Photoreactions of mercury in the freshwater lakes of Kejimkujik National Park, Nova Scotia
Bibliographic record
Abstract
Mercury is a globally distributed, toxic environmental contaminant. Divalent mercury (Hg(II)) in freshwater lakes is reduced to volatile elemental mercury (Hg(0)) through reactions with Dissolved Organic Matter (DOM) and energy from solar radiation. Samples were collected from ten lakes in Kejimkujik National Park, Nova Scotia in May, 2008, 2009 and August 2010 and analysed for DOC (ranging 1.4 - 15.4 mg L-1), attenuation, anions, cations, and mercury photoreduction and oxidation rates. An integrated pseudo first order reaction equation was found to fit the gross reduction data extremely well (R2 value of >0.98; p value <0.0001). In all lakes, unfiltered samples (biotic activity included) had a significantly (p <0.01) higher maximum amount of Hg(0) formed (mean = 149 ± 103 pg) than filter sterilized samples lake water samples (mean = 94 ± 75 pg). Gross reduction rate constants for all samples were between 1.63 x 10-3 h-1 to 8.15 x 10-1 h1 (filtered) and 1.29 x 10-3 h-1 to 3.39 x 10-1 h-1 (unfiltered), and rate constants were significantly larger for filtered samples (p = 0.024). We hypothesize that the presence of particles and microbes primarily affects the amount of photo-reducible mercury available. Ultra violet attenuation was measured for each lake and was combined with the measured reduction and oxidation rates to develop a whole lake model for the production of Hg(0) with depth. It was calculated that the lakes studied cumulatively release 115.4 kg of DGM per year, assuming 12 hours of full sun each day
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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 | 0.000 |
| Open science | 0.001 | 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 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".