Mercury Speciation and Mass Distribution of Cement Production Process in Taiwan
Bibliographic record
Abstract
In this study, the mercury (Hg) speciation and mass distribution at two cement plants located in northern and eastern Taiwan were investigated. Gaseous Hg in the kiln flue gas was sampled by the Ontario Hydro method, and the solid samples were collected to analyze the Hg mass balance. The total Hg concentrations in the raw mill electrostatic precipitator (ESP) input of the two plants were 155.70 and 64.62 µg Nm–3, respectively, which were higher than those at any other sampling point. Approximately 97.5 and 86.5% of the Hg in the raw mill ESP input at Plants 1 and 2, respectively, was particle-bound. Elemental Hg was the major gaseous Hg species emitted into the atmosphere from these two cement plants, accounting for 56.4 to 98.2% of the total Hg in the flue gas. The total Hg mass output was calculated to be 61.374 and 204.596 mg-Hg per metric ton-clinker (mg ton–1) for cement Plants 1 and 2, respectively. The Hg emission factors for Plants 1 and 2 were thus 0.059 and 0.196 g-Hg per metric ton-cement (g ton–1), respectively. These results improve our understanding of Hg emissions from cement plants in Taiwan and provide useful information for selecting Hg control technology.
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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 | 0.001 | 0.001 |
| 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".