CO2 mineralization of kimberlite residues from the Gahcho Kué Diamond Mine, Northwest Territories, Canada
Bibliographic record
Abstract
Kimberlite residues generated at diamond mines have the potential to substantially reduce net greenhouse gas emissions and contribute towards carbon-neutral mining. As part of the De Beers CarbonVault™, we conducted experiments using fine kimberlite residues from the Gahcho Kué Diamond Mine, Northwest Territories, Canada, to assess the mine's potential for CO 2 sequestration. Batch CO 2 leach tests indicate a CO 2 sequestration potential of 12 kg CO 2 /t based on easily extractable cations from non-carbonate sources. However, an evaluation of the short-term reactivity of the residues post-deposition revealed the ability to sequester 0.86 kg CO 2 /t when residues were allowed to dry through optimal water saturation (30–40 %). Furthermore, year-long weathering columns determined a CO 2 removal rate of 0.63 kg CO 2 /t/yr, primarily through mineral trapping. Extrapolating these rates to current annual residue production and emissions indicates that 7 % of the mine's estimated CO 2 e emissions could be sequestered over the life of mine. These rates are based on optimal storage conditions that keep residues exposed for long periods, which should be a consideration of residue management practices during the operating life of the mine and post closure. Further on-site investigations are necessary to refine rates and account for climatic conditions. Assessments conducted in this study affirm the suitability of Gahcho Kué residues for CO 2 sequestration and present strategies for optimizing this process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".