Potential Hazards of Brominated Carbon Sorbents for Mercury Emission Control
Bibliographic record
Abstract
Mercury is a toxic air pollutant, emitted from the combustion of coal. Activated Carbon (AC) or other carbon sorbent (CS) injection into coal combustion flue gases can remove elemental mercury through an adsorption process. Recently, a brominated CS with biomass ash as the carbon source (Br-Ash) was developed as an alternative for costly AC-based sorbent for mercury capture. After mercury capture, these sorbents are disposed in landfill, and the stability of bromine and captured mercury is of paramount importance. The objective of this study is to determine the fate of mercury and bromine from Br-Ash and brominated AC after their service. Mercury and bromine leaching tests were conducted using the standard toxicity characteristic leaching procedure (TCLP). The mercury was found to be stable on both the Br-Ash and commercial brominated AC sorbents, while the bromine leached into the aqueous phase considerably. Mercury pulse injection tests on the sorbent material after leaching indicate that both sorbents retain significant mercury capture capability even after the majority of bromine was removed. Testing of the Br-Ash sorbent over a wider range of pH and liquid:solid ratios resulted in leaching of <5% of mercury adsorbed on the Br-Ash. XPS analysis indicated more organically bound Br and less metal-Br bonds after leaching.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".