Investigating the quantitative and qualitative status of effluent in the wastewater treatment plant in Iran Central Iron Ore
Bibliographic record
Abstract
Abstract The aim of present study was to investigate the quality of the produced effluent from different units of the Iran Central Iron Ore in Bafq city and comparison of effluent with the standards. This study presents the physicochemical and biological parameters data of effluent of three Sequencing batch reactors (SBR) with a capacity of 160 m3∙d−1. Most common parameters include pH, total suspended solids (TSS), total nitrogen (TN), total phosphorus (TP), biochemical oxygen demand (BOD5), chemical oxygen demand (COD), heavy metals, and total coliforms and fecal coliforms as biological indicators. Then, for each SBR system, the average of each parameter was determined, and results were compared with the standard recommended by the Iranian Environmental Protection Agency. Based on the results, some of the parameters, including BOD5, COD, and TSS in the wastewater treatment plant (WWTP) effluent, are higher than the permitted amount for discharge to the surface water. Considering the BOD5, COD, and TSS concentration in WWTPs, the treated wastewater is only suitable for agricultural and irrigation use. Therefore, wastewater produced by Iran Central Iron Ore Co. will need additional treatment to achieve standard quality of water before discharge in surface water and adsorbent well.
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 | 0.000 | 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) | 0.000 | 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 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".