Microplastics pollution in sediments of stormwater retention ponds in Edmonton, AB
Bibliographic record
Abstract
Microplastic is a ubiquitous pollutant in the environment. They are ingested by organisms due to their microscopic size. Recent studies have shown that freshwater environments are contaminated with microplastics. Urban stormwater runoff contributes to microplastic pollution during storm events. Stormwater ponds are a significant study area for understanding the pathway of microplastics to enter rivers and serve as a network for transporting MP from land to water environment. Assessing the impact of urban runoff can help determine the sources of microplastics in Edmonton, Alberta. The sediments of twenty-four stormwater ponds were studied. The samples were characterized based on their land-use type as either Industrial, Natural, Residential, Agriculture, Highway or Park. The microplastics were extracted from each sediment to test the hypothesis of which anthropogenic catchment type contributes to microplastic pollution the most. The extraction was achieved using density separation and organic digestion methods. The samples were stained with Nile Red for quantification using microscopy. Two morphologies, fibres and fragments, were found from the practice sample, Cy-Becker. 76.9% of the particles found were fibre. 54.8% of the particles were blue, followed by 23.1% transparent and 7.7% each green, red and pink. Assessing the impact of urban sources of microplastic helps understand the fate of microplastics in freshwater systems. Department: Physical Sciences Faculty Mentor: Dr. Matthew Ross
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".