Editing IPCC:AR6/WGI/Chapter-5 (section)

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

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<span id="introduction-1"></span>
=== 5.6.1 Introduction ===

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Carbon dioxide removal (CDR) refers to anthropogenic activities that seek to remove CO <sub>2</sub> from the atmosphere and durably store it in geological, terrestrial or ocean reservoirs, or in products (Glossary). CO <sub>2</sub> is removed from the atmosphere by enhancing biological or geochemical carbon sinks or by direct capture of CO <sub>2</sub> from air and storage. Solar radiation modification (SRM) refers to the intentional, planetary-scale modification of the Earth’s radiative budget with the aim of limiting global warming. Most proposed SRM methods involve reducing the amount of incoming solar radiation reaching the surface, but others also act on the longwave radiation budget by reducing optical thickness and cloud lifetime (Glossary). SRM does not fall within the IPCC definitions of mitigation and adaptation (Glossary). CDR and SRM are referred to as ‘geoengineering’ in some of the literature, and are considered separately in this report.

This section assesses the implications of CDR and SRM for biogeochemical cycles. CDR has received growing interest as an important mitigation option in emissions scenarios consistent with meeting the Paris Agreement climate goals (SR1.5, SRCCL). The climate effects of CDR and SRM are assessed in Chapter 4, and a detailed assessment of the socio-economic dimensions of these options is presented in AR6 WGIII, Chapters 7 and 12.

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<span id="biogeochemical-responses-to-carbon-dioxide-removal-cdr"></span>
=== 5.6.2 Biogeochemical Responses to Carbon Dioxide Removal (CDR) ===

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The scope of this section is to assess the general and methods-specific effects of CDR on the global carbon cycle and other biogeochemical cycles. The focus is on Earth system feedbacks that either amplify or reduce carbon sequestration potentials of specific CDR methods, and determine their effectiveness in reducing atmospheric CO <sub>2</sub> and mitigating climate change. Technical carbon sequestration potentials of CDR methods are assessed on a qualitative scale; a comprehensive quantitative assessment is left to the AR6 Working Group III Report (Chapters 7 and 12). Biogeochemical and biophysical side effects of CDR methods are assessed here, while the co-benefits and trade-offs for biodiversity, water and food production are briefly discussed for completeness, but a comprehensive assessment is left to WGII (Chapters 2 and 5) and WGIII (Chapters 7 and 12). The assessment in this chapter emphasizes literature published since the AR5 WGI report (Chapter 6) for the assessment of the global carbon cycle response to CDR, and literature published since SR1.5 (Chapter 4; [[#IPCC--2018|IPCC, 2018]] ), SRCCL (Chapter 6, [[#IPCC--2019a|IPCC, 2019a]] ) and SROCC ( [[#Bindoff--2019|Bindoff et al., 2019]] ) for the assessment of potentials and side effects of specific CDR methods. Emerging literature on deliberate methane removal is also briefly discussed.

In this chapter, CDR methods are categorised by the carbon cycle processes that result in CO <sub>2</sub> removal: (i) enhanced net biological production and storage by land ecosystems; (ii) enhanced net biological production and storage in the open and coastal ocean; (iii) enhanced geochemical processes on land and in the ocean; and (iv) direct air capture and storage by chemical processes. A subset of CDR methods that restore or sustainably manage natural or modified ecosystems while providing human well-being and biodiversity benefits are also referred to as natural or nature-based solutions (Glossary; [[#Griscom--2017|Griscom et al., 2017]] , 2020; [[#Fargione--2018|Fargione et al., 2018]] ). CDR methods commonly discussed in the literature are summarized in Table 5.9. Other CDR options have been suggested, but there is insufficient literature for an assessment. These include ocean biomass burial, ocean downwelling, removal of CO <sub>2</sub> from seawater with storage, and cloud alkalinization ( [[#Keller--2018a|Keller et al., 2018a]] ; [[#GESAMP--2019|GESAMP, 2019]] ).

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'''Table 5.9 |''' '''Characteristics of carbon dioxide removal (CDR) methods''' . Termination effects refer to the possible effects of a hypothetical, sudden and sustained termination of the CDR method.

{| class="wikitable"
|-
! '''Category'''

! '''Methods'''

'''(Section Where the Method is Assessed)'''

! '''Nature of CO''' <sub>2</sub> '''Removal Process/Storage Form'''

! '''Description'''

! '''Time Scale of Carbon Storage'''

! '''Factors that Affect Carbon Storage Time Scale'''

! '''Termination Effects'''

|-
| rowspan="5"| Enhanced biological production and storage on land (in vegetation, soils or geologic formations)

| Afforestation, reforestation and forest management

(5.6.2.2.1)

| Biological/organic

| Store carbon in trees and soils by planting, restoring or managing forests

| Decades to centuries ( [[#Cooper--1983|Cooper, 1983]] )

| Disturbances (e.g., fires, pests), extreme weather

| None

|-
| Soil carbon sequestration

(5.6.2.2.1)

| Biological/organic

| Use agricultural management practices to improve soil carbon storage

| Decades to centuries

( [[#Dignac--2017|Dignac et al., 2017]] )

| Soil and crop management

| None

|-
| Biochar

(5.6.2.2.1)

| Biological/organic

| Burn biomass at high temperature under anoxic conditions to form biochar and add to soils

| Decades to centuries ( [[#Campbell--2018|Campbell et al., 2018]] )

| Fire

| None

|-
| Peatland restoration

(5.6.2.2.1)

| Biological/organic

| Store carbon in soil by creating or restoring peatlands

| Decades to centuries

( [[#Harenda--2018|Harenda et al., 2018]] )

| Peatland drainage, fire, drought, land-use change

| None

|-
| Bioenergy with carbon capture and storage (BECCS)

(5.6.2.2.1)

| Biological/inorganic

| Production of energy from plant biomass combined with carbon capture and storage

| Potentially permanent – analogous to direct air carbon capture with carbon storage (DACCS) ( [[#Szulczewski--2012|Szulczewski et al., 2012]] )

| Leakage

| None

|-
| rowspan="3"| Enhanced biological production and storage in coastal and open ocean

| Ocean fertilization

(5.6.2.2.2)

| Biological/organic

| Fertilize upper ocean with micro (Fe) and macronutrients (N, P) to increase phytoplankton photosynthesis and biomass and deep ocean carbon storage through the biological pump

| Decades to millennia

( [[#Oschlies--2010a|Oschlies et al., 2010a]] ; [[#Robinson--2014|Robinson et al., 2014]] )

| Ocean stratification and circulation ( [[#Robinson--2014|Robinson et al., 2014]] ); efficiency of carbon sequestration in deep ocean ( [[#Yoon--2018|Yoon et al., 2018]] )

| Uncertain ( [[#Keller--2014|Keller et al., 2014]] )

|-
| Artificial ocean upwelling

(5.6.2.2.2)

| Biological/organic

| Pump nutrient-rich deep ocean water to the surface to increase carbon uptake and storage through the biological pump.

| Centuries to millennia ( [[#Oschlies--2010b|Oschlies et al., 2010b]] )

| Ocean circulation; dissolved inorganic carbon content of upwelled waters ( [[#Oschlies--2010b|Oschlies et al., 2010b]] )

| Warming beyond temperatures experienced if artificial ocean upwelling had not been deployed ( [[#Keller--2014|Keller et al., 2014]] )

|-
| Restoration of vegetated coastal ecosystems (“blue carbon”)

(5.6.2.2.2)

| Biological/organic

| Manage coastal ecosystems to increase net primary production and store carbon in sediments

| Decades to centuries if functional integrity of ecosystem maintained ( [[#Mcleod--2011|Mcleod et al., 2011]] )

| Land-use change of coastal ecosystems; extreme weather (e.g., heatwaves); sea level change ( [[#NASEM--2019|NASEM, 2019]] )

| None

|-
| rowspan="2"| Enhanced geochemical processes on land and in ocean

| Enhanced weathering

(5.6.2.2.3)

| Geochemical/inorganic

| Spread alkaline minerals on land to chemically remove atmospheric CO <sub>2</sub> in reactions that form solid minerals (carbonates and silicates) that are stored in soils or in the ocean

| 10,000 to 10 <sup>6</sup> years ( [[#Fuss--2018|Fuss et al., 2018]] )

| Storage in soils or ocean ( [[#Fuss--2018|Fuss et al., 2018]] )

| None

|-
| Ocean alkalinization

(5.6.2.2.3)

| Geochemical/inorganic

| Increased CO <sub>2</sub> uptake via increased alkalinity by deposition of alkaline minerals (e.g., olivine).

| 10,000 to 100,000 years ( [[#Keller--2019|Keller, 2019]] )

| Carbonate chemistry; ocean stratification and circulation ( [[#Keller--2019|Keller, 2019]] )

| Higher rates of warming and acidification than if alkalinization had not begun (under a high emissions scenario) ( [[#González--2018|González et al., 2018]] )

|-
| Chemical

| Direct air carbon capture with storage (DACCS)

(5.6.2.2.4)

| Chemical/inorganic

| Direct removal of CO <sub>2</sub> from air through chemical adsorption, absorption or mineralization, and storage underground, in deep ocean or in long-lasting usable materials

| Potentially permanent

| Leakage

| None

|}

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<span id="global-carbon-cycle-responses-to-cdr"></span>
==== 5.6.2.1 Global Carbon Cycle Responses to CDR ====

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This subsection assesses evidence about the response of the global carbon cycle to CDR from idealized model simulations which assume that CO <sub>2</sub> is removed from the atmosphere directly and stored permanently in the geologic reservoir, which is analogous to direct air carbon capture with carbon storage (DACCS) (Table 5.9). The carbon cycle response to specific land and ocean-based CDR methods is assessed in [[#5.6.2.2.2|Section 5.6.2.2.2]] . At the time of AR5 there were very few studies about the global carbon cycle response to CDR. Based on these studies and general understanding of the carbon cycle, AR5 WGI [[IPCC:Wg1:Chapter:Chapter-6|Chapter 6]] assessed that it is ''virtually certain'' that deliberate removal of CO <sub>2</sub> from the atmosphere will be partially offset by outgassing of CO <sub>2</sub> from the ocean and land carbon sinks. ''Low confidence'' was placed on any quantification of effects. Since AR5 WGI Chapter 6, several studies have investigated the carbon cycle response to CDR in idealized ‘pulse’ removal simulations, whereby a specified amount of CO <sub>2</sub> is removed instantly from the atmosphere, and scenario simulations with CO <sub>2</sub> emissions and removals following a plausible trajectory. In addition, a dedicated carbon dioxide removal model intercomparison project was initiated (CDRMIP; [[#Keller--2018b|Keller et al., 2018b]] ) which includes a range of CDR experiments from idealized simulations to simulations of deployment of specific CDR methods (afforestation and ocean alkalinization).

