Photobleaching of chromophoric dissolved organic matter (CDOM) in the Yangtze River estuary: kinetics and effects of temperature, pH, and salinity
Bibliographic record
Abstract
The kinetics and temperature-, pH- and salinity-dependences of photobleaching of chromophoric dissolved organic matter (CDOM) in the Yangtze River estuary (YRE) were evaluated using laboratory solar-simulated irradiation and compared to those of Suwannee River humic substances (SRHSs). Nearly all CDOM in water at the head of the estuary (headwater herein) was photobleachable in both summer and winter, while significant fractions of CDOM (13-29%) were resistant to photobleaching in saltier waters. The photobleaching rate constant in the headwater was 25% higher in summer than that in winter. The absorbed photon-based photobleaching efficiency (PE) increased with temperature following the linear Arrhenius equation. For a 20 °C increase in temperature, PE increased by ∼45% in the headwater and by 70-81% in the saltier waters. PE for YRE samples exhibited minima at pH from 6 to 7 and increased with both lower and higher pH values, contrasting the consistent increase in PE with pH shown by SRHSs. No consistent effect of salinity on PE was observed for both SRHSs and YRE samples. Photobleaching increased the spectral slope coefficient between 275 nm and 295 nm in summer, consistent with the behavior of SRHSs, but decreased it in winter, implying a difference in the molecular composition of chromophores between the two seasons. Temperature, salinity, and pH modified the photoalteration of the spectral shape but their effects varied spatially and seasonally. This study demonstrates that CDOM quality, temperature, and pH should be incorporated into models involving quantification of photobleaching.
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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".