Monitoring, Reporting and Verification for Marine Carbon Dioxide Removal

Future Science Brief Monitoring, Reporting and Verification for Marine Carbon Dioxide Removal N° 13 November 2025 EMB FUTURE SCIENCE BRIEF 2 The European Marine Board provides a pan-European platform for its Member organisations to develop common priorities, advance marine research, and to bridge the gap between science and policy in order to meet future marine science challenges and opportunities. The European Marine Board (EMB) is an independent and self-sustaining science policy interface organisation that currently represents 38 Member organisations from 19 European countries. It was established in 1995 to facilitate enhanced cooperation between European marine science organisations towards the development of a common vision on the strategic research priorities for marine science in Europe. The EMB promotes and supports knowledge transfer for improved leadership in European marine research. Its membership includes major national marine or oceanographic institutes, research funding agencies and national consortia of universities with a strong marine research focus. Adopting a strategic role, the European Marine Board serves its Member organisations by providing a forum within which marine research policy advice is developed and conveyed to national agencies and to the European Commission, with the objective of promoting the need for, and quality of, European marine research. www.marineboard.eu European Marine Board Member Organisations European Marine Board IVZW National Research Council of Italy UNIVERSITÉS MARINES Irish Marine Universities Consortium N° 13 2025 3 This Future Science Brief is a result of the work of the European Marine Board Expert Working Group on Marine Carbon Dioxide Removal. See Annex 1 for the list and affiliations of the Working Group Members. Working Group Chairs Helene Muri, Olivier Sulpis Contributing Authors Gabriela Argüello, Chelsey A. Baker, Miranda Böttcher, Maribel I. García-Ibáñez, Karol Kuliński, Angela Landolfi, Peter Landschützer, Evin McGovern, Živana Ninčević Gladan, Andreas Oschlies, Elias A. Yfantis Series Editor Sheila J. J. Heymans Publication Editors Ángel Muñiz Piniella, Ana Rodríguez Perez, Paula Kellett, Britt Alexander, Fernanda Bayo Ruiz, Sheila J. J. Heymans External Reviewers Ken Buesseler, David Langlet, Joanna Post, Masahiro Sugiyama, Naomi E. Vaughan Internal review process The content of this document has been subject to internal review and approval by the European Marine Board Member Organisations. Suggested reference Muri, H., Sulpis, O., Argüello, G., Baker, C. A., Böettcher, M., García-Ibáñez, M. I., Kuliński, K., Landolfi, A., Landschützer, P., McGovern, E., Ninčević Gladan, Ž., Oschlies, A., Yfantis, E. A. (2025) Monitoring, Reporting and Verification for Marine Carbon Dioxide Removal. Muñiz Piniella, A., Rodriguez Perez, A., Kellett, P., Alexander, B., Bayo Ruiz, F., Heymans, J. J. [Eds.] Future Science Brief N°. 13 of the European Marine Board, Ostend, Belgium. ISSN: 2593-5232. ISBN: 9789464206388. DOI: https://doi.org/10.5281/zenodo.17435116 www.marineboard.eu [email protected] Design Zoeck Front cover image credit: Mesocosm experiment as part of an Ocean Alkalinity Enhancement trial. Credit: Michael Sswat, GEOMAR First edition, November 2025 This document is licensedunder the Creative Commons Attribution 4.0 International License (CC BY 4.0). In this document, Artificial Intelligence-powered tools Grammarly, ChatGPT and InstaText have been used to assist with the language editing. Artificial Intelligence has not been used for any key writing task, such as producing scientific insights, creating a literature review, drawing scientific conclusions or providing recommendations. European Marine Board IVZW Future Science Brief N° 13 EMB FUTURE SCIENCE BRIEF 4 The European Union (EU) is committed to achieving the goals of the 2015 Paris Agreement to keep the global temperature rise this century to well below 2°C above pre-industrial levels, and to pursue efforts to limit the temperature increase to 1.5°C. With the European Climate Law of 2021, the EU has to reduce emissions by at least 55% by 2030, compared to 1990 levels, reach net zero greenhouse gas emissions by 2050, and negative emissions after 2050. Although reducing emissions is vital to achieving these objectives, deployment of methods to capture carbon dioxide from the atmosphere and storing it long-term, or carbon dioxide removal (CDR), is now considered an option. The potential of the Ocean to store carbon dioxide is substantial compared to land. Marine CDR methods are currently being explored and tested by publicly funded research and private entities yet the outcomes remain highly sensitive to subsequent human activities and the effects can be unpredictable due to the complexities involved. Subsequently, for marine CDR to be deployed responsibly, high-quality standards in terms of Monitoring, Reporting and Verification (MRV) will be required. MRV is essential to evaluate the efficacy and possible environmental impacts of the methods being tested in controlled field trials, and to assess if they are viable for future deployment at scale. Observing platforms combined with complex modelling methodologies, open data and future Digital Twins, combined with robust regulations, governance and international cooperation will all be required for informed MRV protocols for marine CDR. MRV is also crucial for ensuring that CDR deployments generate the promised climate benefits and for the transparent and ethical regulation of a growing carbon removal market. In Autumn 2023, the topic of MRV for marine CDR was selected by the European Marine Board (EMB) as a new Working Group topic. EMB Delegates highlighted that learning about the challenges for achieving robust, transparent and scientifically underpinned MRV frameworks for marine CDR, and how to overcome them, will help society and policymakers to make well-informed decisions for achieving climate goals at national, European and international level. The Working Group kicked-off in August 2024 with a meeting at the InnovOcean Campus (Ostend, Belgium) hosted by the EMB Secretariat. I am pleased to present this strategic document that highlights the need for robust MRV frameworks for marine CDR methods, which, if proven effective, could contribute to climate mitigation. It identifies current knowledge gaps, challenges and uncertainties in developing transparent and standardised MRV systems, and provides a detailed set of recommendations to policymakers and regulators, science funders and to those practitioners at the forefront of these endeavours. On behalf of EMB, I extend my gratitude to the Working Group Members for their collaborative effort in writing this document within such a remarkably short timeframe. I want to especially mention Helene Muri and Olivier Sulpis for their leadership, and the external reviewers and the experts at the EMB Member organisations for their constructive comments. Finally, I would like to thank the EMB Secretariat, in particular Ángel Muñiz Piniella and Ana Rodriguez, for the coordination of the Working Group from inception right through to publication. It is always appreciated. Fiona Grant Chair, European Marine Board November 2025 Foreword N° 13 2025 5 Table of Contents Foreword 4 Executive Summary 7 1. Introduction and scope 11 2. Marine CDR methods 13 2.1. Biotic mCDR methods 13 2.2. Geochemical mCDR methods 21 3. Key challenges for Monitoring, Reporting and Verification 24 3..1 CO2 and other greenhouse gases 24 3.2. Measuring additionality and establishing baselines 24 3.3. Durability - timescales of carbon removal 26 3.4 Life Cycle Assessments 27 3..5 Environmental impact 28 3.6. Co-deployment of mCDR methods 32 4. State of the Ocean carbon observing system and data capacities 34 4.1. Key variables for MRV for mCDR 34 4.2. Observing platforms and the state of the technology 34 4.3. Observing programs 35 4.4. Public databases, accessibility and usability 36 5. State of modelling capabilities 38 5.1. Modelling to inform monitoring, reporting and verification 38 5.2. Small-scale, mechanistic models 38 5.3. Marine ecosystem and food web models 39 5.4. Regional scale models 40 5.5. Global-scale and Earth System Models 40 5.6. Model intercomparison projects 41 5.7. Modelling applications for monitoring, reporting and verification 42 6. Status of MRV regulations and governance 43 6.1. General obligations for MRV for mCDR 43 6.2. Specific obligations 46 6.3. Project-based certifications 48 6.4. EU voluntary certification system 49 7. Existing MRV protocols and LCAs for mCDR and current knowledge gaps 50 7.1. Existing MRV protocols for mCDR 50 7.2 Integrating Life Cycle Assessments (LCAs) into MRV protocols 50 7.3. Knowledge required for MRV for mCDR 51 EMB FUTURE SCIENCE BRIEF 6 8. Overarching challenges and uncertainties for future MRV 53 8.1. Technical challenges and spatial-temporal variability: detection, measurements and models 53 8.2. Regulatory and governance gaps 54 8.3. Summary of uncertainties and challenges 54 9. Recommendations 58 References 60 List of abbreviations and acronyms 72 Glossary 74 Annex 1. Members of the European Marine Board Working Group on marine Carbon Dioxide Removal 78 Annex 2. Pillars of MRV for mCDR 79 N° 13 2025 7 Executive summary Meeting the goals of the Paris Agreement requires rapid and sustained reductions in greenhouse gas emissions, which is a critical priority. In addition, substantial amounts of carbon dioxide removal (CDR) from the atmosphere through human activities are included in scenarios of the Intergovernmental Panel on Climate Change (IPCC) to limit temperature increase to 1.5°C. Marine CDR (mCDR) methods could support reducing atmospheric CO 2 concentrations by leveraging the Ocean's capacity to absorb CO 2 . However, any implementation would require improved observations and understanding of all carbon flows affected by mCDR to ensure accurate accounting of net CO2 removal. Moreover, if mCDR methods are to be scaled-up to help reach climate targets, a robust, consistent Monitoring, Reporting and Verification (MRV) framework must be developed to ensure transparent, accurate and reproducible accounting of net CO2 removal and potential impacts of mCDR methods. This document hence focuses on MRV for mCDR methods. MRV is a comprehensive framework that quantifies net greenhouse gas removals, including CO2 and non-CO2 gases, relative to a counterfactual/baseline, assesses the durability of carbon storage, and evaluates uncertainties. MRV also encompasses Life Cycle Assessments (LCAs) of supply-chain emissions and resource use. MRV should also encompass the quantification of environmental and ecological impacts known as environmental MRV (eMRV). Robust MRV involves integrating observational and modelling methods across relevant spatial and temporal scales, provides transparent reporting of results, and enables independent third-party verification to support credible carbon accounting, governance and market mechanisms for mCDR. At present, all mCDR methods remain at early research or small pilot scale, with none yet demonstrated at large-scale deployment. Consequently, mCDR methods do not have sufficiently robust, comprehensive MRV in place to enable credible large-scale implementation. The MRV landscape remains fragmented, with jurisdictions at different stages of development and varying, overlapping protocols for different mCDR methods. Key MRV challenges include: accounting for greenhouse gases beyond CO2; defining baselines and additionality, where additionality refers to the CO2 removed by mCDR that would not have been removed from the atmosphere in the absence of mCDR; quantifying the duration of carbon storage; performing LCAs; evaluating environmental impacts; and addressing the co-deployment of different mCDR methods. The recommendations of this Future Science Brief highlight current knowledge gaps and the need to establish standardised MRV protocols for mCDR. This document aims to clarify the current scientific, technical and policy challenges that must be addressed to develop appropriate and reliable MRV for any future mCDR activities. It does not take a position on whether mCDR should be pursued. However, the development of robust, method-specific MRV protocols, demonstrated to detect, attribute, and verify net removals while transparently accounting for uncertainties in a manner suitable for policy and market use, is vital if mCDR approaches are to be scaled up or deployed alongside other methods. CDR is not a substitute for reducing emissions, but it may serve as a supplementary measure to help achieve the goals of the Paris Agreement. We recommend that rapid reductions in CO2 emissions remain the top priority in efforts to reach these goals. EMB FUTURE SCIENCE BRIEF 8 Further to this, we recommend: Recommendations for policymakers and regulators: (1) Develop a standardised, comprehensive, regulatory framework for MRV, to overcome the fragmentation, inconsistencies and lack of global governance of existing MRV systems; (2) Standardise the collection and reporting of mCDR MRV information across diverse regulatory fora, rather than relying on non-binding standards from private initiatives; 3) Develop regulations for baseline monitoring that cover both carbon and ecology (water chemistry, biodiversity, habitat). Use these baselines to establish additionality for MRV and to detect/attribute ecological effects, with pre-defined indicators and adaptive triggers; (4) Develop cost-effective, standardised and sustained long-term monitoring and observing systems for carbonate system variables that verify durability and net CO2 removal of mCDR, and complement these with modelling and machine learning when high-frequency or longterm measurements are not feasible; 5) Limit scaling and co-deployment of mCDR methods until MRV protocols for individual methods have been proven and assess changes in efficacy and the practicalities of undertaking robust MRV in co-deployment scenarios; and (6) Consider the requirements of key legislation, such as the Water Framework Directive, the Marine Strategy Framework Directive, the Nature Directives (Birds and Habitats Directives), the Nature Restoration Regulation, the Nitrates Directive and the Maritime Spatial Planning Directive, for the implementation and monitoring of mCDR methods in the European Union. Recommendations for national, European and philanthropic science funders: (7) Fund projects to establish baseline carbon fluxes and sinks, particularly those that support development of instruments allowing high-frequency, long-term, in situ carbonate system measurements. These baselines are essential for MRV, as accurate long-term data enhances the assessment of how different mCDR methods contribute to carbon storage; (8) Fund projects that produce observational data for the purpose of validating and refining models, particularly on deep-Ocean processes. Such projects will help fill critical gaps in our understanding of deep-Ocean dynamics, thereby enhancing the accuracy of models used for MRV for mCDR. This is essential for developing better strategies for possible deployment and understanding the potential impacts on marine environments; (9) Fund projects to investigate how biological processes respond to environmental change as part of MRV assessments, to ensure the direction and magnitude of these changes are acceptable and do not comprise Ocean health. Accurately assessing how biological processes adapt to environmental shifts will directly impact both the effectiveness and the sustainability of various mCDR methods; (10) Fund projects to close knowledge gaps on the long-term efficacy, environmental impacts and scalability of mCDR methods. This includes projects aimed at understanding the dynamics and fate of organic carbon and total alkalinity, providing insight into the effectiveness of mCDR methods in carbon storage and their impacts on overall carbon cycling; N° 13 2025 9 (11) Require transparent data-sharing policies, as well as open-access publications and project outcomes in all funded projects related to MRV and mCDR; (12) Support practical applications of real-world MRV for mCDR, to complement the fundamental research behind mCDR methods; and (13) Support multidisciplinary and trans-disciplinary MRV research projects that scope and map the regulatory landscape, while actively engaging stakeholders and local communities. These projects should involve a broad range of experts, promote collaboration and facilitate community involvement so that MRV projects benefit both society and the environment. Recommendations for MRV scientists, practitioners and project planners: (14) Establish robust local-, regional-, and large-scale baselines in terms of carbon fluxes and sinks to support quantification of additional carbon removal; (15) Quantify uncertainties in MRV protocols for CO2 removal across different scales, including instrumental