FRONTIERS IN OCEAN
OBSERVING
EMERGING TECHNOLOGIES FOR UNDERSTANDING
AND MANAGING A CHANGING OCEAN
IN
PROGRESS
2023 Oceanography Supplement
ON THIS PAGE. A Biogeochemical Argo float. For details, see
Boyd et al. (2023, in this supplement). Photo credit: David Luquet,
licensed under CC BY-SA 4.0 by Thomas Boniface
ON THE FRONT COVER. A depiction of some of the many
platforms that scientists use to sample and sense the ocean,
including (from left to right) moorings, autonomous underwater
vehicles, CTD rosettes, and towed vehicles (not to scale). See
Govindarajan et al. (2023, in this supplement) to read about how
these platforms can be used to sample environmental DNA for
studies of the mesopelagic ocean. Illustration by Natalie Renier,
Woods Hole Oceanographic Institution
FRONTIERS IN OCEAN OBSERVING EXECUTIVE COMMITTEE
• S. Kim Juniper, Ocean Networks Canada
• Sophie Seeyave, Partnership for Observation of the Global Ocean
• Emily Smith, NOAA’s Global Ocean Monitoring and Observing Program
• Martin Visbeck, GEOMAR Helmholtz Center for Ocean Research Kiel
OCEANOGRAPHY
• Ellen S. Kappel, Oceanography Editor
• Vicky Cullen, Oceanography Assistant Editor
• Johanna Adams, Layout & Design
FRONTIERS IN OCEAN OBSERVING GUEST EDITORS
Ocean-Climate Nexus: Observations for Marine Carbon Dioxide Removal
• Jens D. Müller, ETH Zürich
• Toste Tanhua, GEOMAR Helmholtz Center for Ocean Research Kiel
Ecosystems and Their Diversity: Patterns and Trends in Ocean
Biodiversity Under Climate Change
• Mark J. Costello, Nord University
• Qianshuo Zhao, Ocean University of China, Qingdao
• Charles Lavin, Nord University
• Cesc Gordó-Vilaseca, Nord University
Ocean Pollutants: Assessing the Damage Caused by Marine
Plastic Pollution
• Luisa Galgani, GEOMAR Helmholtz Center for Ocean Research Kiel
• Shiye Zhao, Japan Agency for Marine-Earth Science and Technology
Multi-Hazard Warning Systems: Ocean Observations for Coastal
Hazard Warning
• Soroush Kouhi, Ocean Networks Canada
• Benoît Pirenne, Ocean Networks Canada
Technology: Environmental DNA
• Annette Govindarajan, Woods Hole Oceanographic Institution
• Luke McCartin, Lehigh University
ABOUT THIS PUBLICATION
Support for this publication is provided by Ocean Networks Canada,
the National Oceanic and Atmospheric Administration’s Global Ocean
Monitoring and Observing Program, and the Partnership for Observation
of the Global Ocean.
This is an open access document made available under a Creative
Commons Attribution 4.0 International License, which permits use, shar-
ing, adaptation, distribution, and reproduction in any medium or format
as long as users cite the materials appropriately, provide a link to the
Creative Commons license, and indicate the changes that were made
to the original content. Users will need to obtain permission directly
from the license holder to reproduce images that are not included in the
Creative Commons license.
Published by The Oceanography Society
Single printed copies are available upon request from info@tos.org.
PREFERRED CITATION
Kappel, E.S., V. Cullen, M.J. Costello, L. Galgani, C. Gordó-Vilaseca,
A. Govindarajan, S. Kouhi, C. Lavin, L. McCartin, J.D. Müller,
B. Pirenne, T. Tanhua, Q. Zhao, and S. Zhao, eds. 2023. Frontiers in
Ocean Observing: Emerging Technologies for Understanding and
Managing a Changing Ocean. Oceanography 36(Supplement 1),
https://doi.org/10.5670/oceanog.2023.s1.
