supplementary Material Table 5.SM.2, 8.2, 8.4, 8.6, Figure 8.21, 9.4, 9.6, 10.2}

'''C.6.3''' The implementation of packages of multiple city-scale mitigation strategies can have cascading effects across sectors and reduce GHG emissions both within and outside a city’s administrative boundaries. The capacity of cities to develop and implement mitigation strategies varies with the broader regulatory and institutional settings, as well as enabling conditions, including access to financial and technological resources, local governance capacity, engagement of civil society, and municipal budgetary powers. ( ''very high confidence'' ) {Figure 5.7, Supplementary Material Table 5.SM.2, 8.4, 8.5, 8.6, 13.2, 13.3, 13.5, 13.7, Cross-Chapter Box 9 in Chapter 13}

'''C.6.4''' A growing number of cities are setting climate targets, including net-zero GHG targets. Given the regional and global reach of urban consumption patterns and supply chains, the full potential for reducing consumption-based urban emissions to net zero GHG can be met only when emissions beyond cities’ administrative boundaries are also addressed. The effectiveness of these strategies depends on cooperation and coordination with national and sub-national governments, industry, and civil society, and whether cities have adequate capacity to plan and implement mitigation strategies. Cities can play a positive role in reducing emissions across supply chains that extend beyond cities’ administrative boundaries, for example through building codes and the choice of construction materials. ( ''very high confidence'' ) {8.4, Box 8.4, 8.5, 9.6, 9.9, 13.5, 13.9}

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

<div id="h2-14-siblings" class="h2-siblings"></div>

'''C.7. In modelled global scenarios, existing buildings, if retrofitted, and buildings yet to be built, are projected to approach net zero GHG emissions in 2050 if policy packages, which combine ambitious sufficiency, efficiency, and renewable energy measures, are effectively implemented and barriers to decarbonisation are removed. Low ambition policies increase the risk of locking-in buildings’ carbon for decades, while well-designed and effectively implemented mitigation interventions (in both new buildings and existing ones if retrofitted), have significant potential to contribute to achieving SDGs in all regions while adapting buildings to future climate. ( high confidence ) Expand Links to chapters 9.1, 9.3, 9.4, 9.5, 9.6, 9.9'''
<div id="spmbulletcont-c7" class="spmbulletcont"></div>

'''C.7.1''' In 2019, global direct and indirect GHG emissions from buildings and emissions from cement and steel use for building construction and renovation were 12 GtCO 2 -eq. These emissions include indirect emissions from offsite generation of electricity and heat, direct emissions produced onsite and emissions from cement and steel used for building construction and renovation. In 2019, global direct and indirect emissions from non-residential buildings increased by about 55% and those from residential buildings increased by about 50% compared to 1990. The latter increase, according to the decomposition analysis, was mainly driven by the increase of the floor area per capita, population growth and the increased use of emission-intensive electricity and heat while efficiency improvements have partly decreased emissions. There are great differences in the contribution of each of these drivers to regional emissions. ( ''high confidence'' ) {9.3}

'''C.7.2''' Integrated design approaches to the construction and retrofit of buildings have led to increasing examples of zero energy or zero carbon buildings in several regions. However, the low renovation rates and low ambition of retrofitted buildings have hindered the decrease of emissions. Mitigation interventions at the design stage include buildings typology, form, and multi-functionality to allow for adjusting the size of buildings to the evolving needs of their users and repurposing unused existing buildings to avoid using GHG-intensive materials and additional land. Mitigation interventions include: at the construction phase, low-emission construction materials, highly efficient building envelope and the integration of renewable energy solutions; [[#footnote-018|58]] at the use phase, highly efficient appliances/equipment, the optimisation of the use of buildings and their supply with low-emission energy sources; and at the disposal phase, recycling and re-using construction materials. ( ''high confidence'' ) {9.4, 9.5, 9.6, 9.7}

'''C.7.3''' By 2050, bottom-up studies show that up to 61% (8.2 GtCO 2 ) of global building emissions could be mitigated. Sufficiency policies [[#footnote-017|59]] that avoid the demand for energy and materials contribute 10% to this potential, energy efficiency policies contribute 42%, and renewable energy policies 9%. The largest share of the mitigation potential of new buildings is available in developing countries while in developed countries the highest mitigation potential is within the retrofit of existing buildings. The 2020–2030 decade is critical for accelerating the learning of know-how, building the technical and institutional capacity, setting the appropriate governance structures, ensuring the flow of finance, and in developing the skills needed to fully capture the mitigation potential of buildings. ( ''high confidence'' ) {9.3, 9.4, 9.5, 9.6, 9.7, 9.9}