precision, measurement accuracy, temporal and spatial variability, and model prediction fidelity; (16) Determine thresholds for unacceptable ecological and environmental side effects that would trigger policy or management response, such as the cessation or temporary suspension of a mCDR deployment. These thresholds should be set independently of method performance and should be integrated into broader cost-benefit or Life Cycle Assessments that weigh ecological risks against potential carbon removal benefits; (17) Quantify the durability of the CO2 removal, in addition to its magnitude, as part of MRV for mCDR methods. This involves assessing how long the captured CO2 will remain stored, quantifying uncertainty of such estimates, and the potential for any future release back into the atmosphere; (18) Establish how interactions between various mCDR methods being co-deployed may be credited within MRV and carbon removal accounting frameworks; (19) Conduct rigorous Life Cycle Assessments (LCAs) to quantify the net carbon removal effects through mCDR methods. This analysis should consider all stages, from production to longterm storage of carbon, to understand the carbon footprint and impacts of the mCDR methods employed; (20) Develop standardised environmental MRV (eMRV) guidance and baselines, including protocols, methods, Quality Assurance/Quality Control, and data standards for detecting and attributing ecological impacts and non-CO2 forcers; (21) Describe environmental and ecological risks in MRV assessments, at least qualitatively. Any potential risks to ecosystems and biodiversity should be considered alongside the benefits of carbon removal efforts and should be quantified where possible; and (22) Follow ethical principles and codes of conduct for research and prioritise funding from transparent sources. Scientists and practitioners should commit to being transparent (in terms of data - ensuring FAIR data stewardship, approaches and funding), be independent of funding bodies, and seek financial support from sources where the origin and purpose of the funds are clear, e.g. from the European Commission or national research councils. EMB FUTURE SCIENCE BRIEF 16 aquaculture and biotechnology could increase carbon capture efficiency and reduce operational costs for both deployment and monitoring. While techniques for measuring the carbon uptake are relatively well established, robust methods to determine carbon permanence remain underdeveloped (Rose & Hemery, 2023). Standardised MRV protocols and improved methodologies for quantifying carbon uptake and longterm storage still need to be developed. Macroalgae cultivation and sinking has been simulated in experiments using Ocean biogeochemical models, with and without extra nutrients being supplied by artificial upwelling (Wu et al., 2023). They demonstrated that while theoretically macroalgae cultivation and sinking has CDR potential, it leads to a large-scale reorganisation of nutrient fields with implications for primary production and the food webs it supports. Terrestrial biomass sinking, where organic material originating from land is transported and deposited into the deep Ocean for long-term carbon storage, represents a hybrid CDR approach, with removal occurring terrestrially but storage and permanence managed within the marine environment. Terrestrial biomass will mostly not sink unaided and delivery would require active transport and ballasting (or waterlogging) to depths (Chopin et al., 2024). The energy and materials used for collection, processing, offshore transport, and deployment must be included in the life cycle assessment (see Section 3.4) and MRV as operational and embodied emissions and totalled against gross CO2 removal. Although not strictly considered mCDR, its MRV requirements closely align with those of marine biomass sinking, due to shared challenges around carbon fate and permanence, and ecological impacts. Marine biomass for durable products and energy with long-term storage In marine Bioenergy with Carbon Capture and Storage (mBECCS), seaweed is converted to bioenergy with CO 2 captured and stored underground, offering a potential carbon removal pathway. Marine BECCS remains in early development and lags behind its terrestrial counterpart, which faces land and sustainability constraints (Beal et al., 2018; Smith et al., 2016). Carbon can be locked up in longlived products, where durability corresponds to product lifetime, potentially century-scale for some materials, or as compressed CO 2 stored geologically when bioenergy is paired with Carbon Capture and Storage (CCS), utilising long-term reservoir like saline aquifers or depleted petroleum fields. Alternatively, seaweed can be turned into long-lived materials such as bioplastics and construction composites, replacing fossilbased products (Nagarajan et al., 2024). Through pyrolysis, i.e. decomposition through high temperature and no oxygen, marine biomass can also be converted into biochar, a black carbon which can improve soil properties like nutrient retention. The carbon in biochar is stabilised in a long-lasting form, preventing it from returning to the atmosphere and effectively sequestering it in the soil for periods of centuries to millennia (Lehmann & Joseph, 2015). These marine biomass-based methods may offer a dual benefit of reducing atmospheric CO 2 levels and providing alternatives to fossil fuel-based products and energy. However, net removal hinges on the performance and availability of CCS infrastructure. CCS can be resource-demanding (energy, transport, compression), requires suitable storage sites and permitting, and adds monitoring and liability obligations; these factors should be reflected in the MRV and LCA (see Section 3.4). In addition, mechanical harvesting methods disturb marine habitats and lead to bycatch or habitat degradation if not managed responsibly. There are also concerns regarding the scalability, technical limitations, and environmental implications of the removal of nutrients from the Ocean or intensive cultivation practices (see section Biomass sinking above). Harvesting of Saccharina latissima by the Scottish Association for Marine Science (SAMS) at a research focused seaweed farm in Scotland. Macroalgae cultivation and sinking / using it for durable products are mCDR methods. Credit: Alasdair O’Dell. N° 13 2025 17 2.1.3 Ocean fertilisation Ocean fertilisation involves supplying nutrients key to phytoplankton growth, to increase biological CO2 fixation and thus enhance atmospheric CO 2 uptake by the Ocean. The carbon fixed by fertilisation is expected to be sequestered in the deep Ocean through the export of organic particles and their remineralisation at depth, potentially leading to storage over timescales of decades to centuries. However, as only a fraction of the produced organic carbon sinks deep enough to be stored long-term, the storage depends on sinking and remineralisation rates, to quantify the export efficiency into the deep Ocean. Fertilisation can occur through the addition of macronutrients, such as nitrogen and phosphorus, and/or micronutrients, such as iron (a process called Ocean iron fertilisation, OIF, or electrochemical Ocean iron fertilisation, eOIF, which uses electrochemical reactions to dissolve iron from inert electrodes directly into seawater), zinc or manganese (Sunda, 2012), or by relocating nutrients already present in the Ocean through artificial upwelling of nutrient-rich deep waters to the Ocean surface (see Section 2.1.4). As almost a third of the global Ocean is iron limited, OIF could be considered to have substantial geographical scope (Williamson et al., 2022). Successful OIF requires sites that have the right hydrodynamic, biogeochemical and ecological traits, but also carbon accounting technologies that can monitor these sites, e.g. satellite remote sensing and autonomous in situ water column monitoring (Williamson et al., 2022). Outdoor field trials of OIF, such as the Southern Ocean Iron RElease Experiment (SOIREE, Boyd & Law, 2001) and the Haida Gwaii project (Xiu et al., 2014), involved adding iron sulphate to specific marine regions, resulting in increased biological productivity. These trials highlighted the potential of Ocean fertilisation to boost carbon capture but were not designed to collect evidence of durable carbon storage (Smetacek & Naqvi, 2008). They also raised concerns about ecological impacts, disruptions to nutrient cycling and the longterm effects on marine ecosystems, such as induced deoxygenation (Yoon et al., 2018). Other unintended consequences, that are yet to be robustly demonstrated, include a decrease in mid-water oxygen due to organic matter decomposition, increased acidification of the Ocean interior, and the production of methane (CH 4 ) and nitrous oxide (N2O), which could counteract the effect of CO2 removal (Yoon et al., 2018). Compared to OIF, there is less interest in nitrogen and/or phosphorus fertilisation because the quantities of these nutrients needed to stimulate biological CO2 fixation are substantially greater, leading to significantly higher costs (NASEM, 2022). Although short-term biological responses to nutrient addition are relatively well understood, there is only moderate confidence in the overall efficacy of Ocean fertilisation as a long-term carbon removal strategy. Key scientific uncertainties remain around the rate and scale of influx of CO 2 from the atmosphere to the Ocean and the durability of carbon storage (Bach et al., 2023), as well as the scale and significance of potential ecological side effects (GESAMP, 2025). Biochar, a charcoal-like material derived from plant biomass, which can be added to soil to improve properties like nutrient retention. The carbon in biochar is stabilised in a long-lasting form, preventing it from returning to the atmosphere and effectively sequestering it for periods of centuries to millennia. Credit: Iqbal Farooz, Pexels EMB FUTURE SCIENCE BRIEF 18 2.1.4 Artificial upwelling Artificial upwelling (AU) seeks to enhance the Ocean’s natural nutrient cycles by pumping cold, nutrient-rich deep waters to the sunlit surface, thereby stimulating phytoplankton growth and amplifying the biological carbon pump to remove atmospheric CO 2 . The storage pathway mirrors Ocean fertilisation, where organic carbon is exported to depth with conversion to DIC in the Ocean interior, and with a small, buried fraction. First suggested by Lovelock & Rapley (2007), AU leverages both physical transport and microbial nutrient regeneration in deep waters to fertilise surface ecosystems. AU will require floating pipes or fixed structures to pump nutrientrich water from 100–300 m depth to the near-surface, which is not technologically feasible yet, so these methods are primarily conceptual for the time being. To be viable, AU will have to be implemented in lowto mid-latitude regions with nutrient-poor surface waters, particularly in coastal zones where upwelling already occurs. AU has been proposed in the context of macroalgae farming, to provide additional nutrients (Yue et al., 2025). The technical challenges of pumping water up from several tens to a few hundred metres depth are substantial, such as power consumption (Pan et al., 2018), and the few practical field trials could only endure operations for a few days in the challenging marine environment (e.g. White et al., 2010). Engineering research efforts aim to improve efficiency and robustness of AU devices, and test deployments continue, particularly in the context of macroalgae farming (Kimball et al., 2025) or wave energy conversion plants in coastal environments (Zhang et al., 2016). Reported designs span wave-driven pumps (White et al., 2010) to forced systems (Kemper et al., 2022). Energy demand (estimated to be up to 500 kilowatts) rises steeply depending on the density difference between source and discharge layers, and comprehensive LCAs of AU energy use are still lacking. Modelling studies indicate that any increase in surface Ocean CO 2 uptake (or drawdown) from nutrient supply is partly offset because upwelled water also carries respired DIC, which raises surface CO2 and limits the net effect (Oschlies et al., 2010a). Jürchott et al. (2023) found that AU’s effect on net oceanic CO2 uptake is strongly scenariodependent: changes in CO2 solubility in seawater (the physical solubility pump) and in the efficiency of the biological pump modulate the response. In their simulations, AU would be more effective in some regions when paired with Ocean iron fertilisation, because AU brings macronutrients and DIC to the surface, whereas iron limitation can still cap phytoplankton growth. AU could have an impact on Ocean stratification, salinity, and temperature, potentially disrupting Ocean circulation, possibly contributing to global warming (Oschlies et al., 2010b) and leading to disruptions of atmospheric dynamics and the hydrological cycle (Kwiatkowski et al., 2015). Additional impacts on marine biota would include the mechanical effects of pumping large volumes of water through industrial-scale structures, and the mixing of diverse ecosystems previously residing at different depths. Conversely, AU would bring cold deep water to the surface, which could cool the lower atmosphere, and this reduced air temperature could slow down soil and plant respiration, thereby increasing the net uptake and retention of CO2 in terrestrial ecosystems (Oschlies et al., 2010a). Water sampling to investigate a Lepidodinium chlorophorum (non-toxic) phytoplankton bloom in the Bay of Vilaine, France. Ocean fertilisation involves supplying nutrients key to phytoplankton growth, to increase biological CO2 fixation and thus enhance atmospheric CO2 uptake by the Ocean. Credit: Stefane Lesbats, Ifremer. N° 13 2025 19 2.1.5 Coastal Blue Carbon management Carbon is captured and stored by coastal vegetated ecosystems with rooted vegetation, such as mangroves, salt marshes and seagrasses (Figure 2.4) collectively referred to as Blue Carbon ecosystems. Carbon is stored in living biomass (shorter-lived) and as buried organic carbon in sediments, which can persist for centuries to millennia under stable conditions (Piñeiro-Juncal et al., 2025). These coastal vegetated ecosystems may account for half of the organic carbon stored in Ocean sediments (Macreadie et al., 2019), so restoring or creating new coastal ecosystems could increase carbon storage and lock away some atmospheric CO 2 as sedimentary organic carbon, which could be used for issuing carbon credits (see Box 1). However, this coastal sediment reservoir is vulnerable to erosion, drainage, trawling, or sea-level and storm impacts. Coastal wetlands such as mangrove forests, salt marshes or seagrass meadows have lost half of their global area coverage in the last century (Davidson, 2014), due to urban development, pollution and agriculture or aquaculture. Therefore, replanting and restoring these systems could produce organic matter and increase sedimentation. The EMB Policy Brief on Blue Carbon (European Marine Board, 2023) provides additional information on challenges and opportunities of using Blue Carbon to mitigate the climate and biodiversity crises. Coastal vegetated ecosystems can lock away carbon by trapping and burying calcium carbonate (CaCO 3 ) grains or by promoting the formation of CaCO3 , but this process also uses up alkalinity, part of the Ocean’s natural acid buffer, thus offsetting some CO2 removal (Fakhraee et al., 2023b). Conversely, when buried organic matter breaks down, whether by chemical dissolution of carbonates or by oxygenfree microbial decay, alkalinity is released back into seawater, restoring some of the Ocean’s buffering capacity (Fakhraee et al., 2023b). There is also the risk of other unintended consequences, such as emission of methane (Rosentreter et al., 2018), whilst environmental co-benefits could be shoreline protection from erosion and floods (Temmerman et al., 2023), and the creation of hotspots for fisheries and biodiversity. A variation to coastal restoration is planting vegetated ecosystems where there are none, an analogy to terrestrial afforestation. This could have unforeseen consequences to the species that already inhabit those habitats i.e., by disrupting a stable preexisting ecosystem, while simultaneously introducing a new one with potentially higher biodiversity (Sharma et al., 2017), and inappropriate hydrological conditions may hinder the plantation process (Wodehouse & Rayment, 2019). In addition, restoration or new planting of mangroves may encounter land tenure issues, e.g. in abandoned mariculture ponds (Song et al., 2023). Pilot test of a wave-pump for artificial upwelling in the Canary Islands, Spain. The green non-toxic dye was injected to follow the mixing and distribution of the deep water in the surface water. Artificial upwelling seeks to enhance the Ocean’s natural nutrient cycles by pumping cold, nutrient-rich deep waters to the sunlit surface, thereby stimulating