IPCC:AR6/WGI/Chapter-5 - Revision history

Laura: /* FAQ 5.1 | Is the Natural Removal of Carbon From the Atmosp here Weakening? */

2026-06-22T13:30:00Z

FAQ 5.1 | Is the Natural Removal of Carbon From the Atmosp here Weakening?

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	<span id="faq-5.1-is-the-natural-removal-of-carbon-from-the-atmosp-here-weakening"></span>		<span id="faq-5.1-is-the-natural-removal-of-carbon-from-the-atmosp-here-weakening"></span>
	=== FAQ 5.1 \| Is the Natural Removal of Carbon From the ~~Atmosp here~~ Weakening? ===		=== FAQ 5.1 \| Is the Natural Removal of Carbon From the Atmosphere Weakening? ===

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	<span id="faq-5.2-can-thawing-permafrost-substantially-increase-global-warming"></span>		<span id="faq-5.2-can-thawing-permafrost-substantially-increase-global-warming"></span>

	=== FAQ 5.2 \| Can Thawing Permafrost Substantially Increase Global Warming? ===		=== FAQ 5.2 \| Can Thawing Permafrost Substantially Increase Global Warming? ===

Laura: /* 5.6.2.1.4 Symmetry of carbon cycle response to positive and negative CO 2 emissions */

2026-06-22T13:29:19Z

5.6.2.1.4 Symmetry of carbon cycle response to positive and negative CO 2 emissions

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	~~'''~~Box 5.3 \| Carbon Cycle Response to CO~~'''~~ <sub>2</sub> ~~'''~~Removal from~~''' '''~~the Atmosphere~~'''~~		== Box 5.3 \| Carbon Cycle Response to CO <sub>2</sub> Removal from the Atmosphere ==

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	[[File:b0f01dff95c42721b9c68bcb0a161c4c IPCC_AR6_WGI_Box_5_3_Figure_1.png]]		[[File:b0f01dff95c42721b9c68bcb0a161c4c IPCC_AR6_WGI_Box_5_3_Figure_1.png]]

	'''Box 5.3, Figure 1 \|'''		'''Box 5.3, Figure 1 \|''' '''Schematic representation of carbon fluxes between atmosphere, land, ocean and geological reservoirs.''' Different system conditions are shown: '''(a)''' an unperturbed Earth system; and changes in carbon fluxes for '''(b)''' an Earth system perturbed by fossil fuel carbon dioxide (CO <sub>2</sub>) emissions; '''(c)''' an Earth system in which fossil fuel CO <sub>2</sub> emissions are partially offset by carbon dioxide removal (CDR); '''(d)''' an Earth system in which CDR exceeds CO <sub>2</sub> emissions from fossil fuels (‘net negative’ CO <sub>2</sub> emissions). Carbon fluxes depicted in (a) (solid and dashed black lines) also occur in (b–d). The question mark in the land-to-ocean carbon flux perturbation in (c) and (d) indicates that the effect of CDR on this flux is unknown. Note that box sizes do not scale with the size of carbon reservoirs. Adapted from [[#Keller--2018a\|Keller et al. (2018a)]] . Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

	'''Schematic representation of carbon fluxes between atmosphere, land, ocean and geological reservoirs.''' Different system conditions are shown: '''(a)''' an unperturbed Earth system; and changes in carbon fluxes for '''(b)''' an Earth system perturbed by fossil fuel carbon dioxide (CO <sub>2</sub>) emissions; '''(c)''' an Earth system in which fossil fuel CO <sub>2</sub> emissions are partially offset by carbon dioxide removal (CDR); '''(d)''' an Earth system in which CDR exceeds CO <sub>2</sub> emissions from fossil fuels (‘net negative’ CO <sub>2</sub> emissions). Carbon fluxes depicted in (a) (solid and dashed black lines) also occur in (b–d). The question mark in the land-to-ocean carbon flux perturbation in (c) and (d) indicates that the effect of CDR on this flux is unknown. Note that box sizes do not scale with the size of carbon reservoirs. Adapted from [[#Keller--2018a\|Keller et al. (2018a)]] . Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

	When CDR removes more CO <sub>2</sub> emissions than human activities emit (net negative CO <sub>2</sub> emissions), and atmospheric CO <sub>2</sub> declines, the land and ocean sinks initially continue to take up CO <sub>2</sub> from the atmosphere. This is because carbon sinks, particularly the ocean, exhibit inertia and continue to respond to the prior trajectory of rising atmospheric CO <sub>2</sub> concentration. After some time, which is determined by the magnitude of the removal and the rate and amount of CO <sub>2</sub> emissions prior to the CDR application, land and ocean carbon reservoirs begin to release CO <sub>2</sub> into the atmosphere, making CDR less effective (Box 5.3, Figure 1d).		When CDR removes more CO <sub>2</sub> emissions than human activities emit (net negative CO <sub>2</sub> emissions), and atmospheric CO <sub>2</sub> declines, the land and ocean sinks initially continue to take up CO <sub>2</sub> from the atmosphere. This is because carbon sinks, particularly the ocean, exhibit inertia and continue to respond to the prior trajectory of rising atmospheric CO <sub>2</sub> concentration. After some time, which is determined by the magnitude of the removal and the rate and amount of CO <sub>2</sub> emissions prior to the CDR application, land and ocean carbon reservoirs begin to release CO <sub>2</sub> into the atmosphere, making CDR less effective (Box 5.3, Figure 1d).
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	<div id="5.6.2.2" class="h3-container"></div>		<div id="5.6.2.2" class="h3-container"></div>