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

<div id="h2-15-siblings" class="h2-siblings"></div>

'''C.8 Demand-side options and low-GHG emissions technologies can reduce transport sector emissions in developed countries and limit emissions growth in developing countries ( high confidence ). Demand-focused interventions can reduce demand for all transport services and support the shift to more energy efficient transport modes ( medium confidence ). Electric vehicles powered by low-emissions electricity offer the largest decarbonisation potential for land-based transport, on a life cycle basis ( high confidence ). Sustainable biofuels can offer additional mitigation benefits in land-based transport in the short and medium term ( medium confidence ). Sustainable biofuels, low-emissions hydrogen, and derivatives (including synthetic fuels) can support mitigation of CO 2 emissions from shipping, aviation, and heavy-duty land transport but require production process improvements and cost reductions ( medium confidence ). Many mitigation strategies in the transport sector would have various co-benefits, including air quality improvements, health benefits, equitable access to transportation services, reduced congestion, and reduced material demand ( high confidence ). Expand Links to chapters 10.2, 10.4, 10.5, 10.6, 10.7'''
<div id="spmbulletcont-c8" class="spmbulletcont"></div>

'''C.8.1''' In scenarios that limit warming to 1.5°C (&gt;50%) with no or limited overshoot, global transport-related CO 2 emissions fall by 59% (42–68% interquartile range) by 2050 relative to modelled 2020 emissions, but with regionally differentiated trends ( ''high confidence'' ). In global modelled scenarios that limit warming to 2°C (&gt;67%), transport-related CO 2 emissions are projected to decrease by 29% [14–44% interquartile range] by 2050 compared to modelled 2020 emissions. In both categories of scenarios, the transport sector likely does not reach zero CO 2 emissions by 2100 so negative emissions are likely needed to counterbalance residual CO 2 emissions from the sector ( ''high confidence'' ). {3.4, 10.7}

'''C.8.2''' Changes in urban form (e.g., density, land-use mix, connectivity, and accessibility) in combination with programmes that encourage changes in consumer behaviour (e.g., transport pricing) could reduce transport-related greenhouse gas emissions in developed countries and slow growth in emissions in developing countries ( ''high confidence'' ). Investments in public inter- and intra-city transport and active transport infrastructure (e.g., bicycle and pedestrian pathways) can further support the shift to less GHG-intensive transport modes ( ''high confidence'' ). Combinations of systemic changes, including teleworking, digitalisation, dematerialisation, supply chain management, and smart and shared mobility may reduce demand for passenger and freight services across land, air, and sea ( ''high confidence'' ). Some of these changes could lead to induced demand for transport and energy services, which may decrease their GHG emissions reduction potential ( ''medium confidence'' ). {5.3, 10.2, 10.8}

'''C.8.3''' Electric vehicles powered by low-GHG emissions electricity have large potential to reduce land-based transport GHG emissions, on a life cycle basis ( ''high confidence'' ). Costs of electrified vehicles, including automobiles, two- and three-wheelers, and buses, are decreasing and their adoption is accelerating, but they require continued investments in supporting infrastructure to increase scale of deployment ( ''high confidence'' ). Advances in battery technologies could facilitate the electrification of heavy-duty trucks and complement conventional electric rail systems ( ''medium confidence'' ). There are growing concerns about critical minerals needed for batteries. Material and supply diversification strategies, energy and material efficiency improvements, and circular material flows can reduce the environmental footprint and material supply risks for battery production ( ''medium confidence'' ). Sourced sustainably and with low-GHG emissions feedstocks, bio-based fuels, blended or unblended with fossil fuels, can provide mitigation benefits, particularly in the short and medium term ( ''medium confidence'' ). Low-GHG emissions hydrogen and hydrogen derivatives, including synthetic fuels, can offer mitigation potential in some contexts and land-based transport segments ( ''medium confidence'' ). {3.4, 6.3, 10.3, 10.4, 10.7, 10.8, Box 10.6}

'''C.8.4''' While efficiency improvements (e.g., optimised aircraft and vessel designs, mass reduction, and propulsion system improvements) can provide some mitigation potential, additional CO 2 emissions mitigation technologies for aviation and shipping will be required ( ''high confidence'' ). For aviation, such technologies include high energy density biofuels ( ''high confidence'' ), and low-emission hydrogen and synthetic fuels ( ''medium confidence'' ). Alternative fuels for shipping include low-emission hydrogen, ammonia, biofuels, and other synthetic fuels ( ''medium confidence'' ) ''.'' Electrification could play a niche role for aviation and shipping for short trips ( ''medium confidence'' ) and can reduce emissions from port and airport operations ( ''high confidence'' ). Improvements to national and international governance structures would further enable the decarbonisation of shipping and aviation ( ''medium confidence'' ). Such improvements could include, for example, the implementation of stricter efficiency and carbon intensity standards for the sectors ( ''medium confidence'' ). {10.3. 10.5, 10.6, 10.7, 10.8, Box 10.5}

