Using Mercury Stable Isotopes to Quantify Directional Soil–Atmosphere Hg(0) Exchanges in Rice Paddy Ecosystems: Implications for Hg(0) Emissions to the Atmosphere from Land Surfaces
Bibliographic record
Abstract
Gaseous elemental mercury [Hg(0)] emissions from soils constitute a large fraction of global total Hg(0) emissions. Existing studies do not distinguish biotic- and abiotic-mediated emissions and focus only on photoreduction mediated emissions, resulting in an underestimation of soil Hg(0) emissions into the atmosphere. In this study, directional mercury (Hg) reduction pathways in paddy soils were identified using Hg isotopes. Results showed significantly different isotopic compositions of Hg(0) between those produced from photoreduction (δ 202 Hg = −0.80 ± 0.67‰, Δ 199 Hg = −0.38 ± 0.18‰), microbial reduction (δ 202 Hg = −2.18 ± 0.25‰, Δ 199 Hg = 0.29 ± 0.38‰), and abiotic dark reduction (δ 202 Hg = −2.31 ± 0.25‰, Δ 199 Hg = 0.50 ± 0.22‰). Hg(0) exchange fluxes between the atmosphere and the paddy soils were dominated by emissions, with the average flux ranging from 2.2 ± 5.7 to 16.8 ± 21.7 ng m –2 h –1 during different sampling periods. Using an isotopic signature-based ternary mixing model, we revealed that photoreduction is the most important contributor to Hg(0) emissions from paddy soils. Albeit lower, microbial and abiotic dark reduction contributed up to 36 ± 22 and 25 ± 15%, respectively, to Hg(0) emissions on the 110th day. These novel findings can help improve future estimation of soil Hg(0) emissions from rice paddy ecosystems, which involve complex biotic-, abiotic-, and photoreduction processes.
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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) | 0.000 | 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".