Ocean-based Carbon Removal

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Contents ii iii iv v vi

Editorial Board On the Cover Publishing Schedule and Advertisements Guest Editor’s Note from Kate Moran Soundings with Wil Burns


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Lodestar … Curran Crawford


Flood Damage Assessment Using Satellite Observations within the Google Earth Engine Cloud Platform Mehdi Sharifipour


Tadbir Kesht Golestan Company Meisam Amani Wood Environment and Infrastructure Solutions Armin Moghimi K.N. Toosi University of Technology

Martin Scherwath Ocean Networks Canada


Durable Sequestration of Carbon Dioxide: The Ocean to the Rescue Benoît Pirenne, Kunal Khandelwal, Kate Moran,


Ocean Carbon Dioxide Removal using Wavepowered Artificial Upwelling Pumps: Technical Description, Practical Considerations, and Measurement Methodology Philip Kithil, Salvador Garcia, Ian Walsh

Ocean-Based Climate Solutions Inc.


Is Sinking Carbon the Best Carbon Sink? Opportunities and Challenges of Using Sea Kelp to Seek Help with the Climate Crisis Michael James Teasdale, Justin J. So

Wood Kiley Best Fisheries and Marine Institute


Offshore Wind Energy, Direct Air Capture, and Carbon Sequestration in Basalt: Solutions for Atmospheric CO2 Reduction David Goldberg Columbia University Kate Moran Ocean Networks Canada

Peer-Reviewed Papers 38

Experiments of Vortex-induced Vibration for a Smooth Circular Cylinder at Mass Ratios 3<M*<4 Sukru Cem Colakoglu

Gemak TGE Shipyard R&D Center Erinc Dobrucali Bursa Technical University Abdi Kukner, Aytekin Duranay, Omer Kemal Kinaci Istanbul Technical University

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Simulation, Optimization, and Economic Assessment of Pelamis Wave Energy Converter Hana Ghaneei, Mohammadreza Mahmoudi

Northern Illinois University

100 Technicalities … Under Pressure: Getting Carbon Dioxide Out of the Atmosphere and Under the Seafloor Amanda Lefton and Scott Mabry 102 Heavy Metals in Snow Crab (Chionoecetes opilio) Bioproducts Heather Burke

Fisheries and Marine Institute Francesca Kerton Memorial University

Spindrift 128 Q&A with Kelly Oskvig 132 Trade Winds … Global CO2 Initiative 134 Inside Out … A Solution Trifecta for Ocean-based Carbon Dioxide Removal Eric Siegel, Ocean Frontier Institute 136 Turnings … Ocean Drones Provide Systematic Observation to Enable Climate Solutions Richard Jenkins, Saildrone 140 Reverberations … Ocean Solutions in the Carbon Market Freya Chay, CarbonPlan 142 Homeward Bound … Climate Change and Seaweed Cultivation – Somewhere Between Hope and Hype Bill Collins, Cascadia Seaweed 144 Parting Notes … Shorefast Foundation The Journal of Ocean Technology, Vol. 17, No. 1, 2022 i

PUBLISHER Bill Carter Tel. +001 (709) 778-0762 info@thejot.net

MANAGING EDITOR Dawn Roche Tel. +001 (709) 778-0763 info@thejot.net

GRAPHIC DESIGN Danielle Percy Tel. +001 (709) 778-0561 danielle.percy@mi.mun.ca

TECHNICAL CO-EDITORS Dr. David Molyneux Dr. Katleen Robert Director, Ocean Engineering Research Centre Canada Research Chair, Ocean Mapping Faculty of Engineering and Applied Science School of Ocean Technology Memorial University of Newfoundland Fisheries and Marine Institute ADMINISTRATION Crystal-Lynn Gorman

WEB SITE AND DATABASE Mike Quinton and Scott Bruce



EDITORIAL BOARD Dr. Keith Alverson USA Dr. Randy Billard Virtual Marine Canada Dr. Safak Nur Ertürk Bozkurtoglu Ocean Engineering Department Istanbul Technical University Turkey Mr. Terry Bullock Wood plc Canada

Dr. Sebnem Helvacioglu Dept. Naval Architecture and Marine Engineering Istanbul Technical University Turkey Dr. John Jamieson Dept. Earth Sciences Memorial University Canada Ms. Paula Keener Global Ocean Visions USA

Dr. Daniel F. Carlson Institute of Coastal Research Helmholtz-Zentrum Geesthacht Germany

Mr. Richard Kelly Centre for Applied Ocean Technology Marine Institute Canada

Dr. Dimitrios Dalaklis World Maritime University Sweden

Dr. Sue Molloy Glas Ocean Engineering Canada

Mr. Randy Gillespie Windover Group Canada

Dr. Kate Moran Ocean Networks Canada Canada

Ms. Kelly Moret Hampidjan Canada Ltd. Canada Dr. Glenn Nolan Marine Institute Ireland Dr. Emilio Notti Institute of Marine Sciences Italian National Research Council Italy Ms. Elisa Obermann Marine Renewables Canada Canada Prof. Fiona Regan School of Chemical Sciences Dublin City University Ireland Dr. Mike Smit School of Information Management Dalhousie University Canada

A publication of

Dr. Timothy Sullivan School of Biological, Earth, and Environmental Studies University College Cork Ireland Dr. Dietrich Wittekind DW-ShipConsult Germany Dr. Jim Wyse Maridia Research Associates Canada SPECIAL EDITORIAL ADVISORS Louise White Queen Elizabeth II Library Memorial University of Newfoundland Canada Catherine Lawton Dr. C.R. Barrett Library Fisheries and Marine Institute Canada

FPO FS64986 Printed in Canada

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Academic and Scientific Credentials The Journal of Ocean Technology is a scholarly periodical with an extensive international editorial board comprising experts representing a broad range of scientific and technical disciplines. Editorial decisions for all reviews and papers are managed by Dr. David Molyneux, Memorial University of Newfoundland, and Dr. Katleen Robert, Fisheries and Marine Institute.

On the


The Journal of Ocean Technology is indexed with Scopus, EBSCO, Elsevier, and Google Scholar. Such indexing allows us to further disseminate scholarly content to a larger market; helps authenticate the myriad of research activities taking place around the globe; and provides increased exposure to our authors and guest editors. All peerreviewed papers in the JOT are open access since Volume 1, Number 1, 2006. www.thejot.net

A Note on Copyright The Journal of Ocean Technology, ISSN 1718-3200, is protected under Canadian Copyright Laws. Reproduction of any essay, article, paper or part thereof by any mechanical or electronic means without the express written permission of the JOT is strictly prohibited. Expressions of interest to reproduce any part of the JOT should be addressed in writing. Peer-reviewed papers appearing in the JOT and being referenced in another periodical or conference proceedings must be properly cited, including JOT volume, number and page(s).

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A silhouette of giant kelp is framed against the sun and sunrays in clear sea water breaking onto an outcrop of ocean basalt.

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Publishing Schedule at a Glance The JOT production team invites the submission of technical papers, essays, and short articles based on upcoming themes. Technical papers describe cutting edge research and present the results of new research in ocean technology, science or engineering, and are no more than 7,500 words in length. Student papers are welcome. All papers are subjected to a rigorous peer-review process. Essays present well-informed observations and conclusions, and identify key issues for the ocean community in a concise manner. They are written at a level that would be understandable by a nonspecialist. As essays are less formal than a technical paper, they do not include abstracts, listing of references, etc. Typical essay lengths are up to 3,000 words. Short articles are between 400 and 800 words and focus on how a technology works, evolution or advancement of a technology as well as viewpoint/commentary pieces. Submissions and inquiries should be forwarded to info@thejot.net.

Upcoming Themes

All themes will be approached from a Blue Economy perspective.

Summer 2022

Marine archeology

Fall 2022

Climate change and the ocean

Winter 2022

Ocean technology

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Guest Editor's Note There is no place on Earth that will avoid the impacts of climate change. Greenhouse gas (GHG) emissions are over 50% higher than 30 years ago, when scientists’ warnings began to inform political discourse. The impacts are causing long-lasting changes to the climate system and will result in irreversible consequences if we do not act now. Global economic losses from climaterelated disasters are currently in the hundreds of billions of dollars annually and increasing rapidly. Climate action is now being demanded by world youth; around the globe as COVID-19 wanes, millions of young people are again taking part in school strikes for climate action. They are demanding action because they can see for themselves climate change impacts – record-breaking heat waves, extreme storms, coastal retreat, wildfires, small island states on the verge of disappearing, ocean acidification, loss of drinking water, mass migrations, and war.

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Dr. Kate Moran is the president and CEO of Ocean Networks Canada.

It is well recognized that climate scenarios must include negative emission technologies (NETs), sometimes called carbon dioxide removal (CDR), on a massive scale. The Intergovernmental Panel on Climate Change 2018 Special Report (Global Warming of 1.5°C) concluded with high confidence that “… pathways limiting warming to 1.5°C … [all] use CO2 removal … to neutralize emissions from sources for which no mitigation measures have been identified and, in most cases, also to achieve net negative emissions to return global warming to 1.5°C. The longer the delay in reducing CO2 emissions … the larger the likelihood of exceeding 1.5°C, and the heavier the implied reliance on net negative emissions.” Most recently, the International Energy Agency Net Zero by 2050 (2021) report identified the need for NETs as early as 2035. This urgency is one of the reasons that science and industry must look to the ocean, which comprises 70% of the planet, for CDR solutions. The ocean currently is the largest mitigator of our industrial GHG’s by absorbing over 30% of our emission and 90% of the heat generated by global warming. Without the ocean, our ability to survive on the planet today would be severely impaired. Thus, there is a growing community exploring how we might enhance the ocean’s role in CDR to develop an expanded portfolio of removal methods. I encourage you to explore the examples in this issue and other new content, such as the U.S. National Academy of Sciences recent report on ocean-based carbon dioxide removal and an initiative called Solid Carbon that aims to utilize existing ocean technology and combine it with direct air capture of CO2 technology as a future sustainable industry for Canada. With the longest coastline in the world, Canada has the potential to lead ocean-based CDR globally.

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Soundings The Aspen Institute’s Guidance for Ocean-based Carbon Dioxide Removal Projects As a number of studies in recent years have concluded, the temperature objectives of the Paris Agreement can likely only be effectuated at this point by a combination of aggressive decarbonization of the global economy AND large-scale deployment of so-called carbon dioxide removal (CDR) options. The lion’s share of the early research on CDR approaches focused on terrestrial options, such as afforestation/reforestation, regenerative agriculture, bioenergy and carbon capture with sequestration, direct air capture, and enhanced mineral weathering. However, growing concerns about the sustainability of many of ALAN LUNTZ these approaches at large-scale deployment, as well as cost concerns and high energy demands in the case of some options, have led to an increasing focus on the potential role of ocean-based carbon removal, many of which are discussed in this special issue. Ocean-based CDR has the potential to enhance the already substantial role that the seas play as a carbon sink. However, many of these options, most of which are in nascent research stages, could also pose risk to ocean ecosystems and the livelihoods of those who work in sectors such as fishing or tourism. Two international treaty regimes – the London Convention/Protocol and the Convention on Biological Diversity – have sought to establish a regulatory framework for ocean-based CDR approaches. However, the focus has primarily been on only one process, ocean iron fertilization. There has been a failure to identify key stakeholders and potential key players are not parties to one or more of these agreements. There also appears to be little domestic legal guidance in place for ocean CDR approaches that may take place within coastal waters. Concerns of this nature, as well as a sense that it may be premature to establish rigid legal rules for emerging ocean CDR technologies, led the Aspen Institute’s Energy and Environment Program to convene a group of experts to provide “guidance to researchers and practitioners on how to enable responsible research and development of ocean-based CDR activities that may become deployable at scale in a timely fashion.” The drafters of the guidance document emphasized that the narrow remit of the group was to set forth key questions to be considered by policymakers, regulators, communities, and other key actors in the context of research and testing of ocean-based approaches. Among the key principles and questions outlined by the Aspen Institute Discussion Group are the following:

Definition and Verification of Carbon Dioxide Removal Potential. The Discussion Group concluded that research projects should, inter alia, assess the extent of additional sequestration over and above what would have occurred if the project was not deployed, the longevity or permanence of sequestration, evidentiary protocols for demonstrating proof of concept, the results of full life cycle accounting of costs and benefits, and how to report, track, and regulate flows of carbon removal that might cut across the high seas/one territory and another territory.

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Catalogue Potential Environmental Externalities (Negative and Positive). The Discussion Group emphasized the need to identify and report on intended and unintended environmental impacts associated with ocean-based CDR, as well as observational baselines, assessment of the reversibility of approaches that manifested themselves in serious negative impacts, and procedures to ensure that robust ecological impacts assessments are conducted. Catalogue Potential Societal Externalities (Negative and Positive). The Discussion Group emphasized the need to assess the potential societal impacts of ocean CDR research, protocols for identification of stakeholders, optimal structuring of stakeholder engagement, and assessment of both procedural aspects of stakeholder engagement, such as equity and representation, and substantive outcomes; that is, ensuring that the process was responsive to stakeholder concerns. The Group also called for an assessment of potential disproportionate impacts on certain communities or places, and whether this coincides with climatic or other environmental burdens. Governance, Funding, and Cessation. Finally, the Discussion Group focused on protocols for projects that move from laboratory settings to in-situ testing. This includes considerations of engagement of pertinent regulatory regimes at the outset of projects, the adequacy of regulatory institutions at all pertinent scales, the existence of grievance mechanisms, and adequacy of funding for all phases of a project’s operation, including planned or unplanned shutdowns.

The drafters of the Guidance conclude with a series of recommendations for next steps, including testing and honing the guidelines through practical applications by policymakers, researchers, and other stakeholders. Moreover, they call for a parallel development of a more comprehensive Code of Conduct. Of course, therein may lie the rub. Some ocean-based CDR projects are already selling carbon credits in voluntary carbon markets without operationalizing most of the recommendations in the Guidance, and likely will continue to do so unless they are compelled to take more account of the considerations outlined in this document. This may require more active intervention on the part of prospective investors, purchasers of credits, or government entities. To date, a few companies, including Microsoft and Stripe, have embraced many of these standards in vetting potential carbon removal purchases, but they are the exception to the rule. Incorporation of elements of these guidelines by carbon removal verification companies and organizations, such as Verra’s Verified Carbon Standard, Gold Standard, and the Science Based Targets initiative could help to drive adoption by project developers. The Aspen Institute has provided a sound foundation for ensuring the integrity, safety, and equity of ocean-based CDR. Other key actors must now step up to the plate.

Dr. Wil Burns is a visiting professor with the Environmental Policy and Culture Program at Northwestern University in Illinois, U.S.

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Informative Cutting Edge Provocative Challenging Thought Provoking International

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Durable Sequestration of Carbon Dioxide The Ocean to the Rescue by Benoît Pirenne, Kunal Khandelwal, Kate Moran, and Martin Scherwath

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Figure 1: Potential pathway of CO2 equivalent emissions to limit global warming to 1.5°C.

Introduction The world currently adds about 40 Gt of greenhouse gases to the atmosphere each year. The global consequences of this pollution are starting to be felt everywhere through a steady increase of extreme weather events, and the disappearance of sea-ice and the breakup of glaciers leading to sea level rise. Whereas the elimination of fossil fuels will reduce the amplitude of the crisis to come, a long-term solution will require negative emission solutions, i.e., aggressive removal of carbon dioxide through direct or indirect capture as well as permanent storage (Figure

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1). Laboratory research and field experiments have demonstrated not only the possibility to capture CO2 directly from the air but also that its injection into young ocean basalt will convert it to a solid mineral in a matter of two years. Ocean Networks Canada, with partners across academia, governments, and industry, is leading a project to assess the needed technologies and to perform a medium scale storage demonstration. However, even if successful, the volume of CO2 captured with such technologies will not be sufficient to allow for the continued production of greenhouse gases: the techniques can only be

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technologies and their reproduction at scale around the globe to support the needed removal of CO2 from the atmosphere. The technologies needed include direct air capture (DAC) powered by renewable energy and injection into suitable deep basalts below the sediment layers in many areas in the global ocean. To avoid the energy and/or infrastructure costs related to the transport of CO2, and not to compete with sustainable energy needs on land, the system requires offshore renewable energy sources, a CO2 capture plant, a conditioning system to make the CO2 supercritical and ready to be injected from a surface platform a few hundred metres below the seabed. A monitoring system to oversee the injection and verify the transformation of the fluid into a mineral is also required. The technologies have all been independently demonstrated both in the lab and in the field. This project is about evaluating the feasibility of a full scale, offshore system, demonstrating its efficacy and evaluating its scaling potential. A critically important and interesting aspect of the project involves looking at societal and regulatory acceptance as well as investor acceptance.

seen as a mitigation measure to be broadly used after we as a society eliminate the use of fossil fuels for our energy needs. Solid Carbon Among the climate mitigation solutions required to avert the worst consequences of humanity’s careless dumping of greenhouse gases into the atmosphere and, consequently, the ocean, one solution offers a particularly attractive outcome: turning CO2 into rock, and keeping it deep under the seabed for geological times. This solution requires the combination of a number of existing

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This form of ocean-based climate mitigation solution is perhaps the only currently considered one that does not involve diluting more CO2 in the ocean waters and appears to have the least significant side effect. The Technologies and the Potential Direct CO2 air capture has been researched, tested, and prototyped for a few years now. A handful of groups and companies have solutions that are now being operationalized. They include, in particular, Carbon Engineering in British Columbia, and Climeworks in Switzerland whose “Orca” system is now operational in Iceland. The latest capture system implementations are a demonstration that, with suitable marinization of the machinery, offshore operation will be achievable.

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Figure 2: Target area for Solid Carbon project, the northern part of the Cascadia Basin in the NE Pacific with the existing NEPTUNE ocean observatory.


DAC does, however, require a lot of energy in the form of high heat. Clearly, that energy has to be of the renewable kind to make the process meaningful. For use offshore, the energy, therefore, has to come from either wind, solar, wave, net-zero biofuels, or a combination of these. Given the locations foreseen for the implementation of CO2 sequestration systems and the levels required, only the most recent and most powerful floating wind turbines will allow for the supply of energy required. A publication of the study of the requirements is in preparation by the Solid Carbon team. The injection techniques currently being considered involve existing offshore ocean technologies. Storing the CO2 Ninety-five percent of the basalts suitable for turning CO2 into rock are found in the ocean. The Cascadia area of the Juan de Fuca tectonic plate where the Solid Carbon team is planning to perform the demonstration has a theoretical storage capacity of 750 Gt of CO2, or the equivalent of 20 years of recent global

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emissions. This site is chosen for its proximity to the Ocean Networks Canada (ONC) NEPTUNE observatory (Figure 2), a real-time ocean monitoring system that provides power and communication capabilities to hundreds of sensors measuring as many ocean variables. The existence of ONC’s infrastructure close by allows for the establishment of a baseline before the demonstration is conducted, but will also enable the collection of data during and after the experiment and allow for assessment of its performance overall. Societal Impact On the critical path of any major infrastructure installation is the need to obtain the necessary permits and gain the trust and support of the authorities, the public, and investors. Solid Carbon considered these three aspects early on in the process and has placed equal resources on this facet of the project as it has on the technologies and demonstration preparation. The novelty of an undertaking such as Solid Carbon requires preparation as there is no

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precedent to lean on as we look at e.g., permitting. This focus has enabled partner researchers at Columbia University to evaluate and report on the regulatory framework that would guide such a system and identify possible gaps by engaging government officials in both the U.S. and Canada. This engagement has allowed many government levels to not only be aware of the initiative, but also to understand how to prepare for their support well ahead of time. Partner social scientists at the University of British Columbia have performed extensive public opinion surveys in both Washington State and British Columbia to assess the comfort level and the concerns of the wider public with what amounts to a geoengineering initiative. The surveys have so far concluded a good level of comfort with the Solid Carbon concept, particularly owing to having the capture and injection installations invisible from shore, with minimal impact on benthic life, and with the absence of byproducts in the overall process. A third aspect of the societal impact of Solid Carbon is investor acceptance. Successive cohorts of MBA students from the University of Victoria have, in turn, studied the evolving landscape of carbon removal projects, carbon markets, the motivation and requirements of large corporations looking to be part of the solution, and the appeal of Solid Carbon for governments committed to meet their net zero obligations. All of these considerations will lead to the development of a suitable business model that would enable the global scale-up of this gigaton-level solution. Beyond the business model, the teams are also focused on researching sustainable financial models to support such an intrinsically capital-intensive undertaking that include tax credits, subsidies, offsets, and carbon credits. These models also take into consideration the transition of the workforce from a sunsetting fossil fuel industry together with comparators that include the costs of not doing and the various risks of such undertakings.

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Figure 3: Project timeline from early focus research to the potential commercial deployment of this negative emissions technology.

Timeline Solid Carbon is the result of the convergence, over two decades, of a number of separate events and advances (Figure 3): from the first conceptual and theoretical papers conceiving of the storage of CO2 in ocean basalt; a pre-feasibility study funded by the U.S. Department of Energy, CarbonSafe Cascadia; the installation of the Ocean Networks Canada observatory in the critical area where extensive studies and experiments in fluid transport in porous rocks were performed; to storage tests in Iceland (CarbFix) that confirmed the theory. The currently ongoing feasibility work will continue until September 2023, beyond which the team will be able to perform a demonstration at scale of the storage aspects. This is anticipated to take place in 2025. At that point, the design of prototype units and their construction will commence and start operation in 2030. The multiplication of the units based on the lessons learned by the prototype system will continue through 2040 at which point the individual units combining DAC and injection will be installed in multiple regions around the global ocean and operations will start.

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Conclusion As the world continues to burn fossil fuels and the 1.5ºC target of average global temperature rise by 2050 becomes more and more elusive, there will be a need for an aggressive way to remove CO2 from the air by the time we stop most of our greenhouse gas release. There will be no magic wand to be waved to make that happen: the laws of physics will prevent us having an easy way out of this issue: any solution we come up with will be energy intensive as the relative volumes of CO2 in the atmosphere are large. Finding the most efficient solution and implementing it is one of today’s most pressing issues for the sake of our current and future generations. Solid Carbon, as presented in this essay, offers an approach to combine CO2 extraction from the air with a permanent disposal. Its advantages include the capacity of the possible CO2 reservoirs, the permanence of the removal, the minimal impact on property and life, and the operational model of offshore plants that can be remotely controlled with limited physical human presence offshore, operating continuously for at least two decades. On the other side, this will be a capital intensive endeavour with very significant construction and setup costs. But we can do it: the financial models that are emerging and the various approaches to putting a price on CO2 can make this scalable technology a reality within the next two decades. For further details on the Solid Carbon project, see the essay in this issue titled “Offshore Wind Energy, Direct Air Capture, and Carbon Sequestration in Basalt.” u Acknowledgment The authors acknowledge support for the Solid Carbon partnership from the Pacific Institute for Climate Solutions (PICS).

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Benoît Pirenne is Ocean Networks Canada’s director, user engagement. He joined the University of Victoria in October 2004 to build the Data Management and Archiving System for the NEPTUNE Canada and VENUS observatories, now Oceans 3.0. The division he directs consists of four departments: Science Services, Applied Science Solutions, the Canadian Integrated Ocean Observing System-Pacific Regional Association, and the World Data System-International Technology Office. Previously, Mr. Pirenne spent 18 years at the European Southern Observatory (ESO, Munich, Germany), a leading organization for astronomical research. At ESO, he assumed a number of scientific and technical positions. As head of the Operations Technical Support Department in this organization, he was responsible for running the data management and archiving system supporting both ESO’s telescopes and the NASA/ESA Hubble Space Telescope. Mr. Pirenne has a bachelor degree in computer science from Liège, Belgium, and a master’s degree in computer science from the University of Namur, Belgium. As an associate at Ocean Networks Canada, Kunal Khandelwal brings over 10 years of strategic partnerships and business solutions experience. With a MBA in sustainable innovation from the University of Victoria and a bachelor of technology in mechanical engineering, he loves working at the cross-section of marine technology, business, and innovation on projects that have the potential to drive impact to coastal communities across the globe. Having lived and worked in both Canada and India, he brings a unique global perspective spanning both the developed and developing world, with the potential to identify, evaluate, and execute out-of-the-box impactful solutions. Dr. Kathryn (Kate) Moran joined the University of Victoria in September 2011 as a professor in the Faculty of Sciences and as director of NEPTUNE Canada. In 2012, she was promoted to the position of president and CEO, Ocean Networks Canada. Since then, she has led and grown the organization following the vision of enhancing life on Earth by providing knowledge and leadership that deliver solutions to science, society, and industry. Her previous appointment was professor at the University of Rhode Island with a joint appointment in the Graduate School of Oceanography and the Department of Ocean Engineering. She also served as the Graduate School of Oceanography’s associate dean,

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research and administration. From 2009 to 2011, Dr. Moran was seconded to the White House Office of Science and Technology Policy where she served as an assistant director and focused on Arctic, polar, ocean, the Deepwater Horizon oil spill, and climate policy issues. Dr. Moran co-led the Integrated Ocean Drilling Program’s Arctic Coring Expedition, which was the first deepwater drilling operation in the Arctic Ocean. This expedition successfully recovered the first paleoclimate record from the Arctic Ocean. She also led one of the first offshore expeditions to investigate the seafloor following the devastating 2004 Indian Ocean earthquake and tsunami. Previously, Dr. Moran was a scientist at Canada’s Bedford Institute of Oceanography where one of her major research focus areas was the Arctic Ocean. She also served as the director of the international Ocean Drilling Program in Washington, D.C.; managed missionspecific drilling platform operations in the North Atlantic and Arctic; designed and developed oceanographic tools; participated in more than 40 offshore expeditions; and has served as chair and member of national and international science and engineering advisory committees and panels. Professor Moran is active in public outreach (through public lectures, national panel discussions, and teacher training) on topics related to the Arctic, ocean drilling, and climate change. She has testified on climate change to the U.S. Senate Committee on Environment and Public Works. At the University of Rhode Island, she spearheaded a research initiative on offshore renewable energy. Watch Dr. Moran’s TEDx Talk on “connecting our planets to the internet.” Dr. Martin Scherwath is a senior staff scientist at Ocean Networks Canada, and adjunct assistant professor at the School of Earth and Ocean Sciences at the University of Victoria, B.C., Canada, with expertise in marine geophysics, gas hydrates, seabed dynamics, tectonic processes, and more recently worked on geological storage of carbon. Dr. Scherwath earned a M.Sc. degree from Leeds University in the U.K. and a doctorate from Victoria University in Wellington, New Zealand.

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Ocean Carbon Dioxide Removal using Wave-powered Artificial Upwelling Pumps Technical Description, Practical Considerations, and Measurement Methodology by Philip Kithil, Salvador Garcia, and Ian Walsh

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Figure 1: Ocean-Based Climate Solutions Inc.’s ocean deployable artificial upwelling pump (AUP). OCEAN-BASED

Introduction Wave-powered artificial upwelling pumps (AUPs or pumps) have the potential to achieve rapid, large-scale, and low-cost carbon dioxide removal by stimulating natural biological ocean productivity in the form of phytoplankton, with significant co-benefits including cooling of the upper ocean, fisheries enhancement, and reoxygenation of surface waters. The upwelling of nutrients utilized through phytoplankton growth and subsequent export to the deeper ocean is the mechanism by which gradients in nutrients exist in the ocean. Upwelling rates are higher than adjacent areas. For example, in the Eastern Equatorial Pacific, there is generally a commensurate increase in sedimentation rate, which is the ultimate sequestration of carbon. Ocean-Based Climate Solutions Inc. (OceanBased) has developed an ocean deployable AUP that is scalable to the depth required to

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maximize the net export of carbon dioxide from the surface ocean (Figure 1). The pump system consists of a surface buoy and intake valve connected with a fabric tube that serves as the strength member and the conduit for upwelling water. The fabric tube length is customizable for the location of the system. The ocean is a resource that we can use to draw down the atmospheric carbon dioxide concentration. At the least, the wave power of the ocean is a renewable energy resource that is widely distributed at sufficient density to drive nutrient fluxes into the ocean’s photic zone, where phytoplankton will grow. Because no additional energy is needed to drive the uptake of CO2 and subsequent fate, we can decouple ocean-based carbon dioxide sequestration from price changes and the availability of energy. Hence, wave energy drives the pumps, solar energy drives the carbon dioxide absorption process through phytoplankton growth, and biological and

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physical processes drive the export and sequestration. We only require energy for the production, deployment, monitoring, upkeep, and disposal of the pumps and ancillary instruments. It may read like a long list, but those requirements will be similar for every methodology we deploy to reduce atmospheric carbon dioxide. The energy dynamics and carbon flows of artificial upwelling for carbon dioxide removal are relatively simple because the process is an amplification of oceanic ecosystem responses. Artificial upwelling is not introducing new organisms or processes but instead increasing the rate of upper ocean mixing and using the natural reactions to upwelling to increase carbon dioxide fluxes. The ocean is also attractive to the widespread deployment of carbon capture technology because there is minimal interference with other human activities. However, remoteness has a cost also, as access to the remote ocean means transport length scales and time to intervention can become significant and potentially prohibitive. We think that selecting ocean areas to deploy artificial upwelling pumps is more of an economic function than an areal limitation. Vast ocean areas are nutrient-limited for at least a majority of the year. If we looked only at the ocean’s most oligotrophic (nutrient-limited) areas, we would have more than 10 million square kilometres to deploy pumps. Upwelling areas are highly productive relative to oligotrophic areas and often sustain fisheries that are significant on a local to worldwide scale as a protein source. Upwelling areas are also associated with current high carbon deposition environments. That relationship has been confirmed for many years, such that upwelling areas are the source of the fossil fuel deposits that we have exploited to increase atmospheric carbon. Given the clear linkage between upwelling, nutrient supply, and carbon deposition in the ocean, the efficacy of artificial upwelling as

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a sequestration mechanism is only a matter of efficiency and demonstration to convert the potential into reality. Monitoring carbon dioxide uptake and measuring carbon dioxide through certification of carbon dioxide sequestration is nontrivial. The ocean creates unique challenges because of its vastness, remoteness, sparsity observations, and quality measurements. Balancing the lack of ocean data and the cost of that data because of its scarcity is the large scales of the ocean, which allows for a somewhat sparse dataset to be sufficient to generate usable products. Probably the best example of this is the Argo program which, with a base of 3,000 autonomous floats collecting temperature, salinity, and pressure profiles every 10 days, provides a descriptive dataset that enables initialization of ocean and coupled oceanatmosphere models. Because carbon dioxide uptake and phytoplankton productivity relies on conditions local to the phytoplankton itself, the scale of data collection to capture these processes relative to global climate change has to be greater than the current Argo program. Efforts to reach this scale of measurement are currently underway, with the advent of the BioArgo program and developing national and regional scale ocean observing systems. In this regard, artificial upwelling pump deployments can take advantage of the increasing availability of near real-time observations, models, and forecasting and serve as a data source for those activities. Active datasets and models will be used to decide on deployment sites and specific locations, for tracking the plumes of upwelled water, for generating the observations, and finally, for the comparisons necessary to demonstrate the additionality related to the artificial upwelling. Ocean-Based intends to build and deploy arrays of AUPs in low-productivity ocean gyres. Our rollout plan includes monitoring and assessing the benefits of artificial upwelling and potential as of yet undefined problems.

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Figure 2: Surface buoy (left) and intake (right) assemblages.

Considering the intended modification of the ecosystem by supplying nutrients through the mixing of upper thermocline water, the risks of artificial upwelling are small and readily ameliorated by removing the pumps. We mirror our expectations of a rapid response to the onset of artificial upwelling in production and export relative to the deployment by the expectation of rapid diminishment of the effects of pumping upon the removal of the pump. Once we remove the supply of upwelled water, the ambient water effectively closes in on the pump plume in time and space, i.e., the plume will dissipate over the same period that the plume was discernable. Higher trophic levels will revert to ambient at a fraction of their respective mean lifespan.


using standard methods of communicating the positions of the pumps, such as notices to mariners, through the web with open access to pump position information and mooring lighting and radar reflectors. Pump Design and Deployment Ocean-Based’s pump design is based on offthe-shelf and commodity materials available worldwide, allowing for the placement of pump factories near deployment ports. The design shortens the supply chain and reduces operational and carbon footprint costs. The pumps’ monitoring instruments and location and communication systems are readily available from multiple suppliers.

Negative impacts of artificial upwelling and pump deployments relative to human activity will be minimized simply because of the remoteness of the pump deployments. We expect the encounter frequency with ships to be minor. We minimize harmful outcomes by

The Ocean-Based pump design consists of a buoyant surface float with a subsurface pump outlet structure suspended a few metres below the surface float. The submerged outlet is attached to the top of a fabric tube that can be up to 500 m long and customized to the deployment site. At the bottom of

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Figure 3: Sketch of pump operation. 1) Upon initial deployment, water in the tube is of mixed nutrient densities that are mostly tied to which stratum of the ocean that part of the tube is in. 2) As the buoy descends off a wave, it causes the lower pump valve to open, infiltrating nutrient-dense deep ocean water into the bottom. As the buoy moves up the next wave, the valve closes which forces water up the tube. 3) Soon after deployment, the nutrient-dense water has travelled to the top of the tube where it is released, supporting growth of phytoplankton.

the tube is a weighted bottom inlet valve. Before deployment, the tube is spooled onto the buoy and attached to the bottom valve (Figure 2). When deployed, the weighted bottom valve sinks, which unspools the tube while priming it with seawater. The weight of the bottom inlet valve assembly keeps the entire pump near vertical and relatively stiff, allowing the entire pump to move vertically in response to the wave state. The inlet valve system opens during the “downstroke” of the pump as the pump rides down a surface wave and closes as the pump rises to the crest of the next wave. This ratchet effect moves slugs of water from the depth of the inlet valve upwards to spill into the ambient surface water at the outlet depth (Figure 3).

