Assessment of Sulfate Sources in High-Elevation Asian Precipitation Using Stable Sulfur Isotopes
Bibliographic record
Abstract
Stable sulfur isotope measurements (delta34S) made on samples collected from a 2 m snowpit on the Inilchek Glacier, Tien Shan Mountains (42.16 degrees N, 80.25 degrees E, 5100 m) are used to estimate sources of sulfate (SO4(2-)) in high-elevation Central Asian precipitation. Comparison of snowpit oxygen isotope (delta18O) data with previous work constrains the age of the snowpit samples to the summer season during which they were retrieved (1999). Delta34S measurements were made at 10 cm resolution (20 samples total), with delta34S values ranging from 0.4/1000 during background ([SO4(2-)] < 1 microequiv L(-1)) periods to 19.4/1000 during a single high [SO4(2-)] event. On the basis of the significant correlation (r = 0.87) between [SO4(2-)] and delta34S values, coupled with major ion concentration time series and concentration ratios, we suggest a two-component mixing system consisting of evaporite dust and anthropogenic SO4(2-) to explain the observed delta34S values. Using a regression model, we estimate that during the 1999 summer season 60% of the deposited SO4(2-) was from an evaporite dust source, while 40% of the SO4(2-) was from anthropogenic sources. Due to the potentially large and unconstrained range of delta34S values for both evaporite and anthropogenic SO4(2-) sources in Asia, the error in our estimates is difficult to assess. However, the delta34S data from the 1999 Tien Shan snowpit provide the first unambiguous identification of evaporite and anthropogenic SO4(2-) in high-elevation Asian precipitation, and future ice core studies using improved analysis techniques and source delta34S values can provide detailed information on sulfur biogeochemistry and anthropogenic impacts in Asian alpine regions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".