Quantifying the Concentration and Loads of Dissolved Organic Contaminants in Snowmelt Runoff from Manure-Amended Agricultural Fields
Notice bibliographique
Résumé
Agriculture is an integral part of Canada’s economy, making 1.6% of the country’s GDP. In Manitoba, swine production contributed nearly 1.4 billion dollars in revenue from 8.4 million pigs sold to the market. Liquid swine manure is widely used as fertilizer in the province. However, there are risks with the use of liquid swine manure as fertilizer because liquid swine manure can contain organic contaminants, such as antibiotics and steroidal hormones. Globally, there is evidence of increased soil and freshwater contamination from antibiotics and estrogens, resulting in the increased presence of antibiotic-resistant genes and estrogen-related physiological disruptions, respectively. In the Canadian Prairies, a majority of the annual runoff occurs during the brief snowmelt period, when runoff occurs over frozen soils. Temporal changes in the transport of antibiotics and estrogens during this important hydrological period are not well understood but are critical to understanding the fate of these organic contaminants. This thesis quantified the dissolved concentration and load of a 1) steroidal hormone, 17β-estradiol, and 2) antibiotic, sulfamethoxazole, in snowmelt from an agricultural field with a history of manure application under different manure management practices (i.e., no manure applied, manure applied on the sub-surface, and manure applied on the surface) over the snowmelt period. Research experiments in chapter 2 used two components (a field study during snowmelt and a laboratory simulation with flooded intact soil cores collected from the manured field) to quantify the dissolved 17β-estradiol in flood water and pore water for the laboratory simulation and snowmelt for the field study. Chapter 3 quantified the dissolved sulfamethoxazole in snowmelt in the same field study as chapter 2. 17β-estradiol (mean laboratory pore water concentration = 1.65 ± 1.2 μg/L; mean laboratory flood water concentration = 0.488 ± 0.58 μg/L; and mean field snowmelt concentration = 0.0619 ± 0.048 μg/L) and sulfamethoxazole (0.0345 ± 0.066 µg/L) were detected in all water samples, although there were no significant differences in the concentrations measured among the different manure application methods. 17β-estradiol concentrations varied between the laboratory and the field, with higher concentrations measured in the laboratory simulation. Pore water concentrations of 17β-estradiol from the laboratory study significantly increased over time, corresponding with changes in pH. In contrast, there was no significant change in the field snowmelt concentrations measured over time for both 17β-estradiol and sulfamethoxazole. The mean cumulative load of 17β-estradiol (6.91 ± 3.7 ng/m2) and sulfamethoxazole (4.12 ± 3.6 ng/m2) approximates the magnitude of 17β-estradiol and sulfamethoxazole that could be mobilized from manured fields during snowmelt. There was a significant increase in cumulative load over time for both 17β-estradiol and sulfamethoxazole, suggesting that the load is driven by the snowmelt volume rather than concentration. Furthermore, the 17β-estradiol load from plots with manure applied on the sub-surface was significantly larger than the surface application of manure and no manure application. This thesis provides preliminary insights to improve current manure management practices in the Canadian Prairies to include organic contaminants.
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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 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) | 0,000 | 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 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 ».