phytoplankton growth and amplifying the biological carbon pump to remove atmospheric CO2. Credit: Michael Sswat, GEOMAR. EMB FUTURE SCIENCE BRIEF 20 Figure 2.4 Coastal restoration of Blue Carbon habitats is a mCDR method, where the carbon is stored in living biomass or buried organic carbon in sediments can persist for centuries to millennia under stable conditions. Blue Carbon habitats include mangrove forest (left), salt marsh (middle) and seagrass meadows (right). Credit: S. Baez, B. Bernal, J. Lefcheck, adapted from Christianson et al. (2022) (CC BY 4.0). Box 1. In-depth focus: Restoration of coastal Blue Carbon for carbon credits Globally Blue Carbon habitats have declined markedly over recent decades (Hilmi et al., 2021), though there are efforts to restore them. While there are large uncertainties, restoration, or even creation of Blue Carbon habitats, has limited contribution to CO 2 removal relative to global emissions (Macreadie et al., 2021; European Marine Board, 2023). However, they may be considered a favourable climate change mitigation approach, as they are generally relatively low-cost, low-regret, with the potential for significant co-benefits, such as biodiversity enhancement, coastal protection and pollution mitigation, as well as enhancing local livelihoods and employment (Friess et al., 2024; European Marine Board, 2023). There are significant ongoing efforts to map and quantify the coastal Blue Carbon inventory and storage potential in many parts of the world. A number of countries include measures like mangrove restoration in their Nationally Determined Contributions (NDCs) as part of the Paris Agreement (Bonotto, 2024), and this trend will continue in the updated NDCs in 2025. While there is potential to increase Blue Carbon stocks, knowledge gaps include quantifying the carbon removal potential and the significant challenges of monitoring to demonstrate additionality and durability of carbon storage (European Marine Board, 2023). These include difficulties in determination of carbon burial rates, the role of lateral carbon transport, fluxes of other GHGs and short-lived climate forcers like dimethyl sulphide (Szopa et al., 2023), and vulnerability to future climatic and non-climatic change (Williamson & Gattuso, 2022). As an example of restoration, in the USA, Virginia's coastal seagrass meadows (Zostera marina, or eelgrass) disappeared in the 1930s due to a combination of diseases produced by a marine slime mould and the impact of hurricanes. Small patches of natural regrowth were discovered in the 1990s, which led to a 20-year restoration project. Seagrass seedlings have been planted annually, and the project has been monitoring the increasing seagrass cover (Figure 2.5), water quality, carbon and nitrogen levels, as well as marine life such as scallops (Orth et al., 2020). The restored and actively managed meadows have improved water quality, increased marine life populations, and stored 5,000 tonnes of carbon accumulated over twenty years. The long-term monitoring including of the captured carbon has led to this project being issued carbon credits. N° 13 2025 21 Figure 2.5 Seagrass coverage along Virginia’s coast between 2001-2018 where green indicates very dense (>70%), and yellow very sparse seagrass coverage (<10%). Virginia's coastal seagrass meadows disappeared in the 1930s due to a combination of diseases and the impact of hurricanes. Since the 1990s, seagrass seedlings have been planted annually. The restored and actively managed meadows have improved water quality, increased marine life populations, and stored 5,000 tonnes of carbon accumulated over twenty years. Credit: Adapted from Orth et al. 2020 (CC BY-NC 4.0). 2.2 Geochemical mCDR methods Geochemical mCDR methods capture and store atmospheric CO2 through non-biologically mediated chemical processes. These methods are inspired by natural carbon cycles and chemical weathering of rocks on land that help regulate Earth’s climate over geological timescales. The geochemical capture and storage of CO 2 happens through the following mechanisms: atmospheric CO2 dissolves naturally in seawater, where it is in equilibrium with the other forms of DIC, bicarbonate (HCO 3 - ) and carbonate (CO 3 2 -) ions. Dissolved CO 2 represents about 1% of the total DIC in typical surface seawater. Over long timescales, i.e. months to hundreds of years, carbon can be incorporated into carbonate minerals through biologically mediated calcification and eventually contribute to sediment formation (Milliman, 1993). Over longer timescales (10,000–100,000 years), carbonate minerals become buried below the active surface layer of sediments and the carbon they contain enters the geological carbon cycle. The following sections explore a set of geochemical mCDR methods. 2.2.1 Ocean Alkalinity Enhancement The concept of Ocean Alkalinity Enhancement (OAE) is inspired by natural alkalinity production through the weathering of silicate or carbonate rocks on land that removes atmospheric CO 2 and, on geological timescales (> 100,000 years) compensates for CO 2 emissions from volcanic activity (Oschlies et al., 2025a). OAE uses various methods to enhance the oceanic capacity to take up CO 2 from the atmosphere by increasing the transformation of dissolved CO 2 into HCO 3 - and CO 3 2at the Ocean surface, therefore enabling more atmospheric CO 2 to enter the Ocean. When alkalinity in seawater increases, more of the dissolved CO 2 reacts into HCO 3 - and CO 3 2that remain dissolved for roughly 10,000–100,000 years. This exceptional durability arises when added alkalinity converts reactive CO2 into stable dissolved forms, which only re-enter the atmosphere once deep-Ocean carbon reservoirs and sedimentary carbonates reach equilibrium over hundreds of millennia. The stability of HCO3 - and CO3 2plays a key role in storing carbon over time and is essential for regulating the Ocean’s pH and buffering against Ocean acidification. When alkalinity is added to the surface Ocean, the air just above still has higher CO2, so CO2 molecules move from air to sea until the difference in partial pressure of CO 2 (pCO 2 ) shrinks. How fast this “air–sea CO 2 equilibration” happens depends mainly on wind and turbulence (how fast gas crosses the surface), how deep the mixed layer is, and the carbonate chemistry that buffers CO 2 in seawater. Several ideas have been proposed to increase the alkalinity of Ocean surface waters (Eisaman et al., 2023), such as “Ocean liming”, which uses industrially processed hydrated lime (a highly reactive and dissolving quicklime); the use of other alkaline substances such as silicate minerals or alkaline industrial wastes; or electrochemical methods that split seawater into an acid and base, and then removes the acids and leaves the bases behind to boost the Ocean’s ability to take up more CO2. Eisaman et al. (2023) suggest that OAE would be effective in removing CO 2 from the atmosphere. However, the shortand longterm environmental impacts are of major concern (Bach et al., 2019), especially if OAE were to change the marine system to be outside of its natural variability ranges. Large-scale (e.g. >1 gigatonne per year of finely ground mineral feedstock material added to the Ocean) deployment of OAE could raise suspended particulate matter in the Ocean by an order of magnitude, with potential impacts on filterfeeding organisms (Oschlies et al., 2025a). Furthermore, adding alkaline compounds changes carbonate chemistry in a multifaceted way and requires complex calculations of multiple interacting parameters to determine how much CO 2 is actually removed. Additional impacts can be due to the risk of inclusion of (potentially polluting or toxic) heavy metals from the mineral feedstocks or industrial by-products used to increase seawater alkalinity. Deployment of open-Ocean OAE at scale will require repurposed commercial or dedicated vessels for dispersion (Caserini et al., 2021), which could introduce additional environmental challenges, and the extraction and processing of the minerals that will be required for OAE would also need to be factored into the CO2 emissions associated with this mCDR method and the LCA that would be required EMB FUTURE SCIENCE BRIEF 22 Rhodamine red dye is used in Ocean Alkalinity Enhancement experiments to trace the distribution of added substances. Credit: Sarah Schumann. 2.2.2 Artificial downwelling Artificial downwelling creates a downward flow of upper Ocean waters to enhance the transport of both dissolved and particulate carbon to the Ocean interior, to enhance long-term carbon storage of the biological and solubility pumps (NASEM, 2022). Artificial downwelling has been proposed to tackle eutrophication and hypoxia in coastal regions (Stigebrandt et al., 2015) as the downward flow of water will also transport nutrients, oxygen, salt, heat and other properties (NASEM, 2022). Engineering approaches for artificial downwelling include various pump technologies (wave-powered, airlift and bubble pumps), salt-fountain systems to boost water density, thermohaline strategies using Ocean thermal energy conversion cold-water discharge, renewable-energy-driven pumps, and affecting salinity through controlled brine rejection. Each exploit different physical drivers, such as mechanical force, density inversion, or convective processes, to subduct CO 2 -rich water below the mixed layer. All these approaches remain at early development stages with limited field trials (Zhou & Flynn, 2005). They have never been tested in the context of mCDR nor in an open-Ocean environment (NASEM, 2022) but have been tested to oxygenate deep water (Stigebrandt et al., 2015). This method has been considered unreasonably expensive, and therefore not competitive for carbon storage (Zhou & Flynn, 2005). There is little literature specifically assessing artificial downwelling, therefore its efficacy, impacts and scalability is unknown. Another unknown is whether downwelled buoyant organic material will remain in the Ocean interior (NASEM, 2022), whether the return flow of upwelled waters (which must occur due to mass conservation) will lead to increased outgassing of CO2 to the atmosphere (Zhou & Flynn, 2005), and whether there will be a net increase in long-term carbon storage (NASEM, 2022). The return flow could also lead to unintended biological fertilisation as upwelled waters will bring nutrients to the euphotic zone. Artificial downwelling would also alter Ocean ecosystem structure and any benefits may cease upon the termination of the approach (NASEM, 2022). 2.2.3 Direct Ocean carbon removal Direct Ocean carbon removal aims to extract carbon from seawater in a designated facility, e.g. via electrochemistry powered by renewable energy. The CO2 extracted from seawater is stored underground in geological formations, mineralised into stable carbonates (solid phase), or used in products with a long lifetime (e.g. construction materials). CO 2 -depleted seawater is released out of the facility back into the surface Ocean, where it can absorb atmospheric CO 2 via gas exchange through the air-sea interface. However, because Ocean mixing and circulation continually exchange surface waters with deeper layers, the treated water remains in contact with the atmosphere for only days to weeks, preventing CO 2 levels from fully reaching equilibrium, and hence limiting net uptake. If the CO 2 extracted via direct Ocean carbon removal is used for short-lived products (e.g. synthetic fuels), the net result would be an increase in atmospheric CO2 at the expense of the depletion of the Ocean carbon reservoir. Therefore, long-term storage of the extracted CO2 is critical, as the Ocean already represents a durable storage system, and direct Ocean carbon removal must not lead to a net reduction in the durability of CO2 storage. It is important to note that direct Ocean carbon removal itself does not represent a mCDR method; but only the subsequent air-sea flux of CO 2 is climatically relevant N° 13 2025 23 Direct Ocean carbon removal pilot plant in Kona, Hawaii. Credit: Captura Corp. and counts as mCDR. This has implications for MRV, particularly for detection and attribution (see Section 3.1). Technically, direct Ocean carbon removal is based on the same geochemical principle as OAE but flips the sequence: it first acidifies a seawater stream to convert HCO3 - and CO3 2into CO2 gas, which is then vacuum extracted. The acidified water is immediately neutralised with the retained base so that when it’s released back to the Ocean, its overall chemistry, aside from the removed CO2, is unchanged. The electrochemical cells used for extraction consume less energy when operating on higher-salinity water, which is why direct Ocean carbon removal systems are often proposed to be co-located with desalination plants that supply concentrated brine feedstocks. There have been laboratory, modelling, prototypes and pilot plants for direct Ocean carbon removal (Eisaman, 2024). NASEM (2022) noted that a limitation to the scalability of direct Ocean carbon removal could be the renewable energy requirements. However, in principle, hydrogen could be a by-product from of direct Ocean carbon removal, which could incentivise the development of this mCDR method (Patterson et al., 2019). As for possible side effects of direct Ocean carbon removal, it could pose a range of environmental risks, including shifts in seawater chemistry, unintended ecological disturbances, and by-product releases. Key concerns include acid–base imbalances, nutrient perturbations, energy and brine discharges, toxic by-products and governance gaps (Niffenegger et al., 2023). EMB FUTURE SCIENCE BRIEF 24 3.1 CO2 and other greenhouse gases Marine CDR methods primarily focus on removing and sequestering CO2 from the atmosphere. However, they can also lead to the production or mitigation of other greenhouse gases (GHGs), such as methane (CH 4 ) and nitrous oxide (N 2 O). Beyond these non-CO 2 GHGs, short-lived climate forcers such as dimethyl sulphide (DMS) can also be affected by mCDR and should be considered in environmental MRV (eMRV) where relevant (see Section 3.5). Establishing a standard approach to integrate the impacts of CH 4 and N 2 O alongside CO 2 emissions is necessary, yet challenging, as it involves sophisticated analytical methods and robust datasets. CO 2 -equivalent (CO 2 eq) is often used to compare the climate impact of the different gases by expressing their effects in terms of the equivalent amount of CO 2 over a defined time scale (usually 100 years). Because of the atmospheric lifetimes of the different GHGs (e.g. about 12 years for CH4, and about 120 years for N2O), the same CO 2 eq can yield very different climate effects. For mCDR, using CO 2 eq can provide a more accurate representation of the net climate impact by integrating emissions of CH4, N2O and other GHGs, which may offset or complicate the benefits of CO 2 removal. For example, CH 4 has a global warming potential 27 - 30 times higher than CO 2 over a 100-year period (Forster et al., 2023). In the Ocean, CH4 can be produced through biological processes, particularly under low-oxygen conditions that may arise with certain mCDR methods. N2O has a global warming potential about 273 times higher than CO 2 over a 100-year period and can be produced by marine microbial processes in low-oxygen, nitrogen-rich environments. Therefore, measuring the full impact of mCDR methods requires precise tracking of various GHGs produced or mitigated by the methods used. The production of CH 4 and N 2 O as by-products of Ocean fertilisation, for example, complicates MRV because of their different global warming potentials and the difficulty in measuring them accurately in marine environments. CH4 measurement is especially complex due to its potential production in low-oxygen zones, which are difficult to monitor consistently. Accurately measuring N 2 O is challenging due to its sensitivity to microbial nitrogen cycling, a process highly sensitive to oxygen levels and influenced by Ocean fertilisation. Detection and attribution are established concepts in climate science (Stott et al., 2010). For the purpose of MRV for mCDR (Figure 3.1), detection and attribution mean showing that a measurable change in e.g. air-sea CO 2 flux, other greenhouse gases, Dissolved Inorganic Carbon (DIC), pH or an ecological indicator, occurred due to the implemented mCDR method, i.e., beyond natural variability. Attribution evaluates how much of that change was caused by the mCDR activity versus other drivers, e.g. weather, currents, background trends, and gives the confidence in that assignment. In practice, this requires preregistered designs (e.g. impact-reference comparisons, before-aftercontrol-impact), adequate sampling power (from Observing System Simulation Experiments or OSSEs, see Section 5.7), and multiple lines of evidence (in situ sensors, tracers/isotopes and models). Together, detection and attribution allow MRV to distinguish mCDR effects from background variability and to quantify net atmospheric CO2 removal with a range of uncertainty around the estimated value. Marine CDR methods like Ocean fertilisation promote phytoplankton blooms to increase particulate organic carbon (POC) and dissolved organic carbon (DOC) but verifying this production requires deploying sediment traps or optical sensors across vast, often inaccessible Ocean regions, making continuous measurement difficult (Buesseler et al., 2024). Additionally, because only a fraction of produced POC and DOC sinks deep enough to be sequestered long-term, which depends on sinking rates and remineralisation, reports should combine surface biomass increases with observation-derived export efficiency estimates to avoid overestimating net carbon removal. A more detailed discussion on observing systems for MRV is presented in Chapter 4. 