Macroalgae Cultivation for Ocean CDR: An Idealized Numerical Study

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• Si Chen, DAMTP
• Monday 06 February 2023, 13:00-14:00
• MR5, CMS.

If you have a question about this talk, please contact Prof. John R. Taylor.

The cultivation of macroalgae in offshore waters has been proposed as an ocean-based carbon dioxide removal strategy to mitigate the adverse impacts of climate change. However, many uncertainties about this strategy remain, including the possible impact on microalgal primary production, the influence on carbonate chemistry, timescales involved in the air-sea CO2 flux, and the efficiency of macroalgal carbon export to the deep ocean. Here, we couple a kelp growth model with a biogeochemical model and conduct idealized numerical experiments to address some of these questions.

Specifically, we use an intermediate complexity ocean biogeochemical model (LOBSTER) to simulate primary production and biogeochemical interactions among nitrate (NO3), ammonium (NH4), phytoplankton (P), zooplankton (Z), small detritus (D), large detritus (DD), and dissolved organic matter (DOM), plus dissolved inorganic carbon (DIC) and alkalinity (ALK). The model is forced with an idealized seasonal cycle of temperature, mixed layer depth, salinity, and photosynthetic available radiation data, and the result is compared with the Mercator Global Ocean Biogeochemistry Analysis and Forecast data.

The biogeochemical model is then coupled with a model of kelp growth which is a function of environmental variables including the surrounding water temperature, nutrient content, and current speed. The coupled model enables the identification of the impacts of kelp on biogeochemical cycles, natural primary production, carbon export, and air-sea CO2 flux, evaluating kelp as a potential carbon dioxide removal strategy. By varying kelp concentration and geographic locations, for example, we can answer questions as to how and where kelp can be deployed to maximize kelp growth and carbon sequestration while minimizing harmful impacts.

This talk is part of the Quantitative Climate and Environmental Science Seminars series.

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