Pollution of Tanjero River by Some Heavy Metals Generated from Sewage Wastwater and Industrial Wastewater in Sulaimani District
Bibliographic record
Abstract
Tanjero river represents a permanent river located southwest of Sulaimani city about 7km. Qiliasan and Kani-Ban streams confluence to form Tanjero river near Kani-Goma village. Water samples were collected from fifteen sites along the Tanjero river during June 2007 up to January 2008 and analyzed for studying some physico-chemical properties and heavy metals contaminations. The total hardness values recorded in the studied sites were ranged ( 204.96 – 388.06 )mg/L.The values of (8-33.1) ºC, (1.08-496) NTU were recorded for temperature and turbidity respectively, while the values of (0.64 - 9.19) mg / L, (7.26-8.64) and (362 – 1715) µS.Cm-1 were recorded for dissolved oxygen (DO), pH and specific conductance. The values of Cobalt (Co), Chromium (Cr) ,Iron (Fe), Manganese (Mn) and Nickel (Ni), concentration were ranged between, (1.80 to 2.39), (0.2 to 3.31) , (2.13 to 2.55), (0.08 to 3.29) ,and (0.51 to 1.72) mg/L respectively . The result indicates significant differences (P≥ 0.05) for the sampling events with LSD (Least Significant Differences) value of 0.01 for Co Fe, and Ni, while 0.03 and, 0.06 for Cr and Mn respectively. The Copper(Cu) concentration in all studied water samples was within the acceptable levels which ranged (0.11 to 0.51) mg/L . Tanjero river and tributaries were polluted with heavy metals (Fe, Mn, Ni, and Cr) resulted from the impact of sewage wastewater according to water quality standard EU, 2004; USEPA, 2005; Canada, 2005 and WHO, 2006 and should Construct a plant of treatment for treating sewage wastewater of Sulaimani city before direct discharge to the river and it is quite essential to treat the ground water of the studied area before using .
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".