The Role of Lipids on Sorption Characteristics of Freshwater‐ and Wastewater‐Irrigated Soils
Bibliographic record
Abstract
The soil lipid fraction can play an important role in the sorption of organic compounds. In this study, the impact of the lipid fraction of freshwater- and wastewater-irrigated soils on the sorption of non- and relatively polar compounds was assessed. Lipid analyses revealed a clear difference between the two lipid fractions. The lipid extract from the wastewater-irrigated soil was consistent with mainly straight paraffinic chain materials; the lipid extract from freshwater-irrigated soil, on the other hand, exhibited stronger signals of aromatics, double bonds, ester, ether, and methyl, in addition to a smaller contribution from methylene protons. Our data suggest that lipid removal induced a stronger increase in the soil's sorption affinity for solutes capable of polar interactions such as atrazine (2-chloro-4-ethylamino-6-isopropylamino-1,3,5-triazine) and chlorotoluron (N'-(3-chloro-4-methylphenyl)-N,N-dimethylurea) as compared to phenanthrene. Moreover, the level of increase in sorption affinities due to lipid removal was much higher for the freshwater-irrigated soil than for its wastewater-irrigated counterpart, even though the level of lipids in the freshwater-irrigated soil was half that in the wastewater-irrigated one (6 vs. 11% of the total organic C). The higher level of polar functionalities, such as ether and ester moieties, in the lipid fraction from the freshwater-irrigated soil suggests that these extractable compounds compete successfully with the polar solutes (atrazine and chlorotoluron) for specific binding sites in the soil organic matter (SOM). It appears that the composition of the lipid fraction may be a key consideration in unraveling the sorption of organic molecules in soils.
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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".