	<span id="effects-of-specific-cdr-methods-on-biogeochemical-cycles-and-climate"></span>		<span id="effects-of-specific-cdr-methods-on-biogeochemical-cycles-and-climate"></span>

	==== 5.6.2.2 Effects of Specific CDR Methods on Biogeochemical Cycles and Climate ====		==== 5.6.2.2 Effects of Specific CDR Methods on Biogeochemical Cycles and Climate ====

Laura: /* 5.5.2.3 Remaining Carbon Budget */

2026-06-22T13:28:15Z

5.5.2.3 Remaining Carbon Budget

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	~~'''~~Box 5.2 \| Implications of Methodological Advancements in Estimating the Remaining Carbon Budget since the IPCC’s Fifth ~~Assessme''' '''nt~~ Report (AR5)~~'''~~		== Box 5.2 \| Implications of Methodological Advancements in Estimating the Remaining Carbon Budget since the IPCC’s Fifth Assessment Report (AR5) ==

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	All methodological improvements and new evidence combined result in median and 67th percentile remaining carbon budget estimates for limiting warming to 1.5°C being about 300–350 GtCO <sub>2</sub> larger compared to an assessment that would use the evidence and methods available at the time of the AR5. For limiting warming to 2°C, the difference is about 400–500 GtCO <sub>2</sub> . Since SR1.5, fewer key advancements had to be integrated. In a like-with-like comparison, the combined effects of all AR6 updates result in median remaining carbon budget estimates for limiting warming to 1.5°C and 2°C being the same and about 60 GtCO <sub>2</sub> smaller, respectively, in AR6 compared to SR1.5. At the 67th percentile, remaining carbon budget estimates for limiting warming to 1.5°C and 2°C are about 40 to 60 GtCO <sub>2</sub> larger, respectively, mainly as a result of a narrower assessed TCRE range.		All methodological improvements and new evidence combined result in median and 67th percentile remaining carbon budget estimates for limiting warming to 1.5°C being about 300–350 GtCO <sub>2</sub> larger compared to an assessment that would use the evidence and methods available at the time of the AR5. For limiting warming to 2°C, the difference is about 400–500 GtCO <sub>2</sub> . Since SR1.5, fewer key advancements had to be integrated. In a like-with-like comparison, the combined effects of all AR6 updates result in median remaining carbon budget estimates for limiting warming to 1.5°C and 2°C being the same and about 60 GtCO <sub>2</sub> smaller, respectively, in AR6 compared to SR1.5. At the 67th percentile, remaining carbon budget estimates for limiting warming to 1.5°C and 2°C are about 40 to 60 GtCO <sub>2</sub> larger, respectively, mainly as a result of a narrower assessed TCRE range.
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	<div id="5.6" class="h1-container"></div>		<div id="5.6" class="h1-container"></div>

	<span id="biogeochemical-implications-of-carbon-dioxide-removal-and-solar-radiation-modification-1"></span>		<span id="biogeochemical-implications-of-carbon-dioxide-removal-and-solar-radiation-modification-1"></span>

	== 5.6 Biogeochemical Implications of Carbon Dioxide Removal and Solar Radiation Modification ==		== 5.6 Biogeochemical Implications of Carbon Dioxide Removal and Solar Radiation Modification ==

Laura: /* 5.5.1.4 Combined Assessment of TCRE */

2026-06-22T13:27:19Z

5.5.1.4 Combined Assessment of TCRE

Show changes

Laura: /* 5.4.8 Combined Biogeochemical Climate Feedback */

2026-06-22T13:25:30Z

5.4.8 Combined Biogeochemical Climate Feedback

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	[[File:5351138eee306fa6bb1a9910c191dbd9 IPCC_AR6_WGI_Figure_5_29.png]]		[[File:5351138eee306fa6bb1a9910c191dbd9 IPCC_AR6_WGI_Figure_5_29.png]]

