Perfluoroalkyl acids in the Canadian environment: Multi-media assessment of current status and trends
Bibliographic record
Abstract
In Canada, perfluoroalkyl acids (PFAAs) have been the focus of several monitoring programs and research and surveillance studies. Here, we integrate recent data and perform a multi-media assessment to examine the current status and ongoing trends of PFAAs in Canada. Concentrations of perfluorooctane sulfonate (PFOS), perfluorooctanoate (PFOA), and other long-chain perfluorocarboxylates (PFCAs) in air, water, sediment, fish, and birds across Canada are generally related to urbanization, with elevated concentrations observed around cities, especially in southern Ontario. PFOS levels in water, fish tissue, and bird eggs were below their respective Draft Federal Environmental Quality Guidelines, suggesting there is low potential for adverse effects to the environment/organisms examined. However, PFOS in fish and bird eggs tended to exceed guidelines for the protection of mammalian and avian consumers, suggesting a potential risk to their wildlife predators, although wildlife population health assessments are needed to determine whether negative impacts are actually occurring. Long-term temporal trends of PFOS in suspended sediment, sediment cores, Lake Trout (Salvelinus namaycush), and Herring Gull (Larus argentatus) eggs collected from Lake Ontario increased consistently from the start of data collection until the 1990s. However, after this time, the trends varied by media, with concentrations stabilizing in Lake Trout and Herring Gull eggs, and decreasing and increasing in suspended sediment and the sediment cores, respectively. For PFCAs, concentrations in suspended sediment, sediment cores, and Herring Gulls generally increased from the start of data collection until present and concentrations in Lake Trout increased until the late 1990s and subsequently stabilized. A multimedia comparison of PFAA profiles provided evidence that unexpected patterns in biota of some of the lakes were due to unique source patterns rather than internal lake processes. High concentrations of PFAAs in the leachate and air of landfill sites, in the wastewater influent/effluent, biosolids, and air at wastewater treatment plants, and in indoor air and dust highlight the waste sector and current-use products (used primarily indoors) as ongoing sources of PFAAs to the Canadian environment. The results of this study demonstrate the utility of integrating data from different media. Simultaneous evaluation of spatial and temporal trends in multiple media allows inferences that would be impossible with data on only one medium. As such, more co-ordination among monitoring sites for different media is suggested for future sampling, especially at the northern sites. We emphasize the importance of continued monitoring of multiple-media for determining future responses of environmental PFAA concentrations to voluntary and regulatory actions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.028 | 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".