A Laboratory Study on the Isotopic Composition of Hg(0) Emitted From Hg‐Enriched Soils in Wanshan Hg Mining Area
Bibliographic record
Abstract
Abstract Soil Hg(0) emissions are an important source of atmospheric mercury (Hg), but the Hg isotopic signatures of this source remain poorly characterized. In this study, the fractionation of Hg isotopes during Hg (0) emissions from Hg‐enriched agricultural and forest soils in Wanshan Hg mining area were investigated through laboratory experiments. Significant mass‐dependent fractionation (MDF) of Hg isotopes and mass independent fractionation of odd Hg isotopes (odd‐MIF) were observed. Mean MDF enrichment factors (ε202HgHg(0)‐soil) of agricultural soil were in the range of −2.03‰ to −1.34‰ for agricultural soil in light‐, light moisture‐, and temperature‐controlled experiments, which were higher than those of forest soil in similar controls (means = −3.38‰ to −1.98‰). Temperature‐controlled experiments exhibited a larger MDF compared to light‐ and light moisture‐controlled experiments. Photoreduction of Hg in agricultural soil in the presence and absence of soil water generated a larger positive odd‐MIF (mean E199HgHg(0)‐soil = 0.67‰ to 0.76‰, n = 2) than the temperature‐controlled experiments (mean E199HgHg(0)‐soil = 0.18 ± 0.04‰, 1 SD), whereas the E199HgHg(0)‐soil of forest soil in temperature controls (mean = 0.23 ± 0.03‰, 1 SD) were higher than that in light (mean = 0.18 ± 0.06‰, 1 SD) and light moisture‐controlled experiments (mean = −0.03 ± 0.06‰, 1 SD). It is speculated that photoreducible Hg (II) likely dominantly bound to S‐containing ligands in agricultural soil but to both S‐containing and sulfurless ligands in forest soil, resulting in significant positive odd‐MIF in Hg(0) product during photoreduction in the former case and a small magnitude of positive to some negative odd‐MIF in the latter case.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".