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Record W2002458069 · doi:10.1081/pfc-100106193

AMMONIA REMOVAL FROM COMPOST LACHATE USING ZEOLITE. II. A STUDY USING CONTINUOUS FLOW PACKED COLUMNS

2001· article· en· W2002458069 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Environmental Science and Health Part B · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsZeoliteLeachateAmmoniaAdsorptionAmmoniumPacked bedChemistryHydraulic retention timeParticle sizeCompostWaste managementEnvironmental engineeringChromatographyEnvironmental chemistryEnvironmental scienceWastewaterOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

Bench-scale packed zeolite columns were set up and operated to investigate the continuous removal of ammonium ions from compost leachate. The effects of hydraulic retention time (HRT), and particle size of the zeolite on the ammonia adsorption capacity were studied. For both the coarse particle and the powdered zeolite columns, higher ammonia removal efficiencies were achieved with longer HRT (i.e., lower influent flow rate) tests. At the same HRT, ammonia removal efficiencies from tests with powdered zeolite were generally 20% higher than tests with the coarse particle zeolite. A HRT of 6 hours was found appropriate for efficient ammonia removal, and an operating capacity of 1.31 mg N/g zeolite was obtained. Over 98% of the ammonia input from the influent was consistently removed for over 5 bed volumes (BV) of compost leachate flowing through the zeolite column. Zeolite proved to have a great potential as a medium for ammonia removal in treating composting leachate.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
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 head0.044
GPT teacher head0.294
Teacher spread0.250 · 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