'''C.8.5''' The substantial potential for GHG emissions reductions, both direct and indirect, in the transport sector largely depends on power sector decarbonisation, and low-emissions feedstocks and production chains ( ''high confidence'' ). Integrated transport and energy infrastructure planning and operations can enable sectoral synergies and reduce the environmental, social, and economic impacts of decarbonising the transport and energy sectors ( ''high confidence'' ). Technology transfer and financing can support developing countries leapfrogging or transitioning to low-emissions transport systems thereby providing multiple co-benefits ( ''high confidence'' ). {10.2, 10.3, 10.4, 10.5, 10.6, 10.7, 10.8}

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

<div id="h2-15-siblings" class="h2-siblings"></div>

'''C.9 AFOLU mitigation options, when sustainably implemented, can deliver large-scale GHG emission reductions and enhanced removals, but cannot fully compensate for delayed action in other sectors. In addition, sustainably sourced agricultural and forest products can be used instead of more GHG-intensive products in other sectors. Barriers to implementation and trade-offs may result from the impacts of climate change, competing demands on land, conflicts with food security and livelihoods, the complexity of land ownership and management systems, and cultural aspects. There are many country-specific opportunities to provide co-benefits (such as biodiversity conservation, ecosystem services, and livelihoods) and avoid risks (for example, through adaptation to climate change). ( high confidence ) Expand Links to chapters 7.4, 7.6, 7.7, 12.5, 12.6'''
<div id="spmbulletcont-c9" class="spmbulletcont"></div>

'''C.9.1''' The projected economic mitigation potential of AFOLU options between 2020 and 2050, at costs below USD100 tCO 2 -eq –1 , is 8–14 GtCO 2 -eq yr –1 [[#footnote-016|60]] ( ''high confidence'' ). 30–50% of this potential is available at less than USD20 tCO 2 -eq and could be upscaled in the near term across most regions ( ''high confidence'' ). The largest share of this economic potential [4.2–7.4 GtCO 2 -eq yr –1 ] comes from the conservation, improved management, and restoration of forests and other ecosystems (coastal wetlands, peatlands, savannas and grasslands), with reduced deforestation in tropical regions having the highest total mitigation. Improved and sustainable crop and livestock management, and carbon sequestration in agriculture (the latter including soil carbon management in croplands and grasslands, agroforestry and biochar), can contribute 1.8–4.1 GtCO 2 -eq yr –1 reduction. Demand-side and material substitution measures, such as shifting to balanced, sustainable healthy diets, [[#footnote-015|61]] reducing food loss and waste, and using bio-materials, can contribute 2.1 [1.1–3.6] GtCO 2 -eq yr –1 reduction. In addition, demand-side measures together with the sustainable intensification of agriculture can reduce ecosystem conversion and CH 4 and N 2 O emissions, and free up land for reforestation and restoration, and the production of renewable energy. The improved and expanded use of wood products sourced from sustainably managed forests also has potential through the allocation of harvested wood to longer-lived products, increasing recycling or material substitution. AFOLU mitigation measures cannot compensate for delayed emission reductions in other sectors. Persistent and region-specific barriers continue to hamper the economic and political feasibility of deploying AFOLU mitigation options. Assisting countries to overcome barriers will help to achieve significant mitigation ( ''medium'' ''confidence'' ). (Figure SPM.6) {7.1, 7.4, 7.5, 7.6}

'''C.9.2''' AFOLU carbon sequestration and GHG emission reduction options have both co-benefits and risks in terms of biodiversity and ecosystem conservation, food and water security, wood supply, livelihoods and land tenure and land-use rights of Indigenous Peoples, local communities and small land owners. Many options have co-benefits but those that compete for land and land-based resources can pose risks. The scale of benefit or risk largely depends on the type of activity undertaken, deployment strategy (e.g., scale, method), and context (e.g., soil, biome, climate, food system, land ownership) that vary geographically and over time. Risks can be avoided when AFOLU mitigation is pursued in response to the needs and perspectives of multiple stakeholders to achieve outcomes that maximize co-benefits while limiting trade-offs. ( ''high confidence'' ) {7.4, 7.6, 12.3}