CONTENTS
1
Introduction To Frontiers in Ocean Observing
by E.S. Kappel, M.J. Costello, L. Galgani, C. Gordó-Vilaseca, A. Govindarajan, S. Kouhi, C. Lavin, L. McCartin, J.D. Müller,
B. Pirenne, T. Tanhua, Q. Zhao, and S. Zhao
OCEAN-CLIMATE NEXUS: OBSERVATIONS FOR MARINE CARBON DIOXIDE REMOVAL
2
Operational Monitoring of Open-Ocean Carbon Dioxide Removal Deployments: Detection, Attribution,
and Determination of Side Effects
by P.W. Boyd, H. Claustre, L. Legendre, J.-P. Gattuso, and P.-Y. Le Traon
11
Assessing Changes in Marine Biogeochemical Processes Leading to Carbon Dioxide Removal with
Autonomous Underwater Vehicles
by C. Garcia, B. Barone, S. Ferrón, and D. Karl
14
A Low-Cost Carbon Dioxide Monitoring System for Coastal and Estuarine Sensor Networks
by P.J. Bresnahan, E. Farquhar, D. Portelli, M. Tydings, T. Wirth, and T. Martz
16
PERSPECTIVE. The Growing Potential of Antarctic Blue Carbon
by C.J. Sands, N. Zwerschke, N. Bax, D.K.A. Barnes, C. Moreau, R. Downey, B. Moreno, C. Held, and M. Paulsen
18
PERSPECTIVE. Net Zero: Actions for an Ocean-Climate Solution
by A.M. Waite, M. Smit, E. Siegel, G. Hanna, and S. Leslie
ECOSYSTEMS AND THEIR DIVERSITY: PATTERNS AND TRENDS IN OCEAN BIODIVERSITY
UNDER CLIMATE CHANGE
20
Using Soundscapes to Assess Changes in Coral Reef Social-Ecological Systems
by T.-H. Lin, F. Sinniger, S. Harii, and T. Akamatsu
28
Functional Seascapes: Understanding the Consequences of Hypoxia and Spatial Patterning in Pelagic Ecosystems
by S.B. Brandt, S.E. Kolesar, C.N. Glaspie, A. Laurent, C.E. Sellinger, J.J. Pierson, M.R. Roman, and W.C. Boicourt
31
Recent Marine Heatwaves Affect Marine Ecosystems from Plankton to Seabirds in the Northern Gulf of Alaska
by S. Strom and the Northern Gulf of Alaska Long-Term Ecosystem Research Team
34
Modeling Aquaculture Suitability in a Climate Change Future
by A.L. Mackintosh, G.G. Hill, M.J. Costello, A. Jueterbock, and J. Assis
36
Monitoring Algal Blooms with Complementary Sensors on Multiple Spatial and Temporal Scales
by D.R. Williamson, G.M. Fragoso, S. Majaneva, A. Dallolio, D.Ø. Halvorsen, O. Hasler, A.E. Oudijk, D.D. Langer, T.A. Johansen,
G. Johnsen, A. Stahl, M. Ludvigsen, and J.L. Garrett
38
UAV High-Resolution Imaging and Disease Surveys Combine to Quantify Climate-Related Decline in
Seagrass Meadows
by L.R. Aoki, B. Yang, O.J. Graham, C. Gomes, B. Rappazzo, T.L. Hawthorne, J.E. Duffy, and D. Harvell
40
Long-Term Observations of Hypoxia off the Yangtze River Estuary: Toward Prediction and Operational Application
by X. Ni, F. Zhou, D. Zeng, D. Li, T. Zhang, K. Wang, Y. Ma, Q. Meng, X. Ma, Q. Zhang, D. Huang, and J. Chen
OCEAN POLLUTANTS: ASSESSING THE DAMAGE CAUSED BY MARINE PLASTIC POLLUTION
42
Exploring Methods for Understanding and Quantifying Plastic-Derived Dissolved Organic Matter
by L. Zhu, N. Gaggelli, A. Boldrini, A. Stubbins, and S.A. Loiselle
49
On the Potential for Optical Detection of Microplastics in the Ocean
by D. Koestner, R. Foster, and A. El-Habashi
52
Sediment Traps: A Renowned Tool in Oceanography Applied to New Marine Pollutants
by L. Galgani, H. Hepach, K.W. Becker, and A. Engel
54
Developing Realistic Models for Assessing Marine Plastic Pollution in Semi-Enclosed Seas
by J. She, A. Christensen, F. Garaventa, U. Lips, J. Murawski, M. Ntoumas, and K. Tsiaras
MULTI-HAZARD WARNING SYSTEMS: OCEAN OBSERVATIONS FOR COASTAL
HAZARD WARNING
58
Ocean Monitoring and Prediction Network for the Sustainable Development of the Gulf of Mexico and the Caribbean
