A high-resolution nested model to study the effects of alkalinity additions in Halifax Harbour, a mid-latitude coastal fjord
Bibliographic record
Abstract
Abstract. Surface ocean alkalinity enhancement (OAE), through the release of alkaline materials, is an emerging marine carbon dioxide removal technology that could increase the storage of anthropogenic carbon in the ocean. Observations collected during recent and on-going field trials will provide important information on the feasibility and effects of alkalinity additions on carbon cycling and study ecological responses. However, given the scales involved (24/7 continuous addition, meters to hundreds/thousands of kilometers and minutes to months for alkalinity dispersion) observations, even with the use of autonomous platforms, will remain inherently sparse and limited. Alone, they cannot provide a comprehensive quantification of the effects of OAE on the carbonate system, and ultimately of the net air-sea CO2 fluxes. Numerical models, informed and validated by field observations, are therefore essential to OAE deployments and the measurement, reporting, and verification (MRV) of any resulting carbon uptake. They can help guide fieldwork design, including optimal design of measurement monitoring networks, provide forecasts of the ocean state, simulate the effects of alkalinity additions on the seawater carbonate system, and allow one to quantify net CO2 uptake. Here we describe a coupled physical-biogeochemical model that is specifically designed for coastal OAE. The model is an implementation of the Regional Ocean Modelling System (ROMS) in a nested grid configuration with increasing spatial resolution from the Scotian Shelf to Halifax Harbour (coastal fjord, eastern Canada), a current test site for operational alkalinity addition. The biogeochemical model simulates oxygen dynamics, carbonate system processes (including air-sea gas exchange), and feedstock properties (dissolution, sinking). We present a multi-year hindcast validated against the long-term weekly time series available for a long-term monitoring station at the deepest part of Halifax Harbour, as well as alkalinity addition simulations at various locations inside and outside the harbour to show the model’s capabilities for assessing the effects of OAE at this coastal site.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".