This subsection assesses three aspects of the climate–carbon cycle response to CDR: the time-dependent behaviour of CO <sub>2</sub> fluxes in scenarios with CDR, the effectiveness of CDR in drawing down atmospheric CO <sub>2</sub> and cooling global mean temperature, and the symmetry of the climate–carbon cycle response to positive and negative CO <sub>2</sub> emissions.

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<span id="carbon-cycle-response-to-instantaneous-cdr"></span>
===== 5.6.2.1.1 Carbon cycle response to instantaneous CDR =====

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Idealized ‘pulse’ removal Earth system model simulations are useful for understanding the carbon cycle response to CDR. Figure 5.32 illustrates the response of atmospheric CO <sub>2</sub> , land and ocean carbon sinks to an instantaneous CO <sub>2</sub> removal applied from a pre-industrial equilibrium state. Following CO <sub>2</sub> removal from the atmosphere, the atmospheric CO <sub>2</sub> concentration declines rapidly at first and then rebounds (Figure 5.32a). This rebound is due to CO <sub>2</sub> release by the terrestrial biosphere and the ocean in response to declining atmospheric CO <sub>2</sub> levels (Figure 5.32b,c; M. [[#Collins--2013|]] [[#Collins--2013|Collins et al., 2013]] ). For the model simulations shown in Figure 5.32, 23 ± 6% (mean ± 1 standard deviation) of the 100 PgC removed remains out of the atmosphere 80–100 years after the instantaneous removal. The remainder is offset by CO <sub>2</sub> outgassing from the land (49 ± 12%) and ocean (29 ± 7%). While the direction of the CO <sub>2</sub> flux is robust across models, the relative contribution of the outgassing from land and ocean reservoirs to the atmospheric CO <sub>2</sub> rebound after removal varies. These results corroborate the ''high confidence'' placed by AR5 WGI (Chapter 6) on the partial compensation of CO <sub>2</sub> removal from the atmosphere by CO <sub>2</sub> outgassing from the land and ocean. Due to disagreement between models, the magnitude of this outgassing and the relative contribution of land and ocean fluxes remains ''low confidence'' .

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[[File:f3780888188c488285b91664a404d52e IPCC_AR6_WGI_Figure_5_32.png]]

'''Figure 5.32 |''' '''Carbon cycle response to instantaneous carbon dioxide (CO''' <sub>2</sub> ''') removal from''' '''the atmosphere.''' '''(a)''' Atmospheric CO <sub>2</sub> concentration; '''(b)''' change in land carbon reservoir; '''(c)''' change in ocean carbon reservoir. Results are shown for simulations with seven CMIP6 Earth system models and the University of Victoria Earth System Climate Model (UVic ESCM) of intermediate complexity forced with 100 PgC instantaneously removed from the atmosphere. The ‘pulse’ removal is applied from a model state in equilibrium with a pre-industrial atmospheric CO <sub>2</sub> concentration (CDRMIP experiment CDR-pi-pulse; [[#Keller--2018b|Keller et al., 2018b]] ). Changes in land and ocean carbon reservoirs are calculated relative to a pre-industrial control simulation. Data for the UVic ESCM is from [[#Zickfeld--2021|Zickfeld et al. (2021)]] . Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

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<span id="carbon-cycle-response-over-time-in-scenarios-with-cdr"></span>
===== 5.6.2.1.2 Carbon cycle response over time in scenarios with CDR =====

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Since AR5 WGI (Chapter 6), studies with ESMs have explored the land and ocean carbon sink response to scenarios with CO <sub>2</sub> emissions gradually declining during the 21st century. As CDR and other mitigation activities are ramped up, CO <sub>2</sub> emissions in these scenarios reach net zero and, as removals exceed emissions, become net negative. Studies exploring the carbon sink response to such scenarios (e.g., RCP2.6, SSP1-2.6) show that, when net CO <sub>2</sub> emissions are positive but start to decline, uptake of CO <sub>2</sub> by the land and ocean begins to weaken (compare land and ocean CO <sub>2</sub> fluxes in panels a and b of Figure 5.33; [[#Tokarska--2015|Tokarska and Zickfeld, 2015]] ; [[#Jones--2016b|Jones et al., 2016b]] ). During the first decades after CO <sub>2</sub> emissions become net negative, both the ocean and land carbon sinks continue to take up CO <sub>2</sub> , albeit at a lower rate. For the land carbon sink, the sink-to-source transition occurs decades to a century after CO <sub>2</sub> emissions become net negative (Figure 5.33c). The ocean remains a sink of CO <sub>2</sub> for centuries after emissions become net negative (Figure 5.33c–e; [[#5.4.9|Section 5.4.9]] ; Figure 5.30). Whether the transition to source occurs at all, the timing of the transition and the magnitude of the CO <sub>2</sub> source are determined by the magnitude of the removal and the rate and amount of net CO <sub>2</sub> emissions prior to emissions becoming net negative ( ''medium confidence'' ) ( [[#Tokarska--2015|Tokarska and Zickfeld, 2015]] ; [[#Jones--2016b|Jones et al., 2016b]] ). For scenarios with large amounts of CO <sub>2</sub> removal, such as SSP5-3.4-overshoot, the land source is larger than for SSP1-2.6 and the ocean also turns into a source ( [[#5.4.10|Section 5.4.10]] , Figure 5.30). While the qualitative response to scenarios with net-negative emissions is largely robust across models, the timing of the sink-to-source transition and the magnitude of the CO <sub>2</sub> source vary between models, particularly for the land sink. Due to ''low agreement'' between models, there is ''low confidence'' in the timing of the sink-to-source transition and the magnitude of the CO <sub>2</sub> source in scenarios with net-negative CO <sub>2</sub> emissions.

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[[File:cc8957d18d88db9d40ad241c093f7844 IPCC_AR6_WGI_Figure_5_33.png]]

'''Figure 5.33 |''' '''Carbon sink response in a scenario with net carbon dioxide (CO''' <sub>2</sub> ''') removal from the atmosphere.''' Shown are CO <sub>2</sub> flux components from concentration-driven Earth system model (ESM) simulations during different emissions stages of SSP1-2.6 and its long-term extension: '''(a)''' Large net positive CO <sub>2</sub> emissions; '''(b)''' small net positive CO <sub>2</sub> emissions; '''(c)''' , '''(d)''' net negative CO <sub>2</sub> emissions; '''(e)''' net zero CO <sub>2</sub> emissions. Positive flux components act to raise the atmospheric CO <sub>2</sub> concentration, whereas negative components act to lower the CO <sub>2</sub> concentration. Net CO <sub>2</sub> emissions, land and ocean CO <sub>2</sub> fluxes represent the multi-model mean and standard deviation (error bar) of four ESMs (CanESM5, UKESM1, CESM2-WACCM, IPSL-CM6a-LR) and one Earth system model of intermediate complexity (UVic ESCM; [[#Mengis--2020|Mengis et al., 2020]] ). Net CO <sub>2</sub> emissions are calculated from concentration-driven ESM simulations as the residual from the rate of increase in atmospheric CO <sub>2</sub> and land and ocean CO <sub>2</sub> fluxes. Fluxes are accumulated over each 50-year period and converted to concentration units (ppm). Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

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<span id="removal-effectiveness-of-cdr"></span>
===== 5.6.2.1.3 Removal effectiveness of CDR =====

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It is well understood that land and ocean carbon fluxes are sensitive to the level of atmospheric CO <sub>2</sub> and climate change and differ under varied future scenarios ( [[#5.4|Section 5.4]] ). It is therefore important to establish to what extent the removal effectiveness of CDR – here defined as the fraction of total CO <sub>2</sub> removed that remains out of the atmosphere – is dependent on the scenario in which CDR is applied. Different metrics have been proposed to quantify the removal effectiveness of CDR ( [[#Tokarska--2015|Tokarska and Zickfeld, 2015]] ; [[#Jones--2016b|Jones et al., 2016b]] ; [[#Zickfeld--2016|Zickfeld et al., 2016]] ). One is the airborne fraction (AF) of cumulative CO <sub>2</sub> emissions, defined in the same way as for positive emissions (i.e., as the fraction of total CO <sub>2</sub> emissions remaining in the atmosphere), with its use extended to periods of declining and net negative CO <sub>2</sub> emissions. This metric, however, has not proven to be useful to quantify the removal effectiveness of CDR in simulations where CDR is applied from a trajectory of increasing atmospheric CO <sub>2</sub> concentration. This is because it measures the carbon cycle response to CDR as well as to the prior atmospheric CO <sub>2</sub> trajectory ( [[#Tokarska--2015|Tokarska and Zickfeld, 2015]] ; [[#Jones--2016b|Jones et al., 2016b]] ). A more useful metric is the perturbation airborne fraction (PAF; [[#Jones--2016b|Jones et al., 2016b]] ), which measures the AF of the perturbation (in this case the CO <sub>2</sub> removal) relative to a reference scenario ( [[#Tokarska--2015|Tokarska and Zickfeld, 2015]] ; [[#Jones--2016b|Jones et al., 2016b]] ). The advantage of this metric is that it isolates the response to a CO <sub>2</sub> removal from the response to atmospheric CO <sub>2</sub> prior to when the removal is applied. A disadvantage is that the PAF cannot be calculated from a single model simulation, but instead requires a reference simulation to evaluate the effect of the CO <sub>2</sub> removal. When CDR is applied from an equilibrium state, the PAF and AF are equivalent measures.