by J.C. Herguera, E.M. Peters, J. Sheinbaum, P. Pérez-Brunius, V. Magar, E. Pallàs-Sanz, S. Estrada Allis,
M.L. Aguirre-Macedo, V.M. Vidal-Martinez, C. Enriquez, I. Mariño Tapia, H. García Nava, X. Flores Vidal, T. Salgado,
R. Romero-Centeno, J. Zavala-Hidalgo, E.A. Cuevas Flores, A. Uribe Martínez, and L. Carrillo
64
An Experimental Platform to Study Wind, Hydrodynamic, and Biochemical Conditions in the Littoral Zone During
Extreme Coastal Storms
by B.M. Phillips, F.J. Masters, B. Raubenheimer, M. Olabarrieta, E.S. Morrison, P.L. Fernández-Cabán, C.C. Ferraro, J.R. Davis,
T.A. Rawlinson, and M.B. Rodgers
66
Probabilistic Approaches to Coastal Risk Decision-Making Under Future Sea Level Projections
by T. Spencer, M. Dobson, E. Christie, R. Eyres, S. Manson, S. Downie, and A. Hibbert
69
The Texas A&M – University of Haifa Eastern Mediterranean Observatory: Monitoring the Eastern Mediterranean Sea
by G. Milton, S.F. DiMarco, A.H. Knap, J. Walpert, and R. Diamant
70
Subsea Cables as Enablers of a Next Generation Global Ocean Sensing System
by E. Pereira, M. Tieppo, J. Faria, D. Hart, P. Lermusiaux, and the K2D Project Team
72
Integrating Topographic and Bathymetric Data for High-Resolution Digital Elevation Modeling to Support Tsunami
Hazard Mapping
by C. Bosma, A. Shumlich, M. Rankin, S. Kouhi, and R. Amouzgar
74
Assessment of Tsunami Hazard Along British Columbia Coastlines from Coseismic Sources
by S. Kouhi, R. Amouzgar, M. Rankin, C. Bosma, and A. Shumlich
76
Detection of Landslides and Tsunamis in Douglas Channel and Gardner Canal, British Columbia
by F. Nemati, L. Leonard, G. Lintern, C. Brillon, A. Schaeffer, and R. Thomson
78
EASTMOC: Environmental Alert System for Timely Maintenance of the Coastal Zone
by V. Kondrat, I. Šakurova, E. Baltranaitė, and L. Kelpšaitė-Rimkienė
TECHNOLOGY: ENVIRONMENTAL DNA
80
Advances in Environmental DNA Sampling for Observing Ocean Twilight Zone Animal Diversity
by A.F. Govindarajan, A. Adams, E. Allan, S. Herrera, A. Lavery, J. Llopiz, L. McCartin, D.R. Yoerger, and W. Zhang
87
Detecting Mediterranean White Sharks with Environmental DNA
by J.F. Jenrette, J.L. Jenrette, N.K. Truelove, S. Moro, N.I. Dunn, T.K. Chapple, A.J. Gallagher, C. Gambardella, R. Schallert,
B.D. Shea, D.J. Curnick, B.A. Block, and F. Ferretti
90
Toward Identifying the Critical Ecological Habitat of Larval Fishes: An Environmental DNA Window into
Fisheries Management
by E.V. Satterthwaite, A.E. Allen, R.H. Lampe, Z. Gold, A.R. Thompson, N. Bowlin, R. Swalethorp, K.D. Goodwin, E.L. Hazen,
S.J. Bograd, S.A. Matthews, and B.X. Semmens
94
The Use of eDNA to Monitor Pelagic Fish in Offshore Floating Wind Farms
by T.G. Dahlgren, J.T. Hestetun, and J. Ray
96
Deep-Sea Predator-Prey Dynamics Revealed by Biologging and eDNA Analysis
by V.J. Merten, F. Visser, and H.-J.T. Hoving
100 Evaluating Connectivity of Coastal Marine Habitats in the Gulf of Maine by Integrating Passive Acoustics
and Metabarcoding
by G. Milne, J. Miksis-Olds, A. Stasse, B.-Y. Lee, D. Wilford, and B. Brown
102 Authors
106 Acronyms
In this second supplement to Oceanography on frontiers
in ocean observing, articles describe the many creative
and promising ways in which scientists are now sampling
and studying the ocean and its constituents, from carbon
dioxide and oxygen, environmental DNA (eDNA), plastics,
and microplastics, to coral reefs, fish, and whole ecosys-
tems. These papers show, for example, how acoustic tech-
niques are critical components for early warning of natural
hazards such as earthquakes, tsunamis, and landslides
and how they play significant roles in investigations such
