Micropollutant transformation and toxicity: Electrochemical ozonation versus biological metabolism
Bibliographic record
Abstract
Environmental water sources are constantly polluted by anthropogenic compounds, not always minimized by conventional water treatment methods to remove these compounds at the micro- and nano-range. The absolute concentrations of a suite of seven representative environmental micropollutants were compared pre- and post-treatment with both ozone and microbial biofilms, in terms of removal efficiencies and toxicity assays. Both synthetic micropollutant mixes and environmental water samples were evaluated. The study started with two representative micropollutants (carbamazepine, CBZ, and sulfamethoxazole, SMX), and broadened into a suite of pollutants, evaluating whole-sample eco-toxicological footprints. An ozone concentration of 4.24 ± 0.27 mg/L in tap water, resulted in an 87.9% and 96.5% removal of CBZ and SMX, respectively, within 1 min. Despite almost immediate removal of parent micropollutants by oxidation, endocrine disruption potential (anti-estrogenicity) of CBZ and SMX required up to 240 min of ozone treatment to show no assay effect. A broader suite of micropollutants in more complex environmental matrices showed scavenging of ozone (2.95 ± 0.17–0.25 ± 0.03 mg/L) and varying micropollutant recalcitrance to oxidation. Lower matrix pollution led to lower reduction in eco-toxicity. Microbial degradation of CBZ and SMX (56% and 70% versus 19% and 79%, respectively, in duplicate biofilms) by nutrient-limited biofilms showed less removal than ozonation, with marked variation due to the stochastic nature of biofilm sloughing. Microbial degradation of CBZ and SMX resulted in an increase of >90% in both estrogenicity and Aliivibrio inhibition. The results obtained from this study address a gap in understanding the removal efficiency of micropollutants, where the removal process often receives more attention than the comparative reduction of toxicological effects. This shift from a controlled laboratory environment to real-world scenarios also provided comparative insights into the removal of micropollutants and the eco-toxicity of the transformation by-products of each process.
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 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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".