Quantifying the removal of polybrominated diphenyl ethers (PBDEs) in physical, chemical, and biological sludge treatment systems
Bibliographic record
Abstract
Polybrominated diphenyl ethers (PBDE) are priority contaminants historically used as flame retardants. PBDEs are known to occur in wastewater biosolids posing potential concerns with the beneficial land application of the biosolids. This study evaluated the removal of 21 congeners in nine full-scale sludge treatment systems including pelletization (P), alkaline stabilization (AS), and aerobic (AE) and anaerobic (AN) digestion. It is the first study to conduct a mass balance analysis of a broad spectrum of PBDEs during physical, chemical, and biological sludge treatment. The PBDE congener pattern in raw sludge and biosolids samples was consistent with commercial formulations. The fully brominated congener BDE-209 dominated biosolids from all sites with an average concentration of 620 ng/g dry weight (dw), followed by BDE-99 (173 ng/g dw) and BDE-47 (162 ng/g dw). Mass balance analysis on the P and AS processes showed no change in PBDE mass flows with treatment. However, aerobic and anaerobic digestion processes reported significant levels of removal and formation of individual congeners, though the results were not consistent between facilities. One aerobic digestion process (AE2) reported an overall average removal of 48%, whereas the other (AE1) reported very high levels of accumulation of tri- and tetraBDE congeners. Similarly, there were significant variations in PBDE behavior across the five anaerobic digestion plants studied. The plant with the longest solids retention time (SRT) (AN1) reported a moderate removal (50%) of overall PBDE loading and lower congeners, whereas other plants (AN2-AN5) showed significant low (-19%) to high (-166%) levels of formation of lower congeners. The results suggest that reduced SRTs result in formation of lower congeners while extended SRTs can lead to moderate removal of some PBDEs. Conventional sludge treatment result in low to moderate PBDE removal and advanced thermal conversion technologies may be needed to improve the contaminant removal during sludge treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".