as determining how ocean soundscapes may be used to
monitor coral reef ecosystem health. Several articles
demonstrate the application of long-used technologies for
new and important data-gathering purposes, while others
describe how data collected by multiple technologies
deployed simultaneously have improved monitoring of
threats such as harmful algal blooms and oil spills. Some
authors detail the application of eDNA analyses, especially
to midwater environments, where they are providing new
insights, in combination with other sampling and sensing
methods. Modeling is a key aspect of several of the stud-
ies, where ocean observing data serve as critical inputs
and for validation. These innovative observing technolo-
gies and analytical techniques are advancing our under-
standing of the world ocean and supporting its sustainable
use and management.
Similar to last year’s supplement, we invited potential
authors to submit letters of interest aligned with the pri-
orities of the UN Decade of Ocean Science for Sustainable
Development (2021–2030), though topics were further
narrowed into specific themes. In addition, this year each
topic had guest editors, some of whom are early career sci-
entists. The idea was that this supplement would provide
an opportunity for a senior scientist to mentor one from
the next generation and for early career scientists to gain
some experience as guest editors for a journal.
OCEAN-CLIMATE NEXUS
THEME: Observations for Marine Carbon Dioxide Removal
GUEST EDITORS: Toste Tanhua and Jens Daniel Müller
How ocean observations and emerging technologies
are helping to identify potential marine carbon dioxide
removal (mCDR) opportunities and to measure the effec-
tiveness of mCDR actions, including studies evaluating the
potential adverse effects of human interventions on bio-
diversity and ecosystem function.
ECOSYSTEMS AND THEIR DIVERSITY
THEME: Patterns and Trends in Ocean Biodiversity Under
Climate Change
GUEST EDITORS: Mark John Costello, Qianshuo Zhao,
Charles Lavin, and Cesc Gordó-Vilaseca
Ocean observing efforts that record environmental and
related biodiversity changes occurring in different eco-
systems, from the coasts to the deep ocean and from
the tropics to the high latitudes, and that address the link
between observations and policy.
OCEAN POLLUTANTS
THEME: Assessing the Damage Caused by Marine
Plastic Pollution
GUEST EDITORS: Luisa Galgani and Shiye Zhao
Both classical oceanographic approaches and new tech-
niques for quantifying marine plastic pollution as well as
its long-term consequences on ecosystems and climate
through their interaction with natural elements of the
marine environment.
MULTI-HAZARD WARNING SYSTEMS
THEME: Ocean Observations for Coastal Hazard Warning
GUEST EDITORS: Benoît Pirenne and Soroush Kouhi
Observations and monitoring, forecasting, alerting, and
hazard research together with the systems developed
around them and their applications in coastal communities.
TECHNOLOGY
THEME: Environmental DNA Technology
GUEST EDITORS: Annette Govindarajan and Luke McCartin
Recent developments in all aspects of eDNA technology
and interpretive approaches relevant for observing and
studying animal biodiversity, especially in the ocean mid-
water environment.
We thank Ocean Networks Canada, the US National
Oceanic and Atmospheric Administration’s Global Ocean
Monitoring and Observing Program, and the Partnership
for Observation of the Global Ocean for generously sup-
porting publication of this supplement to Oceanography.