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As the water rises in the tube, the colder water will absorb heat from the warmer water surrounding the tube. The absorption of heat, in turn, causes the water in the tube to accelerate upwards as it expands and becomes less dense than the surrounding water. The process is known as the “salt fountain” effect described by Henry Stommel and co-authors in 1956. This addition to the net upward velocity due to the wave-driven valve operation will improve the pump’s efficiency by an estimated 60% compared to the wave-driven velocity alone. Tube Design The Ocean-Based pump design relies on a fabric tube (Figure 4) that serves as both the conduit of the water flow through the pump and the strength member connecting the

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Figure 4: The fabric tube serves as both the conduit of the water flow through the pump and the strength member connecting the bottom inlet valve and the near-surface outlet.

bottom inlet valve and the near-surface outlet. Using a fabric tube instead of a solid structure allows the pump system to be highly compact during shipping and simplifies deployment. The tube is assembled from two 3 m wide panels of silicon-coated woven polyester fabric that is double edge-stitched together to provide a durable tubular construction. In flat water (no waves or pumping), the net water pressure acting against the fabric wall is zero. Assuming a 2 m wave set (the pumping “downstroke”), the maximum pressure on the fabric wall is about 0.65 pounds per square inch. The fabric burst strength is 320 pounds per square inch (weft) and 342 pounds per square inch (warp) – giving a burst safety factor of nearly 500:1. Taking the static load of the bottom weight/valve at 2,500 pounds and tube strength of 82,000 pounds, the lengthwise safety factor is about 33:1.

and transporting the AUPs to be deployed, reasonably low freeboard, and an A-frame and crane to deploy the AUPs (Figure 5).

We estimate the fabric will elongate about 20 metres per 500-metre tube length over time while fully loaded by wave action. This lengthening is not significant, as many factors will combine to determine the exact depth of the inlet, and gradients in nutrient concentration are relatively small at the inlet depths targeted for specific deployments.

One of every 10 AUPs is fitted with a tethered BGC Argo-style autonomous profiling float. The tether line consists of 500 m from the bottom weight/valve to a tethered weight; and 1,500 m from that weight to a surface float and sea anchor. The 500 m section unspools as the AUP valve/bottom weight sinks. When the pump fully unspools its 500 m tube, it releases the tether weight off the deck, which then unspools the 1,500 m section. The autonomous float is attached to the top end of the 1,500 m section to slide down the tether line once in the water. The float and sea anchor maintains the tether line under tension and downstream from

Deployment Procedure Ocean-Based AUPs deploy from workboats or suitable commercial or fishing vessels. Vessel requirements are modest, consisting of sufficient free deck space for securing

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Once the AUPs are loaded and tied down on the deck, the workboat proceeds at a safe speed to the designated deployment location. The workboat orients into the waves to minimize rolling and slows to 1-2 knots at the location. The aft AUP tie-downs are released and the surface buoy, near-surface outlet, and rolled tube component is offloaded into the water, followed by the valve/bottom weight, which quickly sinks, unrolling the tube off the buoy. When the tube has fully unrolled, the connecting lines release the outlet inside the surface buoy, allowing the float sections to rotate about 90°, forming a raft shape. The pump is fully deployed and begins pumping on each wave as described above.

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the AUP. The profiling float then follows its programmed sequence of profiles which can be modified during the deployment to adjust for significant events and length of the deployment. The profiling float operates independently of the sensors on the pump itself and communicates using its antenna and communications system. We monitor the pump’s functioning with sensors and communications systems that report the status of the pump to shore via satellite communications. We equip the surface buoy with a GPS receiver, USCGapproved navigation light, wave height/ period accelerometer, water temperature sensors, satellite communications, and a solarrechargeable battery and controller module. Two temperature sensors are in the water – one inside the pump outlet measuring the temperature of the upwelled water and one outside the pump outlet measuring the ambient water temperature. The difference in temperature between the outlet and the ambient temperatures gives a continuous record of the operation of the pump. We further refine the temperature difference and wave state relationship with data from the wave height/period sensor (triaxial accelerometer), which records the response of the buoy to the waves to generate the volume upwelled with time. We calculate the nutrient flux to the surface layer with

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Figure 5: Deployment requirements are modest – sufficient free deck space, low freeboard, an A-frame, and crane.

the volume and temperature records by multiplying the flow volume at the outlet by the volume concentration of the nutrients at the inlet depth. Measurement, Reporting, and Verification The full scope of the functional mechanisms that will drive the transformation of upwelling nutrients into carbon dioxide sequestration into monetizable assets is beyond the scope of this essay. In order to reach the point of generating a cash flow from artificial upwelling, we will have to measure both the input terms as above and the nutrient flow through the ecosystem and the flux out of the surface layer. On a conceptual basis in an oligotrophic ocean area, we can presume that the nutrient flux to the surface ocean will not remain in the surface ocean and instead will relax towards the ambient concentration, which is essentially non-detectable. The question then becomes how to measure the carbon flux generated from the nutrient flux and consequential uptake by phytoplankton. The sensors on the pump itself will yield the input term for the nutrient flux. We will use other sensor systems to measure the response over time and space. Advances in autonomous systems have made this a tractable problem with multiple solution paths. We fully expect that continued improvements in ocean monitoring and modelling will increase the

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availability of the baseline measurements needed to demonstrate the additionality of artificial upwelling. Our current mechanism to measure the impact of the pumps is to deploy groups of pumps with an autonomous profiling float tethered to one of the pumps. Autonomous profiling floats include a sensor package that measures the bulk properties of the most significant oceanic carbon pools affected by the enhanced vertical exchange of water across the thermocline from the pumping technology. The temperature, salinity, and pressure data yield the density field that we use to generate a mixing model of the pumping effect on the vertical transport of the quasi-conservative heat and salt budgets, constraining the entire system. The rest of the sensors measure the carbon dynamic response to the vertical exchange. The chlorophyll fluorescence and backscattering sensors measure the particle load of particulate organic carbon (backscattering) and the viable phytoplankton (chlorophyll). The fluorescent dissolved organic matter (FDOM) fluorometer measures the concentration of the fluorescent fraction of the dissolved organic matter pool. The pH sensor measures one component of the pCO2 equilibrium. Through the autotrophic and heterotrophic activity, the backscattering and FDOM sensors monitor net carbon transfers between the dissolved and particulate pools. The dissolved oxygen sensor constrains the net community production of fixed carbon and the impact of gas exchange kinetics on pCO2. Finally, the nitrate concentration measurement monitors the effectiveness of the exchange of nutrient-rich deep water with nutrient-depleted surface water through the pumping process and, therefore, the net increase in autotrophic carbon production potential achieved by the pumps. The floats will be deployed in a near field/ far field manner, with one float within the pumping volume and the other deployed outside the pumping volume. The float mission profiles (park depth, profile interval, the rate, and ratio between deep and shallow profiles)

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will be adjusted during the initial trial period and subsequently during rollout to optimize modelling of the effect of the pumps. As the system scales, a network effect of increasing data from the floats relative to the governing scales across time and space will decrease the carbon flux measurement uncertainty between any pair of near and far-field floats, resulting in a measurement system that asymptotically approaches a fixed structural relationship between the pumping and the net sequestration of carbon. Ocean-Based will make all data collected from the profiling floats public so that third parties can incorporate this data into the datasets that will continually improve ocean monitoring and modelling. Maintenance Management AUPs have a design life of 80+ years if properly maintained. Much of the routine maintenance can be accomplished in-situ – removing biofouling from the buoy, swapout of on-buoy electronics, and solar/battery maintenance. Upkeep is achieved by snagging the buoy recovery line, lifting the buoy onto the workboat aft deck, and performing the necessary procedures. If the inspection determines fabric tube replacement is required, we winch in the recovery line to the bottom weight/valve, which lifts it to the surface, emptying water from the tube. The tube is respooled, and we fit a new tube to the top valve outlet and the valve/bottom weight, then deployment procedures are followed. AUPs requiring more extensive repair or refurbishment are brought back to shore and re-cycled or the components repaired and re-used. Conclusion Ocean-Based Climate Solutions is now building commercial-scale artificial upwelling pumps for ocean carbon dioxide removal. The vastness of the open ocean makes this technology a leading candidate to make

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progress in reducing atmospheric CO2 while the global economy continues to reduce its reliance on fossil fuels. u Philip Kithil is an inventor and entrepreneur who is the founder, chief executive officer, and president of Ocean-Based Climate Solutions, Inc. and its parent company, Atmocean, Inc. He has successfully founded six startups, including apparel manufacturing and retailing, economic consulting, advertising, association management and public relations, automotive safety, and ocean carbon removal industries. Mr. Kithil was issued thirteen U.S. and international patents, and has successfully licensed or sold his intellectual property to the automotive industry. He has his bachelor of arts in economics from Middlebury College (VT) and master of science in business administration in economics from the University of Denver. Salvador Garcia is a growth consultant working with OceanBased as chief revenue officer. Previously, he was a Peace Corps Volunteer, serving communities in Peru’s northern and southern Andes. Mr. Garcia had a successful career in real estate, growth consulting, and business mentorship in Lima before his daughter’s birth (and Greta Thunberg) inspired him to focus his experience on serving climate solutions. His experience as a sea scout in Northern California and knowledge in marine biology led him to focus on ocean carbon removal. He earned a bachelor of science in business administration at Cal Poly Humboldt (U.S.) and diplomas in digital marketing and marketing management at IAE Business School (Buenos Aires) and ESAN University (Lima), respectively. Dr. Ian Walsh is a consulting research scientist working with Ocean-Based as chief scientist. He was previously director of science at Sea-Bird Scientific and a research scientist at Oregon State and Texas A&M universities. Dr. Walsh’s research interests include the use of optical data on the particle field to understand basic biogeochemical processes and the influence of physical forcing on those processes, and carbon fluxes and fates including predictive modelling. He earned a bachelor of science in geology from Case Institute of Technology, a master of science in marine geology at Oregon State University, and a doctorate in oceanography at Texas A&M University.

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Is Sinking Carbon the Best Carbon Sink? Opportunities and Challenges of Using Sea Kelp to Seek Help with the Climate Crisis by Michael James Teasdale, Justin J. So, and Kiley Best


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Introduction Seaweed farming is a sustainable and environmentally conscious industry that is being investigated globally as one of the potential avenues to reducing greenhouse gases and mitigating climate change. There are several research areas of these nascent technologies deemed “blue carbon.” One of the concepts is sinking seaweeds to the seafloor to sequester carbon for approximately 1,000 years thereby acting as a long-term carbon sink and helping Canada obtains its net-zero carbon emissions. Other research involves adding a seaweed to livestock feed that causes the cattle to reduce the amount of methane they release. These research areas (and others) are being explored as the Canadian (and North American in general) farmed seaweed production continues its rapid expansion transitioning to larger scales of commercial production. Currently, the major market for North American farmed seaweed is human consumption but investors and seaweed startups are also considering and speculating on future opportunities that the blue carbon market may offer. This essay presents an overview of the feasibility of growing seaweed in Canada and Newfoundland and Labrador (N.L.) within the context of blue carbon and highlights some of the potential opportunities and challenges in terms of environmental conditions, logistics, regulations, and existing infrastructure. Blue Carbon Carbon Sinking (Sequestration) Seaweeds are high in polysaccharide content and naturally have a role in capturing carbon in marine vegetated habitats. It is estimated that global wild seaweed could potentially sequester approximately 173 Tg C year-1 as they are transported to deepsea environments or buried in coastal sediments by ocean currents (see “Further Reading” at end of essay). The idea being that carbon in the seaweed’s biomass will be locked up in the deepsea water cycle and will not re-enter the atmosphere for hundreds of years. In recent years, seaweed farming has garnered attention

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as a possible carbon sequestration strategy where farmed seaweed is transported and then sunk into the deep sea. Whether this potential strategy would be effective is still being scientifically debated. However, various companies are moving forward with feasibility and technical studies to evaluate this pathway for eventually providing “carbon offsetting credits.” Ocean 2050 is currently leading a study to quantify seaweed carbon sequestration at seaweed farms across the globe (including Cascadia Seaweed in B.C.) to provide further scientific support to commercialize this strategy (see “Further Reading”). Other companies are exploring advanced solutions such as unmanned mobile seaweed farms that can grow and release seaweeds. There are several challenges to overcome a transition from an academic pursuit to a sustainable, viable industry method to capture carbon. Sinking seaweed is unlikely to be a practical measure of mitigating climate change at global scales; however, it could be used in the more near-future to minimize carbon footprints at the regional level. The current price of carbon would not cover the current costs of growing seaweed in North America. Another important consideration is the logistics for exporting the seaweed to appropriate depths (>1,000 m). For many of the areas in eastern Canada, this would mean transporting farmed seaweed hundreds of kilometres offshore and off the continental shelf that would have a considerable carbon footprint. The environmental effects of depositing large quantities of organic matter to deepsea environments is also largely unknown. Farming (Livestock and Crop) Another potential carbon mitigation involving seaweed is reducing the carbon footprint of farming (livestock and crops). Methane is a main contributor to greenhouse gas emissions in livestock farming via livestock digestion. Changes in livestock diets have been shown to alter methane production and recent studies have focused on seaweed as livestock food supplement for reducing methane emissions while supporting livestock health

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and production. Feeding small quantities of the tropical red seaweed Asparagopsis species to sheep, dairy cows, and steers have resulted in reductions in methane production of up to 67-98% (see “Further Reading”). Laboratory studies have also shown potential for reduced methane emissions in cattle with some North Atlantic brown (winged kelp, sugar kelp, knotted wrack) and red (Irish moss) seaweeds, though at lower reduction rates (see “Further Reading”). Small commercial operations and field trials are ongoing for producing and using seaweed as supplemental feed for livestock. North Atlantic Organics (Seacow Pond, P.E.I.) currently produces a dried seaweed meal for livestock made from wild harvested brown and red seaweeds. However, widespread implementation as a food supplement remains in the early stages with logistical and regulatory challenges. Seaweeds contain various compounds and metals that can be detrimental at high levels in livestock and humans (i.e., iodine, bromoform). Reduction of methane at national and global scales would also require large quantities of seaweed that are not currently harvested or produced. Methane reduction studies in livestock have mainly tested wild harvested seaweeds for efficacy and found their levels of active methane-reducing compounds somewhat inconsistent; farmed seaweed and their concentrations are more unknown (see “Further Reading”). Ultimately, costs for supplementing livestock feed with seaweed has to be financially sustainable especially if there is a financial burden with no parallel improvements to their products or efficiency. Yet, livestock products with “reduced carbon” or “carbon-neutral” labelling may have added marketplace value. Seaweed farming could also contribute to reducing the carbon footprint of traditional crop farming via seaweed biochar. Biochars (made from organic materials like seaweeds under high heat and low oxygen conditions) are charcoallike materials that can trap carbon for decades or more and also act as a soil amendment. As

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climate change mitigation, research suggests that seaweed may need to be combined with plant material (e.g., forestry and agriculture wastes) to effectively create high carbon biochars (see “Further Reading”). Due to the energy required to generate high temperatures for production, this method of sequestering carbon may be better suited to regions such as N.L. that have access to renewable energies. General Ecosystem Services Seaweeds are not only a potential carbon sink, but also a nutrient sink reducing the effects of eutrophication, including non-point and point source discharges to the marine environment such as those from municipal sewage, farm/ ranch nutrient runoff, fish plants, aquaculture sites, and pulp and paper mills. Unlike terrestrial plants and seagrasses, seaweeds have no functional roots and instead take up nutrients (like nitrogen and phosphorus) directly from the water column. Those waste streams can have serious detrimental effects on the marine environment leading to anoxic dead zones, toxic algal blooms, and fish kills. Seaweeds could be used as a bio-mitigation standard to buffer wastewater eutrophication in coastal environments by creating a “seaweed biofilter” around point-source discharges. Those seaweeds could then be harvested and used as fertilizers or in the biochar process to cycle those excess nutrients back into the soil. For rural communities, this seaweed biofilter would be relatively cheap compared to traditional treatment systems and is a potentially effective solution for coastal water quality. Again, there are logistical and regulatory challenges to consider with this approach. Nutrient uptake rates would vary with the seaweed growth cycle. Many regulations have not kept pace with current knowledge and technologies. For example, sewer and water regulations (at both Canadian federal and provincial levels) regulate the water concentrations at the “end of pipe,” considered the last point of control before being released into the marine environment. But for these types of biofilters to work in an economically viable

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Figure 1: Pathway for development of current and future seaweed markets.

and efficient way, the water quality should be assessed on the ocean side of the seaweed biofilter. Other challenges include provincial regulations that limit aquaculture sites to a single farmed species. The use of integrated multi-trophic aquaculture (IMTA) where two or more organisms are farmed together has been suggested to mitigate and absorb the waste (in fish food and fish waste) generated from salmon farms. In N.L., with a growing salmon farming industry, this approach would not be possible under the current regulations. Opportunities and Challenges There are serious hurdles for N.L. and Eastern Canada that must be overcome both globally and regionally to partake in the blue carbon revolution. For any of these ideas to work, the province needs an existing, governmentand private-supported seaweed farming industry. Many of these solutions relate to the economy of scale so would need to have a viable, thriving smaller scale seaweed farming industry with proven, robust technologies to be able to scale these operations as they would need large systems in place to tackle such enormous global issues like climate change or more local yet ubiquitous issues like seawater

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quality in Canada’s coastal communities. For the blue carbon revolution to happen, we first need to ensure we have the necessary infrastructure and technologies in place to be able to grow and process seaweeds on a commercial scale (Figure 1). Seaweed farming for human consumption, however, is an off-the-shelf existing market that is ready now and projected to grow; a key to moving the blue environmental revolution forward. Food is currently the main market driving seaweed farming in North America on a commercial scale. Seaweeds are low in fat and high in carbohydrates, protein, minerals, and vitamins. As seaweed farming reduces the effects of agricultural runoff and eutrophication, it is less carbon intensive than traditional land-based crops (mostly carbon neutral). Because of the environmental services associated with this kind of culture, seaweed farming is also more socially accepted by local coastal communities and environmental defence groups than other kind of marine aquaculture (a key piece for government and stakeholder support). Further development of the seaweed food market (as well as secondary products such as cosmetics, phyco-colloid

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Figure 2: Typical phases of seaweed farming: Nursery Phase in 1-3: (1) Sourcing the reproductive tissue in the kelp. (2) Extracting the reproductive tissue (sorus). (3) Growing seaweed on spooled string in tank. Planting and Grow-out Phase in 4-6: (4) Transporting spool string to field. (5) Kelp growing on longline. (6) Young kelp on longline. Harvesting/Processing Phase in 7-9: (7) Pulling longline on board to harvest kelp. (8) Kelp harvest (9) Processing kelp in shredder. Photo credits: (2) (7) (8) Merinov | (1) (3) (5) (6) École des Peches et de L’Aquaculture du Quebec | (4) Kim, J.; Stekoll, M.; and Yarish, C. [2019]. Opportunities, challenges and future directions of open water seaweed aquaculture in the United States. Phycologia, 58(5), pp.446-461 | (9) Yarish, C.; Kim, J.K.; Lindell, S.; and Kite-Powell, H. [2017]. Developing an environmentally and economically sustainable sugar kelp aquaculture industry in southern New England: from seed to market.

extraction or other high value molecules extraction, biofuels, bioplastics) would enhance the financial feasibility of seaweed farming, thereby indirectly supporting some of these more nascent blue carbon technologies. Growing Seaweed in North America and Canada Seaweed farming produces 27 million metric tonnes annually and is the largest marine aquaculture market by weight (see “Further Reading”). Most of the global farmed seaweed production (>99%) is from Asia. Commercially scaled seaweed farming exists for the extractives (common gelling agents such as agar and carrageenan) as well as whole food products and other commercial applications (including livestock feed, supplements, polymers, chemicals, agrichemicals, cosmetics,

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nutraceuticals, functional foods, bio-oils, botanicals, and pigments). The typical process of seaweed farming consists of three steps: nursery phase (growing out in the lab in tanks), planting and grow-out phase (typically grown on lines similar to mussel aquaculture), and finally, harvesting/processing (Figure 2). Seaweed farming in North America is an emerging industry although at a much smaller scale than in Asia. The largest and most mature seaweed farming operations in the U.S. are in Maine and Alaska with a focus on kelps (sugar, ribbon) and an emphasis on developing human food domestically for the North American market. Canada also has some long-term operators on the West Coast (Canadian Kelp Resources Ltd., B.C., established in 1982) and East Coast (Acadia

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Seaplants Ltd. (N.B., N.S.), established in 1981). Acadia is one of the largest seaweed exporters in North America, although mostly focused on harvesting wild resources with some limited land-based seaweed aquaculture. Canada also has some new and emerging players such as Cascadia (B.C.; founded in 2019), planning one of the largest seaweed farming yields in North America. Its planned products include human food as well as experimental carbon sequestration. Eastern Canada has a history of wild seaweed harvesting and was previously the world’s largest producer of Irish Moss, primarily used for carrageenan extraction (see “Further Reading”). In Québec, Fermes marines du Québec is a private marine hatchery selling culture lines seeded with seaweed plantlets. These are cultivated on marine farms operated by Fermes Maricole Purmer, Ferme Maricole du Grand Large, or Maliseet Aboriginal Fisheries Management Association; the latter having one of the largest commercial seaweed farms (sugar kelp, winged kelp, and dulse) in Eastern Canada. Cultivated seaweed is ultimately processed into premium food products by Salaweg and Seabiosis. The development of this small industry is supported both by Merinov, a college technology transfer centre, and by Québec School of Fisheries and Aquaculture that have seaweed nurseries, an experimental grow-out field site, and a seaweed processing plant. Their focus is on domesticating new species, adapting and scaling the seaweed farming technologies for working in Atlantic and subarctic climates with ice, develop new products and processing methods, as well as training the seaweed farmers of the future.

further develop seaweed farming, which includes a three-year pilot program (ending in 2022) growing seaweed on existing mussel farms in Cape Breton, and with discussions to develop a seaweed nursery in Nova Scotia in cooperation with local research institutions. There is a long history of commercial wild harvesting Irish Moss for carrageenan extracts in P.E.I. North Atlantic Organics (Seacow Pond, P.E.I.) has a commercial operation for harvesting and processing seaweeds to supplement livestock feed. Although not as extensive as the other east coast Canadian provinces, N.L. does have some limited seaweed harvesting and seaweed research but no existing seaweed farming operations. The provincial government had an initiative after the 1992 cod moratorium for the commercialization of N.L.’s kelp and seaweed with some projects developed including a nutritional supplement. Currently, there is a small-scale industry of companies using harvested kelp for skin care products, servicing restaurants, and selling raw/dried seaweed for human consumption. Seaweed farming is on the rise in Canada but there are some challenges working in the difficult and harsh conditions of the North Atlantic in terms of space and time.

In New Brunswick, Thierry Chopin, longtime researcher and advocate for seaweed farming, is leading the development of IMTA by incorporating blue mussel and kelp into existing Atlantic salmon aquaculture at Magellan Aquafarms Inc. (Bay of Fundy, N.B.). The Aquaculture Association of Nova Scotia is working with mussel farmers to

Space in terms of: Latitude – Sea-ice interacting with seaweed farms is a potential issue in the winter and early spring. Seaweed farmers from Québec have adapted their culturing gear to change the depth of the lines in autumn and spring, similar to mussel farms avoiding damage from sea-ice. • Distance from Market – The most developed farms in North America (Alaska and Maine) have developed their products to be sold in the high-end restaurant industry and close to large urban areas and progressive markets (Maine sells to New York and Boston; Alaska targets the California market). A target for East Coast Canada could be Montreal and Toronto but

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there are some logistical challenges similar to those faced by the more established shellfish and finfish aquaculture industries (although kelp has a longer shelf life). Time in terms of: • Hold Time – Short-term processing is another challenge. The harvest of cultivated seaweed from late May to June (three to four weeks), means that the processing facilities should be able to process large seaweed volumes in a short time, given that shelf life of fresh kelp is no more than two to three days. • Development Time – Longer term, the lack of facilities capable of processing seaweed needs to be addressed in any development strategy for the kelp aquaculture sector. Traditional fish processing plants in coastal regions do not have equipment to process seaweed. Based on the recent developments in New England, it currently takes them approximately three years from initiating a pilot project to have an established commercial scale farm (see “Further Reading”). This means we need to be investing and developing now to compete with other growers in North America and tap into the blue carbon future. Newfoundland and Labrador The potential for seaweed farming and blue carbon in N.L. is considerable for the technologies discussed above (carbon sinking, farming, and general ecosystem services). For example, there are 6,000 dairy cows in N.L. emitting approximately 420 metric tonnes of methane annually. Supplementing their diet with a red seaweed (as discussed above) could equate to removing 10,000 metric tonnes of CO2-equivalence from the atmosphere (annual equivalent of removing 2,000 gasoline-powered cars from the road). With a carbon tax of $50 per tonne of CO2 in 2022 (projected to go to $170 per tonne by 2030) and industry and agencies working together to decrease production costs via increasing efficiencies and technologies, the financial and environmental rewards will continue to potential profitability.

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N.L. also has many of the qualities that make it well suited for seaweed farming including over 17,542 km of coastline with most of it relatively untouched and sparsely developed as well as native populations of commercial seaweed species (including sugar, winged, and horsetail kelp). Like other areas in North America developing seaweed operations (i.e., Alaska and Maine), there are numerous small rural fishing communities with limited economic opportunity where supplemental farming in the offseason could prop up the local economies. In addition, community members already have skillsets and equipment (i.e., working on the water using moorings and fishing gear) that could easily be adapted to seaweed farming. N.L. also has existing infrastructure and resources including marine research centres focused on marine technology and aquaculture developments (Marine Institute, Ocean Science Centre) as well as fish plants that are only seasonally active that could potentially be used for processing and nursery activities. Although the pieces are in place and the environment is conducive to develop seaweed farming in N.L., this will not happen on its own. A common theme of all the commercially viable operations in North America is investment by governments and industry in the local marine research to help with the methods of growing as well as commercialization of the products. N.L. invested in seaweed harvesting in the early 1990s (as well as currently heavily invested in fish farming) but a similar initiative needs to be launched now for seaweed farming so this province can take advantage of the current and expanding markets of seaweed for human consumption and the developing blue technologies. Now is the moment to invest in our coastal communities for the sake of their short-term economic viability as well as their long-term survival. Seaweed farming (as well as other carbon reduction initiatives) is required to mitigate the devastating effects that carbon emissions (i.e., the climate crisis) will continue to have on our coastal community’s future with an increased frequency and severity of storms and coastal flooding. We could all benefit

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from supporting the regional development of a sustainable, carbon-friendly natural resource like seaweed that complements other carbon reducing initiatives and enhances the ecosystem services the ocean naturally provides. u Acknowledgement The authors thank Éric Tamigneaux at Québec School of Fisheries and Aquaculture (Merinov) for reviewing this essay and providing helpful comments and suggestions.

Blue Carbon-Carbon Sinking (Sequestration) Duarte, C.M.; Bruhn, A; and Krause-Jensen, D. [2021]. A seaweed aquaculture imperative to meet global sustainability targets. Nature Sustainability:1-9. Krause-Jensen, D. and Duarte, C.M. [2016]. Substantial role of macroalgae in marine carbon sequestration. Nature Geoscience 9:737–742. Oceans 2050 – https://www.oceans2050.com/ Blue Carbon-Farming (Livestock and Crop) Abbott, D.W.; Aasen, I.M.; Beauchemin, K.A.; Grondahl, F.; Gruninger, R.; Hayes, M.; Huws, S.; Kenny, D.A.; Krizsan, S.J.; Kirwan, S.F.; Lind, V.; Meyer, U.; Ramin, M.; Theodoridou, K.; von Soosten, D.; Walsh, P.J.; Waters, S.; and Xing, X. [2020]. Seaweed and seaweed bioactives for mitigation of enteric methane: challenges and opportunities. Animals 10:2432. Roberts, D.A.; Paul, N.A.; Dworjanyn, S.A.; Bird, M.I.; and de Nys, R. [2015]. Biochar from commercially cultivated seaweed for soil amelioration. Scientific Reports 5:9665. Roque, B.M.; Salwen, J.K.; Kinley, R.; and Kebreab, E. [2019]. Inclusion of Asparagopsis armata in lactating dairy cows’ diet reduces enteric methane emission by over 50 percent. Journal of Cleaner Production 234:132-138. Roque, B.M.; Venegas, M.; Kinley, R.D.; de Nys, R.; Duarte, T.L.; Yang, X.; and Kebreab, E. [2021]. Red seaweed (Asparagopsis taxiformis) supplementation reduces enteric methane by over 80 percent in beef steers. PLOS ONE 16:e0247820. Vijn, S.; Compart, D.P.; Dutta, N.; Foukis, A.; Hess, M.; Hristov, A.N.; Kalscheur, K.F.; Kebreab, E.; Nuzhdin, S.V.; Price, N.N.; Sun, Y.; Tricarico, J.M.; Turzillo, A.; Weisbjerg, M.R.; Yarish, C.; and Kurt, T.D. [2020]. Key considerations for the use of seaweed to reduce enteric methane emissions from cattle. Frontiers in Veterinary Science 7:1135.

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Growing Seaweed Bradford, J.; Filgueira, R.; and Bailey, M. [2020]. Exploring community-based marine aquaculture as a coastal resource management opportunity in Nova Scotia, Canada. FACETS 5, no. 1: 26-48. Chopin, T. and Couturier, C. [2017]. Aquaculture Canada and sea farmers. Seaweed Symposium, Québec City, Canada. Bulletin of the Aquaculture Association of Canada. 1-50. Chopin, T. and Ugarte, R. [1998]. The seaweed resources of eastern Canada. Seaweed Resources of the World. Japan International Cooperation Agency, Yokosuka, Japan, pp. 289-291. Redmond, S.; Green, L.; Yarish, C.; Kim, J.K.; and Neefus, C. [2014]. New England Seaweed Culture Handbook Seaweed Cultivation. Paper 1. Connecticut Sea Grant CTSG-14-01, University of Connecticut, Groton, Connecticut, U.S. pp. 1-92. Yarish, C.; Kim, J.K.; Redmond, S.; Neefus, C.D.; and Green, L. [2014]. Part 1-6. Seaweed Culture in New England. Connecticut Sea Grant CTSG-14-01, University of Connecticut, Groton, Connecticut, U.S. pp. 1-92. Michael James Teasdale, M.Sc., is a senior scientist with Wood since 2007 who specializes in marine habitat monitoring and environmental assessment with a more recent focus on greenhouse gas accounting. Prior to coming to Wood, Mr. Teasdale was a student and technician at three marine wet labs on the Pacific and Atlantic Coasts as well as the Gulf of Mexico. He is also currently developing a seaweed farm in Newfoundland. Justin J. So, M.Sc., is trained in marine biology and science communications and has been working as a biologist with Wood since 2011. He has worked mainly in the fields of habitat monitoring, environmental effects monitoring, and environmental assessment. Mr. So has been involved in planning, implementation, and analysis for numerous coastal and offshore underwater visual surveys. Kiley Best, M.Sc., is a fisheries biologist with the Centre for Fisheries Ecosystems Research (CFER), Marine Institute. She works on fisheries ecosystem field science and monitoring in the coastal and offshore and specializes in aquatic invasive species and ocean literacy. She is the resident aquatic invasive species expert at CFER and is the board co-chair of the Canadian Network for Ocean Education and board chair of the Petty Harbour Mini Aquarium.

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Offshore Wind Energy, Direct Air Capture, and Carbon Sequestration in Basalt Solutions for Atmospheric CO2 Reduction by David Goldberg and Kate Moran


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Introduction The 2021 United Nations climate conference suggests that reaching the reduction limits on CO2 emissions set by the Paris Agreement in 2015 are simply slipping away and will require immediate changes in our global energy systems. The consequences of inaction will potentially have catastrophic impacts on the availability of food and water, human shelter and coastlines, and energy availability. The replacement of fossil fuel-based energy with renewables is an essential first step, but to account for our prior emissions, meeting these targets will also require carbon dioxide to be removed directly from the atmosphere at neverbefore-seen levels. New “negative emission technologies,” or NETs as they are often called, need to become much more commonplace. At the present, these developing technologies involve both energy-consuming and areaintensive processes; implementing them at large scale will require improved efficiencies as well as regulatory guidance and broad incentives. In our research project Solid Carbon, teams study solutions that combine renewable energy resources with engineered direct air capture (DAC) systems in order to scrub CO2 from the atmosphere and store it in offshore environments. Since CO2 has the same concentration everywhere, DAC systems may be located anywhere on Earth. And by placing them in certain offshore settings, captured CO2 may be permanently sequestered immediately below the seafloor within basalt reservoirs, where it converts chemically and securely into solid carbonates. Renewables and DAC Deploying these technologies offshore offers several advantages. In particular, many offshore regions around the globe have abundant and consistent wind resources, providing as much as 90% of the total global wind potential. To take advantage of this, offshore wind farms are expanding in many countries with new large turbines and floating towers that can be deployed in deeper and deeper waters. This investment in offshore

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wind can be combined with DAC and engineered jointly to address global climate targets, thus leveraging maintenance costs and limiting the need for onshore pipelines. Furthermore, offshore deployments of these technologies can reduce the tangle of issues surrounding onshore property rights and longterm risks and liabilities near populated areas. Figure 1 illustrates various notions of combined wind and DAC systems in near-shore/ offshore settings and at varying water depths. Various prototype DAC systems are being tested today and all use heat and electrical energy to capture CO2. Different designs have distinct energy requirements for scrubbing CO2 from gas streams. As efficiencies are anticipated to improve at commercial scales, researchers believe that DAC will become a valuable, modular, and scalable tool to reduce atmospheric CO2 over the coming years. We also indicate that alternative renewable fuel sources, such as green hydrogen or ammonia, may be used with DAC in addition to windgenerated electricity. The area requirements for these technologies may require several locations to be built out, but ultimately, the availability of renewable energy will determine the total CO2 capture capacity. For any combined capture/renewable energy scenario, the collected CO2 would then be transported and permanently stored below the seafloor. CO2 Storage in Offshore Basalt To mitigate global climate change, vast amounts of CO2 must be collected and stored away permanently. Basalt formations offer a unique reservoir for carbon dioxide sequestration. Large volumes of basalt lava flows can be found around the globe, typically formed geologically by sequential deposits that “flood” large areas. Pore spaces exist in between these flows, forming highpermeability layers that can serve as a storage reservoir and physically and chemically trap injected CO2. The reaction of basalt with water and CO2 produces stable, non-toxic carbonate minerals, ultimately trapping carbon as a solid and reducing the risk of post-injection leakage.