	'''Figure 5.29 \|''' '''Estimates of the biogeochemical climate feedback parameter''' (α ''')''' . The parameter α (W m <sup>−2</sup> °C <sup>−1</sup>) for a feedback variable ''x'' is defined as		'''Figure 5.29 \|''' '''Estimates of the biogeochemical climate feedback parameter''' (α ''')''' . The parameter α (W m <sup>−2</sup> °C <sup>−1</sup>) for a feedback variable ''x'' is defined as <code> α <sub>x</sub> = δ N d x / δ x d T</code> where <code>δ N / δ x </code> is the change in top-of-atmosphere energy balance in response to a change in ''x'' induced by a change in surface temperature (''T''), as in [[IPCC:Wg1:Chapter:Chapter-7#7.4.1.1\|Section 7.4.1.1]] . '''(a)''' Synthesis of biogeochemical feedbacks from panels (b) and (c). Orange (blue) bars correspond to positive (negative) feedbacks increasing (decreasing) radiative forcing at the top of the atmosphere. Bars denote the mean and the error bar represents the 5–95% range of the estimates; '''(b)''' carbon-cycle feedbacks as estimated by coupled carbon-cycle climate models in the CMIP5 ([[#Arora--2013\|Arora et al., 2013]]) and CMIP6 ([[#Arora--2020\|Arora et al., 2020]]) ensembles, where dots represent single model estimates, and filled (open) circles are those estimates which do (not) include the representation of a terrestrial nitrogen cycle; '''(c)''' Estimates of other biogeochemical feedback mechanisms based on various modelling studies. Dots represent single estimates, and coloured bars denote the mean of these estimates with no weighting being made regarding the likelihood of any single estimate, and error bars the 5–95% range derived from these estimates. Results in panel (c) have been compiled from (a) [[#5.4.3.2\|Section 5.4.3.2]] ([[#Eliseev--2014a\|Eliseev et al., 2014a]] ; [[#Harrison--2018\|Harrison et al., 2018]]); (b) [[#5.4.3.3\|Section 5.4.3.3]] ([[#Schneider%20von%20Deimling--2012\|Schneider von Deimling et al., 2012]] ; [[#Burke--2013\|Burke et al., 2013]] , 2017b; [[#Koven--2015a\|Koven et al., 2015a]] , c; [[#MacDougall--2016b\|MacDougall and Knutti, 2016b]] ; [[#Gasser--2018\|Gasser et al., 2018]] ; [[#Kleinen--2018\|Kleinen and Brovkin, 2018]]), where the estimates from [[#Burke--2013\|Burke et al., 2013]] have been constrained as assessed in their study (c) [[#5.4.7\|Section 5.4.7]] ([[#Schneider%20von%20Deimling--2012\|Schneider von Deimling et al., 2012]] , 2015; [[#Koven--2015c\|Koven et al., 2015c]] ; [[#Turetsky--2020\|Turetsky et al., 2020]]); (d) [[#5.4.7\|Section 5.4.7]] ([[#Arneth--2010\|Arneth et al., 2010]] ; [[#Denisov--2013\|Denisov et al., 2013]] ; [[#Shindell--2013\|Shindell et al., 2013]] ; B.D. [[#Stocker--2013\|]] [[#Stocker--2013\|Stocker et al., 2013]] ; [[#Zhang--2017\|Zhang et al., 2017]]); (f) [[#5.4.7\|Section 5.4.7]] ([[#Xu-Ri--2012\|Xu-Ri et al., 2012]] ; B.D. [[#Stocker--2013\|]] [[#Stocker--2013\|Stocker et al., 2013]] ; [[#Zaehle--2013\|Zaehle, 2013]] ; [[#Tian--2019\|Tian et al., 2019]]); (g) [[#5.4.7\|Section 5.4.7]] ([[#Martinez-Rey--2015\|Martinez-Rey et al., 2015]] ; [[#Landolfi--2017\|Landolfi et al., 2017]] ; [[#Battaglia--2018b\|Battaglia and Joos, 2018b]]). (h) Section 6.3, Table 6.9 mean and the 5–95% range the assessed feedback parameter. Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

	<code> α ~~</code>~~ <sub>x</sub> =

	δ ~~<code>~~ N ~~</code>~~ d ~~<code>~~ x ~~</code>~~ / δ ~~<code>~~ x ~~</code>~~ d ~~<code>~~ T </code>

