Field Column Study Using Zerovalent Iron for Mercury Removal from Contaminated Groundwater
Bibliographic record
Abstract
Passive in situ remediation technologies, for example, permeable reactive barriers, PRBs, are an attractive and less expensive alternative compared to conventional pump and treat systems for groundwater remediation. Field column experiments were conducted to evaluate the removal of dissolved mercury from groundwater using zerovalent iron as the reactive media. Two column tests were conducted over a 6-week period, which simulated 2 and 10 years of groundwater flow through a potential full-scale treatment system. The influent groundwater pH was 7.8-9.5. The groundwater was reduced with an Eh, corrected to the standard hydrogen electrode, ranging from 0 to 120 mV over the trial period. Prior to treatment the total mercury concentration of the groundwater was approximately 40 microg L(-1). Effluent from the 10-year simulation contained approximately 0.5 microg/L of mercury during the first 3 weeks and increased to as much as 4 microg L(-1) by the end of the testing period. Effluent from the 2-year simulation was generally < 0.1 microg L(-1). Profile sampling of the 2-year simulation suggests that most of the mercury removal occurred in the initial 50% of the 20 cm column. Mineralogical studies, conducted using SEM/EDS and X-ray absorption spectroscopy (XAS), confirm the accumulation of mercury onto a zerovalent iron surface in this 20-cm zone. These analyses indicate that mercury accumulated as a mercury sulfide with a stoichiometery similar to those of cinnabar and metacinnabar (HgS).
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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 | 0.001 | 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".