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Figure 1: The various notions of combined wind and direct air capture systems in near-shore/offshore settings and at varying water depths are shown.

Two recent field projects have demonstrated that CO2 injected into underground basalt reservoirs rapidly converts into carbonates – one in Iceland and one in the U.S. – promising a safe and durable storage solution that can be scaled up. To do so, the tools and technologies used today for oil and gas exploration and reservoir monitoring can be effectively applied to the injection and storage of CO2 into basalt reservoirs both on land and below the seafloor. We are focusing our investigations on an offshore basalt reservoir in the Cascadia Basin, the abyssal plain region off the west coast of Washington State and British

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Columbia, as a potential location for highvolume CO2 storage. This area – one of the best-studied oceanographic sites in the world – has counterparts in other parts of the ocean where the approach could be replicated. In the Cascadia Basin, basalt layers below the seafloor are known to be permeable and injectable, covered by a widespread sediment blanket more than 200-m thick that provides a protective barrier to the overlying ocean. This is important for long-term storage because injected CO2 will remain physically trapped in the subseafloor, allowing time for geochemical processes to occur and preventing the return of CO2 to the ocean and atmosphere.

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Figure 2: The Cascadia Basin is an abyssal plain region off the west coast of Washington State and British Columbia. In the Basin, basalt layers below the seafloor are known to be permeable and injectable, covered by a widespread sediment blanket more than 200-m thick that provides a protective barrier to the overlying ocean. The site offers unique capabilities to monitor and assure storage in real time. The existing subsea cabled NEPTUNE Observatory array, operated by Ocean Networks Canada, currently collects ocean and sea-bottom data that is transmitted to shore for web-enabled surveys and research needs.

For any potential storage reservoir, the long-term distribution and fate of CO2 in the subsurface must be confirmed. Regulations, permitting, and documentation of the CO2 storage reservoir requires careful modelling and monitoring. This assures the environmental safety and health at the site and also provides the tools needed for assessment and valuation of carbon storage credits. The Cascadia Basin site offers unique capabilities to monitor and assure storage in real time. The existing subsea cabled NEPTUNE Observatory array, operated by Ocean Networks Canada, currently collects ocean and sea-bottom data that is transmitted to shore for web-enabled surveys and research needs. Figure 2 shows the range of this wide network across the margin and abyssal plain, and the location of the Cascadia Basin Node to which remote reservoir and CO2 monitoring sensors would be connected. Demonstrating and monitoring a pilot injection experiment at this site is a readily achievable next step toward upscaling CO2 storage solutions in offshore basalt.

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Trade-offs and Risks The offshore environment offers rich renewable energy resources, but of course, the remoteness of most sites will require the buildout of new infrastructure for energy, CO2 capture, injection, and storage. Economic trade-offs will always be critical to consider when faced with finding an acceptable balance between viable reservoirs for large volumes of CO2, renewable energy needs for capture, infrastructure requirements, and the mitigation of risks associated with project execution. Construction costs in the marine environment are higher than on land, but combining investments for integrated solutions can help to diversify the risks. Joint workforces and staging areas may also substantially reduce maintenance and operational expenses. And, as for any climate mitigation approach, a valuation price on carbon will generate economic incentives. Offshore locations for CO2 storage, in particular, will ease ongoing public assurance

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and project safety needs. Importantly, ocean sites allow for regular and less disruptive site monitoring, and their distance from populated areas reduces concerns associated with limited land availability and the proximity to private property. The risks associated with conventional land-based sources of drinking water, permitting, and rights-ofway are reduced and common concerns about leak detection, seismic occurrences, and operational issues are lowered. These advantages may well offset the additional cost burden of offshore operations. In the offshore, and for all storage projects, environmental safety and the careful preservation of the natural environment is a constant priority for success. The ocean is rich in natural life, of course, and the environmental impacts and regulatory policy governing offshore storage sites are being developed and expanded in many countries. The critical information for effective policy relies on the ability to accurately monitor a storage reservoir over the long term. Using the NEPTUNE cabled observatory at Cascadia, a vast range of monitoring tools and sensors could be deployed and connected to its real-time network, including CO2 sampling devices, borehole geophysical and geochemical tools, subsea autonomous vehicles, earthquake monitoring stations, and seafloor cameras. All of these will help to establish and maintain a safe environment for a successful pilot injection experiment at Cascadia, as well as to develop and demonstrate the essential tools for long-term basalt storage at other locations in the future. In summary, combining renewable energy, direct air capture, and carbon storage in offshore basalt reservoirs can produce NETs and mitigate the build-up of carbon dioxide in the atmosphere. Deploying integrated renewable energy-capturestorage solutions offer several advantages by co-locating them offshore, including leveraging infrastructure investments, minimizing onshore pipelines, and reducing environmental and human impacts. In the offshore areas near the

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Cascadia abyssal plain, the basalt formations have been well studied and have estimated total storage capacities in excess of 100 Gt of CO2. Utilizing wind and other renewable energy sources, this location can provide a large-scale and secure reservoir, an existing environmental monitoring network, and a benchmark demonstration site for a combination of technologies and tools to combat climate change. Demonstration of a pilot experiment at Cascadia, with physical and measurable proof that these technologies will work at scale, will allow for similar approaches to be deployed in a variety of marine settings around the globe. u Acknowledgment The authors acknowledge support for the Solid Carbon partnership from the Pacific Institute for Climate Solutions (PICS). Dr. David Goldberg is a Lamont Research Professor at the LamontDoherty Earth Observatory, Columbia University. His interests focus on the integration of different technologies and cross-disciplinary approaches to develop achievable climate solutions. Dr. Goldberg received his undergraduate and MS degrees in earth and planetary sciences from the Massachusetts Institute of Technology, and his doctorate in geophysics and an MBA from Columbia University. He conducted post-doctoral studies at the Institute Français du Petrole in Paris and has been at Lamont-Doherty since 1985. He has acted as principal investigator on many collaborative research projects, including recent multi-national carbon management studies, and been directly involved with various scientific drilling programs. He also currently serves as the deputy director of Lamont-Doherty Earth Observatory, a core faculty member for the Lenfest Center for Sustainable Energy, and a lecturer in the Sustainability Science Program at Columbia University. Dr. Goldberg continues to advise graduate and post-graduate research in carbon management, scientific drilling, and related topics. Dr. Kathryn (Kate) Moran joined the University of Victoria in September 2011 as a professor in the Faculty of Sciences and as director of NEPTUNE Canada. In 2012, she was promoted to the position of president and CEO, Ocean Networks Canada. Since then, she has led and grown the

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organization following the vision of enhancing life on Earth by providing knowledge and leadership that deliver solutions to science, society, and industry. Her previous appointment was professor at the University of Rhode Island with a joint appointment in the Graduate School of Oceanography and the Department of Ocean Engineering. She also served as the Graduate School of Oceanography’s associate dean, research and administration. From 2009 to 2011, Dr. Moran was seconded to the White House Office of Science and Technology Policy where she served as an assistant director and focused on Arctic, polar, ocean, the Deepwater Horizon oil spill, and climate policy issues. Dr. Moran co-led the Integrated Ocean Drilling Program’s Arctic Coring Expedition, which was the first deepwater drilling operation in the Arctic Ocean. This expedition successfully recovered the first paleoclimate record from the Arctic Ocean. She also led one of the first offshore expeditions to investigate the seafloor following the devastating 2004 Indian Ocean earthquake and tsunami. Previously, Dr. Moran was a scientist at Canada’s Bedford Institute of Oceanography where one of her major research focus areas was the Arctic Ocean. She also served as the director of the international Ocean Drilling Program in Washington, D.C.; managed missionspecific drilling platform operations in the North Atlantic and Arctic; designed and developed oceanographic tools; participated in more than 40 offshore expeditions; and has served as chair and member of national and international science and engineering advisory committees and panels. Professor Moran is active in public outreach (through public lectures, national panel discussions, and teacher training) on topics related to the Arctic, ocean drilling, and climate change. She has testified on climate change to the U.S. Senate Committee on Environment and Public Works. At the University of Rhode Island, she spearheaded a research initiative on offshore renewable energy. Watch Dr. Moran’s TEDx Talk on “connecting our planets to the internet.”

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Experiments of Vortex-Induced Vibration for a Smooth Circular Cylinder at Mass Ratios 3<M*<4 Sukru Cem Colakoglu, Erinc Dobrucali, Abdi Kukner, Aytekin Duranay, Omer Kemal Kinaci Flood Damage Assessment Using Satellite Observations Within the Google Earth Engine Cloud Platform Mehdi Sharifipour, Meisam Amani, Armin Moghimi Simulation, Optimization, and Economic Assessment of Pelamis Wave Energy Converter Hana Ghaneei and Mohammadreza Mahmoudi Heavy Metals in Snow Crab (Chionoecetes opilio) Bio-Products Heather Burke and Francesca Kerton

Good Vibrations Researchers consider the “useful” side of vortexinduced vibrations. Who should read this paper?

Sukru Cem Colakoglu

This paper is intended for academicians and researchers in the field of ocean engineering and professionals in the offshore industry. The content of this paper is formed from the initial work carried out to build an experimental setup from start. The paper is considered to be a very good fit (especially) for young academics trying to build a lab to investigate vortex-induced vibrations (VIV) experimentally. The authors examined a rare mass ratio range in their study for benchmarking with the hope of attracting professionals as well as scientists.

Why is it important?

Setting up a VIV lab consists of lengthy stages such as conducting free decay tests, finding spring stiffness, measuring the amplitude and frequency response, etc. All the preliminary work carried out to build the VIV lab at Istanbul Technical University is given in detail in this study. The authors have covered a high mass ratio in a high Reynolds number regime and discussed their experimental findings with other results in the literature. The high discrepancies with some other experiments in other studies are considered to be due to the aspect ratio of the cylinder and/or test section width.

Dr. Erinc Dobrucali

Dr. Abdi Kukner

Renewable energy is a necessity for sustainable development. Conventional forms of energy are triggering climate change and recently the United Nations announced 17 sustainable development goals (SDG) for a sustainable world. Three of them are closely linked with the ocean community: SDG7, SDG13, and SDG14. Recent studies show that vortex-induced vibrations have tremendous potential as a form of renewable energy. In close relationship with SDG7 (Affordable and Clean Energy), marine renewable energy can slow down climate change (SDG13: Climate Action) and sustain the life below water (SDG14: Life Below Water). Currently, there are several applications of VIV in different engineering fields. It is used in energy conversion devices and in flow meters to the authors’ knowledge. One of the authors holds a patent on “self-excited flow-induced pump,” which utilizes VIV to pump water for free from running currents. The technology is constantly evolving and the authors expect that more applications are to follow in the next decades.

About the authors

Sukru Cem Colakoglu holds an associate degree in naval architecture and a bachelor’s degree in mechanical engineering. He has worked in the marine industry in the fields of structural analysis, mechanical design, and naval architecture for many years. He received his master’s degree in offshore engineering from Istanbul Technical University in 2019 and currently works as a mechanical diagnostics engineer at Baker Hughes. Dr. Erinc Dobrucali received his M.Sc. and PhD degrees from the Department of Naval Architecture and Marine Engineering, Istanbul Technical University. He retired from the Turkish Navy in 2021. He currently works at Bursa Technical University as an associate professor. His research interests include ocean renewable energy, computational fluid dynamics, marine engines, and exhaust smoke dispersion on naval ships.

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Dr. Abdi Kukner received his bachelor and M.Sc. degrees from the Department of Naval Architecture and Marine Engineering at Istanbul Technical University. He also received a M.Sc. degree in naval architecture at the University of California, Berkeley, U.S., and received a PhD in ocean engineering at Stevens Institute of Technology, Hoboken, New Jersey, U.S. He retired from Istanbul Technical University in 2019. Currently, he works as a professor at the Department of Mechanical Engineering at Beykent University, Istanbul, Turkey. He is also head of the department. His related fields of study are renewable energy systems, computational fluid mechanics, seakeeping, small and sailing boat design, and electrical cars. Aytekin Duranay is a research assistant at Istanbul Technical University in the Department of Shipbuilding and Ocean Engineering since 2013. After obtaining his bachelor degree from Yildiz Technical University, he focused on fluid-structure interaction (FSI) problems and forms of renewable energy. He has expertise on experimental studies related to FSI problems, data acquisition, and computational fluid dynamics modelling. He currently lives in Istanbul, Turkey. Dr. Omer Kemal Kinaci holds an ocean engineering doctoral degree. After working eight years at Yildiz Technical University, he started working as an associate professor at Istanbul Technical University (ITU) in 2017. He has worked on flowinduced motions as a post-doctoral researcher at the University of Michigan in 20142015. He leads national projects in the naval defence industry and serves as a member in the Applied Vehicle Technology Panel of NATO. Dr. Kinaci has served as a board member at the autonomous university of ITU Northern Cyprus Campus during 2019-2020. He was the coordinator of scientific research at ITU between 2017-2020. His research interests include ship motions and control, underwater acoustics, and vortex-induced vibrations.

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Aytekin Duranay

Dr. Omer Kemal Kinaci

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EXPERIMENTS OF VORTEX-INDUCED VIBRATION FOR A SMOOTH CIRCULAR CYLINDER AT MASS RATIOS 3<M*<4 Sukru Cem Colakoglu1,2, Erinc Dobrucali3, Abdi Kukner2, Aytekin Duranay2,4, Omer Kemal Kinaci2 1 Gemak TGE Shipyard R&D Center, Istanbul, Turkey 2 Faculty of Naval Architecture and Ocean Engineering, Istanbul Technical University, Istanbul, Turkey; kinacio@itu.edu.tr 3 Maritime Faculty, Bursa Technical University, Bursa, Turkey 4 Faculty of Naval Architecture and Ocean Engineering, Izmir Katip Celebi University, Izmir, Turkey ABSTRACT Studies involving vortex-induced vibrations (VIV) are generally conducted in water when the mass ratio is low and in air when it is high. VIV in water gained much attention in the last decade due to the possibility of harnessing hydrokinetic energy and most of the literature on this subject is limited to mass ratios of m* < 2. However, it is known that increasing mass ratio also increases energy harnessing efficiency. In this study, we consider smooth circular cylinders in VIV covering a mass ratio range of 3 < m* < 4 at TrSL3 flow regime. Although studies focusing on this range are not so many, there are considerable discrepancies in results in terms of the amplitude response of the cylinder. Experiments are conducted to allow cross-flow motions while restricting inline vibrations. Our results are discussed in comparison with other experiments published in the literature. We have not observed a correlation between the mass-damping parameter and the maximum amplitudes as previous studies suggest. This is considered to be due to the unreported features of the experimental setups: cylinder positioning, test section width, and the type of test basin are considered to be affecting the cylinder’s VIV response. Our experiments show that increasing mass ratio narrows down the range of synchronization while the maximum achieved amplitude sails around A* ≈ 0.9.

KEYWORDS Mass ratio; 1DOF VIV; TrSL3 flow regime; Vortex shedding; Fluid-structure interaction

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INTRODUCTION As engineers from different disciplines aimed for deeper drilling, longer bridges, higher towers, etc., flow-induced motions of these bluff bodies have become an important design criterion. When vortex-shedding frequency locks in with the natural frequency of the body, catastrophic things might happen. Vortex-induced vibrations (VIV), a branch of flow-induced motions, might cause structural fatigue failure [Gao et al., 2011; Xu et al., 2019]; therefore, it is “something” that should be avoided. However, every cloud has a silver lining: this phenomenon can also be “useful” if used in a correct way. Today, many researchers around the world try to make use of vortex-induced vibrations. Many try to harness energy out of it [Bernitsas et al., 2008; Vinod and Banerjee, 2014; Zhu and Gao, 2017; Wang et al., 2019; Sun and Seok, 2020]. Others exploit the existing knowledge on vortex-induced vibrations and develop products such as flow sensors [Lakka, 2011] or self-powered flow-induced pumps [Kinaci and Gokce, 2015]. As hydrokinetic energy harnessing became popular in the last decade, attention has been drawn to maximize the energy output from water flow [Yang et al., 2019]. Due to the expense of working in the marine environment, most of the VIV literature focus on “nearly-buoyant” bodies to make use of hydrostatic lift to decrease maintenance costs. These studies lie in the range of 1 < m* < 2. On the other hand, it was stated in Sun et al. [2016] and experimentally proven that “increasing the mass ratio has a strong positive effect on hydrokinetic power.” They have not gone beyond m* > 1.7 in their

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study; but noted 19% increase in peak harness efficiency when they increased the mass ratio from 1.007 to 1.685. They also noted that the mass ratio has an upper bound to it as heavier systems increase the initial cost and maintenance considerably. Studies based on high mass ratios are generally conducted in air [Belloli et al., 2012] and they generally have m* ≫ 50. VIV studies having high mass ratios m* > 2 in water can be found in the literature but VIV is a very broad field with lots of parameters affecting the results. Although there are a vast number of papers published recently about vortex-induced vibrations, they generally show variations in:

• •

the geometry of the object. Circular cylinder is dominant in these studies; some others focus on triangular [Tamimi et al., 2019] and rectangular [Mannini et al., 2014] cylinders as well. the fluid. Despite a few studies that consider both [Ramberg and Griffin, 1981], some are in water and others are in air only. the Reynolds number (range). Many fundamental studies focus on low Reynolds numbers such as Re<1000 [Leontini et al., 2006; Zhao et al., 2014; Wu and Wang, 2018]; others are generally in TrSL2 [Pigazzini et al., 2018] and TrSL3 flow regimes [Raghavan and Bernitsas, 2011]. the cylinder type. The majority of VIV studies in the literature are for smooth cylinders while there are also papers based on cylinders with additional roughness [Vinod and Banerjee, 2014; Chang et al., 2011; Park et al., 2012; Gao et al., 2018]. degree-of-freedom (DOF) of the cylinder.

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Table 1: Vortex-induced vibrations (VIV) parameters in different studies. Amplitude responses are given in Figure 1.

In-line motions are generally negligible as compared to cross-flow vibrations; however, 2-DOF VIV studies [Kang et al., 2019; Martins and Avila, 2019] can be found as much as 1-DOF VIV. Despite these variations, some significant papers are available that review the literature on VIV, such as Sarpkaya [2004], Williamson and Govardhan [2004], and Bernitsas [2016]. Our research team was particularly interested in vortex-induced vibrations of smooth circular cylinders at TrSL3 flow regime [Zdravkovich, 1997] in water having mass ratios of m* ≈ 3-4. When the topic is limited with such constraints, it is not easy to find many studies as we could only come up with four papers: Triantafyllou et al. [2003], Stappenbelt and O’Neill [2007], Stappenbelt et al. [2007], and Modir et al. [2016]. The parameters of their results are given in Table 1. Amplitude responses of cylinders are given in Figure 1.

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As Figure 1 reveals, results show a high deviation; although VIV parameters do not show such discrepancy. Maximum achieved amplitude in all these studies are in a broad range between 0.5 < A* < 1.1 while the mass ratio range is narrow (3 ≤ m* ≤ 3.68) and damping ratios are rather low (0.006 ≤ ζ ≤ 0.059). Additionally, we cannot find a correlation between results, as the lowest amplitudes are not achieved in highest mass ratio that we would normally expect [Bahmani and Akbari, 2010; Zhao et al., 2019; Pigazzini et al., 2019]. It was interesting to see that amplitude response of m* = 3.68 was greater than m* = 3.01; although the experiments were carried out by the same group at similar mass-damping ratios. Considering the high nonlinearity of the problem, possible reasons of this difference might be plenty. These dramatic differences in results urged us to

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Figure 1: Amplitude responses of cylinders at different mass ratios published in the literature. Detailed vortex-induced vibrations (VIV) parameters are given in Table 1.

conduct our own experiments which served as the motivation of this study.

in “Discussion.” The paper is finalized with conclusions of the study in “Conclusion.”

The paper continues with the explanation of the experimental setup in the next section. All details including flow velocity, spring stiffness and damping ratio measurements, mechanical design of the VIV apparatus, and the Arduino system to digitize cylinder motion are explained in “Experimental Setup.” “Details of the Experiments” presents the physical parameters of the experiments and Reynolds number and reduced velocity ranges. In “Mathematical Model,” we present the linear mathematical model to extract lift coefficient acting on the cylinder and the phase difference between the cylinder oscillation and the vortex shedding. They help understand the physical insight of the experiments. Results of the experiments are given in “Results” and we discuss these results with respect to other experimental results in the literature


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VIV experiments have been carried out in the circulation channel of Istanbul Technical University (ITU) Ata Nutku Ship Model Testing Laboratory located at the Ayazaga Campus of ITU Istanbul. The channel is two stories high, having a propeller at the lower part (first floor) while the test section is at the higher part (second floor). The test section is provided with glass ports that allow visual observation of the flow field. The channel is 1.5 m wide and 0.64 m deep (depth can be increased up to 80 cm if needed). The channel streams a uniform steady current towards the stationary VIV apparatus, without any necessity of a towing carriage. A view of the channel is given in Figure 2. A digital

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Figure 2: A view of the Circulation Channel in the Ata Nutku Ship Model Testing Laboratory.

electric driver is used to scale the velocity of current over a range of 0 < U < 1.56m/s. The channel was first built in 1974 and renovated in February 2019. Flow Velocity Measurements The circulation channel in the Ata Nutku Lab is rather old; therefore, some parts of the channel were replenished before conducting VIV experiments. A modern type electric motor and a touchscreen panel were installed prior to calibration studies. Teledyne brand and Isco Signature type digital flow meter (Teledyne Isco’s TIENet 350 Area Velocity Sensor) was used to find the flow rate corresponding to the propeller revolution rate (rpm). A photograph taken during the measurements is given in Figure 3. The flow meter can be seen inside the water. Flow velocities were measured before the VIV system was implemented to make sure

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the flow was undisturbed. The ultrasonic sensor was located in the centre of the fully developed section of the circulation channel and in the geometric centre of the area below the water level, so that the flow was not affected from boundaries. The sensor transmits ultrasonic signals into the flow stream and after these signals return back to the sensor, flow velocity is calculated by making use of the Doppler effect. The motor rotates the propeller at a maximum of 1,000 rpm. Flow velocities were measured increasing the propeller rotation rate by 50 rpm. Each measurement was recorded for a minimum of three minutes until it was made sure that flow velocity was stable. Figure 4 shows flow velocity measurements at each propeller rotation rate. It is evident from this figure that there is a linear relationship between propeller rotation and flow velocity. A linear curve was fitted which resulted in an equation of the form:

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Figure 3: Flow velocity measurements in the channel. The flow meter used during measurements is under the water.

Figure 4: Flow velocity in the channel with respect to propeller revolution.

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Figure 5: Drag coefficient versus Reynolds number for a smooth circular cylinder. The graph is taken from Sumer and Fredsoe [2006] and adapted for this study.


This equation can be used to calculate the flow velocity for any propeller rotation rate. Mechanical Design of the VIV System The experimental VIV system is expected to allow vertical motions only, while strictly limiting in-line motions and rotations. Besides, the main frame should have a strong main frame that can resist the forces created by the flow on the cylinder. We know that the maximum in-line force acting on the cylinder can be calculated by the Morison equation which is given as: (2) Here, ρ is the fluid density; D and L are the diameter and length of the cylinder, respectively; Umax is the maximum flow

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velocity; and CD is the drag coefficient. The cylinder has a diameter of D = 0.08m and a length of L = 1.32m. The maximum flow velocity is Umax = 1.56m/s. Taking into consideration the geometry of the cylinder and physical conditions of the channel, the maximum Reynolds number to be achieved becomes Re ≈ 150,000. At these Reynolds numbers, the flow is in subcritical regime [Sumer and Fredsoe, 2006] for stationary cylinders. Although our case has one degree-offreedom (1-DOF), we can have a notion about the flow loading on the cylinder by looking at the drag coefficient graph for a smooth circular cylinder. It is given in Figure 5. Using Equation (2), maximum in-line force acting on the cylinder was found to be Fmax < 150N. Structural design of this VIV system was made accordingly, consisting of the following parts:

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Figure 6: The vortex-induced vibrations (VIV) apparatus consists of two frames. A main frame (left) and a sliding frame (right).

Figure 7: The whole vortex-induced vibrations (VIV) setup. The main frame and the sliding frame are connected to each other. CAD view (left). A photograph during experiments (right). Table 2: Parts of the sliding frame shown in Figure 5.

A main frame that is mainly responsible for strength and rigidity. It consists of two pillars that are used to install the system on channel walls and a beam that connects the pillars. A slider frame that is mounted on the stationary main frame. It holds the cylinder and moves with it, while constraining other possible motions.

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The two frames can be seen in Figure 6. Parts of the slider frame as shown with numbers in this figure are given in Table 2. The whole VIV system is given in Figure 7. The figure on the left is the CAD view of the system while the figure on the right is a photograph taken before the experiments. There, it is possible to see the additional masses that were installed on the aluminum angle bar for balancing the

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Table 3: Length of the spring under variable loads.

slider frame, so that cylinder motion is smooth throughout the oscillation. Calculation of Spring Stiffness Stiffness of a spring can be calculated using its properties in spring equations. However, in this study, spring stiffness was obtained by measuring the extension of the spring under variable loads. The spring was made of steel. It was tested with various masses in the air. The spring was fixed at one end and different masses were placed at the other end. Final lengths of the spring under variable tensions are given in Table 3.

graphed in Figure 8. It is seen that the spring behaves linearly after F > 30N. Assuming that the spring shows linear behaviour after this point, ks will reduce to a constant. Using Equation (5) and taking the average of all trials, we can obtain the spring stiffness constant k. Values presented in Table 3 return the spring stiffness as ks = 320N/m. The cylinder is attached from both ends and, therefore, two springs are used during experiments. In this case, spring stiffness in our experiments becomes:


For springs, Hooke’s law states that: (3) where the spring stiffness ks is a function of displacement x. Change in the displacement is the difference of lengths of the spring under different loading conditions, i.e., ∆z = Ls – Ls-1. Force F is applied by the mass mL hooked up on the spring and it is calculated by:


where ɡ stands for gravitational acceleration. In this case, spring stiffness becomes: (5) The tested spring is an extension spring and does not behave linearly until it is stretched to a certain level. Values presented in Table 3 are

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Free Decay Tests Free decay tests were conducted in air to calculate the mechanical damping of the spring. Added mass in air was neglected. In this case, natural frequency in vacuum can be calculated by the equation:


Stiffness of the spring was ks = 320N/m and the oscillating mass (cylinder mass, 1/3 of spring mass and additional masses) was mosc = 9.8kg. Natural frequency in vacuum using Equation (7) becomes fn,v = 1.2862Hz. This value was taken as a reference to assess the validity of the free decay tests. An initial displacement was given to the cylinder and the successive peaks were noted. The tests were repeated six times; three of them are shown in Figure 9.

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Figure 8: Force applied on the spring versus its extension.

Figure 9: Free decay test results conducted in air.

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Successive peaks yn at each test were subjected to the logarithmic decay equation to calculate the damping coefficient ζn for each peak: (8) Then, the average of the damping coefficients at each peak were taken to calculate the damping coefficient of the system: (9)

Only the first 15 seconds of the motion was taken in calculation of the damping coefficient, as Equation (9) implies. This is due to the small oscillations that our measuring system was unable to capture precisely. Peaks of Test 5 in the first 15 seconds of motion are given in Figure 10 (left). Results of the fast Fourier transform (FFT) analysis are given in Figure 10 (right). The dominant frequency after FFT analysis was found to be f = 1.2868Hz which corresponds to the natural frequency of the spring in vacuum fn,v = 1.2862Hz. The digital values of the upper peaks of the displacement are given in Table 4 and lower peaks in Table 5. Damping coefficient at each peak calculated by Equation (8) is given at the last lines of these tables. The average damping coefficient for the upper peaks was ζn,upper = 0.0124 while it was ζn,lower = 0.0123 for lower peaks. So, the damping coefficient of the system was found to be the average of these two; ζ = 0.0124. Digitization of Cylinder Motion The motion of the cylinder was digitized and transferred to the computer via an Arduino board (Arduino Mega). As might be well known, Arduino is an open-source platform

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used for building electronics projects. It consists of both a microcontroller and an integrated development environment (IDE) that runs on computer. IDE uploads the computer code to the microcontroller. The ultrasonic sensor HC-SR04 measures the distance in a range of 2 to 400 cm within an accuracy of ±3 mm. The sensor module consists of an ultrasonic transmitter (sending sound waves to the target), a receiver (collects the reflected sound waves), and the control circuit. The ultrasonic sensor measures the distance using the following equation:


where y is the displacement of the cylinder, t is the elapsed time between transmission and receival of the ultrasonic signal, and c is the speed of sound in air. The ultrasonic sensor was mounted on the main frame of the VIV system and connected to the computer for recording data. Figure 11 represents the fundamentals of the ultrasonic sensor and shows where it is located in the VIV system. DETAILS OF THE EXPERIMENTS Our study focuses on vortex-induced vibrations of smooth circular cylinders having one degree-of-freedom at TrSL3 flow regime. Cross-flow motions of the cylinder are allowed while in-line vibrations are constrained. Experiments in this study were conducted for three different cases. Parameters involved in the experiments and related non-dimensional coefficients are given in this section. Physical Parameters of the Mechanical System The VIV experiments were conducted for a

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Figure 10: Peaks of the displacement in Test 5 (left). Results of the fast Fourier transform (FFT) analysis (right).

Table 4: Digital values of upper peaks in Test 5 and damping coefficients at each peak.

Table 5: Digital values of lower peaks in Test 5 and damping coefficients at each peak.

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Figure 11: Basic working principle of the ultrasonic sensor (left). Sensor placement in the vortex-induced vibrations (VIV) system (right). The sensor is mounted on the main frame and follows the motion of the cylinder.

cylinder having a diameter of D = 8cm and a length of L = 1.32m. Tests were done by adding three different additional weights (madd = 7kg, 9kg, and 11kg) to the system. The cylinder was attached to two springs that were connected to the main frame. The springs were identical and each had a stiffness of ks = 320N/m. The total spring stiffness of the mechanical system in this case becomes k = 2* ks = 640N/m. The main frame only allows motion perpendicular to the flow (vertical direction). Generally, the oscillating mass mosc consists of the cylinder mcyl, struts mstr, 1/3 of springs (both) mspr, and additional mass madd. Mathematically, the total oscillating mass in the system can be defined as: (11) Additional masses were provided and the mechanical system was in hydrostatic stability in the still fluid. Spring mass was negligible compared to the other components; therefore, it was taken as mspr ≈ 0 in calculations. Masses of each component are given in Table 6 and physical parameters involved in the experiments are presented in Table 7.

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The displaced mass of the cylinder can be calculated by: (12) Here, ρ is the fluid density. In this case, the displaced mass of the cylinder becomes mdisp = 6.64kg. The mass ratio was defined by m* = mosc/mdisp. Natural frequencies in vacuum and still water were defined respectively by:

(13) In these equations, ma represents the added mass of the fluid. The added mass is calculated by: (14) In this equation, Ca represents the added mass coefficient. Although this coefficient is subject to change for a dynamic system, it is taken as Ca = 1, which is actually the added mass coefficient in still water. So, the added

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Table 6: Total oscillating mass and the share of each component.

Table 7: Physical parameters used in the experiments.

Table 8: Parameters of the mechanical system.

mass in the experiments were taken as ma = 6.64kg. The total mechanical damping of the system was ζ=0.03. These parameters of the mechanical system are summarized in Table 8. Range of Reynolds Number and Reduced Velocity The experiments were conducted for a flow velocity range of 0.28m/s < U < 0.67m/s. Reynolds number was defined by and the reduced velocity by . In this case, range of the reduced velocity in experiments was: 4.5 < U* < 11.6

Considering the Reynolds number of the system, the flow can be defined as turbulent flow. This Reynolds number range corresponds to the Transition Shear Layer 3 flow regime as defined by Zdravkovich [1997] and shortly named as TrSL3. MATHEMATICAL MODEL In this study, the mathematical model is used to calculate:

• •

the lift coefficient acting on the cylinder during the oscillation and the phase difference between the cylinder oscillation and the vortex shedding.

and the Reynolds number range was: 22400 < Re < 53600

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These two parameters help understand the experiments and identify the branches. We

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know that the vibration equation reads as:

Collecting sine and cosine terms in Equation (21) shows two distinct equations. Setting: (15) (22)

where mosc is the total mass of the oscillating body, c is the total damping only due to the mechanical parts of the body such as springs, k is the spring stiffness, and F(t) is the fluid force acting on the body. z is the vertical position of the cylinder and z and z are the first and second derivatives of the displacement, indicating the velocity and the acceleration of the body, respectively. Rewriting Equation (15) by plugging in:

(23) and non-dimensionalizing the equation by:





(24) will reduce the linear mathematical model to two equations after some algebraic transformations:


would return: (18) Assuming that the cylinder motion is purely sinusoidal moving with a frequency ωosc, it is possible to set:

(26) In Equations (25) and (26), Cz is the total lift coefficient provided by the fluid, which is non-dimensionalized by the drag equation, and ϕ is the total phase difference. RESULTS



Taking the first and second derivatives of Equation (19) and placing these equations into Equation (18) gives us:

The amplitude and frequency responses of the cylinder were experimentally obtained and are presented in this section. The amplitude and frequency of the cylinder motion were first obtained in dimensional form and then non-dimensionalized using related equations.


