Observations of Shallow Methane Bubble Emissions From Cascadia Margin

Michel, Anna P. M.; Preston, Victoria; Fauria, Kristen E.; Nicholson, David P.

doi:10.3389/feart.2021.613234

Cited by 4 publications

(2 citation statements)

References 33 publications

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“…When methane is supersaturated in seawater, the methane in seawater can be emitted to the atmosphere driven by chemical potential. The methane fluxes to the atmosphere are calculated by the diffusive exchange equation (Solomon et al, 2009;Michel et al, 2021):…”

Section: Methane Flux To the Atmospherementioning

confidence: 99%

Advance in Numerical Simulation Research of Marine Methane Processes

Sun

Wang

et al. 2022

Front. Earth Sci.

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Understanding the modern marine methane processes, which can profoundly affect global climate and have far-reaching impacts on human living environments, is critical for research on the global carbon cycle. Thus, modeling of marine methane processes has attracted increasing attention due to models can accurately simulate and predict the environmental effects of methane on marine and atmospheric ecosystems. In this study, we review the applications of modeling works to marine methane processes, including methanogenesis in sediments, transport and reaction of methane in sediments and seawater, and marine methane emissions to the atmosphere. Compiled a large database of global methanogenesis rates and methane fluxes to the sulfate-methane transition zone, we estimate that the global methanogenesis budget in marine sediments is ∼0.87 Tmol yr−1 and global sedimentary dissolved inorganic carbon produced by anaerobic oxidation of methane is ∼8.9 Tmol yr−1. In addition, although anaerobic oxidation of methane in sediments and aerobic oxidation of methane in seawater act as primary filters to prevent methane leakage from sediments to the hydrosphere as well as the atmosphere, large masses of methane in extreme seafloor environments (e.g., mud volcanic eruptions and hydrate leakage) can still escape microbial oxidation and leakage to seawater or the atmosphere. There is still a lack of models that simulate methane in these extreme marine environments. Therefore, more modeling works are needed to assess the efficiency of marine ecosystems, including sediments and hydrosphere, in filtering methane in the event of large-scale methane leakage from the seafloor. This study provides an interdisciplinary view of methane processes in marine systems and helps identify future directions in the modeling of methane processes in marine system.

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Section: Methane Flux To the Atmospherementioning

confidence: 99%

Advance in Numerical Simulation Research of Marine Methane Processes

Sun

Wang

et al. 2022

Front. Earth Sci.

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“…Methane measurements in ppm were subsequently converted to nanomolar (nM) using coincident salinity and temperature measurements observed by the rosette CTD. Calibration of the GGA was completed using gas standards from Mesa Gas(Michel et al 2021). During the transect, nine of the twelve bottles from Leg 2 were processed using the DGEU and GGA for methane analysis.…”

mentioning

confidence: 99%

Perceive, predict, and plan: robotic expeditionary science in oceanic spatiotemporal fields

Preston¹

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An improved understanding of our ocean would allow us to characterize the largest habitable biosphere on planet Earth, quantify the geochemical processes that control Earth’s climate, and develop responsible regulations for controlling the natural resources stored in its depths. Expeditionary science is the art of collecting in situ observations of an environment to build approximate models of underlying properties that move us towards this understanding. Robotic platforms are a critical technology for collecting observations of the ocean. Depth-capable autonomous underwater vehicles (AUVs) are commonly used to build static maps of the seafloor by executing pre-programmedsurveys. However, there is growing urgency to generate rich data products of spatiotemporal distributions that characterize the physics and chemistry of the deep ocean biogeosphere. In this thesis, the problem of charting dynamic deep sea hydrothermal plumes with depth-capable AUVs is investigated. Effectively collecting samples of geochemical plumes using the operationally preferred strategy of pre-specifying surveys requires access to a dynamics model of the advective currents, bathymetric updrafts, and turbulent mixing at a hydrothermal site. In practice, however, access to this information is unavailable, imperfect, or only partially known, and so a model of plume dynamics must be inferred from observations and subsequently leveraged to improve future sampling performance. As most in situ scientific instruments yield point-measurements, considerable uncertainty is placed over the form of the dynamics in purely data-driven solutions. Challenges related to planning under uncertainty for geochemical surveys in the deep ocean are addressed in this thesis by embedding scientific knowledge as a strong inductive prior for tractable model learning and decision-making. Algorithmic contributions of this thesis show how plumes can be perceived from field data, their fate predicted far into the future (e.g., multiple days), and informative fixed trajectories planned which place an AUV in the right place at the right time. Scientific assessment of observational data collected with AUV Sentry during field trials in the Guaymas Basin, Gulf of California are interwoven with algorithmic analyses, demonstrating how intelligent perception, prediction, and planning enables novel insights about hydrothermal plumes.

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