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Enregistrement W7029282736

The Interplay of Physical and Biogeochemical Processes in Determining Water Cap Oxygen Concentrations within Base Mine Lake, the First Oil Sands Pit Lake

2019· dissertation· en· W7029282736 sur OpenAlexaboutno aff

Notice bibliographique

RevueMacSphere (McMaster University) · 2019
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueMine drainage and remediation techniques
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTailingsBiogeochemical cycleOil sandsHypolimnionEutrophicationLand reclamationWetlandHydrology (agriculture)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Syncrude Canada’s Base Mine Lake (BML), is the first oil sands pit lake and is being used to evaluate water-capped tailings technology for fluid fine tailings (FFT) management. To be successful, pit lakes must achieve the ecological role of a natural lake, requiring the development of oxygenated water cap capable of supporting macrofauna. Due to the reductive nature of the FFT stored at the bottom, oxygen-consuming constituents (OCC) such as methane, sulfide and ammonium can be mobilized into the water cap of oil sands pit lakes, posing a threat to the success of the reclamation. Results from BML are vital to inform successful pit lake design with a further 10+ pit lakes projected for collective waste reclamation required in the region, currently awaiting permitting. This field study established BML water cap depth dependent oxygen consumption rates (OCR), identified the key OCC driving those rates and modeled the roles of biogeochemical oxygen consumption and physical mixing in establishing water cap oxygen profiles during early stage development (< 5 years post commissioning). The balance between these two discrete processes underpins the likely viability of this management strategy for oil sands FFT. Results identify high OCR, in the range of highly productive eutrophic to hyper eutrophic lakes, in the vicinity of the FFT water interface, i.e. where concentrations of OCC are highest. Observed OCR rates decreased away from the FFT water interface, as concentrations of OCC decreased. The important OCC associated with high OCR were methane and ammonium. While the OCR values in the hypolimnion were extremely high, a minimally oxic FFT water interface persisted (<10 μM O2) contrasting the anoxic hypolimnetic waters typically observed in highly productive systems. Water cap oxygen mass balance modeling revealed physical mixing of oxygen into the hypolimnion from the metalimnetic region of the BML water cap currently slightly exceeds the oxygen being consumed through biogeochemical redox cycling, explaining the persistence of low levels of oxygen to the FFT water interface in the BML water cap (~ 10 m in depth). However, higher mobilization of OCC from the FFT as FFT consolidates, and/or higher rates of microbial biogeochemical cycling as microbial communities continue to establish and grow within BML, and/or decreased physical vertical transport of O2 into the hypolimnion, would all shift the oxygen balance towards greater consumption and thus would result in the migration of the oxic-anoxic boundary and OCC higher up into the water cap where they would directly impact the surface zone oxygen concentrations. Modeling results here identify that without the physical injection of oxygen into the hypolimnion, currently observed, OCR rates would generate anoxic conditions that would reach the middle of the metalimnion within this system within 24 hours. The development of an anoxic zone would facilitate greater generation of OCC directly within the water cap through anaerobic microbial biogeochemical cycling, the high levels of sulfate (~ 2 mM) observed within the BML water cap, which exceeds water cap oxygen concentrations by 3 orders of magnitude, indicate that generation of ΣH2S within this pit lake water cap would be a substantive risk to the development of a stable surface oxic zone that can support macro fauna. In addition, the emergence of nitrification, as one of the main oxygen-consuming reactions, was assessed experimentally to determine the potential effects on the oxygen depletion in BML water. Experimental results identified active nitrification with rates in the comparative range of marine to eutrophic estuary environments, with BML water collected from the metalimnion-hypolimnion interface, i.e. where the highest conversion of ammonia to nitrate was observed in field results. However, a comparison of oxygen consumption due to nitrification based on experimental, nitrification only results versus results from the field where nitrification as well as methanotrophy and other oxygen consuming processes are possible indicate oxygen consumption due to nitrification alone in the field is six times lower than the experimental oxygen consumption observed. These results highlight the competition for oxygen by multiple processes within BML, which suppress nitrification below levels observed under ideal experimental conditions. Characterization and modelling results of BML water cap oxygen concentrations carried out in this doctoral research reveal a new understanding of the important processes driving observed oxygen concentrations. These new insights delineate the potential effects of mobilized reduced constituents in the water cap from FFT and processes that may mitigate or exacerbate these impacts. Thus these results are of significant relevance to both the oil sands industry as well as other natural or anthropogenically impacted environments with high oxygen demand.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,681
Score d'incertitude au seuil0,634

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
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 Opus0,005
Tête enseignante GPT0,198
Écart entre enseignants0,193 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
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
Publié2019
Routes d'admission1
Résumé présentoui

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