'''C.9.3''' Realising the AFOLU mitigation potential entails overcoming institutional, economic and policy constraints and managing potential trade-offs ( ''high confidence'' ). Land-use decisions are often spread across a wide range of land owners; demand-side measures depend on billions of consumers in diverse contexts. Barriers to the implementation of AFOLU mitigation include insufficient institutional and financial support, uncertainty over long-term additionality and trade-offs, weak governance, insecure land ownership, low incomes and the lack of access to alternative sources of income, and the risk of reversal. Limited access to technology, data, and know-how is a barrier to implementation. Research and development are key for all measures. For example, measures for the mitigation of agricultural CH 4 and N 2 O emissions with emerging technologies show promising results. However, the mitigation of agricultural CH 4 and N 2 O emissions is still constrained by cost, the diversity and complexity of agricultural systems, and by increasing demands to raise agricultural yields, and increasing demand for livestock products. ( ''high confidence'' ) {7.4, 7.6}

'''C.9.4''' Net costs of delivering 5–6 GtCO 2 yr –1 of forest-related carbon sequestration and emission reduction as assessed with sectoral models are estimated to reach to about USD400 billion yr –1 by 2050. The costs of other AFOLU mitigation measures are highly context specific. Financing needs in AFOLU, and in particular in forestry, include both the direct effects of any changes in activities as well as the opportunity costs associated with land-use change. Enhanced monitoring, reporting and verification capacity, and the rule of law, are crucial for land-based mitigation in combination with policies also recognising interactions with wider ecosystem services, could enable engagement by a wider array of actors, including private businesses, NGOs, and Indigenous Peoples and local communities. ( ''medium confidence'' ) {7.6, 7.7}

'''C.9.5''' Context specific policies and measures have been effective in demonstrating the delivery of AFOLU carbon sequestration and GHG emission reduction options but the above-mentioned constraints hinder large scale implementation ( ''medium confidence'' ). Deploying land-based mitigation can draw on lessons from experience with regulations, policies, economic incentives, payments (e.g., for biofuels, control of nutrient pollution, water regulations, conservation and forest carbon, ecosystem services, and rural livelihoods), and from diverse forms of knowledge such as Indigenous knowledge, local knowledge and scientific knowledge. Indigenous Peoples, private forest owners, local farmers and communities manage a significant share of global forests and agricultural land and play a central role in land-based mitigation options. Scaling successful policies and measures relies on governance that emphasises integrated land-use planning and management framed by SDGs, with support for implementation. ( ''high confidence'' ) {7.4, Box 7.2, 7.6}

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

<div id="h2-16-siblings" class="h2-siblings"></div>

'''C.10 Demand-side mitigation encompasses changes in infrastructure use, end-use technology adoption, and socio-cultural and behavioural change. Demand-side measures and new ways of end-use service provision can reduce global GHG emissions in end-use sectors by 40–70% by 2050 compared to baseline scenarios, while some regions and socioeconomic groups require additional energy and resources. Demand-side mitigation response options are consistent with improving basic well-being for all. ( high confidence ) Expand [[#figure-spm-6|Figure SPM.6]] Links to sections 5.3, 5.4, Figure 5.6, Figure 5.14, 8.2, 9.4, 10.2, 11.3, 11.4, 12.4, Figure TS.22'''
<div id="spmbulletcont-c10" class="spmbulletcont"></div>

'''C.10.1''' Infrastructure design and access, and technology access and adoption, including information and communication technologies, influence patterns of demand and ways of providing services, such as mobility, shelter, water, sanitation, and nutrition. Illustrative global low-demand scenarios, accounting for regional differences, indicate that more efficient end-use energy conversion can improve services while reducing the need for upstream energy by 45% by 2050 compared to 2020. Demand-side mitigation potential differs between and within regions, and some regions and populations require additional energy, capacity, and resources for human well-being. The lowest population quartile by income worldwide faces shortfalls in shelter, mobility, and nutrition. ( ''high confidence'' ) {5.2, 5.3, 5.4, 5.5, Figure 5.6, Figure 5.10, Table 5.2, Figure TS.20, Figure TS.22}

