Phosphorus Retention of a Permeable Reactive Barrier Surpassed by an Unvegetated Artificial Pond
Bibliographic record
Abstract
An artificial pond bisected by a phosphorus (P) retentive permeable reactive barrier (PRB) alongside Forrest Highway, Coolup, Western Australia was designed to remove P from farmland runoff. The pond bed was made of subsoil and road construction materials likely to have a relatively high P sorption capacity, and there was no vegetation in the bed of the pond. Flow through the pond was intercepted by the PRB, constructed from a mixture of sand, coarse crushed limestone, and bauxite residue (with 10% phospho-gypsum). The effectiveness of P removal and the impact of the PRB was measured by comparing the concentration of contaminants immediately either side of the PRB with established standards, and against background levels in runoff from surrounding farmland. Using coarse limestone to increase flow through the PRB failed where permeability was insufficient to avoid overtopping of the PRB and the wall had to be lowered to allow by-pass and avoid collapse. The PRB was effective in removing total P (TP); however, the influent TP concentration was low (mean 0.19 mg L -1 ) because most P entering from farmland was retained in the shallow pond upstream of the PRB. Despite this, TP removal by the PRB was 53% (2009–2012). Occasionally, in spring when the pond was stagnant and anaerobic, P was released from the PRB. This minor P release coincided with a minor release of iron, consistent with anaerobic conditions found in the PRB. Although not designed to do so, the shallow pond upstream of the PRB reduced the TP concentration from farmland by 85% (mean 1.26 mg L -1 down to 0.19 mg L -1 ), mainly by reducing filterable reactive P concentration. Some elements (arsenic, cobalt, conductivity, fluoride, manganese, molybdenum, pH, selenium, uranium and vanadium) were increased by flow through the PRB, but were low relative to surrounding waters and environmental standards
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".