A Source Pollution Control Measure Based on Spatial-Temporal Distribution Characteristic of the Runoff Pollutants at Urban Pavement Sites
Bibliographic record
Abstract
The concentrations of pollutants in urban pavement runoff are normally higher than those in other urban surface runoff, which causes serious problems in protecting the environment of receiving water and soils. The purpose of this study was to propose a source pollution control measure based on the spatial-temporal distribution characteristics of the runoff pollutants at urban pavement sites. Therefore, samples from pavement runoff were collected and tested for analyzing the spatial-temporal distribution characteristics. Then, infiltration tests were conducted on selected purification materials to evaluate their purification ability to the simulated pavement runoff. Results indicated that heavy metals Zn and Pb were at high concentrations near the intersection, the reason being the frequent braking of vehicles at this site. The level of suspended solids was far higher than the limitation in the standard near the site where massive human activities occurred. Besides, the cumulative amounts of all kinds of pollutants tended to be stable with the extension of rainfall duration. The logarithmic function was found to fit the experimental data well. Finally, the pavement runoff was categorized into different situations. The combinations of purification materials were recommended and integrated into a source control measure for the treatments of different pollution situations, which made the most use of each purification material and ensured the high elimination efficiency of different pollutants.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| 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 | 0.000 |
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".