Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
Loading...
At its simplest level, the net CO₂ removed from this multi-pathway system can be calculated as:
Where:
Initial deployments will focus on the sinking of terrestrial woody biomass. This pathway is fully operationalized and accounted for today via:
Direct measurement of the carbon content of representative terrestrial biomass samples contained in the carbon buoys, validated by laboratory testing of biomass characteristics.
The adoption of existing ocean models for predictive modeling of expected carbon buoy transport behavior in the open ocean, also based on assessments of the physical behavior of carbon buoys in lab-replicated ocean environments and empirical data from GPS sensors released alongside deployment.
Direct observation of biomass sinking from a subset of carbon buoys via in-situ image analysis from observational camera systems released alongside carbon buoy deployment.
Quantification of emissions associated with biomass material inputs, production, transport, and deployment.
Initial deployments will also utilize a mixture of calcium carbonate and lime kiln dust for dissolution in the surface ocean. This pathway is operationalized for initial deployments and will be used to buffer any acidity generation that occurs during terrestrial biomass floatation, but will not be used to generate credits through the ocean alkalinity enhancement pathway until the quantification and monitoring methodology is refined in the .
The primary objective in quantifying alkalinity enhancement is to determine what quantity of alkalinizing material has been successfully dissolved into the mixed layer in a given region of the ocean. The amount of CO₂ sequestered by the alkalinity addition will be discounted by the amount of CO₂ released by any reprecipitation of carbonate minerals that occurs in the surface waters, which will be estimated from laboratory experiments and measurements of key parameters in the field (salinity, temperature, pH). To-date, testing of ocean alkalinity enhancement has primarily been conducted in laboratory settings to characterize how quickly alkaline materials dissolve in water. In the laboratory setting, dissolution reactors continuously log temperature, pH, and salinity of water and pCO₂ of air at the surface, alkalinity is measured with an auto titrator, and water samples are sent to independent labs for elemental analysis. Experiments have also been conducted to characterize the effect of organic acid leaching from wood and the mitigation of this by alkaline mineral dissolution, namely lime kiln dust. Supplementing research by external collaborators, additional experiments are planned to further quantify rates of acid leaching from terrestrial biomass and neutralization of this acidity by dissolution of alkaline minerals, and to elucidate the degradation of dissolved organic carbon released by the macroalgae and terrestrial biomass.
Weather permitting, surface water conditions will be monitored and sequentially sampled during deployments to help establish a solid empirical baseline for key parameters related to CO₂ removal, including pH, salinity, total alkalinity, and other chemical constituents as needed. Both the interactions observed from laboratory experiments and surface water sampling during deployments will be incorporated into predictive modeling of the perturbation against baseline seawater carbonate chemistry to evaluate net CO₂ sequestration.
Over time and with scale, direct observation of the carbon chemistry perturbation and how it evolves in time may be possible, and in-situ imaging of alkaline mineral dissolution via instruments such as those shown above may be used to validate results in the open ocean.
Geochemical dynamics embedded within global circulation models will be used to quantify the amount of additional CO₂ transferred from the fast to the slow carbon cycle. Although these models are adapted and developed on an ad hoc basis today, best practices for modeling should be developed at an industry level.
Ongoing research related to OAE quantification includes studying the impact of surface-ocean carbon uptake or alkalinity addition on the air-sea gas exchange of CO₂. While this air-sea flux is an important and well studied area of carbon cycle research, it is primarily a fast cycle transfer of atmospheric CO₂ into surface waters as the dissolved CO₂ that was reallocated to the bicarbonate reservoir is replaced by novel CO₂ exchange across the air-sea boundary. The slow cycle transfer that is the primary activity of carbon removal occurs via the reallocation of fast cycle carbon to the larger and more stable bicarbonate reservoir. While the time horizon to complete the exchange of CO₂ between the atmosphere and ocean may vary, it will eventually equilibrate, completing the fast cycle transfer. The air-sea exchange time horizon for CO₂ relative to the time it takes for surface waters to be subducted to the deep ocean [Sabine et al., 2004] may be relevant to establishing total carbon removed via natural ocean mixing – i.e. if full equilibration has not yet occurred at the time of mixing to the deep ocean, there may be an impact on the fast-to-slow transfer of carbon from that natural pathway associated with project activities. Determining and refining how this is considered in OAE quantification remains an active area of discussion amongst practitioners and the research community as the OAE field matures.
