The role of crystallization‐driven exsolution on the sulfur mass balance in volcanic arc magmas
Bibliographic record
Abstract
Abstract The release of large amounts of sulfur to the stratosphere during explosive eruptions affects the radiative balance in the atmosphere and consequentially impacts climate for up to several years after the event. Quantitative estimations of the processes that control the mass balance of sulfur between melt, crystals, and vapor bubbles is needed to better understand the potential sulfur yield of individual eruption events and the conditions that favor large sulfur outputs to the atmosphere. The processes that control sulfur partitioning in magmas are (1) exsolution of volatiles (dominantly H 2 O) during decompression (first boiling) and during isobaric crystallization (second boiling), (2) the crystallization and breakdown of sulfide or sulfate phases in the magma, and (3) the transport of sulfur‐rich vapor (gas influx) from deeper unerupted regions of the magma reservoir. Vapor exsolution and the formation/breakdown of sulfur‐rich phases can all be considered as closed‐system processes where mass balance arguments are generally easier to constrain, whereas the contribution of sulfur by vapor transport (open system process) is more difficult to quantify. The ubiquitous “excess sulfur” problem, which refers to the much higher sulfur mass released during eruptions than what can be accounted for by amount of sulfur originally dissolved in erupted melt, as estimated from melt inclusion sulfur concentrations (the “petrologic estimate”), reflects the challenges in closing the sulfur mass balance between crystals, melt, and vapor before and during a volcanic eruption. In this work, we try to quantify the relative importance of closed‐ and open‐system processes for silicic arc volcanoes using kinetic models of sulfur partitioning during exsolution. Our calculations show that crystallization‐induced exsolution (second boiling) can generate a significant fraction of the excess sulfur observed in crystal‐rich arc magmas. This result does not negate the important role of vapor migration in sulfur mass balance but rather points out that second boiling (in situ exsolution) can provide the necessary yield to drive the excess sulfur to the levels observed for crystal‐rich systems. In contrast, in crystal‐poor systems, magma recharge that releases sulfur‐rich bubbles is necessary and most likely the primary contributor to sulfur mass balance. Finally, we apply our model to account for the effect of sulfur partitioning during second boiling and its impact on sulfur released during the Cerro Galan supereruption in Argentina (2.08 Ma) and show the potential importance of second boiling in releasing a large amount of sulfur to the atmosphere during the eruption of large crystal‐rich ignimbrites.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".