Advanced Treatment Process for Pharmaceuticals, Endocrine Disruptors, and Flame Retardants Removal
Bibliographic record
Abstract
The objective of this project was to demonstrate the effectiveness of an advanced treatment process that did not utilize reverse osmosis for the removal of pharmaceuticals, endocrine disruptors and flame retardants (collectively referred as contaminants of emerging concern [CECs]) from municipal effluent. The advanced treatment process consisted of (in the order of use): membrane filtration, ozonation (O3), and biologically active carbon (BAC) filtration. Ozone dosage of 5 mg/L or more was needed for desired CEC removal. Biologically active carbon removed flame retardants, and ozonation byproducts including NDMA and aldehydes. The project successfully demonstrated 1) the removal of a wide range of CECs, 2) reduction of estrogen activity to background levels, and 3) removal of ozonation byproducts. Treatment was achieved at lower costs and power utilization than reverse osmosis and without generating a concentrate stream. Results from this project could make CEC removal feasible, especially in situations where reverse osmosis treatment is infeasible.
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 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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".