Partitioning of polycyclic aromatic hydrocarbons, alkylphenols, bisphenol A and phthalates in landfill leachates and stormwater
Bibliographic record
Abstract
Partitioning of organic pollutants is essential to their fate, mobility and removal from water and soil. To study the partitioning behavior of selected alkylphenols, bisphenol A, phthalates and polycyclic aromatic hydrocarbons (PAHs), a method for separating the truly dissolved and colloidal phase of organic pollutants was developed, verified and applied to samples of landfill leachate and stormwater from urban areas and waste-sorting sites. Alkylphenols, bisphenol A, phthalates and PAHs were detected in all the untreated samples (total concentrations), most of the filtered samples and frequently in the colloid-bound phase. Concentrations of alkylphenols and PAHs in urban stormwater were one order of magnitude lower than in the landfill leachates and stormwater from waste-sorting sites. The difference between total, dissolved and colloid-bound concentrations in the water samples was not statistically significant for any phenols or phthalates, but for three of the PAHs; naphthalene (mostly dissolved), phenanthrene and fluoranthene (mostly particulate). These results indicate that in landfill leachates and stormwaters, organic pollutants are predominantly attached to colloids and/or truly dissolved in contrast to their expected strong sorption to particulate matter. Occurrence and concentrations of pollutants in dissolved and colloid-bound phases correlated negatively with the K(OW). However, even highly hydrophobic compounds were frequently detected in filtered samples, i.e. the dissolved phases, and it is suggested that the organic content in the colloids decreases the compounds' partition to particles. The results confirm that the K(OW) values of specific organic pollutants well describe the compounds partition-binding process to dissolved organic carbon (DOC) colloids. Our findings call for a re-assessment of the organic pollutants' mobility and associated risks. This knowledge can also serve as a base for selecting efficient treatment methods for stormwater and landfill leachates.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".