Investigating radiocarbon isotope anomalies in CO2 for CCS monitoring: Insights from the Aquistore project and the influence of coal mine spoils
Bibliographic record
Abstract
• Δ 14 CO 2 anomalies at Aquistore predate injection, challenging its use as a tracer. • Coal seam venting and microbial activity were tested as causes of Δ 14 CO 2 anomalies. • Microbial activity on coal fragments explains Δ 14 CO 2 depletion in dry conditions. • Site-specific monitoring is needed to avoid misinterpreting natural Δ 14 CO 2 signals. • Δ 14 CO 2 should be combined with tracers and emission monitoring for better reliability. The radiocarbon isotope of CO 2 (Δ 14 CO 2 ) is a valuable tool for investigating soil-respired CO 2 and identifying its sources. At Aquistore, a CCS project in Canada, Δ 14 CO 2 is incorporated into surface soil-gas geochemical MMV studies to demonstrate the absence of surface impacts from CO 2 injection. However, some monitoring locations consistently show negative Δ 14 CO 2 values (usually indicative of fossil CO 2 ) that predate CO 2 injections, suggesting these anomalies are natural or linked to soil disturbances. This study investigates the origins of these anomalies. We first hypothesized that CO 2 venting from coal seams underlying parts of the monitoring grid could explain the negative values. A spatial correlation between negative Δ 14 CO 2 values, historic open-pit coal mines, and mine spoils supported this hypothesis. However, Δ 14 CO 2 analysis from a nearby farm (control site) with intact coal seams but no mine spoils showed modern-age signatures (6.8 ± 16 %), ruling out the venting hypothesis. Next, we tested whether microbial decomposition of weathered coal fragments was responsible. A soil survey revealed a strong correlation between coal fragment concentrations (1.85–40.64 % w/w) and Δ 14 CO 2 anomalies. Laboratory incubation experiments further supported this hypothesis, showing that dry soils with weathered coal fragments produced proportionately negative Δ 14 CO 2 values, likely due to microbial activity. These findings underscore the need for a more nuanced and site-specific approach to CCS monitoring. In geochemically complex sites like Aquistore, relying solely on Δ 14 CO 2 may be misleading, and alternative tracers should be considered to ensure accurate soil-gas anomaly interpretations.
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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 | 0.001 | 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".