Production of biodispersants for oil spill remediation in Harsh environment using glycerol from the conversion of fish oil to biodiesel
Notice bibliographique
Résumé
Oil and gas operations have moved from conventional petroleum reserves to unconventional petroleum reserves such as remote offshore, deep Ocean and the Arctic. The management of oil spills is especially challenging due to these conditions. Oil spills are typically due to vessels accidents, tanker discharges, wells, offshore platforms, drilling wastes, or release of refined petroleum products and their by-products, heavier fuels and the spill of any waste oil. Oil spills impact human, plants and wild life including birds, fish and mammals, and therefore the response strategies must attempt to minimize the impact to multiple receptors. In Arctic environments, traditional mitigation and response to oil spill are less effective due to low water/air temperatures, ice cover, and other environmental conditions. Dispersants are a common response method; however there are issues with respect to toxicity and effectiveness of chemically derived dispersants. Biologically derived surfactants and dispersants, produced by naturally occurring bacteria, have some advantages including rapid biodegradation and low toxicity over the synthetic surfactants. However, large scale production is limited because of high costs associated with growth medium and operations. Cost effective production of biosurfactants could be achieved by using industrial wastes and by-products as media/substrate, thereby decreasing expensive medium costs and reducing the environmental impacts of the wastes. In this study the feasibility of glycerol, derived from the conversion of waste fish oil to biodiesel, as an effective carbon source for the production of biodispersants by indigenous Rhodococcus erythropolis and Bacillus subtilis strain is investigated Glycerol, a tribasic alcohol, is a byproduct of the biodiesel production process. Biodiesel is produced via the transesterification reaction of triglycerides in oils or fats and waste oils, with alcohols, in the presence of a homogeneous catalyst (chemical or enzymatic). In general, for every 10 kg of biodiesel produced approximately 1 kg of crude glycerol. As the production of biodiesel increases so will crude glycerol. The glycerol market is a saturated market already, and therefore any alternative market for this byproduct is advantageous to the larger scale production of biodiesel production. The waste stream ability to produce biosurfactant by indigenous Bacillus subtilis and Rhodococcus erythropolis strains will be determined. The cultivations will be performed in 250 mL flasks containing 50 ml medium at room temperature, and stirred in a rotary shaker at 30 C and 200 rpm for 3-4 days. Biosurfactant productivity will be evaluated by surface tension measurement and emulsification index (E24) determination as response variables. The produced biodispersants would have the ability to be used as an effective method to minimize the impacts of spilled oils in offshore Newfoundland and Labrador.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».