Slag columns for upgrading phosphorus removal from constructed wetland effluents
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The current best option to upgrade constructed wetlands (CWs) for phosphorus (P) retention, in terms of efficiency, cost and simplicity, consists in using media having a strong P affinity. The media can be used either in the planted beds or in a filtration system downstream of the beds. The use of slag filters was shown to be efficient for removing P from wastewater as it represented a slow release source of calcium and hydroxide, favouring the formation of hydroxyapatite. Our study aimed at maximising the P retention capacity of slag filters located at the outlet of CWs since electric arc furnace slag has been shown to inhibit the growth of macrophytes when used in the filtration matrix. Bench-scale columns (Vtot = 6.2 L) filled with various combinations of filter media (slag, granite, limestone) of different sizes (2-5, 5-10, 10-20 mm) were fed on-site during four months with a CW effluent (in mg/L: 30 COD, 30 TSS, 10 Pt). Results showed that the best media combination enabling the maximum o-PO4 retention (more than 80% removal without clogging) consisted in a series of a ternary mix column (slag 5-10 mm, granite 2-5 mm, limestone 5-10 mm) followed by a slag column (slag 5-10 mm). Pilot scale columns (Vtot = 300 L), filled with the best media combination, were installed at the outlet of a 28 m2 CW. These columns showed more than 75% removal efficiency during one year and were designed to be easily replaced each year.
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.
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 | 0.001 | 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 | 0.001 | 0.002 |
| 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 it