ARTICLE DOI. https://doi.org/10.5670/oceanog.2023.s1.1
INTRODUCTION TO FRONTIERS IN OCEAN OBSERVING
By Ellen S. Kappel, Mark John Costello, Luisa Galgani, Cesc Gordó-Vilaseca,
Annette Govindarajan, Soroush Kouhi, Charles Lavin, Luke McCartin, Jens Daniel Müller,
Benoît Pirenne, Toste Tanhua, Qianshuo Zhao, and Shiye Zhao
OCEAN-CLIMATE NEXUS
Observations for
Marine Carbon Dioxide
Removal
Operational Monitoring of Open-Ocean Carbon Dioxide Removal Deployments:
Detection, Attribution, and Determination of Side Effects
By Philip W. Boyd*, Hervé Claustre*, Louis Legendre*, Jean-Pierre Gattuso, and Pierre-Yves Le Traon (*equal first authors)
Human activities are causing a sustained increase in the
concentration of carbon dioxide (CO2) and other green-
house gases in the atmosphere. The resulting harmful
effects on Earth’s climate require decarbonizing the econ-
omy and, given the slow pace and inherent limitations of
decarbonization of some industries such as aviation, also
the active removal and safe sequestration of CO2 away
from the atmosphere (i.e., carbon dioxide removal or CDR;
NASEM, 2022). Limiting global warming to 1.5°C—a target
that may already have been exceeded—would require
CDR on the order of 100–1,000 Gt CO2 over the twenty- first
century (IPCC, 2018).
Natural terrestrial and ocean processes already remove
about half of human CO2 emissions from the atmosphere,
with half of this amount (i.e., a quarter of the total) ending
up in the ocean. These natural processes slow down global
warming; without the continuous removal of atmospheric
CO2 since the beginning of the Industrial Era (1750), the
present (2022) level of 420 ppm would have been reached
in the 1980s. In the ocean, CO2 combines with water (H2O)
to form dissolved inorganic carbon (DIC: CO2 gas, H2CO3,
and HCO3
– and CO3
2– ions), and photosynthetic organisms
use some of the DIC to synthesize the organic matter that
is the basis of pelagic marine food webs. Marine organic
carbon exists in both particulate and dissolved forms (POC
and DOC, respectively). A number of physical, chemical,
and biological processes, collectively called ocean carbon
pumps, transfer carbon from surface waters downward
and store it in the ocean as DIC and refractory (i.e., long-
lived) DOC and POC in the ocean. Some of this storage takes
place on climatically significant timescales and is called car-
bon sequestration. Sequestration of DIC can occur at any
depth, but its potential is higher at greater depths.
There is increasing discussion of implementing marine
CDR (mCDR) approaches, which range from methods
based on natural processes to more industrial tech-
niques (NASEM, 2022). Here, we focus on open- ocean
mCDR approaches, including alkalinization (i.e., adding
alkaline substances, such as olivine or lime, to seawater
to enhance the ocean’s chemical uptake of CO2 from the
atmosphere) and nutrient fertilization (i.e., adding a nutri-
ent that limits phytoplankton photosynthesis, such as iron,
to surface waters to enhance the photosynthetic uptake
of DIC), which aim to enhance DIC sequestration resulting
from increased CO2 influx from the atmosphere.
There is a growing body of literature on various aspects
of mCDR approaches. Published mCDR studies have
addressed the appropriateness of implementation, testing
the efficiency of sequestering CO2 and/or assessing det-
rimental ecological effects (laboratory/mesocosm studies,
field trials), and identifying potential deployment sites.
Such pilot studies are precursors to possible future mCDR
deployments (NASEM, 2022), which should only occur in
cases where the pilot studies indicate that mCDR would not
unduly disrupt marine ecosystems. In contrast, this paper
addresses the situation where mCDRs are to be deployed
at scales commensurate with the target of removing giga-
tons of atmospheric carbon.
Here, considering information from satellites and auton-
omous platforms combined with artificial intelligence (AI)
and models (Figure 1), we describe a future operational
monitoring system for the detection, attribution, and deter-
mination of side effects of open- ocean mCDR deployments.
We mainly address the monitoring challenge described
in NASEM (2022), based upon the current and expected
readiness of observational platforms and sensors. This
approach ensures that the proposed monitoring system
would be tractable and deployable. The assessment of
future mCDR deployments will include three components,
together referred to as MRV: measurement or monitoring
FIGURE 1. The three main components of a marine carbon dioxide removal (mCDR) monitor-
ing system are the tools to be used, field implementation, and reporting and verification. These
would interact, and thus progressively improve, prior to and during the long-term mCDR deploy-
ment. The development of tools would be accelerated by the urgency created by the mCDR
deployments. Connections between the three objectives of the monitoring system (i.e., detection,
attribution, and determination of side effects) and the monitored variables are described under
“Monitoring mCDR Deployments” in the text. OSSE = Observation System Simulation Experiment.