In scenario simulations and idealized simulations with instantaneous CO <sub>2</sub> removals applied from an equilibrium state, the removal effectiveness of CDR is found to be slightly dependent on the rate and amount of CDR ( [[#Tokarska--2015|Tokarska and Zickfeld, 2015]] ; [[#Jones--2016b|Jones et al., 2016b]] ; [[#Zickfeld--2021|Zickfeld et al., 2021]] ), and to be strongly dependent on the emissions scenario from which CDR is applied ( [[#Jones--2016b|Jones et al., 2016b]] ; [[#Zickfeld--2021|Zickfeld et al., 2021]] ). The fraction of CO <sub>2</sub> removed remaining out of the atmosphere decreases slightly for larger removals and decreases strongly when CDR is applied from a lower background atmospheric CO <sub>2</sub> concentration (Figure 5.34), due to state dependencies and climate–carbon cycle feedbacks that lead to a stronger overall response to CO <sub>2</sub> removal ( [[#Zickfeld--2021|Zickfeld et al., 2021]] ). Based on the ''high agreement'' between studies, we assess with ''medium confidence'' that the removal effectiveness of CDR is only slightly dependent on the rate and magnitude of removal and is smaller at lower background atmospheric CO <sub>2</sub> concentrations. Simulations with Earth system models of intermediate complexity (EMIC) with instantaneous CO <sub>2</sub> removal from different equilibrium initial states suggest that the smaller removal effectiveness of CDR at lower background CO <sub>2</sub> levels results in greater cooling per unit CO <sub>2</sub> removed ( [[#Zickfeld--2021|Zickfeld et al., 2021]] ). However, there is ''low confidence'' in the robustness of this result as climate sensitivity has been shown to exhibit opposite state dependence in EMICs and ESMs ( [[IPCC:Wg1:Chapter:Chapter-7#7.4.3.1|Section 7.4.3.1]] ).

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[[File:27eab2cc63805dfdc8394b5b275340e4 IPCC_AR6_WGI_Figure_5_34.png]]

'''Figure 5.34 |''' '''Removal effectiveness of carbon dioxide removal (CDR).''' '''(a)''' Fraction of carbon dioxide (CO <sub>2</sub> ) remaining out of the atmosphere for idealized model simulations with CDR applied instantly (pulse removals) from climate states in equilibrium with different atmospheric CO <sub>2</sub> concentration levels (one to four times the pre-industrial atmospheric CO <sub>2</sub> concentration; shown on the horizontal axis). The fraction is calculated 100 years after pulse removal. The black triangle and error bar indicate the multi-model mean and standard deviation for the seven Earth system models shown in Figure 5.32 forced with a 100 PgC pulse removal. Other symbols illustrate results with the UVic ESCM model of intermediate complexity for different magnitudes of pulse removals (triangles: –100 PgC; circles: –500 PgC; squares: –1000 PgC). Data for the UVic ESCM is from [[#Zickfeld--2021|Zickfeld et al. (2021)]] . '''(b)''' Perturbation airborne fraction (see text for definition) for model simulations where CDR is applied from four Representative Concentration Pathways (RCPs) (shown on the horizontal axis in terms of their cumulative CO <sub>2</sub> emissions during 2020–2099). Symbols indicate results for four CDR scenarios, which differ in terms of the magnitude and rate of CDR (see [[#Jones--2016b|Jones et al. (2016b)]] for details). Results are based on simulations with the Hadley Centre Simple Climate-Carbon Model and are shown for the year 2100. Data from [[#Jones--2016b|Jones et al. (2016b)]] . Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

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<span id="symmetry-of-carbon-cycle-response-to-positive-and-negative-co-2-emissions"></span>
===== 5.6.2.1.4 Symmetry of carbon cycle response to positive and negative CO 2 emissions =====

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It is commonly assumed that the climate–carbon cycle response to a negative CO <sub>2</sub> emission (i.e., removal from the atmosphere) is equal in magnitude and opposite in sign to the response to a positive CO <sub>2</sub> emission of equal magnitude – that is, symmetric. If the response were symmetric, a positive CO <sub>2</sub> emission could be offset by a negative emission of equal magnitude. This subsection assesses the symmetry in the coupled climate–carbon cycle response in model simulations with positive and negative CO <sub>2</sub> emission pulses applied from a pre-industrial climate state. Simulations with seven CMIP6 ESMs and the UVic Earth System Climate Model (ESCM) of intermediate complexity suggest that the carbon cycle response is asymmetric for pulse emissions/removals of ±100 PgC (Figure 5.35). For all models, the fraction of CO <sub>2</sub> remaining in the atmosphere after an emission is larger than the fraction of CO <sub>2</sub> remaining out of the atmosphere after a removal (by 4 ± 3%; mean ± standard deviation). In other words, an emission of CO <sub>2</sub> into the atmosphere is more effective at raising atmospheric CO <sub>2</sub> than an equivalent CO <sub>2</sub> removal is at lowering it. Sensitivity experiments with the UVic ESCM suggest that the asymmetry increases for larger amounts of emissions/removals and is insensitive to the background atmospheric CO <sub>2</sub> concentration from which the emissions/removals are applied (Figure 5.35). This asymmetry in the atmospheric CO <sub>2</sub> response originates from asymmetries in the land and ocean carbon fluxes due to non-linearities in the carbon cycle response to CO <sub>2</sub> and temperature ( [[#5.4|Section 5.4]] ) ( [[#Zickfeld--2021|Zickfeld et al., 2021]] ). Given ''medium evidence'' and ''high agreement'' , there is ''medium confidence'' in the sign of the asymmetry of the carbon cycle response to positive and negative CO <sub>2</sub> emissions. The sign of the symmetry of the temperature response differs between models, with three out of seven examined ESMs showing a smaller temperature response to a 100 PgC emission than to an equivalent CO <sub>2</sub> removal. Therefore, there is ''low confidence'' in the sign of the asymmetry of the temperature response to positive and negative CO <sub>2</sub> emissions.

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[[File:0d06ac2654ccbbcf807e96c9a11b2902 IPCC_AR6_WGI_Figure_5_35.png]]

'''Figure 5.35 |''' '''Asymmetry in the atmospheric carbon dioxide (CO''' <sub>2</sub> ''') response to CO''' <sub>2</sub> '''emissions and removals.''' Shown are the fractions of total CO <sub>2</sub> emissions remaining in the atmosphere (right-hand side) and CO <sub>2</sub> removals remaining out of the atmosphere (left-hand side) 80–100 after a pulse emission/removal. Triangles and green circles denote results for seven Earth system models (ESMs) and the UVic ESCM model of intermediate complexity forced with ±100 PgC pulses applied from a pre-industrial state (1 × CO <sub>2</sub> ) (Carbon Dioxide Removal Model Intercomparison Project (CDRMIP) experiment CDR-pi-pulse; [[#Keller--2018b|Keller et al., 2018b]] ). Yellow circles and diamonds indicate UVic ESCM results for CO <sub>2</sub> emissions/removals applied at 1.5 times (1.5 × CO <sub>2</sub> ) and 2 times (2 × CO <sub>2</sub> ) the pre-industrial CO <sub>2</sub> concentration, respectively. Pulses applied from a 2 × CO <sub>2</sub> state span the magnitude ±100 PgC to ±500 PgC. UVic ESCM data is from [[#Zickfeld--2021|Zickfeld et al. (2021)]] . Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

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

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During the industrial era, CO <sub>2</sub> emitted by the combustion of fossil fuels and land-use change has been redistributed between atmosphere, land, and ocean carbon reservoirs due to carbon cycle processes (Box 5.3, Figure 1b and Figure 5.13). Over the past decade (2010–2019), 46% of the emitted CO <sub>2</sub> remained in the atmosphere, 23% was taken up by the ocean, and 31% by the terrestrial biosphere ( [[#5.2.1.5|Section 5.2.1.5]] ). When carbon dioxide removal (CDR) is applied during periods in which human activities are net CO <sub>2</sub> sources to the atmosphere, and the amount of emissions removed by CDR is smaller than the net source (net positive CO <sub>2</sub> emissions), CDR acts to reduce the net emissions (Box 5.3 Figure 1c). In this scenario, part of the CO <sub>2</sub> emissions in the atmosphere are removed by the land and ocean sinks, as has been the case historically.

