Stabilized hydrogen peroxide for the remediation of hydrocarbons and MTBE in high temperature and saline groundwater
Notice bibliographique
Résumé
Abstract A field pilot‐scale test was conducted to determine if the use of citric acid‐stabilized hydrogen peroxide (H2O2) is effective in reducing dissolved concentrations of petroleum hydrocarbon compounds (PHCs) and the additive methyl tert‐butyl ether (MTBE) in impacted high salinity groundwater. The test was carried out adjacent to an operational hydrocarbon fuel facility in Western Saudi Arabia. The pilot test was based on the results of laboratory tests, which suggested that hydrogen peroxide stabilized with citric acid (C6H8O7) would enhance the degradation of the dissolved PHCs and associated MTBE within a saline groundwater. A 7.5 weight percent hydrogen peroxide solution was injected into a series of injection wells positioned to target a PHC‐impacted plume within an unconfined aquifer. The plume contains total benzene, toluene, ethylbenzene, and xylenes (BTEX) at concentrations up to 6,890 micrograms per liter (μg/L). The MTBE concentration within the groundwater was detected at concentrations of up to 55,182 μg/L, whereas the groundwater salinity was approximately 7,000 milligrams per liter (mg/L). A total of 9,012 liters of citric acid‐stabilized hydrogen peroxide solution was injected over three events spaced over a 1‐month period. The results of the pilot test indicated that injection of stabilized hydrogen peroxide was effective in reducing the concentration of dissolved PHCs within the plume, including BTEX and other aromatic hydrocarbons. The average concentration decrease for total BTEX was 72% with up to 97.4% reduction being measured in a sample collected from one key monitoring well during the treatment period. MTBE was also effectively treated during the pilot test with an average MTBE degradation of 50% being realized during the test and up to 86% concentration decrease being measured in some groundwater samples. While reductions in MTBE concentrations were noted, no increase in tertiary butyl alcohol was measured, which is a promising finding. The general water quality did not fluctuate significantly between pre‐ and postinjection with the pH, oxidation–reduction potential, and dissolved oxygen remaining relatively constant. The dissolved iron, nitrate, and sulfate concentrations vary during the injection period with nitrate decreasing to below detection limits following the final injection, whereas sulfate decreased in two of the three monitoring wells following the injection. Dissolved iron concentrations remained relatively constant in two of the three monitoring wells (NJBP45 and NJBP46) during the injection events, whereas dissolved iron in monitoring well NJBP44 decreased from a baseline concentration of 1.03 μg/L to 0.09 μg/L, suggesting that the ferrous iron in solution was being oxidized to ferric iron. Measurements of the preinjection microbiological community indicated that the community is diverse within the injection area based on deoxyribonucleic acid extraction by polymerase chain reaction as well as sequencing and clustering. Subsequent analyses of the microbiological community postinjection indicated that the community diversity and biomass was reduced with a shift to a more aerobic population, at least over the short term. Results of compound specific isotope analyses are consistent with the concentration data and show petroleum hydrocarbon and MTBE was degraded by the citric acid‐stabilized hydrogen peroxide treatment.
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) | 0,000 | 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) | 0,000 | 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 ».