3.2 Measuring additionality and establishing baselines Ensuring additionality is fundamental to regulating mCDR methods. To deliver net carbon removal, mCDR methods must demonstrably remove more carbon than would be removed without it (i.e. additionality, see Figure 3.1). This requires robust calculation of the amount of carbon the Ocean would store without the mCDR method (i.e. baseline stored carbon, see Figure 3.1). As noted by Visser (2025), imprecise use of ‘sequestration’ risks counting natural biological carbon pump turnover as climate-relevant removal; baselines must explicitly exclude this natural turnover to demonstrate additionality. Baselines for mCDR can be defined at different spatial and conceptual scales, each serving distinct purposes. At the deployment scale, baselines describe the local conditions before the intervention, enabling MRV to demonstrate that additional carbon has been removed and stored. Counterfactuals describe the theoretical baseline conditions, often modelled using pre-intervention data, that would have existed without the intervention. At wider local to regional scales, baselines can capture counterfactual system behaviour to assess potential displacement effects, e.g. whether an Ocean iron fertilisation (OIF) deployment at one location reduces productivity and carbon uptake elsewhere. At the global scale, baselines underpin tracking of changes in the global carbon sink over time, supporting climate science objectives such as the global carbon budget. While not directly linked to mCDR MRV, these global 3Key challenges for Monitoring, Reporting and Verification N° 13 2025 25 Credit: EMB based on a concept by Olivier Sulpis. reference points provide important context for understanding cumulative changes from both climate change and mitigation interventions. In this document, baselines and counterfactuals are used interchangeably. In climate mitigation accounting, emission reductions refer to actions that avoid or reduce the release of GHGs into the atmosphere compared to a baseline, whereas CDR refers to human activities that actively remove CO 2 from the atmosphere and store it for a climaterelevant period. Some mCDR methods, such as coastal restoration, can do both: an avoided-emissions component from preventing carbon loss and a removal component from new carbon uptake. Robust MRV must quantify each component separately and apply consistent baselines to ensure transparency and prevent double accounting. Baseline measurements are hence important for regulators to distinguish between carbon removal and emissions reductions. For example, restoring marine ecosystems within a country’s Exclusive Economic Zone (EEZ) might be classified as emissions reduction rather than carbon removal, depending on the baseline applied. If the baseline assumes historical and continued degradation (and associated CO2 emissions) of those ecosystems, then restoration merely avoids these emissions, classifying it as an emission reduction. By contrast, if the baseline assumes stable, non-degrading ecosystems, then any additional carbon stored through biomass expansion would qualify as a carbon removal. Misclassification could lead to double accounting in national climate inventories, allowing countries to overstate their climate mitigation performance and potentially undermine the credibility of their reported contributions (Mengis et al., 2023), or the sale of carbon removal credits which then become meaningless within the voluntary carbon market. However, establishing baselines is highly complex due to the dynamic and variable nature of oceanic carbon fluxes, which are influenced by circulation, mixing and spatially decoupled storage processes (Mengis et al., 2023). The impacts on marine ecosystems from historical anthropogenic activities and ongoing climate change further complicate baseline determination. The selection of a reference ecosystem state to guide restoration efforts is key and involves decisions with significant ecological and regulatory implications. The spatial disconnect between carbon removal and storage (see Section 3.3) raises contentious questions about equity and justice in the allocation of carbon removal credits. This spatial disconnect is two-fold. On the one hand, there is often a geographical difference between where the CO2 is removed from the atmosphere and where it is ultimately sequestered, due to the dynamic nature of Ocean biogeochemical processes. On the other hand, the entity paying for the removal activity may be spatially disconnected from the activity itself. For example, a high-emission country such as Germany might claim credit for climate mitigation resulting from an intervention whose sequestration benefits are realised in the Global South, raising questions about the equitability of the practice. This highlights the justice and equity dimensions that will have to be taken into consideration when developing national and international MRV for mCDR and corresponding regulatory frameworks (Berger et al., 2024). Detection/ attribution Durability Additionality mCDR Stored Carbon Baseline Additional steps for eMRV Non-CO2 greenhouse gases Biological indicators Time CO2CO2 MRV steps for mCDR Figure 3.1 Main components essential for Monitoring, Reporting and Verification (MRV) of mCDR. The different components are explained in this chapter. EMB FUTURE SCIENCE BRIEF 32 3.6 Co-deployment of mCDR methods The (un)intended co-deployment of mCDR methods is a challenge when undertaking robust MRV for mCDR. Examples of intentional co-deployment include electrochemical iron fertilisation and OAE, which could alleviate Ocean acidification as a co-benefit (Taqieddin et al., 2024), Artificial upwelling (AU) to support scalable open Ocean macroalgae farming (Wu et al., 2023), and the dispersal and subsequent burial of alkaline-coated buoys made from terrestrial biomass with macroalgae seedlings attached to the buoys, a strategy that was trialled by a mCDR start-up called Running Tide that has since ceased operations 2 . An example of unintended co-deployment is OAE via dissolution of silicate rocks, which may have secondary fertilisation effects by releasing iron (Bach et al., 2019). Co-deployment of mCDR methods will increase the number of confounding factors leading to increased uncertainty around the efficacy and impacts of the methods (Vivian et al., 2024). Measuring the net effect of more than one mCDR method on carbon uptake and storage will require more parameters to be measured over larger spatio-temporal scales, as the timescales of influence are likely to differ for the different methods. For example, for OAE via dissolution of the mineral olivine (a silicate mineral), measurements of seawater carbonate system parameters may be sufficient to quantify net carbon uptake, if supported by modelling and statistical methods (Ho et al., 2023). However, assessing its unintended iron fertilisation effect would need additional biogeochemical monitoring, such as nutrient (nitrate, phosphate) and iron‐specific sensors, alongside chlorophyll measurements using both in situ samplers and satellite Ocean-colour imagery across meso-scale patches (1,000–10,000km²) and over periods of weeks to months (Buesseler et al., 2024). The combination of a global deployment of AU and OIF may yield great potential, by removing iron-limitation, however it might have negative impacts on the Ocean oxygen and nitrogen content (Jürchott et al., 2024). In addition, the thermal perturbation of the upper Ocean could alter the energy and moisture balance in the atmosphere, leading to changes in terrestrial ecosystems and thus carbon reservoirs (Keller et al., 2014). If mCDR were to be scaled up, distinct mCDR methods will also likely interact with other uses of Ocean space, such as fisheries and aquaculture. Intentional co-deployments should be limited until MRV protocols for individual methods have been tested and proven to be effective. It is critical to address the knowledge gaps in the assessment of changes in efficacy and the practicality of undertaking robust MRV in co-deployment scenarios prior to any co-deployments. 2 https://19987014.fs1.hubspotusercontent-na1.net/hubfs/19987014/docs.runningtide.com%20files/Quantification%20Methodology%20v1.6.0_vPublic.pdf N° 13 2025 33 A bloom of coccolithophores in the Barents Sea on 13 July 2022, captured by the Ocean and Land Colour Instrument (OLCI) aboard the Copernicus Sentinel-3B satellite. Marine CDR methods could shift plankton diversity and abundance and affect calcifying plankton communities, such as coccolithophores, with knock-on effects on the ecosystem. Contains modified Copernicus Sentinel-3 data (2022), processed by EUMETSAT. Credit: Ben Loveday. EMB FUTURE SCIENCE BRIEF 34 4State of the Ocean carbon observing system and data capacities 4.1 Key variables for MRV for mCDR To support robust MRV for mCDR, including the assessment of additionality and durability, it is essential to monitor key variables that help establish a baseline and attribute observed changes to mCDR methods. The selection of observational variables and design of monitoring strategies must be tailored to the specific mCDR method, deployment context, location and monitoring objectives. The sea surface concentration or partial pressure of CO 2 (pCO 2 ) is an essential variable that drives the direction of air-sea CO2 exchange. When the pCO2 in seawater is lower than that in the overlying atmosphere, it creates a concentration or pressure gradient that promotes the uptake of CO 2 by the Ocean. The Ocean’s ability to buffer carbon in its inorganic form is governed by the concentration of dissolved CO 2 products (total dissolved inorganic carbon or DIC, i.e., dissolved CO 2 , HCO 3 - and CO 3 2-) , seawater pH, and the total alkalinity (TA). These four variables of the seawater carbonate system are therefore essential for monitoring the Ocean’s long-term CO2 storage capacity for inorganic carbon. At least two of these four variables (pCO2, pH, DIC, TA) must be measured to fully characterise the seawater carbonate system; measuring only one is insufficient (Zeebe, 2012). Furthermore, measurements of CH4 and N2O complete the observing system for the most important greenhouse gases (GHGs). Monitoring additional variables, such as dissolved organic carbon (DOC) and particulate organic carbon (POC), is required to determine baselines and assess environmental and ecological impacts. POC plays a crucial role in carbon export from the euphotic zone—the upper layer of the Ocean with enough sunlight for photosynthesis—to the Ocean floor. For both DOC and POC, understanding bioavailability and recycling rates is key, as CO 2 can be rapidly respired back into dissolved components. Dissolved inorganic nutrient concentrations, oxygen levels and trace metals should also be monitored to assess environmental and ecological consequences of mCDR (i.e. for eMRV). Where relevant, eMRV should include monitoring of short-lived climate forcers (e.g. DMS) and non-CO2 GHGs, such as CH4 and N2O, and their sea-air fluxes to capture responses of short-lived climate forcers (see Section 3.5). Finally, remote estimates of biomass and primary productivity should be used to assess large-scale ecological effects of mCDR as well as to monitor shifting ecological baselines. Monitoring these variables helps detect unintended environmental side effects, informs adaptive management strategies, and ensures that mCDR methods do not undermine Ocean health or ecosystem services. While some variables, such as sea surface pCO 2 and air-sea CO 2 flux, are broadly relevant across methods, others are approach-specific. For example, full seawater carbonate system parameters may be essential for Ocean Alkalinity Enhancement (OAE) but may be less critical for macroalgal sinking, where monitoring may instead focus on biomass quantification, fate tracking and carbon durability. However, understanding of the air-sea CO2 fluxes in this case may be needed to confirm the additional removal of CO2 from the atmosphere, and to measure any unexpected cascading feedbacks affecting additionality (Bach et al., 2021). Similarly, in Ocean fertilisation, monitoring deep Ocean carbon fluxes and air-sea exchange may be more relevant than DOC/POC measurements in the surface layer. Therefore, MRV design should begin with a clear articulation of the carbon removal mechanism and associated risks, followed by a fit-forpurpose observation strategy that supports additionality, durability and environmental safeguards. See Annex 2 for a suggestion on the minimum metrics, study designs and reporting elements needed to build up and support robust MRV for mCDR. 4.2 Observing platforms and the state of the technology There are multiple ways of observing the Ocean (Figure 4.1). In situ measurements are key to monitoring changes in seawater chemistry and identifying the drivers behind these changes. However, the spatio-temporal heterogeneity of the Ocean requires multiple monitoring strategies. Discrete measurements taken during repeated oceanographic sections or transects on research or commercial vessels can provide insights from annual to decadal scales across Ocean basins. Continuous time-series measurements at fixed locations, e.g. on moorings, capture monthly to interannual variability in specific regions. High-frequency continuous measurements using sensors on platforms, such as gliders, floats, and surface and subsurface robotic vehicles, offer finer resolution and better spatial coverage, which could allow the capture of episodic events that impact seasonal and interannual variability that might be missed with discrete measurements. It is crucial to building on these established methods while embracing innovation and new technology to improve efficiency and coverage. New sensor technology and platforms are continuously being developed to fill the current measurement gaps at various timescales. N° 13 2025 35 4.3 Observing programs To observe the testing and potential future deployment of mCDR, we still lack globally coordinated and sustained observing programs tailored to the needs of this new and emerging field. The pursuit to understand the Ocean as a carbon sink has led to the foundation of global observing programs and coordination efforts that can serve as best practice for future mCDR observing programs. The Global Ocean Observing System 3 (GOOS), established by the Intergovernmental Oceanographic Commission (IOC) of UNESCO4, plays a pivotal role in coordinating global Ocean observation efforts. GOOS aims to address global needs for better climate change forecasting, efficient management of marine resources, disaster mitigation and the sustainable use of coastal and oceanic zones. It also supports the monitoring of Essential Ocean Variables 5 (EOVs), such as inorganic carbon, using innovative technologies like biogeochemical sensors and autonomous profiling floats. By coordinating international efforts, GOOS enhances our ability to collect and share high-quality data, providing key insights into Ocean health and guiding effective marine resource management decision-making. Emerging sensors, autonomous platforms and data integration tools have the potential to enhance long-term monitoring, reduce operational costs and capture processes at higher spatio-temporal resolution. Such developments complement existing observation strategies and are essential for sustaining standardised, cost-effective and long-term monitoring efforts . In addition to in situ measurements, satellite and autonomous sampling methods are also important. While the variables of the seawater carbonate system (pCO2, pH, DIC, and TA) cannot be detected remotely, satellites can provide valuable sea surface chlorophyll concentration, temperature, salt content and Ocean circulation data, which help in understanding the distribution of carbon in the Ocean. Moorings Satellites Commercial vessels Repeated oceanographic sections Research cruises Surface vehicles Gliders Floats Satellites Repeated oceanographic sections Research cruises Surface vehicles Gliders Floats Moorings Pacific Anthropogenic Carbon Between 1991 