Dissolved gaseous mercury dynamics and mercury volatilization in freshwater lakes
Bibliographic record
Abstract
This thesis examines the production and distribution of dissolved gaseous mercury (DGM) in freshwater ecosystems and its relationship to mercury volatilization. The importance of volatilization was assessed within a multidisciplinary mercury mass balance for Big Dam West Lake (BDW) Kejimkujik Park, Nova Scotia. The magnitude of volatilization was found to be approximately double the direct wet deposition over lake and wetlands, and 27% of the direct wet deposition to the terrestrial catchment. Over the entire basin area the mass of mercury volatilized is 46% of the mass deposited by wet deposition. A new method of continuous (5 minute) DGM analysis was developed and tested. The detection limit for DGM was 20 fmol L-1 with 99% removal efficiency. Control experiments showed that there was no interference due to methyl mercury, which is present in similar concentrations to DGM. Experiments comparing continuous DGM analysis with discrete DGM analysis showed that the results are not significantly affected by typical variations in water temperature (4--30°C), oxidation-reduction potential (135--355 mV), dissolved organic carbon (4.5--10.5 mg L-1), or pH (3.5--7.8). The continuous analysis was within 4.5% of the discrete analysis when compared across 12 samples analyzed in triplicate. Diurnal patterns for dissolved gaseous mercury (DGM) and mercury flux were measured (using this new DGM method and a Teflon flux chamber method) in two lakes with contrasting dissolved organic carbon (DOC) concentrations in Kejimkujik Park, Nova Scotia. Consistently higher DGM concentrations were found in the high DOC lake as compared to the low DOC lake. Cross-correlation analysis indicated that DGM dynamics changed in response to solar radiation with lag-times of 65 and 90 minutes. An examination of current mercury flux models using this quantitative data indicated some good correlations between the data and predicted flux (r ranging from 0.27 to 0.83) but generally poor fit (standard deviation of residuals ranging from 0.97 to 3.38). This research indicates that DOC and wind speed may play important roles in DGM and mercury flux dynamics that have not been adequately accounted for in current predictive models. The distribution of DGM in the water columns of shallow and deep freshwater lakes was investigated in Lake Ontario and several small freshwater lakes. When DGM concentrations were expressed on an areal basis, DGM concentrations above the thermocline in Lake Ontario average 1.5 ng m-2 and in small freshwater lakes it ranged between 0.1 and 0.8 ng m -2. Further, it was demonstrated that the majority of DGM in large freshwater lakes such as Lake Ontario exists below the thermocline where photochemical oxidation and reduction processes cannot occur. The depth profiles indicate that vertical mixing in the water column may alter the DGM concentration in the upper epilimnion, and that turn over in deep lakes may result in a transfer of large concentrations of DGM from the hypolimnion into the epilimnion. In addition, the results indicate that microbial processes may be an important factor regulating DGM in the water column of freshwater lakes, particularly in the hypolimnion. (Abstract shortened by UMI.)
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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 | 0.000 | 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".