'''C.10.2''' By 2050, comprehensive demand-side strategies could reduce direct and indirect CO 2 and non-CO 2 GHG emissions in three end-use sectors (buildings, land transport, and food) globally by 40%–70% compared to the 2050 emissions projection of two scenarios consistent with policies announced by national governments until 2020. With policy support, socio-cultural options and behavioural change can reduce global GHG emissions of end-use sectors by at least 5% rapidly, with most of the potential in developed countries, and more until 2050, if combined with improved infrastructure design and access. Individuals with high socio-economic status contribute disproportionately to emissions and have the highest potential for emissions reductions, e.g., as citizens, investors, consumers, role models, and professionals. ( ''high confidence'' ) (Figure SPM.6) {5.2, 5.3, 5.4, 5.5, 5.6, Supplementary Material Table 5.SM.2, 8.4, 9.9, 13.2, 13.5, 13.8, Figure TS.20}

<div id="figure-spm-6" class="Basic-Text-Frame"></div>

[[File:c18e41bf0bdc5166fe5c2cf66a430ad3 IPCC_AR6_WGIII_FigureSPM6.png]]

'''Figure SPM.6 | Indicative potential of''' '''demand-side''' '''mitigation options by 2050.''' Figure SPM.6 covers the indicative potential of demand-side options for the year 2050. Figure SPM.7 covers cost and potentials for the year 2030. Demand-side mitigation response options are categorised into three broad domains: ‘socio-cultural factors’, associated with individual choices, behaviour, lifestyle changes, social norms, and culture; ‘infrastructure use’, related to the design and use of supporting hard and soft infrastructure that enables changes in individual choices and behaviour; and ‘end-use technology adoption’, referring to the uptake of technologies by end-users. Demand-side mitigation is a central element of the IMP-LD and IMP-SP scenarios (Figure SPM.5). '''Panel a''' (Nutrition) demand-side potentials in 2050 assessment is based on bottom-up studies and is estimated following the 2050 baseline for the food sector presented in peer-reviewed literature (more information in Supplementary Material 5.II, and [https://www.ipcc.ch/chapters/chapter-7#7.4.5 Section 7.4.5] ). '''Panel b''' (Manufactured products, mobility, shelter) the assessment of potentials for total emissions in 2050 are estimated based on approximately 500 bottom-up studies representing all global regions (detailed list is in Supplementary Material Table 5.SM.2). Baseline is provided by the sectoral mean GHG emissions in 2050 of the two scenarios consistent with policies announced by national governments until 2020. The heights of the coloured columns represent the potentials represented by the median value. These are based on a range of values available in the case studies from literature shown in Supplementary Material 5.SM.II. The range is shown by the dots connected by dotted lines representing the highest and the lowest potentials reported in the literature. '''Panel a''' shows the demand-side potential of socio-cultural factors and infrastructure use. The median value of direct emissions (mostly non-CO 2 ) reduction through socio-cultural factors is 1.9 GtCO 2 -eq without considering land-use change through reforestation of freed up land. If changes in land-use pattern enabled by this change in food demand are considered, the indicative potential could reach 7 GtCO 2 -eq. Panel b illustrates mitigation potential in industry, land transport and buildings end-use sectors through demand-side options. Key options are presented in the summary table below the figure and the details are in Supplementary Material Table 5.SM.2. '''Panel c''' visualises how sectoral demand-side mitigation options (presented in panel b) change demand on the electricity distribution system. Electricity accounts for an increasing proportion of final energy demand in 2050 (additional electricity bar) in line with multiple bottom-up studies (detailed list is in Supplementary Material Table 5.SM.3), and [https://www.ipcc.ch/chapters/chapter-6 Chapter 6] ( [https://www.ipcc.ch/chapters/chapter-6#6.6 Section 6.6] ). These studies are used to compute the impact of end-use electrification which increases overall electricity demand. Some of the projected increase in electricity demand can be avoided through demand-side mitigation options in the domains of socio-cultural factors and infrastructure use in end-use electricity use in buildings, industry, and land transport found in literature based on bottom-up assessments. Dark grey columns show the emissions that cannot be avoided through demand-side mitigation options. {5.3, Figure 5.7, Supplementary Material 5.SM.II}

'''C.10.3''' A range of 5–30% of global annual GHG emissions from end-use sectors are avoidable by 2050, compared to 2050 emissions projection of two scenarios consistent with policies announced by national governments until 2020, through changes in the built environment, new and repurposed infrastructures and service provision through compact cities, co-location of jobs and housing, more efficient use of floor space and energy in buildings, and reallocation of street space for active mobility ( ''high confidence'' ). (Figure SPM.6) {5.3.1, 5.3.3, 5.4, Figure 5.7, Figure 5.13, Table 5.1, Table 5.5, Supplementary Material Table 5.SM.2, 8.4, 9.5, 10.2, 11.3, 11.4, Table 11.6, Box TS.12}

