Mercury and methylmercury in snowpacks, snowmelt, and tailings ponds of the Athabasca Oil Sands Region, Alberta, Canada
Notice bibliographique
Résumé
The Alberta Oil Sands Region (AOSR) is the third largest proven oil reserve in the world and one of Canada’s major economic drivers. Industrialized extraction of this resource has resulted in the release of contaminants from various sources, such as stack emissions, volatilization and leakage of chemicals from tailings ponds, increased erosion due to land disturbance, and blowing dust from landscape disturbance, road activity, and open-pit mines. Among the contaminants released to the environment from industrial activities are organic pollutants, such as polycyclic aromatic hydrocarbons and naphthenic acids, sulphur dioxide and nitrogenous oxide species, secondary organic aerosols and the 13 elements (Ag, Ar, Be, Cd, Cr, Cu, Hg, Ni, Pb, Se, Sb, Tl, Zn) considered priority pollutants elements under the U.S. Environmental Protection Agency. Mercury (Hg) is also a contaminant of concern in the AOSR, especially methylmercury (MeHg), which is a potent vertebrate neurotoxin that biomagnifies through food webs to concentrations that may be of concern to consumers including humans. Total Hg (THg: all forms of Hg in a sample) concentrations downstream of the AOSR and THg and MeHg loadings in snowpacks have also been found to be elevated; however, sources of this Hg are not known. In this thesis, I: 1) quantify THg and MeHg concentrations in four AOSR tailings ponds varying in composition, age, surface area, and volume; and 2) determine if MeHg is actively produced in AOSR snowpacks and melted snow, or associated with the particles deposited there. I show that surface and sub-surface water concentrations of THg (unfiltered 0.30 ± 0.14 ng/L; filtered 0.26 ± 0.12 ng/L) and MeHg (unfiltered 0.15 ± 0.20 ng/L; filtered 0.08 ± 0.11 ng/L) were low in the four tailings ponds, with the highest concentrations observed in the oldest pond. In mature fine tailings that settle out in the ponds, concentrations of THg (58.6 ± 50.2 ng/g) and MeHg (0.23 ± 0.16 ng/g) were also low, with the highest concentrations also observed in the oldest pond. Overall, these ponds are not likely a major source of THg or MeHg to downstream freshwater ecosystems into which they slowly leak, though further assessment of the source of the MeHg in the oldest pond should be pursued. To determine if MeHg is produced within snowpacks and/or melted snow of the AOSR, I used Hg stable isotope incubation experiments at four sites located varying distances from the major industrial developments. Results from these experiments demonstrated that the potential rate of MeHg production was low in snowpacks (km = 0.001–0.004 d-1) and non-detectable in melted snow, except at one site (km = 0.0007 d-1), and that in situ production is therefore unlikely an important source of MeHg to AOSR snowpacks. Concentrations of MeHg on particles (pMeHg) in snowpacks increased linearly with distance from the upgraders (R2 = 0.71, p <0.0001); however, snowpack total particle and pMeHg loadings decreased exponentially over this same distance (R2 = 0.49, p = 0.0002; R2 = 0.56, p <0.0001). Thus, at near-field sites, total MeHg loadings in snowpacks were high due to high particle loadings, even though particles originating from industrial activities are not MeHg rich compared to those originating from natural sources at distant sites. More research is required to identify snowpack particle sources.
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 | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 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) | 0,002 | 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 ».