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[[File:b0f01dff95c42721b9c68bcb0a161c4c IPCC_AR6_WGI_Box_5_3_Figure_1.png]]

'''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).

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).

<div id="5.6.2.2" class="h3-container"></div>

<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 ====

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The AR5 WGI (Chapter 6) discussed the CDR methods, their implications and unintended side effects on carbon cycle and climate, including their time scales and potentials. Since then, three IPCC special reports (SR) have been published. First, SR1.5 ( [[IPCC:Wg1:Chapter:Chapter-4|Chapter 4]] ( [[#IPCC--2018|IPCC, 2018]] ) assessed the potentials and current understanding, including the side effects, of bioenergy with carbon capture and storage (BECCS), afforestation/reforestation, soil carbon sequestration, biochar, enhanced weathering, ocean alkalinization, direct air carbon capture with storage (DACCS) and ocean fertilization. Second, SRCCL ( [[IPCC:Wg1:Chapter:Chapter-6|Chapter 6]] ( [[#IPCC--2019a|IPCC, 2019a]] ) assessed the potentials, co-benefits and trade-offs of land-based mitigation options. It assessed with ''high confidence'' that land-based CDR options do not sequester carbon indefinitely, except for peatland restoration. Multiple co-benefits were identified in the deployment of CDR options, many of them with a potential to make positive contributions to sustainable development, enhancement of ecosystem functions and services and other societal goals. However, their potential was concluded to be context specific, and limits were identified in their contribution to global mitigation, such as competition for land. The third report, the Special Report on Ocean and the Cryosphere in a Changing Climate (SROCC) [https://www.ipcc.ch/report/ar6/wg1/chapter/chapter-5 Chapter 5] ( [[#IPCC--2019b|IPCC, 2019b]] ), assessed the potential of marine options for climate change mitigation. It concluded that the feasibility of open ocean fertilization and alkalinization approaches were negligible, due to their inconclusive influence on ocean carbon storage on long time scales, due to the unintended side effects on marine ecosystems, and the associated governance challenges. The assessment of blue carbon ecosystems concluded that they could contribute only minimally to atmospheric CO <sub>2</sub> reduction globally, but emphasized that the benefits of protecting and restoring coastal blue carbon extend beyond climate change mitigation (SROCC ( [[#5.5.1|Section 5.5.1]] 2).

<div id="5.6.2.2.1" class="h4-container"></div>

<span id="land-based-biological-cdr-methods"></span>
===== 5.6.2.2.1 Land-based biological CDR methods =====

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Biological CDR methods, introduced in Table 5.9, seek to increase carbon storage on land by enhancing net primary productivity and/or reducing CO <sub>2</sub> sources to the atmosphere.

Forest-based methods include afforestation, reforestation, and forest management (Table 5.9). Building on previous work that emphasized the global potentials of various options, more recent advances have focused on the limits of those global potentials in light of ecological and climate risks that can threaten the long-term permanence of carbon stocks ( [[#Boysen--2017b|Boysen et al., 2017b]] ; [[#Anderegg--2020|Anderegg et al., 2020]] ). Some of those risks arise from droughts, fires, insect outbreaks, diseases, erosion, and other disturbances ( [[#Thompson--2009|Thompson et al., 2009]] ).

Sustainable forest management can help to manage some of these vulnerabilities, while in some cases it can increase and maintain forest sinks through harvest, transfer of carbon to wood products and their use to store carbon and substitute emissions-intensive construction materials ( [[#Churkina--2020|Churkina et al., 2020]] ). Forest genomics techniques can increase the success of both reforestation and conservation initiatives, accelerating breeding for tree health and productivity ( [[#Isabel--2020|Isabel et al., 2020]] ).

In response to increasing risks to permanence of carbon stocks of some types of afforestation practices and the competition for land, there has been an increasing recognition that secondary forest regrowth and restoration of degraded forests and non-forest ecosystems can play a large role in carbon sequestration ( ''high confidence'' ). The rational for this focus builds on their high carbon stocks and rates of sequestration ( [[#Griscom--2017|Griscom et al., 2017]] ; [[#Lewis--2019|Lewis et al., 2019]] ; [[#Maxwell--2019|Maxwell et al., 2019]] ; [[#Pugh--2019|Pugh et al., 2019]] ), high resilience to disturbances ( [[#Dymond--2014|Dymond et al., 2014]] ; [[#Messier--2019|Messier et al., 2019]] ), and additional benefits such as enhanced biodiversity ( [[#Strassburg--2020|Strassburg et al., 2020]] ).

The global sequestration potential of forestation varies substantially depending on the scenario-assumptions of available land and of background climate (AR6 WGIII, [[IPCC:Wg1:Chapter:Chapter-7#7.5|Section 7.5]] ). Afforestation of native grasslands, savannas, and open-canopy woodlands leads to the undesirable loss of unique natural ecosystems with rich biodiversity, carbon storage and other ecosystem services ( [[#Veldman--2015|Veldman et al., 2015]] ; [[#IPBES--2018|IPBES, 2018]] ). Comprehensive approaches to assess the effectiveness of land-based carbon removal options need to be based on the whole carbon cycle, covering both carbon stocks and flows, and establishing the links between human activities and their impacts on the biosphere and atmosphere ( [[#Keith--2021|Keith et al., 2021]] ).

A range of mechanisms could enhance CO <sub>2</sub> sequestration of forest-based methods under future scenarios, including CO <sub>2</sub> fertilization, soil carbon enrichment due to enhanced litter input, or the northward shift of the tree line in future climate projection ( [[#Bathiany--2010|Bathiany et al., 2010]] ; [[#Sonntag--2016|Sonntag et al., 2016]] ; [[#Boysen--2017b|Boysen et al., 2017b]] ; [[#Harper--2018|Harper et al., 2018]] ). There is ''low'' ''confidence'' in the net direction of feedbacks of afforestation on global mean temperature. The feedbacks are highly region dependent. For instance, afforestation at high latitudes would decrease albedo and increase local warming, while at low latitudes, the cooling effect of enhanced evapotranspiration could exceed the warming effect due to albedo decrease ( [[#Pearson--2013|Pearson et al., 2013]] ; W. [[#Zhang--2013|]] [[#Zhang--2013|Zhang et al., 2013]] ; [[#Jia--2019|Jia et al., 2019]] , SRCCL, Section 2.6.1). Both afforestation and reforestation affect the hydrological cycle through increased volatile organic compound (VOC) emissions and cloud albedo ( [[#Teuling--2017|Teuling et al., 2017]] ; [[#Kalliokoski--2020|Kalliokoski et al., 2020]] ), enhanced precipitation ( [[#Ellison--2017|Ellison et al., 2017]] ) and increased transpiration, with potential effects on runoff and, especially in dry regions, on water supply (Figure 5.36 and Cross-Chapter Box 5.1; [[#Farley--2005|Farley et al., 2005]] ; [[#Smith--2016|Smith et al., 2016]] ; [[#Krause--2017|Krause et al., 2017]] ; [[#Teuling--2019|Teuling et al., 2019]] ). Forest-based methods can either raise or lower N <sub>2</sub> O emissions, depending on tree species, previous land use, soil type and climatic factors ( ''low confidence'' ) (Figure 5.36 and Supplementary Materials, Table 5.SM.4; [[#Benanti--2014|Benanti et al., 2014]] ; [[#Chen--2019|Chen et al., 2019]] ; [[#McDaniel--2019|McDaniel et al., 2019]] ). Afforestation will decrease biodiversity if native species are replaced by monocultures ( ''high'' ''confidence'' ), while there is ''medium confidence'' that biodiversity is improved when forests are introduced into land areas with degraded soils or intensive monocultures, or where native species are re-introduced into managed land (Figure 5.36, Supplementary Materials Table 5.SM.4; [[#Hua--2016|Hua et al., 2016]] ; [[#Williamson--2016|Williamson and Bodle, 2016]] ; [[#Smith--2018|P. Smith et al., 2018]] ; [[#Holl--2020|Holl and Brancalion, 2020]] ).

Soil carbon losses from human agriculture accounted for about 116 PgC in the last 12,000 years ( [[#5.2.1.2|Section 5.2.1.2]] ; [[#Sanderman--2017|Sanderman et al., 2017]] ). With best management practices, two-thirds of these losses may be recoverable, setting a theoretical maximum of 77 PgC that can be sequestered in soils. Methods to increase soil carbon content may be applied to the restoration of marginal or degraded land ( [[#Paustian--2016|Paustian et al., 2016]] ; [[#Smith--2016|Smith, 2016]] ), but may also be used in traditional agricultural lands. A simple practice is to increase the input of carbon to the soil by selecting appropriate varieties or species with greater root mass ( [[#Kell--2011|Kell, 2011]] ) or higher yields and net primary production (NPP) ( [[#Burney--2010|Burney et al., 2010]] ). In addition, improved agricultural practices also increase soil carbon content. These include using crop rotation cycles, increasing the amount of crop residues, using crop cover to prevent periods of bare soil ( [[#Poeplau--2015|Poeplau and Don, 2015]] ; [[#Griscom--2017|Griscom et al., 2017]] ), optimizing grazing ( [[#Henderson--2015|Henderson et al., 2015]] ) and residue management ( [[#Wilhelm--2004|Wilhelm et al., 2004]] ), using irrigation ( [[#Campos--2020|Campos et al., 2020]] ), employment of low-tillage or no-tillage (W. [[#Sun--2020|]] [[#Sun--2020|Sun et al., 2020]] ), agroforestry, cropland nutrient recycling, and avoiding grassland conversion ( [[#Paustian--2016|Paustian et al., 2016]] ; [[#Fargione--2018|Fargione et al., 2018]] ). With ''medium confidence,'' methods that seek soil carbon sequestration will diminish nitrous oxide (N <sub>2</sub> O) emissions and nutrient leaching, and improve soil fertility and biological activity (Figure 5.36; [[#Tonitto--2006|Tonitto et al., 2006]] ; [[#Fornara--2011|Fornara et al., 2011]] ; [[#Paustian--2016|Paustian et al., 2016]] ; [[#Smith--2016|Smith et al., 2016]] ; SRCCL, Section 2.6.1.3, [[#IPCC--2019a|IPCC, 2019a]] ). However, if improved soil carbon sequestration practices involve higher fertilization rates, N <sub>2</sub> O emissions would increase ( [[#Gu--2017|Gu et al., 2017]] ). Some soil carbon sequestration methods, such as cover crops and crop diversity, can increase biodiversity ( ''medium confidence'' ) ( [[#Paustian--2016|Paustian et al., 2016]] ; [[#Smith--2018|P. Smith et al., 2018]] ).

