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Record W7081974501 · doi:10.36487/acg_repo/2515_60

Assessing the long-term carbon balance in mine waste storage facilities and implications for mine closure

2025· article· en· W7081974501 on OpenAlexfundno aff

Bibliographic record

VenueMine closure · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
FundersTrinity College DublinAustralian Centre for GeomechanicsCardiff UniversityCanadian Institute of Mining, Metallurgy and Petroleum
KeywordsCarbonationCarbon sequestrationCarbon dioxideCarbonate mineralsCarbonateTailingsClosure (psychology)Carbon capture and storage (timeline)

Abstract

fetched live from OpenAlex

The mining industry excavates and processes billions of tonnes of mine wastes per year and has the potential to leverage its infrastructure and capabilities to use suitable mine wastes for carbon dioxide removal (CDR), by enhanced rock weathering (ERW) as part of mine closure planning to offset mine emissions and mitigate climate change. However, before this opportunity can be realised, further development of key methodologies to measure and predict CO2 flux (uptake and release) from mine waste over the long timescales related to closure is required. While there is an increasing amount of research on the potential for mine wastes to sequester CO2 through the mineral carbonation of Mg-rich and Ca-rich silicates, less research into the determination of net CO2 mass flux/balance is being carried out, which also considers the potential of mine waste to emit CO2 due to cooccurrence of reactive sulphides; organic carbon; and carbonate minerals. This study expands on prior research into mine waste CDR, using novel laboratory and field methods to calculate and estimate the relative balance between sulphide oxidation (oxygen consumption and acidity production), carbonate dissolution (acid neutralisation and CO2 release) and silicate-related carbonation (CO2 sequestration) rates within mine waste. The study describes development of both closed and open system experimental design and utilises data collected to evaluate the carbon balance of various types of mine waste. Findings from the closed-system experiments are used to demonstrate validation of potential testing protocols to estimate site mine waste net CO2 flux. While ERW shows great potential in small-scale laboratory tests, several challenges arise when implementing it on a larger scale. ERW large-scale field trials and improved scaler laboratory-based methods can provide valuable tools for mine closure planning, specifically for designing waste storage facilities and assessing opportunities and risks related to CO2 net flux.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.279
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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