Degradation of progestagens by oxidation with potassium permanganate in wastewater effluents
Bibliographic record
Abstract
BACKGROUND: This study investigated the oxidation of selected progestagenic steroid hormones by potassium permanganate at pH 6.0 and 8.0 in ultrapure water and wastewater effluents, using bench-scale assays. Second order rate constants for the reaction of potassium permanganate with progestagens (levonorgestrel, medroxyprogesterone, norethindrone and progesterone) was determined as a function of pH, presence of natural organic matter and temperature. This work also illustrates the advantages of using a novel analytical method, the laser diode thermal desorption (LDTD-APCI) interface coupled to tandem mass spectrometry apparatus, allowing for the quick determination of oxidation rate constants and increasing sample throughput. RESULTS: The second-order rate constants for progestagens with permanganate determined in bench-scale experiments ranged from 23 to 368 M(-1) sec(-1) in both wastewater and ultrapure waters with pH values of 6.0 and 8.0. Two pairs of progestagens exhibited similar reaction rate constants, i.e. progesterone and medroxyprogesterone (23 to 80 M(-1) sec(-1) in ultrapure water and 26 to 149 M(-1) sec(-1) in wastewaters, at pH 6.0 and 8.0) and levonorgestrel and norethindrone (179 to 224 M(-1) sec(-1) in ultrapure water and 180 to 368 M(-1) sec(-1) in wastewaters, at pH 6.0 and 8.0). The presence of dissolved natural organic matter and the pH conditions improved the oxidation rate constants for progestagens with potassium permanganate only at alkaline pH. Reaction rates measured in Milli-Q water could therefore be used to provide conservative estimates for the oxidation rates of the four selected progestagens in wastewaters when exposed to potassium permanganate. The progestagen removal efficiencies was lower for progesterone and medroxyprogesterone (48 to 87 %) than for levonorgestrel and norethindrone (78 to 97%) in Milli-Q and wastewaters at pH 6.0-8.2 using potassium permanganate dosages of 1 to 5 mg L(-1) after contact times of 10 to 60 min. CONCLUSION: This work presents the first results on the permanganate-promoted oxidation of progestagens, as a function of pH, temperature as well as NOM. Progestagen concentrations used to determine rate constants were analyzed using an ultrafast laser diode thermal desorption interface coupled to tandem mass spectrometry for the analysis of water sample for progestagens.
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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 | 0.000 | 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 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".