Seasonal evaluation of the effluent quality of the Rosarito, Mexico wastewater treatment plant and identification of alternatives for its indirect reuse
Bibliographic record
Abstract
This project addressed the problem of reusing treated wastewater, which is a common practice in the European Union, the United States, Canada, and some parts of Africa.The reuse of treated wastewater is not common in Mexico, and the majority of such water is discharged into the ocean and, to a lesser extent, on land.Because the reuse of this resource depends to a large extent on the quality of the treatment plant discharge, in this study we attempted to evaluate seasonal fluctuations in the quality of the Rosarito Norte treatment facility effluent over the course of one year.The majority of the total dissolved solids were found to consist of chlorides and sulfates such as sodium salts.Also reflected in the overall level of water hardness were salts derived from calcium and magnesium, as well as the carbonates and bicarbonates.These salts were not evaluated in this part of the project, but deserve consideration.The quantity of organic material was minimal with respect to BOD 5 (not up to 270 mg/L) , and did not present a problem for the reuse of treated wastewater.The majority of the nitrogen present (TKN: 1.9-86.3mg/L) was found to consist of proteins that remained as a result of the short curing time, as well as the poor oxygenation during the treatment process.Also present were high levels of total phosphorus and sulfates, between 15.5-38.2mg/L and 197-1200 mg/L, respectively.The microbiological and parasitic analyses yielded excellent results, testing positive in only 33% and 0% of the trials, respectively.These results were compared with data reported for the aquifer into which the water will be infiltrated, and will be shared with the Tijuana office of the State Commission of Services for use as a basis for making decisions regarding the reuse of treated potable water.
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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 | 0.000 | 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 | 0.001 | 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".