	where

	δ <code> N ~~</code>~~ / δ ~~<code>~~ x </code>

	is the change in top-of-atmosphere energy balance in response to a change in ''x'' induced by a change in surface temperature (''T''), as in [[IPCC:Wg1:Chapter:Chapter-7#7.4.1.1\|Section 7.4.1.1]] . '''(a)''' Synthesis of biogeochemical feedbacks from panels (b) and (c). Orange (blue) bars correspond to positive (negative) feedbacks increasing (decreasing) radiative forcing at the top of the atmosphere. Bars denote the mean and the error bar represents the 5–95% range of the estimates; '''(b)''' carbon-cycle feedbacks as estimated by coupled carbon-cycle climate models in the CMIP5 ([[#Arora--2013\|Arora et al., 2013]]) and CMIP6 ([[#Arora--2020\|Arora et al., 2020]]) ensembles, where dots represent single model estimates, and filled (open) circles are those estimates which do (not) include the representation of a terrestrial nitrogen cycle; '''(c)''' Estimates of other biogeochemical feedback mechanisms based on various modelling studies. Dots represent single estimates, and coloured bars denote the mean of these estimates with no weighting being made regarding the likelihood of any single estimate, and error bars the 5–95% range derived from these estimates. Results in panel (c) have been compiled from (a) [[#5.4.3.2\|Section 5.4.3.2]] ([[#Eliseev--2014a\|Eliseev et al., 2014a]] ; [[#Harrison--2018\|Harrison et al., 2018]]); (b) [[#5.4.3.3\|Section 5.4.3.3]] ([[#Schneider%20von%20Deimling--2012\|Schneider von Deimling et al., 2012]] ; [[#Burke--2013\|Burke et al., 2013]] , 2017b; [[#Koven--2015a\|Koven et al., 2015a]] , c; [[#MacDougall--2016b\|MacDougall and Knutti, 2016b]] ; [[#Gasser--2018\|Gasser et al., 2018]] ; [[#Kleinen--2018\|Kleinen and Brovkin, 2018]]), where the estimates from [[#Burke--2013\|Burke et al., 2013]] have been constrained as assessed in their study (c) [[#5.4.7\|Section 5.4.7]] ([[#Schneider%20von%20Deimling--2012\|Schneider von Deimling et al., 2012]] , 2015; [[#Koven--2015c\|Koven et al., 2015c]] ; [[#Turetsky--2020\|Turetsky et al., 2020]]); (d) [[#5.4.7\|Section 5.4.7]] ([[#Arneth--2010\|Arneth et al., 2010]] ; [[#Denisov--2013\|Denisov et al., 2013]] ; [[#Shindell--2013\|Shindell et al., 2013]] ; B.D. [[#Stocker--2013\|]] [[#Stocker--2013\|Stocker et al., 2013]] ; [[#Zhang--2017\|Zhang et al., 2017]]); (f) [[#5.4.7\|Section 5.4.7]] ([[#Xu-Ri--2012\|Xu-Ri et al., 2012]] ; B.D. [[#Stocker--2013\|]] [[#Stocker--2013\|Stocker et al., 2013]] ; [[#Zaehle--2013\|Zaehle, 2013]] ; [[#Tian--2019\|Tian et al., 2019]]); (g) [[#5.4.7\|Section 5.4.7]] ([[#Martinez-Rey--2015\|Martinez-Rey et al., 2015]] ; [[#Landolfi--2017\|Landolfi et al., 2017]] ; [[#Battaglia--2018b\|Battaglia and Joos, 2018b]]). (h) Section 6.3, Table 6.9 mean and the 5–95% range the assessed feedback parameter. Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

	The climate feedback parameter for CO <sub>2</sub> (–1.13 ± 0.45 W m <sup>–2</sup> °C <sup>–1</sup> , mean and 1 standard-deviation range) is dominated by the contribution of the CO <sub>2</sub> -induced increase of ocean and land carbon storage (–1.46 ± 0.41 W m <sup>–2</sup> °C <sup>–1</sup> , corresponding to a β <sub>L+O</sub> of 1.66 ± 0.31 PgC ppm <sup>–1</sup>), with smaller contributions from the carbon cycle’s response to climate (0.24 ± 0.17 W m <sup>–2</sup> °C <sup>–1</sup> , corresponding to γ <sub>L+O</sub> of –50 ± 34 PgC °C <sup>–1</sup>), and emissions from permafrost thaw (0.09 [0.02 to 0.20] W m <sup>–2</sup> °C <sup>–1</sup> , corresponding to γ of –18 [3 to 41] PgC °C <sup>–1</sup> , mean and 5–95% range) (Figure 5.29a). This estimate does not include an estimate of the fire-related CO <sub>2</sub> feedback (range: 0.01–0.06 W m <sup>–2</sup> °C <sup>–1</sup>), as only ''limited evidence'' was available to inform its assessment. The sum (mean and 5–95th percentile range) of feedbacks from natural emissions of CH <sub>4</sub> including permafrost thaw, and N <sub>2</sub> O (0.05 [0.02 to 0.09] W m <sup>–2</sup> °C <sup>–1</sup>), and feedbacks from aerosol and atmospheric chemistry (–0.20 [–0.41 to 0.01] W m <sup>–2</sup> °C <sup>–1</sup>) leads to an estimate of the non-CO <sub>2</sub> biogeochemical feedback parameter of –0.15 [–0.36 to +0.06] W m <sup>–2</sup> °C <sup>–1</sup> . There is ''low confidence'' in the estimate of the non-CO <sub>2</sub> biogeochemical feedbacks, due to the large range in the estimates of α for some individual feedbacks (Figure 5.29c), which can be attributed to the diversity in how models account for these feedbacks, limited process-level understanding, and the existence of known feedbacks where there is insufficient evidence to assess the feedback strength.		The climate feedback parameter for CO <sub>2</sub> (–1.13 ± 0.45 W m <sup>–2</sup> °C <sup>–1</sup> , mean and 1 standard-deviation range) is dominated by the contribution of the CO <sub>2</sub> -induced increase of ocean and land carbon storage (–1.46 ± 0.41 W m <sup>–2</sup> °C <sup>–1</sup> , corresponding to a β <sub>L+O</sub> of 1.66 ± 0.31 PgC ppm <sup>–1</sup>), with smaller contributions from the carbon cycle’s response to climate (0.24 ± 0.17 W m <sup>–2</sup> °C <sup>–1</sup> , corresponding to γ <sub>L+O</sub> of –50 ± 34 PgC °C <sup>–1</sup>), and emissions from permafrost thaw (0.09 [0.02 to 0.20] W m <sup>–2</sup> °C <sup>–1</sup> , corresponding to γ of –18 [3 to 41] PgC °C <sup>–1</sup> , mean and 5–95% range) (Figure 5.29a). This estimate does not include an estimate of the fire-related CO <sub>2</sub> feedback (range: 0.01–0.06 W m <sup>–2</sup> °C <sup>–1</sup>), as only ''limited evidence'' was available to inform its assessment. The sum (mean and 5–95th percentile range) of feedbacks from natural emissions of CH <sub>4</sub> including permafrost thaw, and N <sub>2</sub> O (0.05 [0.02 to 0.09] W m <sup>–2</sup> °C <sup>–1</sup>), and feedbacks from aerosol and atmospheric chemistry (–0.20 [–0.41 to 0.01] W m <sup>–2</sup> °C <sup>–1</sup>) leads to an estimate of the non-CO <sub>2</sub> biogeochemical feedback parameter of –0.15 [–0.36 to +0.06] W m <sup>–2</sup> °C <sup>–1</sup> . There is ''low confidence'' in the estimate of the non-CO <sub>2</sub> biogeochemical feedbacks, due to the large range in the estimates of α for some individual feedbacks (Figure 5.29c), which can be attributed to the diversity in how models account for these feedbacks, limited process-level understanding, and the existence of known feedbacks where there is insufficient evidence to assess the feedback strength.
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	<span id="abrupt-changes-and-tipping-points"></span>		<span id="abrupt-changes-and-tipping-points"></span>

