Insights Into the Declined Efficacy of In Situ Deep Soil Benzene Biostimulation: An Investigation Across Four Sites Over Three Years
Notice bibliographique
Résumé
ABSTRACT Biostimulation is a widely used approach for remediating deep‐layer oil‐contaminated soils. However, at four petroleum hydrocarbon‐contaminated sites in Saskatchewan, Canada, we observed a marked decline in the effectiveness of benzene biostimulation over a three‐year period. The underlying causes of performance decline are poorly understood. To investigate the factors contributing to the reduced efficacy of biostimulation, this study hypothesizes that either the delivery of amendments was affected by soil matrix or the prevalence of benzene‐degrading microbes declined in areas requiring remediation. Deep soil samples were collected annually and analyzed for benzene concentration, water‐soluble ions, and the abundance of functional microbial genes associated with benzene degradation. A generalized linear mixed model (GLMM) was used to examine the relationship between the binary remediation outcome (success or failure) at the sample scale and water‐soluble ion concentrations, with site treated as a random effect. A linear model was applied to investigate the relationship between failure rate of remediation and soil properties at the site scale. The GLMM identified soil pH, along with soluble PO 4 3− , Ca 2+ , SO 4 2− , NO 3 − and NO 2 − as significant contributors to the effectiveness of biostimulation at sample scale. Notably, Ca 2+ and PO 4 3− exhibited comparable importance but opposite effects, with Ca 2+ negatively and PO 4 3− positively associated with successful remediation. The linear model found that soil water‐soluble Ca 2+ and SO 4 2− were positively correlated with the rate of declined remediation outcomes at site scale ( p < 0.05). We inferred that at sites with moderately high background SO 4 2− , decade‐long natural attenuation rendered the benzene more recalcitrant. High soil‐soluble Ca 2+ could sequester the phosphate introduced by amendments, forming precipitates that reduced phosphorus availability. Given that the amendments contained nitric acid, an observed increase in pH or a decrease in electrical conductivity in the samples after biostimulation relative to pre‐biostimulation conditions, suggests that fewer amendments reached the polluted plume. This may indicate that the initial infiltration pathways became clogged, potentially due to Ca–P precipitation. Moreover, the decline in functional genes linked to anaerobic benzene degradation suggests insufficient microbial capacity to utilize the amendments. This emphasizes the need to tailor biostimulation strategies for successful in situ biostimulation, ensuring effective delivery of amendments, particularly over long‐term practices, and to sustain microbial activity under field conditions.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| 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 tête enseignante, 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 ».