Effective treatment of high phosphorus pharmaceutical wastewater by chemical precipitation
Bibliographic record
Abstract
Abstract The conditions for the treatment of high phosphorus pharmaceutical wastewater using chemical precipitation were determined to achieve high efficiency on the removal of total phosphorus (TP). The key factors affecting the TP removal efficiencies of four metal salts (FeCl 3 , AlCl 3 , MgCl 2 , and CaCl 2 ), such as molar ratio, initial wastewater pH, and reaction time, were investigated. The optimal metal mole ratios of FeCl 3 , AlCl 3P , MgCl 2 , and CaCl 2 for the TP removal were 1.8:1, 1.8:1, 1.6:1, and 1.6:1 in the initial pH range, respectively. The TP removal efficiencies obtained by FeCl 3 , AlCl 3 , MgCl 2 , and CaCl 2 were 99.8 %, 98.3 %, 96.9 %, and 99.2 % at the optimal mole ratio and pH conditions with 30 min reaction time, respectively. FeCl 3 and AlCl 3 had better removal performance on COD, wherein the removal rates of COD by FeCl 3 and AlCl 3 were 38.6 % and 27.6 %, respectively. FeCl 3 and CaCl 2 were selected for the combined process of removing TP and overcoming the aforementioned problem. The final effluent quality was better than the one only used on one of the four metal salts, in which the removal rates of TP and COD were as high as 99.8 % and 46.9 %, respectively. The combined process with FeCl 3 and CaCl 2 was an effective method for the pretreatment of high phosphorus pharmaceutical wastewater to reduce the processing cost and to decrease the chemical oxygen demand (COD) and TP.
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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) | 0.000 | 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".