	=== 5.4.9 Abrupt Changes and Tipping Points ===		=== 5.4.9 Abrupt Changes and Tipping Points ===

Laura: /* 5.4.3.3 Soil Carbon */

2026-06-22T13:23:46Z

5.4.3.3 Soil Carbon

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	~~'''~~Box 5.1 \| Permafrost Carbon and ~~Feedb''' '''acks~~ to Climate~~'''~~		== Box 5.1 \| Permafrost Carbon and Feedbacks to Climate ==

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	In conclusion, thawing terrestrial permafrost will lead to carbon release under a warmer world (''high confidence''). However, there is ''low confidence'' on the timing, magnitude and linearity of the permafrost climate feedback owing to the wide range of published estimates and the incomplete knowledge and representation in models of drivers and relationships. It is projected that CO <sub>2</sub> released from permafrost will be 18 (3.1–41) PgC °C <sup>–1</sup> by 2100, with the relative contribution of CO <sub>2</sub> vs CH <sub>4</sub> remaining poorly constrained. Permafrost carbon feedbacks are included among the under-represented feedbacks quantified in Figure 5.29.		In conclusion, thawing terrestrial permafrost will lead to carbon release under a warmer world (''high confidence''). However, there is ''low confidence'' on the timing, magnitude and linearity of the permafrost climate feedback owing to the wide range of published estimates and the incomplete knowledge and representation in models of drivers and relationships. It is projected that CO <sub>2</sub> released from permafrost will be 18 (3.1–41) PgC °C <sup>–1</sup> by 2100, with the relative contribution of CO <sub>2</sub> vs CH <sub>4</sub> remaining poorly constrained. Permafrost carbon feedbacks are included among the under-represented feedbacks quantified in Figure 5.29.
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	<div id="5.4.4" class="h2-container"></div>		<div id="5.4.4" class="h2-container"></div>

	<span id="climate-effects-on-future-ocean-carbon-uptake"></span>		<span id="climate-effects-on-future-ocean-carbon-uptake"></span>

	=== 5.4.4 Climate Effects on Future Ocean Carbon Uptake ===		=== 5.4.4 Climate Effects on Future Ocean Carbon Uptake ===

Laura: /* 5.2.2.5 Methane (CH 4) Budget */

2026-06-22T13:22:17Z

5.2.2.5 Methane (CH 4) Budget

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	== Cross-Chapter Box 5.2 \| Drivers of Atmospheric Methane Changes During 1980–2019 ==		== Cross-Chapter Box 5.2 \| Drivers of Atmospheric Methane Changes During 1980–2019 ==

Laura: /* 5.2.2.5 Methane (CH 4) Budget */

2026-06-22T13:22:00Z

5.2.2.5 Methane (CH 4) Budget

Laura: /* 5.2.1.4.2 Interannual variability in land–atmosphere CO 2 exchange */

2026-06-22T13:20:28Z

5.2.1.4.2 Interannual variability in land–atmosphere CO 2 exchange

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	~~'''~~Cross-Chapter Box 5.1 \| Interactions Between the Carbon and Water Cycles, Particularly Under ~~Dro''' '''ught~~ Conditions~~'''~~		== Cross-Chapter Box 5.1 \| Interactions Between the Carbon and Water Cycles, Particularly Under Drought Conditions ==

