From shower to table: fate of organic micropollutants in hydroponic systems for greywater treatment and lettuce cultivation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT This study evaluated the dual functionality of hydroponic systems to grow edible crops while treating greywater (GW) containing 20 organic micropollutants (OMPs). Various conditions with differing nutrient contents were tested: raw GW, GW with struvite, and GW with commercial nutrient solution. System performance was assessed with plant growth and standard parameters and OMP removal. After 4-week exposure, all conditions produced healthy-looking plants, proving GW as a viable hydroponic growth medium. However, only the condition with commercial solution yielded plants comparable to the biotic control, indicating the necessity of nutrient supplementation. Effluent from conditions with well-developed plants met the requirements of the European water reuse legislation (EU 2020/741) for scenarios B–D (food crops not in direct contact with the reclaimed water and industrial crops), and had the highest OMP removal, showcasing the effectiveness of the system for OMP treatment. Estimated calculations of OMP detected in leaves (10/20 OMP detected, predominantly positive and small) resulted in calculated potential human health risks through lettuce intake for two compounds: atenolol and epoxycarbamazepine. These findings support a continued evaluation of the behavior of other OMPs and their transformation products in water–plant systems, and their consideration in legislation on water reuse and food safety.
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.
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 it