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Enregistrement W4387741151 · doi:10.3897/aca.6.e111354

Relationship Between Sulfidated Nano Zero Valent Iron and a Reductive Dechlorinating Microbial Culture - Synergistic or Antagonistic? 

2023· article· en· W4387741151 sur OpenAlexaff
Chao-Lung Yang, Jingzhi Liang, Hardiljeet K. Boparai, Jiayu Yao, Line Lomheim, Elizabeth A. Edwards, Brent E. Sleep

Notice bibliographique

RevueARPHA Conference Abstracts · 2023
Typearticle
Langueen
DomaineEngineering
ThématiqueEnvironmental remediation with nanomaterials
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésZerovalent ironChemistryEnvironmental remediationReductive dechlorinationBiodegradationSulfidationEnvironmental chemistryOrganic chemistryContaminationAdsorptionBiology

Résumé

récupéré en direct d'OpenAlex

Sulfidated nano zerovalent iron (S-nZVI) has garnered significant attention from researchers due to its potential for effective in-situ remediation applications. Compared to bare nZVI, sulfidation process enhances its reactivity towards chlorinated volatile organic compounds (cVOCs) and improves its longevity (Nunez Garcia et al. 2021). Stabilizing the particles with a polymer, like carboxymethyl cellulose (CMC), can further improve the performance of S-nZVI by imparting higher stability, less toxicity towards microbial cells, and a potential biostimulatory effect, making CMC-S-nZVI a promising in-situ remediation technology (Nunez Garcia et al. 2021). Recently, CMC-S-nZVI has also been applied for field-scale remediation (Nunez Garcia et al. 2020;Brumovský et al. 2021). The contaminated sites usually have multiple pollutants and not all can be degraded by CMC-S-nZVI, thus, leaving some recalcitrant cVOCs untreated (Zhang et al. 2021). Biodegradation of cVOCs by dechlorinating microbial cultures may generate highly toxic intermediates like vinyl chloride (Kocur et al. 2016). However, coupling the two treatments may be able to compensate for each other’s drawbacks, resulting in higher efficiency, longer effectiveness, non-accumulation of intermediates, and degradation of a wider range of target contaminants. However, interacting effects of CMC-S-nZVI on dechlorinating microbial cultures have not been studied yet. This research investigates the potential of combining CMC-S-nZVI and a reductive dechlorinating microbial culture (KB-1) to degrade trichloroethylene (TCE) and 1,2-dichloroethane (1,2-DCA). CMC-S-nZVI was synthesized by a two-step method: (1) CMC-nZVI was first synthesized by reducing ferrous sulfate-CMC solution with dropwise addition of sodium borohydride solution with continuous mixing and (2) then sodium dithionite solution was added as a sulfidation agent to the freshly-synthesized CMC-nZVI (Nunez Garcia et al. 2020). Effects of different sulfur-iron ratios (S/Fe), iron, and CMC concentrations on TCE degradation were studied to obtain an effective CMC-S-nZVI formulation. Results showed a successful TCE removal by the CMC-S-nZVI but 1,2-DCA was not degraded. TCE degradation by CMC-S-nZVI fitted the first-order kinetic model, with the highest degradation rate constant (0.35 h -1 ) achieved at S/Fe = 0.1 with iron and CMC concentrations of 1 gL -1 and 0.4 wt%, respectively. This CMC-S-nZVI formulation was further tested to examine its interaction with KB-1 in terms of cVOCs dechlorination and microbial population responses. A four-day aged CMC-S-nZVI was also tested to study the effect of aging. Degradation pathways for TCE and 1,2-DCA were proposed, based on the formation of degradation products. For the coupled treatment, an increase in microbial abundance was observed by quantifying DNA concentrations. This demonstrated a synergistic relationship between CMC-S-nZVI and KB-1. Unlike the CMC-S-nZVI only treatment, microcosms containing both CMC-S-nZVI and KB-1 were found to successfully degrade the 1,2-DCA. The coupled treatment degraded TCE and 1,2-DCA at faster rates and generated lesser amounts of vinyl chloride than the KB-1 only treatment, confirming the biostimulatory effect of CMC-S-nZVI. In the KB-1 only treatment with CMC as the sole carbon and energy source, TCE and 1,2-DCA were successfully dechlorinated. Transmission electron microscopy illustrated that CMC-S-nZVI particles were attached to the microbes but did not penetrate the bacterial cells. In summary, synergistic abiotic-biotic dechlorination of TCE and 1,2-DCA was achieved by the combined treatment of CMC-S-nZVI and KB-1, suggesting that multi-contaminant sites can benefit from this approach. Additionally, the four-day aged CMC-S-nZVI performed similar to the freshly-synthesized one, demonstrating that the field-scale remediation can have a more feasible time scale for the preparation and application of these amendments.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,699
Score d'incertitude au seuil0,882

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,040
Tête enseignante GPT0,262
Écart entre enseignants0,222 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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