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	In conclusion, extensive deployment of BECCS and afforestation/reforestation will require larger amounts of freshwater resources than used by the previous vegetation, altering the water cycle at regional scales (''high confidence''). Consequences of high water consumption on downstream uses, biodiversity, and regional climate depend on prior land cover, background climate conditions, and scale of deployment (''high confidence''). Therefore, a regional approach is required to determine the efficacy and sustainability of CDR projects.		In conclusion, extensive deployment of BECCS and afforestation/reforestation will require larger amounts of freshwater resources than used by the previous vegetation, altering the water cycle at regional scales (''high confidence''). Consequences of high water consumption on downstream uses, biodiversity, and regional climate depend on prior land cover, background climate conditions, and scale of deployment (''high confidence''). Therefore, a regional approach is required to determine the efficacy and sustainability of CDR projects.
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	<div id="5.2.1.5" class="h3-container"></div>		<div id="5.2.1.5" class="h3-container"></div>

	<span id="co-2-budget"></span>		<span id="co-2-budget"></span>

	==== 5.2.1.5 CO <sub>2</sub> Budget ====		==== 5.2.1.5 CO <sub>2</sub> Budget ====

Laura: /* Biogeochemical Implications of Carbon Dioxide Removal and Solar Radiation Modification */

2026-06-22T13:16:05Z

Biogeochemical Implications of Carbon Dioxide Removal and Solar Radiation Modification

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	'''Wide-ranging side effects of CDR methods have been identified that can either weaken or strengthen the carbon sequestration and cooling potential of these methods and affect the achievement of sustainable development goals (''high confidence'').''' Biophysical and biogeochemical side effects of CDR methods are associated with changes in surface albedo, the water cycle, emissions of CH <sub>4</sub> and N <sub>2</sub> O, ocean acidification and marine ecosystem productivity (''high confidence''). These side effects and associated Earth system feedbacks can decrease carbon uptake and/or change local and regional climate, and in turn limit the CO <sub>2</sub> sequestration and cooling potential of specific CDR methods (''medium confidence''). Deployment of CDR, particularly on land, can also affect water quality and quantity, food production and biodiversity, with consequences for the achievement of related sustainable development goals (''high confidence''). These effects are often highly dependent on local context, management regime, prior land use, and scale of deployment (''high confidence''). A wide range of co-benefits are obtained with methods that seek to restore natural ecosystems or improve soil carbon (''high confidence''). The biogeochemical effects of terminating CDR are expected to be small for most CDR methods (''medium confidence''). {5.6.2.2; Figure 5.36; Cross-Chapter Box 5.1}		'''Wide-ranging side effects of CDR methods have been identified that can either weaken or strengthen the carbon sequestration and cooling potential of these methods and affect the achievement of sustainable development goals (''high confidence'').''' Biophysical and biogeochemical side effects of CDR methods are associated with changes in surface albedo, the water cycle, emissions of CH <sub>4</sub> and N <sub>2</sub> O, ocean acidification and marine ecosystem productivity (''high confidence''). These side effects and associated Earth system feedbacks can decrease carbon uptake and/or change local and regional climate, and in turn limit the CO <sub>2</sub> sequestration and cooling potential of specific CDR methods (''medium confidence''). Deployment of CDR, particularly on land, can also affect water quality and quantity, food production and biodiversity, with consequences for the achievement of related sustainable development goals (''high confidence''). These effects are often highly dependent on local context, management regime, prior land use, and scale of deployment (''high confidence''). A wide range of co-benefits are obtained with methods that seek to restore natural ecosystems or improve soil carbon (''high confidence''). The biogeochemical effects of terminating CDR are expected to be small for most CDR methods (''medium confidence''). {5.6.2.2; Figure 5.36; Cross-Chapter Box 5.1}

	'''Solar radiation modification (SRM) would increase the global land and ocean CO <sub>2</sub> sinks (''medium confidence'') but would not stop CO~~'''~~ <sub>2</sub> from increasing in the atmosphere, thus exacerbating ocean acidification under continued anthropogenic emissions (''high confidence'').''' SRM acts to cool the planet relative to unmitigated climate change, which would increase the land sink by reducing plant and soil respiration and slow the reduction of ocean carbon uptake due to warming (''medium confidence''). SRM would not counteract or stop ocean acidification (''high confidence''). The sudden and sustained termination of SRM would rapidly increase global warming, with the return of positive and negative effects on the carbon sinks (''very'' ''high confidence''). {4.6.3; 5.6.3}		'''Solar radiation modification (SRM) would increase the global land and ocean CO <sub>2</sub> sinks (''medium confidence'') but would not stop CO <sub>2</sub> from increasing in the atmosphere, thus exacerbating ocean acidification under continued anthropogenic emissions (''high confidence'').''' SRM acts to cool the planet relative to unmitigated climate change, which would increase the land sink by reducing plant and soil respiration and slow the reduction of ocean carbon uptake due to warming (''medium confidence''). SRM would not counteract or stop ocean acidification (''high confidence''). The sudden and sustained termination of SRM would rapidly increase global warming, with the return of positive and negative effects on the carbon sinks (''very'' ''high confidence''). {4.6.3; 5.6.3}