Carbon removal by macroalgae will not be operational for initial deployments and will be introduced in subsequent deployments based on the successful recruitment and growth of macroalgae in the open ocean and continued advancements in modeling algal growth versus observed growth.
Most macroalgae species are coastal organisms adapted to thrive in environments with high nutrient concentrations and low wave energy relative to the open ocean. Research on open ocean cultivation of macroalgae has focused on species that will sink intact through the water column, particularly Ulva lactuca and Saccharina latissima. Foundational work has been performed on macroalgal genomics and life cycle, including extraction of high molecular weight DNA from Saccharina latissima and various Ulva species. Isolation, cultivation, and banking of various developmental stages of these species have been performed, and this basic research, conducted in collaboration with Los Alamos National Laboratory, should lead to the first published long-read genomes for Ulva lactuca and Saccharina latissima. Surveys of natural variation at initial deployment locations in West Iceland have also been performed to collect genotype and phenotype data for a variety of macroalgae species in that region.
Alongside this foundational research, a series of coastal macroalgae growth experiments have been performed to establish technical capacity for macroalgae growth and image-based phenotyping alongside environmental time series data collection at the experimental growth site. Initial experiments included measurements of temperature, pH, salinity, light intensity at depth, photosynthetic active radiation (PAR) at depth, and chlorophyll-a content of the ambient water. Later experiments were expanded to include fluorescent dissolved organic matter (fDOM), ammonium, dissolved oxygen, nitrate, turbidity, and subsurface ocean currents. Ongoing coastal experiments afford the opportunity to explore methods of seeding carbon buoys with macroalgae, and observe and measure macroalgae growth rates in an ocean setting. The technology developed in this setting will be applied to the open ocean to support the quantification of macroalgae growth offshore.
Open ocean tests of integrated prototypes have also been conducted, placing macroalgae seed on instrumented buoys in the open ocean to observe open ocean macroalgae seed recruitment and test verification hardware. Critically, the recruitment and growth of macroalgae was successfully imaged in the open ocean.
The results of controlled laboratory experiments are being used to develop biological growth models for macroalgae carbon accumulation — based on inputs related to genetics, macroalgae development stage, and environmental parameters — to predict growth (and thus carbon sequestered) along an ocean deployment trajectory. Laboratory experiments replicate open ocean light, temperature, and nutrient conditions to enable robust models and predictions. Models developed are in part based on existing macroalgae growth models [Broch and Slagstad, 2012]; however, these pre-established models are not specific to macroalgae grown in the open ocean, and as such require significant modification, and must be built and refined against open ocean conditions via quantification outputs from both controlled and test deployments.
Models are trained with imaging data, where predictive quantification of biomass growth is compared with observed growth in the open ocean validated by in-situ imaging, and discrepancies are used to refine model outputs. Machine vision enables the generation of texturized, three-dimensional models from a set of two-dimensional buoy and macroalgae images, providing additional data on macroalgae biomass accumulation and carbon content.
Following initial deployments, it is expected that the ratio of macroalgae to woody biomass will be gradually increased, with the long-term (decadal) goal of achieving a 5:1 ratio of macroalgae mass to carbon buoy mass on a carbon basis. Yields of 50:1 have been observed in fixed research locations with low wave energy, high-nutrient conditions.
With that context, CO₂eTerrestrial, CO₂eOAE, CO₂eMacroalgae, and CO₂eEmissions can be broken down into their component parts.
CO₂ Removal by Sinking of Terrestrial Biomass can be quantified as:
Where:
Calculated based on the total mass of carbon buoys loaded onto a specific deployment vessel, the portion of buoys composed of terrestrial biomass, the moisture content of biomass at the time of loading, and the carbon content of ‘bone dry’ biomass.
