Environmental Factors Affecting Methoprene Concentrations for West Nile Virus Control in a Storm Sewer System
Bibliographic record
Abstract
Abstract To address vector-borne West Nile virus in Canada, chemical larvicides (methoprene) are applied to storm sewer system catch basins (CBs) to control mosquitoes. This study assessed the fate and transport of methoprene in such systems over time relative to precipitation. Rainfall and methoprene concentration patterns revealed the effect of dilution, dissolution, and flushing of the larvicide. In the summer and fall of 2003 to 2005, field monitoring studies were conducted in Toronto, Ontario on two CBs, each treated with a control dose of methoprene, supplied in pellet or ingot formulation. Furthermore, in 2005, concentrations at the storm sewer outfall were measured during nine rainfall events. Based on daily monitoring, findings indicate that (1) the methoprene concentration at the CBs fell below the minimum lethal concentration or LC50 one or two weeks after treatment, and remained below LC50 concentrations over 70% of the time; (2) rainfall flushed methoprene from the CBs to the storm sewer outfall at concentrations higher than the levels specified by Ministry of Environment, which may cause ecosystem damage; (3) based on the number of cycles per diem within each CB in each study period, there was no conclusive pattern in the flushing susceptibility of pellets versus ingots; (4) the mean concentration of methoprene increased with reduced CB sump volume; (5) less total precipitation resulted in higher average methoprene concentrations and a higher number of days above the LC50 based on ingot-dosed CBs; (6) counter-intuitive to (4) and (5), larger sump water volumes and greater rainfall resulted in lower mean concentrations and fewer days above the LC50; and (7) a single ingot dosage was comparable in performance to a three pellet dosage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 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 | 0.001 |
| 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".