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Enregistrement W4402115737 · doi:10.2118/0924-0120-jpt

Rhamnolipids Enhance Bioremediation of Petroleum-Contaminated Soil

2024· article· en· W4402115737 sur OpenAlexaboutno aff
Chris Carpenter

Notice bibliographique

RevueJournal of Petroleum Technology · 2024
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueMicrobial bioremediation and biosurfactants
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBioremediationPetroleumEnvironmental scienceContaminationSoil contaminationWaste managementPetroleum engineeringEnvironmental chemistryGeologyChemistrySoil waterEngineeringSoil scienceEcologyBiology

Résumé

récupéré en direct d'OpenAlex

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 215952, “Enhancing Bioremediation of Petroleum-Contaminated Soil Using Rhamnolipids: A Combined Laboratory and Field Study,” by Pan Ni, Lehigh University; Yonglin Ren, SPE, Stepan Oilfield Solutions; and Derick G. Brown, Lehigh University, et al. The paper has not been peer reviewed. _ Hydrocarbon spills can occur at various stages of the oil and gas exploration and production process. Treating these spills onsite to avoid more-expensive excavation and incineration processes would be beneficial. The study outlined in the complete paper aims to optimize the use of rhamnolipid biosurfactants for enhancing the bioremediation of hydrocarbon-contaminated soil. The goal of this work was to explore the effects of rhamnolipid application on hydrocarbon degradation rate under both laboratory and field conditions and to examine the effects of this treatment on the indigenous soil microorganism population. Introduction The authors write that, to the best of their knowledge, previous research studies on rhamnolipid-based soil remediation focused on either laboratory or field tests and that comparison between laboratory-scale and field-scale tests is overlooked but necessary for practical applications. Materials and Methods Materials and Chemicals. The soil used for this work (23 kg for the laboratory test, 10 metric tons for the field test) was obtained from a contaminated site in Longford Mills, Canada. The soil properties are presented in Table 1 of the complete paper. The rhamnolipid stock solution featured 9.8 wt% rhamnolipid blends in deionized water. Another commercial remediation agent (enzyme-based) was used in the field test to compare with the performance of rhamnolipid. Ammonium chloride (NH4Cl) and potassium hydrogen phosphate (K2HPO4) also were used along with sodium hydroxide (NaOH). Experimental Setup. Both laboratory and field tests were ex-situ tests using simulated soil piles. The laboratory test was conducted for 193 days. For the laboratory experiments, an aerobic/anaerobic respirometer system equipped with a low-temperature incubator was used to monitor the in-situ oxygen uptake inside eight reactors (Fig. 1). Each reactor contained 250 g of soil with rhamnolipid doses of 0, 0.1, 0.5, and 1 g/kg. The temperature was set to 25°C. Inside each reactor was placed 10 mL of 4-M NaOH in a 20-mL glass beaker to adsorb the produced CO2. A parallel set of eight reactors was prepared and operated under the same conditions. The nutrients of nitrogen and phosphorous (NH4Cl and K2HPO4) were added at specific times based on the oxygen uptake rate monitored by the respirometer. To avoid the possible inhibition of the microbes in the soil as a result of high ionic strength (greater than 160 mM) in the soil pore water, NH4Cl and K2HPO4 were added so that the molar concentration in the soil pore water did not exceed 100 mM. The field test is being conducted in Longford Mills, Ontario, Canada, and is ongoing at the time of writing. For the field test, 10 metric tons of soil were mixed to achieve homogeneity before the preparation of the soil piles. Five different treatment conditions were examined using duplicate soil piles (10 piles total), with each consisting of 1 metric ton of soil. Nutrient addition was similar to that used in the laboratory tests. Temperature and moisture were monitored every few days at five points in each soil pile, and the pH was monitored once every month at five points.

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 candidatesCharge utile insuffisante (le modèle a refusé de juger)
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 enseignants0,044
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
Bibliométrie0,0000,001
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)0,0010,000

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 Opus0,004
Tête enseignante GPT0,224
Écart entre enseignants0,221 · 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

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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