Biochar is produced by burning biomass at high temperatures under anoxic conditions (pyrolysis) and, when added to soils, can increase soil carbon stocks and fertility for decades to centuries ( [[#Woolf--2010|Woolf et al., 2010]] ; [[#Lehmann--2015|Lehmann et al., 2015]] ). Biochar application improves many soil qualities and increases crop yield ( ''medium confidence'' ) ( [[#Ye--2020|Ye et al., 2020]] ; SRCCL, Chapter 4.9.5), particularly in already degraded or weathered soils ( [[#Woolf--2010|Woolf et al., 2010]] ; [[#Lorenz--2014|Lorenz and Lal, 2014]] ; [[#Jeffery--2016|Jeffery et al., 2016]] ), increases soil water holding capacity ( ''medium'' ''confidence'' ) ( [[#Karhu--2011|Karhu et al., 2011]] ; [[#Liu--2016|Liu et al., 2016]] ; [[#Fischer--2019|]] [[#Fischer--2019|B.M.C. Fischer et al., 2019]] ; [[#Verheijen--2019|Verheijen et al., 2019]] ) and evapotranspiration ( ''low confidence'' )( [[#Fischer--2019|]] [[#Fischer--2019|B.M.C. Fischer et al., 2019]] ). The use of biochar reduces nutrient losses ( ''low confidence'' ) ( [[#Woolf--2010|Woolf et al., 2010]] ), enhances fertilizer nitrogen use efficiency and improves the bioavailability of phosphorus (Figure 5.36; [[#Clough--2013|Clough et al., 2013]] ; [[#Shen--2016|Shen et al., 2016]] ; [[#Liu--2017|Z. Liu et al., 2017]] ). Biochar addition may decrease methane (CH <sub>4</sub> ) emissions in inundated and acid soils such as rice fields ( ''low confidence'' )( [[#Jeffery--2016|Jeffery et al., 2016]] ; [[#Huang--2019|Huang et al., 2019]] ; [[#Wang--2019|]] [[#Wang--2019|Wang et al., 2019]] ; [[#Yang--2019|Yang et al., 2019]] ). In non-inundated, neutral soils, CH <sub>4</sub> uptake from the atmosphere is suppressed after biochar application ( ''low confidence'' ) ( [[#Jeffery--2016|Jeffery et al., 2016]] ), and soil N <sub>2</sub> O emissions decline ( ''medium confidence'' ) ( [[#Cayuela--2014|Cayuela et al., 2014]] ; [[#Kammann--2017|Kammann et al., 2017]] ). The potential risks of introducing harmful contaminants into the soil environment are not well understood ( [[#Lorenz--2014|Lorenz and Lal, 2014]] ). With ''low confidence'' , application of biochar can have co-benefits for soil microbial biodiversity ( [[#Smith--2018|P. Smith et al., 2018]] ), while the potential trade-offs for biodiversity are due to land requirements ( [[#Tisserant--2019|Tisserant and Cherubini, 2019]] ).

Peatlands are less extensive than forests, croplands and grazing lands, yet per unit area, they hold high carbon stocks ( [[#Griscom--2017|Griscom et al., 2017]] ). Peatland restoration relies on back-conversion or building of high-carbon-density soils through flooding – that is, rewetting ( [[#Leifeld--2019|Leifeld et al., 2019]] ). High water level and anoxic conditions are prerequisites for restoring by returning drained and/or degraded peatlands back to their natural state as CO <sub>2</sub> sinks, but restoration also results in enhanced CH <sub>4</sub> emissions which are similar to or higher than the pre-drainage fluxes ( ''high'' ''confidence'' ) ( [[#Koskinen--2016|Koskinen et al., 2016]] ; [[#Wilson--2016a|Wilson et al., 2016a]] ; [[#Hemes--2019|Hemes et al., 2019]] ; [[#Renou-Wilson--2019|Renou-Wilson et al., 2019]] ; [[#Holl--2020|Holl et al., 2020]] ). In a multi-decadal time frame, the reduction in CO <sub>2</sub> emissions from rewetting more than compensates for the initial increase in radiative forcing due to enhanced CH <sub>4</sub> emissions ( [[#Günther--2020|Günther et al., 2020]] ). Rewetting drained peatlands will decrease N <sub>2</sub> O emissions ( ''medium confidence'' ) ( [[#Wilson--2016b|Wilson et al., 2016b]] ; H. [[#Liu--2020|]] [[#Liu--2020|]] [[#Liu--2020|Liu et al., 2020]] ; [[#Tiemeyer--2020|Tiemeyer et al., 2020]] ). Restored wetlands and peatlands act as buffer zones that provide infiltration and nutrient retention and offer protection to water quality ( [[#Daneshvar--2017|Daneshvar et al., 2017]] ; [[#Lundin--2017|Lundin et al., 2017]] ), particularly in nutrient-loaded agricultural catchments. Peatland restoration can also recover much of the original biodiversity ( ''medium confidence'' ) ( [[#Meli--2014|Meli et al., 2014]] ; [[#Smith--2018|P. Smith et al., 2018]] ).

The concept of BECCS rests on the premise that bioenergy production is carbon neutral – that is, as much CO <sub>2</sub> is sequestered when growing biomass as feedstock as is released by its combustion. If these emissions are also captured and stored, the net effect is removal of CO <sub>2</sub> from the atmosphere ( [[#Fuss--2018|Fuss et al., 2018]] ). Sequestration potentials from BECCS depend strongly on the feedstock, climate, and management practices ( [[#Beringer--2011|Beringer et al., 2011]] ; [[#Kato--2014|Kato and Yamagata, 2014]] ; [[#Heck--2016|Heck et al., 2016]] ; [[#Smith--2016|Smith et al., 2016]] ; [[#Krause--2017|Krause et al., 2017]] ). If woody bioenergy plants replace marginal land, net carbon uptake increases, enriching soil carbon (Don et al., 2012; [[#Heck--2016|Heck et al., 2016]] ; [[#Boysen--2017a|Boysen et al., 2017a]] , b). However, replacing carbon-rich ecosystems with herbaceous bioenergy plants could deplete soil-carbon stocks and reduce the additional sink capacity of standing forests ( [[#Don--2012|Don et al., 2012]] ; [[#Harper--2018|Harper et al., 2018]] ). Furthermore, wood-based BECCS may not be carbon negative in the first decades, initially emitting more CO <sub>2</sub> than sequestering ( [[#Sterman--2018|Sterman et al., 2018]] ). BECCS has several trade-offs to deal with, including possible threats to water supply and soil nutrient deficiencies ( ''medium confidence'' ) (SRCCL Chapters 2 and 6, and Cross-Chapter Box 5.1; [[#Smith--2016|Smith et al., 2016]] ; [[#Krause--2017|Krause et al., 2017]] ; [[#de%20Coninck--2018|de Coninck et al., 2018]] ; [[#Heck--2018|Heck et al., 2018]] ; [[#Roy--2018|Roy et al., 2018]] ). Deployment of BECCS at the scales envisioned by many 1.5°C–2.0°C mitigation scenarios could threaten biodiversity and require large land areas, competing with afforestation, reforestation and food security ( [[#Anderson--2016|Anderson and Peters, 2016]] ; [[#Smith--2018|P. Smith et al., 2018]] ). Additional risks and side effects are related to geologic carbon storage ( [[#Fuss--2018|Fuss et al., 2018]] ; see also [[#5.6.2.2.4|Section 5.6.2.2.4]] ).

In conclusion, land-based CDR methods that rely on enhanced net biological uptake and storage of carbon, have a wide range of biogeochemical and biophysical side effects. These side effects can (directly or indirectly) strengthen or weaken the climate change mitigation effect of a given method, or affect water quality and quantity, food supply and biodiversity (Figure 5.36). With the exception of weakened ocean carbon sequestration, there is ''low confidence'' in the Earth system feedbacks of these methods. Most methods are associated with a range of biogeochemical and biophysical side effects and co-benefits and trade-offs, but these are often highly dependent on local context, management regime, prior land use, and scale ( ''high confidence'' ). Highest co-benefits are obtained with methods that seek to restore natural ecosystems and improve soil carbon sequestration (Figure 5.36) while highest trade-off possibilities (symmetry with the highest co-benefits) occur for reforestation or afforestation with monocultures and BECCS, again with strong dependence on scale and context ( ''medi'' ''um confidence'' ).