Quantified via a combination of direct measurement of mass of material used in buoys and a standard conversion factor for carbon content of material based on species used. Terrestrial biomass is sampled and submitted to a partner lab for analysis of moisture content, carbon content, and ash content.
A small amount of loss may be observed during transport due to high winds and waves.
For initial deployments off of barges, loss is estimated by comparing time lapse camera image analysis to total volume calculated from barge dimensions and loaded height measurement.
In the event of camera issues or unexpected weather events, additional conservative discount factors may be applied.
Laboratory experiments are conducted to measure remineralization rates, sinking rates, and the amount of organic compounds leached, dissolved, or otherwise separated during the flotation time of terrestrial biomass (including particulate organic carbon and dissolved organic carbon such as organic acids).
Direct observation of biomass loss via in-situ image analysis from observational camera systems further informs and refines float times.
Conservative estimates of terrestrial biomass separation during floating periods outside of eligible sinking locations are applied.
Spatial evolution of the carbon buoy population is evaluated across quantification approaches:
Carbon buoy sinking speed is evaluated in laboratory and coastal settings.
Lateral transport of carbon buoys during sinking can be modeled using publicly available ocean current models. These models resolve subsurface ocean currents at various depths, and are validated against in-situ data. Such models can be used to quantify the maximum horizontal distance that a carbon buoy may travel during its descent given a particular .
Modeling and laboratory results can be further supported via direct measurement from GPS sensor buoys.
. Models start with initial distribution of passive floating points (carbon buoys), simulate floating trajectories, and then simulate sinking to the terminal location on the seafloor. The time that carbon buoys sink is simulated using the float time distributions described above and trajectories defined by the interplay between wind, waves and currents. Thousands of simulations are run to determine the probability curve within the range of possible values. The results of these model runs produce a final probability plot of terminal carbon buoy distribution on the seafloor, which defines a single variable output with a given confidence level.
Beyond initial deployments, additional in-situ observations of sinking rate — including the use of submersible AUVs to follow deployments throughout surface drifting and eventual sinking to the seafloor — are planned and expected in the coming years. Benthic research programs with external oceanographic collaborators are currently being finalized.
Actual depth in shallower locations may be of less importance than sedimentation and remineralization rates, as the percentage of organic carbon preservation varies with total sedimentation rate (i.e. the faster something is buried, the more likely its carbon will be preserved in its organic form). Similarly, benthic research programs will be needed to inform expected biomass burial and remineralization rates.
Related to the additionality of project activities. Effective drawdown from terrestrial biomass sinking occurs so long as the biomass would not have otherwise been moved into the slow cycle (certain types of biochar applications, biomass burial, bio-oil injection, etc.) and does not negatively impact the net carbon stock of the .
With a fast-to-slow framing for terrestrial biomass, the primary consideration is the stability of the carbon reservoir in question. Carbon stored in aboveground biomass, whether in short-lived industrial processes, a managed forest, or subject to natural decay, is inherently volatile and subject to a high risk of reversal, meaning that the carbon contained within this biomass may move between fast cycle reservoirs in a matter of months, years, or decades. As such, the removal activity related to this biomass occurs when that potential volatility is eliminated. Aboveground biomass and surface soils are thus functionally fast systems that will largely remain in the fast cycle (in their baseline state, as atmospheric CO₂ or as dissolved CO₂ in the surface ocean) via soil/root respiration or decomposer respiration from dead wood/leaves. Conversely, the underlying “stable” soil carbon layer is functionally a slow cycle reservoir in that the carbon contained is unlikely to move into a different reservoir without human disruption or significant land use change.
While this framing implies that all aboveground terrestrial biomass could potentially be additional from a purely carbon accounting perspective, practically speaking, the management of aboveground biomass and surface soils will impact both fast cycle carbon fluxes and the stability of the underlying stable soil layer, along with critical non-carbon secondary effects on biodiversity, ecosystem health including watershed benefits and oxygen production, and more. As such, biomass eligibility and sourcing considerations are determined not just by fast and slow carbon cycling, but also by their potential impact (positive and negative) on the above secondary effects and fast cycle fluxes.
