Adsorption enhanced biological treatment of hydrothermal liquefaction aqueous phase derived from municipal sludge
Bibliographic record
Abstract
Hydrothermal liquefaction (HTL) is a promising method for municipal sludge valorization through waste minimization and biofuel production. The process wastewater, HTL aqueous, presents a significant challenge for scale-up due to recalcitrant compounds. In this study, granular activated carbon (GAC) was used to remove potential inhibitors from HTL aqueous through adsorption to enhance aerobic and anaerobic biological treatment. GAC removed up to 61 % chemical oxygen demand (COD), 50 % biochemical oxygen demand (BOD) and potential inhibitors, such as total phenolic compounds (87 %) and N-heterocycles (90 % of pyridines) at 100 g/L. Conversely, most volatile fatty acids remained in HTL aqueous. Subsequently, mesophilic and thermophilic specific methane potential increased by up to 97 % and 83 %, respectively. BOD increased by up to 50 %, which enhanced BOD/COD ratio from 81 % to 93 % before and after adsorption. This study established the groundwork for HTL aqueous adsorption, described mechanism for pollutant removal, and provided insights for biological 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 | 0.000 |
| 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 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".