Alkaline Mineral Soil Amendment: A Climate Change ‘Stabilization Wedge’?
Bibliographic record
Abstract
Extreme climate change due to heat-trapping gases, especially carbon dioxide, necessitates its mitigation. In this context, the carbon dioxide sequestration technology of enhanced weathering has for years been investigated, with a possible implementation strategy via alkaline mineral soil amendment being more recently proposed. Candidate materials for enhanced weathering include calcium and magnesium silicates, most notably those belonging to the olivine, pyroxene and serpentine groups of minerals, given their reactivity with CO2 and global availability. When these finely crushed silicate rocks are applied to the soil, the alkaline earth metal cations released during mineral weathering gradually react with carbonate anions and results in the formation of pedogenic carbonates, which, over time, and under the right conditions, can accumulate in the soil. This review paper critically reviews the available literature on alkaline mineral soil amendments and its potential to sequester enough CO2 to be considered a climate change ‘stabilization wedge’. Firstly, evidence of how agricultural soil can serve as a carbon sink in discussed, based on the observed accumulation of inorganic carbon in alkaline mineral-amended soils. Secondly, the impact of alkaline minerals on agricultural soil and crops, and the factors determining the rate of the weathering process are assessed. Lastly, the CO2 sequestration potential via alkaline mineral soil amendment is quantified according to an idealized shrinking core model, which shows that it has the potential to serve as a climate change stabilization wedge.
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) | 0.016 | 0.003 |
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; both teacher heads agree on what is shown here.
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".