For residue sources, this is straightforward; differentiating between materials that would be burned versus left to decay is de minimis, as GHG Protocol guidance for dead organic material states that the timing delay associated with baseline CO₂ emissions from degradation does not require amortization and can be claimed at the time of intervention. Supplier attestations on the alternative baseline state of sourced residue biomass are required to demonstrate additionality.
For biomass sourced from non-residue origins, biomass obtained through sustainable forest management shall be utilized, and on a long-term basis, “purpose-grown feedstock” — i.e. terrestrial biomass that is grown on marginal or arid land for the explicit purpose of biomass-based carbon removal — will be considered, contingent on their impact on secondary effects.
Biomass sourcing standards will need to continue to be developed and adopted at an industry level, especially as competition for available biomass is expected to increase.
Related to the impact on the net carbon stock from land use change due to project activities, and encompassing the harvesting of terrestrial biomass leading directly to emissions elsewhere (i.e., leakage). Supplier attestations for all biomass sources will be required, and any additional emissions that directly result from increased demand for biomass will be monitored and included in the calculation of net carbon removed.
For residues, all biomass sourced is FSC certified and sourced from FSC Forest Management Certified suppliers, or from an equivalent certification system in the event FSC is not in use in a given jurisdiction or with a given species. Low-grade biomass resources are currently in abundant supply, in part due to economic shifts in the demand for materials such as low-grade pulp wood, along with readily available materials such as sawmill cut offs and wildfire management burn piles.
Land use change modeling will follow GHG Protocol best practices and industry standards specific to . Notably, existing land use change models are atmospheric-centric in their design, and as such early deployments are likely to be inherently conservative in their accounting for potential fast cycle fluctuations.
= CO₂ Removal by Sinking of Terrestrial Biomass
= CO₂ Removal by Alkaline Mineral Dissolution
= CO₂ Removal by Macroalgae
= End-to-End System Emissions
= Mass of carbon contained in terrestrial biomass that is deployed to be sunk.
= Mass of carbon contained in terrestrial biomass that is lost between time of loading and time of deployment.
= Portion of carbon in terrestrial biomass separated from carbon buoys prior to or during the sinking process that does not make it to the ocean floor.
= Portion of terrestrial biomass carbon that ends up beached or sunk in areas too shallow to be removed from the coupled upper ocean-atmospheric system in the fast carbon cycle, or at risk of upwelling.
= The portion of carbon in embodied terrestrial biomass that is likely to be removed from the fast carbon cycle in the absence of sinking.
= Emissions impact of any indirect land use change associated with changes in the production of the feedstock due to terrestrial biomass sinking.
CO₂ Removal by Alkaline Mineral Dissolution can be quantified as:
Where:
= Moles of alkalinity added to surface seawater through dissolution of alkaline minerals.
Conversion of alkalinity into CO₂e can be calculated based on the measured addition of alkaline materials into the ocean and their modeled rate of dissolution prior to sinking, informed by laboratory testing in different conditions.
= Moles of secondary precipitation of calcium carbonate (CaCO₃) associated with high surface water alkalinity.
Can be minimized by ensuring rapid dispersal of added alkalinity relative to the rate of alkalinity addition, and potentially assessed by measurements of Total Alkalinity (TA), pH, , and/or dissolved inorganic carbon (DIC) in the deployment region.
= Moles of DIC added to seawater as carbonate equivalents (CO32-) by dissolution of calcium carbonate rather than as bicarbonate.
Represents the uptake efficiency uncertainty associated with carbonate versus bicarbonate formation, as carbonate formation reduces the marginal storage capacity of DIC (via atmospheric CO₂) in seawater per unit of added alkalinity.
Aqueous carbonate vs bicarbonate ion formation in a given area is based on environmental conditions (temperature, pressure, salinity) and pH, and must be accounted for to determine the total reallocation of fast cycle carbon (aqueous CO₂ pool) to the bicarbonate pool as a removal. Water sampling during deployments will be completed for a baseline understanding of these environmental conditions.
