Effect of loading rate on performance of constructed wetlands treating an anaerobic supernatant
Bibliographic record
Abstract
The effect of organic loading, season and plant species on the treatment of fish farm effluent was tested using three-year old mesocosm wetland systems. During one year, nine 1 m2 mesocosms (horizontal subsurface flow), located in a controlled greenhouse environment, were fed with a reconstituted fish farm effluent containing a high fraction of soluble components (1,600 microS/cm and in mg/L: 230 +/- 80 COD, 179 +/- 60 sCOD, 100 +/- 40 TSS, 37 +/- 7 TKN, 14 +/- 2 TP). Combinations of three hydraulic loading rates (30, 60 and 90 L.m(-2) d(-1)) and two plant species (Phragmites australis, Typha angustifolia) and an unplanted control were tested for treatment performance and hydraulic behaviour. Loadings higher than 15 g COD m(-2) d(-1) resulted in a net decrease of hydraulic performances (generation of short circuiting) coupled with low TKN removal. Maximal TKN removal rates (summer: 1.2, winter: 0.6 g.m(-2) d(-1)) were reached in planted units. In all mesocosms, phosphorus was removed during summer (maximal removal rate: 0.3 g TP m(-2) d(-1)) and was released in winter (release rate = approximately half of summer removal rate). This study confirmed that constructed wetlands are susceptible to clogging when treating anaerobic storage tank supernatant rich in highly biodegradable compounds. Contributions of plants to hydraulic efficiency were mainly observed in summer, associated with high evapotranspiration rates. Both plant species gave a similar removal efficiency for all pollutants.
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 | 0.000 |
| 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) | 0.000 | 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".