Feasibility of in-situ carbon mineralization in serpentinite via shallow injection, British Columbia, Canada
Bibliographic record
Abstract
Carbon storage via shallow CO2 injection and mineralization in subsurface geologic formations has been demonstrated at the kilotonne scale in basalt (e.g., Hellisheidi, Iceland) but not in ultramafic rock. This type of storage dissolves CO2 in water that is then injected underground into shallow rock formations from 300-2000 m depth, where it reacts and forms permanent carbonate minerals. This project assesses the potential for CO2 injection into serpentinite, specifically within British Columbia, Canada.Site selection included multi-criteria index overlay analysis for logistical factors (e.g. water, electricity, access) and evaluation of geological data to prioritize which sites contain 1 km2 mapped voluminous serpentinite. Of the 746 mapped ultramafic formations, 84 formations within 21 areas meet threshold criteria, and of these, three stand out with clearly higher potential. These are 1) the Shulaps complex, 2) the Coquihalla serpentine belt, and 3) the Tulameen intrusion, all in southwest British Columbia. These areas have in common that they are close to infrastructure, are located in regions with higher annual temperatures, and have known geological and geophysical characteristics indicative of serpentinite. The Shulaps and Coquihalla are mantle massifs and mainly composed of serpentinized harzburgite, and Tulameen is an Alaskan-type ultramafic intrusion with a serpentinized dunite core.Six different carbon storage potential estimates using volume limitations, dissolution, and reactivity rates from experiments, and natural analogues are shown for the three potential sites, for Shulaps 141.2-18,682 MtCO2, for Coquihalla 9.416-1,245 MtCO2, and for Tulameen 2.825-373.6 MtCO2. Fieldwork observations and preliminary results show, as expected, heterogeneity of protoliths, serpentinization extent, and fracture density between the areas. Coquihalla was selected for a proposed pilot injection study because of its high serpentinization extent (>90%, suggesting high reactivity), continuous high fracture density (suggesting adequate injectivity), site accessibility through existing road systems, and proximity to electricity.An additional aspect of project development is engagement with local communities. All three of the top-ranked sites fall within traditional lands of First Nations peoples, and we conducted early engagement with 22 First Nations or alliances. The priorities for engagement were to inform people about the project and its implications, get consent for fieldwork, have a discussion, and start relationship building.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".