Publications

Publications (Foto: J.-R. Lippels / Hereon)

Following publications have been announced by our Institute of Carbon Cycles. For further information please contact Dr Helmuth Thomas,  co-author of the publications:

Duke, P.J., Else, B.G.T., Jones, S.F., Marriot, S., Ahmed, M.M.M., Nandan, V., Butterworth, B., Gonski, S.F., Dewey, R., Sastri, A., Miller, L.A., Simpson, K.G., & Thomas, H. (2021): Seasonal marine carbon system processes in an Arctic coastal landfast sea ice environment observed with an innovative underwater sensor platform. Elementa: Science of the Anthropocene 21 January 2021; 9 (1): 00103, doi:10.1525/elementa.2021.00103

Abstract:

Studying carbon dioxide in the ocean helps to understand how the ocean will be impacted by climate change and respond to increasing fossil fuel emissions. The marine carbonate system is not well characterized in the Arctic, where challenging logistics and extreme conditions limit observations of atmospheric CO₂ flux and ocean acidification. Here, we present a high-resolution marine carbon system data set covering the complete cycle of sea-ice growth and melt in an Arctic estuary (Nunavut, Canada). This data set was collected through three consecutive yearlong deployments of sensors for pH and partial pressure of CO₂ in seawater (pCO_2sw) on a cabled underwater observatory. The sensors were remarkably stable compared to discrete samples: While corrections for offsets were required in some instances, we did not observe significant drift over the deployment periods. Our observations revealed a strong seasonality in this marine carbon system. Prior to sea-ice formation, air–sea gas exchange and respiration were the dominant processes, leading to increasing pCO_2sw and reduced aragonite saturation state (Ω_Ar). During sea-ice growth, water column respiration and brine rejection (possibly enriched in dissolved inorganic carbon, relative to alkalinity, due to ikaite precipitation in sea ice) drove pCO_2sw to supersaturation and lowered Ω_Ar to < 1. Shortly after polar sunrise, the ecosystem became net autotrophic, returning pCO_2sw to undersaturation. The biological community responsible for this early switch to autotrophy (well before ice algae or phytoplankton blooms) requires further investigation. After sea-ice melt initiated, an under-ice phytoplankton bloom strongly reduced aqueous carbon (chlorophyll-a max of 2.4 µg L^–1), returning Ω_Ar to > 1 after 4.5 months of undersaturation. Based on simple extrapolations of anthropogenic carbon inventories, we suspect that this seasonal undersaturation would not have occurred naturally. At ice breakup, the sensor platform recorded low pCO_2sw (230 µatm), suggesting a strong CO₂ sink during the open water season.

Omar, A.M., García-Ibáñez, M.I., Schaap, A., Oleynik, A., Esposito, M., Jeansson, E., Loucaides, S., Thomas, H., & Alendal, G. (2021): Detection and quantification of CO2 seepage in seawater using the stoichiometric C_seep method: Results from a recent subsea CO2 release experiment in the North Sea. International Journal of Greenhouse Gas Control, Volume 108, 2021, 103310, doi:10.1016/j.ijggc.2021.103310

Abstract:

Carbon Capture and Storage (CCS) is a potential significant mitigation strategy to combat climate change and ocean acidification. The technology is well understood but its current implementation must be scaled up nearly by a hundredfold to become an effective tool that helps meet mitigation targets. Regulations require monitoring and verification at storage sites, and reliable monitoring strategies for detection and quantification of seepage of the stored carbon need to be developed. The C_seep method was developed for reliable determination of CO₂ seepage signal in seawater by estimating and filtering out natural variations in dissolved inorganic carbon (C). In this work, we analysed data from the first-ever subsea CO₂ release experiment performed in the north-western North Sea by the EU STEMM−CCS project. We successfully demonstrated the ability of the C_seep method to (i) predict natural C variations around the Goldeneye site over seasonal to interannual time scales; (ii) establish a process-based baseline C concentration with minimal variability; (iii) determine CO₂ seepage detection threshold (DT) to reliably differentiate released−CO₂ signal from natural variability and quantify released−CO₂ dissolved in the sampled seawater. DT values were around 20 % of the natural C variations indicating high sensitivity of the method. Moreover, with the availability of DT value, the identification of released−CO₂ required no pre-knowledge of seepage occurrence, but we used additional available information to assess the confidence of the results. Overall, the C_seep method features high sensitivity, automation suitability, and represents a powerful future monitoring tool both for large and confined marine areas.