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Record W4402307482 · doi:10.1016/j.cej.2024.155534

On safety of sewage biosolids valorisation: Distribution of PFAS, PAHs, PCDD/Fs, and heavy metals in low-temperature pyrolysis end-products for agricultural and energetic applications

2024· article· en· W4402307482 on OpenAlexafffund
Felizitas Schlederer, Edgar Martín-Hernández, Céline Vaneeckhaute

Bibliographic record

VenueChemical Engineering Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsUniversité LavalCentrEau - Quebec Water Management Research Centre
FundersNatural Sciences and Engineering Research Council of CanadaSustainable Development Technology Canada
KeywordsValorisationBiosolidsEnvironmental chemistryPyrolysisSewage sludgeHeavy metalsEnvironmental scienceSewageWaste managementChemistryEnvironmental engineering

Abstract

fetched live from OpenAlex

• Study on micropollutant distribution between biochar, APL and pyrolysis oil. • Determined PFAS in biochar, APL and pyrolysis oil. • Biochar met the guidelines for agricultural valorisation, except for heavy metals. • High methane production was achieved during anaerobic digestion of APL. • CO 2 supply during pyrolysis achieved highest calorific value of pyrolysis oil. Pyrolysis is a suitable process for sewage sludge valorisation while potentially reducing micropollutants. However, previous studies mainly focused on micropollutants in biochar, neglecting their presence of aqueous pyrolysis liquid (APL), pyrolysis oil, and gas. This study analyses the distribution of 66 micropollutants, including PFAS, dioxins and furans (PCDD/Fs), heavy metals (HMs), and polycyclic aromatic hydrocarbons (PAHs) across biochar, APL and pyrolysis oil. Additionally, the impact of a carrier gas supply (N 2 and CO 2 ) on micropollutants distribution was evaluated. In a second stage, the safe use of the pyrolysis end-products for agricultural and energetic purposes was explored. PFAS from biosolids were distributed in biochar (12–13 %), APL (6–7 %), and the oil phase (2–5 %). 63–74 % remained unaccounted for, possibly transferred to the gas phase, or decomposed during pyrolysis. PAHs were predominantly found in the pyrolysis oil, while PCDD/Fs were found in the biochar and pyrolysis oil. HMs were primarily found in biochar. PAH and PCDD/F values in the biochar met the European Biochar Certificate (EBC) guidelines. However, HMs surpassed the thresholds, suggesting either post-treatment or using biochar as a building material instead. Given that pyrolysis oil contains significant quantities of micropollutants, high-temperature combustion could serve for both micropollutant decomposition and energy reclamation. Energetic valorisation of APL assessed by biomethane potential tests, achieved a methane production yield of 432–450 NmL CH4 /g VS . Overall, a combined anaerobic digester and pyrolysis process, including a recirculation of the APL, the valorisation of pyrolysis oil for process heating, and the use of CO 2 from biogas as pyrolysis carrier gas, is suggested for further study.

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 score0.014
Threshold uncertainty score0.532

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 head0.004
GPT teacher head0.186
Teacher spread0.182 · 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

Citations18
Published2024
Admission routes2
Has abstractyes

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