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Table 9: Dimensional amplitude and frequency response of the cylinder.

Dimensional results of the cylinder response are given in Table 9. The fluid velocity U was non-dimensionalized by the natural frequency in still water times the cylinder diameter fn,w∙D (which is U*), the amplitude A by the cylinder diameter D (which is A*), and the oscillation frequency fosc by the natural frequency in still water fn,w (which is f*). Graphical representation of non-dimensional experimental results is given in Figure 12. The amplitude response of a cylinder in VIV can be divided into four categories [Williamson, 1997]: initial branch, upper branch, lower branch, and the desynchronization range. Experimental results provided in Figure 12 are discussed with respect to these response definitions below.

The initial branch: There was no considerable cylinder motion until U* < 4. At U* ≅ 4 – 5, there was a sudden jump in the amplitudes for m* = 3.064 and m* =

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3.366 which is defined as the initial branch in our experiments. Initial branch started a bit later for the case of m* = 3.667 at about U* ≅ 5 – 6. The upper branch: It can be stated that the upper branch starts at around U* ≅ 5.5 where the amplitudes remain at similar magnitudes (the increase is gradual) until U* ≅ 7 for m* = 3.064 and m* = 3.366 cases. Therefore, it can be said that the upper branch range happened at a limited flow velocity in the experiments with a range of 5.5 < U* < 7. This range was even smaller for the m* = 3.667 case where it happened in the range of 6 < U* <6.5. The lower branch: Drop in the amplitudes start at around U* ≅ 7 for all mass ratios. This decrease in the amplitude response continued until U* ≅ 10. The lower branch range can be identified as 7 < U* < 10. One thing to note here is that the lower branch was oscillatory in m* = 3.366 case between 7 < U* <8.

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Figure 12: The amplitude (left) and frequency (right) responses of the cylinder.

Desynchronization: The experimental results show that the cylinder is no longer synchronized with the flow after U* > 10.

Actually, the existence of the lower branch is still a debatable topic in the literature. Khalak and Williamson [1999] define the lower branch as a range of VIV between the upper branch and desynchronization, in which amplitudes monotonically decrease (or stay constant). In our case, we do not clearly see such a branch; the amplitudes diminish very quickly after the upper branch and reach desynchronization after U* > 10. The difference between Khalak and Williamson’s study and ours is attributed to the difference in VIV flow regimes. Their study was conducted at relatively low Reynolds numbers at TrSL2 flow regime while our experiments reach Reynolds numbers up to 60,000 corresponding to the TrSL3. A decade ago, Raghavan and Bernitsas [2011] showed that, at TrSL3 flow regime, the VIV response is different compared to Khalak and Williamson’s VIV branch definitions. After extensive experiments, they have

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noticed that the lower branch is completely overtaken by the upper branch and was not observable in the amplitude graphs. In our experiments, we have also obtained similar results: the existence of lower branch is not visible to the eye in the amplitude response. The end of the upper branch and the start of the desynchronization range are not clear in the amplitude and frequency responses of the cylinder. However, it is possible to identify the specific border by making use of the mathematical model. For that, we require oscillation frequencies of the cylinder as well as its amplitudes. The frequency responses of the cylinder in nondimensional form f* in experiments are given in Figure 12 (right). This figure clearly identifies the initial branch. There was a sudden jump in the frequency at around U* ≅ 4 – 6 which can be seen as the excitation in the initial branch. The frequency response was in a gradual increase after the start of the upper branch. Another way to identify these branches is by using the mathematical model. The lift

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Table 10: Lift coefficients and phase differences of m*=3.064 calculated using the mathematical model.

Figure 13: The lift coefficient Cz acting on the cylinder (left) and the phase difference ϕ between the oscillation and vortex shedding (right) during the experiments. Graphs are given with respect to the reduced velocity calculated in water (U* ).

coefficient acting on the cylinder and the phase difference between the oscillation and the vortex shedding are calculated using the mathematical model explained briefly in previous sections. When calculated and graphed with respect to the reduced velocity, it provides an insight to the start and end of all defined branches. The amplitude and frequency response of the cylinder in the experiments are provided as inputs to the mathematical model. Results of m* = 3.064 case are tabulated in Table 10 and graphically represented in Figure 13. As it can be observed from Figure 13 (left), the lift coefficient starts with a sharp increase in the initial branch and its peak is at around U* ≅ 5 – 5.5 for all cases, coinciding with the start of the upper branch. After U* ≥ 5.5, Copyright Journal of Ocean Technology 2022

the lift coefficient gradually decreased in the upper branch. It had local minimums at about U* ≅ 8 – 8.5 which is in the lower branch. The behaviour of the lift coefficient seems gradual and insignificant after this point. To identify the other branches, phase difference behaviour should be investigated. It is given in Figure 13 (right). The phase difference between the vortex shedding and the cylinder oscillation was small in the initial and upper branches. However, there were sudden shifts between 7 ≤ U* ≤ 10 and the vortices were then out of phase with the cylinder oscillation. This range actually spots the lower branch and, after that, the increase in phase difference slows down. This is the desynchronization range, where the vortices are completely out of phase.

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DISCUSSION Previously, the discrepancy of amplitude response in different studies for 1-DOF smooth circular cylinders in VIV for 3 < m* < 4 range was noted. In this section, our experimental results are compared with these studies. It is possible to categorize the experiments in three groups:

• •

m* ≈ 3 group which covers studies of Triantafyllou et al. [2003], Stappenbelt and O’Neill [2007], and our experiments at m* = 3.064. m* ≈ 3.4 group which covers the paper by Modir et al. [2016] and our experiments at m* ≈ 3.366. m* ≈ 3.7 group which covers the study of Stappenbelt et al. [2007] and our experiments at m* = 3.667.

Comparisons are given in Figure 14. In m* ≈ 3 group, our experiments show similarity with Triantafyllou et al. [2003]. The most notable difference between the two experiments is the existence of a lower branch in Triantafyllou et al. [2003]. Their experiments were conducted at a Reynolds number of Re = 30,000 staying in TrSL2 flow regime while our experiments reach up to Re ≈ 60,000. Due to our experiments being conducted at TrSL3, we did not observe a lower branch. Amplitude response of Stappenbelt and O’Neill [2007] in this group neither fits with the other two, nor is consistent with the other experiments of the same group (see Figure 1). Results are not in accordance in m* ≈ 3.4 group, as there is a great deviation in amplitude response between our experiments

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and Modir et al. [2016]. There is also a significant difference between their study and the other papers, which is given in Figure 1. Although we cannot make a solid statement about this deviation, it might be that their cylinder was 38 cm long while the test section was 50 cm. High mass-damping ratio should be noted in their study [Khalak and Williamson, 1999] but we are in doubt about the possible effect of tip flow which greatly reduces the effective span of the cylinder [Kinaci et al., 2016; Duanmu et al., 2017]. Agreement in m* ≈ 3.7 group was very good. Our Reynolds number range and mass ratio are very similar to Stappenbelt et al. [2007] and this similarity was reflected to the amplitude response of the cylinder. Initial and lower branches and the range of synchronization match perfectly. The only notable difference between the two experiments is the maximum achieved amplitude. The comparison of maximum amplitudes for each study is given in Table 11. They generally occur at around U* ≈ 6 – 7. Despite using similar parameters (see Table 1), comparisons given in Figure 1 and Figure 14 reveal the highly nonlinear flow features of VIV. The discrepancies between results might actually be lying on the unseen (and mostly unreported): the type of the test basin (towing tank or circulation channel), test section width, the structural robustness of the apparatus (if somehow both ends of the cylinder are not moving together, this might diminish the amplitudes), the positioning of the cylinder (vertical or horizontal), etc. Additionally, it is believed that uncertainties involved in the VIV response of the cylinder

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Figure 14: Comparison of the amplitude response in our experiments with others in the literature.

Table 11: Maximum amplitudes (A* ) obtained at each experiment.

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should also be reported in these experiments [Usta and Duranay, 2021] to be able to assess their level of confidence. On the other hand, when discussed alongside other results published in the literature, it can be said that our results are in line with Triantafyllou et al. [2003] and Stappenbelt et al. [2007]. Experimental conditions at our test facility were very similar with Stappenbelt et al. [2007] but we cannot make any assessment with Triantafyllou et al. [2003] as their paper lacks some important parameters to come up with a conclusion. CONCLUSION In this study, experiments were conducted in Ata Nutku Circulation Channel for a smooth circular cylinder in VIV at TrSL3 flow regime having one degree-of-freedom. The mass ratio range was 3 < m* < 4. This range was selected on purpose due to results in the literature having high discrepancies in the amplitude response. It was found that the increase in mass ratio results in narrower range of synchronization. Unlike some other studies that measure the maximum achieved amplitude around A*max ≈ 0.4 – 0.6, our experiments show that A*max ≅ 1. It is considered that this difference arises from different cylinders/test sections used in different laboratories, where some part of the lift supporting the cylinder escapes from the tips. Other possible reasons are the differences in the test basin used or the positioning of the cylinder. In the future, we will conduct more experiments with cylinders having different lengths and positioning to understand the underlying physical mechanism.

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ACKNOWLEDGMENT This study was supported by the Research Fund of the Istanbul Technical University, Project ID: 41188. The authors declare that they have no conflict of interest. REFERENCES Bahmani, M.H. and Akbari, M.H. [2010]. Effects of mass and damping ratios on VIV of a circular cylinder. Ocean Engineering, 37(5-6), 511-519. Belloli, M.; Giappino, S.; Muggiasca, S.; and Zasso, A. [2012]. Force and wake analysis on a single circular cylinder subjected to vortex induced vibrations at high mass ratio and high Reynolds number. Journal of Wind Engineering and Industrial Aerodynamics, 103, 96-106. Bernitsas, M.M.; Raghavan, K.; Ben-Simon, Y.; and Garcia, E.M.H. [2008]. VIVACE (vortex induced vibration aquatic clean energy): a new concept in generation of clean and renewable energy from fluid flow. Journal of Offshore Mechanics and Arctic Engineering, 130(4). Bernitsas, M.M. [2016]. Harvesting energy by flow included motions. In Springer Handbook of Ocean Engineering (pp. 1163-1244). Springer, Cham. Chang, C.C.J.; Kumar, R.A.; and Bernitsas, M.M. [2011]. VIV and galloping of single circular cylinder with surface roughness at 3.0× 104≤ Re≤ 1.2× 105. Ocean Engineering, 38(16), 1713-1732. Duanmu, Y.; Zou, L.; and Wan, D.C. [2017]. Numerical simulations of vortex-induced vibrations of a flexible riser with different aspect ratios in uniform and shear currents. Journal of Hydrodynamics, 29(6), 1010-1022. Gao, Y.; Zong, Z.; and Sun, L. [2011]. Numerical prediction of fatigue damage in steel catenary riser due to vortex-induced vibration. Journal of Hydrodynamics, 23(2), 154-163. Gao, Y.; Zong, Z.; Zou, L.; and Jiang, Z. [2018]. Effect of surface roughness on vortex-induced vibration response of a circular cylinder. Ships and Offshore Structures, 13(1), 28-42. Kang, Z.; Zhang, C.; Chang, R.; and Ma, G. [2019]. A numerical investigation of the effects of

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Reynolds number on vortex-induced vibration of the cylinders with different mass ratios and frequency ratios. International Journal of Naval Architecture and Ocean Engineering, 11(2), 835-850. Khalak, A. and Williamson, C.H. [1999]. Motions, forces and mode transitions in vortex-induced vibrations at low mass-damping. Journal of Fluids and Structures, 13(7-8), 813-852. Kinaci, O.K. and Gokce, M.K. [2015]. Selfpowered flow-induced pump. Provisional Patent Application. Application No. TR2015/17104. Kinaci, O.K.; Lakka, S.; Sun, H.; and Bernitsas, M.M. [2016]. Effect of tip-flow on vortex induced vibration of circular cylinders for Re < 1.2* 105. Ocean Engineering, 117, 130-142. Lakka, S. [2011]. Flow sensor. Patent Application. Publication No. WO 2011/161298 A1. Leontini, J.S.; Thompson, M.C.; and Hourigan, K. [2006]. The beginning of branching behaviour of vortex-induced vibration during twodimensional flow. Journal of Fluids and Structures, 22(6-7), 857-864. Mannini, C.; Marra, A.M.; and Bartoli, G. [2014]. VIV–galloping instability of rectangular cylinders: Review and new experiments. Journal of Wind Engineering and Industrial Aerodynamics, 132, 109-124. Martins, F.A.C. and Avila, J.P.J. [2019]. Threedimensional CFD analysis of damping effects on vortex-induced vibrations of 2DOF elastically-mounted circular cylinders. Marine Structures, 65, 12-31. Modir, A.; Kahrom, M.; and Farshidianfar, A. [2016]. Mass ratio effect on vortex induced vibration of a flexibly mounted circular cylinder, an experimental study. International Journal of Marine Energy, 16, 1-11. Park, H.; Bernitsas, M.M.; and Ajith Kumar, R. [2012]. Selective roughness in the boundary layer to suppress flow-induced motions of circular cylinder at 30,000< Re< 120,000. Journal of Offshore Mechanics and Arctic Engineering, 134(4). Pigazzini, R.; Contento, G.; Martini, S.; Puzzer, T.; Morgut, M.; and Mola, A. [2018]. VIV analysis of a single elastically-mounted 2D cylinder: parameter identification of a single-degree-offreedom multi-frequency model. Journal of Fluids and Structures, 78, 299-313.

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Pigazzini, R.; Contento, G.; Martini, S.; Morgut, M.; and Puzzer, T. [2019]. An investigation on VIV of a single 2D elastically-mounted cylinder with different mass ratios. Journal of Marine Science and Technology, 24(4), 1078-1091. Raghavan, K. and Bernitsas, M.M. [2011]. Experimental investigation of Reynolds number effect on vortex induced vibration of rigid circular cylinder on elastic supports. Ocean Engineering, 38(5-6), 719-731. Ramberg, S.E. and Griffin, O.M. [1981]. Hydroelastic response of marine cables and risers. Hydrodynamics in Ocean Engineering, 1223-1245. Sarpkaya, T. [2004]. A critical review of the intrinsic nature of vortex-induced vibrations. Journal of Fluids and Structures, 19(4), 389-447. Stappenbelt, B.; Lalji, F.; and Tan, G. [2007]. Low mass ratio vortex-induced motion. In: 16th Australasian Fluid Mechanics Conference (Vol. 12, pp. 1491-1497). Crown Plaza, Gold Coast Australia. Stappenbelt, B. and O’Neill, L. [2007]. Vortexinduced vibration of cylindrical structures with low mass ratio. In: The Seventeenth International Offshore and Polar Engineering Conference. International Society of Offshore and Polar Engineers. Sumer, B.M. and Fredsoe, J. [2006]. Hydrodynamics around cylindrical structures (Vol. 26). World Scientific. Sun, H.; Kim, E.S.; Nowakowski, G.; Mauer, E.; and Bernitsas, M.M. [2016]. Effect of mass-ratio, damping, and stiffness on optimal hydrokinetic energy conversion of a single, rough cylinder in flow induced motions. Renewable Energy, 99, 936-959. Sun, W. and Seok, J. [2020]. A novel self-tuning wind energy harvester with a slidable bluff body using vortex-induced vibration. Energy Conversion and Management, 205, 112472. Tamimi, V.; Naeeni, S.T.O.; Zeinoddini, M.; Seif, M.S.; and Dolatshahi Pirooz, M. [2019]. Effects of after-body on the FIV of a right-angle triangular cylinder in comparison to circular, square, and diamond cross-sections. Ships and Offshore Structures, 14(6), 589-599. Triantafyllou, M.S.; Hover, F.S.; Techet, A.H.; and Yue, D.K.P. [2003]. Vortex-induced vibrations of slender structures in shear flow.

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In: IUTAM Symposium on Integrated Modeling of Fully Coupled Fluid Structure Interactions Using Analysis, Computations and Experiments (pp. 313-327). Springer, Dordrecht. Usta, O. and Duranay, A. [2021]. Uncertainty analysis of experiments of vortex-induced vibrations for circular cylinders. Journal of Applied Fluid Mechanics, 14(2), 541-553. Vinod, A. and Banerjee, A. [2014]. Surface protrusion based mechanisms of augmenting energy extraction from vibrating cylinders at Reynolds number 3×103 – 3×104. Journal of Renewable and Sustainable Energy, 6(6), 063106. Wang, J.; Zhou, S.; Zhang, Z.; and Yurchenko, D. [2019]. High-performance piezoelectric wind energy harvester with Y-shaped attachments. Energy Conversion and Management, 181, 645-652. Williamson, C.H.K. [1997]. Advances in our understanding of vortex dynamics in bluff body wakes. Journal of Wind Engineering and Industrial Aerodynamics, 69, 3-32. Williamson, C.H.K. and Govardhan, R. [2004]. Vortex-induced vibrations. Annual Review of Fluid Mechanics, 36, 413-455. Wu, W. and Wang, J. [2018]. Numerical simulation of VIV for a circular cylinder with a downstream control rod at low Reynolds number. European Journal of Mechanics-B/Fluids, 68, 153-166. Xu, J.; Jia, X.; Duan, M.; Gu, J.; Yu, Y.; and Wang, Y. [2019]. An improved model for VIV fatigue life prediction of slender marine structures in time-varying flows. Journal of Marine Science and Technology, 24(2), 490-499. Yang, K.; Wang, J.; and Yurchenko, D. [2019]. A double-beam piezo-magneto-elastic wind energy harvester for improving the galloping-based energy harvesting. Applied Physics Letters, 115(19), 193901. Zdravkovich, M.M. [1997]. Flow around circular cylinders: Volume 2: Applications (Vol. 2). Oxford University Press. Zhao, M.; Cheng, L.; An, H.; and Lu, L. [2014]. Three-dimensional numerical simulation of vortex-induced vibration of an elastically mounted rigid circular cylinder in steady current. Journal of Fluids and Structures, 50, 292-311. Zhao, J.; Leontini, J.; Jacono, D.L.; and Sheridan,

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J. [2019]. The effect of mass ratio on the structural response of a freely vibrating square cylinder oriented at different angles of attack. Journal of Fluids and Structures, 86, 200-212. Zhu, H. and Gao, Y. [2017]. Vortex induced vibration response and energy harvesting of a marine riser attached by a free-to-rotate impeller. Energy, 134, 532-544.

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DR. CURRAN CRAWFORD, P.ENG. PROFESSOR, DEPARTMENT OF MECHANICAL ENGINEERING UNIVERSITY OF VICTORIA MEMBER, INSTITUTE FOR INTEGRATED ENERGY SYSTEMS VICTORIA, B.C., CANADA Dr. Curran Crawford leads the systems engineering part of the Solid Carbon project, which includes conducting a preliminary design exercise to access performance and economics of a system to capture CO2 and store it in ocean basalts. The project team looks at various CO2 capture methods – including direct air capture (DAC, including various variants) as well as sea water CO2 capture driven by offshore wind energy. CO2 would be compressed and transported via ship or pipeline to the wellhead for injection. Various control and energy storage methods to buffer the wind energy and electrochemical capture processes are under consideration, including hydrogen production for process heat as well as a potential co-product of the system to enhance economics. An overall optimization framework has been assembled to compare different optimal system configurations, as well as to look at different global locations and terrestrial CO2 point-capture sources in British Columbia and basalt reservoirs globally in addition to the baseline Cascadia site. The feasibility study looks for system cost and efficiency improvements and supports followon stages towards front end engineering design work and eventual injection and full system demonstration projects. The team aims to synthesize a viable carbon capture and storage (CCS) that can scale globally to Gt scale, and, Copyright Journal of Ocean Technology 2022

through using non-grid connected “stranded” offshore wind, avoid CCS competing with grid decarbonization efforts. CCS and DAC, in particular, are nascent technologies in an early market development stage. This research, though, is required now so that there is time to design viable solutions for CCS that can be rapidly ramped up as they become critical in the post-2030 period. Decarbonization of our energy system and societal activities in general is a baseline critical endeavour, but given historical and continuing political, industrial, and societal inaction on deep carbon reductions, CCS will be required to abate historical atmospheric CO2 emissions. Dr. Crawford appreciates working in a multidisciplinary team to translate the science of basalt storage formations and legal/social considerations into technical specifications for the design of the system. Students coming out of the research also give him hope as the next generation of researchers take up the mantle of climate change mitigation work in their careers.

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Observing Flood Damage Sharifipour, Amani, and Moghimi developed a method to assess damages to different Land Use/Land Cover types caused by floods. Who should read this paper?

Mehdi Sharifipour

Researchers in the fields of remote sensing, oceanography, hydrology, and natural disasters can benefit from this study. This paper provides a method for global flood change detection using cloud commuting methods. Since many land surface changes frequently occur everywhere, this method is interesting for many researchers who monitor these changes.

Why is it important?

In this study, floods were studied on a global scale without any geographical limitations. Moreover, various datasets, such as satellite observations and machine learning models available in Google Earth Engine cloud computing platform, were employed to get faster and better results. The results of the proposed methods can be used to reduce the flood risk and highlight the location of high-risk areas near coastlines. Moreover, the results can be used to investigate excessive water flows from upstream into the water level downstream. Finally, the proposed method can be used to monitor coastal zones that are prone to marine flooding.

Dr. Meisam Amani

Armin Moghimi

Scan using your smartphone to see the dataset used for this research.

About the authors

Mehdi Sharifipour received a master’s degree in remote sensing and GIS in 2019. He has been working in the field of geospatial data for more than eight years. He has strong experience in GIS and RS project management, satellite estimation of agricultural crops, design and implementation of Web GIS systems, mapping consulting, and cadastre. To this end, he has worked with various optical and radar satellite data as well as many software packages, such as Google Earth Engine, Arc MAP, ENVI, SNAP, TerrSet, and AUTOCAD. Dr. Meisam Amani is currently the remote sensing team lead at Wood PLC, a global consulting and engineering company, where he manages and leads various industrial, governmental, and academic remote sensing projects worldwide. Over the past 11 years, he has worked on different applications of remote sensing, including but not limited to land cover/land use classification, soil moisture estimation, drought monitoring, water quality assessment, watershed management, power/transmission line monitoring, fog detection and nowcasting, and ocean wind estimation. To do these, he has utilized various remote sensing datasets (e.g., UAV, optical, LiDAR, SAR, scatterometer, radiometer, and altimeter) along with different machine learning and big data processing algorithms. A list of his research works, including over 50 peer-reviewed journal and conference papers, can be found at https://www.researchgate.net/profile/Meisam_Amani3. Armin Moghimi received a B.Sc. degree in geomatics engineering from the Shahid Beheshti University (formerly Geomatics College of National Cartographic Center) Tehran, Iran, in 2013; and a M.Sc. degree in photogrammetry engineering in 2015 from the K.N. Toosi University of Technology, Tehran, Iran, where he is currently working toward a PhD degree in photogrammetry and remote sensing. He is currently working as a senior lecturer at the Engineering Faculty of Islamic Azad University South Tehran Branch. His research interests include change detection techniques, image preprocessing, image registration, machine learning. A list of his research works, including over 23 peer-reviewed journal and conference papers, can be found at https://www.researchgate.net/profile/Armin-Moghimi.

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FLOOD DAMAGE ASSESSMENT USING SATELLITE OBSERVATIONS WITHIN THE GOOGLE EARTH ENGINE CLOUD PLATFORM Mehdi Sharifipour1, Meisam Amani2, Armin Moghimi3 Tadbir Kesht Golestan Company, Golestan, Iran; Tadbirkesht93@gmail.com 2 Wood Environment & Infrastructure Solutions, Ottawa, O.N., Canada; meisam.amani@woodplc.com 3 Department of Remote Sensing and Photogrammetry, Faculty of Geodesy and Geomatics Engineering, K.N. Toosi University of Technology, Tehran, Iran; moghimi.armin@gmail.com


ABSTRACT Floods cause significant damages to different assets every year and, thus, it is important to monitor floods and assess their damage using advanced technologies. In this regard, remote sensing systems, which provide frequent and consistent observations over large areas with minimum cost, are great resources. In this study, we developed a method to assess the damages to different Land Use/Land Cover (LULC) types caused by floods in the three countries of Iran, Ireland, and Sweden. The amount of flood damage to different LULCs was investigated using the flooded areas reported in the Emergency Management Service (EMS) and the generated LULC maps using the Support Vector Machine (SVM) algorithm and Sentinel satellite data within the Google Earth Engine (GEE) cloud computing platform. Overall Accuracies (OAs) for the LULC maps of Iran, Ireland, and Sweden were 84%, 88%, and 70%, respectively. The experimental results showed that cropland and barrens with 25,099 and 17,164 flooded areas were the most damaged LULC classes, respectively. The amount of damage for the tree class was 3,949 hectares.

KEYWORDS Flood; Land cover; Google Earth Engine; Machine learning; Sentinel

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INTRODUCTION Floods are among the most frequent and destructive natural disasters, threatening human lives, agricultural activities, and infrustructure [Ward et al., 2013; Chumann et al., 2018; Iqbal et al., 2018]. Therefore, providing a reliable and cost-effective method for flood damage assessment is of great importance. In this regard, remote sensing systems provide a wide range of datasets, which can be effectively utilized for flood mapping and assessing the corresponding damages to the environment [Giustarini et al., 2015]. So far, many statistical and probabilistic models [Al-Abadi, 2018; Costache and Tien, 2019], as well as machine learning and data-mining methods [Avand et al., 2020B] have been employed along with various remote sensing images for flood damage assessment. One of the critical inputs for flood damage assessment is accurate Land Use/Land Cover (LULC) maps from the study area [Luo et al., 2021]. Spaceborne remote sensing datasets have been widely used for LULC classification. For example, currently, there are many openaccess optical and Synthetic Aperture Radar (SAR) systems, the integration of which can considerably improve the accuracy of the LULC maps [Dobrinić et al., 2020]. Moreover, it has been widely argued that multi-temporal remote sensing images could provide reliable and cost-efficient information about LULC [Zhang et al., 2015; Bhatt et al., 2016]. It is required to process a large amount of satellite data when the objective is LULC classification over large areas. To tackle this, various cloud computing platforms, such

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as Google Earth Engine (GEE), have been developed. GEE has been mainly designed for parallel processing, storing, and mapping different remote sensing datasets at various spatial scales. Various machine learning algorithms have been so far developed for LULC classification using satellite images. The Support Vector Machine (SVM), Random Forest (RF) [Avand et al., 2020A], Decision Tree [Khosravi et al., 2018], Artificial Neural Networks (ANN) [Chen et al., 2020; Pham et al., 2020], Frequency Ratio, Quantile Regression Forests [Taillardat et al., 2017], and K-Nearest Neighbor (KNN) are among the widely-used methods. In this regard, RF and SVM have significant potential for land cover mapping since they are flexible and robust against the nonlinear and noisy relations between input features and the corresponding class labels [Friedl and Brodley, 1997]. Moreover, the KNN classifier has been widely used because it is a simple algorithm [Li and Cheng, 2009]. So far, many studies have employed satellite images along with machine learning algorithms in GEE for LULC classification. For instance, the first Canada-wide wetland inventory using Landsat-8 imagery and innovative image processing techniques was created within GEE by Amani et al. [2019]. For this purpose, a large amount of field samples and approximately 30,000 Landsat-8 satellite images were initially processed using several advanced algorithms within GEE. Then, the RF algorithm was applied to classify the entire country. The result was the preliminary Canadian Wetland Inventory map considering the five wetland classes, defined by the

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Canadian Wetland Classification System (i.e., bog, fen, marsh, swamp, and shallow water). Moreover, Ghorbanian et al. [2020] produced an improved Iranian LULC map with 13 classes and a spatial resolution of 10 m. To this end, 2,869 Sentinel-1 and 11,994 Sentinel-2 satellite images along with an object-based RF were utilized. The Overall Accuracy (OA) and Kappa Coefficient of the final map for 2019 were 91.35% and 0.91, respectively [Ghorbanian et al., 2020]. In another study, for the first time, the GEE cloud computing platform was used along with an ANN algorithm and Sentinel-1 and Sentinel-2 images to produce an objectbased Annual space-based Crop Inventory (ACI) map of Canada [Amani et al., 2020]. Although accuracy levels were slightly lower than those of the Agriculture and Agri-Food Canada’s ACI map, this study demonstrated that the proposed cloud computing method should be investigated further because it was more efficient in terms of cost, time, computation, and automation. Traditional methods of flood mapping are based on ground surveys and aerial observations. However, these methods are time-consuming and expensive [Danee and Helen, 2015]. On the other hand, remote sensing technology has many advantages for flood mapping especially over large areas and when the objective is flood monitoring over time. Different remote sensing systems, such as Satellite Pour l’Observation de la Terre Multispectral, Landsat, Moderate Resolution Imaging Spectroradiometer (MODIS), and Advanced Very HighResolution Radiometer have been widely used for flood mapping. For example, Atif et

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al. [2016] used the free MODIS satellite data with 250 m resolution to delineate the flood extents in Pakistan on a daily basis. Based on the above explanations, LULC and flood maps are the two main inputs to assess the flood damage to different LULC classes. In this study, satellite imagery along with machine learning algorithms were employed to generate this information and input them in GEE to assess the damage of floods, which occurred in the three countries of Iran, Ireland, and Sweden in February 2020. MATERIALS AND METHODS Study Area and Data In this study, the flood events which occurred in February 2020 and were reported by Emergency Management Service (EMS) were considered. According to EMS reports, three floods occurred in Iran, Sweden, and Ireland. Table 1 provides some information about these flood events and Figure 1 illustrates their geographical distributions. In this study, the images captured by two satellites of Sentinel-1 and Sentinel-2 were employed. Sentinel-2 is an optical Earth Observation mission launched by the European Space Agency (ESA) to continue ESA’s global services on multispectral high spatial resolution observations. This mission includes the Sentinel-2A and Sentinel-2B satellites. The temporal resolution of the constellation is five days. The Multispectral Instrument (MSI), a push-broom sensor, is the main sensor of Sentinel-2. MSI provides 13 spectral bands with wide spectral coverage over the visible, Near Infrared, and Shortwave Infrared

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Table 1: Flood events occured worldwide in February 2020.

Figure 1: The extent of flood events that occurred in Iran, Ireland, and Sweden in February 2020.

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Figure 2: The proposed method for flood damage assessment.

domains at different spatial resolutions varying from 10 m to 60 m [Rahmati et al., 2016]. In this study, the level 2A products of Sentinel-2, which are available in GEE (Dataset ID: ee.ImageCollection(“COPERNICUS/S2_SR”), were used. Sentinel-1 is also a SAR system launched by ESA. This mission is composed of two satellites, Sentinel-1A and Sentinel-1B, which share the same orbital plane. They carry a C-band SAR instrument which provides a collection of data in all-weather, daytime, and nighttime. The constellation is on a sunsynchronous, near-polar (98.18°) orbit. The orbit has a 12-day repeat cycle and completes 175 orbits per cycle. Method The flowchart of the proposed method to assess flood damage is illustrated in Figure 2. It should be noted that all the flooded regions were considered as damaged areas in this study. The flood layer and LULC maps were the two inputs of the proposed approach which is described below.

zones were initially extracted. EMS uses satellite imagery and other geospatial data to produce these reports. The quality of the vector package and the maps are firstly controlled by the service provider before being published to ensure the delivery of good quality product, and secondly by the European Commission’s Joint Research Centre (EC JRC) to ensure high quality of the final product. This specific workflow, composed of two consecutive rounds of quality control, guarantees both high quality and fast delivery of products. The quality control performed by the EC JRC leads either to the acceptance or to the rejection of the product, depending on whether or not the product is in line with the quality criteria. In case of a rejection, a new version is produced in which the error(s) is corrected. The details of the results of the quality control of EMS flood maps are not available, but several studies, such as Spasenovicl and Carrion [2019], have assessed their accuracies and confirmed their reliability. Thus, it was assumed that their accuracies were high enough to be used in this study.

Flood Layer The vector data related to floods, reported by EMS (see Table 1), and the map of flood

LULC Map As discussed, Sentinel-2 optical and Sentinel-1 SAR satellite data were used to produce LULC

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Figure 3: (a) True colour compsite of Sentinel-2 images (row 1), (b) false colour composite of Sentinel-1 (VV/VH/VV polarizations) images, and (c) Normalized Difference Vegetation Index (NDVI) from three zoomed regions over the study areas.

maps. Initially, the data were preprocessed in GEE to make them suitable for LULC classification. Several preprocessing steps, including time filter, spatial filter, and cloud masking, were performed on the Sentinel-2 images. Along with the main spectral bands of Sentinel-2, the Normalized Difference Vegetation Index (NDVI) was also produced and was used within the classification algorithm to improve the accuracy of the LULC maps. Several preprocessing steps, including time filter, spatial filter, and noise reduction, were also applied to Sentinel-1 data. Figure 3 illustrates the processed Sentinel-2, Sentinel-1, and the NDVI for three zoomed regions in the study areas. After preparing the Sentinel-1/2 satellite images, there were ingested into the SVM machine

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learning algorithm to produce the LULC maps. SVM has several tuning parameters, the most important of which are kernal type, capacity constant, and gamma. These paramters can considerably affect the final result of a classification and, therefore, their optimum values should be selected to obtain the highest possible accuracy. In this study, after several trial and errors, Radial Basis Function, 1,000,000, and 0.01 values were assigned to these three tuning paramters, respectively. SVM is a supervised classification algorithm and, thus, needs training and test samples to train the algorithm and evaluate the final classification accuracy, respectively. In this study, the reference samples for the six LULC classes (i.e., tree, water, building, cropland, barren, and grassland) were generated using

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Figure 4: Land Use/Land Cover (LULC) maps over the study areas, generated using the Support Vector Machine (SVM) classification algorithm and Sentinel satellite images.

visual interpretation of the very high-resolution Google Earth images. All samples were then randomly divided into two groups of training (70%) and validation (30%).

