Historical (1850–2010) mercury stable isotope inventory from anthropogenic sources to the atmosphere
Bibliographic record
Abstract
Abstract Mercury (Hg) stable isotopes provide a new tool to trace the biogeochemical cycle of Hg. An inventory of the isotopic composition of historical anthropogenic Hg emissions is important to understand sources and post-emission transformations of Hg. We build on existing global inventories of anthropogenic Hg emissions to the atmosphere to develop the first corresponding historical Hg isotope inventories for total Hg (THg) and three Hg species: gaseous elemental Hg (GEM), gaseous oxidized Hg (GOM) and particulate-bound Hg (PBM). We compile δ202Hg and Δ199Hg of major Hg emissions source materials. Where possible, δ202Hg and Δ199Hg values in emissions are corrected for the mass dependent Hg isotope fractionation during industrial processing. The framework and Hg isotope inventories can be updated and improved as new data become available. Simulated THg emissions from all sectors between 1850s and 2010s generally show an increasing trend (−1.1‰ to −0.7‰) for δ202Hg, and a stable trend (−0.02‰ to −0.04‰) for Δ199Hg. Δ200Hg are near-zero in source materials and therefore emissions. The δ202Hg trend generally reflects a shift of historically dominant Hg emissions from 19th century Hg mining and liquid Hg0 uses in Au/Ag refining to 20th century coal combustion and non-ferrous metal production. The historical δ202Hg and Δ199Hg curves of GEM closely follow those of THg. The δ202Hg curves of GOM and PBM show no trends. Δ199Hg values for both GOM and PBM decrease from the 1850s to 1950s by ∼0.1‰, and then gradually rebound towards the 2010s. Our updated δ202Hg values (−0.76 ± 0.11 ‰, 1SD, n=9) of bulk emissions from passively degassing volcanoes overlap with δ202Hg of present-day anthropogenic THg emissions.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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".