Seasonal Changes in Physicochemical, Chemical and Bacteriological Parameters of Gomti River in Bangladesh
Bibliographic record
Abstract
BACKGROUND AND AIM: This study was undertaken to investigate the current pollution status of the Gomti river in Bangladesh by collecting water samples from twenty sites along the 120 km stretch of the Gomti river in the rainy season (June 2019) and dry season (January 2020). METHODS: The collected samples were examined for their physicochemical parameters (pH, electrical conductivity (EC), total dissolved solids (TDS), total organic carbon (TOC), and turbidity), chemical parameters (the concentrations of six heavy metals, namely chromium (Cr), copper (Cu), iron (Fe), nickel (Ni), lead (Pb), and zinc (Zn)), and bacteriological parameters (aerobic heterotrophic bacteria and total coliforms) in order to assess the suitability of the river water for various purposes. RESULTS: The heavy metal concentrations of the Gomti river were compared with that of other national and international rivers and it was apparent that Fe, Ni, and Zn may potentially pose adverse effects on the aquatic ecosystems of the Gomti river. A significant (p<0.05) positive correlation was found between Cu and Zn indicating that water pollution by these two metals may have originated from common anthropogenic sources. The present study revealed for the first time that the river Gomti was considerably polluted with bacterial populations. The presence of Shigella spp., Salmonella spp., and Escherichia coli in the bacterial isolates is certainly a major water quality concern. Aerobic heterotrophic bacteria and total coliform counts were found to be 0.45×10² to 1.84×10⁴ CFU/mL and 0.05×10² to 7.32×10³ CFU/mL, respectively, which were above the permissible limits of WHO and are deemed unfit for drinking and domestic purposes, and for fish culture. CONCLUSIONS: From this study, the priority pollutants of concern in the Gomti river water are Fe, Ni, Zn, aerobic heterotrophic bacteria, and total coliforms. KEYWORDS: Water pollution, Heavy metals, Total coliform, Gomti river
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 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".