TRL = Technological Readiness Level. Licensed under CC BY-SA 4.0 by Thomas Boniface
(M) as described in this study, reporting (R) of the result-
ing data to a certified authority, and verification (V) by this
authority, using data and models, that any deployment is
successful at increasing CO2 influx from the atmosphere
and enhancing its sequestration in the ocean. Successful
verification of removal and sequestration will result in cer-
tification of the mCDR. The last two MRV components are
mentioned in the last section of the study.
Our study for this “Frontiers in Ocean Observing” sup-
plement of Oceanography focuses on the observational
aspects of the monitoring of open- ocean mCDR deploy-
ments, with less emphasis on the corresponding, essential
modeling components. We nevertheless briefly describe
the latter where necessary.
OBJECTIVES OF AN mCDR MONITORING SYSTEM
Monitoring is essential in order to quantify the effective-
ness (removal) and durability (sequestration) of carbon
storage resulting from open- ocean mCDR deployments
and to identify environmental impacts (NASEM, 2022).
Here, we examine three objectives of a future open- ocean
mCDR monitoring system. Our definitions of detection and
attribution are consistent with those in the Glossary of the
Intergovernmental Panel on Climate Change (IPCC, 2021).
Detection. To quantify the amount of carbon sequestered
as DIC. This will require quantification of metrics that docu-
ment both the amount of carbon removed, based on mod-
els that assimilate accurate in situ measurements of carbon
system variables, and the durability of its removal (i.e., long-
term [decadal] estimates of air- sea CO2 exchanges).
Attribution. To assign the detected carbon sequestra-
tion solely to a particular mCDR deployment. Attribution
requires an understanding of the processes that jointly
determine the success or failure of the given mCDR
deployment and must thus address the influence of com-
plex drivers in the carbon cycle to demonstrate additional-
ity (see next section). Attribution addresses the proportion
of carbon sequestration that can be attributed to an mCDR
deployment, even if there are contributions by other
drivers within the carbon cycle. This will involve advanced
modeling capabilities that simulate the state of the cou-
pled physical and biogeochemical ocean and its modifica-
tion by the mCDR deployment.
Determination of Side Effects. To identify and quantify
ecological impacts of the mCDR and ensure that they do
not exceed the impacts expected from the pilot studies.
The mCDR deployments will necessarily modify the ocean,
but intended and unintended ecological impacts are poorly
known. This will require monitoring ecological variables in
at least the upper 1,000 m as well as deeper, including at
the seafloor where benthic systems could be affected. Side
effects would be assessed through modeling studies of the
impacts of biogeochemical changes on marine ecosystems.
Unacceptable ecological side effects, acute or chronic, may
lead to the termination of an mCDR deployment.
MODEL VALIDATION, EXCLUSION,
AND ADDITIONALITY
To achieve these three objectives, model simulations will
be run, with and without mCDR. In order to fulfill this role,
simulations will have to capture many ongoing changes
in the ocean that include those due to climate change,
the hysteresis effects from climate change, the effects
of other mCDR (and terrestrial CDR), and the effects of
emissions reductions on the ocean carbon cycle. It will
require advanced modeling capabilities that could effec-
tively simulate the state of the coupled physical and bio-
geochemical ocean and its changes under the different
mCDR scenarios. Such models pose many scientific and
technological challenges that impede the development of
Digital Twins of the Ocean (DTO). The DTO will combine
next- generation ocean modeling, artificial intelligence, and
high- performance computing to create digital replicas of
the ocean that are regularly informed and improved with
observations. Some of the observations will be used in the
models, and others will be kept for model validation.
Extensive validation of these models and their improve-
ments (e.g., optimization of model parameters) will be
needed well in advance of and during mCDR deploy-
ments. Confirming that the simulations are consistent
with observations will require the initiation of monitoring
a long time before any mCDR deployment. During this pre-
deployment period, no mCDR could be undertaken in the
mCDR- intended region.
