Assessing the Costs of Constructed Floating Wetlands for the Treatment of Surface Waters and Wastewater
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The development of constructed floating wetlands (CFWs) as a nature-based solution for water treatment has progressed over the last 25 years. However, full-scale CFW adoption remains relatively limited due in part to the uncertainty regarding the costs of CFWs in terms of capital and operational expenditure (CAPEX and OPEX) and treatment capacity. This study reports on the costs of 11 international CFW schemes including the factors affecting CAPEX and OPEX and levelized costs of nitrogen and phosphorus removal. The estimated levelized CAPEX and OPEX ranged from US$15/m 2 to $2537/m 2 and from $0.5/m 2 y –1 to $181/m 2 y –1, respectively, for CFW schemes of 55–3926 m 2 . Data from six full-scale CFWs showed that the costs per kg of nitrogen removed ($10 to $120/kg) by plant uptake were consistently lower than those of phosphorus ($15 to $3250/kg). CFW scheme scale was found to be a key influencing factor on cost, with cost per kg of nitrogen and phosphorus removed declining as CFW size increased. Use of this cost information can be generalized when considering nutrient removal and adoption of CFW technology compared to other engineered treatment options worldwide.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 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".