Mercury Isotope Variations in Lake Sediment Cores in Response to Direct Mercury Emissions from Non-Ferrous Metal Smelters and Legacy Mercury Remobilization
Bibliographic record
Abstract
Nature archives record atmospheric mercury (Hg) depositions from directly emitted Hg and re-emitted legacy Hg. Tracing the legacy versus newly deposited Hg is still, however, challenging. Here, we measured Hg isotope compositions in three dated sediment cores at different distances from the Flin Flon smelter, the largest Canadian Hg sources to the atmosphere during the 1930s-2000s. During the smelter's operative period, Hg isotope compositions showed limited variations in the near-field lake (<10 km) sediments but were rather variable in middle- (20-75 km) and far-field lake (∼800 km) sediments. Only the post-2000 sediments in middle/far-field lakes showed significantly negative Hg isotope shifts, while sediments from the 1970s-1990s had Hg isotope values resembling those of near-field lake post-1930 sediments. We suggest that the smelter's peak Hg emissions during the 1970s-1990s, which coincided with the deployment of a super stack in the mid-1970s, largely increased the long-range dispersion of smelter plumes. For the top post-2000 sediments, the fugitive dust from ore tailings and terrestrial legacy Hg re-emissions dominated Hg deposition in near-field lakes and middle/far-field lakes, respectively. Our study demonstrates that legacy Hg remobilization now exports substantial amounts of Hg to ecosystems, highlighting the need for aggressive remediation measures of Hg-contaminated sites.
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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 | 0.000 | 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) | 0.001 | 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 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".