Nitrate Controls Methyl Mercury Production in a Streambed Bioreactor
Bibliographic record
Abstract
Organic carbon bioreactors provide low-cost, passive treatment of a variety of environmental contaminants but can have undesirable side effects in some cases. This study examines the production of methyl mercury (MeHg) in a streambed bioreactor consisting of 40 m³ of wood chips and designed to treat nitrate (NO₃) in an agricultural drainage ditch in southern Ontario (Avon site). The reactor provides 30 to 100% removal of NO₃-N concentrations of 0.6 to 4.4 mg L(-1), but sulfate (SO₄(2-)) reducing conditions develop when NO₃ removal is complete. Sulfate reducing conditions are known to stimulation the production of MeHg in natural wetlands. Over one seasonal cycle, effluent MeHg ranged from 0.01 to 0.76 ng L(-1) and total Hg ranged from 1.3 to 3.4 ng L(-1). During all sampling events when reducing conditions were only sufficient to promote NO₃(-) reduction (or denitrification) ( = 5, late fall 2009, winter 2010), MeHg concentrations decreased in the reactor and it was a net sink for MeHg (mean flux of -5.1 μg m(-2) yr(-1)). During all sampling events when SO₄(2-) reducing conditions were present ( = 6, early fall 2009, spring 2010), MeHg concentrations increased in the reactor and it was a strong source of MeHg to the stream (mean flux of 15.2 μg m(-2) yr(-1)). Total Hg was consistently removed in the reactor (10 of 11 sampling events) and was correlated to the total suspended sediment load ( r² = 0.69), which was removed in the reactor by physical filtration. This study shows that organic carbon bioreactors can be a strong source of MeHg production when SO₄(2-) reducing conditions develop; however, maintaining NO₃-N concentrations > 0.5 mg L suppresses the production of MeHg.
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".