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Record W4412511552 · doi:10.1021/acsestwater.5c00439

Assessing the Costs of Constructed Floating Wetlands for the Treatment of Surface Waters and Wastewater

2025· article· en· W4412511552 on OpenAlex
John Awad, Chris Walker, Declan Page, Muhammad Arslan, Sarah A. White, Terry Lucke, Simon Beecham, Ryan J. Winston, William H.J. Strosnider, Phil Nicodemus, C. Streb, J. van Leeuwen

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACS ES&T Water · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsUniversity of Alberta
FundersCommonwealth Scientific and Industrial Research Organisation
KeywordsWetlandWastewaterEnvironmental scienceSurface waterSewage treatmentEnvironmental engineeringWater resource managementHydrology (agriculture)GeologyEcologyGeotechnical engineeringBiology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.254
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it