<div id="5.6.2.2.2" class="h4-container"></div>

<span id="ocean-based-biological-cdr-methods"></span>
===== 5.6.2.2.2 Ocean-based biological CDR methods =====

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Both ocean biological and physical processes drive the CO <sub>2</sub> exchange between the ocean and atmosphere. However, the ocean physical processes that remove CO <sub>2</sub> from the atmosphere, such as large-scale circulation, cannot be feasibly altered, so ocean CDR methods focus on increasing the productivity of ocean ecosystems, and subsequent sequestration of carbon ( [[#GESAMP--2019|GESAMP, 2019]] ). There has been no change to the assessment of SROCC (SROCC [[#5.5.1|Section 5.5.1]] ): there is ''low confidence'' that nutrient addition to the open ocean, either through artificial ocean upwelling or iron fertilization, could contribute to climate change mitigation, due to its inconclusive effect on carbon sequestration and risks of adverse side effects on marine ecosystems (Figure 5.36, Table 5.9; Supplementary Materials Text 5.SM.3 and Table 5.SM.4; AR6 WGIII Chapter 12; [[#Gattuso--2018|Gattuso et al., 2018]] ; [[#Boyd--2019|Boyd and Vivian, 2019]] ; [[#Feng--2020|Feng et al., 2020]] ). In addition, ocean fertilization is currently prohibited by the LondonProtocol ( [[#Dixon--2014|Dixon et al., 2014]] ; [[#GESAMP--2019|GESAMP, 2019]] ).

Restoration of vegetated coastal ecosystems (sometimes referred to as ‘blue carbon’ – see Glossary) refers to the potential for increasing carbon sequestration by plant growth and burial of organic carbon in the soil of coastal wetlands (including salt marshes and mangroves) and seagrass ecosystems. Wider usage of the term blue carbon occurs in the literature, for example, including seaweeds (macroalgae), shelf sea sediments and open ocean carbon exchanges. However, such systems are less amenable to management, with many uncertainties relating to the permanence of their carbon stores ( [[#Windham-Myers--2018|Windham-Myers et al., 2018]] ; [[#Lovelock--2019|Lovelock and Duarte, 2019]] ; SROCC, [[#5.5.1.1|Section 5.5.1.1]] ).

Coastal wetlands and seagrass meadows store significant amounts of carbon and are among the most productive ecosystems per unit area ( [[#Griscom--2017|Griscom et al., 2017]] , 2020; [[#Ortega--2019|Ortega et al., 2019]] ; [[#Serrano--2019|Serrano et al., 2019]] ). These rates could be reduced in the future, since these habitats are vulnerable to changing conditions, such as temperature, salinity, sediment supply, storm severity and continued coastal development ( [[#Bindoff--2019|Bindoff et al., 2019]] ; [[#NASEM--2019|NASEM, 2019]] ). These ecosystems are under threat from anthropogenic conversion and degradation and are being lost at rates between 0.7% and 7% per annum with consequent CO <sub>2</sub> emissions (e.g., [[#Atwood--2017|Atwood et al., 2017]] ; [[#Howard--2017|Howard et al., 2017]] ; [[#Hamilton--2018|Hamilton and Friess, 2018]] ; [[#Sasmito--2019|Sasmito et al., 2019]] ). Although sea level rise might lead to greater carbon sequestration in coastal wetlands ( [[#Rogers--2019|Rogers et al., 2019]] ), there is ''high confidence'' that the frequency and intensity of marine heatwaves will increase (Cross-Chapter Box 9.1; [[#Frölicher--2018|Frölicher and Laufkötter, 2018]] ; [[#Laufkötter--2020|Laufkötter et al., 2020]] ),which poses a more immediate threat to the integrity of coastal carbon stocks ( [[#Smale--2019|Smale et al., 2019]] ). Blue carbon restoration seeks to increase the rate of carbon sequestration, although restoration may be challenging, because of ongoing use of coastal land for human settlement, conversion to agriculture and aquaculture, shoreline hardening and port development.

Biogeochemical factors affecting reliable quantification of the climatic benefits of coastal vegetation include the variable production of CH <sub>4</sub> and N <sub>2</sub> O by such ecosystems ( [[#Adams--2012|Adams et al., 2012]] ; [[#Keller--2018|Keller, 2018]] ; [[#Rosentreter--2018|Rosentreter et al., 2018]] ), uncertainties regarding the provenance of the carbon that they accumulate ( [[#Macreadie--2019|Macreadie et al., 2019]] ), and the release of CO <sub>2</sub> by biogenic carbonate formation in seagrass ecosystems ( [[#Kennedy--2018|Kennedy et al., 2018]] ). While coastal habitat restoration potentially provides significant mitigation of national emissions for some countries ( [[#Taillardat--2018|Taillardat et al., 2018]] ; [[#Serrano--2019|Serrano et al., 2019]] ), the global sequestration potential of blue carbon approaches is &lt;0.02 PgC yr <sup>–1</sup> ( ''medium confidence'' ) (Figure 5.36; SROCC, [[#5.5.1.2|Section 5.5.1.2]] ; [[#Griscom--2017|Griscom et al., 2017]] ; [[#Gattuso--2018|Gattuso et al., 2018]] ; [[#GESAMP--2019|GESAMP, 2019]] ; [[#NASEM--2019|NASEM, 2019]] ).

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<span id="geochemical-cdr-methods"></span>
===== 5.6.2.2.3 Geochemical CDR methods =====

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Enhanced weathering (EW) is based on naturally occurring weathering processes of silicate and carbonate rocks, removing CO <sub>2</sub> from the atmosphere. Weathering is accelerated by spreading ground rocks on soils, coasts or oceans. EW increases the alkalinity and pH of natural waters, helps dampen ocean acidification and increases ocean carbon uptake ( [[#Beerling--2018|Beerling et al., 2018]] ). The dissolution of minerals stimulates biological productivity of croplands ( [[#Hartmann--2013|Hartmann et al., 2013]] ; [[#Beerling--2018|Beerling et al., 2018]] ), but can also liberate toxic trace metals (such as nickel, chromium, copper) into soil or water bodies ( [[#Keller--2018a|Keller et al., 2018a]] ; [[#Strefler--2018|Strefler et al., 2018]] ). EW can also contribute to freshwater salinization as a result of increased salt inputs and cation exchange in watersheds, and so adversely affecting drinking water quality ( ''low confidence'' ) ( [[#Kaushal--2018|Kaushal et al., 2018]] ). With a ''medium confidence'' , amendment of soils with minerals will have lower N <sub>2</sub> O emissions ( [[#Kantola--2017|Kantola et al., 2017]] ; [[#Blanc-Betes--2020|Blanc-Betes et al., 2020]] ) but will not have a marked effect on evapotranspiration or albedo ( [[#Fuss--2018|Fuss et al., 2018]] ; [[#de%20Oliveira%20Garcia--2020|de Oliveira Garcia et al., 2020]] ). The mining of minerals can cause adverse impacts on biodiversity, however, the use of waste materials such as concrete demolition or steel slags for EW can reduce the need for mining ( [[#Renforth--2019|Renforth, 2019]] ). The spreading of minerals on land has a neutral impact on biodiversity ( [[#Smith--2018|P. Smith et al., 2018]] ).

Ocean alkalinization, via the deposition of alkaline minerals (e.g., olivine) or their dissociation products (e.g., quicklime) at the ocean surface, can increase surface total alkalinity and thus increase CO <sub>2</sub> uptake and storage (Glossary; Supplementary Material Text 5.SM.3; AR6 WGIII Chapter 12; [[#GESAMP--2019|GESAMP, 2019]] ; [[#Keller--2019|Keller, 2019]] ). Ocean alkalinization ameliorates surface ocean acidification ( ''high confidence'' ) ( [[#Hauck--2016|Hauck et al., 2016]] ; [[#Tran--2020|Tran et al., 2020]] ), but there are also negative side effects on the marine ecosystem, most of which are poorly understood or quantified (Figure 5.36 and Supplementary Materials Table 5.SM.4; [[#Bach--2019|Bach et al., 2019]] ). Although ocean alkalinization could potentially sequester large amounts of carbon (≥1 PgC yr <sup>–1</sup> ; Figure 5.36; and Supplementary Materials Table 5.SM.5) there is no new evidence to revisit the SROCC (SROCC [[#5.5.1.2.4|Section 5.5.1.2.4]] ) conclusion that there is ''low confidence'' that ocean alkalinization is a viable climate change mitigation approach.

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<span id="chemical-cdr-methods"></span>
===== 5.6.2.2.4 Chemical CDR methods =====

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Direct air carbon capture with carbon storage (DACCS) is a combination of two techniques, direct capture of CO <sub>2</sub> from ambient air (DAC) and carbon storage. DAC entails contacting the air, capturing the CO <sub>2</sub> on a liquid solvent or solid sorbent, and regenerating the solvent or sorbent. Different DAC methods have been proposed, which differ by the chemical process used to capture the CO <sub>2</sub> and to recover it from the sorbent or solvent ( [[#NASEM--2019|NASEM, 2019]] ). The captured CO <sub>2</sub> may be either stored geologically as a high-pressure gas or sequestered by a mineral carbonation process. Storage is potentially permanent in both pressurised gas and mineral form ( [[#Fuss--2018|Fuss et al., 2018]] ). DACCS has significant requirements of energy and, (depending on the type of technology), water and materials ( [[#Smith--2016|Smith et al., 2016]] ; [[#NASEM--2019|NASEM, 2019]] ). Compared to other CDR methods, it has a small land footprint ( [[#Smith--2016|Smith et al., 2016]] ; [[#NASEM--2019|NASEM, 2019]] ). Side effects of DACCS include CO <sub>2</sub> -depleted air leaving the air contactor, which could have adverse effects on crop and ecosystem productivity, and VOC emissions ( [[#NASEM--2019|NASEM, 2019]] ). Additional risks and side effects are related to the high pressure at which CO <sub>2</sub> is stored in geologic formations ( [[#Fuss--2018|Fuss et al., 2018]] ). DACCS is assessed in detail in WGIII Chapter 12.

