Temperature-Phased Biological Hydrolysis and Thermal Hydrolysis Pretreatment for Anaerobic Digestion Performance Enhancement
Bibliographic record
Abstract
Thermal hydrolysis (TH) and biological hydrolysis (BH) are two main and growing anaerobic digestion pretreatment technologies. In this study, municipal wastewater sludge samples were collected from the Guelph Wastewater Treatment Plant (WWTP) in Ontario, Canada. The effects of temperature on BH treatment, including BH at 42 °C (BH42), 42 °C followed by 55 °C (BH42+55), 55 °C followed by 42 °C (BH55+42), and 55 °C (BH55) were evaluated for anaerobic digestion performance enhancement and compared with TH treatment at 165 °C. The TH, BH42, BH42+55, BH55+42, and BH55 treatments caused the reduction of volatile suspended solids (VSS) by 22.6%, 17.5%, 24.6%, 23.1%, and 25.9%, respectively. The soluble chemical oxygen demand (sCOD) content of the sludge increased by 377.5%, 323.8%, 301.3%, 286.9%, and 221.7% by the TH, BH55, BH42+55, BH55+42, and BH42 treatments, respectively. Volatile fatty acids (VFA) constituted around 40% of the sCOD in the BH-treated sludge and 6% in the TH-treated sludge. The cumulative methane yields (NmLCH4/g COD fed) of sludge treated by BH55+42 and TH were respectively 23% and 20% higher than that of the untreated sludge. For BH pretreatment, sludge treated by BH55+42 produced more methane than those treated by BH42+55, BH55, and BH42. The methane yields of the combined sludge treated by the TH and BH55+42 treatments were in the ranges of 248.9 NmLCH4/g COD to 266.1 NmLCH4/g COD fed, and 255.3 NmLCH4/g COD to 282.2 NmLCH4/g COD fed, respectively.
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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".