Phenanthrene Sorption to Sequentially Extracted Soil Humic Acids and Humins
Bibliographic record
Abstract
Humic substances strongly influence the environmental fate of hydrophobic organic chemicals in soils and sediments. In this study, the sorption of phenanthrene by humic acids (HAs) and humins was examined. HAs were obtained from progressively extracting a soil, eight times with 0.1 M Na4P207 and two times with 0.1 M NaOH solution, and then the residue was separated into two humin fractions by their organic carbon contents. The chemical and structural heterogeneity of the HAs and humins were characterized by elemental analysis, ultraviolet-visible spectroscopy, diffuse reflectance infrared Fourier transform spectroscopy, and solid-state 13C NMR. There were significant chemical and structural differences among the HA fractions and humins; the later extracted HAs had relatively high aliphatic carbons content. All sorption data were fitted to a Freundlich equation, S = K(F)C(N), where S and C are the sorbed and solution-phase concentrations, respectively, and K(F) and N are constants. All of the phenanthrene sorptions were nonlinear, and the nonlinearity decreased with further extractions from 0.90 (first extracted HA) to 0.96 (ninth HA) and was the lowest (0.88) for the higher organic carbon content humin. Phenanthrene sorption coefficient by HAs significantly increased with progressive extractions, being the highest for the humins. For HAs isotherms, a positive trend was observed between the sorption coefficient and the aliphaticity, but a negative relation was shown between the nonlinearity and the aliphaticity and between the sorption capacity and polarity of HAs. Phenanthrene sorption was greatly affected by chemical structure and composition of humic substances, even from a same soil. In addition, polarity of humic substances seems to mainly regulate the magnitude of phenanthrene sorption rather than structure.
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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".