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Record W6921549094 · doi:10.7939/81922

Environmental and Crystal Chemical Controls on the Products and Efficiency of Carbon Mineralization Reactions

2025· dissertation· en· W6921549094 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsCarbonateCarbonate mineralsWeatheringMineralization (soil science)Carbon cycleCarbon dioxideBiogeochemical cycleGlobal warmingSustainable energy

Abstract

fetched live from OpenAlex

Negative global consequences associated with the climate crisis are expected to become more extreme and continually worsen as Earth’s mean global temperature approaches, or exceeds, a 2 °C rise from pre-industrial revolution temperatures. To combat this, countries have pledged to transition to sustainable energy systems to limit emissions, primarily as CO2; however, this is a slow process. In order to minimize environmental and societal damage related to anthropogenic climate change, rapid implementation of large-scale carbon dioxide removal (CDR) technologies is necessary to mediate historic and current emissions. While many strategies for CDR are being explored, CO2 storage in geologic environments or as benign carbonate minerals presents a safe, long-term repository for anthropogenic emission. In my thesis, I examine how environmental conditions and biogeochemical processes influence CO2 storage in carbonate minerals to help advance carbon mineralization and enhanced rock weathering (ERW) technologies. Furthermore, this research examines how cation substitution in the Mg–Ca–Fe(II) –H2O–CO2 system affects the long-term stability of secondary carbonate minerals targeted for CDR. This was achieved by integrating data from four research projects (Chapters 2–5): Chapter 2 describes detailed temporal mineral transformation and recrystallization pathways for Ca, Mg, and Ca Mg-carbonates in simulated saline/diagenetic conditions, between 40 and 80 °C, while concomitantly tracking metal partitioning (Sr and Li) and stable oxygen isotope fractionation. Multi-phase assemblages of carbonate minerals formed in a laboratory experiment following the transformation of amorphous Ca-Mg-carbonate. Mineralogical and chemical compositions varied depending on reaction temperature. These results have implications for predicting the evolution of carbonate precipitation reactions and their long-term stability, as well as associated metal release, during CO2 sequestration in saline environments. Chapter 3 examines how Fe(II)-substitution in brucite [Mg(OH)2] and prevailing environmental conditions — reduction-oxidation (redox) state and background anions — affects the long-term stability of secondary Mg–Fe carbonates and the overall carbonation efficiency. These results highlight the importance of considering metal substitution when estimating the CO2 sequestration potential of both mine wastes in surficial environments and serpentinite deposits in subsurface conditions. Long-term carbon sequestration potential in Fe bearing phases is typically limited to siderite (FeCO3) and pyroaurite [Mg6FeIII2CO3(OH)16∙4H2O]. But, as a consequence of the redox sensitive tendencies of Fe bearing phases, captured CO2 can be released from Fe bearing phases during redox fluctuations and environmental changes. Chapter 4 elucidates the influence of dissolved silica and Fe(II) on Mg-carbonate precipitation and transformation pathways, along with co-evolving (low-temperature) silicate formation. This research shows that dissolved silica can accelerate Mg-carbonate nucleation; however, the amount of Mg-carbonate formed depended on the initial silica concentration as amorphous silicates scavenge Mg cations. In Mg-only experiments, the rate of dypingite formation increased as the initial silica concentration increased and, interestingly, nesquehonite did not form as an intermediary phase in experiments containing 100 mM Si but rather dypingite was the sole phase. Carbonate (re)crystallization in solutions containing a mixture of Mg and Fe(II) is controlled by redox conditions and, to a lesser extent, Si concentration. This work demonstrates the importance of considering relationships between carbonate and silicate precipitation reactions and, therefore, these results support our current understanding of silicate–carbonate cycling (i.e., enhanced rock weathering) in alkaline systems. Chapter 5 evaluates whether burial of sulfide minerals, derived from chemoheterotrophic microorganisms (i.e., sulfate reducing microorganisms), and organic carbon facilitates long-term storage of carbonate minerals in Mg- and Fe-rich saline environments. To achieve this, I studied a unique saline playa lake, Basque Lake #2 (near Ashcroft, British Columbia, Canada), where formation of low-temperature magnesite (MgCO3) is associated with sulfidic sediments. Field observations were integrated with laboratory microbial experiments, to determine the role of chemoheterotrophic microorganisms during carbon mineralization. Based on analysis of core samples, it was estimated that only ~1.0% of the total magnesite was generated by alkalinity derived from sulfate reduction: this finding is also supported by microcosm experiments. Additionally, results suggest that previous studies that examined the capability of sulfate reducing microorganisms to induce carbonate precipitation may have overestimated their contribution. The implications from this work extend to developing biogeochemical CDR methods in alkaline mining environments and subsurface geologic systems. This research improves the current understanding of mineralogical, chemical, and biological controls on secondary carbonate precipitation in geologic systems. Overall, my thesis will support future development of CDR methods in geologic environments by integrating these novel findings into future practices.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score1.000

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.167
Teacher spread0.163 · 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.

Study designBench or experimental
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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