However, there may be cases where model validation
could not be undertaken well in advance of the mCDR
deployments, for example, where a deployment would
take place without prior, long- term consultation with the
authority to which monitoring would be reported. In such
a case, the results of model simulations run with and with-
out mCDR could be compared with observations made in
the mCDR- deployment region and one or more control
regions (with long- term time- series observations) where
conditions would be comparable to those in the selected
mCDR region and where no mCDR of any type would
be deployed. Of course, control regions will eventually
become “contaminated” by the spread of DIC—via ocean
circulation—from mCDR deployed elsewhere (e.g., Boyd
and Bressac, 2016), but they could be used for model vali-
dation before this occurs and even after.
Failure to implement either pre- deployment periods
or control regions would make attribution impossible
and therefore compromise the monitoring of all mCDR
deployments in a given ocean region. In addition, an open
registry or metadatabase of the mCDR pilot studies and
deployments would be very useful in this context. It would
provide information, in particular for modelers, on the
location and depth of each activity and key information
on its technical aspects (e.g., for alkalinization, the mineral
type, timing, and amount of alkalinity added).
Furthermore, we assume here the desirable exclusion
principle, whereby the deployment of one type of mCDR
in a given ocean region excludes the possibility of deploy-
ing other types there. This principle stems from the like-
lihood that multiple- type deployments in a given region,
especially as mCDR deployments aim to sequester carbon
at the gigaton scale,1 would make attribution of individ-
ual deployments impossible (Boyd and Bressac, 2016).
Exclusion is also important because multiple-type deploy-
ments could potentially cause interactive side effects that
were not anticipated by single-type mCDR pilot studies.
Pre- deployment periods or control regions—in situ or
in models—are also needed to assess the additionality of
mCDR deployments, defined in IPCC (2022) as: “The prop-
erty of being additional. Mitigation is additional if the
greenhouse gas emission reductions or removals would
not have occurred in the absence of the associated policy
intervention or activity.” Thus, additionality is the require-
ment that the net increase in the air- to- sea CO2 flux due to
an mCDR deployment (i.e., based on detection and attribu-
tion) exceeds the flux in the absence of this mCDR.
Monitoring for additionality will be especially challeng-
ing as the change in net carbon flux into the ocean and the
magnitude of carbon sequestration caused by an mCDR
deployment will be very small compared to natural air-
sea carbon fluxes and the magnitude of the ocean carbon
sink. In addition, the models will need to take into account
the inherent uncertainties of field measurements. This will
pose challenges for both observation and modeling.
1 The intended gigaton-scale magnitude of mCDR deployments would be much larger than existing multiple overlapping uses and perturbations.
For example, global marine capture fisheries and aquaculture harvested 112 Mt of animals and 36 Mt of seaweeds (fresh weight) in marine waters
in 2020 (FAO, 2022), which represented ~0.02 GtC yr–1.
GENERAL REQUIREMENTS FOR AN mCDR
MONITORING SYSTEM
Guidelines for monitoring were set for the Global Ocean
Observing system (GOOS) in the context of the Framework
for Ocean Observation (FOO; Tanhua et al., 2019). A key
element of the FOO is its organization and coordination
around essential ocean variables (EOVs) rather than spe-
cific observing systems. The mCDR operational system
described here differs from the GOOS observations, but
also focuses on EOVs.
We advocate that “essential mCDR variables” would
include most current EOVs (see GOOS, 2021), along with
more detailed data on lower atmosphere CO2 concentra-
tion and oceanic DIC used to estimate air- sea CO2 flux.
Variables would also include wind speed, which has a
strong influence on air- sea gas exchange.
The effects of mCDR deployments on carbon capture and
sequestration will accumulate over time. Consequently,
meeting the three objectives discussed above will require
long- term monitoring.
