Impact of Hydrogen Peroxide and Copper Sulfate on the Delayed Release of Microcystin
Bibliographic record
Abstract
Algicides, like hydrogen peroxide and copper sulfate, are commonly applied to recreational waters and drinking water sources to mitigate cyanobacterial blooms. In this work, the effects of hydrogen peroxide and copper sulfate were evaluated in two natural bloom samples (collected from Canadian and American waterbodies) and one lab-cultured Microcystis aeruginosa suspended in Colorado River water. Five algicide to dissolved organic carbon (DOC) dose ratios were evaluated during an initial exposure period of 24 h. One dose ratio (0.4 H2O2:DOC or 0.25 CuSO4:DOC) was then evaluated during stagnation after quenching (hydrogen peroxide) or extended exposure (copper sulfate) for up to 96 or 168 h. During the initial hydrogen peroxide exposure, the CA bloom had no release of intracellular microcystins (MCs) and the USA bloom only released MC at 4 H2O2:DOC. The reverse occurred with copper sulfate, where the CA bloom released MCs at 0.6 CuSO4:DOC but the USA bloom had no detectable extracellular MCs. Extracellular MC was released from the lab-cultured Microcystis at the lowest hydrogen peroxide and copper sulfate doses. In the hydrogen peroxide stagnation experiment, intracellular MC decreased in the USA bloom after 168 h despite the low dose applied. Similarly, the extended copper sulfate exposure led to intracellular MC decreases in both bloom samples after 168 h, despite showing no impact during the initial 24 h monitoring period. The lab-cultured Microcystis was again less resistant to both algicides, with releases observed after less than 2 h of stagnation or exposure. The damage to cells as measured by pigments during these experiments did not match the MC data, indicating that blooms with depressed pigment levels can still be a risk to nearby drinking water sources or recreational activities. These results provide insight on the timeline (up to one week) required for monitoring the potential release of MCs after algicide application.
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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".