Lanthanides Release and Partitioning in Municipal Wastewater Effluents
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of lanthanides is increasing in our society, whether in communication technologies, transportation, electronics or medical imaging. Some lanthanides enter urban wastewater and flow through municipal wastewater treatment plants (WWTPs). However, little is known about the effectiveness of treatment processes to remove these elements and the concentrations released in effluents to receiving waters. The main objective of this study was to investigate the fate of lanthanides in various wastewater treatment processes. A secondary objective was to better understand the fate of medical gadolinium (Gd) complexes; anthropogenic inputs were differentiated from geological sources using an approach based on concentration normalization with respect to chondrite Post-Archean Australian Shale (PAAS). The hypothesis was that most lanthanides, especially of geological origin, are associated with the particulate phase and could be efficiently removed by WWTPs. To monitor these elements in different WWTPs, various urban influents and effluents from simple aerated lagoons to advanced treatments were sampled in Canada. The results showed that the rates of lanthanide removal by treatment processes decrease with their atomic number; from 95% for cerium (Ce) to 70% for lutetium (Lu), except for Gd, which was minimally removed. The normalization approach permitted the determination of the origin of Gd in these wastewaters, i.e., medical application versus the geological background. By distinguishing the geogenic Gd fraction from the anthropogenic one, the removal efficiency was evaluated according to the origin of the Gd; nearly 90% for geogenic Gd and a rate varying from 15% to 50% in the case of anthropogenic Gd. The processes using alum as the flocculating agent had the highest removal efficiency from wastewater.
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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) | 0.005 | 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 it