Comparison of Changes in Metal Toxicity Following Exposure of Water with High Dissolved Organic Carbon Content to Solar, UV‐B and UV‐A Radiation
Bibliographic record
Abstract
This study examines the effects of natural solar radiation on the metal-binding capacity of dissolved organic matter (DOM). Newington Bog water (35.5 mg L(-1) dissolved organic carbon [DOC]) was irradiated for 20 days under UV-B lamps in the laboratory and under natural solar radiation. In the presence of irradiated DOM, IC(50) (contaminant concentration required to reduce algal growth by 50%) was significantly decreased with UV-B treatment for four metals: Pb, 64%; Cu, 63%; Ni, 35% and Cd, 40%. Solar radiation also significantly decreased IC(50) of Pb (58%) and Cu (49%), DOC concentration (11%), DOM fluorescence (DOMFL, 33%) and DOC-specific UV absorbance. Further experiments on Raisin River water (20.7 mg DOC L(-1)) exposed to 20 days of artificial UV-A and UV-B radiation produced significant decreases in IC(50) for Cu (48%) with UV-A and for Pb (43%) with UV-B. DOC concentration was decreased 20% by UV-B and 24% by UV-A. DOMFL decreased 51.5% in the first 5 days of UV-A exposure, an effect that was not observed with the UV-B treatment. The UV-A treatment decreased UV absorbance more at longer wavelengths and over a broader wavelength band than did the UV-B treatment. Change in toxicity with UV irradiation was inconsistent among the metals tested in this study, indicating that some organic metal-binding ligands were more quickly removed or altered than others. The DOM remaining after irradiation appears to be qualitatively different from the unirradiated DOM. The much greater irradiance of UV-A makes its contribution to the removal and/or alteration of DOM at least as important as the influence of higher energy UV-B.
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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) | 0.001 | 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".