'''C.10.4''' Choice architecture [[#footnote-014|62]] can help end-users adopt, as relevant to consumers, culture and country contexts, low-GHG-intensive options such as balanced, sustainable healthy diets 61 acknowledging nutritional needs; food waste reduction; adaptive heating and cooling choices for thermal comfort; building-integrated renewable energy; and electric light-duty vehicles, and shifts to walking, cycling, shared pooled and public transit; and sustainable consumption by intensive use of longer-lived repairable products ( ''high confidence'' ). Addressing inequality and many forms of status consumption [[#footnote-013|63]] and focusing on wellbeing supports climate change mitigation efforts ( ''high confidence'' ). (Figure SPM.6) {2.4.3, 2.6.2, 4.2.5, 5.1, 5.2, 5.3, 5.4, Figure 5.4, Figure 5.10, Table 5.2, Supplementary Material Table 5.SM.2, 7.4.5, 8.2, 8.4, 9.4, 10.2, 12.4, Figure TS.20}

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

<div id="h2-c17-siblings" class="h2-siblings"></div>

'''C.11 The deployment of carbon dioxide removal (CDR) to counterbalance hard-to-abate residual emissions is unavoidable if net zero CO2 or GHG emissions are to be achieved. The scale and timing of deployment will depend on the trajectories of gross emission reductions in different sectors. Upscaling the deployment of CDR depends on developing effective approaches to address feasibility and sustainability constraints especially at large scales. ( high confidence ) Expand Links to chapters 3.4, 7.4, 12.3, Cross-Chapter Box 8 in Chapter 12'''
<div id="spmbulletcont-c11" class="spmbulletcont"></div>

'''C.11.1''' CDR refers to anthropogenic activities that remove CO 2 from the atmosphere and store it durably in geological, terrestrial, or ocean reservoirs, or in products. CDR methods vary in terms of their maturity, removal process, time scale of carbon storage, storage medium, mitigation potential, cost, co-benefits, impacts and risks, and governance requirements ( ''high confidence'' ). Specifically, maturity ranges from lower maturity (e.g., ocean alkalinisation) to higher maturity (e.g., reforestation); removal and storage potential ranges from lower potential (&lt;1 GtCO 2 yr –1 , e.g., blue carbon management) to higher potential (&gt;3 GtCO 2 yr –1 , e.g., agroforestry); costs range from lower cost (e.g., USD-45–100 per tCO 2 for soil carbon sequestration) to higher cost (e.g., USD100–300 per tCO 2 for DACCS) ( ''medium confidence'' ). Estimated storage time scales vary from decades to centuries for methods that store carbon in vegetation and through soil carbon management, to 10,000 years or more for methods that store carbon in geological formations ( ''high confidence'' ). The processes by which CO 2 is removed from the atmosphere are categorised as biological, geochemical or chemical. Afforestation, reforestation, improved forest management, agroforestry and soil carbon sequestration are currently the only widely practiced CDR methods ( ''high confidence'' ). {7.4, 7.6, 12.3, Table 12.6, Cross-Chapter Box 8 in Chapter 12, Table TS.7; AR6 WGI 5.6}

'''C.11.2''' The impacts, risks and co-benefits of CDR deployment for ecosystems, biodiversity and people will be highly variable depending on the method, site-specific context, implementation and scale ( ''high confidence'' ). Reforestation, improved forest management, soil carbon sequestration, peatland restoration and blue carbon management are examples of methods that can enhance biodiversity and ecosystem functions, employment and local livelihoods, depending on context ( ''high confidence'' ). In contrast, afforestation or production of biomass crops for BECCS or biochar, when poorly implemented, can have adverse socio-economic and environmental impacts, including on biodiversity, food and water security, local livelihoods and on the rights of Indigenous Peoples, especially if implemented at large scales and where land tenure is insecure ( ''high confidence'' ). Ocean fertilisation, if implemented, could lead to nutrient redistribution, restructuring of ecosystems, enhanced oxygen consumption and acidification in deeper waters ( ''medium confidence'' ). {7.4, 7.6, 12.3, 12.5}

'''C.11.3''' The removal and storage of CO 2 through vegetation and soil management can be reversed by human or natural disturbances; it is also prone to climate change impacts. In comparison, CO 2 stored in geological and ocean reservoirs (via BECCS, DACCS, ocean alkalinisation) and as carbon in biochar is less prone to reversal. ( ''high confidence'' ) {6.4, 7.4, 12.3}

