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

==== 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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