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Record W4404631694 · doi:10.1016/j.jwpe.2024.106586

A novel biochar adsorbent for treatment of perfluorooctanoic acid (PFOA) contaminated water: Exploring batch and dynamic adsorption behavior

2024· article· en· W4404631694 on OpenAlexafffund
Malihe Afrooz, Rahman Zeynali, Jafar Soltan, Kerry N. McPhedran

Bibliographic record

VenueJournal of Water Process Engineering · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsUniversity of SaskatchewanGlobal Institute for Water Security
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationUniversity of Saskatchewan
KeywordsBiocharPerfluorooctanoic acidAdsorptionEnvironmental chemistryChemistryContaminationContaminated waterWater treatmentEnvironmental scienceEnvironmental engineeringOrganic chemistryEcology

Abstract

fetched live from OpenAlex

Perfluoroalkyl substances (PFAS), like perfluorooctanoic acid (PFOA), are of concern worldwide given they are ubiquitous in the environment. In this study, the treatment of PFOA-contaminated water was assessed using biochar adsorbents produced from raw canola straw (RCS) through chemical activation with H 3 PO 4 and ZnCl 2 and microwave-assisted pyrolysis (MWP). MWP conditions were evaluated to create optimal H 3 PO 4 -treated (PBC) and ZnCl 2 -treated (ZnBC) biochar adsorbents with treatments determined using a central composite design (CCD) based on the response surface methodology (RSM) considering activator concentration, and microwave heating time and power. The highest PFOA removal efficiency for PBC (3.0 mol/L) was achieved at 92 % (368 μg/g), while for ZnBC (0.55 mol/L) it was 84 % (336 μg/g). In contrast, untreated biochar and RCS had markedly lower PFOA removals of 5 % and 1 %, respectively. Activation of biochar under optimal pyrolysis conditions (6 min at 600 W) led to increased chemical functional groups, porosity, and surface area, as confirmed by FT-IR, XPS, and BET. The kinetic study indicated that chemisorption was the primary PFOA adsorption mechanism, while the Freundlich isotherm model suggested heterogeneous multilayer adsorption for PFOA removal. Further, background salts enhanced PFOA adsorption through divalent bridges and salting-out mechanisms. PBC and ZnBC adsorbents performed well over a broad pH range of 3 to 9. Lastly, Yan and Yoon-Nelson models were used to assess adsorption breakthrough for a model fixed-bed adsorption system. This study exhibits that PBC and ZnBC adsorbents, derived from accessible biomass, offer an environmentally friendly solution to remove PFOA from contaminated water. • Modified biochar adsorbents were synthesized via a facile and inexpensive method. • Activation enhanced biochar surface area, porosity, and functional groups. • H 3 PO 4 -treated biochar showed 92 % adsorption efficiency for PFOA. • PFOA is mainly adsorbed through electrostatic interactions. • Temperature, pH, and co-existing ions are important factors in PFOA adsorption.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.025
GPT teacher head0.269
Teacher spread0.243 · 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 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

Citations23
Published2024
Admission routes2
Has abstractyes

Explore more

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