and 2017 Global Biogeochemical Cycles, Volume: 33, Issue: 5, Pages: 597-617, First published: 29 April 2019, DOI: (10.1029/2018GB006154) Figure 4.1 Visualisation of how different observing systems contribute to the multi-scale monitoring required for MRV for mCDR, adapted from Andrea Fassbender (NOAA PMEL). Ocean carbon monitoring platforms (top row) each have their own respective observational coverage across spatial (metres to global scale), temporal (hours to decades), and depth (surface to >4 km) dimensions (bottom 3D graph). Adapted from Andrea Fassbender (NOAA PMEL), with images from Poseidon System, HCMR; ESA/Mlabspace; Brittany Ferries; Carter et al. (2019); IEO-CSIC; Alberto Dallolio, NTNU; Balearic Islands Coastal Observing and Forecasting System (SOCIB); Olivier Dugornay/Ifremer. Commercial vessels 3 https://goosocean.org/ 4 https://www.ioc.unesco.org/ 5 https://goosocean.org/what-we-do/framework/essential-ocean-variables/ EMB FUTURE SCIENCE BRIEF 36 Ocean observing networks within GOOS include ARGO6, Voluntary Observing Ships7, GO-SHIP8, OceanSITES9, Ocean Gliders10, and others. In addition to in situ efforts, satellite missions, such as GOSAT11, SENTINEL12 and PACE13 provide essential, free and publicly open marine data covering the surface of the global Ocean. Historical observing programs offer invaluable insight for MRV for mCDR, as they provide crucial data on measurement quality, uncertainty, and best practice guidelines (Dickson et al., 2007). Several long-term observing programs, such as Voluntary Observing Ships, GO-SHIP, and ARGO, have received significant funding and support from the USA. Ensuring the continued support for such long-term observing programs, via international cooperation, and across successive administrations, is essential for mCDR and MRV. At the European level, the Integrated Carbon Observation System14 (ICOS) is a research infrastructure that supports climate science and policy by monitoring GHGs, including carbon in the Ocean. With 28 stations in eight countries, using commercial ships, buoys and research vessels, ICOS data includes the four key seawater carbonate system variables: pCO2, pH, TA and DIC, though coverage varies by site and platform (see Section 4.1). While global observing systems such as GOOS are foundational for understanding long-term Ocean trends, supporting climate models, and informing global carbon budgets, they are not sufficient on their own to support MRV for mCDR at the scale of individual deployments or pilot projects. Robust MRV at the project scale requires highresolution, site-specific observations that capture localised changes in carbon fluxes, ecosystem responses and water mass movement. This requires targeted deployments of autonomous vehicles, sensor arrays, moorings and/or ship-based sampling in the vicinity of the mCDR deployments. These local observational strategies must be designed to measure changes relative to a pre-defined baseline, detect signals from the intervention amid natural variability and verify modelled storage outcomes. In this sense, global observing programs provide the necessary context, long-term stability and best practice guidelines, while local and regional observing systems must be developed (and adapted if possible) to directly support MRV efforts as mCDR methods are tested and deployed. 6 https://argo.ucsd.edu/ 7 https://community.wmo.int/en/voluntary-observing-ship-vos-scheme 8 http://www.go-ship.org 9 https://www.ocean-ops.org/oceansites/ 10 https://www.oceangliders.org/ 11 https://earth.esa.int/eogateway/missions/gosat 12 https://sentinels.copernicus.eu/ 13 https://pace.gsfc.nasa.gov/ 14 https://www.icos-cp.eu/ 15 https://glodap.info/ 16 https://socat.info/ 17 https://memento.geomar.de/ 18 https://globalcarbonbudget.org/ 4.4 Public databases, accessibility and usability Community-driven efforts to promote open data systems have led to significant advancements in understanding climate change and marine carbon dynamics. Measurements obtained through different observing programs have been collected and unified in public databases, such as the Global Ocean Data Analysis Project 15 (GLODAP) for interior Ocean biogeochemical observations of seawater carbonate system variables, such as DIC and TA, the Surface Ocean CO 2 Atlas 16 (SOCAT) for surface Ocean pCO2, and the GEOMAR Memento database17 for interior Ocean CH 4 and NO 2 measurements. These databases provide a foundation for studying the natural carbon cycle and its variability over time, thus enabling scientists to build background or baseline concentrations of the essential monitoring variables. The combination of these databases allows the marine carbon cycle community to study and track changes, which is critical for assessing the ongoing impacts of climate change (Friedlingstein et al., 2025). For MRV, measurements need to be of a high standard, must be traceable and undergo routine intercomparisons and audits. For seawater carbonate variables, the JPI Oceans Ocean Carbon Capacities roadmap recommends: (i) establishing a European Hub for certified reference materials for measurements of the seawater carbonate system to reduce the current single-supplier risk (García-Ibáñez et al., 2025); (ii) implementing regular audits of Europe's surface-Ocean CO 2 observing system with clear assessment tools; and (iii) making better use of research and commercial vessels to reverse recent declines in surface CO 2 observations and ensure consistent delivery to SOCAT and the Global Carbon Budget 18 . These actions would strengthen data reliability and improve MRV traceability for mCDR. As mCDR progresses toward deployment and regulation, Findable, Accessible, Interoperable and Reuseable (FAIR) data should be mandatory for project approval and inclusion in national or international carbon inventories. Data collected for the purpose of MRV should be made publicly available in standardised, interoperable formats and deposited in accessible repositories such as the community-accepted databases above. This approach will enable independent verification and quality control, best practice guidance, support cumulative learning across projects, and foster public and stakeholder trust in reported carbon removals. As mCDR methods scale up, adherence to FAIR data principles will be essential to enable coordinated international oversight and avoid fragmented or proprietary reporting that could undermine the credibility of carbon accounting. N° 13 2025 37 Photo credits: Elisabetta Campiani, CNR-ISMAR (top); Christoffer Engstrom, Unsplash (middle); Mišo Pavičić, IZOR (bottom). The VLIZ underway system installed on the research vessel R/V Simon Stevin, measuring the concentration of the greenhouse gases CO2, nitrous oxide (N2O) and methane (CH4) and Total Alkalinity in seawater. Credit: VLIZ, ICOS Group. EMB FUTURE SCIENCE BRIEF 38 5State of modelling capabilities 5.1 Modelling to inform monitoring, reporting and verification A model is a simplified representation of a natural system that helps understand, predict and analyse complex (environmental) processes. Models can be used to support the quantification of the Ocean’s role in the global carbon budget and can provide insights into processes relevant to mCDR. Models can help evaluate the efficacy, scalability potential and storage durability of different mCDR methods, and are particularly useful for identifying and understanding potential (un) intended environment impacts, co-benefits and cascading feedbacks. In this chapter, only numerical models are covered, but physical models used to better understand mCDR methods, such mesocosms, are briefly described in Box 2. Different modelling tools and approaches are used to address various facets of MRV for mCDR. They can range from very localised, highresolution models (on the order of micrometres to millimetres) to global-scale Earth System Models (ESMs), which include representations of the Ocean, land, atmosphere and cryosphere (i.e. the Earth's frozen water, including snow, ice, glaciers, permafrost and sea ice). Higher-resolution, small-scale models tend to describe processes mechanistically, meaning that they explicitly represent the underlying physical, chemical or biological principles governing a process. Conversely, lower-resolution, large-scale models tend to be empirical or statistical, and hence they rely on established relationships between predicted variables and observed data. This diversity of scales and modelling tools is required to support different aspects of MRV, including: (i) predicting alkalinity generation, biomass growth and mineral dissolution relevant to MRV at immediate intervention sites; (ii) assessing atmospheric CO 2 removal efficiency relevant to MRV across local-regional scales and beyond deployment locations; and (iii) evaluating local and non-local ecological and environmental impacts spanning a broad spatio-temporal range. An overview of the current state of modelling approaches relevant for mCDR and MRV is provided below, ranging from process-level models to global ESMs (see also Figure 5.1). 5.2 Small-scale, mechanistic models Models that focus on fine-scale physical, chemical, and biological processes are relevant to mineral dissolution, alkalinity enhancement and biomass growth for mCDR. For Ocean Alkalinity Enhancement (OAE), it is useful to predict the process of alkalinity generation itself, often through mineral dissolution, because it is not instantaneous and is associated with biogeochemical feedbacks at a microscopic scale. The most simplistic of these models are shrinking-core models, able to predict the dissolution of spherical grains of a known initial diameter (Lindman & Simonsson, 1979), assuming that the dissolved by-products mix in the surrounding water. For more complex shapes, more computationally costly 3D models can be used, which can simulate hydrodynamic effects, chemical reactions across heterogeneous grain surfaces and transport limitations (Sulpis et al., 2022a). Mineral dissolution immediately alters water chemistry around the dissolving grains, which may induce the precipitation of authigenic mineral phases (i.e. minerals that precipitate or recrystallise in situ within sediments, forming directly where they are found rather than being transported there), the clogging of sediment pores, or fuel microbial activity (Fuhr et al., 2022). These effects may enhance or reduce the net alkalinity release from mineral dissolution (Moras et al., 2022) and need to be resolved to predict how much alkalinity is being released in seawater. For OAE methods where mineral dissolution happens in the seabed, diagenetic sediment models can be used (i.e. models that describe what happens to the sediment after it settles on the seafloor) (Sulpis et al., 2022b). Such models predict how freshly deposited sediments chemically and physically transform over time as they become buried, through reactions like mineral dissolution, cementation, compaction and microbial breakdown. For methods where dissolution takes place when minerals are suspended or settling through the water column, particle-settling models are used. The models simulate the deployment of minerals at the Ocean surface for OAE purposes, and the subsequent dissolution, settling through the water column, (dis)aggregation, and effects on grazing and organic matter consumption (Fakhraee et al., 2023a). They do not predict mCDR but provide a quantitative basis for the alkalinity generation rates of OAE methods, considering the immediate feedback mechanisms that alter OAE efficiency. For biotic mCDR methods, small-scale models of macroalgae cultivation and phytoplankton productivity are critical for understanding carbon uptake efficiency, nutrient interactions, and physical constraints. Macroalgal growth models, such as the Floating Macroalgal Growth and Drift Model (FMGDMv1.0) (Zhou et al., 2021), simulate macroalgae productivity based on light-dependent photosynthesis, temperature-dependent enzymatic processes and nutrient uptake, and they also take into account light penetration, self-shading and water mixing, which can affect photosynthetic activity (Hurd, 2000). Finally, particle-based biomass settling models track the behaviour of detached macroalgal fragments as they sink and degrade in the deep Ocean, playing a crucial role in assessing the N° 13 2025 39 Figure 5.1 Graphic illustrating examples of how modelling can be used for MRV from mechanistic to Earth System scale models (blue arrow), with some examples of model outputs relevant to MRV (purple arrow). Figures modified from Sulpis et al. (2022), Wang et al. (2025), Baker et al. (2022), Tagliabue et al. (2023), Met Office (2013) Reprinted with permission © Crown Copyright 2013, data supplied by the Met Office. Credit: EMB based on a concept by Chelsey Baker. long-term storage potential of macroalgae-based mCDR strategies. Wu et al. (2023) used such models to simulate macroalgae cultivation and sinking, highlighting the redistribution of nutrients and potential large-scale ecological impacts. Thus, for MRV, models on scales from micrometres to metres are useful for predicting realistic alkalinity release rates from mineral dissolution, biomass growth rate and carbon export in the context of coastal restoration, offshore macroalgal cultures and Ocean fertilisation. Micrometreto metre-scale process models simulate the dissolution of specific minerals (e.g. olivine, calcite) under varying temperature, pH and flow conditions to predict real time alkalinity release rates, guiding the placement and frequency of in situ water chemistry sensors needed for accurate monitoring. They also model local biomass growth and particulate organic carbon (POC) production for coastal restoration or macroalgal farms, informing the design of sediment traps and optical sensors to quantify export fluxes with sufficient spatial resolution (Ho et al., 2023). To predict induced airsea CO 2 fluxes, and environmental and ecological repercussions, larger-scale models are needed (see sections below). Mechanistic Local-regional Basin-scale Global Earth System • Alkalinity release • Biomass growth • Plume tracking • Air-sea CO₂ flux • Counterfactual determination • Durability • Broad-scale environmental impacts • Durability • Additionality issues via feedbacks on other carbon sinks Figure X Andant lia pari ducillaut expel ipsam sit, sa volo ex eatias venet omnis atempos dolecatet. Credit: Sulpis et al. (2022), Wang et al. (2025), Baker et al. (2022), Tagliabue et al. (2023), Met Office (2013) Reprinted with permission © Crown Copyright 2013, data supplied by the Met Office. 