Measuring Methane in the Arctic Ocean - From legal framework to time series analysis via technology innovation

• Main Author: Dølven, Knut Ola
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: UiT Norges arktiske universitet 2022
• Subjects: VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Oseanografi: 452; VDP::Mathematics and natural science: 400::Geosciences: 450::Oceanography: 452; DOKTOR-004; Arctic; Arctic Ocean; Climate change; Spitsbergen
• Online Access: https://hdl.handle.net/10037/24357

Understanding how the earth system interacts with ongoing climate change is important to find a realistic route towards a sustainable future. The impact of Arctic seabed methane seepage on contemporary and future climate is still poorly constrained, described, and quantified. An important limiting factor in our understanding of seabed seepage in the Arctic is a lack of in situ measurements; however, remoteness and harsh environmental conditions make data acquisition difficult. The aim of this thesis is to improve understanding of and ability to measure methane in the Arctic Ocean via inter-disciplinary work, method development and time-series analysis. To fill crucial data gaps and increase the general data coverage in the region demands implementation of innovative technology and increased research activity. Legal scholars have identified emerging legal gaps associated with this increased activity and regulation of marine scientific research. However, our inter-disciplinary assessment indicates that an evolutionary interpretation of the legal framework is currently adequate to regulate and facilitate current conduct of marine scientific research in the Arctic Ocean. We obtained a unique data set from two intense seep sites (at 91 and 246 meter depth) offshore West Spitsbergen by deploying two autonomous ocean observatories which recorded respectively 10 and 3 month time-series of bottom water physical and chemical parameters between July 2015 and May 2016. High short term variability (<∼1000 nmol L −1 on hourly time-scales) were observed which were partly explained by changing ocean currents and location of nearby seeps. A seasonal variation with lower (∼halved) concentrations and variability in winter season was coupled with increased water column mixing. No clear effect of tidal hydrostatic pressure changes were observed, but a negative correlation between methane and temperature at the deepest seep site aligns well with hypothesized seasonal blocking of lateral sedimentary methane pathways. We highlighted and quantified potential uncertainties that can arise from high short-term variability in budget estimates. To enable direct observations of bubble release, we developed a method for using ADCP to monitor seabed seepage. The method makes it possible to integrate all backscatter data from the ADCP and monitor seepage activity on the seafloor by modeling bubble transport in the water column. Using this model, the ADCP at the 91 meter observatory uncovered continuous ongoing seepage to the north of the observatory and a stationary seep configuration. Several chemical sensors, including conventional dissolved methane sensors, rely on separating the medium of interest (e.g. methane) from the measured medium (e.g. water) using equilibrium partitioning across a membrane. This process causes slow response times, which is problematic for applications where steep gradients are expected such as at our observatory location, in profiling or other highly dynamic domains. We developed a new technique to deconvolve slow response signals and obtain fast response data by using the theoretical framework of statistical inverse theory. This method provides an explicit uncertainty estimate, quality assessment of the result and no extra input parameters other than what already provided in standard calibration procedures. There is a vast range of questions that are relevant to pursue to increase our understanding of seabed methane seepage in the Arctic Ocean. In light and line of this work, future efforts to improve quantification of methane and methane seepage could focus on assessing uncertainty in various approaches to budget estimates, further validate new methodology presented herein and use these on e.g. autonomous vehicles capable of providing large volumes of high resolution data within short time spans.