Laboratory testing measuring alkalinity, pH, and DIC are conducted on water samples to calculate the distribution of aqueous carbonate species between aqueous CO₂, bicarbonate ions HCO3-, and carbonate ions (CO32-) at a given point in time.
= Any addition of acidity to the ocean that reduces the alkalinity of surface seawater and the associated sequestration of atmospheric CO₂, expressed as the resulting change in moles of alkalinity.
Terrestrial biomass contains organic compounds with functional groups that, when dissolved in water, may contribute acidity to the surface ocean environment. Leaching experiments in a laboratory setting will quantify the amount of acidity that is generated from organic carbon dissolution, which can be extrapolated to the scope of the project activity.
This release of acidity would effectively counteract a molar-equivalent portion of alkalinity enhancement associated with alkaline mineral dissolution.
= Physical Mixing Factor. The effect of ocean mixing processes on the efficiency of moving CO₂ from the fast to slow cycle – i.e., surface ocean subduction to deeper waters following alkalinity addition and prior to complete re-equilibration.
A chemical perturbation to the surface ocean, such as alkalinity enhancement, that reallocates dissolved CO₂ to the stable bicarbonate reservoir increases the residence of the dissolved carbon, thereby constituting a transfer from the fast to slow cycle. This reallocation or increase in buffering capacity can lead to a chemically unstable gradient between the partial pressure of CO₂ (pCO₂) in the surface ocean and the atmosphere, drawing additional fast cycle CO₂ into the ocean for conversion to bicarbonate ion. If subduction of surface water due to physical mixing processes occurs prior to complete re-equilibration, the fast-to-slow transfer of carbon from that natural physical pathway may be reduced, and as such should be accounted for with a discount factor.
The impact on total carbon removed from this factor is only in relation to the difference between the total amount of dissolved carbon mixed into the deep ocean for durable storage in the absence of project activity versus what is mixed into the deep ocean following the addition of alkalinity and the associated addition of DIC to the surface ocean.
This remains an active area of research and discussion within the scientific community.
= Additional formation of dissolved inorganic carbon could lead to more Particulate Organic Carbon (POC) in the surface ocean, thereby providing additional CO₂ drawdown via increased photosynthetic activity (i.e., a “fertilization effect”).
The positive increase in POC in the surface ocean would only lead to additional carbon removed based on the portion of additional POC that made its way to the deep ocean for durable storage via natural fast-to-slow pathways (i.e. biological pump or ocean mixing activity). When deployed in tandem with the macroalgae carbon removal pathway, this effect may be complementary to macroalgae growth and relevant for nutrient competition considerations (see the BAF variable below). This effect remains uncertain and is an area of further research and exploration.
Quantification of increased primary production due to alkalinity-induced increase in DIC would require remote and/or in-situ measurement of localized chlorophyll-a. concentrations and/or phytoplankton populations.
Leakage refers to emissions caused by the project activity but which are indirect or take place outside the project boundary. For this project, two potential sources of leakage have been identified: (a) harvesting of terrestrial biomass causing emissions elsewhere; and (b) lower amounts of biomass growth in the ocean due to nutrient resource constraints caused by the project’s macroalgae growth.
Both potential leakage considerations are mentioned for clarity, but are addressed and accounted for within the quantification framework above.
In the event other potential sources of leakage are identified, they will be considered and accounted for within future versions of this protocol.
End-to-End System Emissions can be quantified as:
Where:
Based on an assessment of life cycle emissions of the specific electricity or energy sources consumed on-site and via transport across all three carbon removal pathways.
While there are inherent complexities associated with the deployment and quantification of a multi-pathway carbon removal system, its interconnectedness offers numerous quantification advantages, such as logistical (transport, delivery) and verification efficiencies. For example, wave sensors enable cumulative damage analyses of carbon buoys, allowing for validation of remotely sensed wave data, but also of expected macroalgae accumulation and carbonate dissolution rates. Similarly, compressed photos from ocean observation platforms provide visual information about both macroalgae growth rates and terrestrial biomass float times.