5.3 Marine ecosystem and food web models Marine ecosystem and food web models are relevant to any mCDR methods that may alter or interact with marine biota. They can represent biotic life from phytoplankton to fish, to marine mammals and birds, and can range in geospatial scale from specific locations, such as a kelp forest in the California current region (Vilalta-Navas et al., 2018) to global-scale explorations of phytoplankton diversity (Dutkiewicz et al., 2020). These models vary in complexity and can represent different characteristics, behaviours and processes including, but not limited to, marine biodiversity, adaptive responses and acclimation of marine organisms, population dynamics, physiological traits and responses to anthropogenic drivers, as highlighted in the EMB Future Science Brief on marine ecosystem modelling (Heymans et al., 2018). There are a diverse range of marine ecosystem models that could be applicable to mCDR, particularly in terms of understanding the impacts of mCDR perturbations and how they may cascade through the food web. Marine ecosystem models could provide a useful testbed to understand how the ecosystem may respond to mCDR perturbations. For example, kelp forest models can simulate responses to different growth and seabed deposition quantities. For instance, modelled changes in kelp supply to the Arctic seafloor were found to have altered deep-sea food web structure and biodiversity (Vilas et al., 2020); and modelling of large-scale harvesting of beach kelp suggested negative impacts on ecosystem functioning, as beach kelp provides essential food and shelter for coastal fauna (Orr, 2013). In terms of their application to MRV, any cascading impacts that lead to changes in the natural uptake and storage of CO2 because of a mCDR perturbation (e.g. changes to calcifying plankton communities), should be modelled and may need to be included in carbon budget calculations to ensure additional carbon has been removed and stored compared to the counterfactual state. As small-scale field mCDR trials progress, thorough monitoring to capture any ecosystem feedback will be crucial to ensure these models can be further developed, parameterised, calibrated and validated, to capture critical processes and interactions between organisms and their environment and to inform MRV. EMB FUTURE SCIENCE BRIEF 40 5.4 Regional scale models Regional Ocean models, such as the Regional Oceanic Modelling System (ROMS, Shchepetkin & McWilliams, 2005), can be used to simulate Ocean dynamics and changes over time, especially in coastal areas. These models can simulate currents, mixing of water layers, and how substances such as nutrients, tracers or pollutants, spread. Regional models use a special type of grid that follows the shape of the Ocean floor, and can provide results in high resolution (typically from a few kilometres down to hundreds of metres in very localised domains). They can also be connected to larger models, and coupled with other models that simulate Ocean chemistry and ecosystems (Zhang et al., 2024). Thanks to these features, regional Ocean models can capture local and regional Ocean changes that bigger, global models may not be able to simulate. Regional models can also be used to simulate (future) mCDR scenarios. In the context of mCDR, regional models are already used to explicitly simulate OAE deployments, design observing strategies via Observing System Simulation Experiments (OSSEs, see Section 5.7), and compare modelled signals to targeted measurements for attribution (see Section 3.1), which are core MRV tasks (Fennel et al., 2023). Recent studies, building on broader demonstrations of theability to model coastal conditions (Laurent et al., 2021), include simulations of OAE to mitigate local acidification at the Great Barrier Reef (Mongin et al., 2021), and a coupled ice-circulation biogeochemical model that quantified local CO2 uptake and dispersion to assess OAE efficiency in the Bering Sea (Wang et al., 2023). In addition, regional models have been used to assess localised dispersion, carbon storage and ecosystem impacts of OAE in coastal areas, highlighting potential risks like pH spikes in nearshore environments (Anderson et al., 2025). High-resolution nested ROMS models, where a fine-scale grid is embedded inside a coarser grid, have also been used to study effects of alkalinity addition on the Scotian Shelf, revealing enhanced CO2 drawdown in productive shelf waters (Laurent et al., 2025). Furthermore, regional models can inform OAE site selection with passive tracer simulations to identify optimal deployment locations and timings, taking into account seasonal circulation patterns (Guo et al., 2025). Regional Ocean models can be used to model plume tracking, transport pathways, to support the elaboration of footprint maps, and to provide guidance for experimental design for MRV. However, uncertainties in boundary-conditions and atmospheric forcing, process parameterisation, imperfect inclusion of biogeochemistry, and limited reach to model multi-decadal durability are limitations, that means that these regional models must be comprehensively validated with observations and linked to larger-scale global models given the spatial decoupling of uptake and storage. Incorporating regional modelling frameworks alongside global assessments (see Section 5.5) could therefore strengthen MRV by bridging the gap between local observations and system-scale carbon accounting. 5.5 Global-scale and Earth System Models Global Ocean and Earth system models (ESMs) are widely used to investigate processes relevant to all Ocean-based mCDR methods. These low-resolution global simulations, also used extensively by the IPCC (IPCC, 2021), represent how different components of the Earth System interact and respond under various climate conditions and future scenarios. They are particularly valuable for capturing complex feedbacks and for assessing the net removal of atmospheric CO 2 , essential for evaluating the overall efficacy of mCDR methods (Keller et al., 2018). Such models can also project long-term impacts across Earth’s carbon reservoirs, such as changes in terrestrial soil respiration over centuries (Zickfeld et al., 2021). However, computational constraints mean that global models often simplify key processes, which contributes to significant uncertainties. For instance, projections of future biological carbon storage in the Ocean can diverge widely (Henson et al., 2024), with implications for simulations of mCDR methods that perturb the biological pump or alter Ocean alkalinity. Global-scale, Ocean-only models, not coupled to other parts of the Earth system (i.e., atmosphere or land) can be used to investigate physical, biogeochemical and ecological processes at various spatial resolutions (from >100 km grid cells to <10 km grid cells) and span a range of complexity in terms of the structure and parameterisations of biogeochemistry components (Kwiatkowski et al., 2023). While these models help elucidate mechanisms and sensitivities, they cannot on their own demonstrate net CO2 withdrawal from the atmosphere. Models of higher geospatial resolution are better at representing finescale physical, biogeochemical and ecological processes by explicitly resolving smaller spatial and temporal dynamics. Global Ocean models parameterised to describe the formation and propagation of eddies, and the production and settling of biomass, have been used to study natural Ocean processes and to assess the efficacy, scalability and impacts of different mCDR methods through simulations. For example, Ocean models have been used to simulate the potential for global macroalgal cultivation within all EEZs and the subsequent negative impacts on phytoplankton primary production (Berger et al., 2023), how OIF may amplify climate change pressure on marine biomass (Tagliabue et al., 2023), and where near-coast OAE (Palmiéri & Yool, 2024) or offshore OAE (Hauck et al., 2016) is likely to be most effective. One common finding from these studies is that there are significant non-local effects on the carbon system, as well as non-local environmental and ecological impacts, which will have implications for MRV. The scalability, efficacy, co-benefits and impacts of mCDR geochemical and biotic methods have been explored using idealised ESM simulations, for global OAE (Lenton et al., 2018), coastal OAE (Palmiéri & Yool, 2024), Artificial upwelling (AU) (Jürchott et al., 2023), large-scale OIF (Tagliabue et al., 2023), and a combination of OIF and AU (Jürchott et al., 2024). These studies demonstrate that OAE can have meaningful climate mitigation potential when N° 13 2025 41 considering CO 2 removal but will create large-scale perturbations in Ocean biogeochemistry and unclear ecological consequences (Feng (冯玉铭) et al., 2016); high regional variability in impacts and amelioration of Ocean acidification (Lenton et al., 2018); and it may weaken the terrestrial carbon sink (Palmiéri & Yool, 2024). Any CO2 uptake potential from AU without the combination with Ocean iron fertilisation (OIF) is considered to be low due to iron limitation of biological production (Jürchott et al., 2024) and the upwelling of CO2rich-cold deep waters, which would potentially lead to CO2 outgassing under low or net-zero emissions scenarios (Jürchott et al., 2023). Long-term simulations can also investigate the response of deepsea ecosystems, which are still poorly understood and observed, to mCDR methods (Levin et al., 2023). Overall, global-scale models are unsuitable for short-term MRV applications due to their coarse resolution, but they can be useful to predict environmental consequences and identify long-term feedbacks. They can also demonstrate some of the challenges facing robust MRV, such as that more than half of the CO2 uptake takes place away from the OAE addition locations (Palmiéri & Yool, 2024). 5.6 Model intercomparison projects The Coupled Model Intercomparison Project19 (CMIP) is an international modelling initiative that uses ESM simulations to aid in understanding the past, present and future climatic changes in the Earth system due to natural variability and anthropogenic drivers. CMIP coordinates efforts to answer key climate-related research questions by designing comparable experimental ESM simulations that provide climate relevant information for national and international reports such as the IPCC reports (Dunne et al., 2024). The CMIP-endorsed Carbon Dioxide Removal Model Intercomparison Project20 (CDRMIP; Keller et al., 2018), included mCDR in CMIP version 6 (Eyring et al., 2016), and developed an experimental protocol to test the climate system response to a deliberately large, idealised perturbation of global OAE. This unrealistic scale was chosen to isolate and understand theoretical system responses, rather than to represent any feasible deployment. Regardless of the scale of focus of a given model, model intercomparison is essential for quantifying uncertainty and variability in mCDR estimates (Keller et al., 2018). Furthermore, the data sharing infrastructure, coordination and support provided by the CMIP framework provide useful inspiration for future coordination of mCDR and MRV modelling activities. These currently tend to rely on single models but should include community-led assessments of model ensembles (multiple models performing the same experiment), to allow for biases and variability to be identified, and for uncertainty to be quantified. 19 https://wcrp-cmip.org/ 20 https://www.geomar.de/cdrmip 5.7 Modelling applications for monitoring, reporting and verification Models can help to better design observing tools for MRV. For instance, Observing System Simulation Experiments (OSSEs) are used to design effective observation systems and optimise data assimilation strategies (Fennel et al., 2023). Boyd et al. (2023) showed that OSSEs can be used to evaluate the effectiveness of different observational strategies. This emphasises their role in refining MRV protocols by reducing uncertainty and improving the attribution of carbon flux changes to specific mCDR methods. In the context of OAE research, OSSEs can be used to help optimise observations, including where trade-offs exist between observational platforms. To do so, models can be run in dataunconstrained (free historical) mode or with data assimilation (reanalysis hindcasts) to test the value of alternative sampling designs. A hindcast is a model simulation of past conditions, using historical forcing and sometimes partial observational data, which can then be compared with independent observations. Hindcasts are widely used to validate models, improve parameterisations, and refine predictions for future scenarios. OSSEs can help to detect, attribute and assess the impacts of mCDR by integrating high-resolution Ocean models with observing networks (Figure 5.2). This helps to identify the most effective observation strategies for monitoring mCDR while minimising uncertainties and potential unintended environmental consequences. Such modelling efforts are essential to ensure robust regulatory oversight of mCDR methods. Models can also support MRV by helping to quantify carbon removal, storage and durability. To date, two modelling approaches have been used in the context of assessing storage timescales and efficiency. Data-constrained Ocean Circulation Inverse Models (OCIMs) determine the storage timescales by mimicking mCDR carbon storage via direct “injection” of CO2 into the deep Ocean (Siegel et al., 2021) and study the storage timescales of the biological carbon pump (DeVries et al., 2012). These models are parameterised with nutrient data (DeVries et al., 2012), mean circulation and end-of-winter mixed layer depths (DeVries & Primeau, 2011), since the winter maximum depth largely determines how long surface waters and associated carbon remain isolated from the atmosphere. OCIMs do not account for how any future changes in Ocean circulation or mixed layer depths may impact storage timescales. The second approach uses virtual particle tracking to follow water parcels over climate-relevant timescales to estimate the storage efficiency of that parcel of water (Baker et al., 2022). This approach could assess the impact of climate change on sequestration efficiency by using future-projected current fields and mixed layer depths under different climate scenarios. This approach is more computationally expensive than OCIMs and therefore better for estimating sequestration efficiency at targeted deployment locations rather than at the basin scale. EMB FUTURE SCIENCE BRIEF 48 which sets monitoring, reporting, uncertainty and reversal provisions for removals. The standard also includes requirements for reversal and avoidance of leakage and of “other negative environmental and social impacts and respecting human rights and the rights of Indigenous Peoples” (UNFCCC, 2024). PACM defines removals as “the outcomes of processes by which greenhouse gases are removed from the atmosphere as a result of deliberate human activities and are either destroyed or durably stored through anthropogenic activities” (UNFCCC, 2024), making them relevant for mCDR. The Paris Agreement Crediting Mechanism standard requirements for removal activities mandates the monitoring to be based on reliable data from measurements, sampling, remote sensing, thirdparty sources and published literature, and that the data must be statistically representative, conservative and account appropriately for uncertainties (UNFCCC, 2024). Quality control measures must also be implemented, including cross-checking monitoring results with external data sources or published literature, and regularly calibrating measurement equipment. Methodologies must include monitoring and mitigation of identified risks, such as reversal risks and risks to the broader United Nations Sustainable Development Goals, as outlined in the sustainable development tool of the UNFCCC30. This includes ensuring the free, prior and informed consent of Indigenous Peoples directly or indirectly affected by the activity. Participants must also submit a comprehensive monitoring plan as part of the project design document when registering the activity, and this plan must be updated at the beginning of each renewed crediting period, to ensure continuous alignment with improved MRV capacities and standards. The Paris Agreement Article 6.4 requirements also explicitly outline reporting standards and stipulate that those undertaking removals are required to prepare comprehensive monitoring reports. These reports must be based on the above-mentioned pre-approved monitoring plan outlined in the registered project design document and include details of the monitoring methods used, estimated net removals during the period, including estimated uncertainties, and any collected data. They should also provide records of any observed greenhouse gas release events that could lead to reversals and must explain how reversal risks and any negative environmental or social impacts were assessed and mitigated, in line with the measures in the project design document. Although the reports can be submitted at least once every five years, depending on the activity type, risk of reversals and other relevant factors, monitoring must be continuous. In addition to this regular reporting, an immediate report needs to be submitted if an event occurs that could cause a greenhouse gas release and potential reversal. Failure to submit a report by the due date every five years will result in suspension of operations, including issuance, transfer or cancellation of credits (UNFCCC, 2024). And finally, monitoring must continue after the end of the last active crediting period of the activity to detect and quantify any reversals and/or verify ongoing greenhouse gas storage. This post-crediting monitoring can only stop if transparent and verifiable information that shows that the stored greenhouse gases are at a negligible risk of reversal, or if potential future reversals are remediated (UNFCCC, 2024). 6.3. Project-based certifications Apart from the binding obligations described in Sections 6.1 and 6.2, MRV is also based on independent crediting programmes that support voluntary carbon markets. Some of these programmes are shown in Figure 6.1, however, only a small subset of these apply to mCDR. For instance, only Isometric has a certified protocol for OAE projects (IEAGHG, 2024). The non-binding nature of these programmes means that such certifications cannot be counted towards countries’ NDCs (Van Dam et al., 2024), and the verification process only looks at the compliance of the programme and not the net removal of carbon from the atmosphere, which is the outcome of the mCDR method (Schulte et al., 2024). 