It was visually observed that the maps had reasonable accuracies. Moroever, as is clear from Figure 5, the accuracies were high, indicating the high potential of the proposed method for LULC classification.

RESULTS AND DISCUSSION Figure 4 demonstrates the LULC maps produced using the proposed method. Table 2 shows the results of the confusion matrix of the SVM classification and Figure 5 provides the statistical accuracies of the LULC maps using 1,639 validation samples.

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As discussed in the method section, the LULC maps were overlaid on the flood maps to understand the level of flood damage on each LULC type. Figure 6 shows the results of this investigation for three zoomed areas, and Figure 7 illustrates the statistical results about the level of damage to each LULC

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Table 2: Confusion matrix of the Support Vector Machine (SVM) classification.

Figure 5: The overall accuracies and kappa coefficients of the classified Land Use/Land Cover (LULC) maps of Iran, Ireland, and Sweden.

type. The results showed that the highest damage was related to the cropland and barren classes, (25,099 hectares and 17,164 hectares, respectively), and the amount of damage for the tree class was the lowest (3,949 hectares). Therefore, it is essential to pay attention to reducing the damage in the cropland class. CONCLUSION Remote sensing data along with machine learning algorithms can be effectively used to investigate natural events, such as floods,

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and their effect to the environment. This study investigated flood damage using satellite imagery in GEE. First, two datasets, including LULC and flood maps were generated and, then, they were overlaid to assess the damage of floods to different LULC types. The results showed that the amount of flood damage to LULC class in the three countries of Iran, Ireland, and Sweden was 2,342, 33,661, and 19,459 hectares, respectively, and the highest extent of damage was in the cropland and barren areas. Overall, it was concluded that combining open-access satellite data, such as

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Figure 6: Spatial extent of flood damage to different Land Use/Land Cover (LULC) classes in the zoomed images from each study area.

Figure 7: The amount of flood damage to each Land Use/Land Cover (LULC) class.

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those acquired by the Sentinel satellites, and machine learning algorithms in the GEE cloud computing was a cost-efficent and reliable approach for flood damage assessment. One of the limitations of this study was the lack of ground truth data and accuracy levels of the EMS flood maps, which should be considered in future studies. REFERENCES Al-Abadi, A.M. [2018]. Mapping flood susceptibility in an arid region of southern Iraq using ensemble machine learning classifiers: a comparative study. Arabian Journal of Geosciences, 11, 218. https://doi.org/10.1007/ s12517-018-3584-5. Amani, M.; Mahdavi, S.; Afshar, M.; Brisco, B.; Huang, W.; Mohammad Javad Mirzadeh, S.; White, L.; Banks, S.; Montgomery, J.; and Hopkinson, C. [2019]. Canadian Wetland Inventory using Google Earth Engine: the first map and preliminary results. Remote Sensing, 11, 842. https://doi.org/10.3390/rs11070842. Amani, M.; Kakooei, M.; Moghimi, A.; Ghorbanian, A.; Ranjgar, B.; Mahdavi, S.; Davidson, A.; Fisette, T.; Rollin, P.; Brisco, B.; and Mohammadzadeh, A. [2020]. Application of Google Earth Engine Cloud Computing Platform, Sentinel imagery, and neural networks for crop mapping in Canada. Remote Sensing, 12, 3561. https://doi.org/10.3390/rs12213561. Atif, I.; Mahboob, M.; and Waheed, A. [2016]. Spatio-temporal mapping and multi-sector damage assessment of 2014 flood in Pakistan using remote sensing and GIS. Indian Journal of Science and Technology, 9. 10.17485/ ijst/2015/v8i35/76780. Avand, M.; Janizadeh, S.; Bui, D.T.; Pham, V.H.; Ngo, P.T.T.; and Nhu, V. [2020A]. A tree-based intelligence ensemble approach for spatial prediction of potential groundwater. International Journal of Digital Earth, 1-22. https://doi.org/10.1080/17538947.2020.1718785. Avand, M.; Moradi, H.; and Ramazanzadeh lasboyee, M. [2020B]. Using machine learning models, remote sensing, and GIS to investigate

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the effects of changing climates and land sses on flood probability. Journal of Hydrology. doi: https://doi.org/10.1016/j.jhydrol.2020.125663. Bhatt, C.M.; Rao, G.S.; Farooq, M.; Manjusree, P.; Shukla, A.; Sharma, S.V.S.P.; Kulkarni, S.S.; Begum, A.; Bhanumurthy, V.; and Diwakar, P.G. [2016]. Satellite-based assessment of the catastrophic Jhelum floods of September 2014, Jammu and Kashmir, India. Geomatics, Natural Hazards and Risk, 8, 309-327. Chen, W.; Li, Y.; Xue, W.; Shahabi, H.; Li, S.; Hong, H.; Wang, X.; Bian, H.; Zhang, S.; and Pradhan, B. [2020]. Modeling flood susceptibility using data-driven approaches of naive Bayes tree, alternating decision tree, and random forest methods. Science of the Total Environment, 701, 134979. Chumann, G.; Bates, P.D.; Apel, H.; and Aronica, G.T. [2018]. Global flood hazard mapping, modeling, and forecasting: challenges and perspectives. Global Flood Hazard Applications in Modeling, Mapping, and Forecasting, 239-244. Costache, R. and Tien, D. [2019]. Science of the total environment spatial prediction of flood potential using new ensembles of bivariate statistics and artificial intelligence: a case study at the Putna River catchment of Romania. Science of the Total Environment, 691, 10981118. https://doi.org/10.1016/j.scitotenv.2019.07.197. Danee, J.C.S. and Helen, S.M. [2015]. Assessment of surface runoff from sub basin of Kodayar using NRCS CN model with GIS. Indian Journal of Science and Technology, 8(13):60403-11. Dobrinić, D.; Medak, D.; and Gašparović, M. [2020]. Integration of multitemporal Sentinel-1 and Sentinel-2 imagery for land-cover classification using machine learning methods. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLIII-B1, 91-98. https://doi.org/ 10.5194/isprs-archives-XLIII-B1-2020-91. Friedl, M.A. and Brodley, C.E. [1997]. Decision tree classification of land cover from remotely sensed data. Remote Sensing of the Environment, 61, 399-409. Ghorbanian, A.; Kakooei, M.; Amani, M.; Mahdavi, S.; Mohammadzadeh, A.; and Hasanlou, M. [2020]. Improved land cover map of Iran using Sentinel imagery within Google Earth Engine and a novel automatic workflow for

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land cover classification using migrated training samples. ISPRS Journal of Photogrammetry and Remote Sensing, 9.167. https://doi.org/10.1016/j.isprsjprs.2020.07.013. Giustarini, L.; Chini, M.; Hostache, R.; Pappenberger, F.; and Matgen, P. [2015]. Flood hazard mapping combining hydrodynamic modeling and multi annual remote sensing data. Remote Sensing, 7, 14200-14226. Iqbal, M.S.; Dahri, Z.H.; and Querner, E.P. [2018]. The impact of climate change on flood frequency and intensity in the Kabul River basin. Geosciences, 8, 114. Khosravi, K.; Pham, B.T.; Chapi, K.; Shirzadi, A.; Shahabi, H.; Revhaug, I.; Prakash, I.; and Bui, D.T. [2018]. A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran. Science of the Total Environment, 627, 744-755. Li, Y. and Cheng, B. [2009]. An improved k-nearest neighbor algorithm and its application to high resolution remote sensing image classification. Proceedings: 17th International Conference on Geoinformatics, Fairfax, VA, USA, pp. 1-4. Luo, X.; Tong, X.; and Pan, H. [2021]. Integrating multiresolution and multitemporal Sentinel-2 imagery for land-cover mapping in the Xiongan New Area. IEEE Transactions on Geoscience and Remote Sensing, Vol. 59, No. 2, pp. 10291040. doi: 10.1109/TGRS.2020.2999558. Pham, B.T.; Le, L.M.; Le, T.-T.; Bui, K.-T.T.; Le, V.M.; Ly, H.-B.; and Prakash, I. [2020]. Development of advanced artificial intelligence models for daily rainfall prediction. Atmospheric Research, 237, 104845. Rahmati, O.; Pourghasemi, H.R.; and Zeinivand, H. [2016]. Flood susceptibility mapping using 663 frequency ratio and weights-of-evidence models in the Golastan Province, Iran. Geocarto International 664, 31, 42-70. https://doi.org/10.1 080/10106049.2015.1041559. Spasenovic1, K. and Carrion, D. [2019]. Quality check of crisis maps produced over five years by Copernicus EMS. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-2/ W13, ISPRS Geospatial Week, Enschede, The Netherlands. Taillardat, M.; Fougères, A.-L.; Naveau, P.;

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and Mestre, O. [2017]. Forest-based methods and ensemble model output statistics for rainfall ensemble forecasting. arXiv Preprint, arXiv1711.10937. Ward, P. J.; Jongman, B.; Weiland, F.S.; Bouwman, A.; vanBeek, R.; Bierkens, M.F.; Ligtvoet, W.; and Winsemius, H.C. [2013]. Assessing flood risk at the global scale: Model setup, results, and sensitivity. Environmental Research Letters, 8, 044019. Zhang, P.; Lu, J.; Feng, L.; Chen, X.; Zhang, L.; Xiao, X.; and Liu, H. [2015]. Hydrodynamic and inundation modeling of China’s largest freshwater lake aided by remote sensing data. Remote Sensing, 7, 4858-4879.

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WECs in AQWA Ghaneei and Mahmoudi simulate the dynamic behaviour of Pelamis in AQWA software. Who should read this paper?

Hana Ghaneei

This paper aims to bring a better understanding of Pelamis wave energy converter (WEC) operation for those who want to make geometric changes in Pelamis and re-examine its parametric under various marine conditions. Scholars who study hydrodynamic simulations of Pelamis or a horizontal semi-immersed cylinder using numerical methods such as finite volume, finite element, and smooth-particle hydrodynamics will be interested in this paper.

Why is it important?

In designing WECs, an accurate prediction of complex wave-structure interactions is a crucial consideration because they should operate optimally under different wave conditions. It is obvious that the experimental offshore studies are costly and timeconsuming processes, and theoretical methods are based on approximations which are so restrictive they limit the simulation accuracy of WECs. In contrast, computational fluid dynamics methods can be appropriate methods. In this study, which is among the first attempts to use a boundary element – that is, a numerical computational method – Pelamis was simulated in different marine conditions to assess its optimal operation.

Mohammadreza Mahmoudi

Marine energy resources are most predictable among all renewable energies. This characteristic makes it valuable to energy markets. Hence, investment in marine energy converter technologies has considerably increased. The Pelamis was selected because, compared to other WECs, it has several advantages such as high stability and adaption to harsh environments.

About the authors

Hana Ghaneei is a master’s student in industrial engineering in Northern Illinois University, U.S. She holds a master’s in civil engineering, offshore structures from Science and Research branch of Azad University, Tehran, Iran. Her research interests include renewable energy, wave energy converters, and optimization. Mohammadreza Mahmoudi is a PhD candidate at Northern Illinois University. His research interests include financial economics, computational economics, applied econometrics, and optimization.

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SIMULATION, OPTIMIZATION, AND ECONOMIC ASSESSMENT OF PELAMIS WAVE ENERGY CONVERTER Hana Ghaneei1 and Mohammadreza Mahmoudi2 1 Department of Industrial and System Engineering, Northern Illinois University, Dekalb, U.S.; z1939548@students.niu.edu 2 Department of Economics, Northern Illinois University, Dekalb, U.S.; mmahmoudi@niu.edu ABSTRACT Wave energy and power is accessible on almost any body of water. One of the most widely known floating structures to generate renewable energy from the seas and the ocean is wave energy converter Pelamis. In this study, an attempt was made to simulate the dynamic behaviour of Pelamis P2 in the software AQWA under the influence of a nonlinear second-order Stokes wave. Pelamis P2 was simulated in different marine conditions including different water depths, wave heights, periods, and angles to assess its optimal operation. With the results in mind, it can be argued that with an increase in water depth, the intensity of the forces created in the joints decrease. This kind of converter shows better efficiency with lower wave heights, while with a rise in the wave periods, the absorbed energy amounts fall. In the modelling, the best collision angle for the waves is when the Pelamis is in the same direction with the waves. The dynamic behaviour of the converter under the effect of irregular waves was surveyed; it shows a better performance under irregular waves compared with regular waves.

KEYWORDS Pelamis; Wave energy converter; Boundary element; Hydrodynamic analysis; Wave energy; AQWA

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INTRODUCTION The Earth’s average surface temperature has increased about 1.18°C since the late 19th century. The main causes of this change are rise of carbon dioxide (CO2) levels in the atmosphere and other human activities [Gaffney and Steffen, 2017]. Based on NASA’s Global Climate Change website, CO2 is the most effective gas at trapping heat (greenhouse effect) and the largest source of it is burning fossil fuels. Atmospheric concentrations of CO2 have been increased by human activity more than 48% in comparison with pre-industrial levels. This is more than what happened naturally over a 20,000-year period (from the Last Glacial Maximum to 1850, from 185 ppm to 280 ppm). These harmful and longstanding effects of fossil fuel on the Earth indicate the importance of the development of a number of alternative sources of energy that are renewable and non-polluting. Renewable energy sources include biomass, hydropower, geothermal, wind, wave, and solar energy, whose sources are naturally replenishing. Based on data provided by the U.S. Energy Information Administration, renewable energy accounted for about 12% of total primary energy consumption in the United States in 2020. It also emphasized that renewable energy can decrease energy imports and reduce fossil fuel use. Therefore, it plays an important role in U.S. energy security and in reducing greenhouse gas emissions. Due to the vital role of renewable energies like wave energy in the environment and economy of the U.S., government should invest more money to develop these new energy resources than before.

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Moreover, other countries like Canada and Iran, whose economies depend on oil revenues, should consider new sources of energy in order to reduce their budget dependency on oil price fluctuation and achieve sustainable economic development in the long-run [Mahmoudi and Ghaneei, 2022; Mahmoudi, 2021]. These new sources of energy play a pivotal role in the global economy more and more, especially since the COVID-19 pandemic [Mahmoudi, 2022]. It is worth bearing in mind that the first step to developing renewable energy is conducting feasibility studies. Since feasibility studies analyze a project financially and economically, they help us gain a comprehensive perspective. There are a limited number of feasibility studies in the case of United States that provide an assessment of renewable energies. Therefore, there is an obvious need for a well-designed feasibility study. The next major steps are simulation and optimization of energy converters. Wave energy has long been considered as one of the most promising renewable energy sources and wave energy converters are devices to catch this kind of energy. In the design of wave energy converters (WEC), an accurate prediction of complex wave-structure interactions is a crucial consideration because they should operate optimally under different wave conditions. It is obvious that the experimental offshore studies are costly and time consuming processes, and theoretical methods are based on approximations which are so restrictive that they limit the simulation accuracy of WECs. Wave diffraction and radiation effects are taken into account in theoretical methods while viscous effects and nonlinear effects

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are neglected. There is general agreement that computational fluid dynamics (CFD) methods – which not only consider all nonlinear wave diffraction, radiation, and viscous effects but are also qualified in simulation problems which are difficult or impossible to carry out in experimental studies – can be a suitable method for evaluating nonlinear wave force on a body. The Pelamis WEC is a floating offshore device composed of multiple cylindrical sections linked by hinged joints that converts ocean wave energy into electrical energy. Compared with other WECs, the Pelamis has several advantages such as high stability and adaption to harsh environments. In addition to efficiently generating electricity from offshore waves, the Pelamis WEC is environmentally friendly. Pelamis was discovered to have notably lower environmental impact compared to conventional fossil-fuelled power generation [Thomson et al., 2019]. Therefore, to achieve the main goal of this paper, which is a comprehensive understanding of the optimized function of Pelamis, it is crucial to analyze the Pelamis’s performance in a wide range of conditions through dynamic behaviour simulation. In the present study, using the numerical boundary element method, an attempt has been made to simulate the dynamic behaviour of Pelamis P2 (the P2 is the second-generation design of Pelamis WEC) in the software ANSYS AQWA under the influence of the nonlinear second-order Stokes wave and Joint North Sea Wave Project (JONSWAP) wave spectrum. Firstly, in order to verify the simulations and results, a fixed semi-immersed horizontal cylinder is simulated and the results

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have been compared with experimental results, the linear potential theory results, and finite volume results which were carried out using OpenFOAM by Loh et al. [2018]. Secondly, P2 Pelamis was simulated in different marine conditions including different water depths, wave heights, periods, and angles. In recent years, there have been many studies specifically with Pelamis. Dalton et al. [2010] conducted the feasibility study of Pelamis wave energy converter using wave energy data from different locations throughout the world. They created an Excel model which estimated the annual energy output of Pelamis for each location based on wave height and period and they reported financial costs based on input parameters. Westphalen et al. [2010] used four methods for the hydrodynamic simulation of the Pelamis wave energy converter. These methods were the Smoothed Particle Hydrodynamics, a Cartesian Cut Cell method, a Finite Volume method, and a control volume based Finite Element approach. Liu et al. [2011] computed wave forces and floating body motion by a 3D time-domain Green function method. Both infinite and finite water depths cases were investigated in their study. Ganesan and Sen [2015], using time-domain 3D Rankine panel method, studied steep nonlinear waves interacting with a fixed structure. Li and Lin [2012] studied a stationary floating structure under regular and irregular waves in different water depths, wave heights, and periods and calculated nonlinear wave-body interactions in a 2D numerical wave tank. Then they compared their results with experimental and theoretical results [Yemm et al., 2012] by reviewing the progress of Pelamis from its

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origin to its commercial deployment which emphasized that Pelamis is a unique wave energy converter device that can convert energy in reliable and affordable ways. Liu et al. [2016] tried to develop a boundary element numerical method for computing the diffraction and radiation of waves that collide with a horizontal long cylindrical structure. Bruinsma et al. [2018] used a fully nonlinear wave tank to simulate complicated wave-structure interactions of moored floating structures. The tank was based on the Navier-Stokes/6-degrees of freedom (DOF) solver and inter-DyMfoam provided by the open-source CFD-toolbox OpenFOAM. Loh et al. [2018] simulated a semi-immersed horizontal cylinder under different types of wave conditions using OpenFOAM which uses the finite volume method for solving the discretized Navier-Stokes equations. After computing horizontal and vertical forces, they compared those results with linear wave theory and experimental data which was carried out by Martin and Dixon [1983]. THEORETICAL ANALYSIS AQWA is a set of engineering tools used for examining the effects of wave, wind, and current on fixed offshore and floating structures, as well as other ocean structures like compliant towers, conventional tension leg platform, floating production storage and offloading vessels, semi-submersible structures, ships, WECs, and breakwaters. The following actions were taken to perform a hydrodynamic analysis in AQWA: 1. Create a hydrodynamic analysis system. 2. Attach geometry: there are no geometry

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creation tools in the AQWA application so the geometry must be attached to the hydrodynamic system. The geometry can be defined from either of the following sources: Workbench using DesignModeler or a CAD system supported by Workbench. a. General Modelling Requirements: it should be noted that there are some general modelling requirements that should be considered during geometric modelling. b. Configuring the Geometry: it is important that the correct water depth is specified, especially with shallow water conditions, since the seabed acts as a boundary condition to the diffraction analysis. 3. Define parts behaviour: each part will be assigned a structure number for the analysis; the parts can be included or excluded from the analysis. 4. Structure connection points: the connections object helps to create connections between structures or between structures and the environment; the available connections are Cables, Catenary Data, Connection Stiffness, Fenders, Joints. 5. Mesh: the mesh is automatically generated on the bodies of the model; its density is based on the defeaturing tolerance and maximum element size parameters. 6. Establish analysis settings which include Time Response Options, Start Time, Finish Time, Time Step, Number of Steps, etc. Governing Equations for Fluid Flow The flow was considered to be irrotational and the fluid was inviscid and incompressible; therefore, the velocity was defined by the

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gradient of the potential scalar field or velocity potential Φ :


Under these assumptions, the governing equation for fluid flow is the Laplace’s equation:

engineering applications and, for offshore designs, the fifth-order Stokes wave theory is more practical to use. Pelamis is used in deep and relatively deep waters (usually more than 50 m); therefore, the second-order Stokes wave theory has been used to simulate Pelamis WEC under wave action.


According to this theory, the wave surface elevation is obtained by the following equation:



where Φ is the total velocity potential, Φs is the scattering potential, and Φr is the radiation potential.

where k is the wave number and ω is the angular frequency which is a function of the wave length λ and the period T. They are determined by the following equations:

Based on superposition principle:

Wave Theory There are various wave theories available in AQWA which can be chosen to generate waves. Maintained as valid on the part of numerous theories of periodic water wave in Huntley [1977], the Stokes second-order wave theory is the most appropriate for the wave parameters adopted on the present research. Second-order Stokes Wave Theory Stokes in 1847, using the perturbation technique, presented a finite domain wave theory for solving the problem of wave boundary values, where all wave characteristics (velocity potential, velocity, surface profile, etc.) are formulated in terms of power series expressions at higher consecutive degrees of wave steepness (H/L). In this theory, it is assumed that the wave height is small when compared to the water depth. Second-order Stokes wave theory is more common in

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Where the horizontal and vertical components of the velocity of water particles represented by u and v, respectively, are calculated by the following equations:


(8) In the above equations, k = 2π λ and ω are the wave number and angular frequency of the

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wave, respectively, and λ is the wave length which are related by the following equation: (9) In the above equation, g is the gravitational acceleration. It should be noted that, if the wave period is known, the angular frequency can be calculated by ω = 2 π/T. Then, the wave number can be determined using the latter equation. To do this, the equation is rewritten as follows:

Pelamis WEC under the influence of irregular waves was also analyzed. For this purpose, the JONSWAP spectrum was used for modelling the water levels. This spectrum was obtained by Hasselmann et al. [1973] during JONSWAP. The equation of this spectrum, which is presented for a wave condition with finite fetch, was modified by Pierson and Moskowitz [1964] spectrum and equation as follows:



Now by replacing ω and assuming an initial value for kd (for example, 1) the equation will be solved and value of k will be obtained. This will be repeated for different values of kd until the value of k obtained from the left side of the equation is the same as the value of k assumed to the right of the equation. Gauge pressure (the difference between actual pressure and atmospheric pressure) at any point with the coordinate (x,y) at the time t, which is the sum of dynamic pressure induced by the wave and the hydrostatic pressure, is obtained by:


(13) (14)

(15) (16)

(11) In the above equation ρ is the density. JONSWAP Spectrum In this study, the dynamic behaviour of the

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To make this spectrum easier, Hasselmann et al. proposed values between 1.6 and 7 for the coefficient γ, but they recommend 3.3 for general use.

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Table 1: Parameters of the wave components for the first series of simulations.

Table 2: Parameters of the wave components for the first series of simulations.

VALIDATION AND RESULTS Verification of Simulation using AQWA Loh et al. [2018] predicted and analyzed the behaviour of a horizontal semi-immersed cylinder under various wave conditions using OpenFOAM software that solves NavierStokes equations by finite volume method. As they mentioned, it can be considered a simplified model of Pelamis’s segments. In their study, they simulated a fixed horizontal semi-submersible cylinder in a numerical tank that was subjected to waves in one side. Then they calculated vertical and horizontal forces applied to the cylinder using the pressure and shear stress data. They compared their result with the forces obtained from the potential theory and the experimental results of Martin and Dixon [1983]. In this paper, to validate the ANSYS AQWA simulation, those data and information were used. Two different series of test cases were performed to estimate the horizontal forces Fx and vertical forces Fy on the horizontal cylinder with a radius of 0.05 m

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and length of 0.295 m with its centre at the water level. In Table 1, the characteristics of the first series of simulations (1-6) subjected to incident waves with various amplitude and frequencies of 1 Hz and 1.539 wavelength are listed and in Table 2 the second series of simulation (7-11) subjected to incident wave with a constant wave amplitude of 0.02 m and various wavelengths and frequencies are listed. To simulate a semi-submersible horizontal cylinder in the AQWA software, a surface body was used which was fixed in a numerical tank with 20 m length and 0.6 depth. The density of water was 1,000 kg/ m3. Quadrilateral mesh was generated using specific tools in AQWA where the biggest size of element is 0.004 m and the total number of elements and nodes are 19,624 and 19,626, respectively. In the frequency analysis domain, the frequency range is from 0.1 to 2 Hz with steps of 0.05 Hz. In time analysis domain, the total simulation time is set to 50 starting from 0 and the time step was considered 0.01s.

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Figure 1: Comparison of the normalized forces in the numerical results, the potential theory, and experimental data of Martin and Dixon [1983].

In order to compare the obtained horizontal forces Fx and the vertical forces Fy with experimental and theoretical results, square root of mean square forces FRMS is calculated using the following equation:


where ρ is the density of water, g is the gravitational acceleration, a is the radius of the cylinder, A is the wave amplitude, and l is the length of the cylinder. (17) Figure 1 shows the results of solving the governing equation by using the boundary where f (t) is the horizontal or vertical forces as element method and AQWA software, a function of time. The numerical force range experimental results by Martin and Dixon is calculated based on the root mean square, [1983], theoretical estimates, and also with the following equation: results of finite volume method for the first set of simulations (1-6). There is a good (18) correspondence between the theoretical predictions, the experimental data, and both To reach the goal of comparability, the numerical methods (boundary element and dimensionless value of the numerical forces finite volume). The difference between the F'x,y are obtained by the following equation: theoretical estimates and the numerical results

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Figure 2: Comparison of the normalized forces F’x and F’y in the numerical simulations, the potential theory, and the experimental data of Martin and Dixon [1983] for simulations (7-11) based on ka.

for the normalized horizontal F’x and vertical forces F’y increases with the increasing of A/a, being difference smaller in the horizontal forces F’x than in the vertical forces F’y. Similar trends between experimental data and theoretical estimates can also be seen. Difference for large A/a values is most likely due to nonlinear effects because linear theory is valid only for small A/a values. Based on Martin and Dixon, linear potential theory provides a good estimate for their experimental horizontal forces F’x, but for vertical forces F’y it is less accurate when values of A/a are small. In AQWA, the numerical F’y and experimental F’y, when A/a=1, have a difference of about 14% and for A/a=0.8, 0.6, 0.4, 0.2 is slightly less than 10%. Numerical F’x and experimental F’x have a difference of about 3% when A/a=0.6 and for A/a= 0.4, 0.3, 0.2, it is about 1%. In

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OpenFOAM, the difference between numerical F’y and experimental F’y is about 4% when A/ a=0.6; and when A/a=0.4, 0.2, this difference is 1%. The difference between numerical F’x and experimental F’x is about 6% when A/a =0.4 and when A/a=0.3 it is about 5% and for A/a=0.2 it is 2%. Generally, the numerical results of the boundary element are in better agreement with the experimental data than theoretical estimates. But the results of the finite volume method are in better agreement with the theoretical estimates. In larger A/a values, the numerical results for both the horizontal and vertical forces and experimental results follow similar trends. In Figure 2, a comparison between the theoretical estimates, the experimental data, and the numerical results for the second series of simulations (7-11) are presented.

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The difference between theoretical results and experimental data by Martin and Dixon [1983] when A/a=0.4 in both horizontal and vertical forces increase with increasing ka. The results of AQWA and OpenFOAM for numerical horizontal force F’x are closer to theoretical estimates than experimental data. For vertical F’y force, the AQWA results are in better agreement with experimental results than theoretical ones, whereas OpenFOAM is closer to the theoretical results. The difference between the numerical results and the experimental data may be due to the difference between the methods of wave generation, absorption, and dumping that are used in numerical methods and physical wave tanks. According to Martin and Dixon [1983], reflection of waves in the experimental study was more than 5%, whereas in AQWA the waves are absorbed along the numerical tank boundaries completely. Numerical Simulation and Numerical Analysis Results Computational Space Characteristics For simulation in AQWA, a numerical tank with a length of 720 m (in y direction) and a width of 120 m (in x direction) and 50 m depth was used. The density of water is 1,025 kg/m3. The P2 Pelamis WEC is similar to an eel in a semi-submersible state and has five sections linked by four hinged joints. Each section is 34 m long and weighs 260,000 kg. Pelamis has a total weight of 1,300 tons [Yemm et al., 2012]. The mass of each section is defined and concentrated in its centre of gravity. Other important points in the simulation of

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the Pelamis is the definition of the moment of inertia with respect to the coordinate system and the water level for Pelamis. An auxiliary tool of ANSYS was used to calculate the depth of Pelamis under the water level and inertia moments, which provides these values based on geometry and structural weight in the form of a default weight. Figure 3 shows the overview of the Pelamis. For analyzing the effect of different marine conditions on the dynamic behaviour of Pelamis, a set of parameters affecting its behaviour is investigated. In the first case, regular waves are used for dynamic simulation and the parameters like wave height, period, water depth, and angle of incident wave were investigated. In the second case, irregular waves are modelled using the JONSWAP spectrum, the results in this case being compared with regular wave results. Sensitivity to Meshing In order to understand the effect of meshing on the numerical solution results, six meshing models, with various number of elements and fine and coarse mesh dimensions, under a wave with amplitude of 1 m and period of 8 s along the longitudinal direction of Pelamis were examined and the vertical forces applied to part 1, the vertical forces applied to joint 1, and the vertical displacement of part 1 in different models of meshing at different times (0 to 50 s) were calculated. Based on very low effect of meshing dimensions on the boundary element solution and the results in AQWA software, the meshing with 0.5×0.5 dimensions can be used to analyze the hydrodynamic behaviour

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Figure 3: Overview of the Pelamis simulation in AQWA software.

of Pelamis. The other factor affecting the numerical solution is the time step which is considered for analysis. This parameter in the software is determined by the amount of numerical error occurring at each time step of the solution (Time Step Error). However, in all cases, a time step of less than 0.01 s is selected and the numerical error in the time solution is less than 1e-10. Sensitivity to Water Depth Five models of Pelamis (D1 to D5) at different water depths – namely 40, 60, 80, 100, and 1,000 m – were simulated and subjected to a wave with the amplitude of 1 m and a period of 8 s in the longitudinal direction of the Pelamis (y direction) to find the effect of change in water depth. As mentioned previously, the Pelamis WEC is more practical in areas with more than 50 m of water depth; therefore, lower depths were not investigated. To analyze the simulations, the vertical forces

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applied to part 1, part 2, joint 1, and vertical displacement of part 1 and part 2 were used. In Table 3, the normalized vertical forces F’y affecting element 1 and joint 1 (connecting element 1 to element 2) at different water depths are reported. We can see that vertical forces acting on part 1 increase with increasing depth, while the vertical forces affecting joint 1 decrease with increasing water depth. Also, there is a sudden change in the numerical forces from D1 to D2 models; this jump from D1 to D2 is clear, while in other cases the changes are not as noticeable. A similar trend is observed in the force acting on joint 1, where the force from the models D1 to D2 abruptly reduces. Therefore, to investigate the cause of this phenomenon, the time series of vertical displacements of part 1 and part 2 in the models D1 and D2 have been normalized and compared. The difference of normalized vertical displacements of part 1 and part 2 are shown in Figure 4. The force

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Table 3: Comparing the results of the normalized vertical forces applied to part 1 and joint 1 at different water depths.

Figure 4: Comparison of the normalized vertical displacement difference for part 1 and part 2 at different water depths.

generated at the junction point is due to the relative displacement of the elements that are connected to it; therefore, according to information in Table 4 and Figure 5, the higher the difference in normalized vertical displacements of part 1 and part 2, the higher the generated force in joint 1, which is also supported by the given information; as it can be seen, the largest difference in normalized vertical displacements occurred at a water depth of 40 m. Therefore, the maximum force created at the joint 1 is in 40 m water depth and with increasing the depth to 60 m, the value of these displacements difference decreases

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suddenly but as the water depth increases the speed of this difference decreases. In Figure 6, the normalized vertical forces applied to part 1 at different water depths are compared. It can be seen that the forces increase with increasing water depth and the changes are more severe from D1 to D2, but these differences become lower from D3 model to D5. This difference is because waves with the period of 8 s in water depth of 40 m are in an intermediate zone and they have a wavelength of 98.7 m. With increasing to a water depth of 60 m,

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Figure 5: Comparison of the normalized vertical generated forces F’y at joint 1 in different water depths.

Figure 6: Comparison of the normalized vertical forces F’y applied to part 1 at different depths.

Table 4: Comparison of the results of normalized vertical displacements part 1 and part 2 for different water depth.

