Modeling historical budget for β-Hexachlorocyclohexane (HCH) in the Arctic Ocean: A contrast to α-HCH
Why this work is in the frame
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Bibliographic record
Abstract
The historical annual loading to, removal from, and cumulative burden in the Arctic Ocean for β-hexachlorocyclohexane (β-HCH), an isomer comprising 5–12% of technical HCH, is investigated using a mass balance box model from 1945 to 2020. Over the 76 years, loading occurred predominantly through ocean currents and river inflow (83%) and only a small portion via atmospheric transport (16%). β-HCH started to accumulate in the Arctic Ocean in the late 1940s, reached a peak of 810 t in 1986, and decreased to 87 t in 2020, when its concentrations in the Arctic water and air were ∼30 ng m−3 and ∼0.02 pg m−3, respectively. Even though β-HCH and α-HCH (60–70% of technical HCH) are both the isomers of HCHs with almost identical temporal and spatial emission patterns, these two chemicals have shown different major pathways entering the Arctic. Different from α-HCH with the long-range atmospheric transport (LRAT) as its major transport pathway, β-HCH reached the Arctic mainly through long-range oceanic transport (LROT). The much higher tendency of β-HCH to partition into the water, mainly due to its much lower Henry's Law Constant than α-HCH, produced an exceptionally strong pathway divergence with β-HCH favoring slow transport in water and α-HCH favoring rapid transport in air. The concentration and burden of β-HCH in the Arctic Ocean are also predicted for the year 2050 when only 4.4–5.3 t will remain in the Arctic Ocean under the influence of climate change.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it