It is expected that this quantification approach will continue to mature as the research conducted advances our collective understanding of the ocean’s complex and interconnected systems.
CO₂ Removal by Macroalgae can be quantified as:
Where:
Ocean observation platforms capture photos of deployed carbon buoys to provide in-situ visual validation of macroalgae biomass accumulation and growth rates up to the point the buoys begin to sink. Image analysis (through machine vision) is used to extract growth characteristics (blade length, width, area) to correlate to biomass and carbon content. This imaging informs macroalgae loss or shedding that occurs during the growth process and float period.
Models are trained using machine vision to map macroalgae mass using the camera systems deployed on the open ocean observation platforms. Preliminary data has shown high correlations in direct measurements of macroalgae biomass and carbon elemental analysis.
Yields will depend on macroalgae species and genotype, environmental conditions such as macro and micronutrient availability, and episodic mortality events such as disease and storms.
Future quantification will include refined analysis of imaging through water, which will help account for distortion from refraction and turbidity. Currently, image quality is more altered by physical constraints on the system (power, lighting, electronics, etc.).
Biomass accumulation in addition to the specific species of macroalgae seeded on the buoys. Carbon buoys and other materials placed in the ocean are subject to natural photosynthetic ‘biofouling’, i.e. the growth of microorganisms, algae, and other species on submerged surfaces. While this process tends to be undesired for maritime vessels or oceanographic sensors, much like seeded macroalgae recruitment, they represent natural recruitment and growth of carbon-fixing organisms that if sunk are additional to natural biological pump activity.
Quantification of additional biomass accumulation is contingent on the ability to recognize macroalgae species and effectively image and model growth rates in the same fashion as macroalgae seeded on deployed carbon buoys described above.
Similarly, this additional biomass is subject to further benthic and pelagic ecological investigations in relation to the species identified.
Open ocean observation platforms are collecting data on macroalgae biomass accumulation up to the point of sinking, and buoy design promotes an accelerated sinking rate compared to phytoplankton and particulate organic carbon, which will minimize potential shedding rates. Any shed material that has already started sinking is expected to behave similarly to the macroalgae material attached to the buoy.
It is well established that many fish species have a natural affinity to aggregate near floating structures, and as such may view new macroalgae biomass as a potential food source as it moves through the water column. This impact is expected to be immaterial for initial deployments due to intervention design, but further research is being conducted into the potential impact of pelagic organisms on macroalgae consumption and the fraction of that consumed biomass that is transported to the seabed as fecal pellets (i.e., transported to slow carbon cycle) versus being remineralized to CO₂ in the surface water and released back to the fast carbon cycle.
The addition of macroalgae into the open ocean where nutrients are already limiting for photosynthesis has the potential to decrease phytoplankton net primary productivity indirectly through nutrient consumption by macroalgae. Since macroalgae have much higher C:N ratios than phytoplankton, they can form one unit of carbon biomass using a smaller nutrient load than phytoplankton. Although this makes macroalgae more efficient with respect to nutrient utilization, and prevents macroalgae from displacing phytoplankton on a 1:1 basis, macroalgae photosynthesis may still displace phytoplankton photosynthesis to some extent in waters where nutrients are limiting.
For initial deployments, given that algal photosynthesis in the subpolar North Atlantic is primarily iron-limited [Moore et al. 2013], it is expected that phytoplankton-macroalgae competition will be driven by the micronutrient iron.
Net primary productivity tradeoffs are expected to be immaterial for initial deployments. Additional research will be conducted to determine the expected nutrient tradeoff and the associated reduction in total carbon removed that must be accounted for in larger scale interventions. From a carbon perspective, only the expected carbon that would have been naturally removed via the biological pump should be discounted; however, the broader nutrient and ecosystem impacts must also be considered.
This variable reflects a range of potential biogeochemical responses that may be observed when macroalgae grows in a new environment, and which may impact total carbon removed.