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Figure 7: Vertical forces time series for different water depths.

the wave enters the deep water zone and its wavelength becomes equal to 99.9 m and, based on the linear wave theory, increasing wavelength causes increasing wave energy (E = 0.125×ρ×g×H2×L) and this increases the force applied to the elements. The increasing in water depth will no longer have a significant effect on the applied forces to the members, since the wavelength in the deep water range will not change significantly. Figure 7 shows the time series of vertical forces applied to joint 1 at different water depths. In this diagram, the maximum generated force at joint 1 is in D1 model. In Pelamis, the conversion of mechanical energy to electrical energy is done by pumps, which are embedded in the joints; therefore, the greater the generated force in joints, then the more electricity will be produced. Therefore, the D1 model is the most optimal model for generating electricity in terms of the impact of the water depth parameter.

simulated and studied under waves with amplitudes of 1, 2, 3, and 4 m, period of 8 s in the longitudinal direction (in the y direction), and in a water depth of 60 m. Table 5 presents the normalized vertical forces F’y affecting element 1 and joint 1 by waves with different amplitudes. As the wave amplitude increases, the vertical forces F’y affecting part 1 also increase. The applied F’y forces to joint 1 also increase with increasing amplitude but, as it can be seen in Figure 8, the acceleration is smaller than the one of part 1. This means that, although the force applied to the joints increases and it increases the produced electricity, this generally indicates a lower efficiency of the device under larger waves. In addition, higher force is created on the bridle cable and a more resistant body is required for the Pelamis to resist under the wave. Therefore, in contrast to our expectations, although larger waves will increase the produced electricity, it does not necessarily mean they increase energy efficiency.

Sensitivity to the Wave Amplitude Four models (A1 to A4) of Pelamis were

Figure 9 shows the vertical forces time series acting on part 1 due to the waves

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Table 5: Comparison of the results of vertical generated forces at part 1 and joint 1 under different wave amplitudes.

Figure 8: Comparison of the vertical generated forces at part 1 and joint 1 under different wave amplitudes.

Figure 9: Time series of vertical forces acting on part 1 under waves with different amplitudes.

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with different amplitudes. The applied force to element 1 increases with increasing the amplitude wave. The most important point in this graph is the periodicity (period) of the time series of forces which, like the wave period in all models, is approximately 8 s with the exception of the beginning of the graph. This means that the repetition pattern of the forces is similar to the wave surface alignment pattern and the pattern of vertical acceleration of the wave, because, according to the theory of short amplitude waves, the highest vertical applied force by the wave will occur at the moment of maximum vertical acceleration of the wave. According to the amplified part of the graph, which shows time between 10 s to 20 s of simulation, time series in models A1 and A2 have positive max and negative max, but in time series of A3 and A4 models more crests occurred in the positive forces. It was noted previously that the velocity potential function of a problem, based on the superposition principle, is equal to the sum of the velocity potentials of the initial incoming wave, the created wave by the motion of body at six DOF, and the scattered wave due to the presence of a fixed structure. It is obvious that the smaller the amplitude of the wave, the smaller the wave due to its scattering; and the smaller the wave, the less oscillations in the structure in which it has interacted, and the created wave due to this oscillation will be smaller. Therefore, the reason of extra crests in forces time series of models A3 and A4 can be due to this point that amplitude of scattered wave and waves due to the oscillating of the structure increases with the increasing of the wave amplitude and their forces become more visible.

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Sensitivity to the Wave Period Five models (P1 to P5) of Pelamis were studied under the waves in the longitudinal direction (in the y direction) with amplitude of 2 m and periods of 6, 8, 10, 12, and 15 s for the water depth of 60 m. In Table 6, the numerical results of vertical forces with different periods applied to the element 1 and joint 1 are compared. In model P1 both forces applied to part 1 and joint 1 are maximum compared to the other models, and these forces decrease with increasing periods. In Figure 10 these forces are shown graphically. Based on this figure, the variation of forces which affects part 1 has changed from P2 model onwards and has decreased. A similar trend has occurred for the graph of forces affecting joint 1 in the P3 model and its variation has decreased. According to the finite amplitude wave theory equations for Stokes waves, the greater the wave period, the longer the wavelength and, consequently, it leads to increasing wave energy. In the P1 model, the wavelength is about 56.2 m and the wave power (wave energy per unit time P = nE/T) is 23 kW, while in the P5 model, the wavelength is 351.3 m and the wave power is 69 kW. However, the information presented in this section shows the opposite trend. This means that, despite higher wave energy at greater periods, the Pelamis behaves in a way that creates less forces at its joint points and, consequently, converts less energy. The fact that P2 Pelamis absorbs less energy in longer periods may be due to its length which has not being designed for long waves (as a result of which is not mentioned in this study: the longer the Pelamis’s interconnecting segment’s length, the better it performs in higher waves). The definition of an optimal model will correspond to the point of the graph with least

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Table 6: Comparison of the results of the vertical forces Fy applied on part 1 and joint 1 under waves with different periods.

Figure 10: Comparison of the vertical forces applied to part 1 and joint 1 under the effects of waves with different periods.

distance between the force applied to the element and the joint attached to it. According to the diagram, the P2 model, in which the wave period is 8 s, has such a feature and can be considered as the optimal Pelamis device among the simulated models. In Figure 11, the time series of the vertical forces acting on part 1 under the waves with different periods are shown. In this diagram, except for the transient portion at its beginning, the rest of the periodic time series graph of each force is approximately equal to the

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corresponding wave period. The important point in this chart is the maximum force applied to the P1 model, which is significantly higher than other models. This has a major impact on the design of the Pelamis’s structure and its cables to resist such forces. Another issue is the presence of a secondary crest in the P1 model diagram. These smaller crests may be due to generated waves by the oscillations caused by large wave forces (waves with periods of 6 s in vertical direction that affects element 1 of Pelamis). This effect has not been noticeable in other models.

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Figure 11: Time series of the vertical forces acting on part 1 under waves with different periods.

Table 7: Comparison of the results of the vertical forces Fy applied to part 1 and joint 1.

Sensitivity to the Wave Impact Angle Five models of Pelamis (Dir 1 to Dir 5) are subjected to waves with angles of 0, 30, 45, 60, and 90° to the positive direction of the y-axis with amplitude of 2 m and period of 8 s at a water depth of 60 m. The time-domain solution forces in AQWA are in time series. Table 7 compares the results of the vertical forces applied to part 1 and joint 1 under the effects of waves with different angles of impact. It can be seen that the more sideways a wave (relative to the longitudinal direction) hits the wave converter, the greater the force is applied to element 1. Since the contact surface of Pelamis along the x-axis is much

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greater than the contact surface along the y-axis, it is obvious that the closer the wave to the x-axis, the greater the applied force to the surface of the energy converter. The information in Table 7 is plotted in Figure 12. In joint 1, the opposite of part 1, with increasing angle of wave’s impact, less force is generated. According to the diagram, this force is almost zero in the Dir 5 model, whereas the maximum force acting on part 1 occurs in this model. This indicates the least energy absorbing function in this case. Based on the above, the best performance is in Dir 1 simulation; the force applied to the elements is minimal while the force generated at the junctions is maximized.

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Figure 12: Comparison of vertical forces applied to part 1 and joint 1 under the influence of waves with different angles of impact.

Figure 13: Pelamis vertical displacement time series under impact wave along the x-axis (90o).

In Figure 13, at the beginning of the diagram, the displacements of all parts of Pelamis are aligned with each other and there will be no force at the joints if there are no relative displacements against each other. Therefore, in Dir 5 model the force acting on the joints is minimized. Over time, the vertical movement phase of the different

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parts of the Pelamis are slightly different, but the movement phase of the two successive parts, for example part 1 and part 2, against each other is low; that is why the generated force in their joint which connect those parts together reduces. According to what was mentioned, the best performance of the Pelamis WEC occurs in the case where the

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Figure 14: Comparison of the vertical forces on part 1, part 2, and joint 1 under regular and irregular waves.

Figure 15: Time series of vertical applied forces to joint 1 under regular and irregular waves.

wave hits in the longitudinal direction of the converter, and the greater this angle, the relative displacements of the segments of the Pelamis will be reduced; therefore, the efficiency of converter will reduce.

Pelamis (zero degrees relative to the positive direction of the y-axis). The total simulation time was 100 s in order to better observe the irregular effects of waves.

Pelamis Behaviour under Irregular Waves In this section, the Pelamis under the JONSWAP wave spectrum with the wave height of 4 m and period of 8 s at 60 m water depth is simulated. The Gamma in the JONSWAP spectrum was considered equal to 3.3 and the direction of the wave impact is considered along the longitudinal direction of

Figure 14 compares the vertical forces Fy on part 1, part 2, and joint 1 under a regular wave with amplitude of 2 m and a period of 8 s at water depth of 60 m and irregular waves which are modelled by the JONSWAP spectrum. The value of applied force to members 1 and 2 reduce significantly with irregular waves. Part 1’s force under regular wave was about 240 kN which reduces by 43% to 138 kN under

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irregular waves. A similar trend takes place for part 2, where the generated force under regular waves was equal to 205 kN but reduces to 52% and to 98 kN under irregular waves. But this decrease in force due to irregular waves compared to regular waves is only about 8% in joint 1, which indicates a better performance of Pelamis under irregular waves with the JONSWAP spectrum. In Figure 15, the applied vertical forces to joint 1 are compared in a time series under regular and irregular waves’ effects. The regular wave simulation is 50 s long while the irregular wave simulation is set to 100 s, so the blue chart is cut off at 50 s. It can be seen, at the beginning of the simulation, the regular wave forces are greater than the irregular wave forces while, after a certain period of time, the vertical forces increase due to irregular waves. Unlike the irregular wave, the regular wave diagram reaches steady state after approximately 10 seconds and the pattern of diagram changes is repeated afterwards. This is also due to the uniformity of the waves for regular wave. CONCLUSION The hydrodynamic conditions of Pelamis’s segments and joints under different marine conditions include five models in different water depths, four models with different wave heights, and five models with different periods. Also, five models with different wave impact angles are simulated. Finally, a comparison between the force from regular waves modelled with second-order Stokes wave theory and the irregular waves modelled with the JONSWAP spectrum was made. The results of all these simulations can be summarized as follows:

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• •

In deep water conditions (d/L>0.5), increasing or decreasing water depth when other influential parameters are constant will not affect the hydrodynamic performance of P2 Pelamis because the wavelength does not change. Outside the deep water range (d/L≤0.5), increase in the water depth due to the increase in the wavelength increases the force applied to the energy converter segments, while this increase in depth decreases the relative displacement of segments and decreases the force applied at joints. As the height of the wave increases, when the other factors are constant, the forces applied on Pelamis’s segments and joints increase. It should be noted that the forces applied to the segments increase more rapidly than the generated forces in the joints. Based on what was mentioned above, increasing the amplitude of waves increases absorbed energy by Pelamis but reduces its operating efficiency. Increasing the period of the wave reduces the forces applied to segments and joints of the WEC. In terms of performance of the device, the optimal period is 8 s, since the difference between the forces applied to the Pelamis’s segments and joints is minimum. The closer the wave impact angle of Pelamis to its longitudinal direction, more force is created at its joints and the device performs better. On the other hand, the closer this angle is to the perpendicular angle to the longitudinal axis of Pelamis, the greater the applied force to the segments and the efficiency of the converter approaches to zero.

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The force applied to the segments of P2 Pelamis under the JONSWAP irregular wave spectrum is less than the force generated at its joints; however, the forces applied to the segments are always greater than the forces generated in the joints under regular waves. This indicates better performance of the P2 Pelamis under irregular waves.

REFERENCES Bruinsma, N.; Paulsen, B.T.; and Jacobsen, N.G. [2018]. Validation and application of a fully nonlinear numerical wave tank for simulating floating offshore wind turbines. Ocean Engineering, 147:647-658. Dalton, G.J.; Alcorn, R.; and Lewis, T. [2010]. Case study feasibility analysis of the Pelamis wave energy convertor in Ireland, Portugal and North America. Renewable Energy, 35 (2):443-455. Gaffney, O. and Steffen, W. [ 2017]. The anthropocene equation. The Anthropocene Review, 4 (1):53-61. Ganesan, T.S. and Sen, D. [2015]. Time-domain simulation of large-amplitude wave–structure interactions by a 3D numerical tank approach. Journal of Ocean Engineering and Marine Energy, 1 (3):299-324. Hasselmann, K.F.; Barnett, T.P.; Bouws, E.; Carlson, H.; Cartwright, D.E.; Eake, K.; Euring, J.A.; Gicnapp, A.; Hasselmann, D.E.; and Kruseman, P. [1973]. Measurements of wind-wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP). Ergaenzungsheft zur Deutschen Hydrographischen Zeitschrift, Reihe A. Huntley, D.A. [1977]. LE MÉHAUTÉ, B. An introduction to hydrodynamics and water waves. Springer‐Verlag, New York, viii+ 323 p. Wiley Online Library. Li, Y. and Lin, M. [2012]. Regular and irregular wave impacts on floating body. Ocean Engineering, 42:93-101. Liu, C.F.; Teng, B.; Gou, Y.; and Sun, L. [2011]. A 3D time-domain method for predicting the wave-induced forces and motions of a floating

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body. Ocean Engineering, 38 (17-18):2142-2150. Liu, Y.; Gou, Y.; Teng, B.; and Yoshida, S. [2016]. An extremely efficient boundary element method for wave interaction with long cylindrical structures based on free-surface Green’s function. Computation, 4 (3):36. Loh, T.T.; Pizer, D.; Simmonds, D.; Kyte, A.; and Greaves, D. [2018]. Simulation and analysis of wave-structure interactions for a semi-immersed horizontal cylinder. Ocean Engineering, 147:676-689. Mahmoudi, M. [2021]. Identifying the main factors of Iran’s economic growth using growth accounting framework. European Journal of Business and Management Research, 6 (5):239-245. Mahmoudi, M. [2022]. COVID lessons: was there any way to reduce the negative effect of COVID-19 on the United States economy? arXiv preprint arXiv:2201.00274. Mahmoudi, M. and Ghaneei, H. [2022]. Detection of structural regimes and analyzing the impact of crude oil market on Canadian stock market: Markov Regime-Switching Approach. Studies in Economics and Finance. Martin, P.A. and Dixon, A.G. [1983]. The scattering of regular surface waves by a fixed, half- immersed, circular cylinder. Applied Ocean Research, 5 (1):13-23. Pierson Jr., W.J. and Moskowitz, L. [1964]. A proposed spectral form for fully developed wind seas based on the similarity theory of SA Kitaigorodskii. Journal of Geophysical Research, 69 (24):5181-5190. Thomson, R.C.; Chick, J.P.; and Harrison, G.P. [2019]. An LCA of the Pelamis wave energy converter. International Journal of Life Cycle Assessment, 24 (1):51-63. Westphalen, J.; Greaves, D.M.; Hunt-Raby, A.; Williams, C.J.K.; Taylor, P.H.; Hu, Z.Z.; Causon, D.M.; Mingham, C.G.; Stansby, P.K.; and Rogers, B.D. [2010]. Numerical simulation of wave energy converters using Eulerian and Lagrangian CFD methods. Twentieth International Offshore and Polar Engineering Conference. Yemm, R.; Pizer, D.; Retzler, C.; and Henderson, R. [2012]. Pelamis: experience from concept to connection. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 370 (1959):365-380.

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Under Pressure: Getting Carbon Dioxide Out of the Atmosphere and Under the Seafloor by Amanda Lefton and Scott Mabry

Meeting U.S. and global climate targets requires immediate efforts to curtail greenhouse gas emissions. The United States has set an ambitious target to achieve net zero emissions by 2050. Carbon sequestration – the practice of storing captured carbon dioxide in sub-surface geological formations indefinitely – is one tool we can use to help meet this target while the transition to renewable energy sources continues. In November 2021, the U.S. Congress passed, and President Biden signed, the Infrastructure Investment and Jobs Act, also known as the Bipartisan Infrastructure Law. This law is a historic investment in the nation’s infrastructure and competitiveness that will help fight climate change, power homes and businesses across the country, and create good-paying jobs. The law authorizes the Department of the Interior to grant a lease, easement, or right-of-way for activities that “provide for, support, or are directly related to the injection of a carbon dioxide stream into sub-seabed geologic formations for the purpose of long-term carbon sequestration” in federal waters off the U.S. coast. The Department’s Bureau of Ocean Energy Management (BOEM) is partnering with the Bureau of Safety and Environmental Enforcement (BSEE) to draft regulations that ensure such activities are done responsibly and protect the human, marine, and coastal environment. According to the Intergovernmental Panel on Climate Change, limiting global warming to 1.5°C will require carbon dioxide removal and sequestration in addition to greenhouse gas emissions reductions. Other countries, such as Norway, have been exploring carbon sequestration since the 1990s, with one offshore Norwegian project, Sleipner, successfully storing 19 million tonnes of carbon dioxide between 1996 and 2020. In addition to moving toward a decarbonized economy, other factors driving the increase in carbon capture and sequestration (CCS) projects around the world include new technological methods for carbon capture, research, increasing the types of underground spaces used for storage, and government financial incentives providing additional certainty for new projects. According to the Global CCS Institute, the United

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States has more CCS projects than any other country today, but these projects are onshore. However, the Gulf of Mexico is particularly well suited for future offshore carbon sequestration projects in the United States. For example, many potential offshore sequestration sites in the Gulf are near heavily populated coastal areas with carbon-intensive onshore activity, which decreases the costs to transport carbon dioxide to an injection platform. Relevant infrastructure, such as platforms, may also be available for repurposing to a sequestration mission. Further, the Gulf has historically been a region of high offshore activity with a long legacy of sub-seabed data and scientific information to feed into decision-making. The Gulf of Mexico’s subseabed geology also allows for ample space to sequester carbon dioxide safely and indefinitely. As the United States considers its first offshore CCS projects, it can look to the mature regulatory, financial, and policy frameworks of other countries, such as Norway and the Netherlands, to aid in developing policies for U.S. waters. There are several important considerations in developing regulations for offshore carbon sequestration, including site selection criteria; early risk assessment; well qualification and offset infrastructure; components of an offshore leasing program; project approval processes; methods for addressing financial assurance and liability concerns; emergency response and mitigation; socioeconomic issues and impacts, such as environmental justice; and environmental issues, including long-term geological and ecological monitoring requirements and ensuring continuing risk assessments post injection.

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The U.S. Department of the Interior protects and manages the Nation’s natural resources and cultural heritage; provides scientific and other information about those resources; and honours its trust responsibilities or special commitments to American Indians, Alaska Natives, and affiliated Island Communities. The Bureau of Ocean Energy Management’s mission is to manage development of U.S. Outer Continental Shelf energy and mineral resources in an environmentally and economically responsible way. The Bureau of Safety and Environmental Enforcement’s mission is to promote safety, protect the environment, and conserve resources offshore through vigorous regulatory oversight and enforcement.

BOEM and BSEE are currently applying their extensive geological, environmental, social science, and offshore energy regulatory expertise to develop a transparent and robust regulatory regime that will allow for offshore carbon sequestration to make a significant impact as an ocean-based climate solution. While the energy transition to less carbonintensive and renewable sources continues to gain momentum, carbon dioxide removal methods such as CCS offer complementary avenues to reduce greenhouse gas emissions into the atmosphere and slow the pace of climate change that is already impacting communities in the U.S. and around the world. BOEM and BSEE are working diligently to play their parts in reaching U.S. climate goals by developing clear, effective, and environmentally robust regulations for offshore carbon sequestration. Amanda Lefton is the director of the U.S. Bureau of Ocean Energy Management. Scott Mabry is the acting director of the U.S. Bureau of Safety and Environmental Enforcement.

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Heavy Metals and Crab Researchers Burke and Kerton evaluate the levels of trace metal contaminants in crab processing byproducts and their transfer to selected crab bio-product. Who should read this paper?

Heather Burke

Anyone interested in developing high value marine based bio-extracts from underutilized marine resources, such as crab processing discards, will gain a better understanding of some of the environmental factors affecting heavy metal contaminants and their removal from and/or accumulation in these extracts.

Why is it important?

Evaluating the transfer of trace metal contaminants from crab processing byproducts during the extraction of higher value bio-products will be key to developing safe marketable crab bio-products for natural health products and biomedical applications. To date, such studies have been limited and this has delayed Food and Drug Administration approval, for example, of chitosan as a drug delivery agent.

Dr. Fran Kerton

Currently about 30% of crab resource in Newfoundland and Labrador is discarded as waste yet this discarded material contains valuable components that could be recovered and potentially used as natural health or biopharma products. The results will help the ocean community find methods to fully utilize this raw material which in turn may create new opportunities in coastal communities. Understanding heavy metal contaminants and how they are removed or accumulated is not well studied in crab-based bio-products and more research is necessary to develop technologies that produce safe, marketable natural health products and biopharma products. This technology is essential for future commercialization success.

About the authors

Heather Burke is the director of the Centre for Aquaculture and Seafood Development at the Fisheries and Marine Institute. She has broad experience in applied research spanning more than two decades with major emphasis on marine bioprocessing and the development of value chains of unutilized marine biomass materials. Most recently, she has worked on several international crustacean bio-extraction and bio-conversion projects for nutraceutical, biomedical, and bioscience applications. She will complete her PhD (environmental science) at Memorial University of Newfoundland in the spring of 2022. Her thesis research focuses on using simple green technologies and an ocean based biorefinery approach for the extraction of higher value bio-products from snow crab processing discards. Dr. Fran Kerton is a professor in the Department of Chemistry at Memorial University of Newfoundland. She is a member of the Canadian Society for Chemistry, the American Chemical Society, and a Fellow of the Royal Society of Chemistry (U.K.). She obtained her PhD in chemistry at the University of Sussex and was a postdoctoral research associate at the University of British Columbia. In addition to authoring over 70 journal articles, she has contributed several book chapters (Introduction to Chemicals from Biomass and Sustainable Chemical Processes). Her current research group is focused on developing environmentally benign transformations of bio-sourced molecules and materials, and “green” polymers. She received the Canadian Green Chemistry and Engineering Award in 2019.

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HEAVY METALS IN SNOW CRAB (CHIONOECETES OPILIO ) BIO-PRODUCTS Heather Burke1 and Francesca Kerton2 1 Centre for Aquaculture and Seafood Development, Fisheries and Marine Institute, Memorial University of Newfoundland, St. John’s, N.L., Canada; heather.burke@mi.mun.ca 2 Department of Chemistry, Memorial University of Newfoundland, St. John’s, N.L., Canada; kerton@mun.ca ABSTRACT Several potential snow crab (Chionoecetes opilio) bio-products have been identified having potential applications as feed ingredients (for terrestrial and aquatic animals), natural health products (e.g., nutraceuticals, dietary supplements), bio-medical and pharmaceutical products (e.g., drug delivery systems, wound healing products), and in cosmetics (e.g., shampoo, hair care, creams, lotions). Yet studies regarding the purity and safety of such bio-products remain limited. Due to growing concerns over heavy metal contaminants in the environment (air, soil, drinking water, food), their associated adverse health effects, and their tendency to bioaccumulate in marine crustaceans, we evaluated the levels of trace metal contaminants in crab processing byproducts and their transfer to selected crab bio-products: crab protein hydrolysate and crab chitin. Safety and toxicity concerns of residual heavy metals present in these snow crab processing bio-products are also discussed.

KEYWORDS Snow crab (Chionoecetes opilio); Byproducts; Bio-products; Crab meal; Chitin; Chitosan; Toxicity; Heavy metals; Protein hydrolysate; Aluminum; Arsenic

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Figure 1: Value chain of N.L. snow crab processing byproducts and bio-products based on an average annual plant supply of 30,000 tonnes of crab [Burke, 2021].

INTRODUCTION Since the collapse of the Northern cod fishery in 1992, Atlantic snow crab (Chionoecetes opilio) has been the most valuable seafood product harvested in Newfoundland and Labrador (N.L.), Canada. In 2019, snow crab landings were 26,894 tonnes of which 16,658 tonnes were exported to the United States (77%), China (8%), Indonesia (6%), and Vietnam (4%), at a value of $415 million [FLR, 2019]. Crab processing plants in N.L. have historically discarded on average about 30% of their total raw material supply in the form of waste and byproducts. In 2019 this amounted to an estimated 8,100 tonnes. Over the last five years, the average annual plant supply of snow crab in N.L. has been approximately 30,000 tonnes. In N.L., snow crab is primarily processed as individually quick frozen cooked sections which generates waste comprised of carapace (cephalothorax shells), viscera and hepatopancreas, hemolymph [Beaulieu et al.,

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2009], residual meat, and gills. According to personal communications with industry stakeholders, this material is currently not being utilized commercially but could potentially be recovered from processing plant butchering stations as a byproduct and converted into intermediate bio-products (chitin, crab meal, proteins, lipids) or transformed into higher value bio-products (chitosan, peptides, omega-3, astaxanthin). Potential crab processing byproducts and bio-products that could be produced in N.L. based on an average annual plant supply of 30,000 tonnes are depicted in the crab bioproduct value chain in Figure 1. Many of the identified snow crab bio-products (Figure 1) have potential applications as feed ingredients (for terrestrial and aquatic animals), natural health products (e.g., nutraceuticals, dietary supplements), bio-medical and pharmaceutical products (e.g., drug delivery systems, wound healing products), and in cosmetics (e.g., shampoo, hair care, creams, lotions). Therefore, the purity and safety of the

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Table 1: Main heavy metals of concern for seafood and Health Canada maximum allowable levels [Health Canada, 2020].

Table 2: Acceptable limits for elemental impurities in natural health products [Health Canada, 2015].

Table 3: Industry standard for heavy metal levels in medical grade chitosan [ASTM, 2019; USPC, 2020].

bio-products developed will be critical for these applications. Due to growing concerns over heavy metal contaminants in the environment (air, soil, drinking water, food), their associated adverse health effects, and their tendency to bioaccumulate in marine crustaceans [Cubadda et al., 2017; Jaishankar et al., 2014; Gupta et al., 2013; Hardisson et al., 2017; Alabi and Adeoluwa, 2020], we evaluated the levels of trace metal contaminants in crab processing byproducts (i.e., crab meal) and their transfer to selected crab bio-products: crab protein hydrolysate and crab chitin. According to Health Canada, heavy metals including arsenic (As), cadmium, lead, and

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mercury are considered toxic contaminants in seafood and natural health products (NHPs) if present in certain levels. The main heavy metals of concern (Table 1) for edible seafood and for which Health Canada has established maximum allowable levels include arsenic (3.5 ppm), lead (0.5 ppm), and mercury (0.5-1.0 ppm). The acceptable limits for elemental impurities in natural health products in Canada are presented in Table 2. For medical grade chitosan, the heavy metals of concern for which industry [ASTM, 2019; USPC, 2020] has established maximum levels (Table 3) include arsenic (<0.5ppm), lead (<0.5ppm), mercury (<0.2 ppm), chromium

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(<1.0 ppm), nickel (<1.0 ppm), cadmium (<0.2 ppm), and iron (<10 ppm). The industry standard for medical grade chitosan also recommends that the total heavy metal content should not exceed < 40 ppm [ASTM, 2019; USPC, 2020]. While heavy metals are known to have many adverse health effects (e.g., carcinogenic, occupational asthma, skin lesions, neurotoxic), exposure to heavy metals has been increasing in many parts of the world [Cubadda et al., 2017; Jaishankar et al., 2014]. Metals are naturally present in the environment including soil, water, and air, and, therefore, end up in food [Jaishankar et al., 2014; Gupta et al., 2013; Hardisson et al., 2017; Alabi and Adeoluwa, 2020]. Heavy metals tend to accumulate in the organs and tissues of crustaceans such as crabs and prawns [Sayyad et al., 2020; Olowu et al., 2010; Kim and Yoon, 2011]. Organs and tissues account for 80% of the crab byproducts available from N.L. crab processing plants (Figure 1). Therefore, understanding the levels of heavy metals in snow crab byproducts and how they are transferred throughout the crab bio-product value chain will be key to developing safe marketable crab bio-products for natural health product and biomedical/ pharmaceutical applications. To date, few studies have been conducted that evaluate the purity or the toxicity of chitinchitosan polymers, and those studies have focused on molecular weight and degree of deacetylation [Marques et al., 2020; Kean and Thanou, 2010; Matica et al., 2017; Guangyuan et al., 2009]. Therefore, despite the many published studies on chitosan drug delivery products, they are still not approved by the

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Food and Drug Administration (FDA) as they require studies demonstrating they are safe for human use [Marques et al., 2020; Kean and Thanou, 2010; Matica et al., 2017]. To the authors’ knowledge, there have been no studies on the toxicity of chitin/chitosan-based products associated with protein, metals, or other trace contaminants that may be present. PURPOSE AND SCOPE The purpose of this study was to determine if heavy metals present in snow crab processing byproducts collected from a local processing plant were effectively removed during extraction of two intermediate bio-products – protein hydrolysate and chitin. Safety and toxicity concerns of residual heavy metals present in these snow crab processing bioproducts and how this affects their end use applications are also discussed. SELECTION OF CRAB BIO-PRODUCTS Figure 1 identified various bulk intermediate bio-products that could be extracted from snow crab processing byproducts including protein, lipids, chitin, minerals (ash), and astaxanthin. Due to the estimated low yields of lipids and astaxanthin likely to be extracted from the available crab byproducts, these bio-products were not extracted for the purpose of this study. Since chitin and protein are commercially more valuable than the ash, only chitin and protein were extracted and recovered for this study. METHODS Collection and Preparation of Crab Byproduct

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Figure 2: Snow crab processing byproducts.

Snow crab processing byproducts (Figure 2) collected from a processing plant located in Newfoundland and Labrador (N.L.), Canada, in June 2018 were milled and dried to produce crab meal (Figure 3). The crab meal was kept in frozen storage at -20°C in sealed sanitary plastic containers until the protein hydrolysate and chitin fractions could be extracted. The crab meal, protein hydrolysate, and chitin products were analyzed for proximate composition and trace metals. Extraction of Snow Crab Bio-products Raw, fresh, unseparated snow crab processing byproducts were collected in 10 L plastic

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pails (Figure 2), packed in flake ice, and transported to the Marine Institute’s Marine Bioprocessing pilot plant in St. John’s, N.L., where the byproduct was immediately frozen at -20°C until it could be further processed. The frozen crab byproduct was later thawed at 4°C and crushed in a Hobart grinder (Figure 4) in a two-step process: (1) Initially the material was milled through a 17 mm plate and (2) subsequently milled through a 13 mm plate. The crushed crab byproduct was then placed on drying trays in a single layer and dried to a constant weight at 105°C in a convection oven at 40% wind speed then ground to a particle size of ~1-2 mm (Figure 5). This dried crab

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Figure 3: Snow crab meal.

Figure 4: (L) Hobart Grinder. (R) Snow crab byproduct milled through the 17 mm cutting plate. 108 The Journal of Ocean Technology, Vol. 17, No. 1, 2022

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Figure 5: Air dried crab byproduct (L) before milling (13 mm particle size) and (R) after milling (1-2 mm).

meal product was later used for the extraction of additional crab bio-products: protein hydrolysate and chitin. Protein Hydrolysis Protein extraction was conducted using the protease enzyme Alcalase 2.4L, since the protein is not considered suitable for use as an animal feed or nutritional supplement if extracted with NaOH [Jo et al., 2011] due to possible chemical contaminants and protein denaturation. The following protease enzymes were considered: (1) Alcalase, Bacillus licheniformis; (2) Protease, Bacillus subtilis; and (3) Fungal Acid Protease, Aspergillus oryzae. Alcalase 2.4L (Bacillus licheniformis) was selected from the above list for the following reasons: (1) It has been reported to be one of the most highly efficient bacterial proteases used to prepare fish and other protein hydrolysates [See et al., 2011]; (2)

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Gildberg and Stenberg [2001] used Alcalase (2.4 l FG) to deproteinate Northern shrimp (Pandalus borealis) waste to obtain a highquality protein hydrolysate (about 70% of the total amino-N was recovered) without affecting the yield or quality of the chitosan subsequently produced. Protein hydrolysis was conducted using a modified method based on methods previously reported for salmon [See et al., 2011] and shrimp [Gildberg and Stenberg, 2001]. The hydrolysis was carried out at pH 8-8.55 and 55°C for 120 minutes using a crab byproductto-water ratio of 1:10, and 1% (v/w) Alcalase 2.4L. Following hydrolysis, the mixture was heated to 90°C and held at that temperature for 10 minutes to inactivate the protease enzyme [Lindberg et al., 2021]. The protein hydrolysate liquid was centrifuged at 7,000 rpm for 20 minutes, then vacuum filtered through a Whatman No. 41 ashless filter

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paper, and the filtrate spray dried using a Buchi mini spray dryer (Figure 6) to collect the protein hydrolysate (Figure 7). The spray drier operating parameters were set at Inlet temperature 180°C; Outlet temperature 40°C; Aspirator 100%; Pump 20%; Q-Flow 30. Chitin Extraction Most traditional isolation methods of chitin from crab shells involves three main processing steps following initial particle size reduction which include (1) deproteination – removal of protein using strong alkali and heat treatment (e.g., 1-2% w/v KOH, 90°C for two hours); (2) demineralization – removal of minerals, mainly calcium carbonate, by treatment with strong acid (e.g., 5-7% w/v HCl for two hours at room temperature); and (3) decolouration – removal of pigment using a bleaching/oxidizing agent (e.g., hydrogen peroxide, ethanol, acetone, sodium hypochlorite) to obtain a colourless product [Bruck et al., 2012; Synowiecki and ALKhateeb, 2000; Duarte de Holanda and Netto, 2006]. This process may be carried out on fresh or dried shells, and the demineralization and deproteination steps may be carried out in reverse order if pigment recovery is not required [Synowiecki and AL-Khateeb, 2000; Duarte de Holanda and Netto, 2006]. In our study, following enzymatic protein hydrolysis and recovery of the soluble protein, the remaining insoluble shell fraction was collected on a Whatman No. 41 ashless filter paper using vacuum filtration and washed a minimum of three times with deionized water to pH 7. Chitin extraction was conducted using a two-step chemical process: (1) Demineralization with 7% HCl

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(1:10 shells:HCl) for three hours at 25°C; and (2) Deproteination with 10% NaOH (1:10 shells:NaOH) for two hours at 55°C to remove any residual protein not removed by the enzyme treatment. Previous studies have shown that enzymatic deproteination of shrimp using Alcalase did not achieve full deproteination and that the chitin thus obtained contained a residual protein content that was twice as high as chitin obtained via treatment with NaOH [Synowiecki and AL-Khateeb, 2000; Duarte de Holanda and Netto, 2006]. The resulting chitin (Figure 8) was collected on a Whatman No. 41 ashless filter paper using vacuum filtration and washed several times with deionized water to pH 7, followed by low temperature convection drying at 55°C. The chitin sample was not depigmented for this experiment. A schematic illustration summarizing the extraction, recovery, and purification processes used to prepare crab bio-products for this study is presented in Figure 9. Proximate Composition Proximate composition was determined for the dried crab byproduct samples and included determination of Moisture Content-Air Oven Method – AOAC Method 930.14; Kjeldahl Nitrogen – AOAC Method 954.01/988.05; Ash Content – AOAC Method 938.08 Ash of Seafood; and Chitin Content. Chitin Yield and Chitin Content Chitin yield was determined following demineralization of 5-10 g of dried crab meal with 50-100 mL of 7% HCl for three hours at 25°C, followed by deproteination

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Crab protein hydrolysate liquid Crab protein hydrolysate powder

Figure 6: Spray drying snow crab protein hydrolysate using the Buchi mini spray dryer.g5.

with 10% NaOH (1:8 of crab:NaOH) for two hours at 55°C. Chitin was collected on a Whatman No. 41 ashless filter paper using vacuum filtration and washed a minimum of three times with deionized water to pH 7, followed by oven drying at 55-105°C for 2448 hours. The recovered chitin was analyzed for total nitrogen via the Kjeldahl method (AOAC 954.01/988.05) and ash content (AOAC 938.08). Chitin yield was calculated for crab meal using the equation: % Chitin Yield = [weight of chitin (g)/weight of crab meal (g)] x 100 (1)

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Chitin content was calculated for crab chitin using the equation: % Chitin Content = % Nitrogen x 14.5 (2)

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Figure 7: Spray dried snow crab protein hydrolysate powder.

