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Record W7116082613 · doi:10.1016/j.jenvman.2025.128374

Variation in microplastic characteristics during biosolid stabilization across wastewater resource recovery facilities in the United States and Canada

2025· article· en· W7116082613 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Environmental Management · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsnot available
FundersGreat Lakes Water AuthorityUniversity of Memphis
KeywordsBiosolidsResource recoveryWastewaterPolymerAnaerobic digestionIncinerationMicroplastics

Abstract

fetched live from OpenAlex

Microplastic (MP) particles have emerged as contaminants in biosolids globally, raising concerns about their potential ecological risks after land application. This study quantified MP particles in 50 biosolid samples (25 pre-stabilized, 25 post-stabilized) collected from 25 Wastewater Resource Recovery Facilities (WRRFs) across the United States and Canada. Three stabilization processes were evaluated, including Anaerobic Digestion (AD; 21 samples), Lime Stabilization (LS; 2 samples), and Incineration (INC; 2 samples). MP abundance, size distribution, shape, and polymer composition were characterized using standardized digestion, density separation, and micro-FTIR. MP particles after AD increased from 2030 to 2682 MP/g dw (+32.1 %). Small particles (20–150 μm) increased by 443 %, while those >600 μm decreased by 97 %, indicating strong fragmentation. Resistant polymers increased sharply, like PE, PS, and SR, while degradable polymers decreased, including PMMA and PEVA. LS reduced MP particles from 1388 to 964 MP/g dw (−30.5 %), yet fragmentation still occurred, with 20–150 μm particles increasing 442 % and particles >600 μm decreasing 97 %. Polymer shifts included increases in PE, ABS, and PU, and declines in PP, PVC and PEVA. INC lowered MP abundance from 2618 to 1909 MP/g dw (−27.1 %). Small particles increased by 277 %, and particles >600 μm decreased by 99 %. Heat-resistant polymers increased, including PS, PTFE, and PE, while sensitive polymers decreased, such as PMMA, PP and PEVA. Current biosolid stabilization methods are not specifically designed to address MP particles; however, the results of this study clearly show that MP particles become more fragmented and mobile through stabilization, particularly through AD and LS. This enhances the ecological and mobility risks of MP particles once introduced into the environment, particularly in agricultural soils. • Characterized MP particle abundance, size, shape, and polymers in biosolids from 25 WRRFs across the U.S. and Canada. • Anaerobic Digestion increased MP concentration by +32.1 % and strongly shifted particles toward smaller size classes. • Lime Stabilization (−30.5 %) and Incineration (−27.1 %) reduced MP particle counts but increased fine-particle generation. • Resistant polymers became more prevalent post-treatment, while degradable polymers decreased. • Changes in particle size and composition indicate higher mobility and potential environmental risk after land application.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.169
Teacher spread0.166 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2025
Admission routes1
Has abstractyes

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