Fate Mechanisms and Removal of Tetrabromobisphenol-A (2,2â,6,6â-Tetrabromo-4,4â-isopropylidenediphenol) in the Activated Sludge Process
Bibliographic record
Abstract
A novel method for determination of tetrabromobisphenol-A (TBBPA), was developed using gas chromatography-negative ion chemical ionization-mass spectrom- etry (GC-NCI-MS). Samples of municipal wastewater treatment plant (WWTP) influent were analyzed for TBBPA. Levels ranged from 1 to 41 ng/L, with an average of 20 ± 14 ng/L. Matrix effects were shown to be 30 ± 17 % in the influent and -30 ± 11 % in membrane permeate. The method limit of quantitation was 0.1 ng/L TBBPA.\nSorption of TBBPA to fresh mixed-liquor suspended solids (MLSS) from a membrane bioreactor (MBR) were studied. In a kinetic study, sorption was found to be essentially complete after 12 hours of exposure to MLSS. Log Koc and log Kd were measured at 4.7 ± 0.8 and 1.9 ± 0.8 respectively (n = 22). These values were much higher than modelled estimates based on Kow (p ≥ 0.05), and higher\nthan modelled estimates based on Kow and pKa (p ≥ 0.05). Data was successfully modelled using the Freundlich isotherm, having a Kf value of 8.5 and an n value of 1.7. TBBPA adsorbed to borosilicate glassware, with a wall-loss coefficient (Kw) of 0.15 ± 0.1 (n ≥ 3).\nTBBPA levels in WWTP influent varied from 13 to 29 ng/L while effluent concentrations varied from 0 to 2.2 ng/L over the same period. Three pilot-scale membrane bioreactors (MBRs) removed less TBBPA during the same time period, though MBR removal was also significant (p ≥ 0.05). Increasing MBR sludge residence time (SRT) increased removal at the 86 % confidence interval (p = 0.14). A nitrifying MABR was shown to remove TBBPA significantly when spiked with ammonia and TBBPA (p ≥ 0.05), showing that nitrifying bacteria can degrade TBBPA. An MABR hollow fibre was found to adsorb TBBPA.\nVarious soluble microbial products (SMP) were studied from MBRs fed munici- pal influent. Using current measurement practices, SMP were shown to be sensitive to matrix effects. Use of the standard addition technique (SA) can compensate for this. Measurements using SA showed SMP degrades rapidly during storage in the fridge and due to freezing. SA was also used to compare commonly used SMP extraction techniques, and showed that extraction method influences recovery.
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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 | 0.001 | 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 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".