Survey of 218 organic contaminants in groundwater derived from the world's largest untreated wastewater irrigation system: Mezquital Valley, Mexico
Bibliographic record
Abstract
The Mezquital Valley system is the world's oldest and largest example with regard to use of untreated wastewater for agricultural irrigation. Because of the artificial high recharge associated with the Mezquital Valley aquifers, groundwater is extracted for human consumption, and there are plans to use this groundwater as a water resource for Mexico City. Thus, this study analyzed 218 organic micro-contaminants in wastewater, springs, and groundwater from Mezquital Valley. Five volatile organic compounds (VOCs) and nine semi-volatile organic compounds (SVOCs) were detected in the wastewater used for irrigation. Only two SVOCs [bis-2-(ethylhexyl) phthalate and dibutyl phthalate] were detected in all the wastewater canals and groundwater sources, whereas no VOCs were detected in groundwater and springs. Of the 118 pharmaceutically active compounds (PhACs) and 7 reproductive hormones measured, 65 PhACs and 3 hormones were detected in the wastewater. Of these, metformin, caffeine, and acetaminophen account for almost sixty percent of the total PhACs in wastewater. Nevertheless, 23 PhACs were detected in groundwater sources, where the majority of these compounds have low detection frequencies. The PhACs sulfamethoxazole, N,N-diethyl-meta-toluamide, carbamazepine, and benzoylecgonine (primary cocaine metabolite) were frequently detected in groundwater, suggesting that although the soils act as a filter adsorbing and degrading the majority of the organic pollutant content in wastewater, these PhACs still reach the aquifer. Therefore, the presence of these PhACs, together with the high levels of the endocrine disruptor bis-2-(ethylhexyl) phthalate, indicate that water sources derived from the recharge of the studied aquifers may pose a risk to consumer health.
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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) | 0.006 | 0.001 |
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; both teacher heads agree on what is shown here.
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".