Sorption of DOM and hydrophobic organic compounds onto sewage-based activated carbon
Bibliographic record
Abstract
Treatment of stormwater via sorption has the potential to remove both colloidal and dissolved pollutants. Previous research shows that activated carbon produced from sewage sludge is very efficient in sorbing hydrophobic organic compounds (HOCs), frequently detected in stormwater. The aim of this research was to determine whether the presence of dissolved organic matter (DOM) has a negative effect on the adsorption of HOCs onto sludge-based activated carbon (SBAC) in batch adsorption tests. Batch adsorption tests were used to investigate the influence of two types of DOM - soil organic matter and humic acid (HA) technical standard - on the sorption of HOCs onto SBAC, and whether preloading adsorbent and adsorbates with DOM affects HOC sorption. The results indicate that soil DOM and HAs do not have a significant negative effect on the adsorption of HOCs under tested experimental conditions, except for a highly hydrophobic compound. In addition, preloading SBAC or HOCs with DOM did not lead to lower adsorption of HOCs. Batch adsorption tests appear to be inefficient for investigating DOM effects on HOC adsorption, as saturating the carbon is difficult because of high SBAC adsorption capacity and low HOC solubility, so that limited competition occurs on the sorbent.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".