30 https://unfccc.int/documents/632490 Figure 6.1 Examples of different independent crediting programs. N° 13 2025 49 31 https://climate.ec.europa.eu/citizens-stakeholders/events/workshop-carbon-removals-through-enhanced-rock-weathering-and-ocean-alkalinityenhancement-2025-09-25_en 6.4. EU voluntary certification system In November 2024, the European Parliament and the Council of the European Union agreed to establish a voluntary EU certification framework for permanent carbon removals, carbon farming and carbon storage in products (Regulation (EU) 2024/3012, 2024). According to this regulation a voluntary scheme was chosen to facilitate and encourage the uptake of high-quality carbon removals and soil emission reductions. Additionally, the “voluntary nature of the Union certification framework means that existing and new public and private certification schemes will be able to apply for recognition by the Commission under this Regulation but will not be obliged to do so in order to operate in the Union”. The Regulation’s definition of carbon removal and carbon farming is broad enough to include mCDR. Carbon removal is defined as “anthropogenic removal of carbon from the atmosphere and its durable storage in geological, terrestrial or Ocean reservoirs, or in longlasting products”, and carbon farming means “any practice or process carried out over an activity period of at least five years, related to the management of a terrestrial or coastal environment and resulting in the capture and temporary storage of atmospheric or biogenic carbon”. The Regulation distinguishes between permanent removals and carbon farming (Article 2(9)–(10)). Operators must demonstrate that carbon will be stored permanently, with permanent defined as “a duration of several centuries”. By contrast, carbon farming refers to “a practice or process carried out over an activity period of at least five years, related to the management of a terrestrial or coastal environment and resulting in the capture and temporary storage of atmospheric or biogenic carbon in biogenic carbon pools, or in the reduction of soil emissions”. The Regulation prescribes that operators are subject to monitoring obligations that combine onsite measures with remote sensing or modelling. Operators are also liable to address and mitigate identified risks of reversal. Additionally, certification requires operators to submit detailed information on quantification, additionality, storage, monitoring plans and sustainability objectives, all of which will be subject to verification by an accredited certification body. It is the responsibility of Member States to appoint certification bodies. The European Commission will supplement the Regulation with further certification methodologies. Currently, methodologies for OAE are on the regulatory agenda of the EU31. EMB FUTURE SCIENCE BRIEF 50 7Existing MRV protocols and LCAs for mCDR and current knowledge gaps 7.1 Existing MRV protocols for mCDR MRV protocols are being developed by commercial mCDR entities (e.g. Captura32, Planetary Technologies33, Ebb Carbon34, Running Tide [ceased operations]), by carbon registries (e.g. Isometric35) or by companies undertaking MRV tool development (e.g. Hourglass Climate36, [C]Worthy37). The TraceCDR tool38 developed by the Grantham Research Institute provides an overview of MRV protocols, including mCDR, and details how many carbon credits have been issued using these protocols. It highlights that as of October 2024, MRV protocols for mCDR had only been developed and applied for Ocean Alkalinity Enhancement (OAE), marine biomass sinking, terrestrial biomass sinking in the marine environment and direct Ocean carbon removal. The MRV protocols for mCDR are generally international in scope and have only been applied in the context of voluntary markets, as mCDR is not included in current international compliance markets (Mercer & Burke, 2023). Currently MRV protocols are being developed for specific mCDR deployment strategies to account for the intricacies and complexities of each method, and they are likely only being applied in one specific location as commercial mCDR entities are yet to scale. Whilst the protocols vary in technical detail and specific approach, many of them refer to the International Organization for Standardization39 (ISO), e.g. ISO 14064 is a greenhouse gas (GHG) accounting/ verification standard, ISO 14040/14044 is a cradle-to-grave LCA methodology, and ISO 14067 is a method to quantify and report the carbon footprint of a product. Some protocols had a short public consultation period prior to ratification while others provided contact details and invited further feedback, considering the protocol a ‘living document’. Open access sharing of welldocumented MRV protocols, in line with FAIR principles, is crucial to ensure comprehensive, reproducible, and transparent MRV and to drive innovation (Ho et al., 2023). Although mCDR innovators and market leaders largely appear to be adhering to such FAIR principles, the MRV protocols ideally need to be tested in situ and independently validated. 7.2 Integrating Life Cycle Assessments (LCAs) into MRV protocols Life Cycle Assessments (LCAs) can support the MRV for mCDR by providing a comprehensive, transparent framework to quantify and account for both the direct and indirect emissions associated with mCDR methods over their entire life cycle (see Section 3.4). LCAs are typically conducted before deployment or periodically updated to optimise design, compare options and assess net carbon removal potential under different assumptions. It helps to clearly define what constitutes carbon removal by establishing standardised system boundaries and functional units (e.g. per tonne of CO2 removed and permanently stored). This standardisation is crucial for consistent MRV reporting and for comparing different mCDR methods. By accounting for energy inputs, materials and emissions from construction, operation, maintenance and decommissioning, LCA reveals the full carbon footprint of a mCDR method (including non-CO 2 greenhouse gases). This detailed inventory is key for verifying that the net removal is genuine and not offset by indirect emissions (e.g. from energy use or downstream impacts). LCA methodologies quantify uncertainty in process emissions, which must be combined with MRV uncertainty on measured removals, and can be propagated within MRV systems to report confidence intervals on net CO2 removal. This helps decision-makers understand the uncertainty (confidence intervals) around reported carbon removals and could inform adjustments in management strategies if required. The CarbonPlan CDR Verification Framework interactive tool 40 maps key uncertainties (and confidence levels) associated with quantifying net carbon removal and storage durability for different CDR methods, essential for proper MRV protocols. If enough information is available, LCA frameworks can also highlight where the environmental impact is highest during the mCDR process, which can indicate where more precise monitoring is needed. Additionally, LCA may reveal trade-offs or potential cobenefits such as improvements in water quality or ecosystem health, which are valuable for comprehensive MRV. 32 https://capturacorp.com/ 33 https://www.planetarytech.com/ 34 https://www.ebbcarbon.com/ 35 https://isometric.com/ 36 https://hourglassclimate.org/ 37 https://www.cworthy.org/ 38 https://www.lse.ac.uk/granthaminstitute/tracecdr/ 39 https://www.iso.org/standard/66454.html 40 https://carbonplan.org/research/cdr-verification N° 13 2025 51 7.3 Knowledge required for MRV for mCDR MRV for mCDR is needed to determine the amount of additional CO 2 removed from the atmosphere as well as the durability of this removal (Ho et al., 2023). Ideally air-sea CO 2 exchange would be continuously measured and compared against the air-sea CO2 exchange in a control site without the mCDR deployed. Gas exchange of CO 2 across the sea surface is relatively slow and it takes months to years for the Ocean surface mixed layer to reach equilibrium with the atmosphere (Jones et al., 2014). This implies that even short deployments of mCDR will require long-term monitoring. Currently, anthropogenic CO2 in the Ocean is taken up at a rate of about 10.5 gigatonnes of CO2 per year. This is larger than what is envisaged for even large-scale mCDR deployments. Being able to detect the impacts of mCDR methods will rely on accurate knowledge of the baseline, i.e. the rate of uptake the Ocean would have reached without the proposed mCDR method. Monitoring systems based on current global observing systems may provide a good basis but need to be refined specifically for the measurement of biogeochemical variables and ecological parameters and tailored to specific deployment locations (see Chapter 4). Parameters required to describe the state of the Ocean carbon pool, such as primary production, biomass and alkalinity are relatively straightforward to measure but are not sufficient to quantify air-sea CO2 flux. Numerical models will therefore be important for future MRV schemes (see Chapter 5). Maximising information and quantifying uncertainties will require the combination of observational data and numerical models via data assimilation approaches. These will need to include not only physics, as already applied in a few weather centres and universities across Europe, but also biogeochemistry and biological observations and models. These model-data combinations will need to be expanded and all environmental impacts will need to be covered using eMRV. Table 7.1 summarises the current state of perceived MRV-readiness at the pilot-scale for the different mCDR methods considered in this document. This includes, whether field-deployable methods, traceable data streams, Quality Assurance/ Quality Control, uncertainty treatment, and independent verification exist to: (i) set a credible counterfactual baseline, (ii) quantify and verify durability of stored carbon over relevant timescales, (iii) account for non-CO 2 climate forcers (e.g. CH 4 , N 2 O; where relevant, short-lived species), and (iv) assess eMRV impacts. The ratings reflect MRV capability only, not technology efficacy, scale-up potential, costs or permitting, and they are site-, projectand design-dependent. They should be interpreted as a guide to where MRV elements are ready at pilot-stage today, and where targeted MRV development and validation are still needed. They should be revisited as evidence evolves. LCAs quantify cradle-to-grave emissions and resource flows, while Environmental Impact Assessments (EAIs) evaluate likely impacts in a specific location and regulatory context, and eMRV measures the environmental impacts during and after implementation of mCDR. LCA can thus inform project design and alternative selection, EIA can ensure regulatory compliance and mitigation planning, and MRV, including eMRV, can verify whether predicted and permitted environmental and carbon outcomes are achieved in practice. Together these tools can form an integrated framework for rigorously evaluating and governing marine CDR initiatives. However, LCA is a complex method, and it is difficult to capture highresolution and reliable data to build data inventories for the LCA of mCDR methods. The four main challenges are: (1) The definition of boundaries: LCA requires clear boundaries for different processes, whereas mCDR methods involve complex interactions between marine ecosystems, the environment and industrial activities. For example, an LCA of OAE would require an EIA of alkalinity enhancement to account for emissions from mining, transportation and application of minerals. (2) Data availability and quality: obtaining reliable data on methods such as Ocean fertilisation or direct Ocean carbon removal, is very difficult because there are very few pilot projects, and they exist within large natural variability. For instance, the amount of CO2 removed versus unwanted CH4 or N2O emissions would have to be estimated from high-resolution monitoring data that are often unavailable. (3) Temporal and spatial variability: impacts specific to mCDR, such as the carbon sequestration potential of kelp farming, can be highly siteand time-dependent as it may be influenced by seasonal biological growth or changing Ocean currents. (4) Systemic consequences and trade-offs: mCDR may bring non-intended impacts, such as alteration of marine biodiversity or biogeochemical cycling. As the long-term durability of additional carbon sequestration by mCDR methods (see Section 3.3) cannot be measured and needs to be quantified to allow for credits to be issued within carbon markets, we must rely on theoretical understanding and modelling approaches for these durability estimates, and they must be appropriately factored into LCAs. Further research is required to understand and advance different approaches to quantifying durability and the associated uncertainties with these estimates. EMB FUTURE SCIENCE BRIEF 52 mCDR METHOD BASELINE DURABILITY NON-CO2 ACCOUNTING eMRV Preexisting marine biomass removal ¢ Marine biomass cultivation  Ocean Fertilisation  Artificial Upwelling    Coastal Blue Carbon management ¢  ¢ Ocean Alkalinity Enhancement ¢ Artificial Downwelling    Direct Ocean Carbon Removal ¢ ¢   Table 7.1 Pilot-scale MRV-readiness for mCDR methods across four MRV dimensions. Colours indicate whether, at the scale of controlled pilots, they are sufficiently mature: ¢ ready (feasible with established protocols and traceability),  partially ready (key gaps remain, e.g. uncertainty treatment, integration or independent verification),  not ready (foundational methods/validation missing). To build up and support robust MRV for mCDR, a six-pillar framework is proposed, focusing on Baselines, Additionality, Detection and Attribution, Durability, Non-CO2, and Biodiversity. Each pillar illustrates the minimum metrics, study designs and reporting elements needed to show that observed signals exceed natural variability, can be attributed to the intervention, and translate into net atmospheric CO2 removal with quantified uncertainty, while safeguarding ecosystems and monitoring non-CO 2 climate forcers. Here, we illustrate this approach with OAE as a worked example (Figure 7.1), while the method-specific pillars for each of the mCDR methods presented in this document are provided in Appendix 2. These frameworks are templates, not exhaustive prescriptions. Each project must develop a siteand method-specific, pre-registered MRV plan aligned with applicable regulations and permits. Figure 7.1 The six pillars supporting robust MRV for mCDR, illustrated for Ocean Alkalinity Enhancement (OAE) as an example. Similar figures for the other mCDR methods are presented in Annex 2. This framework includes example metrics and checks to show how project signals exceed natural variability, can be attributed to the intervention, and translate into net atmospheric CO2 removal (with uncertainty) while safeguarding ecosystems. Abbreviations include: TA = total alkalinity; DIC = total dissolved inorganic carbon; p CO2 = partial pressure of CO2; Ω = carbonate-mineral saturation state; O2 = dissolved oxygen; N2O = nitrous oxide; CH4 = methane; eDNA = environmental DNA. N° 13 2025 53 8Overarching challenges and uncertainties for future MRV 8.1 Technical challenges and spatial-temporal variability: detection, measurements and models Chapters 4 and 5 identified the central challenge of MRV for mCDR: the difficulty of detecting and attributing changes in Ocean carbon to mCDR methods due to the inherent variability and complexity of Ocean systems. Natural fluctuations in CO2 uptake, circulation and biological processes, combined with uneven and often limited observational coverage complicate efforts to establish carbon baselines and detect additional removal due to mCDR methods. As shown in Chapter 4, current observing systems, while critical for understanding large-scale Ocean carbon dynamics, lack the spatiotemporal resolution to reliably monitor small-scale or short-term changes associated with mCDR. For example, Figure 8.1 illustrates overall declining trends in sub-surface DIC and surface air-sea CO 2 observations since 2015, which underscores persistent coverage gaps in dynamic and remote environments, such as coastal zones and the Southern Ocean. Chapter 4 further emphasise that accurate and credible MRV requires fit-for-purpose monitoring systems, adapted to the characteristics of the specific mCDR method and deployment scales. While a comprehensive global Ocean observing network is unlikely to be achieved in the near term, localised strategies using targeted sensors and platforms can support robust MRV for small-scale trials and early deployments. As mCDR scales, critical uncertainties about long-term carbon fate and storage durability must be addressed. This will increasingly require integrating improved observational coverage with enhanced modelling frameworks (see Chapter 5). Although models are essential tools for estimating additionality and forecasting outcomes, many existing Ocean models are limited by coarse resolution, missing process representation and lack of data for validation (especially for the deep Ocean) (Figure 8.1). New modelling frameworks that integrate machine learning and process-based models could improve predictability and reduce uncertainty, but they too require validation through real-word data. Controlled field trials and experiments remain essential to refine these tools for each mCDR method (Sánchez et al., 2024). Ocean Visions has built a database 41 of all known mCDR-relevant field trials currently operating or concluded. Beyond carbon quantification, Chapters 4 and 5 also highlight the need to understand and monitor the ecological effects of mCDR, including shifts in productivity, biodiversity, dissolved oxygen and Ocean acidification, which are poorly understood (Table 3.2). Effective monitoring will require protocols for integrating carbon flux data with biogeochemistry indicators (e.g. pH, dissolved oxygen, dissolved inorganic nutrients) and to include the range of seawater biogeochemical conditions in which a certain marine environment should be maintained. Adaptation of the MSFD ‘Good Environmental Status’ (GES) to mCDR will be needed, by adding explicit indicators, thresholds and reporting requirements. Controlled field trials are needed to build, test and refine the MRV systems required for different mCDR methods, either in isolation or when co-deployed. This is especially true for the ecosystem effects of mCDR that will require eMRV to recreate realistic environmental conditions, with realistic exposure and accounting for complex behaviours, to identify and monitor indicator species (which still need to be identified). MRV for mCDR should leverage evidence on biological responses not only to Ocean acidification, but also to deoxygenation, nutrient perturbations, and productivity shifts, to anticipate and detect ecological responses to mCDR, and need to select indicator species and thresholds for adaptive management (Bednaršek et al., 2025). The large uncertainties in possible ecological and biogeochemical shifts require careful implementation of MRV for mCDR until the safe operational temporal and spatial scales are identified (see Section 8.2). In summary, technical limitations in observations and models, and the Ocean’s dynamic nature, pose significant barriers to mCDR and its MRV. However, many of these can be overcome through targeted monitoring, strategic modelling and systematic field validation tailored to each mCDR method. 