Figure 8: Snow crab chitin.

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Figure 9: Schematic illustration of the extraction, recovery, and purification processes used to prepare crab bio-products for our heavy metal transfer study.

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Table 4: Proximate composition of extracted crab processing bio-products a.

a Results are reported on a dry weight basis, after isolation from the raw (unprocessed) crab byproduct. b Results

are the mean of three determinations ± standard deviation, except % Moisture for which there was only a single determination. c Results represent one determination due to the small sample size available. Assumptions: All nitrogen in protein hydrolysate is due to protein. All nitrogen in chitin fraction is attributed to chitin.

Elemental Analysis (ICP-MS) – Raw Crab Byproducts Samples of raw (unprocessed) crab byproducts were analyzed by Memorial University’s Department of Earth Sciences for elemental analysis. Samples were prepared by ashing for six hours at 550°C. The cooled samples were then acid digested, sonicated, and dried three times prior to diluting in 10 mL of 0.2M HNO3 in preparation for ICPMS analysis using a Perkin Elmer Elan DRC II ICP-MS instrument. NIST standard 2977 and USGS T-193 were used as the elemental standards. Procedural blanks were run for each element. Elemental Analysis (ICP-MS) – Dried Crab Bio-products Due to a maintenance shutdown of the Memorial University lab that conducted the elemental analysis on the raw (unprocessed) crab byproducts, the subsequently isolated crab bio-products (crab meal, protein hydrolysate, and chitin) were submitted to the Research and Productivity Council (RPC) in New Brunswick, Canada, for analysis of trace metals and mercury. Portions of the samples were prepared by Microwave Assisted Digestion in nitric acid according to RPC’s standard operating procedure SOP

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4.M26. The resulting solutions were analyzed for trace elements by ICP-MS according to RPC’s standard operating procedure SOP 4.M01, while mercury was analyzed by Cold Vapour AAS as per RPC’s standard operating procedures SOP 4.M52 and SOP 4.M53. Procedural blanks were run for each element. RESULTS AND DISCUSSION Proximate Composition The proximate compositions of the extracted crab bio-products are presented in Table 4. While we acknowledge that some of the nitrogen in the crab meal is associated with chitin, and that there may be some residual protein nitrogen remaining in the chitin fraction, for ease of calculation and comparison of the results, we assumed that all nitrogen in the protein hydrolysate was due to protein (factor of 6.25 was used to calculate % protein) and that all nitrogen in the chitin fraction was due to chitin (factor of 14.5 was used to calculate % chitin content). The results of the proximate analyses demonstrate that the extraction methods were effective in separating the protein and the chitin fractions from the crab meal byproduct. The protein hydrolysate contained 64.4%

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protein and 25.2% ash. The chitin fraction had an acceptable low ash content below 1% and a high chitin content (88%). Elemental Composition of Crab Byproducts and Crab Bio-products The purpose of this analysis was to understand the transfer of heavy metals from snow crab processing byproducts during the extraction of bulk intermediate bio-products – crab meal, protein hydrolysate, and chitin. Elemental compositions of the raw (unprocessed) crab byproducts and the extracted crab bio-products are presented in Table 5. Although the analyses were completed by two different labs, for the purpose of this assessment we assumed that any differences due to lab methods, equipment, or sample preparation were negligible. The level of heavy metals in the crab bioproducts evaluated in this study followed the order of crab meal > crab byproduct > protein hydrolysate > chitin. Heavy metals tend to accumulate in the organs and tissues of crustaceans such as crabs and prawns [Sayyad et al., 2020; Olowu et al., 2010]. Kim and Yoon [2011], for example, demonstrated that copper, arsenic, cadmium, and chromium tend to bioaccumulate in the hepatopancreas and gills of Korean Yeongdeok, crab, and Russian snow crab. The high protein and lipid content in our crab meal byproduct (Table 4) indicates it contained high amounts of meat, hepatopancreas, and gills and may explain the higher total heavy metal content in this sample. In addition, grinding and drying (aluminum drying trays) during the processing of the raw (unprocessed) crab byproduct into crab meal may have contributed to the higher metal content.

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Generally, all metals were reduced in the chitin product while some metals (arsenic, sodium, potassium) became more concentrated in the protein hydrolysate. Of particular interest are the high levels of arsenic in the crab meal (21.2 ppm) and protein hydrolysate (54.6 ppm), and the high concentrations of aluminum in the crab meal (185 ppm) and chitin (151 ppm), especially if the intent is to use these bio-products as feed ingredients, natural health products, or for biomedical and pharmaceutical purposes, due to the potential toxic effects of these metals. Arsenic levels were low in crab chitin (< 0.2 ppm) and raw (unprocessed) crab byproduct (3.64 ppm) but high in crab meal (21.2 ppm) and the protein hydrolysate (54.6 ppm), suggesting that arsenic is associated with the protein fraction of snow crab byproducts, and/ or is present in an organic form which would be unable to bind with chitin. Since arsenic was lower in the raw (unprocessed) crab byproduct, it is probable that the grinding steps during processing of the crab meal were an additional source of arsenic which then became more concentrated during isolation and drying of the protein hydrolysate. Aluminum levels were high in crab meal and chitin but low in the protein hydrolysate sample in the following order: crab meal (185 ppm) > chitin (151 ppm) > protein hydrolysate (5 ppm). An interesting observation is that the aluminum level, while high in the raw (unprocessed) crab byproduct (103 ppm), was higher in the processed crab meal and chitin. This suggests that there are likely two main sources of aluminum in the samples: (1) bioaccumulation from the

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Table 5: Elemental composition of raw snow crab byproducts and extracted bio-products on a dry weight basis in parts per million (ppm).

a Results represent the mean ± standard deviation of two replicates. nd = not determined. <DL = below detection limit. Analysis conducted by Memorial University of Newfoundland, Department of Earth Sciences. b Results represent the determination of one composite sample due to limited sample size available and cost of analysis. Analysis conducted by Research and Productivity Council, New Brunswick. 116 The Journal of Ocean Technology, Vol. 17, No. 1, 2022

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Table 6: Comparison of heavy metals in crab meal and protein hydrolysate with Health Canada allowable levels for seafood.

marine environment and (2) contamination from the grinding and drying steps. While aluminum is not listed as a metal of concern for seafood, natural health products, or chitinchitosan, it is classified as a neurotoxic agent [Exley, 2014]. This, coupled with reports of increasing concentrations of aluminum in the environment, food, and drink [Hardisson et al., 2017; Pereira et al., 2019; Mirza et al., 2017], is raising health and safety concerns for some consumers. As we currently do not have a good understanding of what constitutes a safe exposure vs. an unsafe exposure [Exley, 2013], limits for aluminum in food and natural health products have not been established. Protein Hydrolysate Protein hydrolysates have applications as feed additives for terrestrial and aquatic animals, and as natural health products (e.g., protein supplement) for human consumption. The main heavy metals of concern for edible seafood and for which Health Canada has established maximum allowable levels (Table 1) include arsenic, lead, and mercury. The maximum allowable levels of these metals in Canadian seafood are compared with our crab meal and protein hydrolysate samples in Table 6. Mercury and lead levels were below the Health Canada maximum level of 0.5-1 ppm [Health Canada, 2020] for seafood in the crab meal and protein hydrolysate. Total arsenic levels in the crab meal (21.2 ppm) and protein hydrolysate (54.6 ppm) samples, however,

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were significantly higher than the Health Canada maximum level of 3.5 ppm (total arsenic) for seafood [Health Canada, 2020] and 8 ppm in livestock feed [Health Canada, 2017]. Arsenic was more concentrated in the protein hydrolysate sample in comparison to the crab meal sample. The high levels of sodium and potassium (Table 5), while not the focus of our study, may also affect the acceptability of crab meal and protein hydrolysate from a nutritional perspective, in feeds, and natural health products and should be further evaluated. Arsenic Arsenic is the twentieth most abundant element on Earth, and in its inorganic forms (e.g., arsenite AsIII, and arsenate AsV) it is lethal to the environment and living organisms being both toxic and carcinogenic [Cubadda et al., 2017; Jaishankar et al., 2014]. Sources of arsenic in the environment come from industrial sources, natural mine deposits, use of pesticides containing arsenic, and inappropriate disposal of arsenic chemicals [Jaishankar et al., 2014]. The type of arsenic determines its toxicity. Organic arsenic has a more complicated chemical structure (bound to carbon atoms) than inorganic arsenic, yet organic arsenic is harmless, whereas inorganic arsenic (iAs) is toxic [Schwarcz, 2018]. Arsenobetaine

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(C5H11AsO2) is the most abundant form of arsenic found in seafood but is relatively non-toxic since the arsenic atoms are bound to carbon and, therefore, not available to bond with other biomolecules such as protein [Cubadda et al., 2017; FAO/WHO, 2011; Schwarcz, 2018; Taylor et al., 2017]. Organo-arsenicals, such as arsenobetaine, have low toxicity due to their low biological reactivity and their rapid excretion in urine [WHO, 2000]. Dietary exposure to arsenic is largely influenced by the amount of seafood in the diet [WHO, 2000]. Shellfish and seafood have been identified as a key contributor of iAs exposure in the diet, particularly in countries where large quantities of seafood are consumed (e.g., Japan, United States) and have been categorized as a food that is naturally high in iAs [Cubadda et al., 2017; Taylor et al., 2017; WHO, 2000; EPSA, 2009]. While As in seafood is primarily present in its organic form, some marine species have high iAs levels, with shellfish having higher concentrations than finfish [Taylor et al., 2017; Lorenzana et al., 2009]. Lynch et al. [2014] reported that crustaceans may contain high levels of iAs. Total arsenic concentrations in some crustaceans have been reported to be > 100 mg/kg [WHO, 2000; Munóz et al., 2000; Ishinishi et al., 1986]. Anacleto et al. [2010] evaluated the total arsenic content in several fish, cephalopods, and Norway lobster and the latter had the highest levels of total arsenic (23.1-51.2 ppm) among the 12 species evaluated. Munóz et al. [2000] reported total arsenic levels of 1.69-137.32 ppm in

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crustaceans, and Fabris et al. [2006] reported a total arsenic level of 50.7 ppm in Australian lobster. The levels of arsenic found in our snow crab byproduct, crab meal, and protein hydrolysate samples are comparable to these previously reported values. While arsenic speciation was beyond the scope of this study, it is important to understand which arsenic species are present in our samples and in what proportions to determine potential human toxicity. For illustration, we conducted a theoretical assessment based on previous studies by Cubadda et al. [2017] and Lorenzana et al. [2009]. Cubadda et al. [2017] estimated that of the total arsenic present in shellfish, 5% is attributed to iAs, 50% is due to arsenobetaine, and 45% is due to other organoarsenic species (other than arsenobataine), which may or may not be toxic. Lorenzana et al. [2009] found that levels of iAs could be as high as 25% in shellfish. Based on the iAs levels reported for shellfish in these previous studies, our protein hydrolysate sample theoretically could contain anywhere from 2.73-13.65 ppm iAs. At this concentration, our crab protein hydrolysate in its current form would not be an acceptable protein supplement when administered at a dosage of 3-4 g/day [Jensen et al., 2019]. At this dosage, based on our theoretical estimate of iAs, our crab protein hydrolysate exceeds Health Canada’s daily acceptable limits for NHPs (Table 3) resulting in 164-218 ug/day of total arsenic and 8.1954.6 ug/day of iAs. Chitin Shrimp and crab shell waste are the main commercial sources of chitin. Due to its highly crystalline structure and strong hydrogen

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bonds, chitin is not readily dissolved in common solvents which limits its applications. Therefore, it is often converted to its N-deacetylated derivative, chitosan, and/ or other modified forms of chitin/chitosan, which are more soluble in dilute organic acids and water [Manuel, 2017]. The control over molecular weight, viscosity, and degree of deacetylation allows the production of a wide range of chitosans which can be used in medical, pharmaceutical, cosmetic, nutraceutical, and industrial fields, and are the main characteristics used to determine quality and price [Manuel, 2017; Jayakumar et al., 2010; France Chitine, n.d.; Roberts, 1992]. Safety is determined by the levels of residual protein, bacterial endotoxins, and heavy metals present [Manuel, 2017; Khor, 2014]. Currently, chitosan is approved in Canada as a NHP for oral administration as a supplement for weight management and maintaining healthy cholesterol levels [Health Canada, 2018]. In the United States, chitosan has been approved by the FDA for wound healing applications [Kumar and Kumar, 2017], and as a Generally Recognized as Safe food additive [Morin-Crini et al., 2019], while its complete approval by the FDA for all biomedical applications is still pending [Kumar and Kumar, 2017]. It is also approved as a food ingredient in Japan and Korea [Morin-Crini et al., 2019]. Morin-Crini et al. [2019] recently conducted a comprehensive review of the many applications of chitosan in several fields. Based on their review of numerous papers and patents reported over the last two decades, they concluded that although therapeutic and

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biomedical chitosan products are promising, chitosan applications in the biomedical field are still limited due to challenges in accessing biopolymers of sufficient purity and reliability, the high development costs, and the limited number of in vivo studies conducted. Part of this challenge is the lack of a definitive “standard” for either chitin or chitosan [Roberts, 1992], and there are no universally accepted quality standards for the wide array of various chitosans available in the market. However, guidelines and standards have been proposed for chitosan for pharmaceutical and medical applications. Proposed standards by Knapczyk et al. [1989] covered general characteristics, chemical and microbiological purity levels, physiological properties, and biological activity [Roberts, 1992]. More recently, ASTM [2019] and USP-NF [2020] published guidelines for the characterization/ evaluation of chitosan/chitosan-salts for use in biomedical and/or pharmaceutical applications. Large chitin-chitosan manufacturers (e.g., Heppe Medical, Primex) produce these biopolymers under some form of quality management system such as ISO 9001, Good Manufacturing Practices, or Good Laboratory Practices and must meet the requirements of the importing countries’ health regulations [Khor, 2014]. Our chitin sample meets the USP-NF medical grade chitin-chitosan standard for arsenic, cadmium, chromium, iron, lead, mercury, and nickel, but exceeds the total maximum allowable level of heavy metals when aluminum is considered (Table 7). Our chitin sample also meets the Health Canada requirements for levels of arsenic, lead, and mercury in seafood (Table 7). However,

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Table 7: Comparison of heavy metals in chitin with industry standard for medical grade chitosan and Health Canada levels for seafood [Health Canada; 2020; ASTM, 2019; USPC, 2020; CASD, 2014].

a Does not include aluminum. b Including aluminum.

Health Canada has not established limits for levels of total aluminum in food or natural health products. Aluminum Varying amounts of aluminum are naturally present in the environment. Aluminum is the third most common element found in the Earth’s crust constituting about 8% by weight and is the most abundant metal on Earth [Pereira et al., 2019]. It is one of the most common metals found in the environment and occurs naturally in the air, water, and soil and, therefore, in food [Jaishankar et al., 2014; Gupta et al., 2013; Hardisson et al., 2017; Healthy Canadians, 1998; EPA, 2020]. Mining and processing of aluminum increases its level in the environment [Jaishankar et al., 2014; ATSDR, 2008; EPA, 2000] as does acidification of the soils [Hardisson et al., 2017; EPA, 2020]. This acidification of soils and the transfer of soluble aluminum (Al3+) to the aquatic environment has resulted in increasing concentrations of aluminum in food and drink [Hardisson et al., 2017]. Other sources of aluminum include food additives, aluminum utensils, and tea consumption [Sjögren et al., 2007]. However, aluminum has

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no known biological role. It is a non-essential toxic metal to microorganisms, animals, fish, aquatic life, and humans [Hardisson et al., 2017; Olaniran et al., 2013]. In humans, it tends to accumulate in the brain and is, therefore, classified as a neurotoxic agent which has been linked to different diseases such as Alzheimer’s disease and may interfere with other essential metals [Hardisson et al., 2017; Pereira et al., 2019; Mirza et al., 2017; Exley, 2013; 2014]; however, studies to date have been inconclusive. Maximum dietary limit intake levels for aluminum have been established by various organizations. The European Food Safety Authority (EFSA) has established a tolerable weekly intake (TWI) of 1 mg Al per kg of body weight [EFSA, 2011]. The Food and Agriculture Association/World Health Organization (FAO/WHO) Expert Committee on Food Additives has set a provisional tolerable weekly intake of 2 mg/kg of body weight/week [Hardisson et al., 2017; FAO/ WHO, 2011], stating that a daily aluminum intake of up to 7 mg/kg body weight is tolerable [Bruck et al., 2011]. Dietary limit intake levels have not been established by

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Health Canada [2008], and there is currently no established industry standard for aluminum levels in chitin-chitosan. Aluminum levels in a variety of marine products were reviewed by Jaishankar et al. [2014] for the period 2002-2017. They found that aluminum levels varied widely between areas where products were collected, but overall seafood had the highest reported Al levels ranging from 10.2-204.6 mg/kg, in comparison to other food groups, except for processed cheese which had levels of Al between 270-670 mg/kg attributed to the use of sodium-aluminum phosphate as an emulsifying agent [Soni et al., 2002; Saiyed and Yokel, 2005]. Pereira et al. [2019] reported that in marine samples aluminum levels vary and can range from 0.1 to 19.2 ug/g in a variety of fish to as high as 71.9 ug/g in mussels (Mytilus edulis). The Al levels determined for snow crab products in this study are within the range reported by Jaishankar et al. [2014]. Ingestion, inhalation, and dermal contact have all been identified as routes of aluminum exposure [Jaishankar et al., 2014]. Drugs.com reported that in clinical trials the dosage of chitosan administered for glucose control is 1.5 g/day yet could be as high as 15 g/day for weight loss applications [Drugs.com, 2021]. Therefore, our chitin sample could contribute up to 2.265 mg of aluminum daily if used as a weight loss supplement at a dosage of 15 g/day. For a person weighing 80 kg, this is equivalent to 10-20% of the TWI levels established by EFSA and the FAO/WHO Expert Committee on Food Additives. Chitin-chitosan also has various cosmetic applications; aluminum levels in cosmetics has raised concerns due

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to possible linkages with breast cancer and Alzheimer’s disease [Becker et al., 2016; Exley, 2014]. Another proposed use of chitin and chitosan is as a drug delivery agent in inhalation products, and in the manufacture of biodegradable sutures [Matica et al., 2017; Kumar and Kumar, 2017], for which a key consideration is purity. Although the daily aluminum intake through chitin-chitosan products may seem insignificant on its own, the high level of aluminum in our chitin sample may be cause for concern for these types of products when combined with other sources of aluminum exposure by contributing to the body burden of aluminum [Exley, 2013; 2014]. Since aluminum has no biological function [Hardisson et al., 2017; Olaniran et al., 2013], and it is not overtly toxic, it could become covertly toxic because it accumulates in the brain as we age [Exley, 2013; 2014]. Until further scientific data is available regarding safe vs. unsafe exposure levels, a precautionary approach to reduce human exposure to aluminum is advisable [Exley, 2013]. Aluminum was only marginally reduced from 185 ppm in the crab meal sample to 151 ppm in our chitin sample, suggesting that it may bio-adsorb to chitin during the extraction process or that the extraction process was not effective for its removal. Our results indicate that the main source of aluminum is likely bioaccumulation from the marine environment; however, the grinding and drying steps may be an additional source of aluminum contamination. Given the adverse health effects associated with aluminum, it would be prudent to minimize this impurity in chitin-chitosan products intended for natural health products as well as pharmaceutical and biomedical

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applications. If the aluminum is in a nonleachable form, the resulting chitin may still be valuable for external applications. CONCLUSION Understanding the levels of heavy metals in snow crab byproducts and how they are transferred throughout the crab bio-product value chain will be key to developing safe marketable crab bio-products for natural health product and biomedical/pharmaceutical applications. Two metals of concern were identified in the crab bio-products produced during this study: arsenic which causes acute toxicity and aluminum which may be covertly toxic over time. Two potential sources of these metals were also identified: bioaccumulation from the marine environment and contamination from processing equipment. Arsenic (54.6 ppm) was concentrated in the protein hydrolysate and aluminum (151 ppm) in the chitin fraction. Speciation of arsenic was beyond the scope of the current study and, therefore, we cannot accurately quantify the concentration of organic and inorganic arsenic in our sample. However, speciation analysis for selective determination of iAs is important to avoid overestimation (or underestimation) of the health risk associated with dietary arsenic exposure [Cubadda et al., 2017]. It is recommended that arsenic speciation be evaluated in future studies to provide a better understanding of the safety and potential toxicity of crab protein hydrolysates for use as a natural health product. This study has illustrated that care must be taken to remove aluminum and arsenic from the raw (unprocessed) crab byproduct and

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to ensure the extraction process does not increase the concentration of these metals and inadvertently facilitate their transfer to the final bio-products. The processing steps should be further evaluated with the aim of reducing the arsenic and aluminum content in the bioproducts as well as minimizing potential metal contamination from processing equipment. The shell and protein/organs/tissues may need to be separated at the processing plant and processed separately into protein hydrolysate and chitin for more effective removal of metal contaminants. The main limitation of this study was the limited number of samples available. Additional studies using a larger sample size are recommended to better understand levels of heavy metals that are naturally present in raw (unprocessed) snow crab byproducts from N.L. and their final concentrations in extracted crab bio-products. REFERENCES Alabi, O.A. and Adeoluwa, Y.M. [2020]. Production, usage and potential of public health effects of aluminum cookware: a review. Annals of Science and Technology, Vol. 5, pp. 20-30. Anacleto, P.; Lourenço, H.M.; Ferraria, V.; Afonso, C.; Carvalho, M.L.; Martins, M.F.; and Nunes, M.L. [2010]. Total arsenic content in seafood consumed in Portugal. Journal of Aquatic Food Product Technology, Vol. 18, pp. 32-45. ASTM [2019]. Standard guide for characterization and testing of chitosan salts as starting materials intended for use in biomedical and tissue-engineered medical product applications. ASTM International, F2103-18. ATSDR Agency for Toxic Substances and Disease Registry [2008]. Public Health Statement on Aluminum. ATSDR Publication CAS#7429-90-5. Beaulieu, L.; Thibodeau, J.; Bryl, P.; and Carbonneau, M-E. [2009]. Characterization of enzymatic hydrolyzed snow crab (Chionoecetes opilio) by-product fractions: a

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source of high-valued biomolecules. Bioresource Technology, Vol. 100, pp. 3332-3342. Becker, L.C.; Boyer, I.; Bergfeld, W.F.; Belsito, D.V.; Hill, R.A.; Klaassen, C.D.; Liebler, D.C.; Marks Jr., J.G.; Shank, R.C.; Slaga, T.J.; Snyder, P.W.; and Andersen, F.A. [2016]. Safety assessment of alumina and aluminum hydroxide as used in cosmetics. International Journal of Toxicology, Vol. 35(3), pp. 16S-33S. Retrieved from: https://journals.sagepub.com/ doi/pdf/10.1177/1091581816677948. Bruck, W.M.; Slater, J.W.; and Carney, B.F. [2011]. Chitin and chitosan from marine organisms. In: Chitin, Chitosan, Oligosaccharides and their Derivatives (ed. S.K. Kim), CRC Press, Florida, pp.11-23. Bruck, W.M.; Reisse, S.; Garbe, D.; and Bruck, T.B. [2012]. Industry potential and marine bioactive components: downstream processing and vehicles for efficient delivery in situ. In: Marine Bioactive Compounds: Sources, Characterization and Applications (ed. M. Hayes), Springer Science+Business Media, Netherlands, pp. 129-157. Burke, H. [2021]. Characterization and stabilization of marine biomass feedstock from snow crab (Chionoecetes opilio) processing. PhD Thesis Chapter 4 (unpublished), Memorial University of Newfoundland. CASD Centre for Aquaculture and Seafood Development [2014]. Development of a pilotscale process for the production of biomedicalgrade chitosan from shellfish waste. CASD Project Report P-8106, Fisheries and Marine Institute. Cubadda, F.; Jackson, B.P.; Cottingham, K.L.; Van Horne, Y.O.; and Kurzius-Spencer, M. [2017]. Human exposure to dietary inorganic arsenic and other arsenic species: state of knowledge, gaps and uncertainties. Science of the Total Environment, Vol. 579, pp.1228-1239. Drugs.com [2021]. Chitosan. Retrieved from: https://www.drugs.com/npp/chitosan.html. Duarte de Holanda, H. and Netto, F.M. [2006]. Recovery of components from shrimp (Xiphopenaeus kroyeri) processing waste by enzymatic hydrolysis. Journal of Food Science, Vol. 71, pp. 298-303. EFSA European Food Safety Authority [2009]. Panel on contaminants in the food chain

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(CONTAM): Scientific opinion on arsenic in food. EFSA J, Vol. 7, (10):1351. EFSA European Food Safety Authority [2011]. Statement on the evaluation on a new study related to the bioavailability of aluminum in food. EFSA J, Vol. 9(5), 2157. Retrieved from: https://www.efsa.europa.eu/ enefsajournal/pub/2157. EPA Environmental Protection Agency [2020]. Aquatic life criteria – aluminum. Retrieved from: https://www.epa.gov/wqc/aquatic-lifecriteria-aluminum. Exley, C. [2013]. Human exposure to aluminum. Environmental Science: Processes and Impacts, 15, 1807-1816. Exley, C. [2014]. What is the risk of aluminum as a neurotoxin? Expert review of Neurotherapeutics, 14:6, 589-591, DOI: 10.1586/14737175.2014. 915745. Fabris, G.; Turoczy, N.; and Stagnitti, F. [2006]. Trace metal concentrations in edible tissue of snapper, flathead, lobster, and abalone from coastal waters of Victoria, Australia. Ecotoxicology Environmental Safety, Vol. 63, pp. 286-292. FAO/WHO [2011]. Evaluation of certain food additives and contaminants: seventy-fourth report of the Joint FA/WHO Expert Committee on food additives. WHO Technical Report Series, WHO, Switzerland, 966. Retrieved from: http://apps.who.int/iris/bitstream/handle/ 10665/44788/WHO_TRS_966_eng.pdf; jsessionid=FD2960FE9C449EEB8B3C30C12 71AA84C?sequence=1. FLR Fisheries and Land Resources [2019]. Seafood Industry Year in Review 2019. Government of Newfoundland and Labrador. Retrieved from: https://www.gov.nl.ca/ffa/files/2019-SIYIRWEB.pdf. France Chitine [n.d.]. Chitosan a natural product. Retrieved from: http://www.france-chitine. com/chitosan.e.html. Gildberg, A. and Stenberg, E. [2001]. A new process for advanced utilisation of shrimp waste. Process Biochemistry, Vol. 36, pp. 809-812. Guangyuan, L. et al. [2009]. Controlling the degradation of covalently cross-linked carboxymethyl chitosan utilizing bimodal molecular weight distribution. Journal of Biomaterials Applications, Vol. 23, pp. 435-451.

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Gupta, N.; Gaurav, S.S.; and Kumar, A. [2013]. Molecular basis of aluminum toxicity in plants: a review. American Journal of Plant Science, Vol. 4, pp. 21-37. Hardisson, A.; Revert, C.; González-Weller, D.; Gutiérrez, Á.; Paz, S.; and Rubido, C. [2017]. Aluminum exposure through the diet. Journal of Food Science and Nutrition, Vol 3: 020. DOI: 10.24966/FSN-1076/100020. Retrieved from: https://www.heraldopenaccess.us/open access/aluminium-exposure-through-the-diet. Health Canada [2008]. Health Canada review of dietary exposure to aluminum. Retrieved from: https://www.canada.ca/en/health-canada/ services/food-nutrition/food-safety/foodadditives/review-dietary-exposure-aluminum. html. Health Canada [2015]. Quality of natural health products guide. Retrieved from: https://www. canada.ca/en/health-canada/services/drugshealth-products/natural-non-prescription/ legislation-guidelines/guidance-documents/ quality-guide.html#a321. Health Canada [2017]. RG-8 Regulatory Guidance: Contaminants in feed (formerly RG-1, Chapter 7) Section 4: Metal contaminants. Retrieved from: https://inspection.canada.ca/animalhealth/livestock-feeds/regulatory-guidance/rg8/eng/1347383943203/1347384015909?cha p=4. Health Canada [2018]. Monograph Natural Health Product Chitosan. Retrieved from: http://webprod.hc-sc.gc.ca/nhpid-bdipsn/ monoReq.do?id=2740&lang=eng. Health Canada [2020]. Health Canada’s maximum levels for chemical contaminants in foods. Retrieved from: https://www.canada.ca/en/ health-canada/services/food-nutrition/foodsafety/chemical-contaminants/maximumlevels-chemical-contaminants-foods.html. Healthy Canadians [1998]. Aluminum. Retrieved from https://healthycanadians.gc.ca/publications/ healthy-living-vie-saine/water-aluminum-eau/ alt/water-aluminum-eau-eng.pdf. Ishinishi, N. et al. [1986]. Arsenic. In: Handbook of the Toxicology of Metals Vol. II. (eds. L. Friberg, G.F. Nordberg & B.V. Vouk), Elsevier, Amsterdam-New York-Oxford. Cited in: WHO [2000]. Air Quality Guidelines Second Edition, Chapter 6.1 Arsenic. WHO Regional Office for

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Europe, Copenhagen, Denmark. Jaishankar, M.; Tseten, T.; Anbalagan, N.; Mathew, B.; and Beeregowda, K. [2014]. Toxicity, mechanism and health effects of some heavy metals. Interdisciplinary Toxicology, Vol. 7(2), pp. 60-72. Jayakumar, R.; Prabaharan, M.; Nair, S.V.; and Tamura, H. [2010]. Novel chitin and chitosan nanofibers in biomedical applications. Biotechnology Advances, Vol. 28, pp. 42-150. Jensen, C.; Dale, H.F.; Hausken, T.; Lied, T.; Hatlebakk, J.G.; Brønstad, I.; Lied, G.; and Hoff, D.A.L. [2019]. Supplementation with cod protein hydrolysate in older adults: a dose range cross-over study. Journal of Nutritional Science, Vol. 8, e40. doi:10.1017/jns.2019.37. Jo, G-H.; Parl, R-D.; and Jung, W-J. [2011]. Chapter 4. Enzymatic Production of Chitin from Crustacean Shell Waste. In: Chitin, Chitosan, Oligosaccharides and their Derivatives (ed. Se-Kwon Kim). CRC Press, Boca Raton, FL, United States of America, pp. 37-45. Joint FAO/WHO Expert Committee on Food Additives [2011]. Evaluation of certain food additives and contaminants. WHO Technical Report Series 966. Retrieved from: http:// apps.who.int/iris/bitstream/handle/10665/44 788/WHO_TRS_966_eng.pdf;jsessionid=FD 2960FE9C449EEB8B3C30C1271AA84C?seq uence=1. Kean, T. and Thanou, M. [2010]. Biodegradation, biodistribution and toxicity of chitosan. Advanced Drug Delivery Reviews, Vol. 62, pp 3-11. Khor, E. [2014]. Chitosan biomedical commercialization. In: Chitin, (ed. E. Khor), Elsevier, Philadelphia, pp. 21-28. Kim, C.-R. and Yoon, Y.-Y. [2011]. A study on trace metals in Korean Yeongdeok crab and Russian snow crab. Journal of the Korean Society for Marine Environmental Engineering, Vol. 14(3), pp. 147-153. Knapczyk, J.; Krówczynski, L.; Krzek, J.; Brzeski, M.; Nürnberg, E.; Schenk, D.; and Struszczyk, H. [1989]. Chitin and Chitosan, (eds. G. SkjåkBrake, T. Anthonsen and P. Sandford), Elsevier, London, p. 657. Kumar, A.K. and Kumar, A. [2017]. Chitosan as a biomedical material: properties and

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applications. In: Biopolymers: Structure, Performance and Applications. (eds. A. Kumar Mishars, C. Mustansar Hussain et al.), Nova Science Publishers, Inc., pp. 139-153. Lindberg, D.; Solstad, R.G.; Arnesen, J.A.; Helmers, A.K.; and Whitaker, R.D. [2021]. Lab scale sustainable extraction of components from snow crab (Chionoecetes opilio) coproducts, and estimation of processing costs based on a small-scale demonstration plant (Biotep). Nofima AS-Norwegian Institute of Food, Fisheries and Aquaculture Research, Mununbakken 9-13, NO-9019 Tromso, Norway (www.nofima.no). Lorenzana, R.; Yeow, A.; Coleman, J.; Chappell, L.; and Choudhury, H. [2009]. Arsenic in seafood: speciation issues for human health risk assessment. Human and Ecological Risk Assessment, Vol. 15 (1), pp. 185-200. Lynch, H.; Greenberg, G.; Pollock, M.; and Lewis, A. [2014]. A comprehensive evaluation of inorganic arsenic in food and considerations for dietary intake analyses. Science and the Total Environment, Vol. 496, pp. 299-313. Manuel, H. [2017]. Innovations in crustacean processing: bioproduction of chitin and its derivatives. In: Fuels, Chemicals, and Materials from the Oceans and Aquatic Sources, (eds. F.M. Kerton and N. Yan), John Wiley & Sons Ltd, UK, pp. 113-149. Marques, C.; Som, C.; Schmutz, M.; Borges, O.; and Borchard, G. [2020]. How the lack of chitosan characterization precludes implementation of the safe-by-design concept. Frontiers in Bioengineering and Biotechnology, Vol. 8, Article 165, pp. 1-12. Matica, A.; Menghiu, G.; and Ostafe, V. [2017]. Toxicity of chitosan based products. New Frontiers in Chemistry, Vol. 26, pp. 65-74. Mirza, A.; King, A.; Troakes, C.; and Exley, C. [2017]. Aluminum in brain tissue in familial Alzheimer’s disease. Journal of Trace Elements in Medicine and Biology, Vol. 40, pp. 30-36. Morin-Crini, N.; Lichtfouse, E.; Torri, G.; and Crini, G. [2019]. Applications of chitosan in food, pharmaceuticals, medicine, cosmetics, agriculture, textiles, pulp and paper, biotechnology, and environmental chemistry. Environmental Chemistry Letters, Vol. 17, pp. 1667-1692.

