REACTIVE TRANSPORT OF IRON AND HYDROCHAR COLLOIDS IN A HYDROCARBON-CONTAMINATED SUBSURFACE ENVIRONMENT
Notice bibliographique
Résumé
Petroleum hydrocarbon contaminant bioremediation in anoxic subsurface environments is challenging for three main reasons: the low bioavailability of essential nutrients, especially phosphorus (P); the low bioavailability of petroleum hydrocarbons; and the low bioavailability of terminal electron acceptors, e.g., ferric iron [Fe(III)]. Subsurface biogeochemical and transport processes are slow in making these components available to microorganisms that degrade the contaminants. Biostimulation is thus designed to increase nutrient bioavailability and to accelerate the biodegradation of the contaminants. Remedial amendments—either inorganic, organic, or both—are injected into the subsurface to increase nutrient concentrations. However, there is a risk that amendments will be rendered unavailable to microorganisms by the dominant subsurface biogeochemical and transport processes. Therefore, it is important to characterize and study potential amendments for in situ bioremediation. Accordingly, two potential amendments, a protein-based hydrochar and ferric ammonium citrate, were studied. The hydrochar was studied to determine how effective it is at increasing the bioavailability of P and petroleum hydrocarbons, and ferric ammonium citrate was studied to determine whether it increases the bioavailability of Fe(III), the main terminal electron acceptor in anoxic subsurface environments. Using hydrothermal carbonization and bone-meal extracts, several versions of the hydrochar were synthesized by systematically varying reaction conditions. The physical and chemical properties of the hydrochars were extensively characterized using a suite of spectroscopic techniques. Scanning electron microscopy (SEM) and Fourier- transform infrared (FTIR) analyses revealed that they were nonporous colloids with a primarily aliphatic core structure to which P species were attached. X-ray absorption near edge spectroscopy (XANES) analysis revealed that the hydrochars contained mostly bioavailable forms of P (i.e., adsorbed P and magnesium-bearing brushite). Their capacity to adsorb petroleum hydrocarbons was tested using benzene and batch isotherm experiments, and it was found to range between 1.6 and 2.8 μg g−1. This indicates that these potential amendments have a high affinity for petroleum hydrocarbons. A thin-disk flow method was used to determine how initial hydrochar concentration, flow rate, pH, ionic strength, and cation type affect the mechanism and rate of hydrochar attachment onto and detachment from a silty-clay soil. Equilibrium and non-equilibrium advection-dispersion equations were employed to model break- through curves obtained from the miscible displacement experiments, and a pseudo-first order kinetic equation was used to determine the rate of hydrochar detachment onto soil. In general, hydrochar particles attached to the silty-clay soil primarily via weak hydrophobic interactions; rate constants ranged from 0.016 to 0.059 h−1. These results highly suggest that hydrochar transport and distribution would not be greatly impeded in subsurface environments, especially where fluid flow is mainly through interconnected fractures. To bioremediate the groundwater and subsoils at a former gas bar in Stony Plain, AB, Canada, amendment solutions containing ferric ammonium citrate and nutrients were injected into the anoxic groundwater. Colloids in the groundwater (solid particles retained on a 0.45 μm filter) and soil cores were collected from the site. Fe speciation in these samples was characterized using XANES and FTIR spectroscopy. It was found that ferric ammonium citrate did not persist in the contaminated subsurface; however, the Fe(III) it contained was transformed to solid phases: mainly Fe(III)-organic-matter coprecipitate/complex, sulphate and chloride green rusts, and akageneite. Magnetite and ferrous calcium silicate were present in the soil samples, strongly suggesting that the secondary Fe(III) phases served as terminal electron acceptors during the microbial degradation of petroleum hydrocarbons.
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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 ».