Using molecular, isotopic, and spectroscopic analysis to assess natural organic matter sources and petroleum contaminants in water and sediment of the St. Lawrence Waterway (Quebec, Canada)
Notice bibliographique
Résumé
The St. Lawrence waterway is a dynamic aquatic system with inputs of organic matter (OM) originating from various terrestrial and marine sources, and a freshwater to saltwater gradient from the St. Lawrence River to the Gulf. The OM along this waterway is highly reworked in the water column, with a small fraction making its way into the sediments which acts as a long-term sink for organic matter. This waterway is also an important transportation route for numerous commodities, including petroleum and petroleum products. Our research involved the comprehensive mapping of the OM in the sediments and water column of the St. Lawrence River, Estuary, Gulf and the Saguenay Fjord. Water samples were collected along the River, Estuary, Gulf and Saguenay Fjord and parallel factor analysis was used to tease out various groups of fluorophores. In addition to the natural water samples collected along the St. Lawrence waterway, water samples containing UV irradiated petroleum products were included in the PARAFAC model to determine its efficiency at teasing out the components originating from natural OM from those linked to oil contamination. The PARAFAC analysis resulted in the identification of 6 components in our data set, with 4 components indicative of natural organic matter (3 terrestrial OM and one marine OM) and 2 representing oil components. With these findings, we were able to characterize groups of fluorophores along this transect and develop a ratio using 2 components (C4/C1) to differentiate oil contributions from natural OM in the water column. Similarly, surface sediments along the St. Lawrence Estuary, Gulf and Saguenay Fjord were collected and extracted to isolate the straight-chain n-alkanes to map the current abundances and sources of hydrocarbons in sediments of the Estuary and Gulf using molecular (diagnostic ratios) and isotopic fingerprinting (δ13C, δ2H). Variations in the carbon isotope signatures of odd-to-even straight chain alkanes allows for the differentiation of naturally occurring hydrocarbons from those of petroleum source, and the addition of hydrogen isotope signatures further increases our power of discrimination. Based on the diagnostic ratios alone, the OM sources were misrepresented and inaccurate when there was more than one input of OM. However, with the addition of the compound specific carbon and hydrogen isotope analysis, it was determined that n-alkanes were derived predominantly from natural sources. Additionally, we found that even numbered n-alkanes, which are less frequently analyzed due to their lower abundances in natural samples, would allow for the identification and tracking of petroleum-derived contaminants in sediments to a greater degree than molecular data alone. Analyzing both the possibility of oil contamination in the water column and sediments allows for the tracking of recent and long term impacts an oil spill would have along the St. Lawrence River, Estuary Gulf and Saguenay Fjord.
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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 | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 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) | 0,001 | 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 ».