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Record W2904463131 · doi:10.5004/dwt.2018.23418

Efficiency of microplastics removal in selected wastewater treatment plants – preliminary studies

2018· article· en· W2904463131 on OpenAlexaboutno aff
Ewa Wiśniowska, Katarzyna Moraczewska-Majkut, Witold Nocoń

Bibliographic record

VenueDesalination and Water Treatment · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsnot available
Fundersnot available
KeywordsMicroplasticsEffluentWastewaterSewageEnvironmental scienceSewage treatmentPollutionSewage sludgeEnvironmental chemistryEnvironmental engineeringPulp and paper industryChemistryBiologyEcology

Abstract

fetched live from OpenAlex

ABSTRACT Recently more and more attention is being paid to pollution of the environment by microplastics. The problem is well recognized in marine and surface water in Western Europe. There are also well-documented studies on removal of microplastics during wastewater treatment in Germany, Finland, Denmark, Canada and Norway. So far the problem has not been identified in Eastern European countries, including Poland. Because of this, it is of high importance to evaluate the scale of problem also in these countries. The paper presents the results of preliminary studies on microplastics content in influents, effluents and sewage sludge of selected wastewater treatment plants in southern Poland. It was stated that content of microplastics in influents was in the range from 19.4 · 10 3 to 552.2 · 10 3 particles per 1 m 3 , in effluents from 28 to 960 particles per 1 m 3 . Microlitter particles removed from raw wastewater were accumulated in sewage sludge. Total concentration of microplastic particles in the sludge was in the range from 6.7 · 10 3 to 62.6 · 10 3 particles per 1 kg d.m. In liquid phase, finer fractions of microplastics were dominant. In sewage sludge larger particles, especially fibers, were effectively cumulated. About 95%–99% removal efficiency of microplastics from influents was stated. No correlation has been found between the wastewater flow rate and the content of microplastics in influent, these problems require, however, more detailed analysis of microplastics chemical composition and mass.

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 score0.060
Threshold uncertainty score0.378

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 head0.018
GPT teacher head0.246
Teacher spread0.228 · 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

Citations40
Published2018
Admission routes1
Has abstractyes

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