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	~~'''~~Cross-Chapter Box 5.2 \| Drivers of Atmospheric Methane Changes During~~''' '''~~1980–2019~~'''~~		== Cross-Chapter Box 5.2 \| Drivers of Atmospheric Methane Changes During 1980–2019 ==

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	[[File:207a64c729e09a7b3dc27844b35bcd98 IPCC_AR6_WGI_CCBox_5_2_Figure_1.png]]		[[File:207a64c729e09a7b3dc27844b35bcd98 IPCC_AR6_WGI_CCBox_5_2_Figure_1.png]]

	'''Cross-Chapter Box 5.2, Figure 1 \|'''		'''Cross-Chapter Box 5.2, Figure 1 \|''' '''Methane sources and sinks for four decades from atmospheric inversions with the budget imbalance''' (source–sink; dark blue bars) (plotted on the left y-axis). Top-down analysis from [[#Kirschke--2013\|Kirschke et al. (2013)]] ; [[#Saunois--2020\|Saunois et al. (2020)]] . The global CH <sub>4</sub> concentration seen in the black line (plotted on the right y-axis), representing National Oceanic and Atmospheric Administration (NOAA) observed global monthly mean atmospheric CH <sub>4</sub> in dry-air mole fractions for 1983–2019 (Chapter 2, Annex V). Natural sources include emissions from natural wetlands, lakes and rivers, geological sources, wild animals, termites, wildfires, permafrost soils, and oceans. Anthropogenic sources include emissions from enteric fermentation and manure, landfills, waste and wastewater, rice cultivation, coal mining, oil and gas industry, biomass and biofuel burning. The top-down total sink is determined from global mass balance that includes chemical losses due to reactions with hydroxyl (OH), atomic chlorine (Cl), and excited atomic oxygen (O <sup>1</sup> D), and oxidation by bacteria in aerobic soils (Table 5.2). Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

	'''Methane sources and sinks for four decades from atmospheric inversions with the budget imbalance''' (source–sink; dark blue bars) (plotted on the left y-axis). Top-down analysis from [[#Kirschke--2013\|Kirschke et al. (2013)]] ; [[#Saunois--2020\|Saunois et al. (2020)]] . The global CH <sub>4</sub> concentration seen in the black line (plotted on the right y-axis), representing National Oceanic and Atmospheric Administration (NOAA) observed global monthly mean atmospheric CH <sub>4</sub> in dry-air mole fractions for 1983–2019 (Chapter 2, Annex V). Natural sources include emissions from natural wetlands, lakes and rivers, geological sources, wild animals, termites, wildfires, permafrost soils, and oceans. Anthropogenic sources include emissions from enteric fermentation and manure, landfills, waste and wastewater, rice cultivation, coal mining, oil and gas industry, biomass and biofuel burning. The top-down total sink is determined from global mass balance that includes chemical losses due to reactions with hydroxyl (OH), atomic chlorine (Cl), and excited atomic oxygen (O <sup>1</sup> D), and oxidation by bacteria in aerobic soils (Table 5.2). Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

	A few studies emphasize the role of chemical destruction by hydroxyl (OH; the primary sink of methane), in driving changes in the growth of atmospheric methane abundance, in particular after 2006 ([[#Rigby--2017\|Rigby et al., 2017]] ; [[#Turner--2017\|Turner et al., 2017]]). Studies applying three-dimensional atmospheric inversion ([[#McNorton--2018\|McNorton et al., 2018]]), simple multi-species inversion ([[#Thompson--2018\|Thompson et al., 2018]]), as well as empirical methods using a variety of observational constraints based on OH chemistry ([[#Nicely--2018\|Nicely et al., 2018]] ; [[#Patra--2021\|Patra et al., 2021]]), do not find trends in OH large enough to explain the methane changes post-2006. On the contrary, global chemistry–climate models based on fundamental principles of atmospheric chemistry and known emissions trends of anthropogenic non-methane short-lived climate forcers simulate an increase in OH over this period ([[#Zhao--2019\|Zhao et al., 2019]] ; [[#Stevenson--2020\|Stevenson et al., 2020]] ; see Section 6.2.3). These contrasting lines of evidence suggest that OH changes may have had a small moderating influence on methane growth since 2007 (''l'' ''ow confidence'').		A few studies emphasize the role of chemical destruction by hydroxyl (OH; the primary sink of methane), in driving changes in the growth of atmospheric methane abundance, in particular after 2006 ([[#Rigby--2017\|Rigby et al., 2017]] ; [[#Turner--2017\|Turner et al., 2017]]). Studies applying three-dimensional atmospheric inversion ([[#McNorton--2018\|McNorton et al., 2018]]), simple multi-species inversion ([[#Thompson--2018\|Thompson et al., 2018]]), as well as empirical methods using a variety of observational constraints based on OH chemistry ([[#Nicely--2018\|Nicely et al., 2018]] ; [[#Patra--2021\|Patra et al., 2021]]), do not find trends in OH large enough to explain the methane changes post-2006. On the contrary, global chemistry–climate models based on fundamental principles of atmospheric chemistry and known emissions trends of anthropogenic non-methane short-lived climate forcers simulate an increase in OH over this period ([[#Zhao--2019\|Zhao et al., 2019]] ; [[#Stevenson--2020\|Stevenson et al., 2020]] ; see Section 6.2.3). These contrasting lines of evidence suggest that OH changes may have had a small moderating influence on methane growth since 2007 (''l'' ''ow confidence'').
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	[[File:ffb928ecae70a1c4030ba22700f29ce0 IPCC_AR6_WGI_CCBox_5_2_Figure_2.png]]		[[File:ffb928ecae70a1c4030ba22700f29ce0 IPCC_AR6_WGI_CCBox_5_2_Figure_2.png]]

