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Record W4400190783 · doi:10.1016/j.memsci.2024.123045

Evaluation of microplastic particle transmission in a microfiltration process using fluorescence measurements: Effect of pore size and flux

2024· article· en· W4400190783 on OpenAlexaff
Ryan J. LaRue, Ashleigh Warren, David R. Latulippe

Bibliographic record

VenueJournal of Membrane Science · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMembraneMicrofiltrationFiltration (mathematics)Particle sizePermeationParticle (ecology)ChromatographyWastewaterChemistryEffluentChemical engineeringAnalytical Chemistry (journal)Materials scienceEnvironmental engineeringEnvironmental science

Abstract

fetched live from OpenAlex

Microplastic (MP) pollution in the aquatic environment is widespread, with a significant fraction of these particles originating from municipal wastewater treatment plant (WWTP) effluents. Whereas membrane filtration processes are touted as an effective MP removal strategy, the rejection of irregularly-shaped plastic particles, similar to those found in WWTPs, is poorly understood. Here, we characterize the filtration of irregularly-shaped MP particles (∼10 μm) through Durapore® microfiltration membranes (0.45 and 5 μm pore sizes). These particles were produced via ball-milling/sieving processes from a fluorescent polyethylene feedstock, enabling particle concentrations to be quantified using a standard fluorometric plate reader. Permeate samples from the 0.45 μm membrane exhibited low fluorescent intensities relative to feed samples, implying minimal MP transmission. Conversely, appreciable MP transmission through the 5 μm membrane was noted, with sizable MPs (∼2–7 μm) found in the permeate. This transmission was exacerbated at higher fluxes which emphasizes how operating conditions can govern MP retention. Post-filtration analyses demonstrated that particle capture occurred largely at the feed-membrane interface, where greater MP intrusion into the membrane was seen at the larger pore size. These results reaffirm the importance of choosing an appropriate membrane/membrane pore size and operating conditions to maximize MP retention in WWTPs.

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)0.006
metaresearch head score (Gemma)0.001
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 score0.164
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.024
GPT teacher head0.294
Teacher spread0.270 · 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

Citations9
Published2024
Admission routes1
Has abstractyes

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