Enhanced weathering of kimberlite residues in a field experiment: implications for carbon removal quantification and mine waste valorization
Bibliographic record
Abstract
Scaling up enhanced rock weathering (ERW) will require gigatonnes of suitable rock, which could include mine wastes such as the estimated 3.9 Gt of kimberlite residues from historic diamond mining. Here, we conducted meter-scale field experiments (2021–2023) in Ontario, Canada, to assess fine processed kimberlite residues for ERW and test carbon-based methods for CO 2 removal (CDR) quantification, including CO 2 fluxes, and measurements of soil and porewater inorganic carbon. A control plot consisted of local calcareous (16.1 wt.% calcite) Brunisolic soil to assess background weathering rates. Two soil plots were amended with 20 and 40 kg of kimberlite residues from the Gahcho Kué Diamond Mine (Northwest Territories, Canada) that contained 30.2 wt.% lizardite [Mg 3 Si 2 O 5 (OH) 4 ], 9.4 wt.% forsterite (Mg 2 SiO 4 ), and 1.9 wt.% calcite (CaCO 3 ). Coinciding with increases in Mg and Si, dissolved inorganic carbon increased in porewaters with kimberlite dosage (amended: 64–118 mg C/L, control: 56 ± 14 mg C/L), demonstrating CO 2 solubility trapping. Water chemistry data, coupled with a water budget derived from weather and soil moisture data, were used to determine CDR rates. The removal rates by the kimberlite residues were up to 1.4 t CO 2 /ha over 3 years calculated using porewater inorganic carbon loadings, with Ca and Si loadings allowing for partitioning of rates into removal contributions by kimberlite-derived carbonate weathering (~75%) and silicate weathering (~25%), respectively. CO 2 fluxes and soil inorganic carbon proved ineffective for CDR quantification, given the high effluxes due to soil respiration and high and variable carbonate content of the soils, respectively. Stable carbon isotope data demonstrated that the removed CO 2 was derived from organic carbon, suppressing soil CO 2 effluxes to the atmosphere. This study has implications for repurposing environmentally safe mine wastes for ERW with the potential to reduce net CO 2 emissions and storage and remediation costs in the mining industry. We highlight similarities between kimberlite residues and basalt fines, a common quarry by-product used in ERW, advocating for the use of processed rock from current and legacy mining operations for CDR. Further, our CDR monitoring approaches that effectively distinguish between silicate and carbonate weathering may be utilized in other ERW applications.
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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 | 0.000 |
| 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".