Passive sampling to understand and predict sources of wastewater and agricultural contamination in rural watersheds
Notice bibliographique
Résumé
Passive sampling techniques have emerged as valuable tools in environmental monitoring, offering distinct advantages over traditional discrete sampling methods. Discrete sampling techniques are only representative of the time of sampling, often over or underestimating concentrations of constituents in flowing surface waters. Passive samplers contain a collecting medium which accumulates and concentrates constituents to a higher level of detection, and reduces variability associated with discrete sampling. To identify and differentiate non-point sources in rural catchments, this study used passive samplers, including the diffusive gradient in thin-films (DGT) and polar organic chemical integrative sampler (POCIS), along with discrete sampling to detect a range of anthropogenic and agricultural tracers and nutrients. \nPassive samplers were deployed for select compounds including nutrients (PO4-P, NO3-N, NH4-N), anthropogenic tracers (caffeine, carbamazepine, gemfibrozil, ibuprofen, naproxen, sulfamethoxazole, acesulfame potassium, sucralose), and agricultural tracers (glyphosate, aminomethylphosphonic acid (AMPA)). Among the passive samplers deployed, the Metsorb®-DGT, selective for phosphate-bearing compounds, was evaluated for competition impacts between PO4-P and glyphosate. Competition between analytes can occur for sorbents selective for a range of compounds with similar properties. A new sampler using a weak anion exchange (WAX) resin was developed for the uptake of artificial sweeteners acesulfame potassium (ACE-K) and sucralose (SUC). \nPassive samplers were deployed at three distinct locations (Hamlet, Agricultural, and Mixed-land Sites), for 3 to 14 days, while discrete samples were collected every 3 days over 2 weeks in Fall of 2021 and Spring of 2022. The effect of potentially competing ions between phosphate-bearing compounds was evaluated by deploying triplicate Metsorb®-DGT sampler in a solution of high PO4-P and low glyphosate and AMPA. Strata-DGT samplers were developed as a potential sampler for the uptake of ACE-K and SUC and deployed in the Spring 2022 sampling event. The goals of this thesis were to (1) use DGT and POCIS to delineate anthropogenic contamination from agricultural activities to surface waters in rural communities, and to compare their effectiveness to discrete samples and (2) further develop and evaluate DGT samplers. \nDGT and POCIS had comparable concentrations with 64% of compounds not statistically different (ρ > 0.05) from discrete samples. Diffusive boundary layer (DBL) corrections were applied to Spring 2022 DGT samples, increasing the mean absolute error between DGT concentrations (CDGT) and discrete concentrations (CACTIVE) by 32% for all compounds. Phosphate was elevated at the Hamlet Site (74 ± 8.2 µg L-1) in discrete samples compared to the Agriculture Site during the Fall 2021 sampling season. The Hamlet Site land use was 40% urban and 60% agriculture, while the Agriculture and Mixed-land Sites were 94% and 88% agricultural land use, respectively. Tracers consistently showed elevated concentrations of ACE-K (412 ± 202 µg L-1) and SUC (17,089 ± 5370 µg L-1) in discrete samples across both sampling seasons as well as all other anthropogenic tracers at the Hamlet Site, while glyphosate and AMPA were elevated at the Agriculture Site (0.86 ± 1.66 µg L-1 and 1.41 ± 0.85 µg L-1, respectively). Principal component analysis (PCA) and correlation coefficients indicated a positive relationship between phosphate and anthropogenic tracers at the Hamlet Site. Biological markers (Human-specific Bacteroides), specific to human fecal contamination, were also elevated at the Hamlet Site compared to the other sites. The results of this study clearly show septic system contamination in a headwater stream and suggest impacts of septic systems to these surface water bodies may be an underappreciated nonpoint source of nutrients. \nThere was no apparent competition on the Metsorb®-DGT sampler at initial concentrations of 104 µg L-1 of PO4-P, 0.372 µg L-1 of glyphosate, and 2.14 µg L-1 of AMPA as uptake was mostly linear after 6 days of deployment. Strata X-AW resin was not a suitable binding medium for artificial sweeteners, resulting in concentrations only 39% of discrete samples for ACE-K at the Hamlet Site. \nOverall, an array of passive samplers was helpful to distinguish nonpoint sources of septic system from agricultural contamination in rural head-water streams. Passive samplers generally showed comparable results to discrete samples, with the exception of ACE-K, and reduced the variability and additional sampling and analysis associated with discrete sample collection.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| 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 | 0,000 | 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) | 0,000 | 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 tête enseignante, 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 ».