Specific to calcifying organisms, it is unclear whether calcifying organisms will actually recruit onto the macroalgae over a short multi-month timeframe in the open ocean, given their preferred benthic environment on the coastal shelf. In the event calcifying organisms are observed, image analysis through machine vision will be used to identify the species and appropriately discount the modeled carbon content at the point of sinking.
The removal of carbon from the fast to slow cycle in the macroalgae pathway occurs during organic carbon production (photosynthesis) and sinking. Like OAE, this leaves a deficiency of dissolved CO₂ compared to the baseline, particularly due to the high C:N ratio of some macroalgal species, some of which will instantaneously be replaced by a small amount of bicarbonate. If subduction of surface water due to physical mixing processes occurs prior to complete re-equilibration, this amount should be accounted for with a discount factor.
It should be noted that the timescales of surface water subduction versus CO₂ re-equilibration, and the methods to quantify this, are an active area of research within the scientific community.
Similar to terrestrial biomass sinking, spatial evolution of the buoy population can be characterized through a combination of computational modeling, in-situ empirical observation, and laboratory testing, alongside a Monte Carlo analysis to determine the terminal carbon buoy distribution on the seafloor.
Given the deployment areas and float times, this impact is expected to be immaterial for initial deployments.
= The emissions associated with energy use in the process of CO₂ sequestration.
= The associated emissions (including transport) of any materials consumed during project operations, processing, and manufacturing.
= The associated emissions of equipment, facility construction, and other capital expenditures related to project operations.
= Mass of carbon absorbed by deployed macroalgae attached to carbon buoys at the point of sinking.
= Mass of carbon absorbed by non-seeded macroalgae that accumulates on carbon buoys via natural recruitment at the point of sinking.
= Portion of macroalgae carbon shed during the growth and sinking process.
= Biogeochemical Additionality Factor, or the secondary effects on phytoplankton carbon uptake associated with competition with cultivated macroalgae for nutrients or light in the open ocean.
= Biogeochemical Feedback Responses, or the range of potential environmental responses that develop in response to the introduction of macroalgae into the open ocean environment. As a specific example, it is possible that the growth of calcifying epibionts (i.e. an organism that lives on the surface of another living organism) may be observed as macroalgae grows, though their presence is not expected.
= Physical Mixing Factor. The effect of ocean mixing processes on the efficiency of moving CO₂ from the fast-to-slow cycles – i.e., surface ocean subduction to deeper waters before carbon removed from seawater by macroalgae growth is completely re-equilibrated.
= Portion of macroalgae carbon that ends up beached or sunk in areas too shallow or at risk of upwelling.
If sunken carbon makes its way into ocean sediments, either through inorganic or biogeochemical pathways, it will remain out of the fast carbon cycle for geological time scales [Rousselet et al., 2021], with the risk of reversal close to non-existent by design of the system deployed. This design includes selecting only sinking locations that allow for durable storage of accumulated biomass based on depth and local ocean conditions (stability, rates of sedimentation). Selection of sinking locations has a significant impact on mitigating potential reversal risks and is a key component of deployment design; as an example, the movement of deeper water to the surface driven by surface winds (i.e. upwelling) could potentially reduce the durability of storage by recirculating dissolved carbon in the deep ocean back to the surface faster than would occur with typical ocean circulation patterns. However, project activities are conducted far offshore and away from coastal zones where upwelling is prevalent. Non-coastal zones that are associated with upwelling, such as the Equatorial Pacific, would also not be considered ideal sinking locations for that reason.
Once sunk below the ocean’s thermocline, deep-sea ocean conditions and the ocean's natural circulation patterns mitigate virtually all natural reversal risk. Deployment areas must be monitored for potential economic use that could impact the stability of the deep-water area, such as deep-sea mining, trawling, or similar economic activities that could disturb the seabed — but these risks are minimal and can be mitigated through careful site selection and monitoring of deployments.
The exact durability of storage may vary based on site selection, local ocean conditions, and the end fate of sunk biomass, and further research will be conducted to advance a shared understanding of deep ocean circulation patterns.