	'''Cross-Chapter Box 5.2, Figure 2 \|'''		'''Cross-Chapter Box 5.2, Figure 2 \|''' '''Anomalies in global and regional methane (CH''' <sub>4</sub> ''') emissions for 1988–2017''' . The map in the centre shows mean CH <sub>4</sub> emissions for 2010–2016. Multi-model mean (line) and 1-s standard deviations (shaded) for 2000–2017 are shown for 9 surface CH <sub>4</sub> and 10 satellite XCH <sub>4</sub> inversions, and 22 wetland models or model variants that participated in GCP-CH <sub>4</sub> budget assessment ([[#Saunois--2020\|Saunois et al., 2020]]). The results for the period before 2000 are available from two inversions, one using 19 sites ([[#Chandra--2021\|Chandra et al., 2021]] ; also used for the 2010–2016 mean emissions map) and one for global totals ([[#Bousquet--2006\|Bousquet et al., 2006]]). The long-term mean values for 2010–2016 (common for all GCP–CH <sub>4</sub> inversions), as indicated within each panel separately, are subtracted from the annual-mean time series for the calculation of anomalies for each region. Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

	'''Anomalies in global and regional methane (CH''' <sub>4</sub> ''') emissions for 1988–2017''' . The map in the centre shows mean CH <sub>4</sub> emissions for 2010–2016. Multi-model mean (line) and 1-s standard deviations (shaded) for 2000–2017 are shown for 9 surface CH <sub>4</sub> and 10 satellite XCH <sub>4</sub> inversions, and 22 wetland models or model variants that participated in GCP-CH <sub>4</sub> budget assessment ([[#Saunois--2020\|Saunois et al., 2020]]). The results for the period before 2000 are available from two inversions, one using 19 sites ([[#Chandra--2021\|Chandra et al., 2021]] ; also used for the 2010–2016 mean emissions map) and one for global totals ([[#Bousquet--2006\|Bousquet et al., 2006]]). The long-term mean values for 2010–2016 (common for all GCP–CH <sub>4</sub> inversions), as indicated within each panel separately, are subtracted from the annual-mean time series for the calculation of anomalies for each region. Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

	There is evidence from emissions inventories at country level and regional scale inverse modelling that CH <sub>4</sub> growth rate variability between 1988 and 2017 is closely linked to anthropogenic activities (''medium agreement''). Isotopic composition observations and inventory data suggest that concurrent emissions changes from both fossil fuels and agriculture are playing roles in the resumed CH <sub>4</sub> growth since 2007 (''high confidence''). Shorter-term decadal variability is predominantly driven by the influence of El Niño–Southern Oscillation on emissions from wetlands and biomass burning (Cross-Chapter Box 5.2, Figure 2), and loss due to OH variations (''medium confidence''), but lacking quantitative contribution from each of the sectors. By synthesizing all available information regionally from a priori (bottom-up) emissions, satellite and surface observations, including isotopic information, and inverse modelling (top-down), the capacity to track and explain changes in, and drivers of, natural and anthropogenic CH <sub>4</sub> regional and global emissions has improved since AR5, but fundamental uncertainties related to OH variations remain unchanged.		There is evidence from emissions inventories at country level and regional scale inverse modelling that CH <sub>4</sub> growth rate variability between 1988 and 2017 is closely linked to anthropogenic activities (''medium agreement''). Isotopic composition observations and inventory data suggest that concurrent emissions changes from both fossil fuels and agriculture are playing roles in the resumed CH <sub>4</sub> growth since 2007 (''high confidence''). Shorter-term decadal variability is predominantly driven by the influence of El Niño–Southern Oscillation on emissions from wetlands and biomass burning (Cross-Chapter Box 5.2, Figure 2), and loss due to OH variations (''medium confidence''), but lacking quantitative contribution from each of the sectors. By synthesizing all available information regionally from a priori (bottom-up) emissions, satellite and surface observations, including isotopic information, and inverse modelling (top-down), the capacity to track and explain changes in, and drivers of, natural and anthropogenic CH <sub>4</sub> regional and global emissions has improved since AR5, but fundamental uncertainties related to OH variations remain unchanged.
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	=== 5.2.3 N <sub>2</sub> O: Trends, Variability and Budget ===		=== 5.2.3 N <sub>2</sub> O: Trends, Variability and Budget ===