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<span id="methane-removal"></span>
===== 5.6.2.2.5 Methane removal =====

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Proposals to remove CH <sub>4</sub> from the atmosphere are emerging ( [[#de%20Richter--2017|de Richter et al., 2017]] ; [[#Jackson--2019|Jackson et al., 2019]] ). CH <sub>4</sub> removal methods seek to capture CH <sub>4</sub> directly from ambient air, similarly to DACCS for CO <sub>2</sub> using, for example, zeolite trapping, but instead of storing it, CH <sub>4</sub> would be chemically oxidized to CO <sub>2</sub> ( [[#Jackson--2019|Jackson et al., 2019]] ). Methane can be also removed microbially by supporting naturally occurring processes, such as by enhancing the soil microbial uptake through afforestation (J. [[#Wu--2018|]] [[#Wu--2018|Wu et al., 2018]] ) or by directing the venting air from a cow barn into the soil bed of a nearby greenhouse, utilizing microbial CH <sub>4</sub> oxidation ( [[#Nisbet--2020|Nisbet et al., 2020]] ). Microbial CH <sub>4</sub> oxidation could also be used for removal of CH <sub>4</sub> leaked from point sources by building biocatalytic polymers which include methane-oxidizing enzymes ( [[#Blanchette--2016|Blanchette et al., 2016]] ). Methane removal is, however, still in its infancy and the available literature is insufficient for an assessment.

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[[File:d14a8f40ed425711c8d5d7ca00378512 IPCC_AR6_WGI_Figure_5_36.png]]

'''Figure 5.36 |''' '''Characteristics of carbon dioxide removal (CDR) methods, ordered according to the time scale of carbon storage.''' The first column shows biogeophysical (for open-ocean methods) or technical (for all other methods) sequestration potentials (i.e., the sequestration potentials constrained by biological, geophysical, geochemical limits and thermodynamics and, for technical potentials, availability of technologies and practices; technical potentials for some methods also consider social or environmental factors if these represent strong barriers for deployment; see Glossary, Annex VII), classified into low (&lt;0.3 GtCO <sub>2</sub> yr <sup>–1</sup> ), moderate (0.3−3 GtCO <sub>2</sub> yr <sup>–1</sup> ) and large (&gt;3 GtCO <sub>2</sub> yr <sup>–1</sup> ) (details underlying this classification are provided in Supplementary Materials Table 5.SM.5). The other columns show Earth system feedbacks that deployment of a given CDR method would have on carbon sequestration and climate, along with biogeochemical, biophysical, and other side effects of a given method. Earth system feedbacks do not include the direct effect of CO <sub>2</sub> sequestration on atmospheric CO <sub>2</sub> , only secondary effects. For Earth system feedbacks, the colours indicate whether the feedbacks strengthen or weaken carbon sequestration and the climate cooling effect of a given CDR method. For biogeochemical and biophysical side effects the colours indicate whether the deployment of a CDR method increases or decreases the magnitude of the effect, whereas for co-benefits and trade-offs the colour indicates whether deployment of a CDR method results in beneficial (co-benefits) or adverse side effects (trade-offs) for water quality and quantity, food production and biodiversity. The details and references underlying the Earth system feedback and side effect assessment are provided in Supplementary Materials Table 5.SM.4. Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

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<span id="biogeochemical-responses-to-solar-radiation-modification-srm"></span>
=== 5.6.3 Biogeochemical Responses to Solar Radiation Modification (SRM) ===

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This section assesses the possible consequences of solar radiation modification (SRM) on the biosphere and global biogeochemical cycles. The SRM options and the physical climate response to SRM is assessed in detail in [[IPCC:Wg1:Chapter:Chapter-4#4.6.3|Section 4.6.3]] and Table 4.7. Section 6.3.6 assesses the potential effective radiative forcing of aerosol-based SRM options and [[IPCC:Wg1:Chapter:Chapter-8#8.6.3|Section 8.6.3]] assesses the abrupt water cycle changes in response to initiation or termination of SRM. Most literature on the biogeochemical responses to SRM focuses on stratospheric aerosol injection (SAI), and only a few studies have investigated the biogeochemical responses to marine cloud brightening (MCB) and cirrus cloud thinning (CCT). At the time of AR5, there were only a few studies on the biogeochemical responses to SRM. The main assessment of AR5 ( [[#Ciais--2013|Ciais et al., 2013]] ) was that SRM will not interfere with the direct biogeochemical effects of increased CO <sub>2</sub> , such as ocean acidification and CO <sub>2</sub> fertilization, but could affect the carbon cycle through climate–carbon feedbacks. Overall, AR5 concluded that the level of confidence on the effects of SRM on carbon and other biogeochemical cycles is ''very low'' ( [[#Ciais--2013|Ciais et al., 2013]] ). Since AR5, more modelling work has been conducted to examine various aspects of the global biogeochemical cycle responses to SRM.

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[[File:3009735603b3df72dabc344e575ea39c IPCC_AR6_WGI_Figure_5_37.png]]

'''Figure 5.37 |''' '''Cumulative carbon dioxide (CO''' <sub>2</sub> ''') uptake by land and ocean carbon sinks in response to stratospheric sulphur dioxide (SO2) injection.''' Results are shown for a scenario with 50-year (2020−2069) continuous stratospheric SO <sub>2</sub> injection at a rate of 5 Tg yr <sup>–1</sup> appplied to a RCP4.5 baseline scenario (GeoMIP experiment G4; [[#Kravitz--2011|Kravitz et al., 2011]] ), followed by termination in year 2070. Anomalies are shown relative to RCP4.5 for the multi-model ensemble mean and for each of six Earth system models (ESMs) over the 50-year period of stratospheric SO <sub>2</sub> injection (left-hand side), and over 20 years after termination of SO <sub>2</sub> injection (right-hand side). Adapted from [[#Plazzotta--2019|Plazzotta et al. (2019)]] . Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

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<span id="effects-of-srm-on-the-carbon-cycle"></span>
==== 5.6.3.1 Effects of SRM on the Carbon Cycle ====

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Relative to a high-greenhouse gas (GHG) world without solar radiation modification (SRM), SRM would affect the carbon cycles through changes in sunlight, climate (e.g., temperature, precipitation, soil moisture, ocean circulation), and atmospheric chemistry (e.g., ozone; [[IPCC:Wg1:Chapter:Chapter-4#4.6.3.3|Section 4.6.3.3]] ; [[#Cao--2018|Cao, 2018]] ). Net SRM effects on the carbon cycle, relative to a world without SRM, depend on the change of individual factors, and interactions among them.

SRM-mediated sunlight changes directly affect the carbon cycle. In particular, SAI would reduce the sunlight reaching the Earth’s surface, but also increase the fraction of sunlight that is diffuse. These changes in the quantity and quality of the sunlight have opposing effects on the photosynthesis of land plants. On their own, reductions in photosynthetically active radiation (PAR) will reduce photosynthesis. However, diffuse light is more effective than direct light in accessing the light-limited leaves within plant canopies, leading to the so-called ‘diffuse-radiation’ fertilization effect ( [[#Mercado--2009|Mercado et al., 2009]] ). The estimated balance between the negative impacts of reducing PAR and the positive impacts of increasing diffuse fraction differ between models ( [[#Kalidindi--2015|Kalidindi et al., 2015]] ; [[#Xia--2016|Xia et al., 2016]] ; C.-E. [[#Yang--2020|]] [[#Yang--2020|Yang et al., 2020]] ) and across different ecosystems. The change in the absolute amount of direct and diffuse radiation could also depend on the height of the additional sulphate aerosol layer in the stratosphere and the hygroscopic growth of aerosols ( [[#Krishnamohan--2019|Krishnamohan et al., 2019]] , 2020).

