Are enhanced rock weathering rates overestimated? A few geochemical and mineralogical pitfalls
Bibliographic record
Abstract
There is considerable uncertainty when quantifying carbon dioxide removal (CDR) from enhanced rock weathering (ERW). Faster CDR rates mean ERW may significantly impact climate change mitigation, and more carbon credits will financially benefit private companies. However, overestimating CDR risks undermining ERW if meaningless carbon credits are counted. Here, we aim to contribute to the discussion of CDR quantification by describing three potential pitfalls relating to the geochemical and mineralogical compositions of rock powders. First, rock powders used for ERW are often mineralogically complex and may initially exhibit fast dissolution rates due to reactive surfaces and phases, leading to overestimating long-term CDR rates. Second, the dissolution of accessory carbonates within ERW rock powders will tend to dominate cation and dissolved inorganic carbon fluxes, which, if not identified, can be misconstrued as silicate weathering and overestimate CDR. Third, methods that rely on measuring cations may be prone to misinterpretation as cations will often not be balanced with dissolved inorganic carbon, e.g., during strong acid weathering. As another example, mineral dissolution during solid-phase testing (e.g., cation exchange) is also unrelated to carbonic acid weathering and, thus, may overestimate CDR rates. To avoid these pitfalls, we recommend (1) incorporating high-dosage test plots into ERW trials that avoid reapplication of rock powders that replenish initially fast reactivity, (2) screening rock powders for carbonate minerals using sensitive techniques and distinguishing carbonate and silicate weathering, and (3) measuring carbon to verify carbon dioxide removal. High-quality carbon credits must be durable, additional, and not overestimated.
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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) | 0.001 | 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".