'''C.11.4''' In addition to deep, rapid, and sustained emission reductions CDR can fulfil three different complementary roles globally or at country level: lowering net CO 2 or net GHG emissions in the near term; counterbalancing ‘hard-to-abate’ residual emissions (e.g., emissions from agriculture, aviation, shipping, industrial processes) in order to help reach net zero CO 2 or net zero GHG emissions in the mid-term; and achieving net negative CO 2 or GHG emissions in the long term if deployed at levels exceeding annual residual emissions. ( ''high confidence'' ) {3.3, 7.4, 11.3, 12.3, Cross-Chapter Box 8 in Chapter 12}

'''C.11.5''' Rapid emission reductions in all sectors interact with future scale of deployment of CDR methods, and their associated risks, impacts and co-benefits. Upscaling the deployment of CDR methods depends on developing effective approaches to address sustainability and feasibility constraints, potential impacts, co-benefits and risks. Enablers of CDR include accelerated research, development and demonstration, improved tools for risk assessment and management, targeted incentives and development of agreed methods for measurement, reporting and verification of carbon flows. ( ''high confidence'' ) {3.4, 7.6, 12.3}

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

<div id="h2-18-siblings" class="h2-siblings"></div>

'''C.12 Mitigation options costing USD100 tCO 2 -eq –1 or less could reduce global GHG emissions by at least half the 2019 level by 2030 ( high confidence ). Global GDP continues to grow in modelled pathways [[#footnote-012|64]] but, without accounting for the economic benefits of mitigation action from avoided damages from climate change nor from reduced adaptation costs, it is a few percent lower in 2050 compared to pathways without mitigation beyond current policies. The global economic benefit of limiting warming to 2°C is reported to exceed the cost of mitigation in most of the assessed literature ( medium confidence ). Expand [[#figure-spm-7|Figure SPM.7]] Links to chapters 3.6, 3.8, Cross-Working Group Box 1 in Chapter 3, 12.2, Box TS.7'''
<div id="spmbulletcont-c12" class="spmbulletcont"></div>

'''C.12.1''' Based on a detailed sectoral assessment of mitigation options, it is estimated that mitigation options costing USD100 tCO 2 -eq –1 or less could reduce global GHG emissions by at least half of the 2019 level by 2030 (options costing less than USD20 tCO 2 -eq –1 are estimated to make up more than half of this potential). [[#footnote-011|65]] For a smaller part of the potential, deployment leads to net cost savings. Large contributions with costs less than USD20 tCO 2 -eq –1 come from solar and wind energy, energy efficiency improvements, reduced conversion of natural ecosystems, and CH 4 emissions reductions (coal mining, oil and gas, waste). The mitigation potentials and mitigation costs of individual technologies in a specific context or region may differ greatly from the provided estimates. The assessment of the underlying literature suggests that the relative contribution of the various options could change beyond 2030. ( ''medium confidence'' ) (Figure SPM.7) {12.2}

<div id="figure-spm-7" class="Basic-Text-Frame"></div>

[[File:8e13aca272b049bd560f6920e3fd0c61 IPCC_AR6_WGIII_FigureSPM7.png]]

'''Figure SPM.7: Overview of mitigation options and their estimated ranges of costs and potentials in 2030.''' Costs shown are net lifetime costs of avoided greenhouse gas emissions. Costs are calculated relative to a reference technology. The assessments per sector were carried out using a common methodology, including definition of potentials, target year, reference scenarios, and cost definitions. The mitigation potential (shown in the horizontal axis) is the quantity of net GHG emission reductions that can be achieved by a given mitigation option relative to a specified emission baseline. Net GHG emission reductions are the sum of reduced emissions and/or enhanced sinks. The baseline used consists of current policy (around 2019) reference scenarios from the AR6 scenarios database (25/75 percentile values). The assessment relies on approximately 175 underlying sources, that together give a fair representation of emission reduction potentials across all regions. The mitigation potentials are assessed independently for each option and are not necessarily additive. {12.2.1, 12.2.2} The length of the solid bars represents the mitigation potential of an option. The error bars display the full ranges of the estimates for the total mitigation potentials. Sources of uncertainty for the cost estimates include assumptions on the rate of technological advancement, regional differences, and economies of scale, among others. Those uncertainties are not displayed in the figure. Potentials are broken down into cost categories, indicated by different colours (see legend). Only discounted lifetime monetary costs are considered. Where a gradual colour transition is shown, the breakdown of the potential into cost categories is not well known or depends heavily on factors such as geographical location, resource availability, and regional circumstances, and the colours indicate the range of estimates. Costs were taken directly from the underlying studies (mostly in the period 2015–2020) or recent datasets. No correction for inflation was applied, given the wide cost ranges used. The cost of the reference technologies were also taken from the underlying studies and recent datasets. Cost reductions through technological learning are taken into account. [[#footnote-007|69]]

– When interpreting this figure, the following should be taken into account:

– The mitigation potential is uncertain, as it will depend on the reference technology (and emissions) being displaced, the rate of new technology adoption, and several other factors.

