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Record W4406376120 · doi:10.3390/w17020202

Continuous Flow Electrocoagulation System for Enhanced Phosphorous Removal in Decentralized Wastewater Treatment Systems

2025· article· en· W4406376120 on OpenAlexafffund
James Hayden, Bassim Abbassi

Bibliographic record

VenueWater · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsUniversity of Guelph
FundersUniversity of Guelph
KeywordsEffluentElectrocoagulationEutrophicationWastewaterSewage treatmentEnvironmental sciencePhosphorusHydraulic retention timeEnvironmental engineeringSuspended solidsPulp and paper industryChemistryNutrientEngineering

Abstract

fetched live from OpenAlex

Decentralized wastewater treatment systems (DWTS) are significant contributors to the eutrophication of surface water bodies due to a lack of treatment mechanisms that target dissolved phosphorus removal. Existing advanced treatment systems are expensive to operate, large in nature, and require frequent maintenance, making them unattractive to DWTS owners. This study aims to investigate the development of a continuous flow treatment system that uses electrocoagulation (EC) to remove dissolved phosphorus from small wastewater streams such as septic tank effluent (STE). Operational parameters, including system hydraulic retention time (HRT), applied current density, and wastewater composition, were optimized to maximize total phosphorus (TP) removal most cost-effectively. Using an HRT of 10 min, an applied current density of 2.0 mA/cm2, and an influent concentration of 20 mg/L, the orthophosphate (OP) and TP removal percentages achieved were 99.9 and 88.1%, respectively. Under these conditions, the average effluent Al3+ concentration in the treated effluent was measured to be 1.0 mg/L while the total suspended solids concentration was measured to be 51 mg/L. The operation cost was estimated to be 0.056 CAD/m3. The results demonstrate that the EC reactor is effective in removing dissolved phosphorus from wastewater and is therefore a viable option in mitigating the risk of downstream eutrophication caused by inadequately treated STE.

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 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.629

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 studies0.0000.000
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 head0.006
GPT teacher head0.231
Teacher spread0.225 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2025
Admission routes2
Has abstractyes

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