MétaCan
Menu
Retour à la cohorte
Enregistrement W2169580185

Optimizing Solvent Extraction of PCBs from Soil

2009· dissertation· en· W2169580185 sur OpenAlexaboutno aff
Maureen O'Connell

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2009
Typedissertation
Langueen
DomaineEngineering
ThématiqueEnvironmental remediation with nanomaterials
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSolvent extractionExtraction (chemistry)Environmental scienceSolventEnvironmental chemistryChemistryChromatographyOrganic chemistry
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Polychlorinated biphenyls (PCBs) are carcinogenic persistent contaminants. Although their manufacturing in North America ceased in the late 1970s, their high heat resistance made their use widespread over their production lifetime. As a result, PCB contamination has occurred globally and in particular has plague brownfield redevelopment in urban environments. The remediation of PCB contaminated soil or sediments has historically been dealt with through the expensive and unsustainable practice of excavation followed by off-site disposal or incineration. One potential technology that has shown some success with on-site remediation of PCB contamination is solvent extraction. Solvent extraction is technically simple; it involves excavating the contaminated soil, placing it in a vessel and adding solvent. The PCBs are extracted by the solvent and the treated soil is returned for use on site. Although successful at removing a large quantity of PCBs from some soils, this technology can be improved upon by extracting additional PCB mass and making the extraction more efficient and suitable for colder climates.
\nThis thesis aimed to identify the factors controlling PCB extraction with solvents in order to optimize PCB extraction as it is applied on different soil types and in various climates. The research investigated the impact of elevated moisture contents (≤ 20% by weight) on solvent extraction efficiency, the effects of low temperatures (<5ºC) on solvent extraction, and developed a kinetic model to represent PCB solvent extraction. As past research has shown, weathered PCB in soil is more difficult to remove. Contaminated field samples from Southern Ontario, Canada were used for this work, rather than synthetically prepared samples.
\nThe impact of elevated moisture contents and low temperature on extraction efficiency was determined through a series of screening experiments using polar and non-polar solvents at both 20ºC and 4ºC. It was hypothesized that improved extractions may be possible with combinations of polar and non-polar solvents. Based on the results of these screening experiments, a factorial experiment was designed using solvent combinations to further assess the role of moisture contents and low temperatures. The role of PCB mass distribution among grain sizes was also evaluated to see if optimization based on grain size separation is possible. Finally, experiments were performed to generate data suitable for the development of a kinetic model that incorporates key factors affecting solvent extraction.
\nFour suitable solvents for solvent extraction in Ontario were identified through a literature review and these were used for this work: isopropyl alcohol (polar), ethanol (polar), triethylamine (non-polar) and isooctane (non-polar). Triethylamine outperformed isooctane and performed best on its own rather than in combination with polar solvents. An interaction between soil moisture content and choice of polar solvent (isopropyl alcohol versus ethanol) was established: a given polar solvent achieves optimal PCB extraction at a specific moisture content range. Temperature was also identified as significantly influencing PCB extraction. Although it was determined that PCBs were distributed unevenly amongst grain sizes, a simple relationship between grain size and fractional organic carbon or organic content was not found.
\nA simple two-compartment kinetic model was developed which is suitable for predicting the PCB concentrations extracted up to 24 hours. The model incorporates both temperature and soil to solvent ratio in order to estimate PCB concentration extracted.

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)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,048
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
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 Opus0,007
Tête enseignante GPT0,183
Écart entre enseignants0,176 · 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.

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

Citations3
Publié2009
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueUWSpace (University of Waterloo)Même sujetEnvironmental remediation with nanomaterialsTravaux en français237 207