Influence of stormwater management ponds on chloride transport to urban headwater streams
Bibliographic record
Abstract
Sodium chloride (NaCl) is the most common de-icing agent used on roads and parking lots in North America. During the winter and spring, chloride (Cl − ) is readily transported from paved surfaces to stormwater management facilities in a matter of hours to days. According to earlier studies, densimetric stratification in end-of-pipe stormwater management facilities such as wet stormwater management ponds (SWMPs) can result in latencies in Cl − transport to receiving waters. As a result, wet SWMPs may generate Cl − pulses in streams that exceed thresholds of acute toxicity to aquatic biota. This study identified the prevalence of this phenomenon at five headwater streams receiving discharge from wet SWMPs within the Greater Toronto Area over two years. All receiving streams in this study experienced exceedances of the chronic CWQG for Cl − downstream of the SWMP outlet, while only some experienced exceedances of the acute CWQG for Cl − . For most of the salting season, SWMP contributions exacerbate downstream Cl − concentrations, and occasionally are the primary driver of exceedances. Bottom-draw SWMPs were found to accumulate Cl − and flush rapidly following a rain or melt event. Top-draw SWMPs accumulated Cl − throughout the salting season and released diluted concentrations of Cl − near the end of the season. Streams with large upstream catchments diluted SWMP contributions and ameliorated downstream Cl − concentrations.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".