– Cost and mitigation potential estimates were extrapolated from available sectoral studies. Actual costs and potentials would vary by place, context and time.

– Beyond 2030, the relative importance of the assessed mitigation options is expected to change, in particular while pursuing long-term mitigation goals, recognising also that the emphasis for particular options will vary across regions (for specific mitigation options see SPM Sections C4.1, C5.2, C7.3, C8.3 and C9.1).

– Different options have different feasibilities beyond the cost aspects, which are not reflected in the figure (compare with SPM Section E.1).

– The potentials in the cost range USD100–200 tCO 2 -eq –1 may be underestimated for some options.

– Costs for accommodating the integration of variable renewable energy sources in electricity systems are expected to be modest until 2030, and are not included because of complexities in attributing such costs to individual technology options.

– Cost range categories are ordered from low to high. This order does not imply any sequence of implementation.

– Externalities are not taken into account. {12.2, Table 12.3, 6.4, Table 7.3, Supplementary Material Table 9.SM.2, Supplementary Material Table 9.SM.3, 10.6, 11.4, Figure 11.13, Supplementary Material 12.SM.1.2.3}

'''C.12.2''' The aggregate effects of climate change mitigation on global GDP are small compared to global projected GDP growth in assessed modelled global scenarios that quantify the macroeconomic implications of climate change mitigation, but that do not account for damages from climate change nor adaptation costs ( ''high confidence'' ). For example, compared to pathways that assume the continuation of policies implemented by the end of 2020, assessed global GDP reached in 2050 is reduced by 1.3–2.7% in modelled pathways assuming coordinated global action starting between now and 2025 at the latest to limit warming to 2°C (&gt;67%). The corresponding average reduction in annual global GDP growth over 2020–2050 is 0.04–0.09 percentage points. In assessed modelled pathways, regardless of the level of mitigation action, global GDP is projected to at least double (increase by at least 100%) over 2020–2050. For modelled global pathways in other temperature categories, the reductions in global GDP in 2050 compared to pathways that assume the continuation of policies implemented by the end of 2020 are as follows: 2.6–4.2% (C1), 1.6–2.8% (C2), 0.8–2.1% (C4), 0.5–1.2% (C5). The corresponding reductions in average annual global GDP growth over 2020–2050, in percentage points, are as follows: 0.09–0.14 (C1), 0.05–0.09 (C2), 0.03–0.07 (C4), 0.02–0.04 (C5). [[#footnote-010|66]] There are large variations in the modelled effects of mitigation on GDP across regions, depending notably on economic structure, regional emissions reductions, policy design and level of international cooperation [[#footnote-009|67]] ( ''high confidence'' ). Country-level studies also show large variations in the effect of mitigation on GDP depending notably on the level of mitigation and on the way it is achieved ( ''high confidence'' ). Macroeconomic implications of mitigation co-benefits and trade-offs are not quantified comprehensively across the above scenarios and depend strongly on mitigation strategies ( ''high confidence'' ). {3.6, 4.2, Box TS.7, Annex III.I.2, Annex III.I.9, Annex III.I.10 and Annex III.II.3}

'''C.12.3''' Estimates of aggregate economic benefits from avoiding damages from climate change, and from reduced adaptation costs, increase with the stringency of mitigation ( ''high confidence'' ). Models that incorporate the economic damages from climate change find that the global cost of limiting warming to 2°C over the 21st century is lower than the global economic benefits of reducing warming, unless: (i) climate damages are towards the low end of the range; or, (ii) future damages are discounted at high rates ( ''medium confidence'' ). [[#footnote-008|68]] Modelled pathways with a peak in global emissions between now and 2025 at the latest, compared to modelled pathways with a later peak in global emissions, entail more rapid near-term transitions and higher up-front investments, but bring long-term gains for the economy, as well as earlier benefits of avoided climate change impacts ( ''high confidence'' ). The precise magnitude of these gains and benefits is difficult to quantify. {1.7, 3.6, Cross-Working Group Box 1 in Chapter 3, Box TS.7; AR6 WGII SPM B.4}

<div id="D.   Linkages between Mitigation, Adaptation, " class="h1-container openh2"></div>

<span id="d.-linkages-between-mitigation-adaptation-and-sustainable-development"></span>