Given the remote nature and carbon- sequestration tar-
get of open- ocean mCDR deployments, monitoring their
effects will require systems with at least the following char-
acteristics to efficiently address the objectives of detection,
attribution, and determination of side effects:
• Calibrated sensors on autonomous platforms, that is,
satellites (Figure 2) and in situ robots (see Box 1)
• Sampling over large surface areas to address horizontal
eddy diffusion and transport
• Recurrent long- term measurements, commensurate
with the duration of mCDR deployments
• Quasi- simultaneous estimates of air- sea CO2 exchange
and concentrations of DIC, particulate inorganic carbon
(PIC), DOC, and POC from surface to depth to monitor
the fate of the additional carbon
Air- sea CO2 flux cannot be measured directly over large
areas; it would be estimated by modeling. To do so, at
least two parameters of the carbonate system should be
measured in the water column. These parameters include
pH, total DIC, total alkalinity (TA), and CO2 partial pressure
(pCO2). Detecting changes in the carbonate system is chal-
lenging, and detecting a superimposed mCDR effect would
be very difficult.
The monitoring system would combine satellite remote
sensing (Figure 2) and long- term regional in situ measure-
ments. The latter would be performed with autonomous
FIGURE 2. One of the numerous satellites used for mCDR monitoring,
PACE (Plankton, Aerosol, Cloud, ocean Ecosystem, to be launched in
early 2024) will be equipped with a hyperspectral spectrometer that
could be used for assessing possible ecological side effects of mCDR
deployments (e.g., changes in phytoplankton community composi-
tion). This figure is a derivative of https://commons.wikimedia.org/wiki/
File:PACE_Spacecraft_beauty2.jpg by NASA, in the public domain.
robots (see Box 1), as described by Chai et al. (2020).
Biogeochemical data would subsequently be analyzed using
AI and assimilated in models. The integration of these plat-
forms, analyzing their data with AI, and combining the data
with models is already partly implemented in open- ocean
research (e.g., Claustre et al., 2021) and could be readily
applicable to monitor open- ocean mCDR deployments.
Ideally, the observational and modeling components of
the mCDR monitoring system should be in place prior to
an mCDR deployment. If this is impossible, data collected
by the global networks of Biogeochemical- Argo (BGC- Argo)
floats (Figure 3) and ocean color satellites (Figure 2) could
document natural variability and contribute to the valida-
tion/calibration of models required for attribution.
COMPONENTS OF AN mCDR
MONITORING SYSTEM
Satellites and underwater robots operate autonomously,
making relatively high- frequency measurements over sev-
eral years. Present- day BGC- Argo floats (Figure B1) can
achieve 300 profiles of up to 13 different variables2 during
their lifetimes, for example, profiling every five days over
four years. Horizontally, satellites (Figure 2) cover large
surfaces (with a spatial resolution of up to 4 × 4 km), and
2 Temperature, salinity, dissolved O2, pH, dissolved NO3, chlorophyll a, particulate backscattering coefficient (bbp), colored dissolved organic
matter (CDOM), downwelling irradiance, upwelling radiance, particle size spectra, particles and plankton 100–2,00 µm, optical sediment trap
(transmissometer).
BOX 1. ROBOTS
TO MONITOR mCDR
DEPLOYMENTS
The word “robots” refers here to autonomous vehicles and
platforms, which include:
• Buoyancy- driven robots, encompassing
° Biogeochemical (BGC)- Argo floats (Figures B1 and B2)
° BGC- gliders (Figure B3)
• Uncrewed surface vehicles (USVs; Figure B4)
Floats and USVs could rendezvous for data intercomparison
and transfer (Figure B5). In the future, USVs could intercept
and reposition floats to maintain them in the best monitoring
locations or create “virtual moorings.”
FIGURE B1. A jumbo biogeochemical profiling float (BGC- Argo
float, REFINE type NKE CTS5) can provide profiles every five
days over four years. Sensors are identified that contribute
to the three mCDR monitoring objectives (detection, attribu-
tion, and determination of side effects). Photo credit: David
Luquet, used with his permission. Licensed under CC BY- SA
4.0 by Thomas Boniface
FIGURE B2. BGC- Argo floats record variables from 2,000 m
depth to the surface, where data are rapidly transmitted to a sat-
ellite. The floats then descend to a parking depth (e.g., 1,000 m)
where they stay for 10 days before initiating the next vertical
profile. During the parking phase, floats have the potential to
monitor key properties for mCDR such as wind (passive acous-
tic) and particle flux (transmissometer used as optical sediment
trap). Photo credits: (top) David Luquet and (bottom) Thomas
Boniface, used with their permissions. Licensed under CC BY- SA
4.0 by Thomas Boniface.
BGC- Argo Float