Hydraulic Modeling of PPCP Discharges in the Detroit River
Bibliographic record
Abstract
The occurrence and fate of pharmaceutically active and personal care products (PPCPs) in surface waters originating from urban sources is the focus of this paper. At least 80 PPCPs (e.g., analgesics, antibiotics, antiepiletics, antidepressants, and blood lipid regulars) have been identified in outflows from sewage treatment plants (STPs) and surface waters worldwide. Of these, the endocrine-disrupting chemicals (EDCs) are especially of concern because of their broad range of potential health effects. Endocrine disrupting compounds (EDCs) can alter the endocrine system of animals and have been linked to a number of adverse effects in both humans and wildlife. The Detroit River receives a considerable loading of urban and agricultural runoff, as well as sewage treatment plant (STP) discharges at the head of the river. The river is the source of drinking water for approximately 4.5 million residents of the greater Detroit metropolitan area and Windsor, Ontario, Canada. Windsor's main intake for its drinking water treatment plant (WTP) is downstream from Little River Sewerage Treatment Plant (STP), City of Windsor. The contribution of PPCPs from STPs and other sources are of interest to Windsor and other surrounding communities. This paper describes the use of the SMS series of hydraulic models, especially RMA2 and RMA4, in the analysis of the fate and transport of the PPCPs from point of discharge to water treatment plant intake. Measured concentrations are used to validate the model. The present investigation refines the modeling strategies developed by both the U.S. Army Corps of Engineers and the U.S. Geological Survey for the Detroit River waterway, and employs these strategies for contaminants not previously investigated.
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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) | 0.000 | 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".