SRM-mediated cooling also affects the terrestrial carbon cycle. Relative to a high-GHG world without SRM, the simulated responses of net primary production (NPP) to SRM differ widely between models, such that even the sign of global mean change is uncertain ( [[#Glienke--2015|Glienke et al., 2015]] ). SRM-induced cooling would decrease NPP at high latitudes by reducing the length of the growing season ( [[#Glienke--2015|Glienke et al., 2015]] ). At low latitudes, the NPP response to SRM-induced cooling is sensitive to the effect of nitrogen limitation (Glienke et al., 2015; [[#Duan--2020|Duan et al., 2020]] ). SRM-induced cooling tends to increase NPP in models without the nitrogen cycle because of reduced heat stress. However, in models including the nitrogen cycle, this is counteracted by reductions in NPP because of reductions in nitrogen mineralization and nitrogen availability (Glienke et al., 2015). SRM-induced changes in the hydrological cycle ( [[IPCC:Wg1:Chapter:Chapter-8#8.6.3|Section 8.6.3]] ), including changes in evapotranspiration, precipitation, and soil moisture, also pose strong constraints on the vegetation response (Dagon and Schrag, 2019). For the same amount of global mean cooling, different SRM options, such as SAI, MCB, and CCT, would have different effects on gross primary production (GPP) and NPP because of different spatial patterns of temperature, available sunlight and hydrological cycle changes ( [[IPCC:Wg1:Chapter:Chapter-4#4.6.3.3|Section 4.6.3.3]] ) ( [[#Duan--2020|Duan et al., 2020]] ). Modelling studies show that SRM-induced cooling would reduce plant and soil respiration ( [[#Tjiputra--2016|Tjiputra et al., 2016]] ; [[#Cao--2017|Cao and Jiang, 2017]] ; [[#Muri--2018|Muri et al., 2018]] ; C.-E. [[#Yang--2020|]] [[#Yang--2020|Yang et al., 2020]] ). Despite the large uncertainty in modelled NPP response, existing modelling studies consistently show that SRM would increase the global land carbon sink relative to a high-CO <sub>2</sub> world without SRM ( ''hi'' ''gh confidence'' ).

Based on available evidence, SRM with elevated CO <sub>2</sub> would increase global mean NPP and carbon storage on land relative to an unperturbed climate, mainly because of CO <sub>2</sub> fertilization of photosynthesis ( ''high confidence'' ) ( [[#Glienke--2015|Glienke et al., 2015]] ; [[#Tjiputra--2016|Tjiputra et al., 2016]] ; [[#Dagon--2019|Dagon and Schrag, 2019]] ; [[#Duan--2020|Duan et al., 2020]] ; C.-E. [[#Yang--2020|]] [[#Yang--2020|Yang et al., 2020]] ). However, the amount of increase is uncertain as it depends on the extent to which CO <sub>2</sub> fertilization of land plants is limited by nutrient availability.

Relative to a high-CO <sub>2</sub> world without SRM, SRM would also have compensating effects on crop yields. SRM is expected to have a positive impact on crop yields by diminishing heat stress ( [[#Pongratz--2012|Pongratz et al., 2012]] ). However, reductions in light availability will produce a counteracting reduction in crop yields, especially if the crop type does not benefit appreciably from diffuse-light fertilization ( [[#Proctor--2018|Proctor et al., 2018]] ). The balance between these effects varies markedly across crop types and regions, from projected increases in maize production in China ( [[#Xia--2014|Xia et al., 2014]] ) to reductions in groundnut yields in parts of India ( [[#Yang--2016|Yang et al., 2016]] ). Because of these diverging results from a limited set of studies, there is overall ''low confidence'' in the effect of SRM on crop yields.

Consistent with the AR5 assessment, there is ''high confidence'' that SRM would not mitigate CO <sub>2</sub> -induced ocean acidification ( [[#Ciais--2013|Ciais et al., 2013]] ). Some studies even suggest an acceleration of deep-ocean acidification as a result of ocean circulation change ( [[#Tjiputra--2016|Tjiputra et al., 2016]] ; [[#Lauvset--2017|Lauvset et al., 2017]] ). There are large differences in the simulated spatial pattern of ocean NPP change in response to SRM, which depends strongly on the SRM method that is considered ( [[#Partanen--2016|Partanen et al., 2016]] ; [[#Lauvset--2017|Lauvset et al., 2017]] ).

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<span id="consequences-of-srm-and-its-termination-on-atmospheric-co-2-burden"></span>
==== 5.6.3.2 Consequences of SRM and its Termination on Atmospheric CO <sub>2</sub> burden ====

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Modelling studies consistently show that, relative to a high-CO <sub>2</sub> world without SRM, SRM-induced cooling ( [[IPCC:Wg1:Chapter:Chapter-4#4.6.3.3|Section 4.6.3.3]] ) would reduce plant and soil respiration, and also reduce the negative effects of warming on ocean carbon uptake ( [[#Tjiputra--2016|Tjiputra et al., 2016]] ; [[#Xia--2016|Xia et al., 2016]] ; [[#Cao--2017|Cao and Jiang, 2017]] ; [[#Jiang--2018|Jiang et al., 2018]] ; [[#Muri--2018|Muri et al., 2018]] ; [[#Sonntag--2018|Sonntag et al., 2018]] ; [[#Plazzotta--2019|Plazzotta et al., 2019]] ; C.-E. [[#Yang--2020|]] [[#Yang--2020|Yang et al., 2020]] ). A multi-model study ( [[#Plazzotta--2019|Plazzotta et al., 2019]] ) indicates that, relative to a high-CO <sub>2</sub> concentration world without SRM, stratospheric sulphur dioxide (SO <sub>2</sub> ) injection increases the allowable CO <sub>2</sub> emissions by enhancing CO <sub>2</sub> uptake by both land and ocean (Figure 5.37). As a result of enhanced global carbon uptake, SRM would reduce the burden of atmospheric CO <sub>2</sub> ( ''high confidence'' ). However, the amount of SRM-induced reduction in atmospheric CO <sub>2</sub> depends on the future emissions scenario and modelled oceanic and terrestrial carbon sinks, which differ widely between models ( [[#Tjiputra--2016|Tjiputra et al., 2016]] ; [[#Xia--2016|Xia et al., 2016]] ; [[#Cao--2017|Cao and Jiang, 2017]] ; [[#Muri--2018|Muri et al., 2018]] ). Models that include the terrestrial nitrogen cycle usually report a much smaller reduction of atmospheric CO <sub>2</sub> in response to SRM than models without the nitrogen cycle, mainly because nitrogen limitation leads to a weaker terrestrial carbon sink ( [[#Tjiputra--2016|Tjiputra et al., 2016]] ; [[#Muri--2018|Muri et al., 2018]] ; C.-E. [[#Yang--2020|]] [[#Yang--2020|Yang et al., 2020]] ). Large-scale application of SAI is found to reduce the rate of release of CO <sub>2</sub> and CH <sub>4</sub> from permafrost thaw ( [[#Lee--2019|Lee et al., 2019]] ; [[#Chen--2020|Chen et al., 2020]] ).

A hypothetical sudden and sustained termination of SRM would cause a rapid increase in global warming that would pose great risks to biodiversity ( [[#Jones--2013|]] [[#Jones--2013|A. Jones et al., 2013]] ; [[#McCusker--2014|McCusker et al., 2014]] ; [[#Trisos--2018|Trisos et al., 2018]] ) ( [[IPCC:Wg1:Chapter:Chapter-4#4.6.3.3|Section 4.6.3.3]] ). It would also weaken carbon sinks, accelerating atmospheric CO <sub>2</sub> accumulation and inducing further warming (Figure 5.37; [[#Matthews--2007|Matthews and Caldeira, 2007]] ; [[#Tjiputra--2016|Tjiputra et al., 2016]] ; [[#Muri--2018|Muri et al., 2018]] ; [[#Plazzotta--2019|Plazzotta et al., 2019]] ). However, a scenario with gradual phase-out of SRM under emissions reduction could reduce the large negative effect of sudden SRM termination ( [[#MacMartin--2014|MacMartin et al., 2014]] ; [[#Keith--2015|Keith and MacMartin, 2015]] ; [[#Tilmes--2016|Tilmes et al., 2016]] ),though this would be limited by how rapidly emissions reductions can be scaled-up ( [[#Ekholm--2016|Ekholm and Korhonen, 2016]] ).

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<span id="consequences-of-srm-on-other-biogeochemical-cycles"></span>
==== 5.6.3.3 Consequences of SRM on other Biogeochemical Cycles ====

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SAI is found to reduce global average surface ozone concentration ( [[#Xia--2017|Xia et al., 2017]] ) mainly as a result of aerosol-induced reduction in stratospheric ozone at polar regions, resulting in reduced transport of ozone from the stratosphere ( [[#Pitari--2014|Pitari et al., 2014]] ; [[#Tilmes--2018|Tilmes et al., 2018]] ). The reduction in surface ozone, together with alteration to ultraviolet (UV) radiation, would have important implications for vegetation response ( [[#Xia--2017|Xia et al., 2017]] ). A modelling study shows that sea salt aerosol injection for MCB would reduce hydroxyl (OH) concentration and increase CH <sub>4</sub> lifetime, and hence, have potential implications for surface ozone pollution ( [[#Horowitz--2020|Horowitz et al., 2020]] ). It has also been reported that the use of SAI to limit global mean warming from 2°C to 1.5°C would reduce fire weather in many areas ( [[#Burton--2018|Burton et al., 2018]] ).

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<span id="synthesis-of-biogeochemical-responses-to-srm"></span>
==== 5.6.3.4 Synthesis of Biogeochemical Responses to SRM ====

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SRM would alter the global carbon cycle through SRM-induced climate effect, such as changes in sunlight, temperature, precipitation, and ocean circulation. Compared to a high-CO <sub>2</sub> world without SRM, SRM would enhance the net uptake of CO <sub>2</sub> by the terrestrial biosphere and ocean, thus acting to reduce atmospheric CO <sub>2</sub> ( ''high confidence'' ). SRM would also affect surface ozone, UV radiation, and atmospheric chemistry. Due to complex interplays between SRM-induced changes in direct and diffuse sunlight, temperature, the coupling of water-carbon-nitrogen cycles, and atmospheric chemistry, there is ''large uncertainty'' in the overall response of the terrestrial biosphere response to SRM. Thus, the level of ''confidence'' on the effect of SRM on carbon and other biogeochemical cycles is ''low'' .

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<span id="final-remarks"></span>