41 https://oceanvisions.org/mcdr-field-trials/ EMB FUTURE SCIENCE BRIEF 54 Figure 8.1 Global Ocean CO2 observations for the period 1970-2024. (A) Number of sub-surface (> 10m) total dissolved inorganic carbon (DIC) measurements, and (B) their depth distribution over time from the GLODAP database (Source: Lauvset et al., 2024). (C) Surface Ocean CO2 measurements, and (D) their latitudinal distribution from the SOCAT database (Source: Bakker et al., 2016). Colourbars show the observation year, and 3-year mean in black line in (A) and (C). For (B) and (D), the colouring indicates the observation count. Credit: Alizée Roobaert. 8.2 Regulatory and governance gaps There is no overarching international or EU regulatory framework specifically for MRV for mCDR (see Chapter 6). Current MRV obligations lack clear guidelines for continuous monitoring and data-sharing, leading to inconsistent reporting. The lack of MRV standardisation results in inconsistent and non-comparable data, which hinders transparency and accountability. While UNCLOS and the BBNJ Agreement require ongoing monitoring, they do not specify the types of data to be collected. The voluntary nature of many existing MRV initiatives (e.g. EU certification framework and private standards in voluntary carbon markets, see Sections 6.3 and 6.4) further complicates transparency and accountability. Internationally, there is a general trend towards deferring activities other than legitimate scientific research on mCDR. The pending addition of a wider range of mCDR methods to Annex 4 of the London Protocol could provide a framework for permitting legitimate mCDR research, and thus the development of fit-for-purpose MRV. The Paris Agreement’s MRV framework, including the Enhanced Transparency Framework, requires countries to report on emission reductions and carbon removals through their NDCs (see Section 6.2.3). However, there is no clear methodology for incorporating mCDR methods into NDCs. In addition, there are no standardised methods to quantify, verify and report mCDR’s carbon sequestration potential, making it difficult to integrate these methods into national climate targets. The Paris Agreement’s carbon crediting mechanisms (PACM) allow States to trade carbon removals (see Section 6.2.3). While Article 6 establishes general requirements for removals (monitoring plans, uncertainty, reversals, safeguards), there are currently no mCDRspecific methodologies defining how to quantify permanence, leakage or environmental impacts for mCDR, nor agreed accounting treatments for integrating mCDR into national inventories. This means it is unclear whether removals would be double-counted or excluded from national inventories (see Chapter 6). 8.3 Summary of uncertainties and challenges At present, no mCDR method has a mature, independently verifiable, end-to-end MRV system (i.e. the six pillars of MRV: baselines and additionality through detection and attribution, durability, non-CO 2 gases and biodiversity, see Figure 7.1 and Annex 2) suitable for large-scale deployment. Robust, open-Ocean baselines, attribution of additionality and demonstrable durability remain unattainable for all open-Ocean methods. Therefore, only tightly bounded, independently monitored pilot trials with accessible data and pre-defined stop criteria are warranted at this time. This reflects: (i) the high spatio-temporal variability of the Ocean carbon sink, complicating baseline and additionality estimates, and (ii) the need to quantify non-CO2 greenhouse gases (GHG) and ecological side-effects alongside CO 2 fluxes (eMRV). N° 13 2025 55 For site-specific pilots, partial MRV is feasible today (including carbonate system variables, targeted physical/biogeochemical monitoring, model-data combinations). However, for creditgrade, scalable MRV, key gaps persist including: detection and attribution against shifting baselines, slow air-sea equilibration and spatial decoupling of effects, durability quantification on decadal to centennial horizons, and standardised non-CO 2 GHG protocols. To overcome some MRV challenges, independent oversight, open data in community repositories, pre-registration of project assumptions and MRV plans, and ecological safeguards aligned with existing Ocean governance, are required. Until individual MRV protocols are proven to detect, attribute and verify net removals while accounting for uncertainties in a manner suitable for policy/market use, mCDR methods should not be scaled up or co-deployed. Table 8.1 summarises the mCDR methods considered in this document, giving a comparison of their attributes, key uncertainties and MRV challenges. It also describes the Technology Readiness Level42 (TRL), deployment cost considerations, key uncertainties related to efficacy and environmental impact, and the specific MRV challenges associated with each method. The table underscores the significant knowledge gaps and technological hurdles that currently limit the reliable implementation and MRV of various mCDR methods, leading to the key recommendations in Chapter 9. MCDR METHOD DESCRIPTION TECHNOLOGY READINESS LEVEL (TRL) DEPLOYMENT COST CONSIDERATIONS KEY UNCERTAINTIES MRV CHALLENGES DURABILITY BIOTIC METHODS Preexisting marine biomass removal Enhanced sinking of naturally occurring marine biomass to the Ocean interior and seafloor. 4-6 (early to mid-development) • Costs of preexisting seaweed harvesting. Uncertainty around ecosystem and environmental effects at the seafloor; and the long-term viability of carbon sequestration. Logistic challenges in monitoring growth rates and effective biomass utilisation across diverse environments. >100 – >1,000years, if POC exported to deep Ocean. Marine biomass cultivation and sinking Enhanced sinking of cultured and harvested biomass to the Ocean interior and seafloor. 4-6 (early to mid-development) • Infrastructure and deployment costs (building and maintaining seaweed offshore farms). Uncertainty around the scalability of cultivation methods, ecosystem impacts, and the long-term viability of carbon sequestration. Logistic challenges in monitoring growth rates and effective biomass utilisation across diverse environments. 10 – 100 years likely. >100 – 1,000years, if large fraction of POC exported to deep Ocean. Marine biomass cultivation for durable products and energy Using Cultivation of marine organisms to capture CO2, which can be utilised for various durable products or energy generation, including bioenergy with carbon capture and storage (mBECCS). 3-6 (early to mid-development) • Requires substantial upfront infrastructure investment; • Scalability challenges due to cultivation technology dependencies; • Costs linked to biomass processing; and • Carbon Capture and Storage demands (e.g. energy, transport, compression), and long-term carbon storage. Uncertainty around the scalability of cultivation methods, life cycle carbon emissions, ecosystem impacts, and the long-term viability of carbon sequestration (durable products). Logistic challenges in monitoring growth rates and effective biomass utilisation across diverse environments. Tracking life cycle emissions accurately. >10 – 100 years, dependent on storage medium / product. >1,000 years, if using geological storage. Table 8.1 A synthesis of the different mCDR methods and their attributes covered in this document. Specifics can vary significantly, depending on implementation scale, site conditions, and regulatory context. Durability entries are indicative and should be interpreted alongside the durability tiers in Table 3.1 (short/medium/long-term), which set MRV implications by storage reservoir. Abbreviations: Particulate Organic Matter (POC); Microalgaebased Bioenergy with Carbon Capture and Storage (mBECCS); and Greenhouse Gases (GHGs). 42 https://tracker.carbongap.org/glossary/trl/ EMB FUTURE SCIENCE BRIEF 56 MCDR METHOD DESCRIPTION TECHNOLOGY READINESS LEVEL (TRL) DEPLOYMENT COST CONSIDERATIONS KEY UNCERTAINTIES MRV CHALLENGES DURABILITY BIOTIC METHODS Ocean Fertilisation Adding dissolved inorganic nutrients like iron to increase phytoplankton growth and enhance CO2 uptake, increasing the sinking of biomass to the Ocean interior and seafloor. 3-5 (experimental) • High uncertainty in environmental impacts; • Significant site selection risks; and • Operational costs depend on nutrient availability. Uncertainty in environmental impacts due to variable ecological responses and potential negative effects like eutrophication and associated deoxygenation, and methane release. Measuring the net effect of nutrient addition on different GHGs complicates monitoring. 10 – 100 years, location dependent. >100 years, if carbon reaches deep Ocean. Artificial Upwelling Uses engineered systems to bring nutrient-rich deep waters to the surface, which can enhance phytoplankton growth and increase CO2 uptake, increasing the sinking of biomass to the Ocean interior and seafloor. 1-3 (conceptual) • Conceptual stage; • High potential costs; • May pose ecological disruption risks; and • Largely untested in open Ocean. Lack of empirical data on efficacy and potential consequences on deep-sea ecosystems. Uncertainties in measuring upwelled materials' fate and potential ecological impacts complicate monitoring. >100 – >1,000years, if POC exported to deep Ocean. Coastal Blue Carbon Management Enhance carbon storage by restoring or generating new coastal ecosystems (e.g. mangrove forests, seagrass meadows, salt marshes), which also triggers alkalinity release, restoring some of the Ocean’s buffering capacity. 5-7 (established, developing) • Restoration efforts involve ongoing investment; and • Economic viability relies on successful ecosystem rehabilitation. Variability in sediment carbon storage and longterm ecological stability postrestoration. Establishing reliable baselines for carbon storage in restored ecosystems is challenging. 10 – 100 years for biomass. 100 – >1000 years for sediments (siteand disturbancedependent). N° 13 2025 57 MCDR METHOD DESCRIPTION TECHNOLOGY READINESS LEVEL (TRL) DEPLOYMENT COST CONSIDERATIONS KEY UNCERTAINTIES MRV CHALLENGES DURABILITY GEOCHEMICAL METHODS Ocean Alkalinity Enhancement Increases seawater alkalinity to convert dissolved CO2 into stable bicarbonate and carbonate ions, thus increasing the drawdown of CO2 from atmosphere. 2-7 (conceptual to prototype level) • Energyintensive; • Involves mining and processing costs; and • Potential ecological risks require thorough assessment. Efficacy of alkalinity enhancement over time and its ecological implications remain uncertain. Precise tracking of alkalinity changes and attributing carbon storage is difficult. >1,000 years. Artificial Downwelling Uses engineered systems to force CO2-rich surface water into deeper waters, effectively isolating it from the atmosphere. 2-3 (conceptual stage) • Investment in equipment designed to withstand deep - Ocean pressures; and • Comparable costs to upwelling, with additional expenses tied to deep-Ocean challenges. Efficiency of forced downwelling in achieving long-term CO2 isolation; potential disruptions to deep-Ocean nutrient cycles; and impacts on marine ecosystems. Precise measurement of CO2 transfer to deep Ocean, verifying the permanence, uncertainties related to deep-Ocean biogeochemical processes. >100 – >1,000years, if carbon exported to deep Ocean. 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Nature Climate Change, 11(7), 613–617. https://doi.org/10.1038/s41558-021-01061-2 EMB FUTURE SCIENCE BRIEF 72 List of abbreviations and acronyms ARGO International programme comprising a network of oceanography floats AU Artificial Upwelling BBNJ Biodiversity Beyond National Jurisdiction BR Biennial Reports BTR Biennial Transparency Report BUR Biennial Update Reports CaCO3Calcium Carbonate CAPEX Capital expenditure CBD Convention on Biological Diversity CCS Carbon Capture and Storage CDR Carbon Dioxide Removal CH4 Methane CHM Clearing House Mechanism CMIP Coupled Model Intercomparison Project CO2Carbon Dioxide CO2eq Carbon Dioxide equivalent CO3 2Carbonate ion COP Conference of the Parties DIC Total Dissolved Inorganic Carbon DMS Dimethyl Sulphide DOC Dissolved Organic Carbon EEZ Exclusive Economic Zone EIA Environmental Impact Assessment eMRV Environmental Monitoring Reporting and Verification EOV Essential Ocean Variable ERT Expert Review Team ESM Earth System Model ETF Enhanced Transparency Framework EU European Union FAIR Findable, Accessible, Interoperable and Reusable FMGDM Floating Macroalgal Growth and Drift Model GEOMAR Helmholtz Centre for Ocean Research Kiel GES Good Environmental Status GESAMP Joint Group of Experts on the Scientific Aspects of Marine Environmental Protection GGR Greenhouse Gas Removal GHG Greenhouse Gas GLODAP Global Ocean Data Analysis Project GOOS Global Ocean Observing System GOSAT Greenhouse gases Observing SATellite GO-SHIP Global Ocean Ship-based Hydrographic Investigations Program N° 13 2025 73 HCO3 -Bicarbonate ion IAR International Assessment and Review ICA International Consultation and Analysis ICOS Integrated Carbon Observation System IEAGHG International Energy Agency Greenhouse Gas R&D Programme ILC International Law Commission IPCC Intergovernmental Panel on Climate Change ISO International Organization for Standardization LCA Life Cycle Assessment mBECCS Marine Bioenergy with Carbon Capture and Storage mCDR Marine Carbon Dioxide Removal MRV Monitoring, Reporting and Verification MSFD Marine Strategy Framework Directive N2ONitrous Oxide NASEM National Academies of Sciences, Engineering, and Medicine NDC Nationally Determined Contributions NOAA National Oceanic and Atmospheric Administration NRC National Research Council OAE Ocean Alkalinity Enhancement OCIM Ocean Circulation Inverse Models OIF Ocean Iron Fertilisation OPEX Operational Expenditure OSSE Observing System Simulation Experiments PACE Plankton, Aerosol, Cloud, ocean Ecosystem PACM Paris Agreement Crediting Mechanism p CO2Partial pressure of Carbon Dioxide pH potentia hydrogenii - expression of hydrogen ion concentration in water POC Particulate Organic Carbon ROMS Regional Oceanic Modelling System SENTINEL Earth observation mission from the European Union Copernicus Programme SIDS Small Island Developing States SOCAT Surface Ocean CO2 Atlas SOIREE Southern Ocean Iron RElease Experiment SRM Solar Radiation Modification TA Total Alkalinity TER Technical expert reviews UNCLOS United Nations Convention on the Law of the Sea UNFCCC United Nations Framework Convention on Climate Change USA United States of America WFD Water Framework Directive EMB FUTURE SCIENCE BRIEF 80 N° 13 2025 81 EMB FUTURE SCIENCE BRIEF 82 N° 13 2025 83 European Marine Board IVZW Belgian Enterprise Number: 0650.608.890 Jacobsenstraat 1 I 8400 Ostend I Belgium Tel: +32 (0) 59 33 69 24 E-mail: [email protected] www.marineboard.eu European Marine Board IVZW Belgian Enterprise Number: 0650.608.890 Jacobsenstraat 1 I 8400 Ostend I Belgium Tel: +32 (0) 59 33 69 24 E-mail: [email protected] www.marineboard.eu Credit: © Roberto Rinaldi.