Photodegradation-induced changes in dissolved organic matter in acidic waters
Bibliographic record
Abstract
Photodegradation of dissolved organic matter (DOM) from stream waters was investigated using dissolved organic carbon (DOC) analysis, ultraviolet-visible absorbance, three-dimensional excitational emission matrix fluorescence, and high-performance size exclusion chromatography. The effects of altering pH and various iron concentrations on DOM characteristics during irradiation were examined. DOC concentration, absorbance, and fluorescence all decreased with increasing irradiation. These decreases were accompanied by a decrease in absorbance spectral slope and average molecular size and a blue-shift in fluorescence maximum; decreasing pH enhanced these changes. The photooxidation rate constants were wavelength dependent. For the ratio of the photooxidation rate constant at pH 4 to that at pH 8 under ultraviolet irradiation, there were two maxima at wavelengths of approximately 280 and 320 nm, respectively, indicating that aromatic fractions were most pH photosensitive. The isolated humic acid (HA) and fulvic acid (FA) fractions had different photodegradation characteristics in terms of the photooxidation rate constant and the effects of pH and iron. The results suggest that iron played a more significant role in the photodegradation of the HA fraction than that of the FA fraction and that the HA fraction was mainly responsible for the observed DOM photodegradation. The results indicate that DOM photodegradation in stream waters is strongly influenced by iron and acidity.
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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".