Bioretention: assessing effects of winter salt and aggregate application on plant health, media clogging and effluent quality
Bibliographic record
Abstract
Bioretention offers the potential to better match pre-development water balances while improving stormwater quality. The now extensive body of research shows bioretention to be a viable and effective option in the management of stormwater, however there continues to be a demand for information related to cold climate design and performance. To study the impact of winter road salting on bioretention functions, a salt and aggregate mixture was applied to outdoor, bioretention mesocosms with soil, mulch and vegetation layers. Freezing of the media within mesocosms was found to increase the infiltration rates. Smaller increases in infiltration rates occurred for mesocosms exposed to the salt and aggregate mixture, suggesting that media clogging due to high suspended solids loading may be counteracting the effects of expansion due to freezing. Sodium and chloride were temporarily retained in the bioretention media, but were subsequently flushed by infiltrating water. Plant species, Aster nova angliae ‘Red Shades’ and Panicum virgatum were shown to be capable of withstanding high salt exposure. The exposure of the bioretention soils to de-icing materials did not alter the media's ability of the media to remove contaminants. No evidence of increased heavy metal mobility during this study was observed. Overall, results support the potential for application of bioretention facilities in cold climate regions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".