@article {dillon_cost-optimal_2022,
	title = {Cost-optimal wave-powered persistent oceanographic observation},
	journal = {Renewable Energy},
	volume = {181},
	year = {2022},
	pages = {504{\textendash}521},
	abstract = {Historically, energy constraints have limited the spatial range, endurance and capabilities of ocean observation systems. Recently developed wave energy conversion technologies have the potential to help overcome these limitations by providing co-located and persistent power generation for ocean observations, enabling new opportunities for ocean research. In this paper, we develop the first techno-economic model for wave-powered ocean observation systems and use the model to study system characteristics and cost drivers. Our model utilizes time-domain simulation and optimization to identify cost-optimal system characteristics and to estimate capital and operational costs. Using our model, we evaluate the use of wave energy to power a 200~W ocean observation system deployed for five years at five unique geographic locations. We found that, depending on the geographic location, cost-optimal wave energy powered systems require an ≈ 0.5{\textendash}3~kW wave energy converter and an ≈ 15-50~kWh battery. The corresponding range of power system costs over the deployment duration is between \$110,800 and \$673,200. We build on these results by performing a sensitivity analysis of key model parameters and identifying the potential economic impact of future technology advancements. Overall, our results indicate that characteristics of the geographic location, power system durability, and electrical power demand are key drivers of power system economics for ocean observing.},
	keywords = {blue economy, Ocean observation, Techno-economic analysis, Wave energy},
	issn = {0960-1481},
	doi = {10.1016/j.renene.2021.08.127},
	url = {https://www.sciencedirect.com/science/article/pii/S0960148121012957},
	author = {Dillon, Trent and Maurer, Benjamin and Lawson, Michael and Jenne, Dale Scott and Manalang, Dana and Baca, Elena and Polagye, Brian}
}
@article {RN113,
	title = {Global Observing Needs in the Deep Ocean},
	journal = {Frontiers in Marine Science},
	volume = {6},
	year = {2019},
	pages = {241},
	type = {Journal Article},
	abstract = {The deep ocean below 200 m water depth is the least observed, but largest habitat on our planet by volume and area. Over 150 years of exploration has revealed that this dynamic system provides critical climate regulation, houses a wealth of energy, mineral, and biological resources, and represents a vast repository of biological diversity. A long history of deep-ocean exploration and observation led to the initial concept for the Deep-Ocean Observing Strategy (DOOS), under the auspices of the Global Ocean Observing System (GOOS). Here we discuss the scientific need for globally integrated deep-ocean observing, its status, and the key scientific questions and societal mandates driving observing requirements over the next decade. We consider the Essential Ocean Variables (EOVs) needed to address deep-ocean challenges within the physical, biogeochemical, and biological/ecosystem sciences according to the Framework for Ocean Observing (FOO), and map these onto scientific questions. Opportunities for new and expanded synergies among deep-ocean stakeholders are discussed, including academic-industry partnerships with the oil and gas, mining, cable and fishing industries, the ocean exploration and mapping community, and biodiversity conservation initiatives. Future deep-ocean observing will benefit from the greater integration across traditional disciplines and sectors, achieved through demonstration projects and facilitated reuse and repurposing of existing deep-sea data efforts. We highlight examples of existing and emerging deep-sea methods and technologies, noting key challenges associated with data volume, preservation, standardization, and accessibility. Emerging technologies relevant to deep-ocean sustainability and the blue economy include novel genomics approaches, imaging technologies, and ultra-deep hydrographic measurements. Capacity building will be necessary to integrate capabilities into programs and projects at a global scale. Progress can be facilitated by Open Science and Findable, Accessible, Interoperable, Reusable (FAIR) data principles and converge on agreed to data standards, practices, vocabularies, and registries. We envision expansion of the deep-ocean observing community to embrace the participation of academia, industry, NGOs, national governments, international governmental organizations, and the public at large in order to unlock critical knowledge contained in the deep ocean over coming decades, and to realize the mutual benefits of thoughtful deep-ocean observing for all elements of a sustainable ocean.

},
	keywords = {biodiversity, blue economy, deep sea, essential ocean variables, Ocean observation, ocean sensors},
	issn = {2296-7745},
	doi = {10.3389/fmars.2019.00241},
	url = {https://www.frontiersin.org/article/10.3389/fmars.2019.00241},
	author = {Levin, Lisa A. and Bett, Brian J. and Gates, Andrew R. and Heimbach, Patrick and Howe, Bruce M. and Janssen, Felix and McCurdy, Andrea and Ruhl, Henry A. and Snelgrove, Paul and Stocks, Karen I. and Bailey, David and Baumann-Pickering, Simone and Beaverson, Chris and Benfield, Mark C. and Booth, David J. and Carreiro-Silva, Marina and Cola{\c c}o, Ana and Ebl{\'e}, Marie C. and Fowler, Ashley M. and Gjerde, Kristina M. and Jones, Daniel O. B. and Katsumata, K. and Kelley, Deborah and Le Bris, Nadine and Leonardi, Alan P. and Lejzerowicz, Franck and Macreadie, Peter I. and McLean, Dianne and Meitz, Fred and Morato, Telmo and Netburn, Amanda and Pawlowski, Jan and Smith, Craig R. and Sun, Song and Uchida, Hiroshi and Vardaro, Michael F. and Venkatesan, R. and Weller, Robert A.}
}
