Experimental Work on the Behaviour of Synthetic Soils Contaminated with Light Hydrocarbon, and Subsequent Remediation Thereof
Notice bibliographique
Résumé
Abstract The contamination of soil by light hydrocarbons is one of the most frequently encountered environmental problems. Leakage from underground storage tanks at refueling stations is the most common source, but others are refineries or production facilities. Research at the University of Calgary has been examining the application of proven petroleum reservoir engineering methods to address this issue. By use of horizontal boreholes, and cyclic water and gas injection, the contaminant can be recovered in situ. Laboratory work has been ongoing to determine basic data on the contamination and remediation aspects of the process. In this paper, we report work that has been done to characterize the saturations during the contamination and remediation processes. Sand that typifies the grain shape and distribution of native soil was used. This sand was strongly water wet. To examine the impact of the humic acid from topsoil loam, humic acid was extracted and plated onto the sand. Characterization of the sand has been performed to demonstrate that the humic acid has bound to the surface of the sand grain, and has altered the surface wettability. Results of coreflooding also demonstrated that the performance of the organic coated sand, and the untreated sand, will lead to different contamination and remediation results. It appears that the treated sand exhibits hysteresis, for if it was originally in contact with water, it behaves as if water wet. If, instead, it was originally in contact with kerosene, it behaves as if oil wet. Introduction In our industrial world, one of the consequences of economic and technologic development is the discharge of undesirable materials into the environment. Of the many compounds released to the environment, the volume of petroleum related products released is very large. The importance of petroleum as the primary source of energy for our society is the main reason for this, reflecting the widespread usage of petroleum. The main discharge site for liquid hydrocarbons is at commercial refueling stations, from underground storage tanks ("UST") that hold gasoline. Small holes in these tanks can result from corrosion or material stress. Further locations for possible leakage are at pipe connections or flanges, where shifting soil can lead to a compromise in the integrity of the connection. It has been estimated (1) that of the roughly 1.6 million underground storage tanks in the United States, about 20% are or have discharged gasoline or diesel into the surroundings. Furthermore, conservative estimates of the cost to clean up these UST sites are around $37 billion U.S. dollars (year 2000 value). If all sites that have been contaminated by light hydrocarbons are included, such as refineries and airport tank farms, remediation is a multibilliondollar per year industry. For Canada, scaling the $37 billion (U.S.) clean up cost estimate by population and currency differences leads to an estimate of $5 billion Canadian (year 2000 value) for the clean up of contaminated sites in Canada. A significant fiscal incentive therefore exists to improve both the cost effectiveness, and also the process efficiency, of remediation.
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 | 0,001 |
| 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) | 0,001 | 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 ».