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Muñoz, O.; Suñer, M.A.; Vélez, D.; Montoro, R.; Urieta, I.; Macho, M.L.; and Jalón, M. [2000]. Total and inorganic arsenic in fresh and processed fish products. Journal of Agriculture and Food Chemistry, Vol. 48(9), pp. 4369-4376. Olaniran A.O.; Balgobind A.; and Pillay B. [2013]. Bioavailability of heavy metals in soil: impact on microbial biodegradation of organic compounds and possible improvement strategies. International Journal of Molecular Sciences, Vol 14(5), pp. 10197-10228. Olowu, R.A.; Ayejuyo, O.O.; Adejoroi, A.; Adewuyi, G.O.; Osudiya, M.O.; Onwordi, C.T.; Yusuf, K.A.; and Owolabi, M.S. [2010]. Determination of heavy metals in crab and prawn in Ojo Rivers Lagos, Nigeria. E-Journal of Chemistry, Vol. 7(2), pp. 526-530. Pereira, M.; Freitas, D.C.; Neta, L.; Santos, A.V.; Ribeiro, J.N.; and Ribeiro, A.V. [2019]. Chapter 4: Sulfur, aluminum, arsenic, cadmium, lead, mercury, and nickel in marine ecosystems: accumulation, distribution, and environmental effects. In: Marine Ecology: Current and Future Developments, Vol. 1, pp. 68-90. Roberts, G.A. [1992]. Chitin Chemistry. The MacmillanPress Ltd, London, pp. 85-115. Saiyed, S.M. and Yokel, R.A. (2005). Aluminum content of some foods and food products in the USA, with aluminum food additives. Food Additives and Contaminants, Vol. 22, pp. 234-244. https://www.ncbi.nlm.nih.gov/ pubmed/16019791. Sayyad, N.R.; Khan, A.K.; Absari, N.T.; Hashmi, S.; and Shaijh, M.A.J. [2020]. Heavy metal concentrations in different body part of crab, Barytelphusa guerini from Godavari river. Journal of Industrial Pollution Control. Retrieved from: https://www.icontrolpollution. com/articles/heavy-metal-concentrationsin-differentbody-part-of-crab-barytelphusaguerinifrom-godavari-river-.php?aid=45742. Schwarcz, J. [2018]. What’s the difference between organic and inorganic arsenic? Retrieved from: https://www.mcgill.ca/oss/article/health/whatdifference-between-organic-and-inorganicarsenic. See, S.F.; Hoo, L.L.; and Babji, A.S. [2011]. Optimization of enzymatic hydrolysis of salmon (Salmo salar) skin by Alcalase. International Food Research Journal, Vol. 18(4),

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pp. 1359-1365. Sjögren B.; Iregren A.; Elinder C.G.; and Yokel R.A. [2007]. Chapter 17: Aluminum. In: Nordberg GF, Fowler BA, Nordberg M, Friberg L (eds.) Handbook on the Toxicology of Metals, (3rd edition). Academic Press, Amsterdam, Netherlands. Soni, M.G.; White, S.M.; Flamm, W.G.; and Burdock G.A. [2002]. Safety evaluation of dietary aluminum. Regulatory Toxicology and Pharmacology, Vol. 33, pp. 66-79. Synowiecki, J. and AL-Khateeb, N.A.A.Q. [2000]. The recovery of protein hydrolysate during enzymatic isolation of chitin from shrimp Crangon crangon processing discards. Food Chemistry, Vol. 68, pp. 147-152. Taylor, V.; Goodale, B.; Raab, A.; Schwerdtle, T.; Reimer, K.; Conklin, S.; Karagas, M.; and Francesconi, K. [2017]. Human exposure to organic arsenic species from seafood. Science of the Total Environment, Vol. 580, pp. 266-282. USPC 2020. Chitosan. Retrieved from: https://online.uspnf.com/uspnf/document/1_ GUID_30832BBE-AFC1-463B-9695- AB4EF0A14413_6_en-US?source=. WHO World Health Organization [2000]. Air Quality Guidelines Second Edition, Chapter 6.1 Arsenic. WHO Regional Office for Europe, Copenhagen, Denmark.

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Q& A Kelly with


Engineer. Oceanographer. Community volunteer. Senior program officer with the National Academies of Sciences, Engineering, and Medicine where she works to advance priorities of the Ocean Studies Board, exploring science, policy, and infrastructure needed to better understand, protect, and manage coastal and marine environments.

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Where were you born? Where is home today? I was born in Houston, Texas. Growing up, we moved often, but I am technically a native Texan. Today, I live just outside Washington, D.C., with my husband, two kids, two dogs, and two bunnies. I’ve lived in the area for 16 years now and love it. What is your occupation? I am a senior program officer for the Ocean Studies Board at the National Academies of Sciences, Engineering, and Medicine in Washington, D.C. We are a congressionallychartered nonprofit organization that provides independent, objective, expert advice to inform policy and public opinion on matters of science, engineering, and medicine. The types of projects we develop and run include consensus studies, workshops, roundtables, forums, and other activities designed to bring diverse expert volunteers together to progress discussions and solve challenging problems. Why did you choose this occupation? I am interested in everything. Choosing a major was kind of a nightmare for me. I could have chosen 20 different directions and felt passionately about all of them. My high school physics teacher encouraged me to explore engineering and I was starting to get really interested in ocean renewable energy so the suggestion stuck. I figured if I at least started out in engineering, I would have a solid base and other doors would open as I figured it all out … and that turned out to be a pretty good plan. But back to “why”: working as program staff for the National Academies fills my “interest” bucket and does so in a way that I feel is very meaningful. This career has allowed me to explore new and interesting topics on a regular basis. I am lucky to work with top scientists and engineers to help solve our nation’s and our world’s biggest challenges. Just in the past year or so, I have had the privilege to work closely with experts to tackle challenges related to Earth system predictability, ocean-based carbon dioxide removal, marine plastics, and effects of oil on the marine environment. To say the least, I am never bored. Where has your career taken you? I have been in the general field of geosciences for my full career – starting off as a geotechnical

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engineer right out of my undergrad studies analyzing cores of soil below the seafloor in the Gulf of Mexico and adding to that an advanced degree in physical oceanography a few years later. I have been in the field of scientific program management since living in D.C., working for the ocean drilling program initially and, for the past six years, as program staff at the National Academies, where I have had incredible opportunities to develop new program areas such as Understanding Gulf Ocean Systems and to direct important studies such as “A Research Strategy for Ocean-based Carbon Dioxide Removal and Sequestration.” If you had to choose another career, what would it be? I have always thought about teaching. I would love to do more to encourage the next generation and make sure they know about all the amazing possibilities to explore. It took me way too long to figure it out on my own! What is your personal motto? I will channel my inner scout and say “use your resources wisely.” When it comes to time, effort, friendship, energy, opportunities, sleep, food, water – you name it – I think it is so important to make the most of what you have and to minimize waste. What hobbies do you enjoy? When I am not working or driving the kid taxi, I try to be outdoors – I love rollerblading, biking, and hiking and, at the end of the day, enjoying a nice meal or conversation out on the deck. Where do you like to vacation? I most often choose a beach location – any warm beach will do. The sound of the ocean brings me instant happiness. Who inspires you? Who or what? It sounds corny, but nature is a major source of continued inspiration for me. I am in awe and in great appreciation of the power and beauty and perfection of the natural world – every tiny detail of it. I do not want to further mess it up! What has been the highlight of your career so far? When we are working on a consensus study, the full process takes roughly 18-24 months to complete. Each completion is a highlight! The Journal of Ocean Technology, Vol. 17, No. 1, 2022 129

What do you like most about working in this field? Working with our volunteers – they are the best at what they do, and with that comes some pretty amazing and entertaining stories! Also, sometimes I get to go to Hawai’i or other beautiful locations “for work.” What technological advancements have you witnessed? The most recent advancement on my mind, being in the industry of “convening experts,” is the rapid switch to a virtual environment. The past few years have drastically changed the way we do our work and there are lessons learned that can help us do our work more efficiently and effectively going forward. When I started the ocean carbon dioxide removal study, the idea of flying the committee to D.C. to meet every couple of months seemed a bit, shall we say, counterproductive? I think it is great, and most appropriate, that we were able to meet virtually and get our work done with the lowest carbon footprint possible. Additionally, not everyone is able to travel for a variety of reasons (e.g., remote location, dependent care, or health) – the virtual environment is one tool we have been able to advance to promote inclusivity as well. What new technologies would you like to see? Advancements in networks of key oceanographic data throughout the ocean and coastal waters. Of course, scientists always need more data, but we really do need more data! We need it to better understand what is going on with the planet, what the impacts are of our actions or inactions, and what we can responsibly do to conserve, protect, and restore what we have. What advice do you have for those just starting their careers? Select a good mentor from the start. Volunteer to help when you can – you’ll learn more and make connections that can take you in all sorts of new directions. Diversify your networks. Be flexible.

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Trade Winds CO2 Capture and Use: A Mainstream Climate Solution

Global CO2 Initiative

What do we do with oceanic CO2 once it is captured? What incentive is there to drive the process of lowering the CO2 concentration of the ocean? CO2 emissions from human activity have led to ocean acidification that threatens this delicate ecosystem. To restore and preserve the ocean, we need a new paradigm for ocean-based CO2. Instead of thinking of it solely as a problem to be solved, we could think of it as an environmental and economic opportunity. Let’s take a step back to remember that life on planet Earth requires carbon; many of the things we use are carbon based. We are carbon based. Carbon dioxide is an essential component to our existence. CO2 itself is not a problem; the problem only arises when we add excess quantities of CO2 to the atmosphere and ocean. Currently, proven technologies exist that can reuse captured carbon dioxide to make products, ranging from plastics, household chemicals, fuels, and even concrete. The carbon dioxide is chemically converted and not released as carbon dioxide until the products are used or decompose over long times, e.g., when fuels get burned or household chemicals and plastics are discarded. However, when used in concrete, then the carbon dioxide remains as a rock-like substance forever. The key to carbon capture and utilization’s potential is that these carbon-based products have economic value. That value can give companies the incentive to deploy the

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technology at the global scale necessary to slow climate change. We need to stop thinking about CO2 capture from the ocean merely as a waste management process and instead think about it in terms of harvesting a resource – a resource with which we can make products, generate income, and employ people. It is also important to note that, if we utilize oceanic CO2 as a feedstock for new products, then we can stop taking carbon from fossil sources. And, if we stop harvesting fossil sources of carbon, we also stop adding new CO2 to the ocean. While carbon utilized in some products will eventually be released again after several decades when these products are discarded, it can then be recaptured and used again so that the net effect can be carbon neutral. Before launching new technologies to make CO2based products, we must carefully understand the implications of CO2 utilization in a product, including end-of-life scenarios, and conditions needed to make carbon capture and utilization technologies economically viable. Life cycle assessment and techno-economic assessment are tools to provide the required answers before moving technologies into the market to ensure that environmental benefits will be achieved at a cost that markets and societies can and will bear. The mission of the Global CO2 Initiative is to get CO2 capture and use recognized and implemented as a mainstream climate solution.

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This requires leading and accelerating the process to build a global marketplace to capture and transform CO2 into commercially sustainable products that harness gigatons of CO2 every year to make many of the necessary products of everyday living. As a global umbrella organization, we convene and accelerate research, development, and deployment by working with research organizations (academic, government, and commercial) and funding sources (angels, institutional, government, and commercial) throughout the world. Our organization is built on the three pillars of education, evaluation, and research. More specifically, we lead other organizations worldwide by engaging all stakeholders in the ecosystem to:

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• • •

Develop the educational discipline of carbon capture and utilization. Create the global standard tools that accelerate a system-level process of technology assessment. Accelerate the translation of research to development and market introduction and broad-scale deployment.

Our vision is to get CO2 capture and use recognized and implemented as a mainstream climate solution. We look forward to exploring ways in which we can partner with all those who share our vision. For more information: globalco2initiative.org info@globalco2initiative.org

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A Solution Trifecta for Ocean-based Carbon Dioxide Removal by Eric Siegel The climate crisis is the biggest threat to civilization we have ever faced, and the race to find solutions to remove carbon dioxide from the atmosphere is well underway. From technology that pulls carbon directly out of the air to nature-based solutions, there are many ideas that vary in both the approach to the problem and in scalability. What is clear is that we will need a broad portfolio of solutions – that include the “safe bets” and the “wild cards” – if we are to meet 2050 targets and reverse the dangers of climate change.

order to have a meaningful chance to keep the global temperature rise under 1.5°C. To meet this challenge, Elon Musk and the Musk Foundation has funded a new $100M XPRIZE based on finding carbon dioxide removal (CDR) solutions. To win the grand prize, teams must show a scalable working solution that can remove at least 1,000 tonnes of CO2 per year from the atmosphere or ocean; model their costs at a scale of 1 million tonnes per year; and show a pathway to achieving a scale of gigatonnes per year in the future.

Replacing fossil fuels with carbon-free sources is part of the pathway to a net-zero future. But this will not reduce the surplus carbon already in our atmosphere. The enhancement of natural carbon sinks will need to play an important supporting role in offsetting our carbon footprint. These natural climate solutions, involving the restoration of carbon-absorbing ecosystems (such as forests and wetlands), are increasingly featured in newly reformed climate policies. And yet, the planet’s largest carbon reservoir is often missing entirely from climate discussions – the ocean.

Scaling-up CDR technologies will eventually require billion-dollar investments for trilliondollar opportunities. Today, they benefit from world-class mentorship, partnerships, and research and development support to increase their likelihood of success. Ocean Visions recently created the Launchpad program to support teams pursuing ocean-based CDR pathways competing in the XPRIZE Carbon Removal challenge.

The ocean plays a central role in capturing and storing carbon dioxide from the atmosphere. There is approximately 50 times more carbon stored in the ocean than in the atmosphere. And recent research has shown that the ocean’s carbon storage potential could be safely increased. The International Panel on Climate Change estimates a need to remove between 10 to 20 gigatonnes of CO2 per year by 2050 in

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Ocean Visions brings together leading oceanographic research and academic institutions with private sector and publicinterest organizations to design and advance solutions that address the growing threats to our ocean and climate. Ocean Visions will work with the Launchpad teams to identify any potential gaps in technical and disciplinary expertise, as well as the key physical resources they will need (such as testing facilities, vessels, and labs) to enhance their ability to compete. Advisory teams will be recruited from the Ocean Visions network to provide ongoing technical advice

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and support over 12 to 24 months, without charge, to help the selected competitors maximize their chances of winning the prize. The ocean holds enormous potential for CDR solutions, given its sheer size and natural ability to sequester large quantities of carbon. But ocean-based carbon removal is mediated by a complex set of physical, chemical, and biological oceanography interactions. Joining the Ocean Vision Launchpad as a Research Consortium Member, the Ocean Frontier Institute (OFI) will provide much-needed ocean science and modelling expertise. OFI scientists are leading ground-breaking research in atmosphere-ocean interactions and auditing of the Northwest Atlantic carbon sink enabling new scientific discoveries to support ocean-based carbon sequestration activities and used to measure the effectiveness of innovative technologies. The Creative Destruction Lab (CDL) is also supporting the Launchpad as an Acceleration and Impact partner with strategies for scaleup, financing, partnerships, IP protection, and go-to-market plans. CDL delivers an objectives-based mentorship program with a mission to accelerate the commercialization of science for the betterment of humankind. The CDL-Atlantic site hosts the Oceans stream for ventures “disrupting” the ocean economy with emerging technologies such as underwater sensors, autonomous drones, bioresources, new materials, artificial intelligence, and predictive analytics. CDL Oceans mentors from around the world join with diverse entrepreneurial experience and control billions of dollars of venture capital, frequently focused on investments in ventures that make a positive impact to climate, ocean health, and sustainability.

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The Launchpad’s selected teams have proposed enormously innovative ideas that provide a peek into the future of ocean-based CDR for global climate solutions. Teams are composed of scientists, engineers, and entrepreneurs from the world’s top universities and industries. Their visionary concepts include autonomous platforms vertically transporting enormous kelp rafts between the nutrient-rich deep ocean and the sun-lit surface, to huge floating kelp farms anchored to the seafloor with renewable wave-powered fans artificially upwelling nutrients from the deep to fertilize the surface farms. The solution trifecta of OFI, CDL, and the Ocean Visions’ Launchpad will work together to support, mentor, and scale the world’s most innovative ocean-based CDR teams. The success and massive-scalability of many ocean-based CDR ventures will be critical to remove legacy carbon pollution from our atmosphere. If we do not look to the ocean with bold ideas, we cannot slow and ultimately reverse the climate crisis.

Eric Siegel is the chief innovation officer at the Ocean Frontier Institute and serves as the executive in residence for the Creative Destruction Lab Oceans stream.

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Ocean Drones Provide Systematic Observation to Enable Climate Solutions

by Richard Jenkins

It is estimated that the ocean has absorbed 30% of anthropogenic CO2 over the last 100 years; however, there are large areas of the ocean where not a single ocean CO2 measurement has ever been made. Ocean carbon removal strategies present a compelling climate change response, but before those strategies can be implemented, a baseline of ocean carbon uptake and outgassing must be established through systematic, persistent ocean observation. Scientists at the U.S. National Oceanic and Atmospheric Administration (NOAA)’s Pacific Marine Environmental Laboratory (PMEL) have been working for 10 years to develop a CO2 sensor for autonomous vehicles that measures pCO2 in the atmosphere and surface ocean at an accuracy of < 2 μatm. The ASVCO2™ is based on PMEL’s MAPCO2™ system designed for open ocean moorings. While ocean moorings currently in operation in the Atlantic, Pacific, and Indian oceans provide a valuable time series of data, they are fixed to one location and rely on ships to deploy and service. The ASVCO2 sensor requires very little power, is calibrated in-situ, and can be deployed for up to a year.

ASVCO2 system has been integrated into the Saildrone sensor suite. Saildrone USVs are highly manoeuvrable, wind and solar-powered vehicles with a zero operational carbon footprint. They are designed for long-range data collection missions in the most remote areas of the ocean and some of the harshest conditions on the planet. Saildrone has already completed several CO2-specific missions in the Arctic, Pacific, Atlantic, and Southern oceans and the Mediterranean Sea. In 2019, a Saildrone USV equipped with an ASVCO2 circumnavigated Antarctica, during which it collected more than 4,750 air and seawater CO2 measurements over eight months and provided information that altered understanding of the Southern Ocean as both a source and a sink for atmospheric CO2. PMEL has since updated the design of the ASVCO2 and entered into a cooperative research agreement with Saildrone to integrate the second-generation sensor into the Saildrone platform. As part of the collaboration, Saildrone will be manufacturing these secondgeneration ASVCO2 sensors and installing them on Saildrone USVs to increase our ability to take high-quality ocean carbon measurements at scale around the world. The first Saildrone Explorer to carry a Saildrone-manufactured Gen 2 ASVCO2 was deployed to the Tropical Atlantic as part of the Eurosea mission, led by GEOMAR Helmholtz Centre for Ocean Research Kiel. CO2 data collected during the five-month mission will be used to investigate changes in ocean chemistry and estimate how much additional carbon the ocean might be able to absorb in the future.

Saildrone designs, manufactures, and operates a fleet of the world’s most capable, proven, and trusted uncrewed surface vehicles (USVs). Through a public-private partnership between Saildrone and NOAA PMEL, the

Saildrone USVs with Gen 2 ASVCO2 systems have also been deployed to the Gulf Stream, in partnership with the University of Rhode Island and the European Centre for Medium-Range

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Weather Forecasts. The Google.org-funded mission aims to reduce uncertainties about how, where, and how much human-produced carbon dioxide the Gulf Stream can absorb. Three vehicles will sail back and forth across the current continuously at strategic locations to capture as many ocean features as possible. These two missions are at the leading edge of ocean carbon research, and while they are expected to improve understanding of critical climate processes, which will in turn help guide global climate policy and decision-making, we need broad spatial coverage to fully understand the ocean’s role in the global CO2 cycle and its potential for additional carbon removal. The Global Carbon Budget 2021, released at COP26, uses ocean carbon uptake estimates generated by models and sophisticated

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statistical methods to fill gaps where insitu data is lacking. The models work well, despite a scarcity of data, but they cannot yet reconstruct all the rich, spatial patterns in the dynamic ocean environment, and still have uncertainties that preclude efforts to use these estimates to help verify nationally reported emissions. Systematic, sustained ocean observations made by a global fleet of ocean drones is critical to fully understand the physics, and fluxes, of the exchange of heat and carbon between our ocean and atmosphere. This data will be a crucial part of informing potential solutions to assist in the decarbonization of our atmosphere.

Richard Jenkins is the founder and CEO of Saildrone.

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OFI Joins Ocean Visions as Research Consortium Member

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The Ocean Frontier Institute (OFI) has joined Ocean Visions as a research consortium member to contribute ocean science expertise and ocean assets towards solving some of the largest challenges in the ocean and climate. The OFI, a transnational Canadian organization housed at Dalhousie University and Memorial University, Canada, leads at the frontier of ocean research to inform ocean policy and industry to develop a sustainable blue economy. The OFI will join Ocean Visions, together with leading academic institutions such as Georgia Tech, MIT, and WHOI, and impact partners such as Creative Destruction Lab (CDL) and American Geophysical Union, to design and advance solutions to the growing crisis in our ocean and climate. Ocean Visions connects research institutions, governments, investors, and industry to collaborate on the development, testing, and deployment of scalable and equitable solutions at the ocean-climate nexus with a specific focus on three grand challenges – reversing the climate crisis in the ocean, building resilient coastal systems and communities, and building a climateresilient aquatic food system. Ocean Visions’ goals are well aligned with OFI’s leadership in global carbon observation initiatives and the OFI Large Research Projects in atmosphere-ocean interactions, auditing the Northwest Atlantic carbon sink, improving sustainability of aquaculture, and predicting the future of ocean and coastal infrastructure.

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Ocean Solutions in the Carbon Market by Freya Chay

Ocean-based carbon removal presents unique challenges for those participating in carbon markets. Interest is rapidly increasing in approaches like growing and sinking macroalgae and enhancing ocean alkalinity, but the underlying mechanisms are unfamiliar and complex to most, and there are unresolved scientific questions regarding efficacy and potential off-target impacts. Despite these challenges, the carbon market is making moves toward commodifying ocean-based carbon removal. The market is unlikely to wait for the science, so those who know the science need to pay attention and speak up. When companies buy carbon credits, they claim ownership over climate benefits that other people or projects brought about. Some companies purchase carbon credits to satisfy regulatory obligations, but the majority of carbon credits are transacted in what we call the “voluntary” carbon market. These purchases are motivated by a range of objectives, from philanthropy and public relations to honest interest in making good on climate goals. Although all carbon credits are nominally equivalent to one ton of CO2, they can represent different interactions with the carbon cycle, with varying degrees of assurance as to the reliability and permanence of the 140 The Journal of Ocean Technology, Vol. 17, No. 1, 2022

underlying climate benefit. As global climate goals shift toward emphasizing net zero emissions, savvy buyers like Stripe, Microsoft, and Shopify are recognizing the value of buying not just any carbon credits, but credits that represent a ton of carbon dioxide removed from the atmosphere and stored permanently. (In the future, governments could also pursue carbon removal procurement, but for now most of the action is happening in the private sector.) Over the past two years, my team and I have analyzed over 200 carbon dioxide removal (CDR) proposals submitted in response to corporate procurement processes, spanning a range of sectors including forests, soils, ocean, mineralization, and direct air capture. Interest in ocean-based CDR has been accelerating among both buyers and sellers. Most sellers are early stage projects offering speculative tons of CDR from growing and sinking macroalgae, modifying patterns of upwelling and downwelling, or interacting with ocean alkalinity. Many buyers interested in these tons are both looking to purchase carbon credits and to incentivize the development of novel CDR approaches. When we analyze CDR proposals, our goal is to comment on the scientific plausibility of a project’s claims. Two claims we pay close attention to are volume – the quantity of carbon removal a project claims it can deliver – and permanence – the duration over which carbon storage can be reasonably assured. Along both of these dimensions, ocean projects differ notably from projects in other sectors. Carbon market participants are familiar with solutions like forests. When a tree grows, it removes specific molecules of CO2 from the atmosphere via photosynthesis and stores them in its woody tissues. People can see the tree, measure its growth and biomass directly, and track how long the carbon stays there. Forest-based carbon credits have Copyright Journal of Ocean Technology 2022



their fair share of challenges – especially when it comes to evaluating whether they reflect new, or additional, activities relative to what would have happened otherwise – but checking their volume and permanence claims is fairly straightforward, both conceptually and practically. In contrast, ocean projects – especially those interacting with ocean alkalinity – rely on carbon removal mechanisms that are unfamiliar to most buyers. These mechanisms involve chemical equilibria and more indirect forms of atmospheric carbon removal, which require a shift in thinking to understand and evaluate. In addition, key questions around measurement, reporting, and verification remain unanswered, but will need resolution in order to substantiate market claims. Similarly, as demand grows specifically for tons of permanent CDR, buyers are learning to distinguish short duration projects – like those interacting with forests or soils on the order of decades – from projects that result in carbon storage on effectively permanent timescales. However, the permanence of many ocean-based CDR approaches falls somewhere in between, and in many cases we lack methods for reliably estimating or measuring that permanence. Copyright Journal of Ocean Technology 2022

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Part of the reason it is hard to gain confidence in volume and permanence claims made by ocean-based CDR projects is that fundamental questions about the science and practice of these approaches remain unanswered – a fact highlighted in a recent National Academy of Sciences report. For that reason, many of the CDR proposals we have reviewed might be better suited for research funding than they are for procurement-based funding. That said, given market interest, it seems likely that tensions between selling speculative tons and rigorously, carefully acknowledging uncertainties will continue. We hope that as the relevant science progresses, market participants’ understanding and ability to measure the volume and permanence of ocean-based CDR will improve. However, complexity leaves room for obfuscation – we have seen people take advantage of uncertainty in the carbon market before. As excitement about ocean-based carbon removal grows, it will be important for those who know the science to track claims carefully and help others do the same. Freya Chay is a program associate with CarbonPlan and has an interdisciplinary background in decarbonization. www.carbonplan.org

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Climate Change and Seaweed Cultivation – Somewhere Between Hope and Hype

by Bill Collins

Seaweeds are naturally occurring marine algae that have been pursued globally for millennia. Scholars refer to the “Kelp Highway” as delivering food, medicines, and materials supporting human migration along the coast of the Northeast Pacific. In the early 20th century in Asia, the global demand for processed and stabilized food and ingredients inspired industrial-scale production of seaweed for carrageenan and alginates. Today, the seaweed sector is now a very important part of the aquaculture triangle in the western world, providing natural solutions to the climate crisis in the areas of food security, ocean health, and carbon mitigation strategies. The Business of Seaweed Cultivation Seaweed farming is analogous to land farming, with “seed” being sown in “rows” of rope lines suspended between buoys in the ocean. Perhaps one difference is that once seaweed seed has been planted, there is nothing the farmer can do to stimulate growth. Success relies on the natural environment to deliver the sunlight and ocean nutrients required. Financial success is a function of unit economics (internal value stream drivers) and market forces (demand influencing pricing). The value stream can be broken down into basic components: producing seed, planting, harvesting, and transporting the crop to processing facilities. The Value of Seaweed The price paid for seaweed, like most other raw materials, is a function of the market into which it is sold and typically obeys the laws of supply and demand. It can range from a low value as fertilizer, through value as dried sodium 142 The Journal of Ocean Technology, Vol. 17, No. 1, 2022

alginate ($0.35 per kilo and high volumes), up to the body products industry ($25 per dry kilo but low volumes). As a human food product, a western co-packer might pay $2 per dry kilo enroute to a 40% retail gross margin. The going rate for North American fresh-frozen seaweed is about $2.50 per kilo. Seaweed, however, unlike most other raw materials, has a value beyond the unit price. As seaweed grows it offers a bounty of ecosystem services: capturing carbon and nitrogen, producing oxygen, alleviating ocean acidification, and offering habitat to a multitude of species. Seaweed forests can act as a buffer to erosional effects of nearshore waves. If a dollar value of these ecosystem services could be agreed upon, cultivating seaweed for these services alone may be justified. In the realm of ecosystem services valuation, carbon capture and sequestration is the most mature. With guidance from international scientific bodies such as the Intergovernmental Panel on Climate Change, commodity pricing targets for carbon as a proxy for the negative economic impact of greenhouse gases (GHGs) are set. It is with the backdrop of carbon pricing and an understanding of the unit economics in seaweed cultivation that the value proposition arises as a means to capture and dispose of carbon. One caveat is that for ocean-based carbon removal via seaweed cultivation to have the biggest impact, the seaweed must be permanently sequestered at great depth (> 1,000m). Today the economics of growing seaweed in North America only for the purposes of carbon sequestration are challenging where production costs exceed credits generated. However, with increased scale of production, reducing sequestration costs, and innovation in biotech to improve yield, the future value proposition may exist. Copyright Journal of Ocean Technology 2022

Homeward Bound



The Carbon Farming Project, conducted by Oceans 2050, is investigating the value of coastal seaweed farming carbon capture in coastal sediments as a means to add to a farm’s revenue stream through the volunteer offsets market. Seaweed Cultivation and Climate Change Seaweed aquaculture perhaps has greater value in the fight against climate change than ocean carbon disposal. Unless and until the impact of GHGs are reduced, climate change will reduce our ability to grow food on land. The ocean covers about 70% of our planet yet yields only 2% of food. The World Bank Group estimates that by 2050 10% of the world’s food supply could come from cultivated seaweed. Science has also shown that, when some species of seaweed are used as a cattle feed supplement, more than 90% of enteric methane can be avoided. Furthermore, it has also been shown that seaweed improves feed conversion efficiency by more than 15% offering less reliance on terrestrial grown feed. Copyright Journal of Ocean Technology 2022

The connection between hope and seaweed as a climate change mitigator is embedded with innovation opportunities, most importantly the need to drive costs down. The U.S. National Academies of Sciences, Engineering, and Medicine recently recommended that $235 million should be invested in seaweed farming as an ocean-based form of carbon disposal. The government of South Australia recently invested $200 million in the creation of a marine bio-industries sector, some of which supports seaweed agrifeed. And the European community has been enjoying at least a decade of investment in seaweed. With the largest coastline in the world, it is time for Canada to show leadership through investment and innovation in ocean technology to take advantage of our three coasts which offer unprecedented access to natural solutions to climate change. Bill Collins is chairman of Cascadia Seaweed, creating downstream activities in science, human food, and agrifeeds. www.cascadiaseaweed.com

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Parting Notes Seaweed Farming and Carbon Capture On Fogo Island, N.L., our lives are inextricably linked with the sea. The decline of the inshore fishery, Fogo Island’s one and only industry, was devastating, but it also heralded a new era of self-discovery. The fear of losing their island home and identity drove Fogo Islanders to pivot in times of hardship. Creating the Fogo Island Cooperative Society, in 1967, in response to then-Premier Joey Smallwood’s plans for resettlement, and then of registered charity Shorefast in 2003, helped to rebuild Fogo Island into a thriving and resilient coastal community. Now, with the introduction of seaweed cultivation around Fogo Island, we are investing in environmentally regenerative projects of economic, social, and cultural value – allowing sustainable ecosystems and economies to exist hand in hand on Fogo Island, for the benefit of generations to come. https://shorefast.org www.fogoislandcoop.com/home

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