Environmental Assessment of Tannery Wastes from Chittagong, Bangladesh
Bibliographic record
Abstract
The present paper deals with the study of different physico-chemical parameters as well as metal concentration in the effluents discharged by a leather processing industry, Madina Tannery, Chittagong, Bangladesh.Industrial effluents were collected from every section of the leather-processing unit (viz., preliminary soaking,soaking, dehairing, re-liming, bating, pickling, chrome tanning, neutralization, colouring and fat liquoring). The pH value and concentrations (mg.l-1) of TDS, TSS, Cl-, BOD, COD and Cr were found in the range of 3.4-12.8, 570- 85,340- 68,2384,-69,23-125, 1148-8875, 2068-16,231 and 26-6853 respectively. Levels (mg.l-1) of BOD, COD,Chloride (Cl-), Electric Conductivity (EC), Total Alkalinity (TA), Total Dissolved Solid (TDS) and Total Suspended Solid (TSS) were found in the range of 4768-5798, 6636-7859, 1978-2215, 2900-5600, 745-1358, 7068-9068 and 1003-2307 respectively. Metal concentrations (mg.l-1) of Cr, Mn, Fe and Cd were found in the range of 69,74,0.07,0.09, 2.5412,2.8796 and 0.0257,0.0325 respectively. The study reveals that tannery effluents play a key rolein environmental contamination.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".