Physicochemical and Microbiological Evaluation of Reverse Osmosis Drinking Water Quality in Babylon Province, Iraq
Bibliographic record
Abstract
The physical, chemical and microbiological quality of drinking water produced from 25 reverse osmosis (RO) plants in five districts of Babylon Province, Iraq was assessed by applying the Canadian Water Quality Index (WQI). Systematic sampling of water for water quality assessment was undertaken from October 2024 to February 2025. Results showed that pH was between 6.1 to 7.8. Conductivity difference was noted to be large, between 10 and 360 μS/cm, whereas TDS exhibited between 6.14 and 225 mg/L, indicating the outstanding salt rejection in range of from ~90–99.5%. Total hardness showed a significant decrease (10-270 mg/L) with calcium hardness and magnesium hardness decreasing from 1 to 28 mg/L, and 1.458 to 62.694 mg/L, respectively; the concentrations of ions significantly decreased: chloride (11.85-49.98 mg/L), nitrate (0-0.024 mg/), sulfate (0.698-15.938 mg/). Counts of the total bacteria and coliforms were ranging from 177-301CFU/mL and 0-27CFU/100mL respectively in the sites based on microbial test. Based on WQI evaluation, 64% (n=16) of the samples were ranked to be excellent quality(0-25), 24%(n=6) good quality (26-50) and 12% (n=3) was poor quality(51-75). This integrated approach of the great extent study clearly verifies that RO technology has an outstanding performance to remove physicochemical contaminants, while presenting ongoing mastering difficulties such as microbiological safety and aluminum contamination to require more specific applicable guidelines in monitoring actions and regular maintenance works for their optimal operations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".