IMPACTS OF WASTEWATER EFFLUENTS AND SEASONAL TRENDS ON LEVELS OF EMERGING CONTAMINANTS IN TWO COLD-REGION RIVERS
Bibliographic record
Abstract
Emerging contaminants such as pharmaceutical drugs have been detected in waters across the globe and are of concern for human and aquatic ecosystems health. Most pharmaceuticals are found at trace concentrations, but the continuous use and potential accumulation of some of these compounds can potentially lead to effects in aquatic organisms. The principal aim of this research was to enhance our understanding of the environmental risks associated with pharmaceuticals as one group of emerging contaminants. Many pharmaceuticals are ionizable organic chemicals (IOCs), which makes their environmental and toxicological behavior particularly challenging to predict due to their partitioning mechanism which is useful to estimate the distribution of the chemical. Therefore, the objective of this thesis was to evaluate the hypothesis that uptake and effects of IOCs in aquatic organisms are influenced by the interaction between environmental, physicochemical, and biological factors. To this end, first, field studies were conducted during spring, summer, and fall of 2021 on water (diffusive gradient in thin film and conventional grab) and sediments at four locations including upstream and downstream of the wastewater treatment plants (WWTPs) of the cities of Saskatoon and Regina in the South Saskatchewan River and Wascana Creek, Saskatchewan, Canada, respectively. Second, seven representative antipsychotic pharmaceuticals were measured in water, sediment, and fish samples up- and downstream of the City of Regina WWTP. Data collected from this research effort indicate contamination with antipsychotic pharmaceuticals, with the potential to adversely impact exposed organisms. Third, non-target chemical analysis was conducted in water, sediments, and fish samples, at the two locations in Wascana Creek and throughout the three seasons. Data collected from non-target analysis indicated that pharmaceuticals, rubber components and personal care products were the priority pollutants in all the matrices and their transcriptomics changes were also supported by the qPCR analysis. Finally, transcripts of several genes of interest were determined in brain and liver samples from in fathead minnow (Pimephales promelas) exposed to the wastewater effluents in Wascana Creek during summer and fall in 2021, using a qPCR gene expression array (the EcoToxChips). The integrative approach used in this study, strongly supports the need to combine chemical analysis with transcriptomics-based approaches as useful tools for assessing of complex mixtures of contaminants in wastewater discharges and their effects in aquatic organisms. This research provides a better understanding of the risks that pharmaceuticals may pose to aquatic organisms under varying environmental conditions and thereby aid in better protecting aquatic ecosystems in the future.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 source (direct Gemma or distilled Codex), 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".