Reactive Transport Modeling of Natural Carbon Sequestration in Ultramafic Mine Tailings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Atmospheric CO 2 is naturally sequestered in ultramafic mine tailings as a result of the weathering of serpentine minerals [Mg 3 Si 2 O 5 (OH) 4 ] and brucite [Mg(OH) 2 ], and subsequent mineralization of CO 2 in hydrated magnesium carbonate minerals, such as hydromagnesite [Mg 5 (CO 3 ) 4 (OH) 2 ·4H 2 O]. Understanding the CO 2 trapping mechanisms is key to evaluating the capacity of such tailings for carbon sequestration. Natural CO 2 sequestration in subaerially exposed ultramafic tailings at a mine site near Mount Keith, Australia is assessed with a process‐based reactive transport model. The model formulation includes unsaturated flow, equations accounting for energy balance and vapor diffusion, fully coupled with solute transport, gas diffusion, and geochemical reactions. Atmospheric boundary conditions accounting for the effect of climate variations are also included. Kinetic dissolution of serpentine, dissolution‐precipitation of brucite and primary carbonates—calcite (CaCO 3 ), dolomite [MgCa(CO 3 ) 2 ], magnesite (MgCO 3 ), as well as the formation of hydromagnesite, halite (NaCl), gypsum (CaSO 4 ·2H 2 O), blödite [Na 2 Mg(SO 4 ) 2 ·4H 2 O], and epsomite [MgSO 4 ·7H 2 O]—are considered. Simulation results are consistent with field observations and mineralogical data from tailings that weathered for 10 yr. Precipitation of hydromagnesite is both predicted and observed, and is mainly controlled by the dissolution of serpentine (the source of Mg) and equilibrium with CO 2 ingressing from the atmosphere. The predicted rate for CO 2 entrapment in these tailings ranges between 0.6 and 1 kg m −2 yr −1 . However, modeling results suggest that this rate is sensitive to CO 2 ingress through the mineral waste and may be enhanced by several mechanisms, including atmospheric pumping.
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.
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 | 0.001 |
| 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 it