Dissolved black carbon in the global cryosphere: Concentrations and chemical signatures
Bibliographic record
Abstract
Abstract Black carbon (BC) is derived from the incomplete combustion of biomass and fossil fuels and can enhance glacial recession when deposited on snow and ice surfaces. Here we explore the influence of environmental conditions and the proximity to anthropogenic sources on the concentration and composition of dissolved black carbon (DBC), as measured by benzenepolycaroxylic acid (BPCA) markers, across snow, lakes, and streams from the global cryosphere. Data are presented from Antarctica, the Arctic, and high alpine regions of the Himalayas, Rockies, Andes, and Alps. DBC concentrations spanned from 0.62 μg/L to 170 μg/L. The median and (2.5, 97.5) quantiles in the pristine samples were 1.8 μg/L (0.62, 12), and nonpristine samples were 21 μg/L (1.6, 170). DBC is susceptible to photodegradation when exposed to solar radiation. This process leads to a less condensed BPCA signature. In general, DBC across the data set was composed of less polycondensed DBC. However, DBC from the Greenland Ice Sheet (GRIS) had a highly condensed BPCA molecular signature. This could be due to recent deposition of BC from Canadian wildfires. Variation in DBC appears to be driven by a combination of photochemical processing and the source combustion conditions under which the DBC was formed. Overall, DBC was found to persist across the global cryosphere in both pristine and nonpristine snow and surface waters. The high concentration of DBC measured in supraglacial melt on the GRIS suggests that DBC can be mobilized across ice surfaces. This is significant because these processes may jointly exacerbate surface albedo reduction in the cryosphere.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 source (direct Gemma or distilled Codex), 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".