The quality of water and sediments of street runoff in Amman, Jordan
Bibliographic record
Abstract
Abstract Metallic content (Cr, Fe, Mn, Cu, Ni, Pb and Cd) of street sediments and street runoff in addition to major inorganic constituents (Ca, Mg, Na, K, HCO3, Cl, NO3 and SO4) of street runoff were determined under semi‐arid conditions. Two sites in the vicinity of Amman during the pluvial year 1998–1999 were chosen for this investigation. A higher quantity of ionic contents was found at site 2 in comparison to site 1 except for iron, which was significantly higher at site 1. This finding was attributed to higher anthropogenic activity and lower rainfall at site 2, which indicates better water quality of street runoff from residential sites than the city centre. The average concentrations of Pb, Cu and Cd in Amman street runoff compared with the highest levels recorded at humid sites of the world as a result the prevailing semi‐arid conditions in the areas investigated. The highest concentrations of all constituents were detected during the first month of sampling, which might be the result of low rainfall, and a long dry period of atmospheric deposition preceding rainfall events. However, high levels of both lead and copper were recorded (below that of iron) which might be attributed to traffic pollution. In contrast, a significant variation between the average concentrations for Cu, Ni and Cr was found in sediments from the two sites. Moreover, a significant difference was detected only for Cu and Mn at each site overtime. The overall pattern of the results suggests that all heavy metal concentrations for street runoff showed a significant variation over time at site 1 whereas only a significant variation was found for Ni at site 2, which can be explained as the result of higher rainfall at site 1 than at site 2. Copyright © 2001 John Wiley & Sons, Ltd.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".